From f09bcfd7b02d587d3da2027f3beb94f9257ab480 Mon Sep 17 00:00:00 2001
From: Joseph Murtagh <jmurtagh05@qub.ac.uk>
Date: Mon, 26 Jan 2026 16:05:39 +0000
Subject: [PATCH 1/5] created better visualisation function

---
 docs/notebooks/images/conicsections.png    |  Bin 0 -> 125714 bytes
 docs/notebooks/images/orbitellipse.png     |  Bin 0 -> 69021 bytes
 docs/notebooks/orbit_visualizer_demo.ipynb | 8545 ++++++++++++++++++++
 src/layup/dash_ui.py                       | 1833 +++++
 src/layup/data/app.css                     |  124 +
 src/layup/orbit_maths.py                   |  631 ++
 src/layup/visualize.py                     |  402 +
 src/layup_cmdline/visualize.py             |  145 +-
 8 files changed, 11614 insertions(+), 66 deletions(-)
 create mode 100644 docs/notebooks/images/conicsections.png
 create mode 100644 docs/notebooks/images/orbitellipse.png
 create mode 100644 docs/notebooks/orbit_visualizer_demo.ipynb
 create mode 100644 src/layup/dash_ui.py
 create mode 100644 src/layup/data/app.css
 create mode 100644 src/layup/orbit_maths.py
 create mode 100644 src/layup/visualize.py

