Merge pull request #83 from Ipuch/main

update rerun 0.24.1

Author: Ipuch

README.md

@@ -4,8 +4,7 @@
 We can rerun c3d files and display their original content.
 And also animate biorbd models from the pyomeca organization.
 
-``` conda install -c conda-forge pyorerun rerun-sdk=0.22.1```
-
+``` conda install -c conda-forge pyorerun rerun-sdk=0.24.1```
 ``` conda install opensim-org::opensim   # not a mandatory dependency```
 
 # Rerun .c3d - As simple as that

environment.yml

@@ -5,7 +5,7 @@ channels:
 - opensim-org
 dependencies:
 - ezc3d
-- rerun-sdk=0.22.1
+- rerun-sdk=0.24.1
 - numpy
 - matplotlib
 - biorbd>=1.10.5

examples/biorbd/no_mesh.py

@@ -24,7 +24,10 @@ def main():
     rerun_biorbd = PhaseRerun(t_span)
     q = np.zeros((biorbd_model.model.nbQ(), nb_frames))  # no movement
     rerun_biorbd.add_animated_model(biorbd_model, q)
+
     markers = PyoMarkers(data=noisy_markers, channels=[f"marker_{i}" for i in range(1, nb_random_markers + 1)])
+    markers.show_labels = False
+
     rerun_biorbd.add_xp_markers(
         name="noisy_markers",
         markers=markers,

pyorerun/abstract/markers.py

@@ -1,4 +1,5 @@
 from abc import abstractmethod
+from functools import cached_property
 
 import numpy as np
 
@@ -52,15 +53,19 @@ def __init__(
             radius : float | tuple[float, ...]
                 the radius of the markers
             color : np.ndarray
-                the color of the markers
+                the color of the markers in RGB format from 0 to 255, e.g. [0, 0, 255] for blue
             show_labels : bool
                 whether to show the labels of the markers (this can be changed by checking the appropriate box in the GUI)
         """
         self.marker_names = marker_names
         self.radius = radius
-        self.color = color
+        self._color = color
         self.show_labels = show_labels
 
+    @cached_property
+    def color(self):
+        return rgb255_to_hex_rgba(self._color)
+
     @property
     def nb_markers(self):
         """
@@ -107,3 +112,10 @@ def show_labels_to_rerun(self) -> list[bool]:
             return self.show_labels
         else:
             raise ValueError("The show_labels attribute must be a boolean or a list of booleans.")
+
+
+def rgb255_to_hex_rgba(color_rgb, alpha=255) -> int:
+    # color_rgb: np.ndarray ou list \[R, G, B] en 0–255
+    r, g, b = [int(np.clip(c, 0, 255)) for c in color_rgb[:3]]
+    a = int(np.clip(alpha, 0, 255))
+    return (r << 24) | (g << 16) | (b << 8) | a

pyorerun/live_animation.py

@@ -78,7 +78,7 @@ def update_rerun_components(self, the_dof_idx: int, the_value: float):
         self.q[the_dof_idx] = the_value
         # update counter
         self.counter += 1
-        rr.set_time_sequence(timeline="step", sequence=self.counter)
+        rr.set_time(timeline="step", sequence=self.counter)
         # Update the model
         self.update_model(self.q)
         # Update the q trajectories
@@ -93,17 +93,17 @@ def update_trajectories(self, q: np.ndarray):
         dof_names = self.model.dof_names
         for joint_idx in range(self.biorbd_model.nbQ()):
             name = f"q{joint_idx} - {dof_names[joint_idx]}"
-            rr.log(f"{name}/min", rr.SeriesLine(color=[255, 0, 0], name="min", width=0.5))
-            rr.log(f"{name}/max", rr.SeriesLine(color=[255, 0, 0], name="max", width=0.5))
-            rr.log(f"{name}/value", rr.SeriesLine(color=[0, 255, 0], name="q", width=0.5))
+            rr.log(f"{name}/min", rr.SeriesLines(colors=[255, 0, 0], names="min", widths=0.5))
+            rr.log(f"{name}/max", rr.SeriesLines(colors=[255, 0, 0], names="max", widths=0.5))
+            rr.log(f"{name}/value", rr.SeriesLines(colors=[0, 255, 0], names="q", widths=0.5))
 
             q_range = q_ranges[joint_idx]