diff --git a/docs/notebooks/images/conicsections.png b/docs/notebooks/images/conicsections.png
new file mode 100644
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diff --git a/docs/notebooks/orbit_visualizer_demo.ipynb b/docs/notebooks/orbit_visualizer_demo.ipynb
new file mode 100644
index 00000000..a0922de5
--- /dev/null
+++ b/docs/notebooks/orbit_visualizer_demo.ipynb
@@ -0,0 +1,8545 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d89fec02",
+   "metadata": {},
+   "source": [
+    "# Layup Visualize Demo Notebook\n",
+    "Once you have your lovely set of input orbits, why not take a moment to appreciate how they look in space? The pupose of this notebook is to demonstrate a simple way to display the Layup Visualize orbital drawing function (as an ellipse/cone) within Jupyter, without needing to run the full Dash app. The basic driver behind all of this is that we convert any orbit format into a set of classical conic section elements, namely:\n",
+    "\n",
+    "- L (Semilatus rectum, in au)\n",
+    "- e (Eccentricity)\n",
+    "- i (Inclination, in degrees)\n",
+    "- $\\omega$ (Argument of perihelion, in degrees)\n",
+    "- $\\Omega$ (Longitude of ascending node, in degrees) \n",
+    "\n",
+    "From these we can calculate a true anomaly $\\nu$ and describe any conic section, from circular to elliptical to parabolic to hyperbolic orbits.\n",
+    "\n",
+    "<p align=\"center\">\n",
+    "    <img src=\"./images/conicsections.png\" alt=\"conic sections\" width=\"500\"/>\n",
+    "    <img src=\"./images/orbitellipse.png\" alt=\"orbit ellipse\" width=\"800\"/>\n",
+    "</p>"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "a0d60be7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "\n",
+    "from layup.orbit_maths import conic_lines_from_classical_conic, build_ephem_and_mus, build_planet_lines_cache, prepopulate_orbit_variants\n",
+    "from layup.dash_ui import plotly_2D, plotly_3D"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c4fffabc",
+   "metadata": {},
+   "source": [
+    "## 1) Create (or load) some orbits\n",
+    "Below we build a few toy orbits directly with our classical conic elements. In your real workflow, you’d typically get a `ClassicalConic` object via our existing converters in `orbit_maths.py`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "01a2a186",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[('Obj-00', 61000.,  9.62653851, 0.01      , 22.24788145,  81.80593984, 272.91158643,  70.06993483)\n",
+      " ('Obj-01', 61000.,  6.10822362, 0.21917606, 55.60589933, 199.65052333, 127.62934853, 168.01956134)\n",
+      " ('Obj-02', 61000., 10.51527816, 0.15256361, 38.6319072 ,  22.9742122 , 349.45128878,  15.76935568)\n",
+      " ('Obj-03', 61000.,  8.82236431, 0.19747983, 49.3656968 , 297.94722192, 321.52360368,  55.54421714)\n",
+      " ('Obj-04', 61000.,  2.48886215, 0.07204341, 26.60485193, 227.39918368, 280.21805895, 245.89762317)]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# --- toy dataset: 5 example orbits ---\n",
+    "rng = np.random.default_rng(42)\n",
+    "N = 5\n",
+    "dtype = [\n",
+    "    (\"ObjID\", \"U32\"),\n",
+    "    (\"epochMJD_TDB\", \"f8\"),\n",
+    "    (\"a\", \"f8\"),\n",
+    "    (\"e\", \"f8\"),\n",
+    "    (\"inc\", \"f8\"),\n",
+    "    (\"argPeri\", \"f8\"),\n",
+    "    (\"node\", \"f8\"),\n",
+    "    (\"ma\", \"f8\")\n",
+    "]\n",
+    "\n",
+    "orbits = np.zeros(N, dtype=dtype)\n",
+    "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
+    "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
+    "orbits[\"a\"] = rng.uniform(1.5, 12.0, size=N)\n",
+    "orbits[\"e\"] = np.clip(rng.normal(0.2, 0.15, size=N), 0.01, 0.85) # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
+    "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
+    "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"ma\"] = rng.uniform(0, 360, size=N)\n",
+    "\n",
+    "print(orbits)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8bf5a280",
+   "metadata": {},
+   "source": [
+    "## 2) Generate a cache of all ellipse/hyperbola lines\n",
+    "Under the hood, Layup Visualize will create a cache in all four combinations of barycentric+heliocentric && equatorial+ecliptic, regardless of your input specification via `prepopulate_orbit_variants` (we just use your input to tell us where to start for conversion). This allows us to easiy toggle between any combination you want"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "5b0bcdcd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "conic_cache, lines_cache, sunpos_cache, pos_cache = prepopulate_orbit_variants(\n",
+    "    orbits,\n",
+    "    orbit_format=\"KEP\",\n",
+    "    input_plane=\"ecliptic\",\n",
+    "    input_origin=\"heliocentric\",\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f5602f83",
+   "metadata": {},
+   "source": [
+    "## 3) Get the heliocentric ecliptic frame orbits\n",
+    "\n",
+    "By default in the Dash app we render our orbits, regardless of input, as heliocentric ecliptic framed. In the app you can toggle between heliocentric <-> barycentric origins and ecliptic <-> equatorial reference planes no matter what input you gave via the buttons. For now though, let's specify explicitly the output we want as `key`\n",
+    "\n",
+    "`conic_lines_from_classical_conic` then returns an array shaped `(N, n_points, 3)` with XYZ points in au for your N objects"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "628ece22",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(5, 400, 3)"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "key = (\"helio\", \"ecl\")\n",
+    "conic = conic_cache[key]\n",
+    "orbit_pos = pos_cache[key]\n",
+    "sun_xyz = sunpos_cache[key]\n",
+    "\n",
+    "lines = conic_lines_from_classical_conic(conic, n_points=400)\n",
+    "lines.shape"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f378c519",
+   "metadata": {},
+   "source": [
+    "## 4) Plot objects (2D and 3D)\n",
+    "\n",
+    "`plotly_2D` and `plotly_3D` can now produce some nice figures of our orbits. Here we'll first render all of our objects in our set in 2D. `plotly_2d` takes an argument `plots` (plural) which can be one of XY / XZ / YZ. This produces side by side of any of: a bird's eye (top-down, or XY plane) view, or a side (edge-on, or XZ / YZ plane) view of all our orbits, as well as the Sun. We note that XY is always returned with equal aspect ratios, as that is the reference plane, and we don't want to distort the orbit shapes. The scatter markers represent where each input object was at the reference epoch specified in the input file\n",
+    "\n",
+    "Try moving your mouse over each plot to play around with the interactive aspect! Hover over an orbit to get a tooltip containing some orbital elements of that object, pan and squash/stretch the axes by clicking and dragging your mouse along them, or zoom in and out of the figure. In the top right, you can reset the figure to its initial position, as well as save the figure as a .png if you like"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e3295200",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": "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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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+        },
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+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 0.2192<br>i: 55.61°<br>Ω: 127.63°<br>ω: 199.65°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "JFC"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
+         "type": "scatter",
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 0.2192<br>i: 55.61°<br>Ω: 127.63°<br>ω: 199.65°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "JFC"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
+         "type": "scatter",
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+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 0.1526<br>i: 38.63°<br>Ω: 349.45°<br>ω: 22.97°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
+         "type": "scatter",
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
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+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
+         "type": "scatter",
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+        },
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+         "hovertemplate": "Obj-03<br>e: 0.1975<br>i: 49.37°<br>Ω: 321.52°<br>ω: 297.95°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Other"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
+         "type": "scatter",
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+        },
+        {
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Other"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
+         "type": "scatter",
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 0.0720<br>i: 26.60°<br>Ω: 280.22°<br>ω: 227.40°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
+         "type": "scatter",
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+        {
+         "hovertemplate": "Obj-04<br>e: 0.0720<br>i: 26.60°<br>Ω: 280.22°<br>ω: 227.40°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
+         "type": "scatter",
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+             "fill": {
+              "color": "#EBF0F8"
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+             "line": {
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+            "header": {
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+             "line": {
+              "color": "white"
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+            "type": "table"
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+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
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+          "autotypenumbers": "strict",
+          "coloraxis": {
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+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          0.45
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "X [AU]"
+         }
+        },
+        "xaxis2": {
+         "anchor": "y2",
+         "domain": [
+          0.55,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "X [AU]"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "scaleanchor": "x",
+         "scaleratio": 1,
+         "showgrid": true,
+         "title": {
+          "text": "Y [AU]"
+         }
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "Z [AU]"
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6a9c4831",
+   "metadata": {},
+   "source": [
+    "2D plots can also be single panelled if the user prefers. `plotly_2d` takes an argument for `panel` (singular this time) that can be one of XY / XZ / YZ. All other parts of plotting stay the same!"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "1c8c9141",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
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+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 0.2192<br>i: 55.61°<br>Ω: 127.63°<br>ω: 199.65°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "JFC"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
+         "type": "scatter",
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 0.1526<br>i: 38.63°<br>Ω: 349.45°<br>ω: 22.97°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
+         "type": "scatter",
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
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+         },
+         "meta": {
+          "kind": "Other"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
+         "type": "scatter",
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 0.0720<br>i: 26.60°<br>Ω: 280.22°<br>ω: 227.40°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
+         "type": "scatter",
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+         },
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+            "header": {
+             "fill": {
+              "color": "#C8D4E3"
+             },
+             "line": {
+              "color": "white"
+             }
+            },
+            "type": "table"
+           }
+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
+          },
+          "autotypenumbers": "strict",
+          "coloraxis": {
+           "colorbar": {
+            "outlinewidth": 0,
+            "ticks": ""
+           }
+          },
+          "colorscale": {
+           "diverging": [
+            [
+             0,
+             "#8e0152"
+            ],
+            [
+             0.1,
+             "#c51b7d"
+            ],
+            [
+             0.2,
+             "#de77ae"
+            ],
+            [
+             0.3,
+             "#f1b6da"
+            ],
+            [
+             0.4,
+             "#fde0ef"
+            ],
+            [
+             0.5,
+             "#f7f7f7"
+            ],
+            [
+             0.6,
+             "#e6f5d0"
+            ],
+            [
+             0.7,
+             "#b8e186"
+            ],
+            [
+             0.8,
+             "#7fbc41"
+            ],
+            [
+             0.9,
+             "#4d9221"
+            ],
+            [
+             1,
+             "#276419"
+            ]
+           ],
+           "sequential": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ],
+           "sequentialminus": [
+            [
+             0,
+             "#0d0887"
+            ],
+            [
+             0.1111111111111111,
+             "#46039f"
+            ],
+            [
+             0.2222222222222222,
+             "#7201a8"
+            ],
+            [
+             0.3333333333333333,
+             "#9c179e"
+            ],
+            [
+             0.4444444444444444,
+             "#bd3786"
+            ],
+            [
+             0.5555555555555556,
+             "#d8576b"
+            ],
+            [
+             0.6666666666666666,
+             "#ed7953"
+            ],
+            [
+             0.7777777777777778,
+             "#fb9f3a"
+            ],
+            [
+             0.8888888888888888,
+             "#fdca26"
+            ],
+            [
+             1,
+             "#f0f921"
+            ]
+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "X [AU]"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "scaleanchor": "x",
+         "scaleratio": 1,
+         "showgrid": true,
+         "title": {
+          "text": "Y [AU]"
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, plot_sun=True, panel=\"XY\", return_fig=True)\n",
+    "fig2d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aaffcd3b",
+   "metadata": {},
+   "source": [
+    "We can also add some planets on top quite easily by just constructing them in a very similar way to our orbits. The only difference is we need to make use of Assist to get accurate Sun + Planet positions based on the users bootstrapped auxiliary files"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "f1e51608",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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D2T/W1UkYwRjZPx53Rk2jrdg/OJ0vXzRC2D8GZo23ddbXPzoYUr5oatc/BFmM2Q7+1j+nqhNtaZHWP/6yUtp5JNY/OGYKgEG31T9oVjK6wUnVP0WX8OH729Q/g66iTfFt1D/o+xlRo//TP5ZG4j0TkdM/5cGwY0Ii0z/ANesQMrPSP0OyRZPjQ9I/om1iOFjU0T/obYtOkWTRPwKbUiWQ9NA/b3owDlaE0D+cWg5d5BPQPxV6d9F4Rs8/zB9/Fr9kzj/uiEpEnoLNP11SNx0ZoMw/SwERazK9yz+YRg7/7NnKP4pjtLFL9sk/HMmNYlESyT9Zf/z3AC7IP5LV1l5dScc/KAcVimlkxj+IjnlyKH/FPxjlPxadmcQ/dDy5eMqzwz81qhqis83CP2YZJZ9b58E/DEjpgMUAwT/ABY1c9BnAP2rfM5bWZb4/6FB00lqXvD8keEmue8i6P3OPv3A/+bg/ouEzZ6wptz827P7kyFm1P0x+JUObibM/WGnZ3ym5sT/YEZw89tCvP72FWcwqL6w/lKNcRv6MqD+DK0WJfeqkP4zN8Hm1R6E/MpQ+BGZJmz8c/m8fBgOUPx+FL03KeIk/DH4N93PWdT9KQHBphxNdvz5BzakCMIK/hrd8wKNekL/ShwHlBaWXv+YzRvkN656/lqYkIVEYo7/VDROL1Lqmv5To4m8EXaq/UnydENT+rb8tBuVdG9Cwv1Rkg+ePoLK/EkleXMFwtL8HVeR8qUC2vzNLwhNCELi/l+WN9oTfub+iMsYGbK67v9xQnjLxfL2/evjAdQ5Lv78ZEPnsXozAv4m23Lv8csG/SzdCu11Zwr933nIGfz/Dv9rUL8BdJcS/Wp9yEvcKxb9bI/wtSPDFv6INy0lO1ca/pLE4oga6x7/G+hh4bp7Ivxrtog+Dgsm//LZGr0Fmyr/pOnWep0nLv5MMgSSyLMy/y+Vkh14Pzb9wNNMKqvHNv8neVu+R086/qQ2mcRO1z7+mshDlFUvQvwy1TBZsu9C/4woL5Ior0b879njjcJvRv0R8gKccC9K/NS/rwIx60r/VUoy+v+nSv7fKey20WNO/eMs+mWjH07/tngaM2zXUv8J6444LpNS/xL30KfcR1b+fLaDknH/Vv+X8r0X77NW/u62B0xBa1r9LLCYU3MbWv9wZgI1bM9e/44ZcxY2f179SIZNBcQvYvztHD4gEd9i//EjsHkbi2L/gWIaMNE3Zv95gjVfOt9m/q1cWBxIi2r+BB7gi/ovav4FNlTKR9dq/Nkp+v8le279/XwpTpsfbv42vt3clMNy/uWEMuUWY3L8J28WjBQDdv3Pu98VjZ92/MfBDr17O3b+7Vgnx9DTev9aAmx4lm96/thh4ze0A37+mHomVTWbfv+5+VBFDy9+/0MIfb+YX4L/A/GPO9Engv2znXvjLe+C/rGe8QGut4L+feAr90d7gv08QzIT/D+G/vYqTMfNA4b85BhZfrHHhv0IuPWsqouG/UVI1tmzS4b+YEH2icgLivzta6JQ7MuK/tv+o9MZh4r/IZk4rFJHiv95+waQiwOK/uJc6z/Hu4r9h9TUbgR3jv+EnWfvPS+O/Msda5N1547+h4N5Mqqfjv6CyTK001eO/Xneif3wC5L8O6To/gS/kvzg0l2hCXOS/gcMheb+I5L9qCfHu97Tkv0ejikjr4OS/DweuBJkM5b9rGByiADjlv1NObp8hY+W/cxPyevuN5b9nUY6yjbjlv2rPscPX4uW/MQxPK9kM5r88tthlkTbmv775Te//X+a/kyFJQySJ5r+qARTd/bHmv64hvzeM2ua/HvU+zs4C579JOYIbxSrnvwgKkJpuUue/HSShxsp5578qaTgb2aDnv660OBSZx+e/ajr8LQru578fL2LlKxTov3as4bf9Oei/08OWI39f6L9gdE6nr4Tov/ZYkMKOqei/CKGq9RvO6L88FLbBVvLov020oKg+Fum/JME0LdM56b/I0CDTE13pv5oIAB8AgOm/v+lmlpei6b9/C+u/2cTpv1OUMyPG5um/vbAISVwI6r9MWGa7mynqvyRCkQWESuq/XeQxtBRr6r/T9mtVTYvqv6Ls/ngtq+q/b4VlsLTK6r94JveO4unqv+g/Daq2COu/OvQimTAn67+vFPr1T0Xrvz93u1wUY+u/WUcVbH2A678ROlXFip3rv/wmgQw8uuu/jfhk6JDW67/YnKACifLrv2M/rQckDuy/wwndpmEp7L90ZVSSQUTsvxoKAH/DXuy//m6AJOd47L8iXRU9rJLsv5tPgoUSrOy/YDbvvBnF7L9tFMWkwd3svz/BiQAK9uy/ISm0lfIN7b8B/IIreyXtv3cmz4qjPO2/w3ndfWtT7b+nNy/Q0mntv9zEVE7Zf+2/e9i8xX6V7b/GoYkEw6rtv3BRZtmlv+2/j4tgEyfU7b8j0sWBRujtv7sACPQD/O2/uLKjOV8P7r9PwhAiWCLuvztDt3zuNO6/QUTrGCJH7r+cU+7F8ljuv85N+FJgau6/26VBj2p77r/ZKxVKEYzuv9dA41JUnO6/LptXeTOs7r+ND3CNrrvuv6JPlV/Fyu6/+nCwwHfZ7r+PlUKCxefuv4PBeXau9e6/hBNEcDID778QaWJDURDvv3d2dsQKHe+/ookRyV4p778KKMAnTTXvv7ZJFLjVQO+/S/itUvhL779x5EPRtFbvv94ZqQ4LYe+/FX7U5vpq77+gSuc2hHTvv09CNN2mfe+/a7hHuWKG778P4vGrt47vv2RtUZellu+/tzDiXiye779s1I3nS6Xvv+7ZvxcErO+/rfd811Sy77/+oH4QPrjvv23eUK6/ve+/vZ90ntnC779rK4TQi8fvvwygWTbWy++/dEU2xLjP779Dy+lwM9Pvv5fW9jVG1u+/87i0D/HY778zg2v9M9vvvy9caQEP3e+/xawPIYLe77+QS9dkjd/vv361Stgw4O+/r9D2iWzg77+oNVKLQODvv9kKnPCs3++/Naqz0LHe779uaepET93vv0ds0WiF2++/ObsEWlTZ778qZPU3vNbvv8XhsyO90++//vq7P1fQ77+JksKviszvv3wJh5hXyO+/4FanH77D7792Dnhrvr7vvxo44KJYue+/NXM47Yyz7795/i5yW63vv8mOrlnEpu+/l3zJy8ef778eq6jwZZjvv2JofvCekO+/H1p883KI77+8sc4h4n/vv6yYmaPsdu+/FPD6oJJt77+OVA9C1GPvvxR/+q6xWe+/M4PxDytP77+Ke0mNQETvv3BQhk/yOO+/gAlsf0At778DBhFGKyHvv90Q8cyyFO+/+WT/PdcH779u1LrDmPruv/DnPon37O6/NT1VuvPe7r9QfIWDjdDuv7NCJBLFwe6/fzdflJqy7r+zj0o5DqPuvz1k6jAgk+6/Wzs8rNCC7r/NRD/dH3Luv2cm/PYNYe6/qqmKLZtP7r8dlBq2xz3uv3Z9+caTK+6/8/eal/8Y7r8Ai6FgCwbuv+Cs6Vu38u2/BfmUxAPf7b+ysxvX8MrtvwCdXdF+tu2/KgG48q2h7b/TEh98foztv2h1O7Dwdu2/Ul2J0wRh7b+3JH8su0rtv8lbsgMUNO2/1nwApA8d7b8Z1bdargXtv8yQvHfw7ey/u56uTdbV7L88MgUyYL3svyReJH2OpOy/cApoimGL7L8ojCO42XHsv6bZkWf3V+y/4m29/Lo97L9dj1beJCPsv9qqgHU1COy/O+GVLe3s67+OYORzTNHrvx4vZbdTteu/8EN3aAOZ679J9Zb4W3zrv0vzG9pdX+u/cF/8fwlC67+gSJddXyTrvzC+g+ZfBuu/HjJtjgvo6r/thfHIYsnqv1PIiAlmquq/NopywxWL6r9wM6lpcmvqv+Tl1m58S+q/J1dURTQr6r++ziRfmgrqvxfX9y2v6em/64ksI3PI6b9oXtev5qbpv6pRxkQKhem/tOaMUt5i6b8s8IpJY0DpvxKu95mZHem/Bknts4H66L835HUHHNfovzcRlgRps+i/Pr9eG2mP6L9b5Pi7HGvov6LptFaERui/jpsZXKAh6L+r1fM8cfznv+ttYmr31ue/0PDoVTOx57/2uXpxJYvnv3v9iC/OZOe/PiEQAy4+57/elaBfRRfnv2pTbrkU8Oa/yydYhZzI5r/bDPI43aDmvxQ2jkrXeOa/m4lGMYtQ5r/UFgJl+Sfmv/J0gl4i/+W/EtxplwbW5b+h8EWKpqzlv/IBm7ICg+W/LbjxjBtZ5b/Zw+KW8S7lv2cOLU+FBOW/VKrGNdfZ5L/83fTL567kv72fZpS3g+S/EiZTE0dY5L8JSpfOlizkv9bA3U2nAOS/qpnAGnnU47/gQ+/ADKjjv/Z0Us5ie+O/Cpot03tO478/UDZiWCHjv9ZerBD58+K/dn1edl7G4r/CsaYtiZjiv9uCV9N5auK/9P6aBjE84r+Rdb5orw3iv4KU+Zz13uG/8HQhSASw4b/cIVgQ3IDhv80At5x9UeG/HdX5lOkh4b+6lSihIPLgv38BUWkjwuC/hBVAlfKR4L8xrErMjmHgvwV8ILX4MOC/Pjur9TAA4L85I+dlcJ7fv9WQMSIePN+/",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
+          "bdata": 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h9D/r9GtMty/1PyT7hRKwPfY/TybC415L9z++SKgqwFj4P8RQK03QZfk/fY2lvoty+j8YNZXq7n77Pw5OezH2ivw/w6Bm7p2W/T8VsAh54qH+Py9J/CLArP8/EajznZlbAEBntSIWnOAAQI3l2rRlZQFAfszttPTpAUCRpeBSR24CQAH4Gs1b8gJAmA91YTB2A0DE8hRKw/kDQD2C0sYSfQRAWeMjHh0ABUAQz4yR4IIFQF5pgl1bBQZAhwyTuouHBkAaa8TcbwkHQFXNB/EFiwdAIroaI0wMCEAeJfCnQI0IQAMhxrPhDQlAOGIteC2OCUCHFdEmIg4KQMEyTPK9jQpAY7JKDP8MC0ASMBSm44sLQE1y1/xpCgxAReiyU5CIDEBqP2DrVAYNQKLYBgO2gw1Ajisz2LEADkBWMrWkRn0OQBd/4Jty+Q5A1OJD9DN1D0DFcwzriPAPQI9wrty3NRBALGR/SvNyEECLkVXZ9a8QQFn8L6O+7BBAimq7wEwpEUCZOghMn2URQKf8Jma1oRFANQpEMo7dEUCKfwLUKBkSQFqkYnCEVBJA+PWaLaCPEkDxqI8xe8oSQE1lOKEUBRNA3cFHpms/E0BW6oNsf3kTQKrwQB1PsxNAsgrj39nsE0DYZDPaHiYUQBE/vy8dXxRA2FLCANSXFEA6iAZvQtAUQE0FiqBnCBVACThUukJAFUCqs8/g0ncVQHNfGjkXrxVAgBhH6Q7mFUC7+lcXuRwWQG+yVusUUxZAFhTwlCGJFkC1TnBG3r4WQFC7XjJK9BZAwfEOjGQpF0Cz5lWHLF4XQEpTD1ehkhdA3jBvLMLGF0Cv8d88jvoXQHnHXcAELhhABWwM7SRhGEArWgv47ZMYQD5uMRZfxhhADnrFe3f4GECq74lbNioZQLIYW+uaWxlAXnxyZ6SMGUBKIw0NUr0ZQGy8RRqj7RlA/tcAz5YdGkBEy6xsLE0aQEHfnzRjfBpAs5staTqrGkDkxf9SsdkaQNUvEjzHBxtA4NDYbHs1G0CStOsszWIbQCAzFcO7jxtAFYBWdEa8G0ATooGDbOgbQCf+dzctFBxA5zyt2oc/HEAiou62e2ocQAhXihYIlRxAGWBtRSy/HECkGiOR5+gcQFPz30c5Eh1AdUSYvCA7HUDtUINKnWMdQIZyQ0+uix1A5oPsKVOzHUBHcWQ7i9odQAGMteVVAR5Abd0mirInHkD5u9iJoE0eQMylaUsfcx5AhPyXNi6YHkAljmWxzLweQG0AICH64B5AQtLY6rUEH0DS3sxy/ycfQHsYDhzWSh9A+ry7TjltH0D2HkF4KI8fQB1E0QajsB9ApcZEaqjRH0BbevQUOPIfQIB8q70oCSBAeBk9CfoYIEA8JZSpjyggQA27vl7pNyBAuHFp6QZHIEAo6TcK6FUgQHTTDoKMZCBAZXHzEfRyIEDxoV56HoEgQBGkp3sLjyBA31Ew2bqcIECMOrFXLKogQCjv1LtftyBAYYviylTEIECw/xpLC9EgQOb8fwOD3SBACOOKu7vpIEC+Ygs+tfUgQBhDaFlvASFA0sz53OkMIUDPuRSZJBghQApBKV8fIyFAaxZPAdotIUA5KUlRVDghQHagxyGOQiFAyNdwSIdMIUB6G/yaP1YhQHv7jO62XyFAKDwxGO1oIUCBPPrs4XEhQHpaiEGVeiFAEwV66gaDIUAQzcm/NoshQJpyfJskkyFARIwnWNCaIUD0OaLROaIhQF0mY+VgqSFA0o03ckWwIUBqAL5X57YhQGCk6XhGvSFACUZevGLDIUDgQoEJPMkhQHt5UEjSziFAK4x+YSXUIUBdZRQ+NdkhQI+ElMYB3iFApdgz5IriIUARDEqD0OYhQL6VsJDS6iFAdw0g+ZDuIUDzodKpC/IhQD8GvZBC9SFAe+ounDX4IUDzbRu75PohQG+vZuBP/SFA5/izAXf/IUBkw4YVWgEiQBduohP5AiJA4Fgc9VMEIkDbsMyzagUiQPVVe0k9BiJACmwUsssGIkAgClHsFQciQG3/zPYbByJAivr2z90GIkBG1HN2WwYiQIonEemUBSJAXqw0JooEIkCi2yctOwMiQCwn9wCoASJAdbwhptD/IUCeIfEhtf0hQAmsLXtV+yFAZ49XurH4IUDYrC/pyfUhQDSVpRKe8iFALi3URS7vIUAHfMeUeushQOrOIxKD5yFAteY80UfjIUCqdQfmyN4hQHpth2QG2iFAX3P/XwDVIUAflBntts8hQIPjDCMqyiFAlOHVGFrEIUCFwDnlRr4hQBzrVp/wtyFAFQK/XlexIUAIof86e6ohQP70xkxcoyFARLzpsPqbIUDEoyaGVpQhQNNHMOxvjCFAWmQwBEeEIUBuIMzw23shQBR5edUucyFA1iMd1j9qIUDJOt0ZD2EhQI7wM8qcVyFA4+2HEOlNIUAkOGcW9EMhQA32ugW+OSFAlE1+CEcvIUDL4CFIjyQhQJ9oue+WGSFAu0CZLV4OIUCFV6cw5QIhQEyPUygs9yBAQRIxRTPrIEBoaAq5+t4gQLfaTbaC0iBAN4XMcMvFIEAclpog1bggQMzrrf+fqyBAcMloSCyeIECg39M1epAgQOefdQOKgiBAmdqX7Ft0IEA1H80r8GUgQEG+yf1GVyBAsx/0oGBIIEDRwg1TPTkgQMMqmlHdKSBAMvtR2kAaIECxPRgraAogQA6DEAOn9B9AQFY0OgbUH0DACk6C7rIfQJCPj2RgkR9AYZtObFxvH0DwUQco40wfQJb9MCn1KR9AayOkApMGH0AqDThJveIeQDANQpl0vh5A0ZbtkbmZHkD8lNrRjHQeQE1QoPfuTh5ASDrCoeAoHkC2X55tYgIeQB9ko/Z02x1AyKom3Bi0HUCjGX3BTowdQIl1TUkXZB1Ad69vFnM7HUAyFvnMYhIdQJanMxLn6BxAbYmKiwC/HEB7Ex3ir5QcQHZi2cb1aRxApdS47NI+HEAa5YIHSBMcQLTDScxV5xtAWDXl8Py6G0Cw6DUqPo4bQMuXeywaYRtAAwBBsZEzG0AjBKNzpQUbQD+nKC1W1xpA1gHblqSoGkAXR91pkXkaQPkI8l4dShpAj//0LUkaGkA2JsCTFeoZQNqBG1ODuRlAWBjcL5OIGUDnbXjvRVcZQPr1y1mcJRlA1R2eOJfzGEBReOtVN8EYQIHYZX59jhhAcQVthWpbGEBrHPE+/ycYQAkOpn089BdACGJ6EyPAF0CnoETRs4sXQLWZXYXvVhdArH0B/NYhF0DmTq4Fa+wWQMTQSnSsthZA5C74F5yAFkCCcmXAOkoWQB2KqT2JExZA84n7X4jcFUBjERL3OKUVQJi0ptebbRVAKzHX3LE1FUBx1L/ie/0UQEtwfcb6xBRAb6aRZi+MFECamiCiGlMUQDXFBVe9GRRAucnlYxjgE0BbXr6sLKYTQP6bRhX7axNAF3w5f4QxE0CTJz/LyfYSQEFGENnLuxJAPHF6houAEkCXo7+vCUUSQLSkKjZHCRJAyvni/UTNEUDSf2vqA5ERQJFHy9+EVBFAQpUxw8gXEUAqNVR60NoQQAd4I+qcnRBAskNW+y5gEECO1M2bhyIQQCZKA3FPyQ9AN7zqeSBND0ApgwwnhNAOQM+dnkl8Uw5A5TkVrArWDUC40VEWMVgNQPFKg1jx2QxA+LlzQU1bDEBJFYabRtwLQF4qiy/fXAtAOWIAxhjdCkC6kekl9VwKQFp0ehV23AlATENDZ51bCUArM8r2bNoIQCXrQ6DmWAhA3YfPQQzXB0COq7K731QHQBH7De5i0gZAQroatZdPBkCGLePwf8wFQIEeC4kdSQVA/2CfYHLFBEAZxw5VgEEEQHHUhT9JvQNA5ByU9M44A0CoerZBE7QCQL3mY/EXLwJA8LIU196pAUCCWY7GaSQBQAniZpC6ngBA4PvTBNMYAEA0B3DpaSX/P0gQCWDEGP4/XjQXCrkL/T/BcMiYS/77Pyy5Vst/8Po/THNeW1ni+T8hWcb929P4P314GmMLxfc/HzHXM+u19j/5ZBEKf6b1P+D8ZoHKlvQ/++I+Q9GG8z9+w4TwlnbyP8p0xiAfZvE/1EXWZm1V8D8noFWjConuPxyz+tDUZuw/HRKOY0BE6j+7xTaYVCHoP/2suboY/uU/9hHFEZTa4z+uVuzlzbbhP580dAKbJd8/IGwTSDTd2j+xK8j3dZTWPzftbJxuS9I/WNxsulkEzD9Ir6VUfnHDP7ubeQbPvLU/9e3hXItZkj+9fMPJICCpv7uJDkhUtr2/VLiwQxlux79TSNT8XADQv06qkXF4SdS/EAVtbFGS2L/+cz1h2trcv3dNrOKCkeC/ZeR1D2O14r8I7cr4Btnkv3wog65n/Oa/oLoAMH4f6b9jrC6GQ0Lrv77brb+wZO2/NLjS8r6G779zbG6kM9Twv3zR44PR5PG/xlmtszX18r8Vp3rJXAX0vyPXJGlDFfW/lMCIQuYk9r8lQDcOQjT3v2pCBY5TQ/i/toFAkRdS+b88+ODlimD6v/Twb0aqbvu/ukUjb3J8/L8U6Nwg4In9v/ukMx3wlv6/Nyb6Jp+j/7/MLTME9VcAwPwNAcnm3QDA",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 0.2192<br>i: 55.61°<br>Ω: 127.63°<br>ω: 199.65°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "JFC"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 0.2192<br>i: 55.61°<br>Ω: 127.63°<br>ω: 199.65°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "JFC"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 0.1526<br>i: 38.63°<br>Ω: 349.45°<br>ω: 22.97°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 0.1526<br>i: 38.63°<br>Ω: 349.45°<br>ω: 22.97°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Other"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-03<br>e: 0.1975<br>i: 49.37°<br>Ω: 321.52°<br>ω: 297.95°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Other"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 0.0720<br>i: 26.60°<br>Ω: 280.22°<br>ω: 227.40°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 0.0720<br>i: 26.60°<br>Ω: 280.22°<br>ω: 227.40°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
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+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
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+          "yaxis": {
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+         "showgrid": true,
+         "title": {
+          "text": "X [AU]"
+         }
+        },
+        "xaxis2": {
+         "anchor": "y2",
+         "domain": [
+          0.55,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "X [AU]"
+         }
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "scaleanchor": "x",
+         "scaleratio": 1,
+         "showgrid": true,
+         "title": {
+          "text": "Y [AU]"
+         }
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "rgba(255,255,255,0.08)",
+         "showgrid": true,
+         "title": {
+          "text": "Z [AU]"
+         }
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ephem, _, _ = build_ephem_and_mus(None)\n",
+    "epochJD_center = float(61000.0 + 2400000.5)\n",
+    "\n",
+    "planet_names = [\"Mercury\", \"Venus\", \"Earth\", \"Mars\", \"Jupiter\", \"Saturn\"]\n",
+    "planet_lines_cache, planet_id = build_planet_lines_cache(\n",
+    "    ephem,\n",
+    "    epochJD_center,\n",
+    "    planet_names=planet_names,\n",
+    "    n_points=900,\n",
+    ")\n",
+    "\n",
+    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3ce3a5f6",
+   "metadata": {},
+   "source": [
+    "3D plots are equally as easy, just call `plotly_3D` instead! Again, we plot in heliocentric ecliptic by default, and now we overplot the ecliptic plane in red to help you orient yourself better. On the Dash app version you can control the transparency of this (including turning it off entirely - if you want to do this here, just change `show_plane` to False), and convert it to the equatorial plane via a toggle button. Planets can be added in the exact same way as before. Play around and try hovering over orbit lines again to see how our toy objects look in 3D this time. Try lining up the XY and XZ planes as in the 2D case above - do they match? "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "2dc7374b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
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+         "hoverinfo": "skip",
+         "name": "ref-plane",
+         "opacity": 0.5,
+         "showscale": false,
+         "surfacecolor": {
+          "bdata": "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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+          "dtype": "f8",
+          "shape": "40, 40"
+         },
+         "type": "surface",
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",
+          "dtype": "f8",
+          "shape": "40, 40"
+         },
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",
+          "dtype": "f8",
+          "shape": "40, 40"
+         },
+         "z": {
+          "bdata": "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                ",
+          "dtype": "f8",
+          "shape": "40, 40"
+         }
+        },
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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",
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+         }
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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",
+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter3d",
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+         },
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",
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+         },
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+         }
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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h9D/r9GtMty/1PyT7hRKwPfY/TybC415L9z++SKgqwFj4P8RQK03QZfk/fY2lvoty+j8YNZXq7n77Pw5OezH2ivw/w6Bm7p2W/T8VsAh54qH+Py9J/CLArP8/EajznZlbAEBntSIWnOAAQI3l2rRlZQFAfszttPTpAUCRpeBSR24CQAH4Gs1b8gJAmA91YTB2A0DE8hRKw/kDQD2C0sYSfQRAWeMjHh0ABUAQz4yR4IIFQF5pgl1bBQZAhwyTuouHBkAaa8TcbwkHQFXNB/EFiwdAIroaI0wMCEAeJfCnQI0IQAMhxrPhDQlAOGIteC2OCUCHFdEmIg4KQMEyTPK9jQpAY7JKDP8MC0ASMBSm44sLQE1y1/xpCgxAReiyU5CIDEBqP2DrVAYNQKLYBgO2gw1Ajisz2LEADkBWMrWkRn0OQBd/4Jty+Q5A1OJD9DN1D0DFcwzriPAPQI9wrty3NRBALGR/SvNyEECLkVXZ9a8QQFn8L6O+7BBAimq7wEwpEUCZOghMn2URQKf8Jma1oRFANQpEMo7dEUCKfwLUKBkSQFqkYnCEVBJA+PWaLaCPEkDxqI8xe8oSQE1lOKEUBRNA3cFHpms/E0BW6oNsf3kTQKrwQB1PsxNAsgrj39nsE0DYZDPaHiYUQBE/vy8dXxRA2FLCANSXFEA6iAZvQtAUQE0FiqBnCBVACThUukJAFUCqs8/g0ncVQHNfGjkXrxVAgBhH6Q7mFUC7+lcXuRwWQG+yVusUUxZAFhTwlCGJFkC1TnBG3r4WQFC7XjJK9BZAwfEOjGQpF0Cz5lWHLF4XQEpTD1ehkhdA3jBvLMLGF0Cv8d88jvoXQHnHXcAELhhABWwM7SRhGEArWgv47ZMYQD5uMRZfxhhADnrFe3f4GECq74lbNioZQLIYW+uaWxlAXnxyZ6SMGUBKIw0NUr0ZQGy8RRqj7RlA/tcAz5YdGkBEy6xsLE0aQEHfnzRjfBpAs5staTqrGkDkxf9SsdkaQNUvEjzHBxtA4NDYbHs1G0CStOsszWIbQCAzFcO7jxtAFYBWdEa8G0ATooGDbOgbQCf+dzctFBxA5zyt2oc/HEAiou62e2ocQAhXihYIlRxAGWBtRSy/HECkGiOR5+gcQFPz30c5Eh1AdUSYvCA7HUDtUINKnWMdQIZyQ0+uix1A5oPsKVOzHUBHcWQ7i9odQAGMteVVAR5Abd0mirInHkD5u9iJoE0eQMylaUsfcx5AhPyXNi6YHkAljmWxzLweQG0AICH64B5AQtLY6rUEH0DS3sxy/ycfQHsYDhzWSh9A+ry7TjltH0D2HkF4KI8fQB1E0QajsB9ApcZEaqjRH0BbevQUOPIfQIB8q70oCSBAeBk9CfoYIEA8JZSpjyggQA27vl7pNyBAuHFp6QZHIEAo6TcK6FUgQHTTDoKMZCBAZXHzEfRyIEDxoV56HoEgQBGkp3sLjyBA31Ew2bqcIECMOrFXLKogQCjv1LtftyBAYYviylTEIECw/xpLC9EgQOb8fwOD3SBACOOKu7vpIEC+Ygs+tfUgQBhDaFlvASFA0sz53OkMIUDPuRSZJBghQApBKV8fIyFAaxZPAdotIUA5KUlRVDghQHagxyGOQiFAyNdwSIdMIUB6G/yaP1YhQHv7jO62XyFAKDwxGO1oIUCBPPrs4XEhQHpaiEGVeiFAEwV66gaDIUAQzcm/NoshQJpyfJskkyFARIwnWNCaIUD0OaLROaIhQF0mY+VgqSFA0o03ckWwIUBqAL5X57YhQGCk6XhGvSFACUZevGLDIUDgQoEJPMkhQHt5UEjSziFAK4x+YSXUIUBdZRQ+NdkhQI+ElMYB3iFApdgz5IriIUARDEqD0OYhQL6VsJDS6iFAdw0g+ZDuIUDzodKpC/IhQD8GvZBC9SFAe+ounDX4IUDzbRu75PohQG+vZuBP/SFA5/izAXf/IUBkw4YVWgEiQBduohP5AiJA4Fgc9VMEIkDbsMyzagUiQPVVe0k9BiJACmwUsssGIkAgClHsFQciQG3/zPYbByJAivr2z90GIkBG1HN2WwYiQIonEemUBSJAXqw0JooEIkCi2yctOwMiQCwn9wCoASJAdbwhptD/IUCeIfEhtf0hQAmsLXtV+yFAZ49XurH4IUDYrC/pyfUhQDSVpRKe8iFALi3URS7vIUAHfMeUeushQOrOIxKD5yFAteY80UfjIUCqdQfmyN4hQHpth2QG2iFAX3P/XwDVIUAflBntts8hQIPjDCMqyiFAlOHVGFrEIUCFwDnlRr4hQBzrVp/wtyFAFQK/XlexIUAIof86e6ohQP70xkxcoyFARLzpsPqbIUDEoyaGVpQhQNNHMOxvjCFAWmQwBEeEIUBuIMzw23shQBR5edUucyFA1iMd1j9qIUDJOt0ZD2EhQI7wM8qcVyFA4+2HEOlNIUAkOGcW9EMhQA32ugW+OSFAlE1+CEcvIUDL4CFIjyQhQJ9oue+WGSFAu0CZLV4OIUCFV6cw5QIhQEyPUygs9yBAQRIxRTPrIEBoaAq5+t4gQLfaTbaC0iBAN4XMcMvFIEAclpog1bggQMzrrf+fqyBAcMloSCyeIECg39M1epAgQOefdQOKgiBAmdqX7Ft0IEA1H80r8GUgQEG+yf1GVyBAsx/0oGBIIEDRwg1TPTkgQMMqmlHdKSBAMvtR2kAaIECxPRgraAogQA6DEAOn9B9AQFY0OgbUH0DACk6C7rIfQJCPj2RgkR9AYZtObFxvH0DwUQco40wfQJb9MCn1KR9AayOkApMGH0AqDThJveIeQDANQpl0vh5A0ZbtkbmZHkD8lNrRjHQeQE1QoPfuTh5ASDrCoeAoHkC2X55tYgIeQB9ko/Z02x1AyKom3Bi0HUCjGX3BTowdQIl1TUkXZB1Ad69vFnM7HUAyFvnMYhIdQJanMxLn6BxAbYmKiwC/HEB7Ex3ir5QcQHZi2cb1aRxApdS47NI+HEAa5YIHSBMcQLTDScxV5xtAWDXl8Py6G0Cw6DUqPo4bQMuXeywaYRtAAwBBsZEzG0AjBKNzpQUbQD+nKC1W1xpA1gHblqSoGkAXR91pkXkaQPkI8l4dShpAj//0LUkaGkA2JsCTFeoZQNqBG1ODuRlAWBjcL5OIGUDnbXjvRVcZQPr1y1mcJRlA1R2eOJfzGEBReOtVN8EYQIHYZX59jhhAcQVthWpbGEBrHPE+/ycYQAkOpn089BdACGJ6EyPAF0CnoETRs4sXQLWZXYXvVhdArH0B/NYhF0DmTq4Fa+wWQMTQSnSsthZA5C74F5yAFkCCcmXAOkoWQB2KqT2JExZA84n7X4jcFUBjERL3OKUVQJi0ptebbRVAKzHX3LE1FUBx1L/ie/0UQEtwfcb6xBRAb6aRZi+MFECamiCiGlMUQDXFBVe9GRRAucnlYxjgE0BbXr6sLKYTQP6bRhX7axNAF3w5f4QxE0CTJz/LyfYSQEFGENnLuxJAPHF6houAEkCXo7+vCUUSQLSkKjZHCRJAyvni/UTNEUDSf2vqA5ERQJFHy9+EVBFAQpUxw8gXEUAqNVR60NoQQAd4I+qcnRBAskNW+y5gEECO1M2bhyIQQCZKA3FPyQ9AN7zqeSBND0ApgwwnhNAOQM+dnkl8Uw5A5TkVrArWDUC40VEWMVgNQPFKg1jx2QxA+LlzQU1bDEBJFYabRtwLQF4qiy/fXAtAOWIAxhjdCkC6kekl9VwKQFp0ehV23AlATENDZ51bCUArM8r2bNoIQCXrQ6DmWAhA3YfPQQzXB0COq7K731QHQBH7De5i0gZAQroatZdPBkCGLePwf8wFQIEeC4kdSQVA/2CfYHLFBEAZxw5VgEEEQHHUhT9JvQNA5ByU9M44A0CoerZBE7QCQL3mY/EXLwJA8LIU196pAUCCWY7GaSQBQAniZpC6ngBA4PvTBNMYAEA0B3DpaSX/P0gQCWDEGP4/XjQXCrkL/T/BcMiYS/77Pyy5Vst/8Po/THNeW1ni+T8hWcb929P4P314GmMLxfc/HzHXM+u19j/5ZBEKf6b1P+D8ZoHKlvQ/++I+Q9GG8z9+w4TwlnbyP8p0xiAfZvE/1EXWZm1V8D8noFWjConuPxyz+tDUZuw/HRKOY0BE6j+7xTaYVCHoP/2suboY/uU/9hHFEZTa4z+uVuzlzbbhP580dAKbJd8/IGwTSDTd2j+xK8j3dZTWPzftbJxuS9I/WNxsulkEzD9Ir6VUfnHDP7ubeQbPvLU/9e3hXItZkj+9fMPJICCpv7uJDkhUtr2/VLiwQxlux79TSNT8XADQv06qkXF4SdS/EAVtbFGS2L/+cz1h2trcv3dNrOKCkeC/ZeR1D2O14r8I7cr4Btnkv3wog65n/Oa/oLoAMH4f6b9jrC6GQ0Lrv77brb+wZO2/NLjS8r6G779zbG6kM9Twv3zR44PR5PG/xlmtszX18r8Vp3rJXAX0vyPXJGlDFfW/lMCIQuYk9r8lQDcOQjT3v2pCBY5TQ/i/toFAkRdS+b88+ODlimD6v/Twb0aqbvu/ukUjb3J8/L8U6Nwg4In9v/ukMx3wlv6/Nyb6Jp+j/7/MLTME9VcAwPwNAcnm3QDA",
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+         },
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",
+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 0.0100<br>i: 22.25°<br>Ω: 272.91°<br>ω: 81.81°<extra></extra>",
+         "line": {
+          "color": "rgba(144, 167, 209, 0.7)",
+          "width": 3
+         },
+         "meta": {
+          "kind": "Centaur"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
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+         },
+         "meta": {
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+         "name": "Obj-01",
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+         "line": {
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+         "meta": {
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+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "line": {
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+          "width": 3
+         },
+         "meta": {
+          "kind": "MBA"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+          "dtype": "f8"
+         }
+        },
+        {
+         "customdata": [
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ]
+         ],
+         "hovertemplate": "%{text}<br>@ MJD %{customdata[0]}<br>(%{customdata[1]})<extra></extra>",
+         "marker": {
+          "color": "rgba(255,255,255,0.9)",
+          "size": 3.5
+         },
+         "meta": {
+          "kind": "epoch"
+         },
+         "mode": "markers",
+         "showlegend": false,
+         "text": [
+          "Obj-00",
+          "Obj-01",
+          "Obj-02",
+          "Obj-03",
+          "Obj-04"
+         ],
+         "type": "scatter3d",
+         "x": {
+          "bdata": "eZjBuvfIDEAyzzr0H3gUwH8khKGS0RxAZkvQ3mXlG0DgPmryrWQAQA==",
+          "dtype": "f8"
+         },
+         "y": {
+          "bdata": "WkkNMrV6IUDxP553kPEUQOx2LTHgXg1AlaIyulmvDsAgcpMOk3jxPw==",
+          "dtype": "f8"
+         },
+         "z": {
+          "bdata": "N4p1d9ps+j+9ToUmzwH0P/hlDrxhgg9Ar7ZGo9Hq+D+0i7J0sLbxPw==",
+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertext": "Sun",
+         "marker": {
+          "color": "yellow",
+          "size": 6
+         },
+         "mode": "markers",
+         "showlegend": false,
+         "type": "scatter3d",
+         "x": [
+          0
+         ],
+         "y": [
+          0
+         ],
+         "z": [
+          0
+         ]
+        }
+       ],
+       "layout": {
+        "autosize": true,
+        "font": {
+         "color": "white"
+        },
+        "margin": {
+         "b": 0,
+         "l": 0,
+         "r": 0,
+         "t": 40
+        },
+        "paper_bgcolor": "rgba(0,0,0,0)",
+        "plot_bgcolor": "rgba(0,0,0,0)",
+        "scene": {
+         "aspectmode": "data",
+         "camera": {
+          "center": {
+           "x": 0,
+           "y": 0,
+           "z": -0.25
+          }
+         },
+         "xaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "X [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         },
+         "yaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "Y [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         },
+         "zaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "Z [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         }
+        },
+        "template": {}
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig3d = plotly_3D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, show_plane=True, return_fig=True)\n",
+    "fig3d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9a2957ed",
+   "metadata": {},
+   "source": [
+    "## 5) Parabolic & hyperbolic orbits\n",
+    "\n",
+    "Parabolic and hyperbolic orbits are naturally handelled by Layup Visualize in the exact same way as any other regular orbit. The only difference is we set a maximum distance that we draw the parabolae/hyperbolae out to, which the user can alter if they want to see more or less of the trajectory"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "9da31523",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
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btj+p9oqBTQq2PxCjfH6vOLU/ko3rCopmtD90aWVb4pOzP2iWVKq9wLI/kuuhNyHtsT+b00RIEhmxP29zJyaWRLA/LMDBPmTfrj9XKjAM1zStP1e6I2CPias/doSe7JfdqT8bYFdp+zCoPwuz9ZLEg6Y/q5MqKv7VpD9KX3XzsiejP80YkbXteKE/oPhxcnKTnz9qpoOQQDScP6/xq1lb1Jg/ndNjYdhzlT+N7n04zRKSP2v6bdmeYo0/AfQqC+mehj9jY/gPSLV/P0fMxYH1K3I/zKEXmcCIUj8LvrDqZM9hv+rqJPhccXa/G29vHz39gb/vjxK0WsGIv4Pt4+rchI+/MSzczMwjk798Gwlfs4SWv9WG7D8N5Zm/LZJImsVEnb9M5PXX41Ggvy20TW7/AKK/pEYjS6uvo7/BSkY33V2lv9Fa/AmLC6e/Psebqaq4qL9+TSMMMmWqv/vK8DcXEay/kPnJQ1C8rb9rdzdY02avv+Nhw1dLiLC/uts5S8hcsb/aKla22zCyv2iMqNKABLO/aq/J47LXs7973FM3baq0v3ThgiWrfLW/Ln4pEWhOtr8LVflnnx+3vwcduKJM8Le/TfRyRWvAuL8AXcDf9o+5v1yOrQzrXrq/kopPc0Mtu7+6jqzG+/q7vxiK9sUPyLy/xhizPHuUvb/omeECOmC+v2+QL/1HK7+/JC7aHKH1v795BhiwoF/Av+tvN2kSxMC/njf4xSMowb9FwSLZ0ovBv8R7J7wd78G/+YUqjwJSwr+cRxZ5f7TCv1XjhaeSFsO/+mL9Tjp4w78dXNKqdNnDvxYYO/0/OsS/twNVj5qaxL/mSiqxgvrEv9E9vrn2WcW/v9vyBvW4xb+UwLn9exfGv7IM+AmKdca//rKPnh3Txr9+ZGA1NTDHv8TAR0/PjMe/riQodOrox79cEMoyhUTIv6tdBiGen8i/lTem2zP6yL/OPmcGRVTJvwWs90vQrcm/j9PxXdQGyr/bGd70T1/Kv8IPEdBBt8q/UpfPtagOy78Iyytzg2XLv9q+BNzQu8u/Zab+yo8RzL+renohv2bMv2Ejjcddu8y/fNj8q2oPzb+rkxzE5GLNvysi6gvLtc2/C6TohRwIzr+yQxw72FnOv1bO/jr9qs6/xe1zm4r7zr9WY8N4f0vPvyITc/Xams+/i4ZgOpzpz7+3Hk074RvQv6ZYrG+mQtC/mlT4Vx1p0L/6pOKURY/Qv671H8oetdC/M8ZUnqja0L/6OCC74v/Qv9yJCM3MJNG/TJF2g2ZJ0b+QJ66Qr23Rv21yxqmnkdG/dPSkhk610b9FWOrho9jRv2+b+3in+9G/x6zuC1ke0r8CQoVduEDSvzLFJDPFYtK/NDfOVH+E0r+vCBaN5qXSv3iLHqn6xtK/rTKFeLvn0r9GL2rNKAjTv8CYXXxCKNO/3NBZXAhI07/JPbtGemfTv2oDOBeYhtO/fS7aq2Gl07+WoO3k1sPTv1mMBqX34dO/IFnv0MP/079U36JPOx3Uv+0wRApeOtS/1mcW7CtX1L9wvXbipHPUvwxWy9zIj9S/UMmIzJer1L9B8SClEcfUvwQr/Vs24tS/gVh26AX91L857cxDgBfVv5UZI2mlMdW/0ZxsVXVL1b/AfHMH8GTVv0vkx38VftW/z4m6wOWW1b83ClXOYK/Vv89SUq6Gx9W/WRoXaFff1b9WRqwE0/bVv9kKsI75Dda/d9NZEssk1r+udmudRzvWv0XkKz9vUda/yAFgCEJn1r+emEMLwHzWv0IDhFvpkda/DYQyDr6m1r/zjMc5PrvWv9AtFfZpz9a/IRJCXEHj1r/z3cKGxPbWv66dU5HzCde/VsfymM4c178D0tS7VS/XvyzoZhmJQde/sJhC0mhT17+OLCkI9WTXv42L/d0tdte/dzS+dxOH17+RmID6pZfXvx73ZYzlp9e/QoGdVNK317+rT1l7bMfXv80Tyim01te/f4YZiqnl17976mTHTPTXv3eitw2eAti/oPUGip0Q2L8CWyhqSx7Yv8H+0tynK9i/SCeWEbM42L8HTtU4bUXYvw8qw4PWUdi/1s1cJO9d2L95xWVNt2nYv6OdXzIvddi/096KB1eA2L/ErN4BL4vYvy02BVe3ldi/uUJXPfCf2L9w09fr2anYvz6WMJp0s9i/oJ+qgMC82L+b2i7YvcXYv0XZPtpszti/vJXxwM3W2L8Jfe/G4N7Yvy+Lbiem5ti/7g0vHh7u2L9ZhnXnSPXYv3OLCsAm/Ni/rMA05bcC2b9b4bWU/AjZv3VAxwz1Dtm/klgWjKEU2b97a8FRAhrZv4eWVJ0XH9m/4/fEruEj2b8L7G/GYCjZv4dFFiWVLNm/C6TZC38w2b9xbzm8HjTZv1HhD3h0N9m/TViPgYA62b8Iiz4bQz3ZvwAy94e8P9m/qEriCu1B2b9eqHXn1EPZv6hRcWF0Rdm/rurcvMtG2b/LPwU+20fZvx95eSmjSNm/BS4JxCNJ2b+apsFSXUnZv6ie6xpQSdm/TPwIYvxI2b+bktJtYkjZv5jbNYSCR9m/hh9T61xG2b9973rp8UTZv45YLMVBQ9m//9ASxUxB2b/ZPwQwEz/Zvx0P/0yVPNm/z0goY9M52b/8fcm5zTbZvyz1T5iEM9m/1nNJRvgv2b88dmMLKSzZv2ZEaS8XKNm//EtC+sIj2b+jg/CzLB/ZvylyjqRUGtm/6zVPFDsV2b/1sXpL4A/ZvwWdbZJECtm/N7KXMWgE2b+qSnpxS/7Yv9D/ppru99i/bsy99VHx2L8W4W3LderYv3E0cWRa49i/ql2NCQDc2L/I2pEDZ9TYvzvjVpuPzNi/CUK8GXrE2L/diqfHJrzYv4WwBe6Vs9i/HvjF1ceq2L8ZlNvHvKHYv6T6Ow11mNi/xerd7vCO2L8FeLi1MIXYv80cwqo0e9i/AQDvFv1w2L85XDNDimbYvyvAfXjcW9i/03i5//NQ2L+P9Mwh0UXYv6T6mCd0Oti/iuj3Wd0u2L84AbwBDSPYvzKAsmcDF9i/5z6d1MAK2L91yTWRRf7Xv17IK+aR8de/mF4kHKbk17+sjLl7gtfXv8CFeE0nyte/CmXl2ZS817/ROXRpy67Xv629jETLoNe/CsGIs5SS178dq7P+J4TXv0v+SW6Fdde/Zq93Sq1m17+ydFzbn1fXv886BGldSNe/lnNrO+Y4179mgn2aOinXv8hZFM5aGde/5Rz4HUcJ17/vxN7R//jWv2l3ajGF6Na/UnouhNfX1r/K/6YR98bWv0IZPiHktda/PyBK+p6k1r9qcQ3kJ5PWv9MqtiV/gda/xX5cBqVv1r8jMAjNmV3Wvx3Np8BdS9a/AioWKPE41r99xBhKVCbWv92UX22HE9a/KuKE2IoA1r93jwvSXu3Vv+oYZaAD2tW/OUHoiXnG1b+TDNfUwLLVv7IcXcfZntW/dZWPp8SK1b/zA227gXbVv6uk20gRYtW/LtqvlXNN1b8vUaLnqDjVv610VoSxI9W/VsFYsY0O1b/puh60PfnUv+vjBtLB49S/iLdYUBrO1L/N5UJ0R7jUv3ZN4oJJotS/s4c3wSCM1L8r3y10zXXUv76XmeBPX9S/ovQ3S6hI1L9lQK/41jHUv2b/jC3cGtS/kVVNLrgD1L+vEVA/a+zTvw4Q4KT11NO/Z3cxo1e90792y2F+kaXTvzsBeHqjjdO/Bqdi2411078jsP/kUF3Tv0AEEdvsRNO/6EdEAWIs07/PDTGbsBPTv1z0WOzY+tK/lMQnONvh0r8ej/HBt8jSv0PY+sxur9K/GbBsnACW0r8r21xzbXzSv9z3y5S1YtK/YKWlQ9lI0r/zq8DC2C7Sv18m31S0FNK/8JGsPGz60b/iYca8AODRv1KVrxdyxdG/NUfZj8Cq0b/SxaBn7I/RvxzDT+H1dNG/C4YcP91Z0b9B7yfDoj7Rvz9hhq9GI9G/vOkyRskH0b+PJhjJKuzQv+ZQDnpr0NC/vHTbmou00L8iqTNti5jQv10JtzJrfNC/I+36LCtg0L9Zqnydy0PQv/TJqsVMJ9C/Ggfj5q4K0L+QGeWE5NvPv2RoLDMuos+/MeXwWjtoz78OuXV+DC7Pv74K0R+i886/ov7+wPy4zr9Snd3jHH7Ov8hZLQoDQ86/zZiRta8Hzr/8OZFnI8zNvy9akqFekM2/Yfrt5GFUzb/I6tOyLRjNv2VrXozC28y/R/iN8iCfzL+K2klmSWLMv666YGg8Jcy/zU2Eefrny7/Wfl0ahKrLvyCsb8vZbMu/gsosDfwuy7+YG/Ff6/DKvz/HA0Sossq/FnaXOTN0yr+o6sXAjDXKvyqkpFm19sm/KXknhK23yb+UNDXAdXjJvw43o40OOcm/9xc2bHj5yL9KR6Lbs7nIv8STh1vBeci/qD6Ga6E5yL9c/iCLVPnHv9wM0jnbuMe/SrUG9zV4x7+/+x9CZTfHv+VFc5pp9sa/nARLf0O1xr/fJeJv83PGvymfeet5Msa/IdA5cdfwxb8UCEiADK/Fv7b+wZcZbcW/4IK+Nv8qxb9HKk7cvejEvxuzdgdWpsS/gO1IN8hjxL/4ncHqFCHEv1Ni36A83sO/",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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3Db8C5KYROGsNv4aZVMr3ng2/Nph69P3RDb+kvSeD9QMOv4StaeWHNA6/sJR7/l1jDr9EtL9IIZAOv1Y+siF9ug6/LFWUOSDiDr8wUIodvgYPv9o73M4QKA+/4DpZVtpFD79yFf8/5l8Pv750++kKdg+/0mm8kiqID79i3NQUNJYPv+ove0QjoA+/tCbk6ACmD7/+dART4qcPv+yHPJropQ+/EqxOjT+gD79a6hhqHJcPv0TLc3C8ig+/jFV1ZGN7D7/SN28SWmkPvyhs1uPsVA+/PHpukGo+D7987SvzIiYPv5ZingZmDA+/zlOaCYPxDr+kPYbKx9UOv1RF9hWAuQ6/6KFERPWcDr+OZlvhbYAOv/q+vWktZA6/2iEzGHRIDr/EjcS/fi0Ov046Va6GEw6/2OWolMH6Db/ovkBxYeMNv8hMEXyUzQ2/zuGAEYW5Db96rMabWacNv/hr/nk0lw2/mLrY5DOJDb+6KQDRcX0Nv7AyuM8DdA2/oDhd7vpsDb/YE7GVY2gNv+wm+mlFZg2/ll4TLaNmDb82Yo+jemkNv5jaF37Ebg2/qHEHSHR2Db+U9DxceIANv/4x4eC5jA2/tCPSyhybDb8GUg/pf6sNvzYqivi8vQ2/ovZowKjRDb/cb+w2E+cNv7o55K7H/Q2/qgnmDY0VDr+E4WMLJi4Ov1ZOEnlRRw6/Jp46lcpgDr9+Be5nSXoOv7hrYCyDkw6/4kkByCqsDr/6GzxR8cMOvzbn7aeG2g6/XtqsIZrvDr/cAM9L2wIPvyhFl8T6Ew+/6gohLKsiD7/4O1Qsoi4Pv54DjZWZNw+/mnh3i1A9D7/0P067jD8Pv9qhLZIbPg+/DofDZ9M4D78OWNSPlC8Pv94+/UNKIg+/UI89V+sQD78QvkmmevsOv0oLuDoH4g6/YMZJG6zEDr/GeLzIj6MOvx7XF2zjfg6/YEiZwOFWDr/AwoLHzSsOv6Yc+lbx/Q2/eCAqlpvNDb8I4Fp4H5sNv0icokbSZg2/au7+RAoxDb8G1+B7HfoMv5SKwatgwgy/FIfubCaKDL+U8tZ6vlEMv1JRBCh1GQy/ipd09pLhC79mEgFPXKoLv4IFU1IRdAu/6uzUve0+C7+g5WXfKAsLv1zZMpP12Aq/rGqMR4KoCr+oDmAD+XkKv4z5h2x/TQq/ULnPyzYjCr9MfA8NPPsJvxihZ7qn1Qm/EC3t8Y2yCb/GFMZV/pEJvwib6/YDdAm/fHVHO6VYCb/ouCfA4z8Jv5aIbTq8KQm/cFkEViYWCb9MoYqWFAUJv2IYNDt09gi/yHwXKC3qCL+wFhrXIeAIvyx7t1Iv2Ai/qLeuPC3SCL+UIHPi7c0Iv/TJ9mA+ywi/5LLu2ObJCL8Opmq0qskIv/q7+/1Iygi/Eo9byXzLCL9IiPus/cwIv8gOoEuAzgi/+o3g7LbPCL9qijAjUtAIv4pZCn4B0Ai/DvXPRnTOCL+6JwVHWssIv/J0ipZkxgi/apCtcEa/CL+a5bQOtrUIv/y5jYZtqQi/0troqyuaCL+2fabxtIcIv4zhwEjUcQi//r8v+VtYCL8s3TRwJjsIv5aPr/4WGgi/hnwUgRr1B784KxPqJ8wHv5h0pqhAnwe/9MBt4nBuB79itSh8zzkHv0q6hOt9AQe/vqm8z6fFBr8Ayh9RgoYGvxpXo0pLRAa/TL6gQ0j/Bb+6obBCxbcFv7L6mYQTbgW/gB/EI4giBb9AON28etUEv+hB6BxEhwS/RmlNAz04BL/Kc8AAvegDv3Kk7XgZmQO/RI29yqRJA7/u7jigrfoCv57PKmV+rAK/kEm/4VxfAr/YiFX1iRMCvw5zs2xByQG/Kmen7rmAAb/WOgP6JDoBv+DsGfCu9QC/yjhSJ3+zAL+Uwv4BuHMAv9j3BwZ3NgC/iOif5an3/77IXh+my4f/vogeSxJyHf++aH5dqbK4/r447sqhmVn+vli/H9cpAP6+HAa0qVys/b6QNcfRIV79vjiCTShfFf2+EILQaPDR/L7wWYDwppP8vuR5dH9JWvy+6EndAZQl/L5oLqdnN/X7vkSLa5HZyPu+KGL1WRWg+770133Denr7vjznUU+PV/u+9CnLhc42+77kaDWzqhf7vogBfNyN+fq+GF5y7Nrb+r54BDUY7736vhhdpXYjn/q+AB64xM5++r6E9CVOR1z6vjiwV/DkNvq+BO5XLAMO+r7sH/U7A+H5vtS0bx5Or/m+aHW1kVZ4+b6Q4Fvumjv5vmQf3t2m+Pi+ELBl5BSv+L4AKay4j174vjxZEGbTBvi+ZAnzNa6n97786zpeAUH3vhDJVHPB0va+BMpunPZc9r5kz5CIvN/1vhQ+rCNCW/W+mKHbCsnP9L7oS7q/pD30voSYkps5pfO+ICiqhPsG874UjEFpbGPyvog5NYYau/G+vN31gJ4O8b7saL5emV7wvnh2CclkV+++4A5G2Snt7b7wQBF/3H/svigp1vnWEOu+AKL1Q2+h6b5gRRRv8zLovnhHrmGmxua+mEX2Ar1d5b4Qc1zbW/njviAc+yuVmuK+2BheeWdC4b5Az2kEeePfvvCs/C3RUt2+ICCli1TU2r5g34WWVGnYvoB8FnP3Eta+8BdVjjjS077QF1Rt6afRviC0jSxlKc++YAIJ9ygyy75gYROs0GrHvoAq777B08O+YEg6vxVtwL6A4YMTNm26vkAgCgyqX7S+AL1Qsu9frb4AH1lv8LeivgCgnzaog5G+AHCmyxYkUT4AWiIZ0mGSPgBMhSjGPqE+AEXTrkW9qD4AHi95RrivPgB+Ool9HrM+AKfOX/Qstj6AO0/ycA+5PgA3/UR9zrs+gNy76jpzvj7AYSvZqoPAPkDYCO14ysE+gPuCxEoTwz5AtQ7DhmPEPkAUALOmwMU+QOY52iUwxz5AlwZzbbfIPkCM6BHAW8o+QLUAnCQizD7AJbCCUQ/OPkBbWn7ME9A+QMyIdms30T4Aap2IMHTSPuAYTfh8y9M+4BM1cGM+1T6go+2ipM3WPsDIkoutedg+QH55PZdC2j5gyeIjKCjcPsC4d4nWKd4+8C7jHGYj4D5A2fGG9T7hPoA/DBvpZuI+oG3jC3Ka4z6g0hZNptjkPrDacuGDIOY+IEzzQ/Rw5z4wJA3gz8joPrB5IpDhJuo+AP0xGeqJ6z5wKMmbo/DsPiBaMfLEWe4+8Lbx8wTE7z6gCvrKDpfwPmBVyW9nS/E+mM8H1nD+8T6wFYYYla/yPtgBsiFFXvM+CGSkqvkJ9D4Q09gUNLL0Pjge/B1/VvU+IIbebW/29T74Wtj/o5H2PmB/22nGJ/c+EANZBIu49z7oOpj2sEP4PsA8BywCyfg+CJr2NlNI+T4Ay4klg8H5PkhfhE17NPo+CI1rEy+h+j5gEPewmwf7PpjHiv7HZ/s+eKqxQsTB+z6QTBEKqhX8PhhThAmcY/w+2ClzC8ar/D5YS4ToXO78PigJG4ueK/0+YM7++9Fj/T6wDKR1R5f9PuhEWXpYxv0+UG+O6Gfx/T5I3v0G4hj+PlC4bYE8Pf4+8BpDTfZe/j5AQTtsl37+PnjkooKwnP4+IDoiNtq5/j7geGpKtNb+PsCoXXLk8/4+ON17zhQS/z7opO8U8jH/PuArUWQpVP8+MHcAyGV5/z5wUph7TaL/PhByjwF/z/8+eHGoE8cAAD8weNWKgBwAP3B1f8cmOwA/RDYZPutcAD/4dibz9IEAP6RuNbpfqgA/eLzTvjvWAD+INYpajQUBP2B6RjZNOAE//EEosWhuAT/UIX6DwqcBPwwbVpIz5AE/CAQV54sjAj845J++k2UCP3A+o6QMqgI/7DkIkbLwAj/I2MP/PDkDPwRuCP1fgwM/VPnoIc3OAz/4/RB/NBsEP4hzqHRFaAQ/4GlLd6+1BD+Yde7CIgMFPzjXsPxQUAU/HFjpxO2cBT8A0rI6r+gFP5ibIHJOMwY/uH373Yd8Bj/M1d6tG8QGP1zhJyHOCQc/0P0bz2dNBz+oPXjktY4HP/BqplaKzQc/MJ6mDLwJCD90Ogn+JkMIP8hfLkiseQg/HCtYOjKtCD88ziFZpN0IP6A2NFrzCgk/PIcbGRU1CT8MrWaGBFwJP+RmKZLBfwk/kGkxE1GgCT/4HiCsvL0JP/i3nq8S2Ak//LbVBGbvCT/ElA0NzgMKP3T6T4tmFQo/fGmHjk8kCj94X2perTAKP4wVEmuoOgo/tMPSPm1CCj/M1mpxLEgKP6TIN5saTAo/dHuHRnBOCj8sL5XcaU8KP7z0M4tHTwo/TP18H01OCj+4JF3RwUwKP1ClWvvvSgo/yOaguSRJCj9EJlZrr0cKPwhbmBHhRgo/sOxMiAtHCj8QoFyWgEgKPyTOEtWQSwo/rLgVcYpQCj/EbdDKt1cKPxA81/9dYQo/kGGIarttCj90QXooBn0KP9y3Zbpqjwo/nC0p0QqlCj+MJ0la/L0KPwA2VNtI2go/MB7LJu35Cj+0JSVv2RwLP6BS77XxQgs/TFnsjg5sCz9MNdwp/pcLP7TMFZKFxgs/ZDuAEWL3Cz+EC5WkSioMPwjkym7xXgw/IESTIQWVDD8MUFxLMswMP5SueockBA0/",
+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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DE0AuLy9qhjYTQBPN3TNjKRNAXRHOsAMcE0BmdHMaaA4TQBPy1aqQABNA9kmLnH3yEkDdbroqL+QSQPD6H5Gl1RJAcHERDOHGEkCju37Y4bcSQI+L8jOoqBJA8a+RXDSZEkD/URmRhokSQC2S2xCfeRJAryy6G35pEkANBR7yI1kSQB3A7dSQSBJAkSKNBcU3EkBrbfbFwCYSQIZO5liEFRJAf9rlARAEEkBO1iQFZPIRQGjdU6eA4BFA9V+WLWbOEUDAHoLdFLwRQGSnIf2MqRFAQXz10s6WEUBt8/Ol2oMRQLAAiL2wcBFAJwqPYVFdEUC0R1bavEkRQBDIlnDzNRFAV/NvbfUhEUCdn18aww0RQPaLOMFc+RBA8kAerMLkEEDOyZcl9c8QQIS+u3j0uhBArhhJ8cClEEBK84vbWpAQQMpXNYTCehBALPNJOPhkEEC63CFF/E4QQJlfbfjOOBBABD85oHAiEED0lvGK4QsQQIK+xg5E6g9Aus56yWS8D0AzQiDlJY4PQGobmQGIXw9AnBuDv4swD0AVLC3AMQEPQLfPiKV60Q5AjeIfEmehDkC57i2p93AOQOCo8g4tQA5AuIn66AcPDkAvmADeiN0NQGGVm5Wwqw1AWeINuH95DUC7mz7u9kYNQGbSwOEWFA1ARDHaPODgDEDjBoeqU60MQAJOetZxeQxAqaEbbTtFDEDK8YIbsRAMQLbucY/T2wtABstJd6OmC0AeKP2BIXELQCnN+15OOwtAErYfvioFC0BXArRPt84KQJ1VtcT0lwpAStUiz+NgCkDpvfchhSkKQNh11nDZ8QlA/7DIb+G5CUBL/i3TnYEJQC/rvk8PSQlADueTmjYQCUDV4yhpFNcIQGjfXnGpnQhA9Xh7afZjCEC/KScI/CkIQOVzaQS77wdA7K+jFTS1B0DYK4fzZ3oHQGnCBlZXPwdAGNxG9QIEB0DHt56Ja8gGQDApz8uRjAZAy3ZedXZQBkBKMLNAGhQGQDbyzuh91wVA6xEIKaKaBUAvm/K8h10FQPsLZmAvIAVAZquHz5niBECEN9PGx6QEQBp8IAO6ZgRAH+elQXEoBEBpFvo/7ukDQOVYErwxqwNAQAg/dDxsA0BT1CMnDy0DQDquqpOq7QJAoh7yeA+uAkDerEaWPm4CQEULR6s4LgJAf9k7eP7tAUDBh0m+kK0BQLG3OD/wbAFA4g4kvR0sAUDdP1H6GesAQNhXLbnlqQBAhntSvIFoAEBpiozG7iYAQHtVtDVbyv8/MM/Y+H1G/z9d2EZdR8L+P4teFOq4Pf4/FyKgJtS4/T9sLX+amjP9P3YsYM0Nrvw/+hvoRi8o/D8rRpeOAKL7P3Kp9SuDG/s/wCkzp7iU+j+o7raJog36P8tG5l1Chvk/4Ph8rpn++D9XuS0Gqnb4Py8Klu907vc/lYdQ9ftl9z/OVAeiQN32P/g0g4BEVPY/OkyzGwnL9T/fI7L+j0H1P2Jjx7Tat/Q/85Nkyeot9D/gaB7IwaPzPwv9mjxhGfM/CsR2ssqO8j820yq1/wPyP8M6JtABefE/3kZYj9Lt8D86HuF/c2LwP0GbIWDMre8/8MuRXViW7j8HawgWjn7tP52ZcqdwZuw//GrRLwNO6z+gxFrNSDXqP80nkJ5EHOk/ZblHwvkC6D/DL6tXa+nmPxeoK36cz+U/9vRwVZC15D/7gDj9SZvjP3Y1JZXMgOI/cE15PBtm4T+QQcUROUvgPw+HvmVSYN4/NTNLe90p3D8ED72iGfPZP5/LLR4NvNc/jrb8ML6E1T+/XW8dM03TP3Dl2iNyFdE/61VOBQO7zT8SYA7tzkrJP90ZR3VU2sQ/GM5VEaBpwD8LbG1jfPG3P/oUtQ/tHq4/rNzxkh21mD8VUYq/waeFv4bt7g9fLqe/O3qFzkV5tL8S8h1aIlu9v8gNrkJWHsO/jM0T2eWOx79aaTKfM//Lv/X0RZ+ZN9C/UC0rL2xv0r9jeStUC6fUv5syheVw3ta/wWfGvJYV2b+gtHC1dkzbv2baqawKg92/WYL7gEy537/PexgJm/fgvyVDoKBgEuK/eXki+PMs479LX0QBUkfkv1raWK53YeW/NPOF8mF75r/qPAPCDZXnvy7ORBJ4rui/F4We2Z3H6b9IdQQOfODqvwgd46MP+eu/74aSjlUR7b/ki6jBSinuv0bjwjHsQO+/n1VVahss8L9zYJ/Qk7fwv/9MrMfdQvG/ZyLhy/fN8b/N1hpa4Fjyvyo/su+V4/K/8K2EChdu879wPf4oYvjzv071K8p1gvS/eFnVbVAM9b+tQ6CU8JX1v4rNMsBUH/a/D9Ujc3uo9r/F03YwYzH3v59i8noKuve/A+Uh1W9C+L97EPfBkcr4v1lmR8VuUvm/3vjpYwXa+b+T+asjVGH6vzkYPotZ6Pq/busmIhRv+78PfrpwgvX7v+j5FgCje/y/tlYiWnQB/b/vno0J9Yb9v0j+25kjDP6/2oVxl/6Q/r8mUq2PhBX/v7GJBRG0mf+/i/+B1cUOAMCwT+32hFAAwPBY1LQWkgDAJd0eV3rTAMCXXdAlrxQBwO69Tmm0VQHAD4N6aomWAcDXSqpyLdcBwBivoMufFwLAc2qEv99XAsBTZdyY7JcCwCuBjaLF1wLAf7TbJ2oXA8BP22x02VYDwMRMTtQSlgPAQvH+kxXVA8DRyH0A4RMEwPieXWd0UgTAyrrOFs+QBMA/oX1d8M4EwIJnPYrXDAXAA/DU64NKBcCBDTTR9IcFwIXNx4kpxQXA8UyiZSECBsCsqn612z4GwFQOu8pXewbAaW5S95S3BsCwE9qNkvMGwBfggOFPLwfAhE8QRsxqB8Aoz+4PB6YHwNlgJJT/4AfA/CthKLUbCMDNeAkjJ1YIwEGuRdtUkAjAnp8NqT3KCMA4OhLl4AMJwCgubOg9PQnAFGpQDFR2CcBwiyiqIq8JwOuN5Bup5wnAYFoqvOYfCsBHclvm2lcKwJoUivaEjwrAKJluSeTGCsBPOV88+P0KwKSVSi3ANAvAoci0ejtrC8DebLWDaaELwFul+KdJ1wvADsPCR9sMDMBIn/jDHUIMwHhiLX4QdwzA15aw2LKrDMDtNoM2BOAMwJ84FfsDFA3AolXuibFHDcDEvKxGDHsNwN2HVZUTrg3AYdeU2sbgDcBE7c57JRMOwMe+HN8uRQ7AmJVFa+J2DsCPrbuHP6gOwJlvnJxF2Q7A7FeyEvQJD8Dxn3lTSjoPwHB6JslHag/AIgCu3uuZD8Cv9dL/NckPwO0bOJkl+A/A3OI5DF0TEMDI2Al2eSoQwCSLtsFnQRDAxuQhpydYEMDEcFfeuG4QwL1Crx8bhRDAQrLzI06bEMBA8G6kUbEQwL4K6lolxxDAMKioAcncEMDlxWVTPPIQwEJ5UQt/BxHAZRkQ5ZAcEcAaCLqccTERwEFC3O4gRhHAjil6mJ5aEcBPpxBX6m4RwHgYnOgDgxHAme2fC+uWEcCSiSl/n6oRwIyqvQIhvhHAyncrVm/REcB+m285iuQRwI4rzGxx9xHACUbwsCQKEsAS/gnHoxwSwEF3xnDuLhLATpVMcARBEsBRjjiI5VISwFoBmXuRZBLASYntDQh2EsAyciYDSYcSwP6mpR9UmBLAu55AKCmpEsAaYUTix7kSwL79exMwyhLAl6I5gmHaEsCo8F31W+oSwLiRTjQf+hLAqEHQBqsJE8BTpeI0/xgTwGpJzoYbKBPAlQZQxf82E8DV9rO5q0UTwAPr2i0fVBPASyw47FliE8BWsc6/W3ATwBa4L3QkfhPArp161bOLE8C9u12wCZkTwBTLF9IlphPA/lZ6CAizE8BRXO0hsL8TwLDxdO0dzBPAaIK5OlHYE8A1jQ/aSeQTwAhtc5wH8BPAp5xoU4r7E8B94M3Q0QYUwLNy2+bdERTAMmtKaK4cFMCiy3MoQycUwB8/WPubMRTAqpyctbg7FMAn0oQsmUUUwN4l8DU9TxTAQr1WqKRYFMBRZ8haz2EUwEo47CS9ahTA+BwB321zFMBTvN9h4XsUwPtx/oYXhBTAw9p3KBCMFMCgxhIhy5MUwEdHQkxImxTAEIIMhoeiFMCl/dyqiKkUwN78dJdLsBTAupsNKdC2FMDrWn09Fr0UwCYhRrMdwxTAes2UaebIFMD62T1AcM4UwL4Quxe70xTAEwkr0cbYFMCF81FOk90UwGR1m3Eg4hTA3YsdHm7mFMB2lpw3fOoUwFZCkaJK7hTAwvMwRNnxFMCAJHgCKPUUwJEgMMQ2+BTAWI/fcAX7FMApHqDwk/0UwKisAyzi/xTAYM8tDPABFcDVuf16vQMVwGZvImNKBRXAAJAcsJYGFcBbmTpOogcVwDBwlSptCBXAc0AOM/cIFcDqf01WQAkVwJ/EwoNICRXAEFalqw8JFcAFrfW+lQgVwLdogK/aBxXAF4Tjb94GFcCX35XzoAUVwAm77C4iBBXArbkQF2ICFcCb0dWhYAAVwKZDlMUd/hTAH0ozeZn7FMBrylG00/gUwODaXm/M9RTAL92co4PyFMCEmBxL+e4UwDP6t2At6xTAumMO4B/nFMBSb4LF0OIUwDL0OA5A3hTA",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+         "yaxis": "y2"
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+         "line": {
+          "color": "rgba(120,255,210,0.95)",
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+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Uranus",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Uranus<extra></extra>",
+         "line": {
+          "color": "rgba(120,255,210,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Uranus",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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sH0D5cU0TFq0eQIr+IU+ELR5AEqZt85atHUAcg/xaTy0dQJMaP+yurBxA5h2fircrHEB4W/Ana6obQN2fs2/LKBtArbaC09mmGkCLawNIlyQaQFYnXekEohlA/uqjJCQfGUB0x/Ok9psYQFb943J+GBhA03tHQr2UF0CTG0eJtBAXQMWga6hljBZAAQQ85dEHFkBB3Ujx+oIVQEbi5ofi/RRAalF+R4p4FEC6Izqm8/ITQHZJ1qsfbRNAqAzMmQ/nEkAbj3v5xGASQEWyZKFB2hFARm/2vIdTEUAittsImcwQQGJ4FfF2RRBAb2GDRUV8D0C58uNjOm0OQBiuHWDQXQ1ADGmRnApODEC4dkuo7D0LQJWYhd15LQpAJ4Gux7QcCUC2Z+ZOoAsIQIsMtI4/+gZAJP+YFpboBUDwu4fxp9YEQJHbrk54xANArZ6J5QmyAkCHSd7kXp8BQFKLind5jABAajIBxrny/j/tH7eeGcz8P5JXi6sapfo/Q4CqdMR9+D9xreGCHFb2P14uAnIoLvQ/+lyTme0F8j/1OdDM5LrvP0BYj+58aes/IaOCoLAX5z+Mfi8ujMXiP9fJV3Az5tw/+lw7ncdA1D/JoJhp5DXHP7BIMLqVpqc/RgVhpNDFtr+EvZBVia/MvwiOOZsJ/ta/Kgo7Cy6k3793Z90QDyXkv35gvLTfd+i/LtVjqnjK7L+/EtRHZY7wv3+LnQJjt/K/hsH2QS/g9L/ZGKLXwwj3vyG0EE4ZMfm/A7Y7AihZ+79HMCNU54D9vzL2BsdPqP+/2TMQv63nAMA0QRREAvsBwECtDo0iDgPApiXkqgohBMB4b/TrtTMFwJHkpLwfRgbADKv8sENYB8B4oWt2HmoIwB/ndPWsewnAqrfbquuMCsB822/Z1p0LwFNIFfhprgzANwJD4KC+DcB7aIXyd84OwKno5ozr3Q/Aq2M9G3x2EMDyPFLCzP0QwMRa2U7lhBHAB2MobMMLEsD0SLjoZJISwNebkCrIGBPAEiRipuueE8DqbVqfzSQUwFpLMh9sqhTAhnwCrMQvFcACcZ/w1LQVwCQUT8+aORbAf9OMVRS+FsBkhVrSP0IXwGux7TwbxhfAz9fDbqRJGMCJpSw72cwYwJa7cYO3TxnANK2TrT3SGcCWtu4YalQawChp5vw61hrAHvxlSK5XG8CPk6NpwdgbwBMAeQdyWRzA3uvZD77ZHMBPW5DMo1kdwJhuktYh2R3ARrc4ajZYHsCvlTmb39YewEm9ZEYbVR/AXrFMQOfSH8DBc1/oICggwMEESpyUZiDAdpXd3M2kIMBSmRqyy+IgwKIYOvSMICHATboKnRBeIcBN2lnAVZshwDRlXKJb2CHAT8BgpCEVIsD4u4/yplEiwLTWaZ7qjSLAkmYli+vJIsBMyHWYqAUjwFG7vOQgQSPAUOx8nVN8I8AFNKgMQLcjwGAaWWfl8SPAiUwvs0IsJMCrojkHV2YkwJ0UXX8hoCTAPGqmZaHZJMAPSRcY1hIlwIN/1sK+SyXAZHb6fVqEJcClqZg0qLwlwCPL5N+m9CXAYgo4vlUsJsDX9wEltGMmwOTlBozBmibAjMu8SH3RJsBCXAl65gcnwCZYOjz8PSfAtEdFn71zJ8DhFV3lKaknwHdSZ2lA3ifAlXqpbAATKMCP0lovaUcowBvONMd5eyjAveBhWjGvKMDo1i1Ej+IowOzK7PCSFSnAgpL07DtIKcDMOSmWiXopwCeVBxR7rCnAPcokgQ/eKcCI4NfsRQ8qwDdLmqwdQCrA51FmPJZwKsDCFNwSr6AqwOwzyaRn0CrA5NgTLb//KsDhcSPrtC4rwMyScTxIXSvAaIwPi3iLK8C4HF1iRbkrwFaToCCu5ivASF7FALITLMA3iKA2UEAswDm6I/OHbCzAMLtmtFiYLMBxUaAYwsMswKbTG7zD7izAfvUwLV0ZLcB7gBCxjUMtwBG0K4dUbS3A0mKS/LCWLcDKvk11or8twKoG5Ico6C3A9YAVr0IQLsA2hSdW8DcuwCUwSNgwXy7Af3+RggOGLsDaCA7iZ6wuwLZLsJRd0i7AMODYOOT3LsDLZKVV+xwvwBBwPyaiQS/A4b3j5NdlL8BUrSLbm4kvwDZhBIDtrC/Ap72xiMzPL8D+PZ2ROPIvwKPj8pMYCjDAg0tV2doaMMD2rV2+YiswwLG/7wCwOzDAP64VY8JLMMBg70eumVswwLLTsqQ1azDAEqXA65V6MMB5ITwuuokwwAhEihuimDDA6Wh8e02nMMDi1WEwvLUwwBlaXQ3uwzDAaWBJ3OLRMMDJnAVLmt8wwNsCT/cT7TDA8b0Ilk/6MMDvRGrmTAcxwGPRdL4LFDHAVQRv84sgMcCrM/NCzSwxwKz6qmvPODHAr2MZJpJEMcA2m05AFVAxwEXD5ZxYWzHAHdmiD1xmMcCy2rFlH3ExwKYM/E+iezHAPUmTd+SFMcAFLXyg5Y8xwHk9eZ6lmTHApB84YiSjMcBR5MvXYawxwAyaM9JdtTHAsu4WHRi+McBSbtJzkMYxwHDeDKbGzjHA3GLYlrrWMcBXXpAkbN4xwGm1SzLb5THAipgQjAftMcCrXzn78PMxwEbUW12X+jHAaqSPm/oAMsCgMlm6GgcywG3IiLP3DDLAaAX3Z5ESMsCyC2Cr5xcywGvUXj76HDLA3uhr/MghMsCPlYjaUyYywKZqtNWaKjLAUfIJ9J0uMsCtsVogXTIywHwArT7YNTLAPa27Og85MsBmm7IGAjwywFzWB6+wPjLA4qViNBtBMsDBSyKHQUMywO8dR44jRTLAgGIVI8FGMsApkNk+GkgywGoOTfIuSTLAx/HpWP9JMsBthMqSi0oywF1pCp7TSjLANyxLbddKMsCd0zXwlkoywNLoXh0SSjLAqsBhC0lJMsATCprNO0gywIMPzXTqRjLAr9gFCVVFMsA4H8mBe0MywEjeQPBdQTLAddTWc/w+MsC47D43VzwywLF8hmVuOTLAnOn0BUI2MsAXow8W0jIywLIXFo8eLzLAbOqyeicrMsCP+9YJ7SYywCtWdm5vIjLAUrRc264dMsBsiu1xqxgywNWwBjxlEzLAGgUKVNwNMsAmX63aEAgywBWQJQADAjLAyKNz97L7McBLRLLYIPUxwKh6rbpM7jHAPz8qrzbnMcB8NKHa3t8xwPBTNYRF2DHAUxDb8GrQMcA7u4VlT8gxwLfURA3zvzHAZ/dN+FW3McATikZCeK4xwKr8xw1apTHAuvDDmfubMcBx+K4vXZIxwBPLGQZ/iDHAox0/UWF+McDJi6U1BHQxwKBBJ+VnaTHAqI1cq4xeMcBxk2DPclMxwKUDaZkaSDHAwVJtNYQ8McCAA8e6rzAxwEx0pU6dJDHA5vuAIU0YMcAwr1yHvwsxwLLPZtz0/jDA916aae3xMMCV7H1uqeQwwKl6vw8p1zDA/EjbemzJMMA0rA7xc7swwPCzmLQ/rTDAF9+OEtCeMMD7lwJCJZAwwFwHpG0/gTDAYwMsyR5yMMAvByqOw2IwwOUwEhcuUzDAIqfOv15DMMD0fS3RVTMwwDbZ9YQTIzDA0d0H9ZcSMMDQafFG4wEwwCAL6G3r4S/AQMpWHp+/L8BcxZpZ4pwvwC8hqa21eS/ATeIXjhlWL8DeCStpDjIvwG16haqUDS/AJ5tM+azoLsAQDiz5V8MuwHsvpDWWnS7Ae73IImh3LsDHLYgAzlAuwGISyTPIKS7AUjcmTVcCLsAY9DABfNotwEfAMSY3si3AVv8EXImJLcAGl8Mic2AtwA+mjt/0Ni3An4HS7g4NLcDVd37sweIswNrA5X0OuCzASFVbT/WMLMBS/NwAd2EswJY93AGUNSzAUBjt3kwJLMDJe288otwrwAZGnuGUryvA35TyriWCK8CA7wVKVVQrwHTLHjskJivAGrfa6JL3KsCtQmi+ocgqwOjAPHRRmSrAPbep2KJpKsAyQKTPljkqwMbdZCYuCSrAmKRGb2nYKcAwq/RHSacpwDqmk1DOdSnAlWwrTvlDKcCB9/QeyxEpwBfh5XRE3yjAvtjA+GWsKMAzpSo2MHkowArbZsajRSjA1MDriMERKMAZPbBsit0nwIaHg3b/qCfAGVhhhSF0J8BJ1MU28T4nwDBt5yVvCSfApG7s55vTJsCC8ClJeJ0mwCqWoz4FZybA9vGap0MwJsD7JcliNPklwJq6aCPYwSXADoqaoC+KJcBC4OHCO1IlwBfC2Xn9GSXAKXglzHXhJMBuK1OUpagkwEkUOXaNbyTAty7/Fy42JMCdf/ohiPwjwOoLnIWcwiPALuX0XWyII8BEqru0+E0jwN30NopCEyPA7VfonkrYIsDGNlOsEZ0iwEAro4qYYSLAcYeMG+AlIsCuwGhn6ekhwCJAFFi1rSHAzeqcuERxIcASh9dVmDQhwB3ezvaw9yDA79wspo+6IMChEeWJNX0gwH5G6LajPyDAqaxTL9sBIMByYflTuYcfwAmqia9RCx/AcZIxDYGOHsAJMEdHSREewLOIwq+skx3A6bzqaK0VHcA3TfdhTZccwC10w2SOGBzAu9cUC3KZG8DGfBdd+hkbwLfNP38pmhrA",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Neptune<extra></extra>",
+         "line": {
+          "color": "rgba(185,120,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Neptune",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Neptune<extra></extra>",
+         "line": {
+          "color": "rgba(185,120,255,0.95)",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Neptune",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 1.4071<br>i: 29.34°<br>Ω: 73.56°<br>ω: 349.22°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 1.4071<br>i: 29.34°<br>Ω: 73.56°<br>ω: 349.22°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 5.7201<br>i: 45.58°<br>Ω: 233.47°<br>ω: 173.28°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 5.7201<br>i: 45.58°<br>Ω: 233.47°<br>ω: 173.28°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
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+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+        },
+        {
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+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 5.0662<br>i: 33.28°<br>Ω: 287.07°<br>ω: 170.76°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 5.0662<br>i: 33.28°<br>Ω: 287.07°<br>ω: 170.76°<extra></extra>",
+         "line": {
+          "color": "rgba(144,167,209,0.7)",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+         "title": {
+          "text": "X [AU]"
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+         "anchor": "x",
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+         "gridcolor": "rgba(255,255,255,0.08)",
+         "scaleanchor": "x",
+         "scaleratio": 1,
+         "showgrid": true,
+         "title": {
+          "text": "Y [AU]"
+         }
+        },
+        "yaxis2": {
+         "anchor": "x2",
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+         "title": {
+          "text": "Z [AU]"
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+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# --- toy dataset: 5 example hyperbolic orbits ---\n",
+    "rng = np.random.default_rng(24601)\n",
+    "N = 5\n",
+    "dtype = [\n",
+    "    (\"ObjID\", \"U32\"),\n",
+    "    (\"epochMJD_TDB\", \"f8\"),\n",
+    "    (\"q\", \"f8\"),\n",
+    "    (\"e\", \"f8\"),\n",
+    "    (\"inc\", \"f8\"),\n",
+    "    (\"argPeri\", \"f8\"),\n",
+    "    (\"node\", \"f8\"),\n",
+    "    (\"t_p_MJD_TDB\", \"f8\")\n",
+    "]\n",
+    "\n",
+    "orbits = np.zeros(N, dtype=dtype)\n",
+    "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
+    "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
+    "orbits[\"q\"] = rng.uniform(1.5, 12.0, size=N)\n",
+    "orbits[\"e\"] = np.clip(rng.normal(5.0, 2.5, size=N), 1.0, 10.0) # <-- keep it hyperbolic now\n",
+    "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
+    "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"t_p_MJD_TDB\"] = float(58000.0)\n",
+    "\n",
+    "# --- build lines again, but set a maximum render distance of 60 au ---\n",
+    "conic_cache, lines_cache, sunpos_cache, pos_cache = prepopulate_orbit_variants(\n",
+    "    orbits,\n",
+    "    orbit_format=\"COM\",\n",
+    "    input_plane=\"ecliptic\",\n",
+    "    input_origin=\"heliocentric\",\n",
+    ")\n",
+    "\n",
+    "planet_names = [\"Mercury\", \"Venus\", \"Earth\", \"Mars\", \"Jupiter\", \"Saturn\", \"Uranus\", \"Neptune\"]\n",
+    "planet_lines_cache, planet_id = build_planet_lines_cache(\n",
+    "    ephem,\n",
+    "    epochJD_center,\n",
+    "    planet_names=planet_names,\n",
+    "    n_points=900,\n",
+    ")\n",
+    "\n",
+    "key = (\"helio\", \"ecl\")\n",
+    "conic = conic_cache[key]\n",
+    "orbit_pos = pos_cache[key]\n",
+    "sun_xyz = sunpos_cache[key]\n",
+    "\n",
+    "lines = conic_lines_from_classical_conic(conic, n_points=400, r_max=60)\n",
+    "\n",
+    "# --- draw 2d plot ---\n",
+    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[('helio',\"ecl\")], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "95d55183",
+   "metadata": {},
+   "source": [
+    "Or again, equivalently in 3D"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "fce96344",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
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+         "hoverinfo": "skip",
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+         "showscale": false,
+         "surfacecolor": {
+          "bdata": "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               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+          "dtype": "f8",
+          "shape": "40, 40"
+         },
+         "type": "surface",
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",
+          "dtype": "f8",
+          "shape": "40, 40"
+         },
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",
+          "dtype": "f8",
+          "shape": "40, 40"
+         },
+         "z": {
+          "bdata": "                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                ",
+          "dtype": "f8",
+          "shape": "40, 40"
+         }
+        },
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "rgba(190,190,190,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "rgba(255,190,90,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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",
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+         }
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "rgba(90,210,255,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "rgba(255,90,90,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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",
+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "rgba(255,165,120,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter3d",
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+         },
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",
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+         },
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+         }
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "rgba(255,230,150,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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",
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+         },
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",
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+         },
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+         },
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+         }
+        },
+        {
+         "hovertemplate": "Neptune<extra></extra>",
+         "line": {
+          "color": "rgba(185,120,255,0.95)",
+          "width": 5
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Neptune",
+         "showlegend": false,
+         "type": "scatter3d",
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",
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+         },
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",
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+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 1.4071<br>i: 29.34°<br>Ω: 73.56°<br>ω: 349.22°<extra></extra>",
+         "line": {
+          "color": "rgba(144, 167, 209, 0.7)",
+          "width": 3
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
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+         "meta": {
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+         "meta": {
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+          "dtype": "f8"
+         }
+        },
+        {
+         "customdata": [
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ],
+          [
+           "61000.00000",
+           "2025 Nov 2"
+          ]
+         ],
+         "hovertemplate": "%{text}<br>@ MJD %{customdata[0]}<br>(%{customdata[1]})<extra></extra>",
+         "marker": {
+          "color": "rgba(255,255,255,0.9)",
+          "size": 3.5
+         },
+         "meta": {
+          "kind": "epoch"
+         },
+         "mode": "markers",
+         "showlegend": false,
+         "text": [
+          "Obj-00",
+          "Obj-01",
+          "Obj-02",
+          "Obj-03",
+          "Obj-04"
+         ],
+         "type": "scatter3d",
+         "x": {
+          "bdata": "JhFoF7dJMsAT79OPfg86wO22Zmc8NzvAyywTiEP/PMAEajTMYOpCwA==",
+          "dtype": "f8"
+         },
+         "y": {
+          "bdata": "PD63nBBuFkB4kApNpBwoQOKoRleZ/jdAVLiQb91JN0D9CZaIoeEXwA==",
+          "dtype": "f8"
+         },
+         "z": {
+          "bdata": "MUHuYgaBJUBFOzWWbW3aPwkJaKJycULAT54tLQBkLsAX7z8lJ+I4wA==",
+          "dtype": "f8"
+         }
+        },
+        {
+         "hovertext": "Sun",
+         "marker": {
+          "color": "yellow",
+          "size": 6
+         },
+         "mode": "markers",
+         "showlegend": false,
+         "type": "scatter3d",
+         "x": [
+          0
+         ],
+         "y": [
+          0
+         ],
+         "z": [
+          0
+         ]
+        }
+       ],
+       "layout": {
+        "autosize": true,
+        "font": {
+         "color": "white"
+        },
+        "margin": {
+         "b": 0,
+         "l": 0,
+         "r": 0,
+         "t": 40
+        },
+        "paper_bgcolor": "rgba(0,0,0,0)",
+        "plot_bgcolor": "rgba(0,0,0,0)",
+        "scene": {
+         "aspectmode": "data",
+         "camera": {
+          "center": {
+           "x": 0,
+           "y": 0,
+           "z": -0.25
+          }
+         },
+         "xaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "X [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         },
+         "yaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "Y [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         },
+         "zaxis": {
+          "gridcolor": "rgba(255, 255, 255, 0.02)",
+          "showbackground": false,
+          "title": {
+           "text": "Z [AU]"
+          },
+          "zerolinecolor": "rgba(255, 255, 255, 0.4)"
+         }
+        },
+        "template": {}
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig3d = plotly_3D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, show_plane=True, return_fig=True)\n",
+    "fig3d"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0b154ba2",
+   "metadata": {},
+   "source": [
+    "## 6) (Optional) Altering the look of the figure\n",
+    "Layup Visualize supplies a default figure look via some internal CSS styling. Some users may have their own artistic idea in mind however for how they want orbits to look, so we give an example below on how you can use Plotly's inbuilt methods to update and decorate your plots to your hearts content. Have a look at [the Plotly documentation](https://plotly.com/python/reference/) for more information on what you can change and how to do it"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "88f60be7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.plotly.v1+json": {
+       "config": {
+        "plotlyServerURL": "https://plot.ly"
+       },
+       "data": [
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mercury<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mercury",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Venus<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Venus",
+         "showlegend": false,
+         "type": "scatter",
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",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Earth<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Earth",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+          "dtype": "f8"
+         },
+         "xaxis": "x",
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Mars<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Mars",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Jupiter<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Jupiter",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Saturn<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Saturn",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Uranus<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Uranus",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Uranus<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Uranus",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
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+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Neptune<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Neptune",
+         "showlegend": false,
+         "type": "scatter",
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",
+          "dtype": "f8"
+         },
+         "xaxis": "x",
+         "y": {
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fEUCLKyd8YPURQMBQFKr1yhJAjSIdKFSgE0BsKwPwd3UUQOFtIV1dShVA2reNAwUfFkC71/PsbfMWQGZ7lxeUxxdA8b1fX3WbGEBT7EEQEG8ZQEPP/oNgQhpAAXF9GmUVG0DoSrjAHegbQKW9Xn6GuhxAyal5QZqMHUAI5e+uV14eQCeakx+9Lx9AEo9ZP2MAIEAHzgmxuGggQG4XBpLd0CBAUgSQCc84IUCHaa1Ji6AhQH52gw4SCCJAdSBcaWFvIkDOGB5WdtYiQKPcYSJPPSNA27jfFuqjI0APMZu2RAokQOT8CqRdcCRAcnRjkTPWJECI4MVIwzslQK4RuRkKoSVAlVgtSgcGJkD4xvs9uWomQBuCyF0dzyZA5rOeLjIzJ0CrsvHd9ZYnQNLXHL1l+idA3qc3xIBdKED5mPuwRsAoQPMOdEe1IilAHWJpIcqEKUDETcuUhOYpQD58GKzjRypAnhGI1eWoKkArwCKkigkrQExFqSrRaStAGbQbC7fJK0A0Jk9fOyksQEYJjLBeiCxAEGtk7B/nLED193l7fUUtQNlD5gJ3oy1AKpSWlgsBLkClUNnfOV4uQCG6XiACuy5A8dE3XGQXL0AthsyWXnMvQKtYjorvzi9A81IAzQsVMEB5n68ca0IwQCXYqy2VbzBAWLiH+4mcMEAEvk4ISckwQEvdrW/R9TBAsaVlPiMiMUDRq0m0Pk4xQOKODA4jejFAO3VAmc+lMUCUVWtDRNExQHwS+5iA/DFAFzuaFYQnMkDehmndTlIyQFP4oZHgfDJAI6LqCjinMkCM1rHlVNEyQKHUE0s3+zJA3vEQnN4kM0AxDJ4iSk4zQF1rmJd5dzNAuEosJmygM0C6rILtIMkzQEgUb/KX8TNAVJ+X5dAZNEClJwt9ykE0QCtEfd2DaTRA9MP5tPyQNECmXYYpNLg0QGEut2gp3zRA0pxzGtwFNUCIVp4qSyw1QBmN+Sd1UjVAd/MDqll4NUB6UItk+J01QKcNhSJQwzVAUsf54V/oNUCQR6gDJw02QAbMS22kMTZA7GS0RtdVNkCfKa1xv3k2QPTsKSdcnTZA2Yb6/avANkBCegtsruM2QExSOUxjBjdAouib2ckoN0C+5pKI4Uo3QEJUDyWqbDdApucewiKON0Cjj5KaSq83QJz/MfYh0DdAKEB5wKjwN0BpaEEX3hA4QJA9o6DBMDhAEp1VVFNQOEATpsO7km84QIJa1r9/jjhASUr9sBqtOEBjMeT7Yss4QKUh99dX6ThAW4ECjvkGOUCVw8BfSCQ5QMhNU9NDQTlAr9VVz+tdOUDVlOpdQHo5QFIc1OhAljlA6JpdU+2xOUAT02U4Rs05QPhEjWRL6DlA3BbUFPwCOkDDnqBOWB06QDgoizlgNzpAx/qfgxNROkC/bmpDcmo6QPFl+KV8gzpA0xY98jGcOkBvtVe3kbQ6QArL3X+czDpAilxTTlLkOkAdC5p6svs6QF0U6ei8EjtARLt1eHEpO0AU7qOSzz87QOxzKz3XVTtAU6FeyYhrO0CL+uyD44A7QITY+5PmlTtAc2BpDJKqO0BwHnDP5b47QKnYPDnh0jtAwObdFoTmO0AjmeoHzvk7QIrw0/a9DDxAsct4e1MfPEBeunjQjjE8QE0p3UhvQzxA5OMd1PNUPEAL0oUWHGY8QCRRg47ndjxAbCo0aFWHPECdf/5wZZc8QFxpKmYXpzxAFM4iE2q2PECrhp+qXMU8QOzQaUrv0zxAGyn7jyHiPEA//A678u88QF4Fdppi/TxAW30EtXAKPUAoIhY8HBc9QGxqVUplIz1AUQ6bMkwvPUBZ0MNI0Do9QKF0LfXwRT1AyBkKeK5QPUALM8vLCFs9QCag/rf/ZD1AYk7EnpNuPUAUhFyHxHc9QGSTNciRgD1A5bSQjPuIPUBydaSWApE9QIErB9emmD1Ar6/XGOifPUBZB8y5xqY9QMsajrhCrT1ACZ3iAVyzPUASpolUE7k9QC73vyZpvj1Ag3V5+FzDPUB6MZ3J7sc9QEpHZFQfzD1AzZ21xe7PPUBaxCIqXdM9QNoy9A1r1j1AVXR1bRjZPUAHlGL0ZNs9QEehC1BR3T1AITN/Pd7ePUC5V2F/C+A9QFGUdv/Y4D1AhrlIMUfhPUBpAQUaVuE9QBHBYtQF4T1AdB05F1fgPUD626T0Sd89QEHJ49Dd3T1A0Ujx8xLcPUBJQO8L6tk9QIDdhfZi1z1ANjl2l33UPUBHDy0zOtE9QH3lCm+YzT1AuJN4AJjJPUBgjtOBOcU9QMBtBhp9wD1AcX+YC2K7PUAqeqEc6LU9QDlueoIPsD1A7ERA6depPUBcEn0mQaM9QOx6AG9LnD1ACSEsJ/aUPUAs3s59QI09QHGXlrsqhT1AgHnhGbV8PUCrlTn23nM9QCt85wCoaj1A4E9HPhBhPUDkq0IwF1c9QOmZare8TD1AQtJMXQFCPUBt6Rvu5DY9QOZ/LbJmKz1Auztf3IYfPUARjQTjRRM9QLxV26ijBj1AjUocZqD5PEB0XUqKPOw8QNBuRsV33jxA2tGzFVLQPEDWz5F8zME8QNn1D3LnsjxA6MpsuaKjPEDD/syy/pM8QPKWSPf7gzxAVA9+rppzPEC2akR522I8QK+rNEe/UTxANArBHUZAPEBUnynrby48QGaH4qc9HDxAJdieH7AJPEA1A8N7x/Y7QF3wuFWE4ztAxzhbR+fPO0CsPwNQ8Ls7QPE1oQ6gpztA+vB7wPeSO0BW7mi59307QIj/P+CfaDtAu/2e6/BSO0DKVteT6zw7QAF+fx2QJjtAz7a5Sd8PO0AUsB/T2fg6QHJJDpR/4TpApGMDzNDJOkBzAz2jzrE6QA6zfKB5mTpAzcFLxNGAOkBOTIyZ12c6QDnmJIKLTjpA8ZPMeO00OkBbQNox/ho6QBfycYa+ADpAoQZgQC7mOUDqhS4qTcs5QJ+0pPcbsDlAdLTnDZuUOUDOInNfyng5QAFAOFiqXDlAQXqFGDtAOUDbTjAafCM5QEtNP5ttBjlAnVfIXhDpOECuX1k3ZMs4QLuDYb1orThAZAGUMx6POEDzXZSfhHA4QEHiltGbUThAJzraTWQyOEAHyQFc3hI4QDJNUFkJ8zdA+jcDMOXSN0AvOYamcrI3QM0SYuqxkTdAf97+6KJwN0D6pbAdRk83QNr8iaibLTdAL8gda6MLN0DrLco6Xuk2QD9zS/zMxjZA4y0Ame+jNkAQZvEvxoA2QK18Mp9RXTZAjrXEapI5NkCFOj0DiRU2QD5PK3Q28TVAKryFRZvMNUB2MRVmt6c1QNa2I7SLgjVA/5xrgxldNUBCDDJDYTc1QLNYultjETVAUT9suiDrNEAqOVrhmcQ0QEJ521bPnTRAfiGcccJ2NECu7NsbdE80QOgBu2LkJzRAH82T7BMANEBpZS73A9gzQJvGICW1rzNAtIlbGyiHM0AsVeHuXV4zQKiAvwdXNTNA9eccnhMMM0CQzaH4lOIyQAbLe0fcuDJAn0XAwumOMkBAcRXpvWQyQIId96xZOjJAZkxlib0PMkAK1Uwh6uQxQDu3BqbguTFAlVUniaGOMUCbpFqyLGMxQPZZ7/WCNzFAPJxfZ6ULMUAMmE5NlN8wQPJ0JRpQszBAI1Rxg9mGMEBWvIuOMFowQDJdenBVLTBA+/yJQEkAMEAB3Qb7GKYvQFoazKo9Sy9AnnA6IgHwLkAy7QyhZJQuQFXvh1hoOC5AG9oR/QzcLUB54BDaU38tQHwvPoE8Ii1A9p1YZ8bELEASkf0l82YsQPavMvLDCCxAkZfLdTiqK0Aik30+UUsrQMPGPDsP7CpAxYwmWnKMKkAcZNCLeywqQEmPgPkszClAUG2nE4drKUDrW458iQopQOhv1rk1qShAHAgooI1HKEA/gY3qkeUnQAsqiCNEgydAnrTcB6YgJ0CT8aHbt70mQFSFXcZ6WiZAt+t/xfH2JUBb/1qGHpMlQLc1EocBLyVAb/P9k5zKJEA8iU6Z8WUkQA6zMrUBASRAciWbLM+bI0AvGomsXDYjQHxz4eiq0CJAd2Rxs7pqIkD1s67njgQiQDCWtdIpniFAgFOYlIw3IUCwJfU9udAgQALqdp6xaSBACt9jdXYCIEDAa4veEzYfQL7yv2LeZh5A5fMa2U6XHUDoeh+aZsccQAP7QjEq9xtACWXBop0mG0Bshc1ow1UaQIIKMi+ghBlAdPnD9TezGECtjCk1i+EXQGzltImcDxdAGfN33nE9FkBgtCpGDmsVQEZdlBRzmBRA9athz6PFE0DA3RLuovISQF46H65xHxJAMQL+RhRMEUD5Jz3hjngQQK9dfsrCSQ9AI4j84RiiDUCs8EvcJ/oLQGw70Dn0UQpAwxHWw3+pCEBhvalt0AAHQCMD9rnoVwVA/7KOeMauA0A+zYlXbgUCQPwmxzPoWwBAE/6uOWhk/T8rc7GQohD6P8OhGf+HvPY/XCqGPBxo8z+F2HWRYRPwP+vU3vPKfOk/WCYcQF/S4j8ogLUB6U7YP2qjqSRV8MU/KT04E9X5or+33MFKXW7Pv4E21e+gD92/7ewJ4S405b+rFJUiqODrv6ZCUCObRvG/",
+          "dtype": "f8"
+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Neptune<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 2.2
+         },
+         "meta": {
+          "kind": "Planet"
+         },
+         "mode": "lines",
+         "name": "Neptune",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
+          "bdata": 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",
+          "dtype": "f8"
+         },
+         "xaxis": "x2",
+         "y": {
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",
+          "dtype": "f8"
+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 1.4071<br>i: 29.34°<br>Ω: 73.56°<br>ω: 349.22°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
+         "x": {
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-00<br>e: 1.4071<br>i: 29.34°<br>Ω: 73.56°<br>ω: 349.22°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-00",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 2.8163<br>i: 7.13°<br>Ω: 341.77°<br>ω: 87.69°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-01<br>e: 2.8163<br>i: 7.13°<br>Ω: 341.77°<br>ω: 87.69°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-01",
+         "showlegend": false,
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+         },
+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 5.7201<br>i: 45.58°<br>Ω: 233.47°<br>ω: 173.28°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-02<br>e: 5.7201<br>i: 45.58°<br>Ω: 233.47°<br>ω: 173.28°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-02",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
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+         "hovertemplate": "Obj-03<br>e: 2.9019<br>i: 54.22°<br>Ω: 304.11°<br>ω: 105.26°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+        },
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+         "line": {
+          "color": "red",
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+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-03",
+         "showlegend": false,
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+         "yaxis": "y2"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 5.0662<br>i: 33.28°<br>Ω: 287.07°<br>ω: 170.76°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
+         "type": "scatter",
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+         },
+         "yaxis": "y"
+        },
+        {
+         "hovertemplate": "Obj-04<br>e: 5.0662<br>i: 33.28°<br>Ω: 287.07°<br>ω: 170.76°<extra></extra>",
+         "line": {
+          "color": "red",
+          "width": 1.5
+         },
+         "meta": {
+          "kind": "Hyperbolic"
+         },
+         "mode": "lines",
+         "name": "Obj-04",
+         "showlegend": false,
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+              "color": "#EBF0F8"
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+              "color": "white"
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+              "color": "white"
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+            "type": "table"
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+          ]
+         },
+         "layout": {
+          "annotationdefaults": {
+           "arrowcolor": "#2a3f5f",
+           "arrowhead": 0,
+           "arrowwidth": 1
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+          "autotypenumbers": "strict",
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+            "outlinewidth": 0,
+            "ticks": ""
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+          },
+          "colorscale": {
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+             "#c51b7d"
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+             "#de77ae"
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+            [
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+            [
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+             "#bd3786"
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+             "#ed7953"
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+             "#fb9f3a"
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+             "#fdca26"
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+             1,
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+           ]
+          },
+          "colorway": [
+           "#636efa",
+           "#EF553B",
+           "#00cc96",
+           "#ab63fa",
+           "#FFA15A",
+           "#19d3f3",
+           "#FF6692",
+           "#B6E880",
+           "#FF97FF",
+           "#FECB52"
+          ],
+          "font": {
+           "color": "#2a3f5f"
+          },
+          "geo": {
+           "bgcolor": "white",
+           "lakecolor": "white",
+           "landcolor": "#E5ECF6",
+           "showlakes": true,
+           "showland": true,
+           "subunitcolor": "white"
+          },
+          "hoverlabel": {
+           "align": "left"
+          },
+          "hovermode": "closest",
+          "mapbox": {
+           "style": "light"
+          },
+          "paper_bgcolor": "white",
+          "plot_bgcolor": "#E5ECF6",
+          "polar": {
+           "angularaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "radialaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "scene": {
+           "xaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "yaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           },
+           "zaxis": {
+            "backgroundcolor": "#E5ECF6",
+            "gridcolor": "white",
+            "gridwidth": 2,
+            "linecolor": "white",
+            "showbackground": true,
+            "ticks": "",
+            "zerolinecolor": "white"
+           }
+          },
+          "shapedefaults": {
+           "line": {
+            "color": "#2a3f5f"
+           }
+          },
+          "ternary": {
+           "aaxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "baxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           },
+           "bgcolor": "#E5ECF6",
+           "caxis": {
+            "gridcolor": "white",
+            "linecolor": "white",
+            "ticks": ""
+           }
+          },
+          "title": {
+           "x": 0.05
+          },
+          "xaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          },
+          "yaxis": {
+           "automargin": true,
+           "gridcolor": "white",
+           "linecolor": "white",
+           "ticks": "",
+           "title": {
+            "standoff": 15
+           },
+           "zerolinecolor": "white",
+           "zerolinewidth": 2
+          }
+         }
+        },
+        "xaxis": {
+         "anchor": "y",
+         "domain": [
+          0,
+          0.45
+         ],
+         "gridcolor": "lightgray",
+         "linecolor": "black",
+         "mirror": true,
+         "showgrid": true,
+         "showline": true,
+         "tickfont": {
+          "color": "black"
+         },
+         "title": {
+          "text": "X [AU]"
+         },
+         "zeroline": false
+        },
+        "xaxis2": {
+         "anchor": "y2",
+         "domain": [
+          0.55,
+          1
+         ],
+         "gridcolor": "lightgray",
+         "linecolor": "black",
+         "mirror": true,
+         "showgrid": true,
+         "showline": true,
+         "tickfont": {
+          "color": "black"
+         },
+         "title": {
+          "text": "X [AU]"
+         },
+         "zeroline": false
+        },
+        "yaxis": {
+         "anchor": "x",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "lightgray",
+         "linecolor": "black",
+         "mirror": true,
+         "scaleanchor": "x",
+         "scaleratio": 1,
+         "showgrid": true,
+         "showline": true,
+         "tickfont": {
+          "color": "black"
+         },
+         "title": {
+          "text": "Y [AU]"
+         },
+         "zeroline": false
+        },
+        "yaxis2": {
+         "anchor": "x2",
+         "domain": [
+          0,
+          1
+         ],
+         "gridcolor": "lightgray",
+         "linecolor": "black",
+         "mirror": true,
+         "showgrid": true,
+         "showline": true,
+         "tickfont": {
+          "color": "black"
+         },
+         "title": {
+          "text": "Y [AU]"
+         },
+         "zeroline": false
+        }
+       }
+      }
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[('helio',\"ecl\")], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "\n",
+    "# --- layout / background ---\n",
+    "fig2d.update_layout(\n",
+    "    plot_bgcolor=\"grey\",\n",
+    "    paper_bgcolor=\"grey\",\n",
+    ")\n",
+    "\n",
+    "# --- x-axes ---\n",
+    "fig2d.update_xaxes(\n",
+    "    title_text=\"X [AU]\",\n",
+    "    showgrid=True,\n",
+    "    showline=True, # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
+    "    mirror=True, \n",
+    "    linecolor=\"black\",\n",
+    "    gridcolor=\"lightgray\",\n",
+    "    tickfont=dict(color=\"black\"),\n",
+    "    zeroline=False,\n",
+    ")\n",
+    "\n",
+    "# --- y-axes ---\n",
+    "fig2d.update_yaxes(\n",
+    "    title_text=\"Y [AU]\",\n",
+    "    showgrid=True,\n",
+    "    showline=True,\n",
+    "    mirror=True, # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
+    "    linecolor=\"black\",\n",
+    "    gridcolor=\"lightgray\",\n",
+    "    tickfont=dict(color=\"black\"),\n",
+    "    zeroline=False,\n",
+    ")\n",
+    "\n",
+    "# --- style orbit lines + markers ---\n",
+    "fig2d.for_each_trace(\n",
+    "    lambda tr: tr.update(line=dict(color=\"red\")) if tr.mode == \"lines\" and (tr.meta is None or tr.meta.get(\"kind\") != \"planet\") # <-- planets have a special internal tag so you can colour input objects separately\n",
+    "    else None\n",
+    ")\n",
+    "\n",
+    "fig2d.update_traces(\n",
+    "    selector=dict(mode=\"markers\"),\n",
+    "    marker=dict(size=8, color=\"blue\"),\n",
+    ")\n",
+    "\n",
+    "\n",
+    "fig2d\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0886d6e4",
+   "metadata": {},
+   "source": [
+    "## 7) (Optional) Saving the figure\n",
+    "Plotly offers the ability to save the current frame, however you choose to orient, zoom, or pan the plot, as a png file via the camera button in the top right of the output. Alternatively, we have specified `return_fig=True` in `plotly_2D`/`plotly_3D`, which means we can make use of a Plotly feature to save to any format via the following (see the [Plotly documentation](https://plotly.github.io/plotly.py-docs/generated/plotly.io.write_image.html) for more info on this method, you may need to install external image exporting engines to properly utilise this method): "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "42d9da79",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "fig2d.write_image('/foo/bar/baz/image.pdf')\n",
+    "fig3d.write_image('/foo/bar/baz/image.pdf')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b82b41f4",
+   "metadata": {},
+   "source": [
+    "# 8) (Optional) Running the Dash app in a notebook\n",
+    "We've been mentioning running the Dash App in the web (i.e. in a window in your browser of choice) a lot so far, but it is possible to get the full interactivity of Layup Visualize in a Jupyter notebook cell. We've made a convenient wrapper funciton, `visualize_notebook` that essentially calls the CLI functions behind the scenes with either a string path to your input file, or a structured numpy array like we've been making for our toy models here. Let's call it here on another set of toy orbits: "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "a3108eee",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "--input-origin not provided. Inferring heliocentric from input file format column FORMAT=KEP\n",
+      "--input-plane not provided. Inferring ecliptic for input file format column FORMAT=KEP\n",
+      "Requested 100 orbits, but only 5 orbits in input. Capping to 5\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "\n",
+       "        <iframe\n",
+       "            width=\"100%\"\n",
+       "            height=\"650\"\n",
+       "            src=\"http://127.0.0.1:8050/\"\n",
+       "            frameborder=\"0\"\n",
+       "            allowfullscreen\n",
+       "            \n",
+       "        ></iframe>\n",
+       "        "
+      ],
+      "text/plain": [
+       "<IPython.lib.display.IFrame at 0x168783770>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from layup.visualize import visualize_notebook\n",
+    "import numpy as np\n",
+    "\n",
+    "# --- toy dataset: 5 example orbits ---\n",
+    "rng = np.random.default_rng(8675309)\n",
+    "N = 5\n",
+    "dtype = [\n",
+    "    (\"ObjID\", \"U32\"),\n",
+    "    (\"epochMJD_TDB\", \"f8\"),\n",
+    "    (\"a\", \"f8\"),\n",
+    "    (\"e\", \"f8\"),\n",
+    "    (\"inc\", \"f8\"),\n",
+    "    (\"argPeri\", \"f8\"),\n",
+    "    (\"node\", \"f8\"),\n",
+    "    (\"ma\", \"f8\"),\n",
+    "    (\"FORMAT\", \"U32\")\n",
+    "]\n",
+    "\n",
+    "orbits = np.zeros(N, dtype=dtype)\n",
+    "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
+    "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
+    "orbits[\"a\"] = rng.uniform(1.5, 12.0, size=N)\n",
+    "orbits[\"e\"] = np.clip(rng.normal(0.2, 0.15, size=N), 0.01, 0.85) # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
+    "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
+    "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",
+    "orbits[\"ma\"] = rng.uniform(0, 360, size=N)\n",
+    "orbits[\"FORMAT\"] = \"KEP\"\n",
+    "\n",
+    "visualize_notebook(orbits)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ea4236e3",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "layupnewviz",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.11"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/layup/dash_ui.py b/src/layup/dash_ui.py
new file mode 100644
index 00000000..75e64f2a
--- /dev/null
+++ b/src/layup/dash_ui.py
@@ -0,0 +1,1833 @@
+import logging
+from typing import Literal, Tuple, Optional, Any
+
+import numpy as np
+from datetime import datetime, timedelta
+
+from layup.orbit_maths import ClassicalConic
+
+PANEL = Literal["XY", "XZ", "YZ"]
+
+PLANET_COLOURS_NIGHT = {
+    "Mercury": "rgba(190,190,190,0.95)",   # silver
+    "Venus":   "rgba(255,190,90,0.95)",    # warm amber
+    "Earth":   "rgba(90,210,255,0.95)",    # cyan 
+    "Mars":    "rgba(255,90,90,0.95)",     # red
+    "Jupiter": "rgba(255,165,120,0.95)",   # salmon/orange
+    "Saturn":  "rgba(255,230,150,0.95)",   # pale gold
+    "Uranus":  "rgba(120,255,210,0.95)",   # mint
+    "Neptune": "rgba(185,120,255,0.95)",   # purple 
+}
+
+PLANET_COLOURS_DAY = {
+    "Mercury": "rgba(90,90,90,0.95)",      # dark gray
+    "Venus":   "rgba(180,110,0,0.95)",     # brown/orange
+    "Earth":   "rgba(0,140,190,0.95)",     # teal-blue 
+    "Mars":    "rgba(170,0,0,0.95)",       # dark red
+    "Jupiter": "rgba(170,90,60,0.95)",     # brown
+    "Saturn":  "rgba(160,140,40,0.95)",    # olive gold
+    "Uranus":  "rgba(0,150,110,0.95)",     # green-teal
+    "Neptune": "rgba(115,0,170,0.95)",     # deep purple 
+}
+
+logger = logging.getLogger(__name__)
+
+# --- set up plots ---
+def add_reference_plane_xy(
+        fig,
+        lines: np.ndarray,
+        planet_lines: np.ndarray,
+        opacity: float = 0.10
+):
+    """
+    Add the reference plane (either ecliptic or equatorial) to the 3D plot at Z=0
+
+    Parameters
+    -----------
+    fig : object 
+        Plotly figure object
+    
+    lines : numpy float array
+        Array of x,y,z coordinates of objects to be plotted
+
+    lines : numpy float array
+        Array of x,y,z coordinates of planets to be plotted
+
+    opacity : float, optional (default = 0.10)
+        Transparency of the reference plane
+    """
+    import plotly.graph_objects as go
+
+    # extract all x/y coords and flatten (ravel) to 1D
+    x_obj = lines[..., 0].ravel()
+    y_obj = lines[..., 1].ravel()
+
+    # either take the extent of the plane to be the furthest orbit or furthest planet 
+    if planet_lines is not None and np.size(planet_lines) > 0:
+        x_pla = planet_lines[..., 0].ravel()
+        y_pla = planet_lines[..., 1].ravel()
+        x0 = min(np.nanmin(x_obj), np.nanmin(x_pla))
+        x1 = max(np.nanmax(x_obj), np.nanmax(x_pla))
+        y0 = min(np.nanmin(y_obj), np.nanmin(y_pla))
+        y1 = max(np.nanmax(y_obj), np.nanmax(y_pla))
+    else:
+        x0, x1 = np.nanmin(x_obj), np.nanmax(x_obj)
+        y0, y1 = np.nanmin(y_obj), np.nanmax(y_obj)
+
+    # add a bit of padding from the edges
+    padx = 0.05 * (x1 - x0) if (x1 - x0) > 0 else 1.0
+    pady = 0.05 * (y1 - y0) if (y1 - y0) > 0 else 1.0
+    x0, x1 = x0 - padx, x1 + padx
+    y0, y1 = y0 - pady, y1 + pady
+    
+    # now create the plane as nx x ny grid
+    nx, ny = 40, 40
+    xs = np.linspace(x0, x1, nx)
+    ys = np.linspace(y0, y1, ny)
+    X, Y = np.meshgrid(xs, ys)
+    Z = np.zeros_like(X)
+
+    # add to the figure
+    fig.add_trace(
+        go.Surface(
+            x=X, y=Y, z=Z,
+            showscale=False,
+            opacity=opacity,
+            surfacecolor=np.zeros_like(X),
+            hoverinfo="skip",
+            name="ref-plane",
+            hovertemplate=None
+        )
+    )
+
+# --- very crude orbit classifier ---
+def classify(
+        a: float, 
+        e: float, 
+        Tj: float
+) -> str:
+    """
+    Rough first pass orbit classifier based on input orbital elements. Does NOT do any
+    orbit integrations to verify e.g. Trojan or other resonant behaviour, so use only as
+    an approximate guess. Check your orbits thoroughly.
+
+    Parameters
+    -----------
+    a : float
+        Semimajor axis of the object, in units of AU
+
+    e : float
+        Eccentricity of the object
+
+    Tj : float
+        Tisserand parameter with respect to Jupiter of the object 
+    """
+    q = a * (1 - e)
+
+    # these are some very very crude dynamical classifiers for filtering
+    # purposes, don't take them as gospel - do your own checks!!
+    if e >= 1.0:
+        return "Hyperbolic"
+    elif np.isfinite(a) and a > 2000:
+        return "Inner Oort Cloud"
+    elif np.isfinite(Tj) and (Tj < 2.0):
+        return "LPC"
+    elif np.isfinite(Tj) and (2.0 <= Tj < 3.0) and (q < 5.2):
+        return "JFC"
+    elif np.isfinite(q) and (q < 1.3):
+        return "NEO"
+    elif np.isfinite(q) and (1.3 <= q < 1.66):
+        return "Mars-Crosser"
+    elif np.isfinite(a) and (2.0 <= a <= 3.5) and np.isfinite(q) and (q >= 1.66):
+        return "MBA"
+    elif np.isfinite(a) and (a < 30.04) and np.isfinite(q) and (q >= 7.35):
+        return "Centaur"
+    elif np.isfinite(a) and (30.04 <= a < 2000.0) and np.isfinite(q) and (q >= 7.35):
+        return "TNO"
+    else:
+        return "Other"
+
+
+# --- plot in 2D ---
+def plotly_2D(
+        lines: np.ndarray,
+        canon: ClassicalConic,
+        plot_sun: bool = True,
+        orbit_pos: Optional[np.ndarray] = None,
+        sun_xyz: Optional[np.ndarray] = None,
+        planet_lines: Optional[np.ndarray] = None,
+        planet_id: Optional[np.ndarray] = None,
+        return_fig: bool = False,
+        output: Optional[str] = None,
+        panel: Optional[PANEL] = None,
+        panels: Optional[Tuple[PANEL, PANEL]] = None
+):
+    """
+    Create a 2D (1x2 subplot) interactive Plotly figure of orbits
+
+    Parameters
+    -----------
+    lines : dict of numpy array
+        Dictionary of arrays with the orbit lines for each object in each plane+origin combination
+
+    canon : ClassicalConic object
+        Object with the conic section class instances of each object and their properties
+
+    plot_sun : bool, optional (default = True)
+        Flag to turn on/off plotting the Sun
+
+    orbit_pos : dict of numpy array, optional (default = None)
+        Dictionary of arrays with object positions in each plane+origin combination
+
+    sun_xyz : dict of numpy array, optional (default = None)
+        Dictionary of arrays with the Sun positions in each plane+origin combination
+
+    planet_lines : dict of arrays, optional (default = None)
+        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        combination of shape (n_planets, n_points, 3)
+
+    planet_id : numpy string array, optional (default = None)
+        Array containing ID tags for each planet of shape (n_planets,)
+
+    return_fig : bool, optional (default = False)
+        Flag to turn on/off returning the figure object
+
+    output : str, optional (default = None)
+        String containing the html of the figure
+
+    panel: str, optional (default = None)
+        String containing which orientation to draw a single panel of. Must be one of "XY", "XZ", "YZ"
+
+    panels: str, optional (default = None)
+        String containing which orientation to draw two panels of. Must be one of "XY", "XZ", "YZ"
+
+    Returns
+    --------
+    fig : object
+        Plotly figure object
+    """
+    import plotly.graph_objects as go
+    from plotly.subplots import make_subplots
+    
+    def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
+        if p == "XY":
+            return x, y, "X [AU]", "Y [AU]", True # <-- the final True here is letting later on know to plot this panel equal aspect, as top-down is onto the reference plane
+        if p == "XZ":
+            return x, z, "X [AU]", "Z [AU]", False # <-- this and YZ are inclination driven so shouldn't be equal aspect
+        if p == "YZ":
+            return y, z, "Y [AU]", "Z [AU]", False
+        logger.error(f"Unknown panel {p!r} (expected 'XY', 'XZ', 'YZ')")
+        raise ValueError(f"Unknown panel {p!r} (expected 'XY', 'XZ', 'YZ')")
+    
+    # -- panel configuration --
+    if panels is not None:
+        panels_to_show: Tuple[PANEL, ...] = tuple(panels) # < -- if >1 panels, turn whichever options they are into tuple
+    elif panel is not None:
+        panels_to_show = (panel,) # < -- if 1 panel, turn that option into tuple
+    else:
+        panels_to_show = ("XY", "XZ") # < -- if none specified, default to 2 panel XY+XZ
+
+    if len(panels_to_show) not in (1, 2):
+        logger.error(f"Expected 1 or 2 panels, got {len(panels_to_show)}: {panels_to_show}")
+        raise ValueError(f"Expected 1 or 2 panels, got {len(panels_to_show)}: {panels_to_show}")
+    
+    ncols = len(panels_to_show)
+
+    fig = make_subplots(
+        rows=1, cols=ncols,
+        horizontal_spacing=0.10 if ncols == 2 else 0.02
+    )
+
+    # -- plot planets --
+    if planet_lines is not None:
+        if planet_id is None:
+            # in the case you have planet lines but no id, just assign them generic name tags
+            planet_id = np.array([f"Planet {i}" for i in range(planet_lines.shape[0])], dtype="U32")
+
+        for i in range(planet_lines.shape[0]):
+            # get planet coords and colour by searching the global variable (default is night mode,
+            # we can change that in the dash app and css later)
+            x = planet_lines[i, :, 0]
+            y = planet_lines[i, :, 1]
+            z = planet_lines[i, :, 2]
+            colour = PLANET_COLOURS_NIGHT.get(str(planet_id[i]), "rgba(200,200,200,0.6)")
+
+            hover_text = f"{planet_id[i]}<extra></extra>"
+
+            # loop over however many panels we have
+            for col, p in enumerate(panels_to_show, start=1):
+                xa, ya, _, _, _ = coords_for(p, x, y, z) # <-- grab the correct axes x/y coords for whatever plane it is
+                fig.add_trace(
+                    go.Scatter(
+                        x=xa, y=ya,
+                        mode="lines",
+                        line=dict(color=colour, width=2.2),
+                        hovertemplate=hover_text,
+                        showlegend=False,
+                        name=str(planet_id[i]),
+                        meta={"kind": "Planet"} # <-- this tag is to prevent colours being overwritten later
+                    ),
+                    row=1, col=col
+                )
+
+    # -- plot input objects --
+    for i in range(lines.shape[0]):
+        # get object coords
+        x = lines[i, :, 0]
+        y = lines[i, :, 1]
+        z = lines[i, :, 2]
+
+        # it may not be best practice to paste unicode symbols here but ¯\_(ツ)_/¯
+        hover_text = (
+            f"{canon.obj_id[i]}<br>"
+            f"e: {canon.e[i]:.4f}<br>"
+            f"i: {np.rad2deg(canon.inc[i]):.2f}°<br>"
+            f"Ω: {np.rad2deg(canon.node[i]):.2f}°<br>"
+            f"ω: {np.rad2deg(canon.argp[i]):.2f}°"
+        )
+
+        # these are being extracted so we can crudely classify them later
+        L = float(canon.L[i])
+        e = float(canon.e[i])
+        inc = float(canon.inc[i])
+        if abs(1 - e**2) < 1e-12: # <-- protect against parabolic orbits
+            a = np.inf
+        else:
+            a = L / (1 - e**2)
+        if (not np.isfinite(a)) or (a == 0.0): # <-- same again
+            Tj = np.nan
+        else:
+            Tj = (5.2044 / a) + 2.0 * np.cos(inc) * np.sqrt((a / 5.2044) * (1 - e**2))
+        pop = classify(a, e, Tj)
+
+        # loop over however many panels we have
+        for col, p in enumerate(panels_to_show, start=1):
+            xa, ya, _, _, _ = coords_for(p, x, y, z) # <-- grab the correct axes x/y coords for whatever plane it is
+            fig.add_trace(
+                go.Scatter(
+                    x=xa, y=ya,
+                    mode="lines",
+                    line=dict(color="rgba(144,167,209,0.7)", width=1.5),
+                    hovertemplate=hover_text+"<extra></extra>",
+                    showlegend=False,
+                    name=str(canon.obj_id[i]),
+                    meta={"kind": pop}
+                ),
+                row=1, col=col
+            )
+
+    
+    # -- plot input object epoch position --
+    if orbit_pos is not None:
+        # want to get a hover label with epoch info so first 
+        # extract from conic objects
+        mjd = np.asarray(canon.epochMJD_TDB, dtype=float)
+        mjd_str = np.array([f"{m:.5f}" for m in mjd], dtype="U32")
+
+        # also good to have it in YYYY MM DD format
+        ymd_str = np.empty(mjd.shape[0], dtype="U10")
+        base = datetime(1858, 11, 17) # <-- MJD 0
+        for i, mjd in enumerate(mjd):
+            dt = base + timedelta(days=float(mjd))
+            ymd_str[i] = dt.strftime("%Y %b %d") 
+
+        # vectorise it by stacking all labels together to add
+        # as one trace into plotly
+        mjd_stack = np.column_stack([mjd_str, ymd_str])
+        hover_text = (
+            "%{text}<br>"
+            "@ MJD %{customdata[0]}<br>"
+            "(%{customdata[1]})"
+            "<extra></extra>"
+        )
+
+        # loop over however many panels we have
+        for col, p in enumerate(panels_to_show, start=1):
+            xa, ya, _, _, _ = coords_for(p, orbit_pos[:, 0], orbit_pos[:, 1], orbit_pos[:, 2]) # <-- grab the correct axes x/y coords for whatever plane it is
+            fig.add_trace(
+                go.Scatter(
+                    x=xa, y=ya,
+                    mode="markers",
+                    marker=dict(size=5, color="rgba(255,255,255,0.9)"),
+                    showlegend=False,
+                    text=np.asarray(canon.obj_id),
+                    customdata=mjd_stack,
+                    hovertemplate=hover_text,
+                    meta={"kind": "epoch"}
+                ),
+                row=1, col=col
+            )
+
+
+    # -- plot the sun --
+    if plot_sun:
+        if sun_xyz is None:
+            sx, sy, sz = 0.0, 0.0, 0.0
+        else:
+            sx, sy, sz = float(sun_xyz[0]), float(sun_xyz[1]), float(sun_xyz[2])
+
+        # loop over however many panels we have
+        for col, p in enumerate(panels_to_show, start=1):
+            xa, ya, _, _, _ = coords_for(p, np.array([sx]), np.array([sy]), np.array([sz])) # <-- grab the correct axes x/y coords for whatever plane it is
+            fig.add_trace(
+                go.Scatter(
+                    x=xa, y=ya,
+                    mode="markers",
+                    marker=dict(size=10, color="yellow"),
+                    showlegend=False,
+                    name="Sun",
+                ),
+                row=1, col=col,
+            )
+
+    # -- pretty up the figure --
+    fig.update_layout(
+        plot_bgcolor="rgba(0,0,0,0)",
+        paper_bgcolor="rgba(0,0,0,0)",
+        font=dict(color="white"),
+        autosize=True,
+        margin=dict(l=60,r=60,t=40,b=60),
+        hoverdistance=0,
+        hovermode="closest"
+    )
+
+    fig.update_xaxes(showgrid=True, gridcolor='rgba(255,255,255,0.08)')
+    fig.update_yaxes(showgrid=True, gridcolor='rgba(255,255,255,0.08)')
+
+    # axis titles + equal aspect for any XY panel
+    # loop over however many panels we have
+    for col, p in enumerate(panels_to_show, start=1):
+        _, _, xtitle, ytitle, want_equal = coords_for(p, np.array([0.0]), np.array([0.0]), np.array([0.0])) # <-- grab the correct axes x/y titles for whatever plane it is
+        fig.update_xaxes(title_text=xtitle, row=1, col=col)
+        fig.update_yaxes(title_text=ytitle, row=1, col=col)
+        if want_equal:
+            if col == 1:
+                fig.update_layout(yaxis=dict(scaleanchor="x", scaleratio=1))
+            elif col == 2:
+                fig.update_layout(yaxis2=dict(scaleanchor="x2", scaleratio=1))
+    
+    # return figure object if user wants
+    if return_fig:
+        return fig
+    
+    # otherwise write out and show
+    if output:
+        fig.write_html(output)
+        fig.show()
+
+    fig.show()
+
+# --- plot in 3D ---
+def plotly_3D(
+        lines: np.ndarray,
+        canon: ClassicalConic,
+        plot_sun: bool = True,
+        show_plane: bool = True,
+        orbit_pos: Optional[np.ndarray] = None,
+        planet_lines: Optional[np.ndarray] = None,
+        planet_id: Optional[np.ndarray] = None,
+        sun_xyz: Optional[np.ndarray] = None,
+        return_fig: bool = False,
+        output: Optional[str] = None    
+):
+    """
+    Create a 3D interactive Plotly figure of orbits
+
+    Parameters
+    -----------
+    lines : dict of numpy array
+        Dictionary of arrays with the orbit lines for each object in each plane+origin combination
+
+    canon : dict of objects
+        Dictionary with the conic section class instances of each object and their properties
+
+    plot_sun : bool, optional (default = True)
+        Flag to turn on/off plotting the Sun
+