             self.to_serie_line(name=name, min=q_range.min(), max=q_range.max(), val=q[joint_idx])
 
     def to_serie_line(self, name: str, min: float, max: float, val: float):
-        rr.log(f"{name}/min", rr.Scalar(min))
-        rr.log(f"{name}/max", rr.Scalar(max))
-        rr.log(f"{name}/value", rr.Scalar(val))
+        rr.log(f"{name}/min", rr.Scalars(min))
+        rr.log(f"{name}/max", rr.Scalars(max))
+        rr.log(f"{name}/value", rr.Scalars(val))
 
     def rerun(self, name: str = None):
         # update manually here

pyorerun/model_components/model_markers.py

@@ -134,12 +134,15 @@ def to_chunk(self, q: np.ndarray) -> dict[str, list]:
 
         return {
             self.name: [
-                rr.Points3D.indicator(),
-                rr.components.Position3DBatch(markers).partition(partition),
-                rr.components.ColorBatch([self.marker_properties.color for _ in range(nb_frames_trials)]),
-                rr.components.RadiusBatch([self.marker_properties.radius for _ in range(nb_frames_trials)]),
-                rr.components.TextBatch(partition_marker_names).partition(partition),
-                rr.components.ShowLabelsBatch([self.marker_properties.show_labels for _ in range(nb_frames_trials)]),
+                *rr.Points3D.columns(
+                    positions=markers,
+                    labels=partition_marker_names,
+                ).partition(partition),
+                *rr.Points3D.columns(
+                    colors=[self.persistent_options.color for _ in range(nb_frames_trials)],
+                    radii=[self.persistent_options.radius for _ in range(nb_frames_trials)],
+                    show_labels=[self.persistent_options.show_labels for _ in range(nb_frames_trials)],
+                ),
             ]
         }
 

pyorerun/multi_frame_rate_phase_rerun.py

@@ -85,14 +85,14 @@ def rerun_by_frame(
 
         for phase_rerun in self.phase_reruns:
             frame = 0
-            rr.set_time_seconds("stable_time", phase_rerun.t_span[frame])
+            rr.set_time("stable_time", duration=phase_rerun.t_span[frame])
             phase_rerun.timeless_components.to_rerun()
             phase_rerun.biorbd_models.to_rerun(frame)
             phase_rerun.xp_data.to_rerun(frame)
 
         cumulative_frames_in_merged_t_span = self.cumulative_frames_in_merged_t_span
         for frame, (t, idx) in enumerate(zip(self.merged_t_span[1:], self.frame_t_span_idx[1:])):
-            rr.set_time_seconds("stable_time", t)
+            rr.set_time("stable_time", duration=t)
             for i in idx:
                 frame_i = cumulative_frames_in_merged_t_span[i][frame + 1]
                 self.phase_reruns[i].biorbd_models.to_rerun(frame_i)
@@ -119,12 +119,12 @@ def rerun(
 
         for phase_rerun in self.phase_reruns:
             frame = 0
-            rr.set_time_seconds("stable_time", phase_rerun.t_span[frame])
+            rr.set_time("stable_time", duration=phase_rerun.t_span[frame])
             phase_rerun.timeless_components.to_rerun()
             phase_rerun.models.initialize()
             phase_rerun.xp_data.initialize()
 
-            times = [rr.TimeSecondsColumn("stable_time", phase_rerun.t_span)]
+            times = [rr.TimeColumn("stable_time", duration=phase_rerun.t_span)]
 
             for name, chunk in phase_rerun.xp_data.to_chunk().items():
                 rr.send_columns(

pyorerun/phase_rerun.py

@@ -240,13 +240,13 @@ def rerun_by_frame(
             rr.init(f"{name}_{self.phase}", spawn=True if not notebook else False)
 
         frame = 0
-        rr.set_time_seconds("stable_time", self.t_span[frame])
+        rr.set_time("stable_time", duration=self.t_span[frame])
         self.timeless_components.to_rerun()
         self.models.to_rerun(frame)
         self.xp_data.to_rerun(frame)
 
         for frame, t in enumerate(self.t_span[1:]):