+    show_plane : bool, optional (default = True)
+        Flag to turn on/off plotting the reference plane (ecliptic or equatorial)
+
+    orbit_pos : dict of numpy array, optional (default = None)
+        Dictionary of arrays with object positions in each plane+origin combination
+
+    planet_lines : dict of arrays, optional (default = None)
+        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        combination of shape (n_planets, n_points, 3)
+
+    planet_id : numpy string array, optional (default = None)
+        Array containing ID tags for each planet of shape (n_planets,)
+
+    sun_xyz : dict of numpy array, optional (default = None)
+        Dictionary of arrays with the Sun positions in each plane+origin combination
+
+    return_fig : bool, optional (default = False)
+        Flag to turn on/off returning the figure object
+
+    output : str, optional (default = None)
+        String containing the html of the figure
+
+    Returns
+    --------
+    fig : object
+        Plotly figure object
+    """
+    import plotly.graph_objects as go
+
+    fig = go.Figure()
+
+    # -- plot reference plane --
+    if show_plane:
+        add_reference_plane_xy(fig, lines, planet_lines, opacity=0.50)
+    
+    # -- plot planets --
+    if planet_lines is not None:
+        if planet_id is None:
+            planet_id = np.array([f"Planet {i}" for i in range(planet_lines.shape[0])], dtype="U32")
+
+        for i in range(planet_lines.shape[0]):
+            # get planet coords and colour by searching the global variable (default is night mode,
+            # we can change that in the dash app and css later)
+            x = planet_lines[i, :, 0]
+            y = planet_lines[i, :, 1]
+            z = planet_lines[i, :, 2]
+            colour = PLANET_COLOURS_NIGHT.get(str(planet_id[i]), "rgba(200,200,200,0.6)")
+
+            fig.add_trace(
+                go.Scatter3d(
+                    x=x, y=y, z=z,
+                    mode="lines",
+                    line=dict(color=colour, width=5),
+                    hovertemplate=f"{planet_id[i]}<extra></extra>",
+                    showlegend=False,
+                    name=str(planet_id[i]),
+                    meta={"kind": "Planet"} # <-- this tag is to prevent colours being overwritten later
+                )
+            )
+
+    # -- plot input objects --
+    for i in range(lines.shape[0]):
+        x = lines[i, :, 0]
+        y = lines[i, :, 1]
+        z = lines[i, :, 2]
+
+        # it may not be best practice to paste unicode symbols here but ¯\_(ツ)_/¯
+        hover_text = (
+            f"{canon.obj_id[i]}<br>"
+            f"e: {canon.e[i]:.4f}<br>"
+            f"i: {np.rad2deg(canon.inc[i]):.2f}°<br>"
+            f"Ω: {np.rad2deg(canon.node[i]):.2f}°<br>"
+            f"ω: {np.rad2deg(canon.argp[i]):.2f}°"
+        )
+
+        # these are being extracted so we can crudely classify them later
+        L = float(canon.L[i])
+        e = float(canon.e[i])
+        inc = float(canon.inc[i])
+        if abs(1 - e**2) < 1e-12: # <-- protect against parabolic orbits
+            a = np.inf
+        else:
+            a = L / (1 - e**2)
+        if (not np.isfinite(a)) or (a == 0.0): # <-- same again
+            Tj = np.nan
+        else:
+            Tj = (5.2044 / a) + 2.0 * np.cos(inc) * np.sqrt((a / 5.2044) * (1 - e**2))
+        pop = classify(a, e, Tj)
+
+        fig.add_trace(
+            go.Scatter3d(
+                x=x, y=y, z=z,
+                mode="lines",
+                line=dict(color="rgba(144, 167, 209, 0.7)", width=3),
+                hovertemplate=hover_text + "<extra></extra>",
+                showlegend=False,
+                name=str(canon.obj_id[i]),
+                meta={"kind": pop}
+            )
+        )
+
+    # -- plot input object epoch position --
+    if orbit_pos is not None:
+        # want to get a hover label with epoch info so first 
+        # extract from conic objects
+        mjd = np.asarray(canon.epochMJD_TDB, dtype=float)
+        mjd_str = np.array([f"{m:.5f}" for m in mjd], dtype="U32")
+
+        # also good to have it in YYYY MM DD format
+        ymd_str = np.empty(mjd.shape[0], dtype="U10")
+        base = datetime(1858, 11, 17) # <-- MJD 0
+        for i, mjd in enumerate(mjd):
+            dt = base + timedelta(days=float(mjd))
+            ymd_str[i] = dt.strftime("%Y %b %d") 
+
+        # vectorise it by stacking all labels together to add
+        # as one trace into plotly
+        mjd_stack = np.column_stack([mjd_str, ymd_str])
+        hover_text = (
+            "%{text}<br>"
+            "@ MJD %{customdata[0]}<br>"
+            "(%{customdata[1]})"
+            "<extra></extra>"
+        )
+
+        fig.add_trace(
+            go.Scatter3d(
+                x=orbit_pos[:, 0],
+                y=orbit_pos[:, 1],
+                z=orbit_pos[:, 2],
+                mode="markers",
+                marker=dict(size=3.5, color="rgba(255,255,255,0.9)"),
+                showlegend=False,
+                meta={"kind": "epoch"},
+                text=np.asarray(canon.obj_id),
+                customdata=mjd_stack,
+                hovertemplate=hover_text
+            )
+        )
+
+    # -- plot the sun --
+    if plot_sun:
+        if sun_xyz is None:
+            sx, sy, sz = 0.0, 0.0, 0.0
+        else:
+            sx, sy, sz = float(sun_xyz[0]), float(sun_xyz[1]), float(sun_xyz[2])
+
+        fig.add_trace(
+            go.Scatter3d(
+                x=[sx], y=[sy], z=[sz],
+                
+                mode="markers",
+                marker=dict(size=6, color="yellow"),
+                showlegend=False,
+                hovertext="Sun"
+            )
+        )
+
+    # -- pretty up the figure --
+    fig.update_layout(
+        template=None,
+        paper_bgcolor="rgba(0,0,0,0)",
+        plot_bgcolor="rgba(0,0,0,0)",
+        font=dict(color="white"),
+        autosize=True,
+        margin=dict(l=0, r=0, t=40, b=0),
+        scene=dict(
+            xaxis=dict(title="X [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
+            yaxis=dict(title="Y [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
+            zaxis=dict(title="Z [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
+            aspectmode="data",
+            camera=dict(
+                center=dict(x=0, y=0, z=-0.25)  # <-- for some reason default camera looks really low to me, negative z shifts scene up in the frame
+            )
+        )
+    )
+
+    # return figure object if user wants
+    if return_fig:
+        return fig
+    
+    # otherwise write out and show
+    if output:
+        fig.write_html(output)
+        fig.show()
+
+    fig.show()
+
+
+# --- make the dash app ---
+def run_dash_app(
+        fig2d_cache: dict[tuple[str, str], "object"],
+        fig3d_cache: dict[tuple[str, str], "object"]
+):
+    """
+    Create and 
+    """
+    import dash
+    from dash import Dash, dcc, html, Input, Output, State, ctx
+    import dash_daq as daq
+    import dash_ag_grid as dag
+    import copy
+    import os
+    import threading
+    import webbrowser
+
+    # set up app and (very optionally) link to latex stylesheet
+    app = Dash(__name__, assets_folder="data", external_stylesheets=["https://cdn.jsdelivr.net/npm/katex@0.16.9/dist/katex.min.css"])
+
+    # establsh day/night mode theming
+    THEME = {
+        "night": {
+            "bg": "black",
+            "fg": "white",
+            "muted": "rgba(255,255,255,0.82)",
+            "grid": "rgba(255,255,255,0.08)",
+            "zero": "rgba(255,255,255,0.12)",
+            "drawer_bg": "rgba(0,0,0,0.70)",
+            "tab_bg": "rgba(0,0,0,0.55)",
+            "border": "rgba(255,255,255,0.18)"
+        },
+        "day": {
+            "bg": "white",
+            "fg": "#111111",
+            "muted": "rgba(0,0,0,0.75)",
+            "grid": "rgba(0,0,0,0.10)",
+            "zero": "rgba(0,0,0,0.18)",
+            "drawer_bg": "rgba(255,255,255,0.86)",
+            "tab_bg": "rgba(255,255,255,0.75)",
+            "border": "rgba(0,0,0,0.15)"
+        }
+    }
+
+    ORBIT_COLOUR = {
+        "night": "rgba(144,167,209,0.70)",
+        "day": "rgba(30,60,120,0.85)"
+    }
+
+    # defaults
+    night_default = True
+    theme0 = THEME["night"] if night_default else THEME["day"]
+    fg0 = theme0["fg"]
+
+    origin_bary_default = False
+    plane_equ_default = False
+    view_3d_default = True
+    opacity_default = 0.5
+
+    default_key = ("helio", "ecl")
+    initial_fig = fig3d_cache.get(default_key) or next(iter(fig3d_cache.values()))
+
+    # in order to make a selecter for the orbits, we build an inventory of all selectable objects
+    def collect_inventory(figs: list[object]):
+        planets: set[str] = set()
+        objids: set[str] = set()
+        kinds: dict[str, str] = {}
+
+        for f in figs:
+            for tr in getattr(f, "data", []) or []:
+                meta = getattr(tr, "meta", None)
+                name = str(getattr(tr, "name", ""))
+
+                if not name or name == "ref-plane":
+                    continue
+                
+                if isinstance(meta, dict):
+                    k = meta.get("kind") # <-- finally the meta tags come in to play!
+
+                    if k == "Planet":
+                        planets.add(name)
+                        continue
+
+                    if getattr(tr, "type", None) in ("scatter", "scatter3d") and getattr(tr, "mode", None) == "lines":
+                        objids.add(name)
+                        kinds.setdefault(name, k)
+
+        return sorted(planets), sorted(objids), kinds
+    
+    # get our list of selectable things (if for some reason the cache is partial or could be
+    # broken, fall back to whatever the initial_fig is)
+    inv_planets, inv_objids, orbit_kinds = collect_inventory(list(fig3d_cache.values()))
+    if not inv_planets or not inv_objids:
+        inv_planets, inv_objids, orbit_kinds = collect_inventory([initial_fig])
+
+    # these are our table inventory rows
+    inventory_rows = (
+        [{"kind": "Planet", "name": p} for p in inv_planets] +
+        [{"kind": orbit_kinds.get(o, "Other"), "name": o} for o in inv_objids]
+    )
+
+    # set up title/label styling helpers for swapping day/night, frame, origin, and view modes
+    def title_style(fg: str):
+        return {"marginBottom": "10px", "fontSize": "20px", "color": fg, "opacity": 0.95}
+    
+    def sublabel_style(fg: str):
+        return {"fontSize": "17px", "color": fg, "opacity": 0.90}
+    
+    # this creates the proper div environment for the toggle switches so the labels wrap well and look nice
+    def labeled_toggle(left_label: str, toggle_id: str, right_label: str, value: bool, fg: str, width_pix: int=220):
+        return html.Div(
+            [
+                html.Div(left_label, style={**sublabel_style(fg), "marginRight": "14px", "whiteSpace": "nowrap"}, className="toggle-label"),
+                daq.ToggleSwitch(
+                    id=toggle_id,
+                    value=value,
+                    size=70,
+                    color="#4cd964"
+                ),
+                html.Div(right_label, style={**sublabel_style(fg), "marginLeft": "14px", "whiteSpace": "nowrap"}, className="toggle-label")
+            ],
+            style={
+                "display": "flex",
+                "alignItems": "center",
+                "justifyContent": "center",
+                "width": "100%"
+            }
+        )
+    
+    # set up a template consistent "block" for all controls to be built into
+    def control_block(title: str, body, fg: str, width_px: int=200):
+        return html.Div(
+            [
+                html.Div(title, style={**title_style(fg), "textAlign": "center", "width": "100%"}),
+                html.Div(body, style={"display": "flex", "justifyContent": "center", "width": "100%"})
+            ],
+            style={
+                "width": "100%",
+                "minWidth": "0",
+                "display": "flex",
+                "flexDirection": "column",
+                "alignItems": "center"
+            }
+        )
+    
+    # create a special plane toggle block with the slider
+    plane_block_layout = control_block(
+        "Plane",
+        html.Div(
+            [
+                html.Div(
+                    labeled_toggle("Ecl", "plane-toggle", "Equ", value=plane_equ_default, fg=fg0, width_pix=220),
+                    style={"display": "flex", "justifyContent": "center", "width": "100%", "maxWidth": "260px", "margin": "0 auto 14px auto"}
+                ),
+                html.Div(
+                    [
+                        html.Div(
+                            "Opacity",
+                            style={**sublabel_style(fg0), "flex": "1 1 auto", "textAlign": "center"}
+                        ),
+                        html.Div(
+                            "Colour",
+                            style={**sublabel_style(fg0), "flex": "0 0 42px", "textAlign": "center"}
+                        )
+                    ],
+                    style={"width": "100%", "maxWidth": "260px", "display": "flex", "gap": "10px", "margin": "0 auto 6px auto"}
+                ),
+                html.Div(
+                    [
+                        html.Div(
+                            dcc.Slider(
+                                id="plane-opacity",
+                                min=0.0,
+                                max=1.0,
+                                step=0.02,
+                                value=opacity_default,
+                                marks={0.0: "0", 0.5: "0.5", 1.0: "1.0"},
+                                className="opacity-slider"
+                            ),
+                            style={"flex": "1 1 auto", "minWidth": "0"}
+                        ),
+                        html.Button(
+                            "🖌\uFE0E", # <-- is emoji pasting good coding practice? 
+                            id="plane-colour-button",
+                            n_clicks=0,
+                            style={"flex": "0 0 42px", "width": "42px", "height": "34px", "borderRadius": "10px", "border": f"1px solid {theme0['border']}", "background": theme0["tab_bg"], "color": fg0, "cursor": "pointer", "padding": "0", "display": "flex", "alignItems": "center", "justifyContent": "center"},
+                            title="Edit Colour"
+                        )
+                    ],
+                    style={"width": "100%", "maxWidth": "260px", "margin": "0 auto", "display": "flex", "alignItems": "center", "gap": "10px"}
+                )
+            ],
+            style={"display": "flex", "flexDirection": "column", "alignItems": "center", "gap": "10px", "width": "100%", "minWidth": "0"}
+        ),
+        fg=fg0
+    )
+
+    # create a special switch for 2D plots to choose which panels to display and how many
+    panel_mode_block = html.Div(
+        [
+            html.Div(
+                "2D Panel Controls",
+                style={**sublabel_style(fg0), "textAlign": "center", "marginBottom": "6px"}
+            ),
+            dcc.RadioItems(
+                id="panel-mode",
+                options=[
+                    {"label": "1 panel", "value": "single"},
+                    {"label": "2 panels", "value": "double"},
+                ],
+                value="double",
+                inline=True,
+                style={"display": "flex", "justifyContent": "center", "gap": "18px"},
+                labelStyle={**sublabel_style(fg0), "cursor": "pointer"}
+            ),
+        ],
+        style={"width": "220px", "display": "flex", "flexDirection": "column", "alignItems": "center", "marginTop": "14px"},
+    )
+
+    
+    # -- create entire layout of page --
+    app.layout = html.Div(
+        [
+            # these store camera/zoom info across theme/origin/plane changes, whether the
+            # controls drawer is open or not, and the height of the drawer
+            dcc.Store(id="view-state", data={"mode": None, "camera": None, "xrange": None, "yrange": None}),
+            dcc.Store(id="controls-open", data=False),
+            dcc.Store(id="drawer-height", data=0),
+            # our visible object sets
+            dcc.Store(id="visible-objids", data=inv_objids),
+            dcc.Store(id="visible-planets", data=inv_planets),
+            # here's our button to toggle down the settings menu
+            html.Button(
+                "⌄",
+                id="controls-tab",
+                n_clicks=0,
+                style={
+                    "position": "fixed",
+                    "top": "10px",
+                    "left": "50%",
+                    "transform": "translateX(-50%)",
+                    "zIndex": 10000,
+                    "pointerEvents": "auto",
+                    "width": "64px",
+                    "height": "36px",
+                    "borderRadius": "14px",
+                    "border": f"1px solid {theme0['border']}",
+                    "background": theme0["tab_bg"],
+                    "color": fg0,
+                    "fontSize": "26px",
+                    "cursor": "pointer",
+                    "backdropFilter": "blur(10px)",
+                    "transition": "top 180ms ease"
+                },
+            ),
+            html.Div(
+                [
+                    html.Div(
+                        [
+                            html.Div(
+                                [
+                                    html.Div("", style={"justifySelf": "start"}),
+                                    html.Div("Controls", style={"fontSize": "22px", "fontWeight": 600, "justifySelf": "center"}),
+                                    html.Button(
+                                        "x",
+                                        id="controls-close",
+                                        n_clicks=0,
+                                        style={
+                                            "justifySelf": "end",
+                                            "border": "none",
+                                            "background": "transparent",
+                                            "color": "inherit",
+                                            "fontSize": "22px",
+                                            "cursor": "pointer"
+                                        }
+                                    )
+                                ],
+                                style={
+                                    "display": "grid",
+                                    "gridTemplateColumns": "1fr auto 1fr",
+                                    "alignItems": "center",
+                                    "marginBottom": "14px",
+                                }
+                            ),
+                            html.Div(
+                                html.Div(
+                                    [
+                                        control_block(
+                                            "Theme",
+                                            labeled_toggle("Day", "theme-toggle", "Night", value=night_default, fg=fg0, width_pix=220),
+                                            fg=fg0,
+                                            width_px=220
+                                        ),
+                                        control_block(
+                                            "Origin",
+                                            labeled_toggle("Helio", "origin-toggle", "Bary", value=origin_bary_default, fg=fg0, width_pix=220),
+                                            fg=fg0,
+                                            width_px=220
+                                        ),
+                                        plane_block_layout,
+                                        html.Div(
+                                            [
+                                                control_block(
+                                                    "View",
+                                                    labeled_toggle("2D", "view-toggle", "3D", value=view_3d_default, fg=fg0, width_pix=200),
+                                                    fg=fg0,
+                                                    width_px=220
+                                                ),
+                                                html.Div(
+                                                    panel_mode_block,
+                                                    id="panel-controls-wrapper",
+                                                    style={"display": "none"}  # <-- start hidden since default view is 3D
+                                                )
+                                            ],
+                                            style={"display": "flex", "flexDirection": "column", "alignItems": "center", "gap": "10px", "width": "100%", "minWidth": "0"}
+                                        ),
+                                        control_block(
+                                            "Edit Objects",
+                                            html.Div(
+                                                html.Button(
+                                                    [html.Span("✎", style={"marginRight": "10px"}), "Edit"],
+                                                    id="objects-open",
+                                                    n_clicks=0,
+                                                    style={
+                                                        "width": "180px",
+                                                        "height": "44px",
+                                                        "borderRadius": "14px",
+                                                        "border": f"1px solid {theme0['border']}",
+                                                        "background": theme0["tab_bg"],
+                                                        "color": fg0,
+                                                        "fontSize": "20px",
+                                                        "fontWeight": 600,
+                                                        "cursor": "pointer"
+                                                    }
+                                                ),
+                                                style={"marginTop": "6px"}
+                                            ),
+                                            fg=fg0,
+                                            width_px=220
+                                        )
+                                    ],
+                                    id="controls-row",
+                                    style={
+                                        "display": "grid",
+                                        "gridTemplateColumns": "repeat(5, minmax(260px, 1fr))", # <-- this makes it an evenly spaced grid of 5 objects
+                                        "alignItems": "start",
+                                        "gap": "32px",
+                                        "width": "100%",
+                                        "boxSizing": "border-box",
+                                        "justifyItems": "stretch"
+                                    }
+                                ),
+                                style={
+                                    "width": "100%",
+                                    "overflowX": "auto",
+                                    "overflowY": "visible",
+                                    "paddingLeft": "32px",
+                                    "paddingRight": "32px",
+                                    "boxSizing": "border-box"
+                                }
+                            )
+                        ],
+                        id="controls-content",
+                        style={
+                            "padding": "18px",
+                            "paddingBottom": "64px",
+                            "boxSizing": "border-box",
+                            "background": theme0["drawer_bg"],
+                            "color": fg0,
+                            "borderBottom": f"1px solid {theme0['border']}",
+                            "backdropFilter": "blur(10px)",
+                        }
+                    )
+                ],
+                id="controls-drawer",
+                style={
+                    "position": "fixed",
+                    "top": "0",
+                    "left": "0",
+                    "right": "0",
+                    "zIndex": 4000,
+                    "background": "rgba(0,0,0,0)",
+                    "borderBottom": "none",
+                    "backdropFilter": "none",
+                    "overflow": "visible",
+                    "display": "flex",
+                    "flexDirection": "column",
+                    "transform": "translateY(-100%)",
+                    "transition": "transform 180ms ease",
+                    "pointerEvents": "none",
+                }
+            ),
+            html.Div(
+                [
+                    # this is the actual plot being drawn
+                    dcc.Graph(
+                        id="orbit-graph",
+                        figure=initial_fig,
+                        style={"width": "100%", "height": "100%"},
+                        config={
+                            "displaylogo": False,
+                            "responsive": True,
+                            "displayModeBar": True
+                        }
+                    ),
+                    # panel dropdown overlay (on-plot, not in drawer)
+                    html.Div(
+                        [
+                            dcc.Dropdown(
+                                id="panel-single",
+                                options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
+                                value="XY",
+                                clearable=False,
+                                style={"width": "110px", "color": "#111111"}
+                            ),
+                        ],
+                        id="panel-overlay-single",
+                        style={
+                            "position": "absolute",
+                            "left": "50%",
+                            "top": "10px",
+                            "transform": "translateX(-50%)",
+                            "zIndex": 2000,
+                            "display": "none",
+                            "padding": "10px 12px",
+                            "borderRadius": "14px",
+                            "background": theme0["tab_bg"],
+                            "border": f"1px solid {theme0['border']}",
+                            "backdropFilter": "blur(10px)",
+                            "pointerEvents": "auto"
+                        }
+                    ),
+                    html.Div(
+                        [
+                            dcc.Dropdown(
+                                id="panel-left",
+                                options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
+                                value="XY",
+                                clearable=False,
+                                style={"width": "110px", "color": "#111111"}
+                            ),
+                        ],
+                        id="panel-overlay-left",
+                        style={
+                            "position": "absolute",
+                            "left": "25%",
+                            "top": "10px",
+                            "transform": "translateX(-50%)",
+                            "zIndex": 2000,
+                            "display": "none",
+                            "padding": "10px 12px",
+                            "borderRadius": "14px",
+                            "background": theme0["tab_bg"],
+                            "border": f"1px solid {theme0['border']}",
+                            "backdropFilter": "blur(10px)",
+                            "pointerEvents": "auto"
+                        }
+                    ),
+                    html.Div(
+                        [
+                            dcc.Dropdown(
+                                id="panel-right",
+                                options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
+                                value="YZ",
+                                clearable=False,
+                                style={"width": "110px", "color": "#111111"}
+                            )
+                        ],
+                        id="panel-overlay-right",
+                        style={
+                            "position": "absolute",
+                            "left": "75%",
+                            "top": "10px",
+                            "transform": "translateX(-50%)",
+                            "zIndex": 2000,
+                            "display": "none",
+                            "padding": "10px 12px",
+                            "borderRadius": "14px",
+                            "background": theme0["tab_bg"],
+                            "border": f"1px solid {theme0['border']}",
+                            "backdropFilter": "blur(10px)",
+                            "pointerEvents": "auto"
+                        }
+                    )
+                ],
+                style={"position": "fixed", "inset": "0", "zIndex": 1}
+            ),
+
+            # make the object table modal manager
+            html.Div(
+                id="objects-modal",
+                style={
+                    "display": "none",
+                    "position": "fixed",
+                    "inset": 0,
+                    "zIndex": 20000,
+                    "background": "rgba(0,0,0,0.55)",
+                    "backdropFilter": "blur(6px)",
+                    "pointerEvents": "auto"
+                },
+                children=[
+                    html.Div(
+                        id="objects-modal-card",
+                        style={
+                            "width": "min(1200px, 96vw)",
+                            "height": "min(820px, 92vh)",
+                            "margin": "4vh auto",
+                            "background": theme0["drawer_bg"],
+                            "border": f"1px solid {theme0['border']}",
+                            "borderRadius": "16px",
+                            "padding": "16px",
+                            "boxSizing": "border-box",
+                            "display": "flex",
+                            "flexDirection": "column",
+                            "gap": "12px"
+                        },
+                        children=[
+                            html.Div(
+                                style={"display": "flex", "alignItems": "center", "justifyContent": "space-between", "gap": "10px"},
+                                children=[
+                                    html.Div(
+                                        "Object Manager",
+                                        style={"fontSize": "22px", "fontWeight": 700, "color": fg0}
+                                    ),
+                                    html.Button(
+                                        "x",
+                                        id="objects-close",
+                                        n_clicks=0,
+                                        style={"border": "none", "background": "transparent", "color": fg0, "fontSize": "22px", "cursor": "pointer"}
+                                    )
+                                ]
+                            ),
+                            html.Div(
+                                style={"display": "flex", "gap": "10px", "flexWrap": "wrap", "alignItems": "center"},
+                                children=[
+                                    dcc.Input(
+                                        id="obj-quickfilter",
+                                        type="text",
+                                        placeholder="Search... (filter rows)",
+                                        value="",
+                                        style={"width": "340px", "height": "40px", "borderRadius": "12px", "border": f"1px solid {theme0['border']}", "padding": "0 12px", "outline": "none"}
+                                    ),
+                                    html.Div(id="obj-count", style={"color": fg0, "opacity": 0.9, "fontSize": "14px"})
+                                ]
+                            ),
+                            html.Div(
+                                style={"display": "flex", "gap": "10px", "flexWrap": "wrap", "alignItems": "center"},
+                                children=[
+                                    html.Button("Show selected", id="obj-show-selected", n_clicks=0),
+                                    html.Button("Hide selected", id="obj-hide-selected", n_clicks=0),
+                                    html.Button("Show filtered", id="obj-show-filtered", n_clicks=0),
+                                    html.Button("Hide filtered", id="obj-hide-filtered", n_clicks=0),
+                                    html.Button("Show all", id="obj-show-all", n_clicks=0),
+                                    html.Button("Hide all", id="obj-hide-all", n_clicks=0),
+                                    html.Button("Invert Selection", id="obj-invert", n_clicks=0)
+                                ]
+                            ),
+                            html.Div(
+                                style={"flex": "1 1 auto", "minHeight": "0"},
+                                children=[
+                                    dag.AgGrid(
+                                        id="objects-grid",
+                                        columnDefs=[
+                                            {
+                                                "headerName": "Kind",
+                                                "field": "kind",
+                                                "width": 120,
+                                                "filter": True
+                                            },
+                                            {
+                                                "headerName": "Name",
+                                                "field": "name",
+                                                "flex": 1,
+                                                "filter": True,
+                                                "checkboxSelection": True,
+                                                "headerCheckboxSelection": True
+                                            },
+                                            {
+                                                "headerName": "Visible",
+                                                "field": "visible",
+                                                "width": 120,
+                                                "filter": True
+                                            },
+                                        ],
+                                        rowData=[],
+                                        defaultColDef={"sortable": True, "resizable": True},
+                                        dashGridOptions={
+                                            "rowSelection": "multiple", 
+                                            "animateRows": False, 
+                                            "suppressRowClickSelection": False,
+                                            "rowHeight": 34
+                                        },
+                                        className="ag-theme-quartz",
+                                        style={"height": "100%", "width": "100%"}
+                                    )
+                                ]
+                            )
+                        ]
+                    )
+                ]
+
+            ),
+            # make the colour selector window
+            dcc.Store(id="plane-colour-open", data=False),
+            html.Div(
+                id="plane-colour-modal",
+                n_clicks=0,
+                style={"display": "none", "position": "fixed", "inset": 0, "zIndex": 25000, "background": "rgba(0,0,0,0.55)", "backdropFilter": "blur(6px)", "pointerEvents": "auto"},
+                children=[
+                    html.Div(
+                        id="plane-colour-card",
+                        n_clicks=0,
+                        style={"width": "min(520px, 92vw)", "margin": "12vh auto", "background": theme0["drawer_bg"], "border": f"1px solid {theme0['border']}", "borderRadius": "16px", "padding": "16px", "boxSizing": "border-box"},
+                        children=[
+                            html.Div(
+                                style={"display": "flex", "alignItems": "center", "justifyContent": "space-between"},
+                                children=[
+                                    html.Div(
+                                        "Reference Plane Colour",
+                                        style={"fontSize": "18px", "fontWeight": 700, "color": fg0}
+                                    ),
+                                    html.Button(
+                                        "x",
+                                        id="plane-colour-close",
+                                        n_clicks=0,
+                                        style={"border": "none", "background": "transparent", "color": fg0, "fontSize": "22px", "cursor": "pointer"}
+                                    )
+                                ]
+                            ),
+                            html.Div(
+                                style={"marginTop": "12px", "display": "flex", "justifyContent": "center"},
+                                children=[
+                                    daq.ColorPicker(
+                                        id="plane-colour",
+                                        value={"hex": "#F5B277"},
+                                        size=220
+                                    )
+                                ]
+                            )
+                        ]
+                    )
+                ]
+            )
+        ],
+        id="app-shell",
+        className="theme-dark" if night_default else "theme-light",
+        style={
+            "height": "100vh",
+            "width": "100vw",
+            "margin": "0",
+            "padding": "0",
+            "backgroundColor": theme0["bg"],
+            "color": fg0,
+        }
+    )
+
+
+    # -- interactive --
+    # this bit does a bit of javascript-y hackery: basically 1) whenever the controls-open state
+    # changes, we grab its id, then 2) get its pixel dimensions on screen (r = ...), then 3) we
+    # get that height (or 0 if missing) and store it in drawer-height - all of this is done in web  
+    app.clientside_callback(
+        """
+        function(is_open) {
+            const el = document.getElementById("controls-drawer");
+            if (!el) return 0;
+            const r = el.getBoundingClientRect();
+            return (r && r.height) ? r.height : 0;
+        }
+        """,
+        Output("drawer-height", "data"),
+        Input("controls-open", "data")
+    )
+
+    # this bit lets the code know what state the dropdown controls tab is in (open/closed?)
+    @app.callback(
+        Output("controls-open", "data"),
+        Input("controls-tab", "n_clicks"), # <-- toggle tab open/close
+        Input("controls-close", "n_clicks"), # <-- force close 
+        State("controls-open", "data"),
+        prevent_initial_call=True
+    )
+    def toggle_controls(_tab_clicks: int|None, _close_clicks: int|None, is_open: bool):
+        trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else "" # <-- this registers what input fires the callback
+        if trig == "controls-close":
+            return False # <-- if the X button is pressed, force closed
+        return not bool(is_open) # <-- if the \/ button is pressed, invert whatever state is_open is in (ie close/open)
+
+    # now we will alter the position, state, movement, and buttons on the controls drawer here
+    @app.callback(
+        Output("controls-drawer", "style"),
+        Output("controls-tab", "children"),
+        Output("controls-tab", "style"),
+        Input("controls-open", "data"),
+        Input("theme-toggle", "value"),
+        Input("drawer-height", "data"),
+        State("controls-drawer", "style"),
+        State("controls-tab", "style")
+    )
+    def style_drawer(is_open: bool, night_mode: bool, drawer_h: float|int|None, drawer_style: dict[str, Any]|None, tab_style: dict[str, Any]|None):
+        theme = THEME["night"] if night_mode else THEME["day"]
+        fg = theme["fg"]
+
+        # alter some aspects of the drawer (note: in this context a drawer is the slidey box
+        # that comes down when we press the \/ button). note that the style differs if it is
+        # open or closed
+        ds = dict(drawer_style or {})
+        ds["background"] = "rgba(0,0,0,0)"
+        ds["borderBottom"] = "none"
+        ds["backdropFilter"] = "none"
+        ds["overflow"] = "visible"
+        ds["display"] = "flex"
+        ds["flexDirection"] = "column"
+        ds["transition"] = "transform 180ms ease" # <-- make it smooth pulling out
+        ds["transform"] = "translateY(0%)" if is_open else "translateY(-100%)"
+        ds["zIndex"] = 4000
+        ds["pointerEvents"] = "auto" if is_open else "none" # <-- makes sure it wont block the plotly plot elements when closed
+
+        # alter some aspects of the button (note: in this context its also called a tab). the
+        # colour and theme changes depending on day/night mode
+        ts = dict(tab_style or {})
+        ts["position"] = "fixed"
+        ts["left"] = "50%"
+        ts["transform"] = "translateX(-50%)"
+        ts["zIndex"] = 10000
+        ts["pointerEvents"] = "auto"
+        ts["width"] = "64px"
+        ts["height"] = "36px"
+        ts["cursor"] = "pointer"
+        ts["fontSize"] = "26px"
+        ts["borderRadius"] = "14px"
+        ts["background"] = theme["tab_bg"]
+        ts["color"] = fg
+        ts["border"] = f"1px solid {theme['border']}"
+        ts["backdropFilter"] = "blur(10px)"
+        ts["transition"] = "top 180ms ease"
+
+        # this bit places the \/ button either near the top (10px) when closed, or near the bottom edge
+        # of the drawer (inset top_px) when open
+        try:
+            h = float(drawer_h) if drawer_h is not None else 0.0
+        except Exception:
+            h = 0.0
+
+        if is_open and h > 0:
+            top_px = max(10, int(h-36-10)) # <-- drawer bottom (h) - button height (36) - small padding (10)
+            ts["top"] = f"{top_px}px"
+        else:
+            ts["top"] = "10px"
+
+        chevron ="⌃" if is_open else "⌄"
+        
+        return ds, chevron, ts
+    
+    # reference plane colour picker
+    @app.callback(
+        Output("plane-colour-modal", "style", allow_duplicate=True),
+        Output("plane-colour-card", "style"),
+        Input("plane-colour-button", "n_clicks"),
+        Input("plane-colour-close", "n_clicks"),
+        Input("theme-toggle", "value"),
+        State("plane-colour-modal", "style"),
+        State("plane-colour-card", "style"),
+        prevent_initial_call=True
+    )
+    def toggle_plane_colour_modal(open_clicks: int|None, close_clicks: int|None, night_mode: bool, modal_style: dict[str, Any]|None, card_style: dict[str, Any]|None):
+        theme = THEME["night"] if night_mode else THEME["day"]
+        ms = dict(modal_style or {})
+        cs = dict(card_style or {})
+
+        # keep theme in sync
+        cs["background"] = theme["drawer_bg"]
+        cs["border"] = f"1px solid {theme['border']}"
+
+        trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else ""
+        if trig == "plane-colour-button":
+            ms["display"] = "block"
+        elif trig == "plane-colour-close":
+            ms["display"] = "none"
+
+        return ms, cs
+    
+    # add ability to close out of colour picker by just selecting backdrop
+    @app.callback(
+        Output("plane-colour-modal", "style", allow_duplicate=True),
+        Input("plane-colour-modal", "n_clicks"),
+        Input("plane-colour-card", "n_clicks"),
+        State("plane-colour-modal", "style"),
+        prevent_initial_call=True
+    )
+    def close_plane_colour_on_backdrop(modal_clicks: int|None, card_clicks: int|None, style: dict[str, Any]|None):
+        trig = ctx.triggered_id
+
+        # if the backdrop itself was clicked, then close altogether
+        if trig == "plane-colour-modal":
+            style = dict(style or {})
+            style["display"] = "none"
+            return style
+        
+        # but if click was inside the colour picker card, do nothing
+        raise dash.exceptions.PreventUpdate
+
+    # object manager callback stuff (open/close + theming)
+    @app.callback(
+        Output("objects-modal", "style"),
+        Output("objects-modal-card", "style"),
+        Input("objects-open", "n_clicks"),
+        Input("objects-close", "n_clicks"),
+        Input("theme-toggle", "value"),
+        State("objects-modal", "style"),
+        State("objects-modal-card", "style"),
+        prevent_initial_call=True
+    )
+    def toggle_objects_modal(open: int|None, close: int|None, night_mode: bool, modal_style: dict[str, Any]|None, card_style: dict[str, Any]|None):
+        theme = THEME["night"] if night_mode else THEME["day"]
+        fg = theme["fg"]
+
+        ms = dict(modal_style or {})
+        cs = dict(card_style or {})
+
+        # keep theme in sync even if modal already open
+        cs["background"] = theme["drawer_bg"]
+        cs["border"] = f"1px solid {theme['border']}"
+
+        trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else ""
+        if trig == "objects-open":
+            ms["display"] = "block"
+        elif trig == "objects-close":
+            ms["display"] = "none"
+        
+        return ms, cs
+    
+    # add search filtering
+    @app.callback(
+        Output("objects-grid", "quickFilterText"),
+        Input("obj-quickfilter", "value")
+    )
+    def grid_quickfilter(txt: str|None):
+        return txt or ""
+    
+    # make orbits visible / invisibile from table selections
+    @app.callback(
+        Output("objects-grid", "rowData"),
+        Output("obj-count", "children"),
+        Input("visible-objids", "data"),
+        Input("visible-planets", "data")
+    )
+    def sync_grid_rows(visible_objids: list[str]|None, visible_planets: list[str]|None):
+        vis_o = set(visible_objids or [])
+        vis_p = set(visible_planets or [])
+
+        rows = []
+        for r in inventory_rows:
+            k = r["kind"]
+            name = r["name"]
+            if k == "Planet":
+                vis = (name in vis_p)
+            else:
+                vis = (name in vis_o)
+            rows.append({"kind": k, "name": name, "visible": "✓" if vis else ""})
+
+        shown = len(vis_o) + len(vis_p)
+        total = len(inv_objids) + len(inv_planets)
+        return rows, f"Visible: {shown} / {total}"
+    
+    # bulk actions from the manager
+    @app.callback(
+        Output("visible-objids", "data"),
+        Output("visible-planets", "data"),
+        Input("obj-show-selected", "n_clicks"),
+        Input("obj-hide-selected", "n_clicks"),
+        Input("obj-show-filtered", "n_clicks"),
+        Input("obj-hide-filtered", "n_clicks"),
+        Input("obj-show-all", "n_clicks"),
+        Input("obj-hide-all", "n_clicks"),
+        Input("obj-invert", "n_clicks"),
+        State("objects-grid", "selectedRows"),
+        State("objects-grid", "virtualRowData"),
+        State("visible-objids", "data"),
+        State("visible-planets", "data"),
+        prevent_initial_call=True
+    )
+    def bulk_visibility(n1: int|None, n2: int|None, n3: int|None, n4: int|None, n5: int|None, n6: int|None, n7: int|None, selected_rows: list[dict[str, Any]]|None, virtual_rows: list[dict[str, Any]]|None, visible_objids: list[str]|None, visible_planets: list[str]|None):
+        # /\ all of the n* are the various click values for the inputs, if they're not there plotly and dash break
+        trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else ""
+
+        vis_o = set(visible_objids or [])
+        vis_p = set(visible_planets or [])
+
+        def split(rows: list[dict[str, Any]]|None):
+            rows = rows or []
+            ps = {str(r.get("name")) for r in rows if str(r.get("kind")) == "Planet" and r.get("name") is not None}
+            os = {str(r.get("name")) for r in rows if str(r.get("kind")) != "Planet" and r.get("name") is not None}
+            return ps, os
+        
+        sel_p, sel_o = split(selected_rows)
+        fil_p, fil_o = split(virtual_rows)
+
+        # joe learns logical operators:
+        if trig == "obj-show-selected":
+            vis_p |= sel_p
+            vis_o |= sel_o
+        elif trig == "obj-hide-selected":
+            vis_p -= sel_p
+            vis_o -= sel_o
+        elif trig == "obj-show-filtered":
+            vis_p |= fil_p
+            vis_o |= fil_o
+        elif trig == "obj-hide-filtered":
+            vis_p -= fil_p
+            vis_o -= fil_o
+        elif trig == "obj-show-all":
+            vis_p = set(inv_planets)
+            vis_o = set(inv_objids)
+        elif trig == "obj-hide-all":
+            vis_p = set()
+            vis_o = set()
+        elif trig == "obj-invert":
+            vis_p = set(inv_planets) - vis_p
+            vis_o = set(inv_objids) - vis_o
+        else:
+            raise dash.exceptions.PreventUpdate
+        
+        return sorted(vis_o), sorted(vis_p)
+
+    # this section records the zoom/camera state into view-state
+    @app.callback(
+        Output("view-state", "data"),
+        Input("orbit-graph", "relayoutData"),
+        State("view-toggle", "value"),
+        State("view-state", "data"),
+        prevent_initial_call=True
+    )
+    def capture_view(relayout: dict[str, Any]|None, view_3d: bool, state: dict[str, Any]|None):
+        # ignore any callbacks that don't actually change the view
+        if not relayout:
+            return dash.no_update
+        
+        # ignore relayouts that are just layout/style updates
+        camera_keys = {"scene.camera", "xaxis.range[0]", "xaxis.range[1]", "yaxis.range[0]", "yaxis.range[1]", "xaxis.autorange", "yaxis.autorange"}
+
+        if not any(k in relayout for k in camera_keys):
+            return dash.no_update
+        
+        # figure out what mode we're in
+        state = dict(state or {})
+        mode = "3d" if view_3d else "2d"
+
+        # if the mode has changed since last time, reset the stored view 
+        # (viewpoint between 2d <-> 3d shouldn't be saved)
+        if state.get("mode") != mode:
+            state = {"mode": mode, "camera": None, "xrange": None, "yrange": None}
+        state["mode"] = mode
+
+        # if we're in 3d and the camera exists, store it
+        if mode == "3d":
+            cam = relayout.get("scene.camera")
+            if cam:
+                state["camera"] = cam
+        # however if we're in 2d, store the x/y axes ranges
+        else:
+            x0 = relayout.get("xaxis.range[0]")
+            x1 = relayout.get("xaxis.range[1]")
+            y0 = relayout.get("yaxis.range[0]")
+            y1 = relayout.get("yaxis.range[1]")
+
+            if x0 is not None and x1 is not None:
+                state["xrange"] = [x0, x1]
+            if y0 is not None and y1 is not None:
+                state["yrange"] = [y0, y1]
+
+            # or if the range is reset due to autoranging, clear stored ranges
+            if relayout.get("xaxis.autorange") or relayout.get("yaxis.autorange"):
+                state["xrange"] = None
+                state["yrange"] = None
+
+        return state
+
+    # here we're gonna update everything that is actual content such as figures, rather
+    # than just updating the drawer/toggle mechanics
+    @app.callback(
+        Output("orbit-graph", "figure"),
+        Output("app-shell", "style"),
+        Output("app-shell", "className"),
+        Output("panel-controls-wrapper", "style"),
+        Output("panel-overlay-single", "style"),
+        Output("panel-overlay-left", "style"),
+        Output("panel-overlay-right", "style"),
+        Input("theme-toggle", "value"),
+        Input("view-toggle", "value"),
+        Input("origin-toggle", "value"),
+        Input("plane-toggle", "value"),
+        Input("plane-opacity", "value"),
+        Input("plane-colour", "value"),
+        Input("panel-mode", "value"),
+        Input("panel-single", "value"),
+        Input("panel-left", "value"),
+        Input("panel-right", "value"),
+        Input("visible-objids", "data"),
+        Input("visible-planets", "data"),
+        State("view-state", "data")
+    )
+    def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_equ: bool, opacity: float, plane_colour, panel_mode: str, panel_single: str, panel_left: str, panel_right: str, visible_objids: list[str]|None, visible_planets: list[str]|None, view_state: dict[str, object]):
+        # set up some figure themings
+        theme = THEME["night"] if night_mode else THEME["day"]
+        bg = theme["bg"]
+        fg = theme["fg"]
+        grid = theme["grid"]
+        zero = theme["zero"]
+        orbit_colour = ORBIT_COLOUR["night"] if night_mode else ORBIT_COLOUR["day"]
+
+        # set a default plot to show first
+        origin = "bary" if origin_bary else "helio"
+        plane = "equ" if plane_equ else "ecl"
+
+        # deepcopy important as fig.data is mutable, so altering colours messes up cached figures and so toggles
+        if view_3d:
+            fig = copy.deepcopy(fig3d_cache[(origin, plane)])
+        else:
+            if panel_mode == "single":
+                fig = copy.deepcopy(fig2d_cache[(origin, plane, "single", panel_single, None)])
+            else:
+                fig = copy.deepcopy(fig2d_cache[(origin, plane, "double", panel_left, panel_right)])
+
+        for trace in fig.data:
+            # we need to differentiate planets from input objects to make sure
+            # they are coloured properly, so we use their meta tags we set up 
+            # earlier to toggle their colours appropriately
+            is_planet = (
+                getattr(trace, "meta", None) is not None
+                and isinstance(trace.meta, dict)
+                and trace.meta.get("kind") == "Planet"
+            )
+            if is_planet:
+                name = str(trace.name)
+                trace.line.color = (
+                    PLANET_COLOURS_NIGHT.get(name, "rgba(220,220,220,0.7)")
+                    if night_mode else
+                    PLANET_COLOURS_DAY.get(name, "rgba(220,220,220,0.7)")
+                )
+                continue
+            
+            # every other non-planet is the default colour then
+            if trace.type in ("scatter", "scatter3d") and getattr(trace, "mode", None) == "lines":
+                trace.line.color = orbit_colour
+
+            # also colour input object epoch markers differently if day or night mode
+            meta = getattr(trace, "meta", None)
+            if isinstance(meta, dict) and meta.get("kind") == "epoch":
+                trace.marker.color = (
+                    "rgba(255,255,255,0.9)" if night_mode
+                    else "rgba(30,30,30,0.9)"
+                )
+
+        # apply object visibility
+        vis_o = set(visible_objids or [])
+        vis_p = set(visible_planets or [])
+
+        for trace in fig.data:
+            meta = getattr(trace, "meta", None)
+            kind = meta.get("kind") if isinstance(meta, dict) else None
+            
+            if kind == "Planet":
+                trace.visible = (str(getattr(trace, "name", "")) in vis_p)
+                continue
+
+            if getattr(trace, "type", None) in ("scatter", "scatter3d") and getattr(trace, "mode", None) == "lines":
+                name = str(getattr(trace, "name", ""))
+                if name and name != "ref-plane":
+                    trace.visible = (name in vis_o)
+
+            if isinstance(meta, dict) and meta.get("kind") == "epoch":
+                texts = getattr(trace, "text", None)
+                texts_list = [] if texts is None else list(texts)
+
+                base = "rgba(255,255,255,0.9)" if night_mode else "rgba(100,100,100,0.9)"
+                hidden = "rgba(0,0,0,0)"
+
+                trace.marker.color = [base if str(t) in vis_o else hidden for t in texts_list]
+
+        # if the view is 3d then set the reference plane opacity+colour
+        if view_3d:
+            for trace in fig.data:
+                if getattr(trace, "name", None) == "ref-plane":
+                    trace.opacity = opacity
+
+                    if plane_colour and "hex" in plane_colour:
+                        c = plane_colour["hex"]
+                        trace.update(colorscale=[[0,c], [1,c]], cmin=0, cmax=1, showscale=False)
+
+        # set up the background of the whole figure canvas + plotting region 
+        # so that they are transparent (ie page theme is controlling background,
+        # not plotly itself)
+        paper = "rgba(0,0,0,0)" if bg == "black" else "rgba(255,255,255,0)"
+        fig.update_layout(
+            paper_bgcolor=paper,
+            plot_bgcolor=paper,
+            font=dict(color=fg),
+            uirevision="keep"
+        )
+
+        # style the axis grids in 2d or 3d
+        if hasattr(fig, "update_xaxes"):
+            fig.update_xaxes(gridcolor=grid, zerolinecolor=zero)
+            fig.update_yaxes(gridcolor=grid, zerolinecolor=zero)
+
+        if getattr(fig.layout, "scene", None) is not None:
+            fig.update_scenes(
+                xaxis_gridcolor=grid, xaxis_zerolinecolor=zero,
+                yaxis_gridcolor=grid, yaxis_zerolinecolor=zero,
+                zaxis_gridcolor=grid, zaxis_zerolinecolor=zero
+            )
+        
+        # get current view state
+        view_state = view_state or {}
+        mode = "3d" if view_3d else "2d"
+
+        # if we're in the same view mode, reapply the stored view. this helps us 
+        # preserve the view across theme/origin/plane changes
+        if view_state.get("mode") == mode:
+            if mode == "3d" and view_state.get("camera") and getattr(fig.layout, "scene", None) is not None:
+                fig.update_layout(scene_camera=view_state["camera"])
+            if mode == "2d":
+                xr = view_state.get("xrange")
+                yr = view_state.get("yrange")
+                if xr is not None:
+                    fig.update_xaxes(range=xr, autorange=False)
+                if yr is not None:
+                    fig.update_yaxes(range=yr, autorange=False)
+        
+        # set the style of the outermost html container
+        shell_style = {
+            "height": "100vh",
+            "width": "100vw",
+            "margin": "0",
+            "padding": "0",
+            "backgroundColor": bg,
+            "color": fg
+        }
+        shell_class = "theme-dark" if night_mode else "theme-light"
+
+        # show/hide the 2D panel-mode selector under the view toggle
+        panel_controls_style = {"display": "none"} if view_3d else {}
+
+        # per-2D panel overlay base style
+        base_overlay = {
+            "position": "absolute",
+            "top": "10px",
+            "zIndex": 2000,
+            "padding": "10px 12px",
+            "borderRadius": "14px",
+            "background": theme["tab_bg"],
+            "border": f"1px solid {theme['border']}",
+            "backdropFilter": "blur(10px)",
+            "pointerEvents": "auto",
+            "display": "none"
+        }
+
+        single_style = dict(base_overlay)
+        left_style = dict(base_overlay)
+        right_style = dict(base_overlay)
+
+        # positions of dropdown menus
+        single_style["left"] = "25%"
+        single_style["transform"] = "translateX(-50%)"
+
+        left_style["left"] = "25%"
+        left_style["transform"] = "translateX(-50%)"
+
+        right_style["left"] = "75%"
+        right_style["transform"] = "translateX(-50%)"
+
+        if not view_3d:
+            if panel_mode == "single":
+                single_style["display"] = "block"
+            else:
+                left_style["display"] = "block"
+                right_style["display"] = "block"
+
+        return fig, shell_style, shell_class, panel_controls_style, single_style, left_style, right_style
+
+    # auto-open the browser
+    def open_browser():
+        webbrowser.open_new("http://127.0.0.1:8050/")
+
+    # this is a reloader that prevents us accidentally opening two tabs
+    # at the same time (this kept happening to me in debugging), 
+    # giving the server time to start before the browser visits the url 
+    # (see https://stackoverflow.com/questions/9449101/how-to-stop-flask-from-initialising-twice-in-debug-mode?)
+    if os.environ.get("WERKZEUG_RUN_MAIN") == "true":
+        threading.Timer(1.0, open_browser).start()
+
+    # avoid spam in the terminal 
+    log = logging.getLogger("werkzeug")
+    log.setLevel(logging.ERROR)
+
+    # now run the server!
+    app.run(debug=False, use_reloader=True)
\ No newline at end of file
diff --git a/src/layup/data/app.css b/src/layup/data/app.css
new file mode 100644
index 00000000..6cfc78a4
--- /dev/null
+++ b/src/layup/data/app.css
@@ -0,0 +1,124 @@
+/* --- layout ---*/
+/*
+remove the browser defaults and force full view
+*/
+html, body {
+  margin: 0 !important;
+  padding: 0 !important;
+  height: 100% !important;
+  width: 100% !important;
+  overflow: hidden;  /* <-- no page scrolling! */
+}
+
+/*
+because we have multiple wrapper divs around react, we must explicitly
+say to fill the view or the plots won't size correctly 
+*/
+#react-entry-point,
+#react-entry-point > div,
+#_dash-app-content {
+  height: 100% !important;
+  width: 100% !important;
+}
+
+
+/* --- themes --- */
+/* 
+dark theme stuff, allows us to just swap the class on the container
+when we toggle the theme button
+*/
+.theme-dark {
+  --bg: #000000;
+  --fg: #ffffff;
+  --muted: rgba(255,255,255,0.82);
+  --grid: rgba(255,255,255,0.08);
+  --rail: rgba(255,255,255,0.20);
+  --track: rgba(255,255,255,0.35);
+  --handle: rgba(255,255,255,0.85);
+}
+
+/* 
+light theme stuff, same as dark theme but inverted basically
+*/
+.theme-light {
+  --bg: #ffffff;
+  --fg: #111111;
+  --muted: rgba(0,0,0,0.75);
+  --grid: rgba(0,0,0,0.10);
+  --rail: rgba(0,0,0,0.15);
+  --track: rgba(0,0,0,0.30);
+  --handle: rgba(0,0,0,0.70);
+}
+
+
+/* --- styling --- */
+/*
+this is the "shell" of the app behind the figure and controls, and 
+because the plotly backgrounds are transparent, /this/ is the colour
+*/
+.app-shell {
+  background: var(--bg);
+  color: var(--fg);
+  min-height: 100vh;
+}
+
+/*
+raise the plotly modebar with the camera controls and save plot button
+avove the controls drawer so it remains clickable
+*/
+.js-plotly-plot .plotly .modebar {
+  z-index: 6000 !important;
+}
+
+/* slider stuff */
+/*
+all of this is just restyling the slider based on the active theme
+*/
+.rc-slider-mark-text {
+  color: var(--muted) !important; /* <-- tick labels */
+}
+
+.rc-slider-rail {
+  background-color: var(--rail) !important; /* <-- inactive portion */
+}
+
+.rc-slider-track {
+  background-color: var(--track) !important; /* <-- active portion */
+}
+
+.rc-slider-handle {
+  border: 2px solid var(--handle) !important; /* <-- handle outline */
+  background-color: var(--bg) !important; /* <-- handle fill */
+}
+
+/* drawer / controls stuff */
+/*
+same as slider, just make the text follow the active theme 
+*/
+#controls-drawer {
+  color: var(--fg);
+}
+
+
+/* --- latex font --- */
+/*
+i couldn't find an exact latex (computer modern) font sheet, so 
+i'm using the next closest thing i could find
+*/
+.toggle-label {
+  font-family: "KaTeX_Main", "Latin Modern Roman", "Computer Modern", serif;
+  font-size: 17px;
+  font-weight: 400;
+  letter-spacing: 0.1px;
+  color: var(--fg);
+  opacity: 0.9;
+}
+
+/*
+in theory this should apply the font across the entire app so everything
+is consistent - in practice plotly renders plots without seeing the 
+style sheet. what can ya do ¯\_(ツ)_/¯
+*/
+#app-shell, #app-shell * {
+  font-family: "KaTeX_Main", "Latin Modern Roman", "Computer Modern", serif;
+}
diff --git a/src/layup/orbit_maths.py b/src/layup/orbit_maths.py
new file mode 100644
index 00000000..efa2d01d
--- /dev/null
+++ b/src/layup/orbit_maths.py
@@ -0,0 +1,631 @@
+import logging
+from dataclasses import dataclass
+from typing import Literal, Optional
+
+import numpy as np
+
+from layup.utilities.layup_configs import LayupConfigs
+from layup.utilities.bootstrap_utilties.download_utilities import make_retriever
+
+from sorcha.ephemeris.simulation_geometry import equatorial_to_ecliptic
+from sorcha.ephemeris.simulation_constants import ECL_TO_EQ_ROTATION_MATRIX, EQ_TO_ECL_ROTATION_MATRIX
+from sorcha.ephemeris.orbit_conversion_utilities import universal_cartesian
+
+from assist import Ephem
+
+logger = logging.getLogger(__name__)
+
+# --- orbit types and their columns ---
+ORBIT_FORMAT = Literal["BCART", "BCOM", "BKEP", "CART", "COM", "KEP"]
+REQUIRED_COLUMN_NAMES: dict[str, list[str]] = {
+    "BCART": ["ObjID", "FORMAT", "x", "y", "z", "xdot", "ydot", "zdot", "epochMJD_TDB"],
+    "BCOM": ["ObjID", "FORMAT", "q", "e", "inc", "node", "argPeri", "t_p_MJD_TDB", "epochMJD_TDB"],
+    "BKEP": ["ObjID", "FORMAT", "a", "e", "inc", "node", "argPeri", "ma", "epochMJD_TDB"],
+    "CART": ["ObjID", "FORMAT", "x", "y", "z", "xdot", "ydot", "zdot", "epochMJD_TDB"],
+    "COM": ["ObjID", "FORMAT", "q", "e", "inc", "node", "argPeri", "t_p_MJD_TDB", "epochMJD_TDB"],
+    "KEP": ["ObjID", "FORMAT", "a", "e", "inc", "node", "argPeri", "ma", "epochMJD_TDB"],
+}
+
+PLANET_PERIOD_DAYS = {
+    "Mercury": 87.969,
+    "Venus": 224.701,
+    "Earth": 365.256,
+    "Mars": 686.980,
+    "Jupiter": 4332.589,
+    "Saturn": 10759.22,
+    "Uranus": 30688.5,
+    "Neptune": 60182.0
+}
+
+@dataclass(frozen=True)
+class ClassicalConic:
+    "Data class for each object conic section"
+
+    obj_id: np.ndarray
+    "object identifer tag"
+    L: np.ndarray
+    "object semilatus rectum (au)"
+    e: np.ndarray
+    "object eccentricity"
+    inc: np.ndarray
+    "object inclination (radians)"
+    node: np.ndarray
+    "object longitude of ascending node (radians)"
+    argp: np.ndarray
+    "object argument of perihelion (radians)"
+    epochMJD_TDB: np.ndarray
+    "epoch of object observation (MJD TDB)"
+
+
+# --- converter ---
+def convert_cart_to_classical_conic(
+        rows: np.ndarray,
+        mu: float
+) -> ClassicalConic:
+    """
+    Convert cartesian elements into classical conic elements (L, e, i, Omega, omega)
+
+    Parameters
+    -----------
+    rows : numpy structured array
+        Array with all of the orbits (shape = (N,), i.e. one orbit per row/record)
+
+    mu : float
+        Standard gravitional parameter (au^3 / day^2)
+
+    Returns
+    --------
+    ClassicalConic : object
+        Object instance containing N orbits and their classical elements
+    """
+    # read each orbit id tag
+    obj_id = rows["ObjID"].astype(str)
+
+    # set up our position and velocity vectors
+    r = np.vstack([rows["x"], rows["y"], rows["z"]]).T.astype(float)
+    v = np.vstack([rows["xdot"], rows["ydot"], rows["zdot"]]).T.astype(float)
+
+    # calculate specific angular momentum:
+    # hvec = r x v
+    # hnorm = |hvcec|
+    hvec = np.cross(r, v)
+    hnorm = np.linalg.norm(hvec, axis=1)
+
+    # calculate inclination:
+    # i = cos^-1(h_z / |h|)
+    # notes: hvec[:, 2] = h_z, we use np.maximum and np.clip to avoid 
+    # division by zero and floating point arithmetic giving answers that 
+    # aren't in the range -1 <= h_z / |h| <= 1
+    incl = np.arccos(np.clip(hvec[:, 2] / np.maximum(hnorm, 1e-30), -1.0, 1.0))
+
+    # calculate the node vector:
+    # nvec = zhat x hvec
+    # nnorm = |nvec|
+    zhat = np.array([0.0, 0.0, 1.0])
+    nvec = np.cross(np.tile(zhat, (r.shape[0], 1)), hvec)
+    nnorm = np.linalg.norm(nvec, axis=1)
+
+    # calculate longitude of ascending node:
+    # Omega = atan2(n_y, n_x)
+    # notes: doing arctan2 rather than arccos just to skip having
+    # to check quadrants when nhat dot jhat > or < 0, then wrapping
+    # from what atan2 returns (-pi, pi] to [0, 2pi)
+    node = np.arctan2(nvec[:, 1], nvec[:, 0]) % (2 * np.pi)
+
+    # calculate eccentricity vector:
+    # evec = (v x hvec)/mu - r/|r|
+    # e = |e| <- this is eccentricity
+    rnorm = np.linalg.norm(r, axis=1)
+    evec = (np.cross(v, hvec) / mu) - (r / rnorm[:, None])
+    e = np.linalg.norm(evec, axis=1)
+
+    # calculate semilatus rectum:
+    # L = |h|^2 / mu
+    L = hnorm**2 / mu
+
+    # np.maxmimum prevents us doing division by 0 for circular
+    # orbits (e=0) or equatorial orbits (nnorm = 0)
+    e = np.maximum(e, 1e-30)
+    nnorm = np.maximum(nnorm, 1e-30)
+
+    # calculate the argument of perihelion:
+    # omega = atan2(sin(omega), cos(omega))
+    # cos(omega) = (nvec dot evec) / (|n||e|)
+    # sin(omega) = ((nvec x evec) dot hvec) / (|n||e||h|)
+    # note: we're clipping again for the same reasons as above
+    # (floating point arithmetic + division by zero), and we do 
+    # np.sum as we have an (N, 3) list of orbits in e.g. nvec, so
+    # doing np.dot would result in matrix multiplication (if pedro
+    # reads this in future, yes np.einsum does this but i hate the 
+    # notation :p). finally arctan2 once again solves quadrant issues
+    cosw = np.sum(nvec * evec, axis=1) / (nnorm * e)
+    cosw = np.clip(cosw, -1.0, 1.0)
+    sinw = np.sum(np.cross(nvec, evec) * hvec, axis=1) / (nnorm * e * np.maximum(hnorm, 1e-30))
+    argp = (np.arctan2(sinw, cosw) % (2 * np.pi))
+
+    # finally check if orbit is sat in reference plane, if so we 
+    # overwrrite Omega to be = 0, and even though omega is strictly
+    # undefined in this case, perihelion direction isn't due to evec,
+    # which we need to draw the orbit later, therefore we just recalc
+    # it as the angle from the ref x axis to perihelion again via atan2
+    equatorial = nnorm < 1e-12
+    if np.any(equatorial):
+        node[equatorial] = 0.0
+        argp[equatorial] = (np.arctan2(evec[equatorial, 1], evec[equatorial, 0]) % (2 * np.pi))
+
+    return ClassicalConic(obj_id=obj_id, L=L, e=e, inc=incl, node=node, argp=argp, epochMJD_TDB=rows["epochMJD_TDB"])
+
+
+# --- frame swapping ---
+def rv_to_cart(
+        obj_id: np.ndarray,
+        r: np.ndarray,
+        v: np.ndarray,
+        epochMJD_TDB: np.ndarray
+) -> np.ndarray:
+    """
+    Wrapper function to create structured array of cartesian elements from position+velocity state vectors
+
+    Parameters
+    -----------
+    obj_id : numpy string array 
+        Object identifier tags
+
+    r : numpy float array
+        Object position state vector with shape (N, 3) (au)
+
+    v : numpy float array
+        Object velocity state vector with shape (N, 3) (au/day)
+
+    epochMJD_TDB: numpy float array
+        Object epoch with shape (N, 3) (MJD TDB)
+
+    Returns
+    --------
+    out : numpy structured array
+        Array containing the cartesian elements (x,y,z,vx,vy,vz) with shape (N,)
+    """
+    out = np.empty(r.shape[0], dtype=[("ObjID","U64"), ("x","f8"), ("y","f8"), ("z","f8"), ("xdot","f8"), ("ydot","f8"), ("zdot","f8"), ("epochMJD_TDB","f8")])
+    out["ObjID"] = obj_id.astype("U64")    
+    out["x"], out["y"], out["z"] = r[:,0], r[:,1], r[:,2]
+    out["xdot"], out["ydot"], out["zdot"] = v[:,0], v[:,1], v[:,2]
+    out["epochMJD_TDB"] = epochMJD_TDB.astype("f8")
+    return out
+
+def to_rv(
+        rows: np.ndarray,
+        fmt: ORBIT_FORMAT,
+        mu_sun: float,
+        mu_total: float
+) -> tuple[np.ndarray, np.ndarray]:
+    """
+    Convert orbits into cartesian state vectors regardless of format utilising Sorcha functions.
+    Cometary/keplerian formats are converted using universal_cartesian()
+
+    Parameters
+    -----------
+    rows : numpy structured array
+        Array with all of the orbits (shape = (N,), i.e. one orbit per row/record)
+
+    fmt : str
+        Format of the orbit. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP" 
+
+    mu_sun : float
+        Standard (heliocentric) gravitional parameter (au^3 / day^2)
+
+    mu_total : float
+        Standard (barycentric) gravitional parameter (au^3 / day^2)
+
+    Returns
+    --------
+    r : numpy float array
+        Object position state vector with shape (N, 3) (au)
+
+    v : numpy float array
+        Object velocity state vector with shape (N, 3) (au/day)
+    """
+    epochJD = rows["epochMJD_TDB"].astype(float) + 2400000.5
+
+    # if it's cartesian we can just pass it straight through
+    if fmt in ("CART", "BCART"):
+        r = np.vstack([rows["x"], rows["y"], rows["z"]]).T.astype(float)
+        v = np.vstack([rows["xdot"], rows["ydot"], rows["zdot"]]).T.astype(float)
+        return r, v
+    # if it's cometary however, we convert to cartesian for easy origin shifting
+    if fmt in ("COM", "BCOM"):
+        mu = mu_sun if fmt == "COM" else mu_total
+
+        q = rows["q"].astype(float)
+        e = rows["e"].astype(float)
+        incl = np.deg2rad(rows["inc"].astype(float))
+        node = np.deg2rad(rows["node"].astype(float))
+        argp = np.deg2rad(rows["argPeri"].astype(float))
+        tpJD = rows["t_p_MJD_TDB"].astype(float) + 2400000.5
+
+        r = np.empty((rows.size, 3), dtype=float)
+        v = np.empty((rows.size, 3), dtype=float)
+
+        for i in range(rows.size):
+            x, y, z, vx, vy, vz = universal_cartesian(
+                mu, q[i], e[i], incl[i], node[i], argp[i], tpJD[i], epochJD[i]
+            )
+            r[i] = (x, y, z)
+            v[i] = (vx, vy, vz)
+        
+        return r, v
+    # same for keplerian orbits
+    if fmt in ("KEP", "BKEP"):
+        mu = mu_sun if fmt == "KEP" else mu_total
+
+        a = rows["a"].astype(float)
+        e = rows["e"].astype(float)
+        incl = np.deg2rad(rows["inc"].astype(float))
+        node = np.deg2rad(rows["node"].astype(float))
+        argp = np.deg2rad(rows["argPeri"].astype(float))
+        M = np.deg2rad(rows["ma"].astype(float))
+
+        M_wrap = M.copy()
+        idx = M_wrap > np.pi
+        M_wrap[idx] -= 2*np.pi
+
+        tpJD = epochJD - M_wrap * np.sqrt(a**3/mu)
+        q = a * (1.0 - e)
+
+        r = np.empty((rows.size, 3), dtype=float)
+        v = np.empty((rows.size, 3), dtype=float)
+
+        for i in range(rows.size):
+            x, y, z, vx, vy, vz = universal_cartesian(
+                mu, q[i], e[i], incl[i], node[i], argp[i], tpJD[i], epochJD[i]
+            )
+            r[i] = (x, y, z)
+            v[i] = (vx, vy, vz)
+        
+        return r, v
+    
+    logger.error(f"Unsupported format: {fmt}")
+    raise ValueError(f"Unsupported format: {fmt}")
+
+def build_ephem_and_mus(cache_dir: Optional[str] = None) -> tuple[Ephem, float, float]:
+    """
+    Create Assist instance utilising Layup functions in order to find standard gravitationl parameters 
+    
+    Parameters
+    -----------
+    cache_dir : str, optional
+        Cache directory containing Assist+Rebound files if used
+
+    Returns
+    --------
+    ephem : Assist object
+        Assist instance containing the Sun, planets, and massive perturbers
+
+    mu_sun : float
+        Standard (heliocentric) gravitional parameter (au^3 / day^2)
+
+    mu_total : float
+        Standard (barycentric) gravitional parameter (au^3 / day^2)
+    """
+    # yoink layup's auxiliary config class to locate the user's cached files 
+    configs = LayupConfigs()
+    aux = configs.auxiliary
+
+    retriever = make_retriever(aux, cache_dir)
+    ephem = Ephem(planets_path=retriever.fetch(aux.jpl_planets), asteroids_path=retriever.fetch(aux.jpl_small_bodies))
+    
+    # calculate mu same way as in sorcha
+    mu_sun = ephem.get_particle("Sun", 0).m
+    mu_total = sum(sorted([ephem.get_particle(i,0).m for i in range(27)]))
+
+    return ephem, mu_sun, mu_total
+
+def convert_sun_to_baryecliptic(
+        ephem: Ephem,
+        epochJD: np.ndarray
+) -> tuple[np.ndarray, np.ndarray]:
+    """
+    Function to create translation vectors to go from barycentric to heliocentric origins
+    
+    Parameters
+    -----------
+    ephem : assist Ephem object
+        Assist built ephemeris of the Sun, planets, and massive perturbers
+
+    epochJD : numpy float array
+        Array of input object epochs in Julian dates of shape (N,)
+
+    Returns
+    --------
+    S_r : numpy float array
+        Translation barycentric -> heliocentric position vector of shape (N,3)
+
+    S_v : numpy float array
+        Translation barycentric -> heliocentric velocity vector of shape (N,3)
+    """
+    # we'll build a cache of the sun's state vectors in all four combinations here
+    cache: dict[float, object] = {}
+    S_r = np.empty((epochJD.size, 3), dtype=float)
+    S_v = np.empty((epochJD.size, 3), dtype=float)
+
+    # we're just using assist here to get the sun's position at each epoch of our objects
+    for i, t in enumerate(epochJD):
+        t_key = float(t)
+        if t_key not in cache:
+            cache[t_key] = ephem.get_particle("Sun", t_key - ephem.jd_ref)
+        sun = cache[t_key]
+
+        # quick convert to ecliptic as assist is in equatorial
+        S_r[i] = -equatorial_to_ecliptic([sun.x, sun.y, sun.z])
+        S_v[i] = -equatorial_to_ecliptic([sun.vx, sun.vy, sun.vz])
+
+    return S_r, S_v
+
+# --- build all variants ---
+def prepopulate_orbit_variants(
+        rows: np.ndarray,
+        orbit_format: ORBIT_FORMAT,
+        input_plane: Literal["equatorial", "ecliptic"],
+        input_origin: Literal["heliocentric", "barycentric"]
+) -> tuple[
+    dict[tuple[str, str], ClassicalConic],
+    dict[tuple[str, str], np.ndarray],
+    dict[tuple[str, str], np.ndarray],
+    dict[tuple[str, str], np.ndarray]
+]:
+    """
+    Create an output cache of input object class instances, an empty placeholder dict for their 
+    associated orbit lines, the Sun's positions, and the object's positions in all four combinations 
+    of plane+origin
+
+    Parameters
+    -----------
+    rows : numpy structured array
+        Array with all of the orbits (shape = (N,), i.e. one orbit per row/record)
+
+    orbit_format : str
+        String detailing the input orbit format. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP" 
+
+    input_plane : str
+        Input reference plane of the orbits. Must be one of "equatorial" or "ecliptic"
+
+    input_origin : str
+        Input origin of the orbits. Must be one of "heliocentric" or "barycentric"
+    
+    Returns
+    --------
+    canon_cache : dict of objects
+        Dictionary with the conic section class instances of each object and their properties
+    
+    lines_cache : dict of numpy array
+        Dictionary of arrays with the orbit lines for each object in each plane+origin combination
+
+    sunpos_cache : dict of numpy array
+        Dictionary of arrays with the Sun positions in each plane+origin combination
+
+    pos_cache : dict of numpy array
+        Dictionary of arrays with object positions in each plane+origin combination
+    """
+    # grab our planets+major perturbers and solar gravitational parameters
+    # # (mu_sun = heliocentric, mu_total = barycentric) 
+    ephem, mu_sun, mu_total = build_ephem_and_mus()
+    
+    obj_id = rows["ObjID"].astype(str)
+    epochJD = rows["epochMJD_TDB"].astype(float) + 2400000.5
+
+    # grab state vectors
+    r_raw, v_raw = to_rv(rows, orbit_format, mu_sun, mu_total)
+    S_r, S_v = convert_sun_to_baryecliptic(ephem, epochJD)
+
+    # everything is easier if we start from one frame+origin combo, so let's choose
+    # heliocentric ecliptic and convert equa -> ecl first to this if needs be
+    if input_plane == "equatorial":
+        r_raw = np.dot(r_raw, EQ_TO_ECL_ROTATION_MATRIX)
+        v_raw = np.dot(v_raw, EQ_TO_ECL_ROTATION_MATRIX)
+    
+    # again, easier if it's heliocentric ecliptic, so convert bary -> helio
+    r_helio_eclipt = r_raw.copy()
+    v_helio_eclipt = v_raw.copy()
+    if input_origin == "barycentric":
+        r_helio_eclipt = r_helio_eclipt + S_r
+        v_helio_eclipt = v_helio_eclipt + S_v
+
+    # now we can find heliocentric equatorial via obliquity rotation matrix
+    r_helio_equa = np.dot(r_helio_eclipt, ECL_TO_EQ_ROTATION_MATRIX)
+    v_helio_equa = np.dot(v_helio_eclipt, ECL_TO_EQ_ROTATION_MATRIX)
+
+    # barycentric ecliptic is just a subtraction of the sun's barycentre state vector
+    r_bary_eclipt = r_helio_eclipt - S_r
+    v_bary_eclipt = v_helio_eclipt - S_v
+
+    # and barycentric equatorial is another obliquity rotation matrix
+    r_bary_equa = np.dot(r_bary_eclipt, ECL_TO_EQ_ROTATION_MATRIX)
+    v_bary_equa = np.dot(v_bary_eclipt, ECL_TO_EQ_ROTATION_MATRIX)
+
+    # now we build up our cache of different orbit lines
+    canon_cache: dict[tuple[str, str], ClassicalConic] = {}
+    lines_cache: dict[tuple[str, str], np.ndarray] = {}
+
+    variants = {
+        ("helio", "ecl"): (r_helio_eclipt, v_helio_eclipt, mu_sun),
+        ("helio", "equ"): (r_helio_equa, v_helio_equa, mu_sun),
+        ("bary", "ecl"): (r_bary_eclipt, v_bary_eclipt, mu_total),
+        ("bary", "equ"): (r_bary_equa, v_bary_equa, mu_total),
+    }
+
+    # these are for the scatter marker positions of the sun and the objects themselves
+    sunpos_cache = {
+        ("helio", "ecl"): np.array([0.0, 0.0, 0.0]),
+        ("helio", "equ"): np.array([0.0, 0.0, 0.0]),
+        ("bary", "ecl"): (-S_r[0]),
+        ("bary", "equ"): (np.dot(-S_r[0], ECL_TO_EQ_ROTATION_MATRIX)),
+    }
+
+    pos_cache: dict[tuple[str, str], np.ndarray] = {}
+
+    for key, (r_i, v_i, mu_i) in variants.items():
+        pos_cache[key] = r_i
+        cart_rows = rv_to_cart(obj_id, r_i, v_i, rows["epochMJD_TDB"].astype(float))
+        canon_cache[key] = convert_cart_to_classical_conic(cart_rows, mu_i)
+
+    return canon_cache, lines_cache, sunpos_cache, pos_cache
+
+
+# --- orbit line generation ---
+def conic_lines_from_classical_conic(
+        canon: ClassicalConic,
+        n_points: int = 200,
+        r_max: float = 50.0
+) -> np.ndarray:
+    """
+    Given a set of classical conic elements (L, e, i, Omega, omega), draw the line of the orbit via
+    conic section (see page 27 onwards in "Solar System Dynamics" by Murray & Dermott)
+
+    Parameters
+    -----------
+    canon : object
+        Object instance containing N orbits and their classical elements
+
+    n_points : int, optional (default=200)
+        Number of points to use to construct the line
+
+    r_max : float, optional (default=50.0 au)
+        Maximum distance to render out to for hyperbolic orbits
+
+    Returns
+    --------
+    r : numpy float array
+        Object position state vector with shape (N, n_points, 3) (au)
+    """
+    # unpack classical elements for readability
+    e = canon.e
+    L = canon.L
+
+    # set up true anomaly array
+    nu = np.empty((e.size, n_points))
+
+    # which orbits are elliptical or hyperbolic (and near-parabolic)
+    ell = e < 1.0
+    hyp = ~ell
+
+    # if elliptical, we just draw it from -pi to pi so it's centered on 
+    # perihelion rather than 0 to 2pi
+    if np.any(ell):
+        nu[ell] = np.linspace(-np.pi, np.pi, n_points)
+
+    # if hyperbolic, we want to draw the orbit out to some max position
+    # r_max, so our maximum angular extent is calculated as:
+    # nu_max = arccos( (L/r_max - 1)/e )
+    # then we make our nu array by just making it as [-nu_max, +nu_max]
+    if np.any(hyp):
+        c = (L[hyp] / r_max - 1.0) / np.maximum(e[hyp], 1e-15)
+        c = np.clip(c, -1.0, 1.0)
+        nu_max = np.arccos(c)
+        t = np.linspace(-1.0, 1.0, n_points)
+        nu[hyp] = nu_max[:, None] * t
+
+    # now we calculate radial distance of the conic section via the polar
+    # coordinates equation:
+    # r = L / (1 + e cos(nu))
+    # note: as always we are preventing division by zero via np.maximum
+    rdist = L[:, None] / np.maximum(1.0 + e[:, None] * np.cos(nu), 1e-12)
+
+    # now in the perifocal frame (ie origin at focus, q1 towards perihelion),
+    # the orbit will be in the q1q2 plane:
+    # qvec = (q1, q2, q3) = (r cos(nu), r sin(nu), 0)
+    q1 = rdist * np.cos(nu)
+    q2 = rdist * np.sin(nu)
+    q3 = np.zeros_like(q1)
+
+    # and now we rotate back into inertial frame via rotation matrix:
+    # R = R_z(Omega)R_x(i)R_z(omega)
+    c0, s0 = np.cos(canon.node), np.sin(canon.node)
+    co, so = np.cos(canon.argp), np.sin(canon.argp)
+    ci, si = np.cos(canon.inc), np.sin(canon.inc)
+
+    # we now find the position vector rvec by:
+    # rvec = (x, y, z) = R qvec
+    x = (c0*co - s0*so*ci)[:, None]*q1 + (-c0*so - s0*co*ci)[:, None]*q2
+    y = (s0*co + c0*so*ci)[:, None]*q1 + (-s0*so + c0*co*ci)[:, None]*q2
+    z = (so*si)[:, None]*q1 + (co*si)[:, None]*q2
+    r = np.stack([x, y, z], axis=-1)
+
+    return r
+
+def build_planet_lines_cache(
+        ephem: Ephem,
+        epochJD_center: float,
+        planet_names: list[str],
+        n_points: int = 800
+) -> tuple[dict[tuple[str, str], np.ndarray], np.ndarray]:
+    """
+    
+    Parameters
+    -----------
+    ephem : Assist object
+        Assist instance containing the Sun, planets, and massive perturbers
+
+    epochJD_center : float
+        Reference epoch to use to sample ellipse symmetrically over one orbtial period (JD)
+    
+    planet_names : list
+        List of planet names as strings
+
+    n_points : int, optional (default=800)
+        Number of points to use to construct the line
+
+    Returns 
+    --------
+    planet_lines_cache : dict of arrays
+        Dictiionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        combination of shape (n_planets, n_points, 3)
+    
+    planet_id : numpy string array
+        Array containing ID tags for each planet of shape (n_planets,)
+    """
+    # much like the object orbits, it will be easier if we start from some frame+origin and
+    # convert to the other 3 from there. we choose barycentric equatorial here 
+    planet_id = np.array(planet_names, dtype="U32")
+    lines_bary_equ = np.empty((len(planet_names), n_points, 3), dtype=float)
+
+    for p, name in enumerate(planet_names):
+        P = PLANET_PERIOD_DAYS[name]
+        if P is None:
+            logger.error(f"Missing period for planet: '{name}' in PLANET_PERIOD_DAYS")
+            raise KeyError(f"Missing period for planet: '{name}' in PLANET_PERIOD_DAYS")
+        
+        # basically build an ellipse of times to get the planet positions at where the epochJD_center
+        # is a reference epoch, which should just be the epoch of the first input object (no scatter
+        # points so really just need the shape of orbit) 
+        epochJD = np.linspace(epochJD_center - float(P)/2.0, epochJD_center + float(P)/2.0, n_points)
+
+        for i, jd in enumerate(epochJD):
+            part = ephem.get_particle(name, float(jd) - ephem.jd_ref)
+            lines_bary_equ[p, i, :] = (part.x, part.y, part.z)
+
+    # this looks weird but it's just being fancy and instead of looping over it all we reshape 
+    # lines_bary_equ from (N_planets, N_points, 3) -> (N_planets*N_points, 3) (ie one xyz per row)
+    # so we can apply rotation matrix quickly and easily. then we do the inverse reshape back 
+    lines_bary_ecl = np.dot(lines_bary_equ.reshape(-1, 3), EQ_TO_ECL_ROTATION_MATRIX).reshape(lines_bary_equ.shape)
+
+    # because the sun has different positions at each planet's epochs, we need to redo S_r here
+    S_r_ecl = np.empty_like(lines_bary_ecl)
+    S_r_equ = np.empty_like(lines_bary_ecl)
+
+    for p, name in enumerate(planet_names):
+        P = PLANET_PERIOD_DAYS[name]
+        epochJD = np.linspace(epochJD_center - float(P)/2.0, epochJD_center + float(P)/2.0, n_points)
+
+        S_r, _ = convert_sun_to_baryecliptic(ephem, epochJD)
+        S_r_ecl[p, :, :] = S_r
+        S_r_equ[p, : ,:] = np.dot(S_r, ECL_TO_EQ_ROTATION_MATRIX)
+
+    # now we can simply build our cache of planets
+    planet_lines_cache: dict[tuple[str, str], np.ndarray] = {}
+
+    planet_lines_cache[("bary", "equ")] = lines_bary_equ
+    planet_lines_cache[("bary", "ecl")] = lines_bary_ecl
+
+    planet_lines_cache[("helio", "equ")] = lines_bary_equ + S_r_equ
+    planet_lines_cache[("helio", "ecl")] = lines_bary_ecl + S_r_ecl
+
+    return planet_lines_cache, planet_id
diff --git a/src/layup/visualize.py b/src/layup/visualize.py
new file mode 100644
index 00000000..b105b4f9
--- /dev/null
+++ b/src/layup/visualize.py
@@ -0,0 +1,402 @@
+import logging
+from pathlib import Path
+from typing import Literal, Optional
+
+import numpy as np
+
+from layup.utilities.file_io.CSVReader import CSVDataReader
+from layup.utilities.file_io.HDF5Reader import HDF5DataReader
+from layup.utilities.data_processing_utilities import get_format
+
+from layup.orbit_maths import REQUIRED_COLUMN_NAMES, build_ephem_and_mus, build_planet_lines_cache, conic_lines_from_classical_conic, prepopulate_orbit_variants
+from layup.dash_ui import plotly_2D, plotly_3D, run_dash_app
+
+logger = logging.getLogger(__name__)
+
+DASH_THREAD = None
+
+def build_fig_caches(
+        rows: np.ndarray,
+        orbit_format: str,
+        input_plane: Literal["equatorial", "ecliptic"],
+        input_origin: Literal["heliocentric", "barycentric"],
+        n_points: int = 500,
+        r_max: float = 50.0,
+        cache_dir: Optional[str] = None
+):
+    """
+    
+    """
+    # get the assist ephem object and build epoch array 
+    logger.info(f"Building Assist ephemeris for planets")
+    ephem, _, _ = build_ephem_and_mus(cache_dir)
+    epochJD_center = float(rows["epochMJD_TDB"].astype(float)[0] + 2400000.5)
+
+    # construct planet lines 
+    logger.info(f"Constructing planet orbit lines")
+    planet_names = ["Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune"]
+    planet_lines_cache, planet_id = build_planet_lines_cache(
+        ephem,
+        epochJD_center,
+        planet_names=planet_names,
+        n_points=900,
+    )
+
+    # construct input orbits lines, scatters, and sun positions
+    logger.info(f"Constructing input object orbit lines")
+    conic_cache, lines_cache, sunpos_cache, pos_cache = prepopulate_orbit_variants(
+        rows,
+        orbit_format,
+        input_plane=input_plane,
+        input_origin=input_origin,
+    )
+
+    for key, conic in conic_cache.items():
+        lines_cache[key] = conic_lines_from_classical_conic(
+            conic,
+            n_points=n_points,
+            r_max=r_max,
+        )
+
+    logger.info(f"Creating cache of all input object and/or planet lines in heliocentric+barycentric && equatorial+ecliptic frames")
+    # create caches of all figure combinations
+    PANELS = ("XY", "XZ", "YZ")
+    fig2d_cache = {}
+    fig3d_cache = {}
+    for key in conic_cache.keys():
+        # 3D has few variants
+        fig3d_cache[key] = plotly_3D(
+            lines_cache[key],
+            conic_cache[key],
+            sun_xyz=sunpos_cache[key],
+            orbit_pos=pos_cache[key],
+            planet_lines=planet_lines_cache[key],
+            planet_id=planet_id,
+            plot_sun=True,
+            return_fig=True,
+        )
+
+        # 2D however has ref plane + origin + XY/XZ/YZ panel combinations + single or double panels
+        # first do single panel variants
+        for p in PANELS:
+            fig2d_cache[(key[0], key[1], "single", p, None)] = plotly_2D(
+                lines_cache[key],
+                conic_cache[key],
+                sun_xyz=sunpos_cache[key],
+                orbit_pos=pos_cache[key],
+                planet_lines=planet_lines_cache[key],
+                planet_id=planet_id,
+                plot_sun=True,
+                panel=p,
+                return_fig=True,
+            )
+        
+        # now do double panel variants:
+        for pL in PANELS:
+            for pR in PANELS:
+                fig2d_cache[(key[0], key[1], "double", pL, pR)] = plotly_2D(
+                    lines_cache[key],
+                    conic_cache[key],
+                    sun_xyz=sunpos_cache[key],
+                    orbit_pos=pos_cache[key],
+                    planet_lines=planet_lines_cache[key],
+                    planet_id=planet_id,
+                    plot_sun=True,
+                    panels=(pL, pR),
+                    return_fig=True,
+                )
+    
+    return fig2d_cache, fig3d_cache
+
+
+def visualize_cli(
+        input: str,
+        input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
+        input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
+        num_orbs: int = 100,
+        block_size: int = 10000,
+        n_points: int = 500,
+        r_max: float = 50.0,
+        random: bool = False,
+        cache_dir: Optional[str] = None
+):
+    """
+    Create visualisation plots of a given set of input orbits from the command line
+
+    Parameters
+    -----------
+    input : str
+        Input file path
+
+    input_plane : str, optional (default=None)
+        Input file reference plane. Must be one of "equatorial", "ecliptic"
+
+    input_origin : str, optional (default=None)
+        Input file frame of origin. Must be one of "heliocentric", "barycentric"
+
+    num_orbs : int, optional (default=100)
+        Number of orbits to plot at once
+
+    block_size : int, optional (default=10000)
+        Number of rows to read per time in the input file reader
+
+    n_points : int, optional (default=500)
+        Number of points sampled when constructing the line
+
+    r_max : float, optional (default=50 au)
+        Maximum distance to render hyperbolic orbits out to 
+
+    random : bool, optional (default=False)
+        Flag to turn on/off random orbit plotting
+
+    cache_dir : str, optional (default=None)
+        Path to directory of cached auxiliary data
+    """
+
+    logger.info(f"Reading input file: {input}")
+    # read in input
+    input_file = Path(input)
+    if not input_file.exists():
+        logger.error(f"File not found: {input}")
+        raise FileNotFoundError(input_file)
+    
+    # probe reader to get format
+    logger.info(f"Probing input to infer orbit origin, reference plane, and format...")
+    suffix = input_file.suffix.lower()
+    if suffix == ".csv":
+        probe_reader = CSVDataReader(
+            input_file,
+            format_column_name="FORMAT",
+            required_column_names=["FORMAT"]
+        )
+    else:
+        probe_reader = HDF5DataReader(
+            input_file,
+            format_column_name="FORMAT",
+            required_column_names=["FORMAT"]
+        )
+    probe_rows = probe_reader.read_rows(block_start=0, block_size=100)
+    if "FORMAT" in probe_rows.dtype.names:
+        n = np.unique(probe_rows["FORMAT"])
+        if n.size != 1:
+            logger.error(f"Expected a single FORMAT in file, found {n}")
+            raise ValueError(f"Expected a single FORMAT in file, found {n}")
+    orbit_format = get_format(probe_rows)
+
+    # infer some stuff about the input
+    input_origin_infer = input_origin
+    input_plane_infer = input_plane
+    input_format_infer = orbit_format
+
+    # BCART_EQ can be normalised down to BCART to not break maths later,
+    # and we just asign equatorial now
+    if input_format_infer == "BCART_EQ":
+        input_format_infer = "BCART"
+        if input_plane_infer is None:
+            logger.warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+            # raise Warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+        input_plane_infer = "equatorial"
+
+    # infer origin if not user supplied
+    if input_origin_infer is None:
+        input_origin_infer = "barycentric" if input_format_infer.startswith("B") else "heliocentric"
+        logger.warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
+        # raise Warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
+
+    # infer plane if not user supplied
+    if input_plane_infer is None:
+        if input_format_infer in ("COM", "BCOM", "KEP", "BKEP"):
+            input_plane_infer = "ecliptic"
+            logger.warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
+            raise Warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
+        else:
+            logger.warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+            # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+
+    logger.info(f"Inferred input orbit origin: {input_origin_infer}")
+    logger.info(f"Inferred input orbit reference plane: {input_plane_infer}")
+    logger.info(f"Inferred input orbit format: {input_format_infer}")
+
+    # full reader with required columns
+    logger.info(f"Reading full input file: {input}")
+    required_cols = REQUIRED_COLUMN_NAMES[orbit_format]
+    if suffix == ".csv":
+        reader = CSVDataReader(
+            input_file,
+            format_column_name="FORMAT",
+            required_column_names=required_cols
+        )
+    else:
+        reader = HDF5DataReader(
+            input_file,
+            format_column_name="FORMAT",
+            required_column_names=required_cols
+        )
+    rows = reader.read_rows(block_start=0, block_size=block_size)
+
+    # make sure we actually have the requested number of orbits, else return all,
+    # then either randomly sample that many or sample the first that many 
+    if num_orbs > rows.size:
+        num_orbs = rows.size
+        logger.warning(f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}")
+        # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+    if random:
+        logger.info(f"Sampling {num_orbs} random orbits")
+        rows = rows[np.random.choice(rows.size, size=num_orbs, replace=False)]
+    else:
+        logger.info(f"Sampling first {num_orbs} orbits")
+        rows = rows[:num_orbs]
+
+    # quick check to make sure orbit format didn't change somehow between probe and full read
+    orbit_format_check = get_format(rows)
+    if orbit_format_check != orbit_format:
+        logger.error(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
+        raise ValueError(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
+    
+    fig2d_cache, fig3d_cache = build_fig_caches(
+        rows=rows,
+        orbit_format=orbit_format,
+        input_plane=input_format_infer,
+        input_origin=input_origin_infer,
+        n_points=n_points,
+        r_max=r_max,
+        cache_dir=cache_dir
+    )
+
+    logger.info(f"Running Dash web app")
+    run_dash_app(fig2d_cache, fig3d_cache)
+
+def visualize_notebook(
+        data: str|Path|np.ndarray,
+        input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
+        input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
+        num_orbs: int = 100,
+        block_size: int = 10000,
+        n_points: int = 500,
+        r_max: float = 50.0,
+        random: bool = False,
+        cache_dir: Optional[str] = None
+):
+    """
+    Create visualisation plots of a given set of input orbits in a Jupyter notebook
+
+    Parameters
+    -----------
+    input : str
+        Input file path
+
+    input_plane : str, optional (default=None)
+        Input file reference plane. Must be one of "equatorial", "ecliptic"
+
+    input_origin : str, optional (default=None)
+        Input file frame of origin. Must be one of "heliocentric", "barycentric"
+
+    num_orbs : int, optional (default=100)
+        Number of orbits to plot at once
+
+    block_size : int, optional (default=10000)
+        Number of rows to read per time in the input file reader
+
+    n_points : int, optional (default=500)
+        Number of points sampled when constructing the line
+
+    r_max : float, optional (default=50 au)
+        Maximum distance to render hyperbolic orbits out to 
+
+    random : bool, optional (default=False)
+        Flag to turn on/off random orbit plotting
+
+    cache_dir : str, optional (default=None)
+        Path to directory of cached auxiliary data
+    """
+    if isinstance(data, (str, Path)):
+        visualize_cli(
+            str(data),
+            input_plane=input_plane,
+            input_origin=input_origin,
+            num_orbs=num_orbs,
+            block_size=block_size,
+            n_points=n_points,
+            r_max=r_max,
+            random=random,
+            cache_dir=cache_dir
+        )
+    elif isinstance(data, np.ndarray):
+        if data.dtype.names is None or "FORMAT" not in data.dtype.names:
+            logger.error("Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])")
+            raise ValueError("Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])")
+        
+        rows = data
+        orbit_format = get_format(rows)
+
+        input_origin_infer = input_origin
+        input_plane_infer = input_plane
+        input_format_infer = orbit_format
+
+        # BCART_EQ can be normalised down to BCART to not break maths later,
+        # and we just asign equatorial now
+        if input_format_infer == "BCART_EQ":
+            input_format_infer = "BCART"
+            if input_plane_infer is None:
+                logger.warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+                # raise Warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+            input_plane_infer = "equatorial"
+
+        # infer origin if not user supplied
+        if input_origin_infer is None:
+            input_origin_infer = "barycentric" if input_format_infer.startswith("B") else "heliocentric"
+            logger.warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file format column FORMAT={orbit_format}")
+            # raise Warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
+
+        # infer plane if not user supplied
+        if input_plane_infer is None:
+            if input_format_infer in ("COM", "BCOM", "KEP", "BKEP"):
+                input_plane_infer = "ecliptic"
+                logger.warning(f"--input-plane not provided. Inferring ecliptic for input file format column FORMAT={orbit_format}")
+                # raise Warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
+            else:
+                logger.warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+                # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+
+        logger.info(f"Inferred input orbit origin: {input_origin_infer}")
+        logger.info(f"Inferred input orbit reference plane: {input_plane_infer}")
+        logger.info(f"Inferred input orbit format: {input_format_infer}")
+
+        # make sure we actually have the requested number of orbits, else return all,
+        # then either randomly sample that many or sample the first that many 
+        if num_orbs > rows.size:
+            logger.warning(f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}")
+            num_orbs = rows.size
+            # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+        if random:
+            logger.info(f"Sampling {num_orbs} random orbits")
+            rows = rows[np.random.choice(rows.size, size=num_orbs, replace=False)]
+        else:
+            logger.info(f"Sampling first {num_orbs} orbits")
+            rows = rows[:num_orbs]
+
+        # quick check to make sure orbit format didn't change somehow between probe and full read
+        orbit_format_check = get_format(rows)
+        if orbit_format_check != orbit_format:
+            logger.error(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
+            raise ValueError(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
+        
+        fig2d_cache, fig3d_cache = build_fig_caches(
+            rows=rows,
+            orbit_format=orbit_format,
+            input_plane=input_format_infer,
+            input_origin=input_origin_infer,
+            n_points=n_points,
+            r_max=r_max,
+            cache_dir=cache_dir
+        )
+
+        run_dash_app(fig2d_cache, fig3d_cache)
+
+    else:
+        raise TypeError("Input data must be a file path or a numpy structured array")
+    
+
+
+
+
diff --git a/src/layup_cmdline/visualize.py b/src/layup_cmdline/visualize.py
index bfddd848..1bc6bbab 100644
--- a/src/layup_cmdline/visualize.py
+++ b/src/layup_cmdline/visualize.py
@@ -1,10 +1,7 @@
-#
-# The `layup visualize` subcommand implementation
-#
 import argparse
-from layup_cmdline.layupargumentparser import LayupArgumentParser
 import logging
-import sys
+
+from layup_cmdline.layupargumentparser import LayupArgumentParser
 