-            rr.set_time_seconds("stable_time", t)
+            rr.set_time("stable_time", duration=t)
             self.models.to_rerun(frame + 1)
             self.xp_data.to_rerun(frame + 1)
 
@@ -265,12 +265,12 @@ def rerun(
             rr.init(f"{name}_{self.phase}", spawn=True if not notebook else False)
 
         frame = 0
-        rr.set_time_seconds("stable_time", self.t_span[frame])
+        rr.set_time("stable_time", duration=self.t_span[frame])
         self.timeless_components.to_rerun()
         self.models.initialize()
         self.xp_data.initialize()
 
-        times = [rr.TimeSecondsColumn("stable_time", self.t_span)]
+        times = [rr.TimeColumn("stable_time", duration=self.t_span)]
 
         for name, chunk in self.xp_data.to_chunk().items():
             rr.send_columns(
@@ -287,7 +287,7 @@ def rerun(
             )
 
         if clear_last_node:
-            rr.set_time_seconds("stable_time", self.t_span[-1])
+            rr.set_time("stable_time", duration=self.t_span[-1])
             for component in [
                 *self.models.component_names,
                 *self.xp_data.component_names,

pyorerun/rrc3d.py

@@ -136,10 +136,10 @@ def rrc3d(
             for j, axis in enumerate(["X", "Y", "Z"]):
                 rr.send_columns(
                     f"markers_graphs/{m}/{axis}",
-                    indexes=[rr.TimeSecondsColumn("stable_time", t_span)],
+                    indexes=[rr.TimeColumn("stable_time", duration=t_span)],
                     columns=[
-                        *rr.Scalar.columns(
-                            scalar=phase_rerun.xp_data.xp_data[0].markers_numpy[j, marker_names.index(m), :]
+                        *rr.Scalars.columns(
+                            scalars=phase_rerun.xp_data.xp_data[0].markers_numpy[j, marker_names.index(m), :]
                         )
                     ],
                 )
@@ -153,7 +153,7 @@ def set_event_as_log(c3d_file: str) -> None:
     context = c3d_file["parameters"]["EVENT"]["CONTEXTS"]["value"]
 
     for i, (time, label, description, context) in enumerate(zip(times, labels, descriptions, context)):
-        rr.set_time_seconds("stable_time", time)
+        rr.set_time("stable_time", duration=time)
         rr.log(
             f"events",
             rr.TextLog(

pyorerun/xp_components/force_vector.py

@@ -4,6 +4,9 @@
 import rerun as rr
 
 from ..abstract.abstract_class import ExperimentalData
+from ..abstract.markers import rgb255_to_hex_rgba
+
+VECTOR_COLOR = rgb255_to_hex_rgba(np.array([201, 219, 227]))
 
 
 class Vector(ExperimentalData, ABC):
@@ -27,7 +30,7 @@ def to_component(self, frame: int) -> np.ndarray:
         return rr.Arrows3D(
             origins=self.vector_origins[:, frame],
             vectors=self.vector_magnitude[:, frame],
-            colors=np.array([201, 219, 227]),
+            colors=VECTOR_COLOR,
         )
 
     def initialize(self):
@@ -41,20 +44,12 @@ def to_rerun(self, frame) -> None:
 
     def to_chunk(self, **kwargs) -> dict[str, list]:
 
-        # return {
-        #     self.name: [
-        #         rr.Arrows3D.indicator(),
-        #         rr.components.Position3DBatch(self.vector_origins.T),
-        #         rr.components.Vector3DBatch(self.vector_magnitude.T),
-        #         rr.components.ColorBatch([np.array([201, 219, 227]) for _ in range(self.nb_frames)]),
-        #     ]
-        # }
         return {
             self.name: [
                 *rr.Arrows3D.columns(
                     origins=self.vector_origins.T.tolist(),
                     vectors=self.vector_magnitude.T.tolist(),
-                    colors=[np.array([201, 219, 227]) for _ in range(self.nb_frames)],
+                    colors=[VECTOR_COLOR for _ in range(self.nb_frames)],
                 )
             ]
         }