 logger = logging.getLogger(__name__)
 
@@ -13,99 +10,115 @@ def main():
     parser = LayupArgumentParser(
         prog="layup visualize",
         formatter_class=argparse.ArgumentDefaultsHelpFormatter,
-        description="This would start visualize",
+        description="Launch the interactive orbit visualizer (Dash).",
     )
 
     positionals = parser.add_argument_group("Positional arguments")
     positionals.add_argument(
-        help="input orbit file",
+        help="input orbit file (csv or hdf5)",
         dest="input",
         type=str,
     )
 
+    frame = parser.add_argument_group("Frame arguments")
+    frame.add_argument(
+        "--input-plane",
+        help="reference plane of the input orbit elements",
+        dest="input_plane",
+        type=str,
+        choices=["equatorial", "ecliptic"],
+        required=False,
+        default=None
+    )
+    frame.add_argument(
+        "--input-origin",
+        help="origin of the input orbit elements",
+        dest="input_origin",
+        type=str,
+        choices=["heliocentric", "barycentric"],
+        required=False,
+        default=None
+    )
+
     optional = parser.add_argument_group("Optional arguments")
     optional.add_argument(
-        "-i",
-        "--input-type",
-        help="input format type of file",
-        dest="i",
-        type=str.lower,
-        default="csv",
-        required=False,
+        "--block-size",
+        help="number of rows to read from file (initial load)",
+        dest="block_size",
+        type=int,
+        default=10000,
+        required=False
     )
     optional.add_argument(
         "-n",
-        "--num",
-        help="random number of orbits to take from input file",
-        dest="n",
-        type=str,
-        default=1000,
-        required=False,
+        "--num-orbs",
+        help="random number of orbits to plot (sampled without replacement)",
+        dest="num_orbs",
+        type=int,
+        default=100,
+        required=False
     )
     optional.add_argument(
-        "-d",
-        "--dimensions",
-        help="dimensions the plot will be in [2D, 3D]",
-        dest="d",
-        type=str,
-        default="2D",
-        required=False,
+        "--n-points",
+        help="number of points per orbit line",
+        dest="n_points",
+        type=int,
+        default=500,
+        required=False
     )
     optional.add_argument(
-        "-b",
-        "--backend",
-        help="backend used for plotting [matplot, plotly]",
-        dest="b",
-        type=str,
-        default="matplot",
-        required=False,
+        "--r-max",
+        help="maximum radius (au) when drawing hyperbolic orbits",
+        dest="r_max",
+        type=float,
+        default=50.0,
+        required=False
+    )
+    optional.add_argument(
+        "--random",
+        help="randomly display --num_orbs from input file",
+        dest="random",
+        type=bool,
+        default=False,
+        required=False
     )
     optional.add_argument(
-        "-o",
-        "--output",
-        help="output file stem. default path is current working directory",
-        dest="o",
+        "--ar-data-file-path",
+        dest="ar_data_file_path",
         type=str,
-        default="output",
+        default=None,
         required=False,
+        help=argparse.SUPPRESS,  # hide from --help, i don't think a visualize user will be specifying this, but it is needed for bootstrapping fles if user doesn't have them
     )
 
     args = parser.parse_args()
-
     return execute(args)
 
 
 def execute(args):
+    from layup.visualize import visualize_cli
+    from layup.utilities.file_access_utils import find_file_or_exit
+    from layup.utilities.bootstrap_utilties.download_utilities import download_files_if_missing
+    from layup.utilities.layup_configs import LayupConfigs
 
-    from layup.utilities.file_access_utils import find_file_or_exit, find_directory_or_exit
-    from layup.utilities.layup_logging import LayupLogger
+    configs = LayupConfigs()
+    download_files_if_missing(configs.auxiliary, args)
 
-    layup_logger = LayupLogger()
-    logger = layup_logger.get_logger("layup.visualize_cmdline")
+    cache_dir = getattr(args, "ar_data_file_path", None)
 
-    # check input exists
     find_file_or_exit(args.input, "input")
 
-    # Check that output directory exists
-    find_directory_or_exit(args.o, "-o, --")
-
-    # check format of input file
-    if args.i.lower() == "csv":
-        output_file = args.o + ".csv"
-    elif args.i.lower() == "hdf5":
-        output_file = args.o + ".h5"
-    else:
-        logger.error("File format must be 'csv' or 'hdf5'")
-        sys.exit("ERROR: File format must be 'csv' or 'hdf5'")
-
-    if args.d.upper() not in ["2D", "3D"]:
-        logger.error(f"Value for -d --dimensions must be '2D' or '3D', but is {args.d.upper()}")
-        sys.exit("ERROR: -d --dimensions must be '2D' or '3D'")
-
-    if args.b not in ["matplot", "plotly"]:
-        logger.error(f"Value for -b --backend must be 'matplot' or 'plotly', but is {args.b}")
-        sys.exit("ERROR: -b --backend must be 'matplot' or 'plotly'")
-
+    visualize_cli(
+        input=args.input,
+        input_plane=args.input_plane,
+        input_origin=args.input_origin,
+        num_orbs=args.num_orbs,
+        block_size=args.block_size,
+        n_points=args.n_points,
+        r_max=args.r_max,
+        random=args.random,
+        cache_dir=cache_dir
+    )
 
 if __name__ == "__main__":
-    main()
+    main()
\ No newline at end of file

From 6bd4f4dddc2038c2fb3ebbea8e30fec09b195291 Mon Sep 17 00:00:00 2001
From: Joseph Murtagh <jmurtagh05@qub.ac.uk>
Date: Mon, 26 Jan 2026 16:35:14 +0000
Subject: [PATCH 2/5] fix pre-commit-conifg.yaml to let notebooks with pre-ran
 cells

---
 .pre-commit-config.yaml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 9863a961..bf709342 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -17,7 +17,7 @@ repos:
         name: Clear output from Jupyter notebooks
         description: Clear output from Jupyter notebooks.
         files: \.ipynb$
-        exclude: ^docs/pre_executed
+        exclude: ^docs/notebooks/.*\.ipynb
         stages: [pre-commit]
         language: system
         entry: jupyter nbconvert --clear-output

From 3860d69adce83d6a300bc6b84e112adf60dc8b39 Mon Sep 17 00:00:00 2001
From: Joseph Murtagh <jmurtagh05@qub.ac.uk>
Date: Mon, 26 Jan 2026 16:40:17 +0000
Subject: [PATCH 3/5] added plotly and dash dependencies to pyproject.toml

---
 pyproject.toml | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

diff --git a/pyproject.toml b/pyproject.toml
index 789341fa..a8ef9dde 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,7 +23,11 @@ dependencies = [
     "tqdm",
     "sorcha @ git+https://github.com/dirac-institute/sorcha.git",
     "jax",
-    "scipy"
+    "scipy",
+    "plotly",
+    "dash",
+    "dash-daq",
+    "dash-ag-grid"
 ]
 
 [project.scripts]

From 3c9c440497613ee76eefa96b325ff11542805612 Mon Sep 17 00:00:00 2001
From: Joseph Murtagh <jmurtagh05@qub.ac.uk>
Date: Mon, 26 Jan 2026 16:41:44 +0000
Subject: [PATCH 4/5] forgot to lint files

---
 src/layup/dash_ui.py           | 976 ++++++++++++++++++++-------------
 src/layup/orbit_maths.py       | 171 +++---
 src/layup/visualize.py         | 187 ++++---
 src/layup_cmdline/visualize.py |  19 +-
 4 files changed, 805 insertions(+), 548 deletions(-)

diff --git a/src/layup/dash_ui.py b/src/layup/dash_ui.py
index 75e64f2a..28da0132 100644
--- a/src/layup/dash_ui.py
+++ b/src/layup/dash_ui.py
@@ -9,44 +9,40 @@
 PANEL = Literal["XY", "XZ", "YZ"]
 
 PLANET_COLOURS_NIGHT = {
-    "Mercury": "rgba(190,190,190,0.95)",   # silver
-    "Venus":   "rgba(255,190,90,0.95)",    # warm amber
-    "Earth":   "rgba(90,210,255,0.95)",    # cyan 
-    "Mars":    "rgba(255,90,90,0.95)",     # red
-    "Jupiter": "rgba(255,165,120,0.95)",   # salmon/orange
-    "Saturn":  "rgba(255,230,150,0.95)",   # pale gold
-    "Uranus":  "rgba(120,255,210,0.95)",   # mint
-    "Neptune": "rgba(185,120,255,0.95)",   # purple 
+    "Mercury": "rgba(190,190,190,0.95)",  # silver
+    "Venus": "rgba(255,190,90,0.95)",  # warm amber
+    "Earth": "rgba(90,210,255,0.95)",  # cyan
+    "Mars": "rgba(255,90,90,0.95)",  # red
+    "Jupiter": "rgba(255,165,120,0.95)",  # salmon/orange
+    "Saturn": "rgba(255,230,150,0.95)",  # pale gold
+    "Uranus": "rgba(120,255,210,0.95)",  # mint
+    "Neptune": "rgba(185,120,255,0.95)",  # purple
 }
 
 PLANET_COLOURS_DAY = {
-    "Mercury": "rgba(90,90,90,0.95)",      # dark gray
-    "Venus":   "rgba(180,110,0,0.95)",     # brown/orange
-    "Earth":   "rgba(0,140,190,0.95)",     # teal-blue 
-    "Mars":    "rgba(170,0,0,0.95)",       # dark red
-    "Jupiter": "rgba(170,90,60,0.95)",     # brown
-    "Saturn":  "rgba(160,140,40,0.95)",    # olive gold
-    "Uranus":  "rgba(0,150,110,0.95)",     # green-teal
-    "Neptune": "rgba(115,0,170,0.95)",     # deep purple 
+    "Mercury": "rgba(90,90,90,0.95)",  # dark gray
+    "Venus": "rgba(180,110,0,0.95)",  # brown/orange
+    "Earth": "rgba(0,140,190,0.95)",  # teal-blue
+    "Mars": "rgba(170,0,0,0.95)",  # dark red
+    "Jupiter": "rgba(170,90,60,0.95)",  # brown
+    "Saturn": "rgba(160,140,40,0.95)",  # olive gold
+    "Uranus": "rgba(0,150,110,0.95)",  # green-teal
+    "Neptune": "rgba(115,0,170,0.95)",  # deep purple
 }
 
 logger = logging.getLogger(__name__)
 
+
 # --- set up plots ---
-def add_reference_plane_xy(
-        fig,
-        lines: np.ndarray,
-        planet_lines: np.ndarray,
-        opacity: float = 0.10
-):
+def add_reference_plane_xy(fig, lines: np.ndarray, planet_lines: np.ndarray, opacity: float = 0.10):
     """
     Add the reference plane (either ecliptic or equatorial) to the 3D plot at Z=0
 
     Parameters
     -----------
-    fig : object 
+    fig : object
         Plotly figure object
-    
+
     lines : numpy float array
         Array of x,y,z coordinates of objects to be plotted
 
@@ -62,7 +58,7 @@ def add_reference_plane_xy(
     x_obj = lines[..., 0].ravel()
     y_obj = lines[..., 1].ravel()
 
-    # either take the extent of the plane to be the furthest orbit or furthest planet 
+    # either take the extent of the plane to be the furthest orbit or furthest planet
     if planet_lines is not None and np.size(planet_lines) > 0:
         x_pla = planet_lines[..., 0].ravel()
         y_pla = planet_lines[..., 1].ravel()
@@ -79,7 +75,7 @@ def add_reference_plane_xy(
     pady = 0.05 * (y1 - y0) if (y1 - y0) > 0 else 1.0
     x0, x1 = x0 - padx, x1 + padx
     y0, y1 = y0 - pady, y1 + pady
-    
+
     # now create the plane as nx x ny grid
     nx, ny = 40, 40
     xs = np.linspace(x0, x1, nx)
@@ -90,22 +86,21 @@ def add_reference_plane_xy(
     # add to the figure
     fig.add_trace(
         go.Surface(
-            x=X, y=Y, z=Z,
+            x=X,
+            y=Y,
+            z=Z,
             showscale=False,
             opacity=opacity,
             surfacecolor=np.zeros_like(X),
             hoverinfo="skip",
             name="ref-plane",
-            hovertemplate=None
+            hovertemplate=None,
         )
     )
 
+
 # --- very crude orbit classifier ---
-def classify(
-        a: float, 
-        e: float, 
-        Tj: float
-) -> str:
+def classify(a: float, e: float, Tj: float) -> str:
     """
     Rough first pass orbit classifier based on input orbital elements. Does NOT do any
     orbit integrations to verify e.g. Trojan or other resonant behaviour, so use only as
@@ -120,12 +115,12 @@ def classify(
         Eccentricity of the object
 
     Tj : float
-        Tisserand parameter with respect to Jupiter of the object 
+        Tisserand parameter with respect to Jupiter of the object
     """
     q = a * (1 - e)
 
     # these are some very very crude dynamical classifiers for filtering
-    # purposes, don't take them as gospel - do your own checks!!
+    # purposes, don't take them as gospel - do your own checks!!
     if e >= 1.0:
         return "Hyperbolic"
     elif np.isfinite(a) and a > 2000:
@@ -150,17 +145,17 @@ def classify(
 
 # --- plot in 2D ---
 def plotly_2D(
-        lines: np.ndarray,
-        canon: ClassicalConic,
-        plot_sun: bool = True,
-        orbit_pos: Optional[np.ndarray] = None,
-        sun_xyz: Optional[np.ndarray] = None,
-        planet_lines: Optional[np.ndarray] = None,
-        planet_id: Optional[np.ndarray] = None,
-        return_fig: bool = False,
-        output: Optional[str] = None,
-        panel: Optional[PANEL] = None,
-        panels: Optional[Tuple[PANEL, PANEL]] = None
+    lines: np.ndarray,
+    canon: ClassicalConic,
+    plot_sun: bool = True,
+    orbit_pos: Optional[np.ndarray] = None,
+    sun_xyz: Optional[np.ndarray] = None,
+    planet_lines: Optional[np.ndarray] = None,
+    planet_id: Optional[np.ndarray] = None,
+    return_fig: bool = False,
+    output: Optional[str] = None,
+    panel: Optional[PANEL] = None,
+    panels: Optional[Tuple[PANEL, PANEL]] = None,
 ):
     """
     Create a 2D (1x2 subplot) interactive Plotly figure of orbits
@@ -183,7 +178,7 @@ def plotly_2D(
         Dictionary of arrays with the Sun positions in each plane+origin combination
 
     planet_lines : dict of arrays, optional (default = None)
-        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin
         combination of shape (n_planets, n_points, 3)
 
     planet_id : numpy string array, optional (default = None)
@@ -208,35 +203,46 @@ def plotly_2D(
     """
     import plotly.graph_objects as go
     from plotly.subplots import make_subplots
-    
+
     def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
         if p == "XY":
-            return x, y, "X [AU]", "Y [AU]", True # <-- the final True here is letting later on know to plot this panel equal aspect, as top-down is onto the reference plane
+            return (
+                x,
+                y,
+                "X [AU]",
+                "Y [AU]",
+                True,
+            )  # <-- the final True here is letting later on know to plot this panel equal aspect, as top-down is onto the reference plane
         if p == "XZ":
-            return x, z, "X [AU]", "Z [AU]", False # <-- this and YZ are inclination driven so shouldn't be equal aspect
+            return (
+                x,
+                z,
+                "X [AU]",
+                "Z [AU]",
+                False,
+            )  # <-- this and YZ are inclination driven so shouldn't be equal aspect
         if p == "YZ":
             return y, z, "Y [AU]", "Z [AU]", False
         logger.error(f"Unknown panel {p!r} (expected 'XY', 'XZ', 'YZ')")
         raise ValueError(f"Unknown panel {p!r} (expected 'XY', 'XZ', 'YZ')")
-    
+
     # -- panel configuration --
     if panels is not None:
-        panels_to_show: Tuple[PANEL, ...] = tuple(panels) # < -- if >1 panels, turn whichever options they are into tuple
+        panels_to_show: Tuple[PANEL, ...] = tuple(
+            panels
+        )  # < -- if >1 panels, turn whichever options they are into tuple
     elif panel is not None:
-        panels_to_show = (panel,) # < -- if 1 panel, turn that option into tuple
+        panels_to_show = (panel,)  # < -- if 1 panel, turn that option into tuple
     else:
-        panels_to_show = ("XY", "XZ") # < -- if none specified, default to 2 panel XY+XZ
+        panels_to_show = ("XY", "XZ")  # < -- if none specified, default to 2 panel XY+XZ
 
     if len(panels_to_show) not in (1, 2):
         logger.error(f"Expected 1 or 2 panels, got {len(panels_to_show)}: {panels_to_show}")
         raise ValueError(f"Expected 1 or 2 panels, got {len(panels_to_show)}: {panels_to_show}")
-    
+
     ncols = len(panels_to_show)
 
-    fig = make_subplots(
-        rows=1, cols=ncols,
-        horizontal_spacing=0.10 if ncols == 2 else 0.02
-    )
+    fig = make_subplots(rows=1, cols=ncols, horizontal_spacing=0.10 if ncols == 2 else 0.02)
 
     # -- plot planets --
     if planet_lines is not None:
@@ -256,18 +262,22 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
 
             # loop over however many panels we have
             for col, p in enumerate(panels_to_show, start=1):
-                xa, ya, _, _, _ = coords_for(p, x, y, z) # <-- grab the correct axes x/y coords for whatever plane it is
+                xa, ya, _, _, _ = coords_for(
+                    p, x, y, z
+                )  # <-- grab the correct axes x/y coords for whatever plane it is
                 fig.add_trace(
                     go.Scatter(
-                        x=xa, y=ya,
+                        x=xa,
+                        y=ya,
                         mode="lines",
                         line=dict(color=colour, width=2.2),
                         hovertemplate=hover_text,
                         showlegend=False,
                         name=str(planet_id[i]),
-                        meta={"kind": "Planet"} # <-- this tag is to prevent colours being overwritten later
+                        meta={"kind": "Planet"},  # <-- this tag is to prevent colours being overwritten later
                     ),
-                    row=1, col=col
+                    row=1,
+                    col=col,
                 )
 
     # -- plot input objects --
@@ -290,11 +300,11 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
         L = float(canon.L[i])
         e = float(canon.e[i])
         inc = float(canon.inc[i])
-        if abs(1 - e**2) < 1e-12: # <-- protect against parabolic orbits
+        if abs(1 - e**2) < 1e-12:  # <-- protect against parabolic orbits
             a = np.inf
         else:
             a = L / (1 - e**2)
-        if (not np.isfinite(a)) or (a == 0.0): # <-- same again
+        if (not np.isfinite(a)) or (a == 0.0):  # <-- same again
             Tj = np.nan
         else:
             Tj = (5.2044 / a) + 2.0 * np.cos(inc) * np.sqrt((a / 5.2044) * (1 - e**2))
@@ -302,63 +312,64 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
 
         # loop over however many panels we have
         for col, p in enumerate(panels_to_show, start=1):
-            xa, ya, _, _, _ = coords_for(p, x, y, z) # <-- grab the correct axes x/y coords for whatever plane it is
+            xa, ya, _, _, _ = coords_for(
+                p, x, y, z
+            )  # <-- grab the correct axes x/y coords for whatever plane it is
             fig.add_trace(
                 go.Scatter(
-                    x=xa, y=ya,
+                    x=xa,
+                    y=ya,
                     mode="lines",
                     line=dict(color="rgba(144,167,209,0.7)", width=1.5),
-                    hovertemplate=hover_text+"<extra></extra>",
+                    hovertemplate=hover_text + "<extra></extra>",
                     showlegend=False,
                     name=str(canon.obj_id[i]),
-                    meta={"kind": pop}
+                    meta={"kind": pop},
                 ),
-                row=1, col=col
+                row=1,
+                col=col,
             )
 
-    
     # -- plot input object epoch position --
     if orbit_pos is not None:
-        # want to get a hover label with epoch info so first 
+        # want to get a hover label with epoch info so first
         # extract from conic objects
         mjd = np.asarray(canon.epochMJD_TDB, dtype=float)
         mjd_str = np.array([f"{m:.5f}" for m in mjd], dtype="U32")
 
         # also good to have it in YYYY MM DD format
         ymd_str = np.empty(mjd.shape[0], dtype="U10")
-        base = datetime(1858, 11, 17) # <-- MJD 0
+        base = datetime(1858, 11, 17)  # <-- MJD 0
         for i, mjd in enumerate(mjd):
             dt = base + timedelta(days=float(mjd))
-            ymd_str[i] = dt.strftime("%Y %b %d") 
+            ymd_str[i] = dt.strftime("%Y %b %d")
 
         # vectorise it by stacking all labels together to add
         # as one trace into plotly
         mjd_stack = np.column_stack([mjd_str, ymd_str])
-        hover_text = (
-            "%{text}<br>"
-            "@ MJD %{customdata[0]}<br>"
-            "(%{customdata[1]})"
-            "<extra></extra>"
-        )
+        hover_text = "%{text}<br>" "@ MJD %{customdata[0]}<br>" "(%{customdata[1]})" "<extra></extra>"
 
         # loop over however many panels we have
         for col, p in enumerate(panels_to_show, start=1):
-            xa, ya, _, _, _ = coords_for(p, orbit_pos[:, 0], orbit_pos[:, 1], orbit_pos[:, 2]) # <-- grab the correct axes x/y coords for whatever plane it is
+            xa, ya, _, _, _ = coords_for(
+                p, orbit_pos[:, 0], orbit_pos[:, 1], orbit_pos[:, 2]
+            )  # <-- grab the correct axes x/y coords for whatever plane it is
             fig.add_trace(
                 go.Scatter(
-                    x=xa, y=ya,
+                    x=xa,
+                    y=ya,
                     mode="markers",
                     marker=dict(size=5, color="rgba(255,255,255,0.9)"),
                     showlegend=False,
                     text=np.asarray(canon.obj_id),
                     customdata=mjd_stack,
                     hovertemplate=hover_text,
-                    meta={"kind": "epoch"}
+                    meta={"kind": "epoch"},
                 ),
-                row=1, col=col
+                row=1,
+                col=col,
             )
 
-
     # -- plot the sun --
     if plot_sun:
         if sun_xyz is None:
@@ -368,16 +379,20 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
 
         # loop over however many panels we have
         for col, p in enumerate(panels_to_show, start=1):
-            xa, ya, _, _, _ = coords_for(p, np.array([sx]), np.array([sy]), np.array([sz])) # <-- grab the correct axes x/y coords for whatever plane it is
+            xa, ya, _, _, _ = coords_for(
+                p, np.array([sx]), np.array([sy]), np.array([sz])
+            )  # <-- grab the correct axes x/y coords for whatever plane it is
             fig.add_trace(
                 go.Scatter(
-                    x=xa, y=ya,
+                    x=xa,
+                    y=ya,
                     mode="markers",
                     marker=dict(size=10, color="yellow"),
                     showlegend=False,
                     name="Sun",
                 ),
-                row=1, col=col,
+                row=1,
+                col=col,
             )
 
     # -- pretty up the figure --
@@ -386,18 +401,20 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
         paper_bgcolor="rgba(0,0,0,0)",
         font=dict(color="white"),
         autosize=True,
-        margin=dict(l=60,r=60,t=40,b=60),
+        margin=dict(l=60, r=60, t=40, b=60),
         hoverdistance=0,
-        hovermode="closest"
+        hovermode="closest",
     )
 
-    fig.update_xaxes(showgrid=True, gridcolor='rgba(255,255,255,0.08)')
-    fig.update_yaxes(showgrid=True, gridcolor='rgba(255,255,255,0.08)')
+    fig.update_xaxes(showgrid=True, gridcolor="rgba(255,255,255,0.08)")
+    fig.update_yaxes(showgrid=True, gridcolor="rgba(255,255,255,0.08)")
 
     # axis titles + equal aspect for any XY panel
     # loop over however many panels we have
     for col, p in enumerate(panels_to_show, start=1):
-        _, _, xtitle, ytitle, want_equal = coords_for(p, np.array([0.0]), np.array([0.0]), np.array([0.0])) # <-- grab the correct axes x/y titles for whatever plane it is
+        _, _, xtitle, ytitle, want_equal = coords_for(
+            p, np.array([0.0]), np.array([0.0]), np.array([0.0])
+        )  # <-- grab the correct axes x/y titles for whatever plane it is
         fig.update_xaxes(title_text=xtitle, row=1, col=col)
         fig.update_yaxes(title_text=ytitle, row=1, col=col)
         if want_equal:
@@ -405,11 +422,11 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
                 fig.update_layout(yaxis=dict(scaleanchor="x", scaleratio=1))
             elif col == 2:
                 fig.update_layout(yaxis2=dict(scaleanchor="x2", scaleratio=1))
-    
+
     # return figure object if user wants
     if return_fig:
         return fig
-    
+
     # otherwise write out and show
     if output:
         fig.write_html(output)
@@ -417,18 +434,19 @@ def coords_for(p: PANEL, x: np.ndarray, y: np.ndarray, z: np.ndarray):
 
     fig.show()
 
+
 # --- plot in 3D ---
 def plotly_3D(
-        lines: np.ndarray,
-        canon: ClassicalConic,
-        plot_sun: bool = True,
-        show_plane: bool = True,
-        orbit_pos: Optional[np.ndarray] = None,
-        planet_lines: Optional[np.ndarray] = None,
-        planet_id: Optional[np.ndarray] = None,
-        sun_xyz: Optional[np.ndarray] = None,
-        return_fig: bool = False,
-        output: Optional[str] = None    
+    lines: np.ndarray,
+    canon: ClassicalConic,
+    plot_sun: bool = True,
+    show_plane: bool = True,
+    orbit_pos: Optional[np.ndarray] = None,
+    planet_lines: Optional[np.ndarray] = None,
+    planet_id: Optional[np.ndarray] = None,
+    sun_xyz: Optional[np.ndarray] = None,
+    return_fig: bool = False,
+    output: Optional[str] = None,
 ):
     """
     Create a 3D interactive Plotly figure of orbits
@@ -451,7 +469,7 @@ def plotly_3D(
         Dictionary of arrays with object positions in each plane+origin combination
 
     planet_lines : dict of arrays, optional (default = None)
-        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        Dictionary of arrays containing planet orbit lines for each planet in each plane+origin
         combination of shape (n_planets, n_points, 3)
 
     planet_id : numpy string array, optional (default = None)
@@ -478,7 +496,7 @@ def plotly_3D(
     # -- plot reference plane --
     if show_plane:
         add_reference_plane_xy(fig, lines, planet_lines, opacity=0.50)
-    
+
     # -- plot planets --
     if planet_lines is not None:
         if planet_id is None:
@@ -494,13 +512,15 @@ def plotly_3D(
 
             fig.add_trace(
                 go.Scatter3d(
-                    x=x, y=y, z=z,
+                    x=x,
+                    y=y,
+                    z=z,
                     mode="lines",
                     line=dict(color=colour, width=5),
                     hovertemplate=f"{planet_id[i]}<extra></extra>",
                     showlegend=False,
                     name=str(planet_id[i]),
-                    meta={"kind": "Planet"} # <-- this tag is to prevent colours being overwritten later
+                    meta={"kind": "Planet"},  # <-- this tag is to prevent colours being overwritten later
                 )
             )
 
@@ -523,11 +543,11 @@ def plotly_3D(
         L = float(canon.L[i])
         e = float(canon.e[i])
         inc = float(canon.inc[i])
-        if abs(1 - e**2) < 1e-12: # <-- protect against parabolic orbits
+        if abs(1 - e**2) < 1e-12:  # <-- protect against parabolic orbits
             a = np.inf
         else:
             a = L / (1 - e**2)
-        if (not np.isfinite(a)) or (a == 0.0): # <-- same again
+        if (not np.isfinite(a)) or (a == 0.0):  # <-- same again
             Tj = np.nan
         else:
             Tj = (5.2044 / a) + 2.0 * np.cos(inc) * np.sqrt((a / 5.2044) * (1 - e**2))
@@ -535,39 +555,36 @@ def plotly_3D(
 
         fig.add_trace(
             go.Scatter3d(
-                x=x, y=y, z=z,
+                x=x,
+                y=y,
+                z=z,
                 mode="lines",
                 line=dict(color="rgba(144, 167, 209, 0.7)", width=3),
                 hovertemplate=hover_text + "<extra></extra>",
                 showlegend=False,
                 name=str(canon.obj_id[i]),
-                meta={"kind": pop}
+                meta={"kind": pop},
             )
         )
 
     # -- plot input object epoch position --
     if orbit_pos is not None:
-        # want to get a hover label with epoch info so first 
+        # want to get a hover label with epoch info so first
         # extract from conic objects
         mjd = np.asarray(canon.epochMJD_TDB, dtype=float)
         mjd_str = np.array([f"{m:.5f}" for m in mjd], dtype="U32")
 
         # also good to have it in YYYY MM DD format
         ymd_str = np.empty(mjd.shape[0], dtype="U10")
-        base = datetime(1858, 11, 17) # <-- MJD 0
+        base = datetime(1858, 11, 17)  # <-- MJD 0
         for i, mjd in enumerate(mjd):
             dt = base + timedelta(days=float(mjd))
-            ymd_str[i] = dt.strftime("%Y %b %d") 
+            ymd_str[i] = dt.strftime("%Y %b %d")
 
         # vectorise it by stacking all labels together to add
         # as one trace into plotly
         mjd_stack = np.column_stack([mjd_str, ymd_str])
-        hover_text = (
-            "%{text}<br>"
-            "@ MJD %{customdata[0]}<br>"
-            "(%{customdata[1]})"
-            "<extra></extra>"
-        )
+        hover_text = "%{text}<br>" "@ MJD %{customdata[0]}<br>" "(%{customdata[1]})" "<extra></extra>"
 
         fig.add_trace(
             go.Scatter3d(
@@ -580,7 +597,7 @@ def plotly_3D(
                 meta={"kind": "epoch"},
                 text=np.asarray(canon.obj_id),
                 customdata=mjd_stack,
-                hovertemplate=hover_text
+                hovertemplate=hover_text,
             )
         )
 
@@ -593,12 +610,13 @@ def plotly_3D(
 
         fig.add_trace(
             go.Scatter3d(
-                x=[sx], y=[sy], z=[sz],
-                
+                x=[sx],
+                y=[sy],
+                z=[sz],
                 mode="markers",
                 marker=dict(size=6, color="yellow"),
                 showlegend=False,
-                hovertext="Sun"
+                hovertext="Sun",
             )
         )
 
@@ -611,20 +629,37 @@ def plotly_3D(
         autosize=True,
         margin=dict(l=0, r=0, t=40, b=0),
         scene=dict(
-            xaxis=dict(title="X [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
-            yaxis=dict(title="Y [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
-            zaxis=dict(title="Z [AU]", showbackground=False, gridcolor="rgba(255, 255, 255, 0.02)", zerolinecolor="rgba(255, 255, 255, 0.4)"),
+            xaxis=dict(
+                title="X [AU]",
+                showbackground=False,
+                gridcolor="rgba(255, 255, 255, 0.02)",
+                zerolinecolor="rgba(255, 255, 255, 0.4)",
+            ),
+            yaxis=dict(
+                title="Y [AU]",
+                showbackground=False,
+                gridcolor="rgba(255, 255, 255, 0.02)",
+                zerolinecolor="rgba(255, 255, 255, 0.4)",
+            ),
+            zaxis=dict(
+                title="Z [AU]",
+                showbackground=False,
+                gridcolor="rgba(255, 255, 255, 0.02)",
+                zerolinecolor="rgba(255, 255, 255, 0.4)",
+            ),
             aspectmode="data",
             camera=dict(
-                center=dict(x=0, y=0, z=-0.25)  # <-- for some reason default camera looks really low to me, negative z shifts scene up in the frame
-            )
-        )
+                center=dict(
+                    x=0, y=0, z=-0.25
+                )  # <-- for some reason default camera looks really low to me, negative z shifts scene up in the frame
+            ),
+        ),
     )
 
     # return figure object if user wants
     if return_fig:
         return fig
-    
+
     # otherwise write out and show
     if output:
         fig.write_html(output)
@@ -634,12 +669,9 @@ def plotly_3D(
 
 
 # --- make the dash app ---
-def run_dash_app(
-        fig2d_cache: dict[tuple[str, str], "object"],
-        fig3d_cache: dict[tuple[str, str], "object"]
-):
+def run_dash_app(fig2d_cache: dict[tuple[str, str], "object"], fig3d_cache: dict[tuple[str, str], "object"]):
     """
-    Create and 
+    Create and
     """
     import dash
     from dash import Dash, dcc, html, Input, Output, State, ctx
@@ -651,7 +683,11 @@ def run_dash_app(
     import webbrowser
 
     # set up app and (very optionally) link to latex stylesheet
-    app = Dash(__name__, assets_folder="data", external_stylesheets=["https://cdn.jsdelivr.net/npm/katex@0.16.9/dist/katex.min.css"])
+    app = Dash(
+        __name__,
+        assets_folder="data",
+        external_stylesheets=["https://cdn.jsdelivr.net/npm/katex@0.16.9/dist/katex.min.css"],
+    )
 
     # establsh day/night mode theming
     THEME = {
@@ -663,7 +699,7 @@ def run_dash_app(
             "zero": "rgba(255,255,255,0.12)",
             "drawer_bg": "rgba(0,0,0,0.70)",
             "tab_bg": "rgba(0,0,0,0.55)",
-            "border": "rgba(255,255,255,0.18)"
+            "border": "rgba(255,255,255,0.18)",
         },
         "day": {
             "bg": "white",
@@ -673,14 +709,11 @@ def run_dash_app(
             "zero": "rgba(0,0,0,0.18)",
             "drawer_bg": "rgba(255,255,255,0.86)",
             "tab_bg": "rgba(255,255,255,0.75)",
-            "border": "rgba(0,0,0,0.15)"
-        }
+            "border": "rgba(0,0,0,0.15)",
+        },
     }
 
-    ORBIT_COLOUR = {
-        "night": "rgba(144,167,209,0.70)",
-        "day": "rgba(30,60,120,0.85)"
-    }
+    ORBIT_COLOUR = {"night": "rgba(144,167,209,0.70)", "day": "rgba(30,60,120,0.85)"}
 
     # defaults
     night_default = True
@@ -708,20 +741,23 @@ def collect_inventory(figs: list[object]):
 
                 if not name or name == "ref-plane":
                     continue
-                
+
                 if isinstance(meta, dict):
-                    k = meta.get("kind") # <-- finally the meta tags come in to play!
+                    k = meta.get("kind")  # <-- finally the meta tags come in to play!
 
                     if k == "Planet":
                         planets.add(name)
                         continue
 
-                    if getattr(tr, "type", None) in ("scatter", "scatter3d") and getattr(tr, "mode", None) == "lines":
+                    if (
+                        getattr(tr, "type", None) in ("scatter", "scatter3d")
+                        and getattr(tr, "mode", None) == "lines"
+                    ):
                         objids.add(name)
                         kinds.setdefault(name, k)
 
         return sorted(planets), sorted(objids), kinds
-    
+
     # get our list of selectable things (if for some reason the cache is partial or could be
     # broken, fall back to whatever the initial_fig is)
     inv_planets, inv_objids, orbit_kinds = collect_inventory(list(fig3d_cache.values()))
@@ -729,76 +765,88 @@ def collect_inventory(figs: list[object]):
         inv_planets, inv_objids, orbit_kinds = collect_inventory([initial_fig])
 
     # these are our table inventory rows
-    inventory_rows = (
-        [{"kind": "Planet", "name": p} for p in inv_planets] +
-        [{"kind": orbit_kinds.get(o, "Other"), "name": o} for o in inv_objids]
-    )
+    inventory_rows = [{"kind": "Planet", "name": p} for p in inv_planets] + [
+        {"kind": orbit_kinds.get(o, "Other"), "name": o} for o in inv_objids
+    ]
 
     # set up title/label styling helpers for swapping day/night, frame, origin, and view modes
     def title_style(fg: str):
         return {"marginBottom": "10px", "fontSize": "20px", "color": fg, "opacity": 0.95}
-    
+
     def sublabel_style(fg: str):
         return {"fontSize": "17px", "color": fg, "opacity": 0.90}
-    
+
     # this creates the proper div environment for the toggle switches so the labels wrap well and look nice
-    def labeled_toggle(left_label: str, toggle_id: str, right_label: str, value: bool, fg: str, width_pix: int=220):
+    def labeled_toggle(
+        left_label: str, toggle_id: str, right_label: str, value: bool, fg: str, width_pix: int = 220
+    ):
         return html.Div(
             [
-                html.Div(left_label, style={**sublabel_style(fg), "marginRight": "14px", "whiteSpace": "nowrap"}, className="toggle-label"),
-                daq.ToggleSwitch(
-                    id=toggle_id,
-                    value=value,
-                    size=70,
-                    color="#4cd964"
+                html.Div(
+                    left_label,
+                    style={**sublabel_style(fg), "marginRight": "14px", "whiteSpace": "nowrap"},
+                    className="toggle-label",
+                ),
+                daq.ToggleSwitch(id=toggle_id, value=value, size=70, color="#4cd964"),
+                html.Div(
+                    right_label,
+                    style={**sublabel_style(fg), "marginLeft": "14px", "whiteSpace": "nowrap"},
+                    className="toggle-label",
                 ),
-                html.Div(right_label, style={**sublabel_style(fg), "marginLeft": "14px", "whiteSpace": "nowrap"}, className="toggle-label")
             ],
-            style={
-                "display": "flex",
-                "alignItems": "center",
-                "justifyContent": "center",
-                "width": "100%"
-            }
+            style={"display": "flex", "alignItems": "center", "justifyContent": "center", "width": "100%"},
         )
-    
+
     # set up a template consistent "block" for all controls to be built into
-    def control_block(title: str, body, fg: str, width_px: int=200):
+    def control_block(title: str, body, fg: str, width_px: int = 200):
         return html.Div(
             [
                 html.Div(title, style={**title_style(fg), "textAlign": "center", "width": "100%"}),
-                html.Div(body, style={"display": "flex", "justifyContent": "center", "width": "100%"})
+                html.Div(body, style={"display": "flex", "justifyContent": "center", "width": "100%"}),
             ],
             style={
                 "width": "100%",
                 "minWidth": "0",
                 "display": "flex",
                 "flexDirection": "column",
-                "alignItems": "center"
-            }
+                "alignItems": "center",
+            },
         )
-    
+
     # create a special plane toggle block with the slider
     plane_block_layout = control_block(
         "Plane",
         html.Div(
             [
                 html.Div(
-                    labeled_toggle("Ecl", "plane-toggle", "Equ", value=plane_equ_default, fg=fg0, width_pix=220),
-                    style={"display": "flex", "justifyContent": "center", "width": "100%", "maxWidth": "260px", "margin": "0 auto 14px auto"}
+                    labeled_toggle(
+                        "Ecl", "plane-toggle", "Equ", value=plane_equ_default, fg=fg0, width_pix=220
+                    ),
+                    style={
+                        "display": "flex",
+                        "justifyContent": "center",
+                        "width": "100%",
+                        "maxWidth": "260px",
+                        "margin": "0 auto 14px auto",
+                    },
                 ),
                 html.Div(
                     [
                         html.Div(
                             "Opacity",
-                            style={**sublabel_style(fg0), "flex": "1 1 auto", "textAlign": "center"}
+                            style={**sublabel_style(fg0), "flex": "1 1 auto", "textAlign": "center"},
                         ),
                         html.Div(
-                            "Colour",
-                            style={**sublabel_style(fg0), "flex": "0 0 42px", "textAlign": "center"}
-                        )
+                            "Colour", style={**sublabel_style(fg0), "flex": "0 0 42px", "textAlign": "center"}
+                        ),
                     ],
-                    style={"width": "100%", "maxWidth": "260px", "display": "flex", "gap": "10px", "margin": "0 auto 6px auto"}
+                    style={
+                        "width": "100%",
+                        "maxWidth": "260px",
+                        "display": "flex",
+                        "gap": "10px",
+                        "margin": "0 auto 6px auto",
+                    },
                 ),
                 html.Div(
                     [
@@ -810,24 +858,51 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                 step=0.02,
                                 value=opacity_default,
                                 marks={0.0: "0", 0.5: "0.5", 1.0: "1.0"},
-                                className="opacity-slider"
+                                className="opacity-slider",
                             ),
-                            style={"flex": "1 1 auto", "minWidth": "0"}
+                            style={"flex": "1 1 auto", "minWidth": "0"},
                         ),
                         html.Button(
-                            "🖌\uFE0E", # <-- is emoji pasting good coding practice? 
+                            "🖌\ufe0e",  # <-- is emoji pasting good coding practice?
                             id="plane-colour-button",
                             n_clicks=0,
-                            style={"flex": "0 0 42px", "width": "42px", "height": "34px", "borderRadius": "10px", "border": f"1px solid {theme0['border']}", "background": theme0["tab_bg"], "color": fg0, "cursor": "pointer", "padding": "0", "display": "flex", "alignItems": "center", "justifyContent": "center"},
-                            title="Edit Colour"
-                        )
+                            style={
+                                "flex": "0 0 42px",
+                                "width": "42px",
+                                "height": "34px",
+                                "borderRadius": "10px",
+                                "border": f"1px solid {theme0['border']}",
+                                "background": theme0["tab_bg"],
+                                "color": fg0,
+                                "cursor": "pointer",
+                                "padding": "0",
+                                "display": "flex",
+                                "alignItems": "center",
+                                "justifyContent": "center",
+                            },
+                            title="Edit Colour",
+                        ),
                     ],
-                    style={"width": "100%", "maxWidth": "260px", "margin": "0 auto", "display": "flex", "alignItems": "center", "gap": "10px"}
-                )
+                    style={
+                        "width": "100%",
+                        "maxWidth": "260px",
+                        "margin": "0 auto",
+                        "display": "flex",
+                        "alignItems": "center",
+                        "gap": "10px",
+                    },
+                ),
             ],
-            style={"display": "flex", "flexDirection": "column", "alignItems": "center", "gap": "10px", "width": "100%", "minWidth": "0"}
+            style={
+                "display": "flex",
+                "flexDirection": "column",
+                "alignItems": "center",
+                "gap": "10px",
+                "width": "100%",
+                "minWidth": "0",
+            },
         ),
-        fg=fg0
+        fg=fg0,
     )
 
     # create a special switch for 2D plots to choose which panels to display and how many
@@ -835,7 +910,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
         [
             html.Div(
                 "2D Panel Controls",
-                style={**sublabel_style(fg0), "textAlign": "center", "marginBottom": "6px"}
+                style={**sublabel_style(fg0), "textAlign": "center", "marginBottom": "6px"},
             ),
             dcc.RadioItems(
                 id="panel-mode",
@@ -846,13 +921,18 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                 value="double",
                 inline=True,
                 style={"display": "flex", "justifyContent": "center", "gap": "18px"},
-                labelStyle={**sublabel_style(fg0), "cursor": "pointer"}
+                labelStyle={**sublabel_style(fg0), "cursor": "pointer"},
             ),
         ],
-        style={"width": "220px", "display": "flex", "flexDirection": "column", "alignItems": "center", "marginTop": "14px"},
+        style={
+            "width": "220px",
+            "display": "flex",
+            "flexDirection": "column",
+            "alignItems": "center",
+            "marginTop": "14px",
+        },
     )
 
-    
     # -- create entire layout of page --
     app.layout = html.Div(
         [
@@ -885,7 +965,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                     "fontSize": "26px",
                     "cursor": "pointer",
                     "backdropFilter": "blur(10px)",
-                    "transition": "top 180ms ease"
+                    "transition": "top 180ms ease",
                 },
             ),
             html.Div(
@@ -895,7 +975,14 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             html.Div(
                                 [
                                     html.Div("", style={"justifySelf": "start"}),
-                                    html.Div("Controls", style={"fontSize": "22px", "fontWeight": 600, "justifySelf": "center"}),
+                                    html.Div(
+                                        "Controls",
+                                        style={
+                                            "fontSize": "22px",
+                                            "fontWeight": 600,
+                                            "justifySelf": "center",
+                                        },
+                                    ),
                                     html.Button(
                                         "x",
                                         id="controls-close",
@@ -906,48 +993,78 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                             "background": "transparent",
                                             "color": "inherit",
                                             "fontSize": "22px",
-                                            "cursor": "pointer"
-                                        }
-                                    )
+                                            "cursor": "pointer",
+                                        },
+                                    ),
                                 ],
                                 style={
                                     "display": "grid",
                                     "gridTemplateColumns": "1fr auto 1fr",
                                     "alignItems": "center",
                                     "marginBottom": "14px",
-                                }
+                                },
                             ),
                             html.Div(
                                 html.Div(
                                     [
                                         control_block(
                                             "Theme",
-                                            labeled_toggle("Day", "theme-toggle", "Night", value=night_default, fg=fg0, width_pix=220),
+                                            labeled_toggle(
+                                                "Day",
+                                                "theme-toggle",
+                                                "Night",
+                                                value=night_default,
+                                                fg=fg0,
+                                                width_pix=220,
+                                            ),
                                             fg=fg0,
-                                            width_px=220
+                                            width_px=220,
                                         ),
                                         control_block(
                                             "Origin",
-                                            labeled_toggle("Helio", "origin-toggle", "Bary", value=origin_bary_default, fg=fg0, width_pix=220),
+                                            labeled_toggle(
+                                                "Helio",
+                                                "origin-toggle",
+                                                "Bary",
+                                                value=origin_bary_default,
+                                                fg=fg0,
+                                                width_pix=220,
+                                            ),
                                             fg=fg0,
-                                            width_px=220
+                                            width_px=220,
                                         ),
                                         plane_block_layout,
                                         html.Div(
                                             [
                                                 control_block(
                                                     "View",
-                                                    labeled_toggle("2D", "view-toggle", "3D", value=view_3d_default, fg=fg0, width_pix=200),
+                                                    labeled_toggle(
+                                                        "2D",
+                                                        "view-toggle",
+                                                        "3D",
+                                                        value=view_3d_default,
+                                                        fg=fg0,
+                                                        width_pix=200,
+                                                    ),
                                                     fg=fg0,
-                                                    width_px=220
+                                                    width_px=220,
                                                 ),
                                                 html.Div(
                                                     panel_mode_block,
                                                     id="panel-controls-wrapper",
-                                                    style={"display": "none"}  # <-- start hidden since default view is 3D
-                                                )
+                                                    style={
+                                                        "display": "none"
+                                                    },  # <-- start hidden since default view is 3D
+                                                ),
                                             ],
-                                            style={"display": "flex", "flexDirection": "column", "alignItems": "center", "gap": "10px", "width": "100%", "minWidth": "0"}
+                                            style={
+                                                "display": "flex",
+                                                "flexDirection": "column",
+                                                "alignItems": "center",
+                                                "gap": "10px",
+                                                "width": "100%",
+                                                "minWidth": "0",
+                                            },
                                         ),
                                         control_block(
                                             "Edit Objects",
@@ -965,25 +1082,25 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                                         "color": fg0,
                                                         "fontSize": "20px",
                                                         "fontWeight": 600,
-                                                        "cursor": "pointer"
-                                                    }
+                                                        "cursor": "pointer",
+                                                    },
                                                 ),
-                                                style={"marginTop": "6px"}
+                                                style={"marginTop": "6px"},
                                             ),
                                             fg=fg0,
-                                            width_px=220
-                                        )
+                                            width_px=220,
+                                        ),
                                     ],
                                     id="controls-row",
                                     style={
                                         "display": "grid",
-                                        "gridTemplateColumns": "repeat(5, minmax(260px, 1fr))", # <-- this makes it an evenly spaced grid of 5 objects
+                                        "gridTemplateColumns": "repeat(5, minmax(260px, 1fr))",  # <-- this makes it an evenly spaced grid of 5 objects
                                         "alignItems": "start",
                                         "gap": "32px",
                                         "width": "100%",
                                         "boxSizing": "border-box",
-                                        "justifyItems": "stretch"
-                                    }
+                                        "justifyItems": "stretch",
+                                    },
                                 ),
                                 style={
                                     "width": "100%",
@@ -991,9 +1108,9 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                     "overflowY": "visible",
                                     "paddingLeft": "32px",
                                     "paddingRight": "32px",
-                                    "boxSizing": "border-box"
-                                }
-                            )
+                                    "boxSizing": "border-box",
+                                },
+                            ),
                         ],
                         id="controls-content",
                         style={
@@ -1004,7 +1121,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             "color": fg0,
                             "borderBottom": f"1px solid {theme0['border']}",
                             "backdropFilter": "blur(10px)",
-                        }
+                        },
                     )
                 ],
                 id="controls-drawer",
@@ -1023,7 +1140,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                     "transform": "translateY(-100%)",
                     "transition": "transform 180ms ease",
                     "pointerEvents": "none",
-                }
+                },
             ),
             html.Div(
                 [
@@ -1032,11 +1149,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                         id="orbit-graph",
                         figure=initial_fig,
                         style={"width": "100%", "height": "100%"},
-                        config={
-                            "displaylogo": False,
-                            "responsive": True,
-                            "displayModeBar": True
-                        }
+                        config={"displaylogo": False, "responsive": True, "displayModeBar": True},
                     ),
                     # panel dropdown overlay (on-plot, not in drawer)
                     html.Div(
@@ -1046,7 +1159,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                 options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
                                 value="XY",
                                 clearable=False,
-                                style={"width": "110px", "color": "#111111"}
+                                style={"width": "110px", "color": "#111111"},
                             ),
                         ],
                         id="panel-overlay-single",
@@ -1062,8 +1175,8 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             "background": theme0["tab_bg"],
                             "border": f"1px solid {theme0['border']}",
                             "backdropFilter": "blur(10px)",
-                            "pointerEvents": "auto"
-                        }
+                            "pointerEvents": "auto",
+                        },
                     ),
                     html.Div(
                         [
@@ -1072,7 +1185,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                 options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
                                 value="XY",
                                 clearable=False,
-                                style={"width": "110px", "color": "#111111"}
+                                style={"width": "110px", "color": "#111111"},
                             ),
                         ],
                         id="panel-overlay-left",
@@ -1088,8 +1201,8 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             "background": theme0["tab_bg"],
                             "border": f"1px solid {theme0['border']}",
                             "backdropFilter": "blur(10px)",
-                            "pointerEvents": "auto"
-                        }
+                            "pointerEvents": "auto",
+                        },
                     ),
                     html.Div(
                         [
@@ -1098,7 +1211,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                 options=[{"label": p, "value": p} for p in ["XY", "XZ", "YZ"]],
                                 value="YZ",
                                 clearable=False,
-                                style={"width": "110px", "color": "#111111"}
+                                style={"width": "110px", "color": "#111111"},
                             )
                         ],
                         id="panel-overlay-right",
@@ -1114,13 +1227,12 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             "background": theme0["tab_bg"],
                             "border": f"1px solid {theme0['border']}",
                             "backdropFilter": "blur(10px)",
-                            "pointerEvents": "auto"
-                        }
-                    )
+                            "pointerEvents": "auto",
+                        },
+                    ),
                 ],
-                style={"position": "fixed", "inset": "0", "zIndex": 1}
+                style={"position": "fixed", "inset": "0", "zIndex": 1},
             ),
-
             # make the object table modal manager
             html.Div(
                 id="objects-modal",
@@ -1131,7 +1243,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                     "zIndex": 20000,
                     "background": "rgba(0,0,0,0.55)",
                     "backdropFilter": "blur(6px)",
-                    "pointerEvents": "auto"
+                    "pointerEvents": "auto",
                 },
                 children=[
                     html.Div(
@@ -1147,39 +1259,70 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                             "boxSizing": "border-box",
                             "display": "flex",
                             "flexDirection": "column",
-                            "gap": "12px"
+                            "gap": "12px",
                         },
                         children=[
                             html.Div(
-                                style={"display": "flex", "alignItems": "center", "justifyContent": "space-between", "gap": "10px"},
+                                style={
+                                    "display": "flex",
+                                    "alignItems": "center",
+                                    "justifyContent": "space-between",
+                                    "gap": "10px",
+                                },
                                 children=[
                                     html.Div(
                                         "Object Manager",
-                                        style={"fontSize": "22px", "fontWeight": 700, "color": fg0}
+                                        style={"fontSize": "22px", "fontWeight": 700, "color": fg0},
                                     ),
                                     html.Button(
                                         "x",
                                         id="objects-close",
                                         n_clicks=0,
-                                        style={"border": "none", "background": "transparent", "color": fg0, "fontSize": "22px", "cursor": "pointer"}
-                                    )
-                                ]
+                                        style={
+                                            "border": "none",
+                                            "background": "transparent",
+                                            "color": fg0,
+                                            "fontSize": "22px",
+                                            "cursor": "pointer",
+                                        },
+                                    ),
+                                ],
                             ),
                             html.Div(
-                                style={"display": "flex", "gap": "10px", "flexWrap": "wrap", "alignItems": "center"},
+                                style={
+                                    "display": "flex",
+                                    "gap": "10px",
+                                    "flexWrap": "wrap",
+                                    "alignItems": "center",
+                                },
                                 children=[
                                     dcc.Input(
                                         id="obj-quickfilter",
                                         type="text",
                                         placeholder="Search... (filter rows)",
                                         value="",
-                                        style={"width": "340px", "height": "40px", "borderRadius": "12px", "border": f"1px solid {theme0['border']}", "padding": "0 12px", "outline": "none"}
+                                        style={
+                                            "width": "340px",
+                                            "height": "40px",
+                                            "borderRadius": "12px",
+                                            "border": f"1px solid {theme0['border']}",
+                                            "padding": "0 12px",
+                                            "outline": "none",
+                                        },
+                                    ),
+                                    html.Div(
+                                        id="obj-count",
+                                        style={"color": fg0, "opacity": 0.9, "fontSize": "14px"},
                                     ),
-                                    html.Div(id="obj-count", style={"color": fg0, "opacity": 0.9, "fontSize": "14px"})
-                                ]
+                                ],
                             ),
                             html.Div(
-                                style={"display": "flex", "gap": "10px", "flexWrap": "wrap", "alignItems": "center"},
+                                style={
+                                    "display": "flex",
+                                    "gap": "10px",
+                                    "flexWrap": "wrap",
+                                    "alignItems": "center",
+                                },
                                 children=[
                                     html.Button("Show selected", id="obj-show-selected", n_clicks=0),
                                     html.Button("Hide selected", id="obj-hide-selected", n_clicks=0),
@@ -1187,8 +1330,8 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                     html.Button("Hide filtered", id="obj-hide-filtered", n_clicks=0),
                                     html.Button("Show all", id="obj-show-all", n_clicks=0),
                                     html.Button("Hide all", id="obj-hide-all", n_clicks=0),
-                                    html.Button("Invert Selection", id="obj-invert", n_clicks=0)
-                                ]
+                                    html.Button("Invert Selection", id="obj-invert", n_clicks=0),
+                                ],
                             ),
                             html.Div(
                                 style={"flex": "1 1 auto", "minHeight": "0"},
@@ -1200,7 +1343,7 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                                 "headerName": "Kind",
                                                 "field": "kind",
                                                 "width": 120,
-                                                "filter": True
+                                                "filter": True,
                                             },
                                             {
                                                 "headerName": "Name",
@@ -1208,74 +1351,95 @@ def control_block(title: str, body, fg: str, width_px: int=200):
                                                 "flex": 1,
                                                 "filter": True,
                                                 "checkboxSelection": True,
-                                                "headerCheckboxSelection": True
+                                                "headerCheckboxSelection": True,
                                             },
                                             {
                                                 "headerName": "Visible",
                                                 "field": "visible",
                                                 "width": 120,
-                                                "filter": True
+                                                "filter": True,
                                             },
                                         ],
                                         rowData=[],
                                         defaultColDef={"sortable": True, "resizable": True},
                                         dashGridOptions={
-                                            "rowSelection": "multiple", 
-                                            "animateRows": False, 
+                                            "rowSelection": "multiple",
+                                            "animateRows": False,
                                             "suppressRowClickSelection": False,
-                                            "rowHeight": 34
+                                            "rowHeight": 34,
                                         },
                                         className="ag-theme-quartz",
-                                        style={"height": "100%", "width": "100%"}
+                                        style={"height": "100%", "width": "100%"},
                                     )
-                                ]
-                            )
-                        ]
+                                ],
+                            ),
+                        ],
                     )
-                ]
-
+                ],
             ),
             # make the colour selector window
             dcc.Store(id="plane-colour-open", data=False),
             html.Div(
                 id="plane-colour-modal",
                 n_clicks=0,
-                style={"display": "none", "position": "fixed", "inset": 0, "zIndex": 25000, "background": "rgba(0,0,0,0.55)", "backdropFilter": "blur(6px)", "pointerEvents": "auto"},
+                style={
+                    "display": "none",
+                    "position": "fixed",
+                    "inset": 0,
+                    "zIndex": 25000,
+                    "background": "rgba(0,0,0,0.55)",
+                    "backdropFilter": "blur(6px)",
+                    "pointerEvents": "auto",
+                },
                 children=[
                     html.Div(
                         id="plane-colour-card",
                         n_clicks=0,
-                        style={"width": "min(520px, 92vw)", "margin": "12vh auto", "background": theme0["drawer_bg"], "border": f"1px solid {theme0['border']}", "borderRadius": "16px", "padding": "16px", "boxSizing": "border-box"},
+                        style={
+                            "width": "min(520px, 92vw)",
+                            "margin": "12vh auto",
+                            "background": theme0["drawer_bg"],
+                            "border": f"1px solid {theme0['border']}",
+                            "borderRadius": "16px",
+                            "padding": "16px",
+                            "boxSizing": "border-box",
+                        },
                         children=[
                             html.Div(
-                                style={"display": "flex", "alignItems": "center", "justifyContent": "space-between"},
+                                style={
+                                    "display": "flex",
+                                    "alignItems": "center",
+                                    "justifyContent": "space-between",
+                                },
                                 children=[
                                     html.Div(
                                         "Reference Plane Colour",
-                                        style={"fontSize": "18px", "fontWeight": 700, "color": fg0}
+                                        style={"fontSize": "18px", "fontWeight": 700, "color": fg0},
                                     ),
                                     html.Button(
                                         "x",
                                         id="plane-colour-close",
                                         n_clicks=0,
-                                        style={"border": "none", "background": "transparent", "color": fg0, "fontSize": "22px", "cursor": "pointer"}
-                                    )
-                                ]
+                                        style={
+                                            "border": "none",
+                                            "background": "transparent",
+                                            "color": fg0,
+                                            "fontSize": "22px",
+                                            "cursor": "pointer",
+                                        },
+                                    ),
+                                ],
                             ),
                             html.Div(
                                 style={"marginTop": "12px", "display": "flex", "justifyContent": "center"},
                                 children=[
-                                    daq.ColorPicker(
-                                        id="plane-colour",
-                                        value={"hex": "#F5B277"},
-                                        size=220
-                                    )
-                                ]
-                            )
-                        ]
+                                    daq.ColorPicker(id="plane-colour", value={"hex": "#F5B277"}, size=220)
+                                ],
+                            ),
+                        ],
                     )
-                ]
-            )
+                ],
+            ),
         ],
         id="app-shell",
         className="theme-dark" if night_default else "theme-light",
@@ -1286,14 +1450,13 @@ def control_block(title: str, body, fg: str, width_px: int=200):
             "padding": "0",
             "backgroundColor": theme0["bg"],
             "color": fg0,
-        }
+        },
     )
 
-
     # -- interactive --
     # this bit does a bit of javascript-y hackery: basically 1) whenever the controls-open state
     # changes, we grab its id, then 2) get its pixel dimensions on screen (r = ...), then 3) we
-    # get that height (or 0 if missing) and store it in drawer-height - all of this is done in web  
+    # get that height (or 0 if missing) and store it in drawer-height - all of this is done in web
     app.clientside_callback(
         """
         function(is_open) {
@@ -1304,22 +1467,26 @@ def control_block(title: str, body, fg: str, width_px: int=200):
         }
         """,
         Output("drawer-height", "data"),
-        Input("controls-open", "data")
+        Input("controls-open", "data"),
     )
 
     # this bit lets the code know what state the dropdown controls tab is in (open/closed?)
     @app.callback(
         Output("controls-open", "data"),
-        Input("controls-tab", "n_clicks"), # <-- toggle tab open/close
-        Input("controls-close", "n_clicks"), # <-- force close 
+        Input("controls-tab", "n_clicks"),  # <-- toggle tab open/close
+        Input("controls-close", "n_clicks"),  # <-- force close
         State("controls-open", "data"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def toggle_controls(_tab_clicks: int|None, _close_clicks: int|None, is_open: bool):
-        trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else "" # <-- this registers what input fires the callback
+    def toggle_controls(_tab_clicks: int | None, _close_clicks: int | None, is_open: bool):
+        trig = (
+            ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else ""
+        )  # <-- this registers what input fires the callback
         if trig == "controls-close":
-            return False # <-- if the X button is pressed, force closed
-        return not bool(is_open) # <-- if the \/ button is pressed, invert whatever state is_open is in (ie close/open)
+            return False  # <-- if the X button is pressed, force closed
+        return not bool(
+            is_open
+        )  # <-- if the \/ button is pressed, invert whatever state is_open is in (ie close/open)
 
     # now we will alter the position, state, movement, and buttons on the controls drawer here
     @app.callback(
@@ -1330,9 +1497,15 @@ def toggle_controls(_tab_clicks: int|None, _close_clicks: int|None, is_open: boo
         Input("theme-toggle", "value"),
         Input("drawer-height", "data"),
         State("controls-drawer", "style"),
-        State("controls-tab", "style")
+        State("controls-tab", "style"),
     )
-    def style_drawer(is_open: bool, night_mode: bool, drawer_h: float|int|None, drawer_style: dict[str, Any]|None, tab_style: dict[str, Any]|None):
+    def style_drawer(
+        is_open: bool,
+        night_mode: bool,
+        drawer_h: float | int | None,
+        drawer_style: dict[str, Any] | None,
+        tab_style: dict[str, Any] | None,
+    ):
         theme = THEME["night"] if night_mode else THEME["day"]
         fg = theme["fg"]
 
@@ -1346,10 +1519,12 @@ def style_drawer(is_open: bool, night_mode: bool, drawer_h: float|int|None, draw
         ds["overflow"] = "visible"
         ds["display"] = "flex"
         ds["flexDirection"] = "column"
-        ds["transition"] = "transform 180ms ease" # <-- make it smooth pulling out
+        ds["transition"] = "transform 180ms ease"  # <-- make it smooth pulling out
         ds["transform"] = "translateY(0%)" if is_open else "translateY(-100%)"
         ds["zIndex"] = 4000
-        ds["pointerEvents"] = "auto" if is_open else "none" # <-- makes sure it wont block the plotly plot elements when closed
+        ds["pointerEvents"] = (
+            "auto" if is_open else "none"
+        )  # <-- makes sure it wont block the plotly plot elements when closed
 
         # alter some aspects of the button (note: in this context its also called a tab). the
         # colour and theme changes depending on day/night mode
@@ -1371,22 +1546,24 @@ def style_drawer(is_open: bool, night_mode: bool, drawer_h: float|int|None, draw
         ts["transition"] = "top 180ms ease"
 
         # this bit places the \/ button either near the top (10px) when closed, or near the bottom edge
-        # of the drawer (inset top_px) when open
+        # of the drawer (inset top_px) when open
         try:
             h = float(drawer_h) if drawer_h is not None else 0.0
         except Exception:
             h = 0.0
 
         if is_open and h > 0:
-            top_px = max(10, int(h-36-10)) # <-- drawer bottom (h) - button height (36) - small padding (10)
+            top_px = max(
+                10, int(h - 36 - 10)
+            )  # <-- drawer bottom (h) - button height (36) - small padding (10)
             ts["top"] = f"{top_px}px"
         else:
             ts["top"] = "10px"
 
-        chevron ="⌃" if is_open else "⌄"
-        
+        chevron = "⌃" if is_open else "⌄"
+
         return ds, chevron, ts
-    
+
     # reference plane colour picker
     @app.callback(
         Output("plane-colour-modal", "style", allow_duplicate=True),
@@ -1396,9 +1573,15 @@ def style_drawer(is_open: bool, night_mode: bool, drawer_h: float|int|None, draw
         Input("theme-toggle", "value"),
         State("plane-colour-modal", "style"),
         State("plane-colour-card", "style"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def toggle_plane_colour_modal(open_clicks: int|None, close_clicks: int|None, night_mode: bool, modal_style: dict[str, Any]|None, card_style: dict[str, Any]|None):
+    def toggle_plane_colour_modal(
+        open_clicks: int | None,
+        close_clicks: int | None,
+        night_mode: bool,
+        modal_style: dict[str, Any] | None,
+        card_style: dict[str, Any] | None,
+    ):
         theme = THEME["night"] if night_mode else THEME["day"]
         ms = dict(modal_style or {})
         cs = dict(card_style or {})
@@ -1414,16 +1597,18 @@ def toggle_plane_colour_modal(open_clicks: int|None, close_clicks: int|None, nig
             ms["display"] = "none"
 
         return ms, cs
-    
+
     # add ability to close out of colour picker by just selecting backdrop
     @app.callback(
         Output("plane-colour-modal", "style", allow_duplicate=True),
         Input("plane-colour-modal", "n_clicks"),
         Input("plane-colour-card", "n_clicks"),
         State("plane-colour-modal", "style"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def close_plane_colour_on_backdrop(modal_clicks: int|None, card_clicks: int|None, style: dict[str, Any]|None):
+    def close_plane_colour_on_backdrop(
+        modal_clicks: int | None, card_clicks: int | None, style: dict[str, Any] | None
+    ):
         trig = ctx.triggered_id
 
         # if the backdrop itself was clicked, then close altogether
@@ -1431,7 +1616,7 @@ def close_plane_colour_on_backdrop(modal_clicks: int|None, card_clicks: int|None
             style = dict(style or {})
             style["display"] = "none"
             return style
-        
+
         # but if click was inside the colour picker card, do nothing
         raise dash.exceptions.PreventUpdate
 
@@ -1444,9 +1629,15 @@ def close_plane_colour_on_backdrop(modal_clicks: int|None, card_clicks: int|None
         Input("theme-toggle", "value"),
         State("objects-modal", "style"),
         State("objects-modal-card", "style"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def toggle_objects_modal(open: int|None, close: int|None, night_mode: bool, modal_style: dict[str, Any]|None, card_style: dict[str, Any]|None):
+    def toggle_objects_modal(
+        open: int | None,
+        close: int | None,
+        night_mode: bool,
+        modal_style: dict[str, Any] | None,
+        card_style: dict[str, Any] | None,
+    ):
         theme = THEME["night"] if night_mode else THEME["day"]
         fg = theme["fg"]
 
@@ -1462,25 +1653,22 @@ def toggle_objects_modal(open: int|None, close: int|None, night_mode: bool, moda
             ms["display"] = "block"
         elif trig == "objects-close":
             ms["display"] = "none"
-        
+
         return ms, cs
-    
+
     # add search filtering
-    @app.callback(
-        Output("objects-grid", "quickFilterText"),
-        Input("obj-quickfilter", "value")
-    )
-    def grid_quickfilter(txt: str|None):
+    @app.callback(Output("objects-grid", "quickFilterText"), Input("obj-quickfilter", "value"))
+    def grid_quickfilter(txt: str | None):
         return txt or ""
-    
+
     # make orbits visible / invisibile from table selections
     @app.callback(
         Output("objects-grid", "rowData"),
         Output("obj-count", "children"),
         Input("visible-objids", "data"),
-        Input("visible-planets", "data")
+        Input("visible-planets", "data"),
     )
-    def sync_grid_rows(visible_objids: list[str]|None, visible_planets: list[str]|None):
+    def sync_grid_rows(visible_objids: list[str] | None, visible_planets: list[str] | None):
         vis_o = set(visible_objids or [])
         vis_p = set(visible_planets or [])
 
@@ -1489,15 +1677,15 @@ def sync_grid_rows(visible_objids: list[str]|None, visible_planets: list[str]|No
             k = r["kind"]
             name = r["name"]
             if k == "Planet":
-                vis = (name in vis_p)
+                vis = name in vis_p
             else:
-                vis = (name in vis_o)
+                vis = name in vis_o
             rows.append({"kind": k, "name": name, "visible": "✓" if vis else ""})
 
         shown = len(vis_o) + len(vis_p)
         total = len(inv_objids) + len(inv_planets)
         return rows, f"Visible: {shown} / {total}"
-    
+
     # bulk actions from the manager
     @app.callback(
         Output("visible-objids", "data"),
@@ -1513,21 +1701,41 @@ def sync_grid_rows(visible_objids: list[str]|None, visible_planets: list[str]|No
         State("objects-grid", "virtualRowData"),
         State("visible-objids", "data"),
         State("visible-planets", "data"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def bulk_visibility(n1: int|None, n2: int|None, n3: int|None, n4: int|None, n5: int|None, n6: int|None, n7: int|None, selected_rows: list[dict[str, Any]]|None, virtual_rows: list[dict[str, Any]]|None, visible_objids: list[str]|None, visible_planets: list[str]|None):
+    def bulk_visibility(
+        n1: int | None,
+        n2: int | None,
+        n3: int | None,
+        n4: int | None,
+        n5: int | None,
+        n6: int | None,
+        n7: int | None,
+        selected_rows: list[dict[str, Any]] | None,
+        virtual_rows: list[dict[str, Any]] | None,
+        visible_objids: list[str] | None,
+        visible_planets: list[str] | None,
+    ):
         # /\ all of the n* are the various click values for the inputs, if they're not there plotly and dash break
         trig = ctx.triggered[0]["prop_id"].split(".")[0] if ctx.triggered else ""
 
         vis_o = set(visible_objids or [])
         vis_p = set(visible_planets or [])
 
-        def split(rows: list[dict[str, Any]]|None):
+        def split(rows: list[dict[str, Any]] | None):
             rows = rows or []
-            ps = {str(r.get("name")) for r in rows if str(r.get("kind")) == "Planet" and r.get("name") is not None}
-            os = {str(r.get("name")) for r in rows if str(r.get("kind")) != "Planet" and r.get("name") is not None}
+            ps = {
+                str(r.get("name"))
+                for r in rows
+                if str(r.get("kind")) == "Planet" and r.get("name") is not None
+            }
+            os = {
+                str(r.get("name"))
+                for r in rows
+                if str(r.get("kind")) != "Planet" and r.get("name") is not None
+            }
             return ps, os
-        
+
         sel_p, sel_o = split(selected_rows)
         fil_p, fil_o = split(virtual_rows)
 
@@ -1555,7 +1763,7 @@ def split(rows: list[dict[str, Any]]|None):
             vis_o = set(inv_objids) - vis_o
         else:
             raise dash.exceptions.PreventUpdate
-        
+
         return sorted(vis_o), sorted(vis_p)
 
     # this section records the zoom/camera state into view-state
@@ -1564,24 +1772,32 @@ def split(rows: list[dict[str, Any]]|None):
         Input("orbit-graph", "relayoutData"),
         State("view-toggle", "value"),
         State("view-state", "data"),
-        prevent_initial_call=True
+        prevent_initial_call=True,
     )
-    def capture_view(relayout: dict[str, Any]|None, view_3d: bool, state: dict[str, Any]|None):
+    def capture_view(relayout: dict[str, Any] | None, view_3d: bool, state: dict[str, Any] | None):
         # ignore any callbacks that don't actually change the view
         if not relayout:
             return dash.no_update
-        
+
         # ignore relayouts that are just layout/style updates
-        camera_keys = {"scene.camera", "xaxis.range[0]", "xaxis.range[1]", "yaxis.range[0]", "yaxis.range[1]", "xaxis.autorange", "yaxis.autorange"}
+        camera_keys = {
+            "scene.camera",
+            "xaxis.range[0]",
+            "xaxis.range[1]",
+            "yaxis.range[0]",
+            "yaxis.range[1]",
+            "xaxis.autorange",
+            "yaxis.autorange",
+        }
 
         if not any(k in relayout for k in camera_keys):
             return dash.no_update
-        
+
         # figure out what mode we're in
         state = dict(state or {})
         mode = "3d" if view_3d else "2d"
 
-        # if the mode has changed since last time, reset the stored view 
+        # if the mode has changed since last time, reset the stored view
         # (viewpoint between 2d <-> 3d shouldn't be saved)
         if state.get("mode") != mode:
             state = {"mode": mode, "camera": None, "xrange": None, "yrange": None}
@@ -1633,9 +1849,23 @@ def capture_view(relayout: dict[str, Any]|None, view_3d: bool, state: dict[str,
         Input("panel-right", "value"),
         Input("visible-objids", "data"),
         Input("visible-planets", "data"),
-        State("view-state", "data")
+        State("view-state", "data"),
     )
-    def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_equ: bool, opacity: float, plane_colour, panel_mode: str, panel_single: str, panel_left: str, panel_right: str, visible_objids: list[str]|None, visible_planets: list[str]|None, view_state: dict[str, object]):
+    def update_orbit_plot(
+        night_mode: bool,
+        view_3d: bool,
+        origin_bary: bool,
+        plane_equ: bool,
+        opacity: float,
+        plane_colour,
+        panel_mode: str,
+        panel_single: str,
+        panel_left: str,
+        panel_right: str,
+        visible_objids: list[str] | None,
+        visible_planets: list[str] | None,
+        view_state: dict[str, object],
+    ):
         # set up some figure themings
         theme = THEME["night"] if night_mode else THEME["day"]
         bg = theme["bg"]
@@ -1659,7 +1889,7 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
 
         for trace in fig.data:
             # we need to differentiate planets from input objects to make sure
-            # they are coloured properly, so we use their meta tags we set up 
+            # they are coloured properly, so we use their meta tags we set up
             # earlier to toggle their colours appropriately
             is_planet = (
                 getattr(trace, "meta", None) is not None
@@ -1670,11 +1900,11 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
                 name = str(trace.name)
                 trace.line.color = (
                     PLANET_COLOURS_NIGHT.get(name, "rgba(220,220,220,0.7)")
-                    if night_mode else
-                    PLANET_COLOURS_DAY.get(name, "rgba(220,220,220,0.7)")
+                    if night_mode
+                    else PLANET_COLOURS_DAY.get(name, "rgba(220,220,220,0.7)")
                 )
                 continue
-            
+
             # every other non-planet is the default colour then
             if trace.type in ("scatter", "scatter3d") and getattr(trace, "mode", None) == "lines":
                 trace.line.color = orbit_colour
@@ -1682,10 +1912,7 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
             # also colour input object epoch markers differently if day or night mode
             meta = getattr(trace, "meta", None)
             if isinstance(meta, dict) and meta.get("kind") == "epoch":
-                trace.marker.color = (
-                    "rgba(255,255,255,0.9)" if night_mode
-                    else "rgba(30,30,30,0.9)"
-                )
+                trace.marker.color = "rgba(255,255,255,0.9)" if night_mode else "rgba(30,30,30,0.9)"
 
         # apply object visibility
         vis_o = set(visible_objids or [])
@@ -1694,15 +1921,18 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
         for trace in fig.data:
             meta = getattr(trace, "meta", None)
             kind = meta.get("kind") if isinstance(meta, dict) else None
-            
+
             if kind == "Planet":
-                trace.visible = (str(getattr(trace, "name", "")) in vis_p)
+                trace.visible = str(getattr(trace, "name", "")) in vis_p
                 continue
 
-            if getattr(trace, "type", None) in ("scatter", "scatter3d") and getattr(trace, "mode", None) == "lines":
+            if (
+                getattr(trace, "type", None) in ("scatter", "scatter3d")
+                and getattr(trace, "mode", None) == "lines"
+            ):
                 name = str(getattr(trace, "name", ""))
                 if name and name != "ref-plane":
-                    trace.visible = (name in vis_o)
+                    trace.visible = name in vis_o
 
             if isinstance(meta, dict) and meta.get("kind") == "epoch":
                 texts = getattr(trace, "text", None)
@@ -1721,18 +1951,13 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
 
                     if plane_colour and "hex" in plane_colour:
                         c = plane_colour["hex"]
-                        trace.update(colorscale=[[0,c], [1,c]], cmin=0, cmax=1, showscale=False)
+                        trace.update(colorscale=[[0, c], [1, c]], cmin=0, cmax=1, showscale=False)
 
-        # set up the background of the whole figure canvas + plotting region 
-        # so that they are transparent (ie page theme is controlling background,
+        # set up the background of the whole figure canvas + plotting region
+        # so that they are transparent (ie page theme is controlling background,
         # not plotly itself)
         paper = "rgba(0,0,0,0)" if bg == "black" else "rgba(255,255,255,0)"
-        fig.update_layout(
-            paper_bgcolor=paper,
-            plot_bgcolor=paper,
-            font=dict(color=fg),
-            uirevision="keep"
-        )
+        fig.update_layout(paper_bgcolor=paper, plot_bgcolor=paper, font=dict(color=fg), uirevision="keep")
 
         # style the axis grids in 2d or 3d
         if hasattr(fig, "update_xaxes"):
@@ -1741,16 +1966,19 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
 
         if getattr(fig.layout, "scene", None) is not None:
             fig.update_scenes(
-                xaxis_gridcolor=grid, xaxis_zerolinecolor=zero,
-                yaxis_gridcolor=grid, yaxis_zerolinecolor=zero,
-                zaxis_gridcolor=grid, zaxis_zerolinecolor=zero
+                xaxis_gridcolor=grid,
+                xaxis_zerolinecolor=zero,
+                yaxis_gridcolor=grid,
+                yaxis_zerolinecolor=zero,
+                zaxis_gridcolor=grid,
+                zaxis_zerolinecolor=zero,
             )
-        
+
         # get current view state
         view_state = view_state or {}
         mode = "3d" if view_3d else "2d"
 
-        # if we're in the same view mode, reapply the stored view. this helps us 
+        # if we're in the same view mode, reapply the stored view. this helps us
         # preserve the view across theme/origin/plane changes
         if view_state.get("mode") == mode:
             if mode == "3d" and view_state.get("camera") and getattr(fig.layout, "scene", None) is not None:
@@ -1762,7 +1990,7 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
                     fig.update_xaxes(range=xr, autorange=False)
                 if yr is not None:
                     fig.update_yaxes(range=yr, autorange=False)
-        
+
         # set the style of the outermost html container
         shell_style = {
             "height": "100vh",
@@ -1770,7 +1998,7 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
             "margin": "0",
             "padding": "0",
             "backgroundColor": bg,
-            "color": fg
+            "color": fg,
         }
         shell_class = "theme-dark" if night_mode else "theme-light"
 
@@ -1788,7 +2016,7 @@ def update_orbit_plot(night_mode: bool, view_3d: bool, origin_bary: bool, plane_
             "border": f"1px solid {theme['border']}",
             "backdropFilter": "blur(10px)",
             "pointerEvents": "auto",
-            "display": "none"
+            "display": "none",
         }
 
         single_style = dict(base_overlay)
@@ -1819,15 +2047,15 @@ def open_browser():
         webbrowser.open_new("http://127.0.0.1:8050/")
 
     # this is a reloader that prevents us accidentally opening two tabs
-    # at the same time (this kept happening to me in debugging), 
-    # giving the server time to start before the browser visits the url 
+    # at the same time (this kept happening to me in debugging),
+    # giving the server time to start before the browser visits the url
     # (see https://stackoverflow.com/questions/9449101/how-to-stop-flask-from-initialising-twice-in-debug-mode?)
     if os.environ.get("WERKZEUG_RUN_MAIN") == "true":
         threading.Timer(1.0, open_browser).start()
 
-    # avoid spam in the terminal 
+    # avoid spam in the terminal
     log = logging.getLogger("werkzeug")
     log.setLevel(logging.ERROR)
 
     # now run the server!
-    app.run(debug=False, use_reloader=True)
\ No newline at end of file
+    app.run(debug=False, use_reloader=True)
diff --git a/src/layup/orbit_maths.py b/src/layup/orbit_maths.py
index efa2d01d..233cd496 100644
--- a/src/layup/orbit_maths.py
+++ b/src/layup/orbit_maths.py
@@ -34,9 +34,10 @@
     "Jupiter": 4332.589,
     "Saturn": 10759.22,
     "Uranus": 30688.5,
-    "Neptune": 60182.0
+    "Neptune": 60182.0,
 }
 
+
 @dataclass(frozen=True)
 class ClassicalConic:
     "Data class for each object conic section"
@@ -58,10 +59,7 @@ class ClassicalConic:
 
 
 # --- converter ---
-def convert_cart_to_classical_conic(
-        rows: np.ndarray,
-        mu: float
-) -> ClassicalConic:
+def convert_cart_to_classical_conic(rows: np.ndarray, mu: float) -> ClassicalConic:
     """
     Convert cartesian elements into classical conic elements (L, e, i, Omega, omega)
 
@@ -93,8 +91,8 @@ def convert_cart_to_classical_conic(
 
     # calculate inclination:
     # i = cos^-1(h_z / |h|)
-    # notes: hvec[:, 2] = h_z, we use np.maximum and np.clip to avoid 
-    # division by zero and floating point arithmetic giving answers that 
+    # notes: hvec[:, 2] = h_z, we use np.maximum and np.clip to avoid
+    # division by zero and floating point arithmetic giving answers that
     # aren't in the range -1 <= h_z / |h| <= 1
     incl = np.arccos(np.clip(hvec[:, 2] / np.maximum(hnorm, 1e-30), -1.0, 1.0))
 
@@ -133,17 +131,17 @@ def convert_cart_to_classical_conic(
     # cos(omega) = (nvec dot evec) / (|n||e|)
     # sin(omega) = ((nvec x evec) dot hvec) / (|n||e||h|)
     # note: we're clipping again for the same reasons as above
-    # (floating point arithmetic + division by zero), and we do 
+    # (floating point arithmetic + division by zero), and we do
     # np.sum as we have an (N, 3) list of orbits in e.g. nvec, so
     # doing np.dot would result in matrix multiplication (if pedro
-    # reads this in future, yes np.einsum does this but i hate the 
+    # reads this in future, yes np.einsum does this but i hate the
     # notation :p). finally arctan2 once again solves quadrant issues
     cosw = np.sum(nvec * evec, axis=1) / (nnorm * e)
     cosw = np.clip(cosw, -1.0, 1.0)
     sinw = np.sum(np.cross(nvec, evec) * hvec, axis=1) / (nnorm * e * np.maximum(hnorm, 1e-30))
-    argp = (np.arctan2(sinw, cosw) % (2 * np.pi))
+    argp = np.arctan2(sinw, cosw) % (2 * np.pi)
 
-    # finally check if orbit is sat in reference plane, if so we 
+    # finally check if orbit is sat in reference plane, if so we
     # overwrrite Omega to be = 0, and even though omega is strictly
     # undefined in this case, perihelion direction isn't due to evec,
     # which we need to draw the orbit later, therefore we just recalc
@@ -151,24 +149,21 @@ def convert_cart_to_classical_conic(
     equatorial = nnorm < 1e-12
     if np.any(equatorial):
         node[equatorial] = 0.0
-        argp[equatorial] = (np.arctan2(evec[equatorial, 1], evec[equatorial, 0]) % (2 * np.pi))
+        argp[equatorial] = np.arctan2(evec[equatorial, 1], evec[equatorial, 0]) % (2 * np.pi)
 
-    return ClassicalConic(obj_id=obj_id, L=L, e=e, inc=incl, node=node, argp=argp, epochMJD_TDB=rows["epochMJD_TDB"])
+    return ClassicalConic(
+        obj_id=obj_id, L=L, e=e, inc=incl, node=node, argp=argp, epochMJD_TDB=rows["epochMJD_TDB"]
+    )
 
 
 # --- frame swapping ---
-def rv_to_cart(
-        obj_id: np.ndarray,
-        r: np.ndarray,
-        v: np.ndarray,
-        epochMJD_TDB: np.ndarray
-) -> np.ndarray:
+def rv_to_cart(obj_id: np.ndarray, r: np.ndarray, v: np.ndarray, epochMJD_TDB: np.ndarray) -> np.ndarray:
     """
     Wrapper function to create structured array of cartesian elements from position+velocity state vectors
 
     Parameters
     -----------
-    obj_id : numpy string array 
+    obj_id : numpy string array
         Object identifier tags
 
     r : numpy float array
@@ -185,18 +180,28 @@ def rv_to_cart(
     out : numpy structured array
         Array containing the cartesian elements (x,y,z,vx,vy,vz) with shape (N,)
     """
-    out = np.empty(r.shape[0], dtype=[("ObjID","U64"), ("x","f8"), ("y","f8"), ("z","f8"), ("xdot","f8"), ("ydot","f8"), ("zdot","f8"), ("epochMJD_TDB","f8")])
-    out["ObjID"] = obj_id.astype("U64")    
-    out["x"], out["y"], out["z"] = r[:,0], r[:,1], r[:,2]
-    out["xdot"], out["ydot"], out["zdot"] = v[:,0], v[:,1], v[:,2]
+    out = np.empty(
+        r.shape[0],
+        dtype=[
+            ("ObjID", "U64"),
+            ("x", "f8"),
+            ("y", "f8"),
+            ("z", "f8"),
+            ("xdot", "f8"),
+            ("ydot", "f8"),
+            ("zdot", "f8"),
+            ("epochMJD_TDB", "f8"),
+        ],
+    )
+    out["ObjID"] = obj_id.astype("U64")
+    out["x"], out["y"], out["z"] = r[:, 0], r[:, 1], r[:, 2]
+    out["xdot"], out["ydot"], out["zdot"] = v[:, 0], v[:, 1], v[:, 2]
     out["epochMJD_TDB"] = epochMJD_TDB.astype("f8")
     return out
 
+
 def to_rv(
-        rows: np.ndarray,
-        fmt: ORBIT_FORMAT,
-        mu_sun: float,
-        mu_total: float
+    rows: np.ndarray, fmt: ORBIT_FORMAT, mu_sun: float, mu_total: float
 ) -> tuple[np.ndarray, np.ndarray]:
     """
     Convert orbits into cartesian state vectors regardless of format utilising Sorcha functions.
@@ -208,7 +213,7 @@ def to_rv(
         Array with all of the orbits (shape = (N,), i.e. one orbit per row/record)
 
     fmt : str
-        Format of the orbit. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP" 
+        Format of the orbit. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP"
 
     mu_sun : float
         Standard (heliocentric) gravitional parameter (au^3 / day^2)
@@ -251,7 +256,7 @@ def to_rv(
             )
             r[i] = (x, y, z)
             v[i] = (vx, vy, vz)
-        
+
         return r, v
     # same for keplerian orbits
     if fmt in ("KEP", "BKEP"):
@@ -266,9 +271,9 @@ def to_rv(
 
         M_wrap = M.copy()
         idx = M_wrap > np.pi
-        M_wrap[idx] -= 2*np.pi
+        M_wrap[idx] -= 2 * np.pi
 
-        tpJD = epochJD - M_wrap * np.sqrt(a**3/mu)
+        tpJD = epochJD - M_wrap * np.sqrt(a**3 / mu)
         q = a * (1.0 - e)
 
         r = np.empty((rows.size, 3), dtype=float)
@@ -280,16 +285,17 @@ def to_rv(
             )
             r[i] = (x, y, z)
             v[i] = (vx, vy, vz)
-        
+
         return r, v
-    
+
     logger.error(f"Unsupported format: {fmt}")
     raise ValueError(f"Unsupported format: {fmt}")
 
+
 def build_ephem_and_mus(cache_dir: Optional[str] = None) -> tuple[Ephem, float, float]:
     """
-    Create Assist instance utilising Layup functions in order to find standard gravitationl parameters 
-    
+    Create Assist instance utilising Layup functions in order to find standard gravitationl parameters
+
     Parameters
     -----------
     cache_dir : str, optional
@@ -306,26 +312,26 @@ def build_ephem_and_mus(cache_dir: Optional[str] = None) -> tuple[Ephem, float,
     mu_total : float
         Standard (barycentric) gravitional parameter (au^3 / day^2)
     """
-    # yoink layup's auxiliary config class to locate the user's cached files 
+    # yoink layup's auxiliary config class to locate the user's cached files
     configs = LayupConfigs()
     aux = configs.auxiliary
 
     retriever = make_retriever(aux, cache_dir)
-    ephem = Ephem(planets_path=retriever.fetch(aux.jpl_planets), asteroids_path=retriever.fetch(aux.jpl_small_bodies))
-    
+    ephem = Ephem(
+        planets_path=retriever.fetch(aux.jpl_planets), asteroids_path=retriever.fetch(aux.jpl_small_bodies)
+    )
+
     # calculate mu same way as in sorcha
     mu_sun = ephem.get_particle("Sun", 0).m
-    mu_total = sum(sorted([ephem.get_particle(i,0).m for i in range(27)]))
+    mu_total = sum(sorted([ephem.get_particle(i, 0).m for i in range(27)]))
 
     return ephem, mu_sun, mu_total
 
-def convert_sun_to_baryecliptic(
-        ephem: Ephem,
-        epochJD: np.ndarray
-) -> tuple[np.ndarray, np.ndarray]:
+
+def convert_sun_to_baryecliptic(ephem: Ephem, epochJD: np.ndarray) -> tuple[np.ndarray, np.ndarray]:
     """
     Function to create translation vectors to go from barycentric to heliocentric origins
-    
+
     Parameters
     -----------
     ephem : assist Ephem object
@@ -360,21 +366,22 @@ def convert_sun_to_baryecliptic(
 
     return S_r, S_v
 
+
 # --- build all variants ---
 def prepopulate_orbit_variants(
-        rows: np.ndarray,
-        orbit_format: ORBIT_FORMAT,
-        input_plane: Literal["equatorial", "ecliptic"],
-        input_origin: Literal["heliocentric", "barycentric"]
+    rows: np.ndarray,
+    orbit_format: ORBIT_FORMAT,
+    input_plane: Literal["equatorial", "ecliptic"],
+    input_origin: Literal["heliocentric", "barycentric"],
 ) -> tuple[
     dict[tuple[str, str], ClassicalConic],
     dict[tuple[str, str], np.ndarray],
     dict[tuple[str, str], np.ndarray],
-    dict[tuple[str, str], np.ndarray]
+    dict[tuple[str, str], np.ndarray],
 ]:
     """
-    Create an output cache of input object class instances, an empty placeholder dict for their 
-    associated orbit lines, the Sun's positions, and the object's positions in all four combinations 
+    Create an output cache of input object class instances, an empty placeholder dict for their
+    associated orbit lines, the Sun's positions, and the object's positions in all four combinations
     of plane+origin
 
     Parameters
@@ -383,19 +390,19 @@ def prepopulate_orbit_variants(
         Array with all of the orbits (shape = (N,), i.e. one orbit per row/record)
 
     orbit_format : str
-        String detailing the input orbit format. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP" 
+        String detailing the input orbit format. Must be one of "BCART", "BCOM", "BKEP", "CART", "COM", "KEP"
 
     input_plane : str
         Input reference plane of the orbits. Must be one of "equatorial" or "ecliptic"
 
     input_origin : str
         Input origin of the orbits. Must be one of "heliocentric" or "barycentric"
-    
+
     Returns
     --------
     canon_cache : dict of objects
         Dictionary with the conic section class instances of each object and their properties
-    
+
     lines_cache : dict of numpy array
         Dictionary of arrays with the orbit lines for each object in each plane+origin combination
 
@@ -406,9 +413,9 @@ def prepopulate_orbit_variants(
         Dictionary of arrays with object positions in each plane+origin combination
     """
     # grab our planets+major perturbers and solar gravitational parameters
-    # # (mu_sun = heliocentric, mu_total = barycentric) 
+    # # (mu_sun = heliocentric, mu_total = barycentric)
     ephem, mu_sun, mu_total = build_ephem_and_mus()
-    
+
     obj_id = rows["ObjID"].astype(str)
     epochJD = rows["epochMJD_TDB"].astype(float) + 2400000.5
 
@@ -421,7 +428,7 @@ def prepopulate_orbit_variants(
     if input_plane == "equatorial":
         r_raw = np.dot(r_raw, EQ_TO_ECL_ROTATION_MATRIX)
         v_raw = np.dot(v_raw, EQ_TO_ECL_ROTATION_MATRIX)
-    
+
     # again, easier if it's heliocentric ecliptic, so convert bary -> helio
     r_helio_eclipt = r_raw.copy()
     v_helio_eclipt = v_raw.copy()
@@ -472,9 +479,7 @@ def prepopulate_orbit_variants(
 
 # --- orbit line generation ---
 def conic_lines_from_classical_conic(
-        canon: ClassicalConic,
-        n_points: int = 200,
-        r_max: float = 50.0
+    canon: ClassicalConic, n_points: int = 200, r_max: float = 50.0
 ) -> np.ndarray:
     """
     Given a set of classical conic elements (L, e, i, Omega, omega), draw the line of the orbit via
@@ -507,7 +512,7 @@ def conic_lines_from_classical_conic(
     ell = e < 1.0
     hyp = ~ell
 
-    # if elliptical, we just draw it from -pi to pi so it's centered on 
+    # if elliptical, we just draw it from -pi to pi so it's centered on
     # perihelion rather than 0 to 2pi
     if np.any(ell):
         nu[ell] = np.linspace(-np.pi, np.pi, n_points)
@@ -544,21 +549,19 @@ def conic_lines_from_classical_conic(
 
     # we now find the position vector rvec by:
     # rvec = (x, y, z) = R qvec
-    x = (c0*co - s0*so*ci)[:, None]*q1 + (-c0*so - s0*co*ci)[:, None]*q2
-    y = (s0*co + c0*so*ci)[:, None]*q1 + (-s0*so + c0*co*ci)[:, None]*q2
-    z = (so*si)[:, None]*q1 + (co*si)[:, None]*q2
+    x = (c0 * co - s0 * so * ci)[:, None] * q1 + (-c0 * so - s0 * co * ci)[:, None] * q2
+    y = (s0 * co + c0 * so * ci)[:, None] * q1 + (-s0 * so + c0 * co * ci)[:, None] * q2
+    z = (so * si)[:, None] * q1 + (co * si)[:, None] * q2
     r = np.stack([x, y, z], axis=-1)
 
     return r
 
+
 def build_planet_lines_cache(
-        ephem: Ephem,
-        epochJD_center: float,
-        planet_names: list[str],
-        n_points: int = 800
+    ephem: Ephem, epochJD_center: float, planet_names: list[str], n_points: int = 800
 ) -> tuple[dict[tuple[str, str], np.ndarray], np.ndarray]:
     """
-    
+
     Parameters
     -----------
     ephem : Assist object
@@ -566,24 +569,24 @@ def build_planet_lines_cache(
 
     epochJD_center : float
         Reference epoch to use to sample ellipse symmetrically over one orbtial period (JD)
-    
+
     planet_names : list
         List of planet names as strings
 
     n_points : int, optional (default=800)
         Number of points to use to construct the line
 
-    Returns 
+    Returns
     --------
     planet_lines_cache : dict of arrays
-        Dictiionary of arrays containing planet orbit lines for each planet in each plane+origin 
+        Dictiionary of arrays containing planet orbit lines for each planet in each plane+origin
         combination of shape (n_planets, n_points, 3)
-    
+
     planet_id : numpy string array
         Array containing ID tags for each planet of shape (n_planets,)
     """
     # much like the object orbits, it will be easier if we start from some frame+origin and
-    # convert to the other 3 from there. we choose barycentric equatorial here 
+    # convert to the other 3 from there. we choose barycentric equatorial here
     planet_id = np.array(planet_names, dtype="U32")
     lines_bary_equ = np.empty((len(planet_names), n_points, 3), dtype=float)
 
@@ -592,20 +595,22 @@ def build_planet_lines_cache(
         if P is None:
             logger.error(f"Missing period for planet: '{name}' in PLANET_PERIOD_DAYS")
             raise KeyError(f"Missing period for planet: '{name}' in PLANET_PERIOD_DAYS")
-        
+
         # basically build an ellipse of times to get the planet positions at where the epochJD_center
         # is a reference epoch, which should just be the epoch of the first input object (no scatter
-        # points so really just need the shape of orbit) 
-        epochJD = np.linspace(epochJD_center - float(P)/2.0, epochJD_center + float(P)/2.0, n_points)
+        # points so really just need the shape of orbit)
+        epochJD = np.linspace(epochJD_center - float(P) / 2.0, epochJD_center + float(P) / 2.0, n_points)
 
         for i, jd in enumerate(epochJD):
             part = ephem.get_particle(name, float(jd) - ephem.jd_ref)
             lines_bary_equ[p, i, :] = (part.x, part.y, part.z)
 
-    # this looks weird but it's just being fancy and instead of looping over it all we reshape 
+    # this looks weird but it's just being fancy and instead of looping over it all we reshape
     # lines_bary_equ from (N_planets, N_points, 3) -> (N_planets*N_points, 3) (ie one xyz per row)
-    # so we can apply rotation matrix quickly and easily. then we do the inverse reshape back 
-    lines_bary_ecl = np.dot(lines_bary_equ.reshape(-1, 3), EQ_TO_ECL_ROTATION_MATRIX).reshape(lines_bary_equ.shape)
+    # so we can apply rotation matrix quickly and easily. then we do the inverse reshape back
+    lines_bary_ecl = np.dot(lines_bary_equ.reshape(-1, 3), EQ_TO_ECL_ROTATION_MATRIX).reshape(
+        lines_bary_equ.shape
+    )
 
     # because the sun has different positions at each planet's epochs, we need to redo S_r here
     S_r_ecl = np.empty_like(lines_bary_ecl)
@@ -613,11 +618,11 @@ def build_planet_lines_cache(
 
     for p, name in enumerate(planet_names):
         P = PLANET_PERIOD_DAYS[name]
-        epochJD = np.linspace(epochJD_center - float(P)/2.0, epochJD_center + float(P)/2.0, n_points)
+        epochJD = np.linspace(epochJD_center - float(P) / 2.0, epochJD_center + float(P) / 2.0, n_points)
 
         S_r, _ = convert_sun_to_baryecliptic(ephem, epochJD)
         S_r_ecl[p, :, :] = S_r
-        S_r_equ[p, : ,:] = np.dot(S_r, ECL_TO_EQ_ROTATION_MATRIX)
+        S_r_equ[p, :, :] = np.dot(S_r, ECL_TO_EQ_ROTATION_MATRIX)
 
     # now we can simply build our cache of planets
     planet_lines_cache: dict[tuple[str, str], np.ndarray] = {}
diff --git a/src/layup/visualize.py b/src/layup/visualize.py
index b105b4f9..5343e550 100644
--- a/src/layup/visualize.py
+++ b/src/layup/visualize.py
@@ -8,31 +8,36 @@
 from layup.utilities.file_io.HDF5Reader import HDF5DataReader
 from layup.utilities.data_processing_utilities import get_format
 
-from layup.orbit_maths import REQUIRED_COLUMN_NAMES, build_ephem_and_mus, build_planet_lines_cache, conic_lines_from_classical_conic, prepopulate_orbit_variants
+from layup.orbit_maths import (
+    REQUIRED_COLUMN_NAMES,
+    build_ephem_and_mus,
+    build_planet_lines_cache,
+    conic_lines_from_classical_conic,
+    prepopulate_orbit_variants,
+)
 from layup.dash_ui import plotly_2D, plotly_3D, run_dash_app
 
 logger = logging.getLogger(__name__)
 
 DASH_THREAD = None
 
+
 def build_fig_caches(
-        rows: np.ndarray,
-        orbit_format: str,
-        input_plane: Literal["equatorial", "ecliptic"],
-        input_origin: Literal["heliocentric", "barycentric"],
-        n_points: int = 500,
-        r_max: float = 50.0,
-        cache_dir: Optional[str] = None
+    rows: np.ndarray,
+    orbit_format: str,
+    input_plane: Literal["equatorial", "ecliptic"],
+    input_origin: Literal["heliocentric", "barycentric"],
+    n_points: int = 500,
+    r_max: float = 50.0,
+    cache_dir: Optional[str] = None,
 ):
-    """
-    
-    """
-    # get the assist ephem object and build epoch array 
+    """ """
+    # get the assist ephem object and build epoch array
     logger.info(f"Building Assist ephemeris for planets")
     ephem, _, _ = build_ephem_and_mus(cache_dir)
     epochJD_center = float(rows["epochMJD_TDB"].astype(float)[0] + 2400000.5)
 
-    # construct planet lines 
+    # construct planet lines
     logger.info(f"Constructing planet orbit lines")
     planet_names = ["Mercury", "Venus", "Earth", "Mars", "Jupiter", "Saturn", "Uranus", "Neptune"]
     planet_lines_cache, planet_id = build_planet_lines_cache(
@@ -58,7 +63,9 @@ def build_fig_caches(
             r_max=r_max,
         )
 
-    logger.info(f"Creating cache of all input object and/or planet lines in heliocentric+barycentric && equatorial+ecliptic frames")
+    logger.info(
+        f"Creating cache of all input object and/or planet lines in heliocentric+barycentric && equatorial+ecliptic frames"
+    )
     # create caches of all figure combinations
     PANELS = ("XY", "XZ", "YZ")
     fig2d_cache = {}
@@ -90,7 +97,7 @@ def build_fig_caches(
                 panel=p,
                 return_fig=True,
             )
-        
+
         # now do double panel variants:
         for pL in PANELS:
             for pR in PANELS:
@@ -105,20 +112,20 @@ def build_fig_caches(
                     panels=(pL, pR),
                     return_fig=True,
                 )
-    
+
     return fig2d_cache, fig3d_cache
 
 
 def visualize_cli(
-        input: str,
-        input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
-        input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
-        num_orbs: int = 100,
-        block_size: int = 10000,
-        n_points: int = 500,
-        r_max: float = 50.0,
-        random: bool = False,
-        cache_dir: Optional[str] = None
+    input: str,
+    input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
+    input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
+    num_orbs: int = 100,
+    block_size: int = 10000,
+    n_points: int = 500,
+    r_max: float = 50.0,
+    random: bool = False,
+    cache_dir: Optional[str] = None,
 ):
     """
     Create visualisation plots of a given set of input orbits from the command line
@@ -144,7 +151,7 @@ def visualize_cli(
         Number of points sampled when constructing the line
 
     r_max : float, optional (default=50 au)
-        Maximum distance to render hyperbolic orbits out to 
+        Maximum distance to render hyperbolic orbits out to
 
     random : bool, optional (default=False)
         Flag to turn on/off random orbit plotting
@@ -159,21 +166,17 @@ def visualize_cli(
     if not input_file.exists():
         logger.error(f"File not found: {input}")
         raise FileNotFoundError(input_file)
-    
+
     # probe reader to get format
     logger.info(f"Probing input to infer orbit origin, reference plane, and format...")
     suffix = input_file.suffix.lower()
     if suffix == ".csv":
         probe_reader = CSVDataReader(
-            input_file,
-            format_column_name="FORMAT",
-            required_column_names=["FORMAT"]
+            input_file, format_column_name="FORMAT", required_column_names=["FORMAT"]
         )
     else:
         probe_reader = HDF5DataReader(
-            input_file,
-            format_column_name="FORMAT",
-            required_column_names=["FORMAT"]
+            input_file, format_column_name="FORMAT", required_column_names=["FORMAT"]
         )
     probe_rows = probe_reader.read_rows(block_start=0, block_size=100)
     if "FORMAT" in probe_rows.dtype.names:
@@ -193,24 +196,34 @@ def visualize_cli(
     if input_format_infer == "BCART_EQ":
         input_format_infer = "BCART"
         if input_plane_infer is None:
-            logger.warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+            logger.warning(
+                "FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial"
+            )
             # raise Warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
         input_plane_infer = "equatorial"
 
     # infer origin if not user supplied
     if input_origin_infer is None:
         input_origin_infer = "barycentric" if input_format_infer.startswith("B") else "heliocentric"
-        logger.warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
+        logger.warning(
+            f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}"
+        )
         # raise Warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
 
     # infer plane if not user supplied
     if input_plane_infer is None:
         if input_format_infer in ("COM", "BCOM", "KEP", "BKEP"):
             input_plane_infer = "ecliptic"
-            logger.warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
-            raise Warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
+            logger.warning(
+                f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}"
+            )
+            raise Warning(
+                f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}"
+            )
         else:
-            logger.warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+            logger.warning(
+                "--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)"
+            )
             # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
 
     logger.info(f"Inferred input orbit origin: {input_origin_infer}")
@@ -221,24 +234,18 @@ def visualize_cli(
     logger.info(f"Reading full input file: {input}")
     required_cols = REQUIRED_COLUMN_NAMES[orbit_format]
     if suffix == ".csv":
-        reader = CSVDataReader(
-            input_file,
-            format_column_name="FORMAT",
-            required_column_names=required_cols
-        )
+        reader = CSVDataReader(input_file, format_column_name="FORMAT", required_column_names=required_cols)
     else:
-        reader = HDF5DataReader(
-            input_file,
-            format_column_name="FORMAT",
-            required_column_names=required_cols
-        )
+        reader = HDF5DataReader(input_file, format_column_name="FORMAT", required_column_names=required_cols)
     rows = reader.read_rows(block_start=0, block_size=block_size)
 
     # make sure we actually have the requested number of orbits, else return all,
-    # then either randomly sample that many or sample the first that many 
+    # then either randomly sample that many or sample the first that many
     if num_orbs > rows.size:
         num_orbs = rows.size
-        logger.warning(f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}")
+        logger.warning(
+            f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}"
+        )
         # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
     if random:
         logger.info(f"Sampling {num_orbs} random orbits")
@@ -251,8 +258,10 @@ def visualize_cli(
     orbit_format_check = get_format(rows)
     if orbit_format_check != orbit_format:
         logger.error(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
-        raise ValueError(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
-    
+        raise ValueError(
+            f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}"
+        )
+
     fig2d_cache, fig3d_cache = build_fig_caches(
         rows=rows,
         orbit_format=orbit_format,
@@ -260,22 +269,23 @@ def visualize_cli(
         input_origin=input_origin_infer,
         n_points=n_points,
         r_max=r_max,
-        cache_dir=cache_dir
+        cache_dir=cache_dir,
     )
 
     logger.info(f"Running Dash web app")
     run_dash_app(fig2d_cache, fig3d_cache)
 
+
 def visualize_notebook(
-        data: str|Path|np.ndarray,
-        input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
-        input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
-        num_orbs: int = 100,
-        block_size: int = 10000,
-        n_points: int = 500,
-        r_max: float = 50.0,
-        random: bool = False,
-        cache_dir: Optional[str] = None
+    data: str | Path | np.ndarray,
+    input_plane: Optional[Literal["equatorial", "ecliptic"]] = None,
+    input_origin: Optional[Literal["heliocentric", "barycentric"]] = None,
+    num_orbs: int = 100,
+    block_size: int = 10000,
+    n_points: int = 500,
+    r_max: float = 50.0,
+    random: bool = False,
+    cache_dir: Optional[str] = None,
 ):
     """
     Create visualisation plots of a given set of input orbits in a Jupyter notebook
@@ -301,7 +311,7 @@ def visualize_notebook(
         Number of points sampled when constructing the line
 
     r_max : float, optional (default=50 au)
-        Maximum distance to render hyperbolic orbits out to 
+        Maximum distance to render hyperbolic orbits out to
 
     random : bool, optional (default=False)
         Flag to turn on/off random orbit plotting
@@ -319,13 +329,17 @@ def visualize_notebook(
             n_points=n_points,
             r_max=r_max,
             random=random,
-            cache_dir=cache_dir
+            cache_dir=cache_dir,
         )
     elif isinstance(data, np.ndarray):
         if data.dtype.names is None or "FORMAT" not in data.dtype.names:
-            logger.error("Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])")
-            raise ValueError("Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])")
-        
+            logger.error(
+                "Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])"
+            )
+            raise ValueError(
+                "Structured array input must contain a FORMAT column, which must be one of: ['CART'. 'BCART', 'BCART_EQ', 'KEP', 'BKEP', 'COM', 'BCOM'])"
+            )
+
         rows = data
         orbit_format = get_format(rows)
 
@@ -338,24 +352,32 @@ def visualize_notebook(
         if input_format_infer == "BCART_EQ":
             input_format_infer = "BCART"
             if input_plane_infer is None:
-                logger.warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
+                logger.warning(
+                    "FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial"
+                )
                 # raise Warning("FORMAT=BCART_EQ implies using equatorial plane. Setting --input-plane = equatorial")
             input_plane_infer = "equatorial"
 
         # infer origin if not user supplied
         if input_origin_infer is None:
             input_origin_infer = "barycentric" if input_format_infer.startswith("B") else "heliocentric"
-            logger.warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file format column FORMAT={orbit_format}")
+            logger.warning(
+                f"--input-origin not provided. Inferring {input_origin_infer} from input file format column FORMAT={orbit_format}"
+            )
             # raise Warning(f"--input-origin not provided. Inferring {input_origin_infer} from input file column FORMAT={orbit_format}")
 
         # infer plane if not user supplied
         if input_plane_infer is None:
             if input_format_infer in ("COM", "BCOM", "KEP", "BKEP"):
                 input_plane_infer = "ecliptic"
-                logger.warning(f"--input-plane not provided. Inferring ecliptic for input file format column FORMAT={orbit_format}")
+                logger.warning(
+                    f"--input-plane not provided. Inferring ecliptic for input file format column FORMAT={orbit_format}"
+                )
                 # raise Warning(f"--input-plane not provided. Inferring ecliptic for input file column FORMAT={orbit_format}")
             else:
-                logger.warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
+                logger.warning(
+                    "--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)"
+                )
                 # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
 
         logger.info(f"Inferred input orbit origin: {input_origin_infer}")
@@ -363,9 +385,11 @@ def visualize_notebook(
         logger.info(f"Inferred input orbit format: {input_format_infer}")
 
         # make sure we actually have the requested number of orbits, else return all,
-        # then either randomly sample that many or sample the first that many 
+        # then either randomly sample that many or sample the first that many
         if num_orbs > rows.size:
-            logger.warning(f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}")
+            logger.warning(
+                f"Requested {num_orbs} orbits, but only {rows.size} orbits in input. Capping to {rows.size}"
+            )
             num_orbs = rows.size
             # raise Warning("--input-plane is required for CART/BCART formats unless FORMAT column encodes it (e.g. BCART_EQ)")
         if random:
@@ -378,9 +402,13 @@ def visualize_notebook(
         # quick check to make sure orbit format didn't change somehow between probe and full read
         orbit_format_check = get_format(rows)
         if orbit_format_check != orbit_format:
-            logger.error(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
-            raise ValueError(f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}")
-        
+            logger.error(
+                f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}"
+            )
+            raise ValueError(
+                f"FORMAT changed between probe and full read: {orbit_format} -> {orbit_format_check}"
+            )
+
         fig2d_cache, fig3d_cache = build_fig_caches(
             rows=rows,
             orbit_format=orbit_format,
@@ -388,15 +416,10 @@ def visualize_notebook(
             input_origin=input_origin_infer,
             n_points=n_points,
             r_max=r_max,
-            cache_dir=cache_dir
+            cache_dir=cache_dir,
         )
 
         run_dash_app(fig2d_cache, fig3d_cache)
 
     else:
         raise TypeError("Input data must be a file path or a numpy structured array")
-    
-
-
-
-
diff --git a/src/layup_cmdline/visualize.py b/src/layup_cmdline/visualize.py
index 1bc6bbab..0da6bf6c 100644
--- a/src/layup_cmdline/visualize.py
+++ b/src/layup_cmdline/visualize.py
@@ -28,7 +28,7 @@ def main():
         type=str,
         choices=["equatorial", "ecliptic"],
         required=False,
-        default=None
+        default=None,
     )
     frame.add_argument(
         "--input-origin",
@@ -37,7 +37,7 @@ def main():
         type=str,
         choices=["heliocentric", "barycentric"],
         required=False,
-        default=None
+        default=None,
     )
 
     optional = parser.add_argument_group("Optional arguments")
@@ -47,7 +47,7 @@ def main():
         dest="block_size",
         type=int,
         default=10000,
-        required=False
+        required=False,
     )
     optional.add_argument(
         "-n",
@@ -56,7 +56,7 @@ def main():
         dest="num_orbs",
         type=int,
         default=100,
-        required=False
+        required=False,
     )
     optional.add_argument(
         "--n-points",
@@ -64,7 +64,7 @@ def main():
         dest="n_points",
         type=int,
         default=500,
-        required=False
+        required=False,
     )
     optional.add_argument(
         "--r-max",
@@ -72,7 +72,7 @@ def main():
         dest="r_max",
         type=float,
         default=50.0,
-        required=False
+        required=False,
     )
     optional.add_argument(
         "--random",
@@ -80,7 +80,7 @@ def main():
         dest="random",
         type=bool,
         default=False,
-        required=False
+        required=False,
     )
     optional.add_argument(
         "--ar-data-file-path",
@@ -117,8 +117,9 @@ def execute(args):
         n_points=args.n_points,
         r_max=args.r_max,
         random=args.random,
-        cache_dir=cache_dir
+        cache_dir=cache_dir,
     )
 
+
 if __name__ == "__main__":
-    main()
\ No newline at end of file
+    main()

From d349cdd910b6eaa02563cbcd17e22e00fdb2b4c5 Mon Sep 17 00:00:00 2001
From: Joseph Murtagh <jmurtagh05@qub.ac.uk>
Date: Mon, 26 Jan 2026 17:43:02 +0000
Subject: [PATCH 5/5] linted notebook

---
 docs/notebooks/orbit_visualizer_demo.ipynb | 100 ++++++++++++++++-----
 1 file changed, 80 insertions(+), 20 deletions(-)

diff --git a/docs/notebooks/orbit_visualizer_demo.ipynb b/docs/notebooks/orbit_visualizer_demo.ipynb
index a0922de5..cb1d6cd5 100644
--- a/docs/notebooks/orbit_visualizer_demo.ipynb
+++ b/docs/notebooks/orbit_visualizer_demo.ipynb
@@ -31,7 +31,12 @@
    "source": [
     "import numpy as np\n",
     "\n",
-    "from layup.orbit_maths import conic_lines_from_classical_conic, build_ephem_and_mus, build_planet_lines_cache, prepopulate_orbit_variants\n",
+    "from layup.orbit_maths import (\n",
+    "    conic_lines_from_classical_conic,\n",
+    "    build_ephem_and_mus,\n",
+    "    build_planet_lines_cache,\n",
+    "    prepopulate_orbit_variants,\n",
+    ")\n",
     "from layup.dash_ui import plotly_2D, plotly_3D"
    ]
   },
@@ -74,14 +79,16 @@
     "    (\"inc\", \"f8\"),\n",
     "    (\"argPeri\", \"f8\"),\n",
     "    (\"node\", \"f8\"),\n",
-    "    (\"ma\", \"f8\")\n",
+    "    (\"ma\", \"f8\"),\n",
     "]\n",
     "\n",
     "orbits = np.zeros(N, dtype=dtype)\n",
     "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
     "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
     "orbits[\"a\"] = rng.uniform(1.5, 12.0, size=N)\n",
-    "orbits[\"e\"] = np.clip(rng.normal(0.2, 0.15, size=N), 0.01, 0.85) # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
+    "orbits[\"e\"] = np.clip(\n",
+    "    rng.normal(0.2, 0.15, size=N), 0.01, 0.85\n",
+    ")  # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
     "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
     "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
     "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",
@@ -4013,7 +4020,16 @@
     "    n_points=900,\n",
     ")\n",
     "\n",
-    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d = plotly_2D(\n",
+    "    lines,\n",
+    "    conic,\n",
+    "    orbit_pos=orbit_pos,\n",
+    "    planet_lines=planet_lines_cache[key],\n",
+    "    planet_id=planet_id,\n",
+    "    plot_sun=True,\n",
+    "    panels=(\"XY\", \"XZ\"),\n",
+    "    return_fig=True,\n",
+    ")\n",
     "fig2d"
    ]
   },
@@ -4481,7 +4497,16 @@
     }
    ],
    "source": [
-    "fig3d = plotly_3D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, show_plane=True, return_fig=True)\n",
+    "fig3d = plotly_3D(\n",
+    "    lines,\n",
+    "    conic,\n",
+    "    orbit_pos=orbit_pos,\n",
+    "    planet_lines=planet_lines_cache[key],\n",
+    "    planet_id=planet_id,\n",
+    "    plot_sun=True,\n",
+    "    show_plane=True,\n",
+    "    return_fig=True,\n",
+    ")\n",
     "fig3d"
    ]
   },
@@ -6137,14 +6162,14 @@
     "    (\"inc\", \"f8\"),\n",
     "    (\"argPeri\", \"f8\"),\n",
     "    (\"node\", \"f8\"),\n",
-    "    (\"t_p_MJD_TDB\", \"f8\")\n",
+    "    (\"t_p_MJD_TDB\", \"f8\"),\n",
     "]\n",
     "\n",
     "orbits = np.zeros(N, dtype=dtype)\n",
     "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
     "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
     "orbits[\"q\"] = rng.uniform(1.5, 12.0, size=N)\n",
-    "orbits[\"e\"] = np.clip(rng.normal(5.0, 2.5, size=N), 1.0, 10.0) # <-- keep it hyperbolic now\n",
+    "orbits[\"e\"] = np.clip(rng.normal(5.0, 2.5, size=N), 1.0, 10.0)  # <-- keep it hyperbolic now\n",
     "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
     "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
     "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",
@@ -6174,7 +6199,16 @@
     "lines = conic_lines_from_classical_conic(conic, n_points=400, r_max=60)\n",
     "\n",
     "# --- draw 2d plot ---\n",
-    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[('helio',\"ecl\")], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d = plotly_2D(\n",
+    "    lines,\n",
+    "    conic,\n",
+    "    orbit_pos=orbit_pos,\n",
+    "    planet_lines=planet_lines_cache[(\"helio\", \"ecl\")],\n",
+    "    planet_id=planet_id,\n",
+    "    plot_sun=True,\n",
+    "    panels=(\"XY\", \"XZ\"),\n",
+    "    return_fig=True,\n",
+    ")\n",
     "fig2d"
    ]
   },
@@ -6694,7 +6728,16 @@
     }
    ],
    "source": [
-    "fig3d = plotly_3D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[key], planet_id=planet_id, plot_sun=True, show_plane=True, return_fig=True)\n",
+    "fig3d = plotly_3D(\n",
+    "    lines,\n",
+    "    conic,\n",
+    "    orbit_pos=orbit_pos,\n",
+    "    planet_lines=planet_lines_cache[key],\n",
+    "    planet_id=planet_id,\n",
+    "    plot_sun=True,\n",
+    "    show_plane=True,\n",
+    "    return_fig=True,\n",
+    ")\n",
     "fig3d"
    ]
   },
@@ -8366,7 +8409,16 @@
     }
    ],
    "source": [
-    "fig2d = plotly_2D(lines, conic, orbit_pos=orbit_pos, planet_lines=planet_lines_cache[('helio',\"ecl\")], planet_id=planet_id, plot_sun=True, panels=(\"XY\", \"XZ\"), return_fig=True)\n",
+    "fig2d = plotly_2D(\n",
+    "    lines,\n",
+    "    conic,\n",
+    "    orbit_pos=orbit_pos,\n",
+    "    planet_lines=planet_lines_cache[(\"helio\", \"ecl\")],\n",
+    "    planet_id=planet_id,\n",
+    "    plot_sun=True,\n",
+    "    panels=(\"XY\", \"XZ\"),\n",
+    "    return_fig=True,\n",
+    ")\n",
     "\n",
     "# --- layout / background ---\n",
     "fig2d.update_layout(\n",
@@ -8378,8 +8430,8 @@
     "fig2d.update_xaxes(\n",
     "    title_text=\"X [AU]\",\n",
     "    showgrid=True,\n",
-    "    showline=True, # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
-    "    mirror=True, \n",
+    "    showline=True,  # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
+    "    mirror=True,\n",
     "    linecolor=\"black\",\n",
     "    gridcolor=\"lightgray\",\n",
     "    tickfont=dict(color=\"black\"),\n",
@@ -8391,7 +8443,7 @@
     "    title_text=\"Y [AU]\",\n",
     "    showgrid=True,\n",
     "    showline=True,\n",
-    "    mirror=True, # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
+    "    mirror=True,  # <-- draws axis spines top/right, plotly only draws bottom/left by default\n",
     "    linecolor=\"black\",\n",
     "    gridcolor=\"lightgray\",\n",
     "    tickfont=dict(color=\"black\"),\n",
@@ -8400,8 +8452,14 @@
     "\n",
     "# --- style orbit lines + markers ---\n",
     "fig2d.for_each_trace(\n",
-    "    lambda tr: tr.update(line=dict(color=\"red\")) if tr.mode == \"lines\" and (tr.meta is None or tr.meta.get(\"kind\") != \"planet\") # <-- planets have a special internal tag so you can colour input objects separately\n",
-    "    else None\n",
+    "    lambda tr: (\n",
+    "        tr.update(line=dict(color=\"red\"))\n",
+    "        if tr.mode == \"lines\"\n",
+    "        and (\n",
+    "            tr.meta is None or tr.meta.get(\"kind\") != \"planet\"\n",
+    "        )  # <-- planets have a special internal tag so you can colour input objects separately\n",
+    "        else None\n",
+    "    )\n",
     ")\n",
     "\n",
     "fig2d.update_traces(\n",
@@ -8410,7 +8468,7 @@
     ")\n",
     "\n",
     "\n",
-    "fig2d\n"
+    "fig2d"
    ]
   },
   {
@@ -8429,8 +8487,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig2d.write_image('/foo/bar/baz/image.pdf')\n",
-    "fig3d.write_image('/foo/bar/baz/image.pdf')"
+    "fig2d.write_image(\"/foo/bar/baz/image.pdf\")\n",
+    "fig3d.write_image(\"/foo/bar/baz/image.pdf\")"
    ]
   },
   {
@@ -8495,14 +8553,16 @@
     "    (\"argPeri\", \"f8\"),\n",
     "    (\"node\", \"f8\"),\n",
     "    (\"ma\", \"f8\"),\n",
-    "    (\"FORMAT\", \"U32\")\n",
+    "    (\"FORMAT\", \"U32\"),\n",
     "]\n",
     "\n",
     "orbits = np.zeros(N, dtype=dtype)\n",
     "orbits[\"ObjID\"] = [f\"Obj-{i:02d}\" for i in range(N)]\n",
     "orbits[\"epochMJD_TDB\"] = float(61000.0)\n",
     "orbits[\"a\"] = rng.uniform(1.5, 12.0, size=N)\n",
-    "orbits[\"e\"] = np.clip(rng.normal(0.2, 0.15, size=N), 0.01, 0.85) # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
+    "orbits[\"e\"] = np.clip(\n",
+    "    rng.normal(0.2, 0.15, size=N), 0.01, 0.85\n",
+    ")  # <-- keep it elliptical for the sake of discussion, but could be hyperbolic\n",
     "orbits[\"inc\"] = rng.uniform(0, 60, size=N)\n",
     "orbits[\"argPeri\"] = rng.uniform(0, 360.0, size=N)\n",
     "orbits[\"node\"] = rng.uniform(0, 360.0, size=N)\n",