Rename rename dingo package to dingo-walk

Author: vfisikop

.gitignore

@@ -12,4 +12,4 @@ volestipy.egg-info
 venv
 lp_solve_5.5/
 .devcontainer/
-.github/dependabot.yml
+.github/dependabot.yml

README.md

@@ -1,4 +1,4 @@
-<p align="center"><img src="doc/logo/dingo.jpg" width="260" height="260"></p>
+<p align="center"><img src="https://raw.githubusercontent.com/GeomScale/dingo/refs/heads/develop/doc/logo/dingo.jpg" width="260" height="260"></p>
 
 **dingo** is a Python package that analyzes metabolic networks.
 It relies on high dimensional sampling with Markov Chain Monte Carlo (MCMC)
@@ -290,7 +290,7 @@ plot_histogram(
 
 The default number of bins is 60. dingo uses the package `matplotlib` for plotting.
 
-![histogram](./doc/e_coli_aconta.png)
+![histogram](https://raw.githubusercontent.com/GeomScale/dingo/refs/heads/develop/doc/e_coli_aconta.png)
 
 ### Plot a copula between two fluxes
 
@@ -314,6 +314,6 @@ plot_copula(data_flux1, data_flux2, n=10)
 
 The default number of cells is 5x5=25. dingo uses the package `plotly` for plotting.
 
-![histogram](./doc/aconta_ppc_copula.png)
+![histogram](https://raw.githubusercontent.com/GeomScale/dingo/refs/heads/develop/doc/aconta_ppc_copula.png)
 
 

dingo/MetabolicNetwork.py

@@ -250,18 +250,18 @@ def set_active_bound(reaction: str, reac_index: int, bound: float) -> None:
         # Turn off reactions not present in media
         for rxn_id in exchange_rxns - frozen_media_rxns:
             """
-            is_export for us, needs to check on the S 
-            order reactions to their lb and ub 
+            is_export for us, needs to check on the S
+            order reactions to their lb and ub
             """
             # is_export = rxn.reactants and not rxn.products
             reac_index = self._reactions.index(rxn_id)
-            products = np.any(self._S[:,reac_index] > 0) 
+            products = np.any(self._S[:,reac_index] > 0)
             reactants_exist = np.any(self._S[:,reac_index] < 0)
             is_export = True if not products and reactants_exist else False
             set_active_bound(
                 rxn_id, reac_index, min(0.0, -self._lb[reac_index] if is_export else self._ub[reac_index])
             )
-    
+
     def set_solver(self, solver: str):
         self._parameters["solver"] = solver
 

dingo/__init__.py

@@ -75,7 +75,7 @@ def dingo_main():
 
     # Move to the output directory
     os.chdir(output_path_dir)
-    
+
     set_default_solver(args.solver)
 
     if args.model_name is None:
@@ -133,7 +133,7 @@ def dingo_main():
             raise Exception("An unknown format file given.")
 
         model.set_solver(args.solver)
-        
+
         result_obj = model.fva()
 
         with open("dingo_fva_" + name + ".pckl", "wb") as dingo_fva_file:
@@ -147,7 +147,7 @@ def dingo_main():
             model = MetabolicNetwork.fom_mat(args.metabolic_network)
         else:
             raise Exception("An unknown format file given.")
-        
+
         model.set_solver(args.solver)
 
         result_obj = model.fba()

dingo/bindings/bindings.cpp

@@ -461,7 +461,7 @@ void HPolytopeCPP::apply_rounding(int rounding_method, double* new_A, double* ne
 
    // run the rounding method
    if (rounding_method == 1) { // max ellipsoid
-      round_res = inscribed_ellipsoid_rounding<MT, VT, NT>(P, CheBall.first);
+      round_res = inscribed_ellipsoid_rounding<MT, VT, NT, decltype(P), Point, 2>(P, CheBall.first);
 
    } else if (rounding_method == 2) { // isotropization
       round_res = svd_rounding<AcceleratedBilliardWalk, MT, VT>(P, CheBall, 1, rng);

dingo/illustrations.py

@@ -32,7 +32,7 @@ def plot_copula(data_flux1, data_flux2, n = 5, width = 900 , height = 600, expor
     fig = go.Figure(
             data   = [go.Surface(z=copula)],
             layout = go.Layout(
-                height = height, 
+                height = height,
                 width  = width,
             )
         )
@@ -48,7 +48,7 @@ def plot_copula(data_flux1, data_flux2, n = 5, width = 900 , height = 600, expor
             margin=dict(r=30, b=30, l=30, t=50))
 
     fig.layout.template = None
-    
+
     fig.show()
     fig_name = data_flux1[1] + "_" + data_flux2[1] + "_copula." + export_format
 
@@ -97,7 +97,7 @@ def plot_corr_matrix(corr_matrix, reactions, removed_reactions=[], format="svg")
     removed_reactions -- A list with the removed reactions in case of a preprocess.
                          If provided removed reactions are not plotted.
     """
-    
+
     sns_colormap = [[0.0, '#3f7f93'],
                     [0.1, '#6397a7'],
                     [0.2, '#88b1bd'],
@@ -109,26 +109,26 @@ def plot_corr_matrix(corr_matrix, reactions, removed_reactions=[], format="svg")
                     [0.8, '#e8848b'],
                     [0.9, '#e15e68'],
                     [1.0, '#da3b46']]
-    
+
     if removed_reactions != 0:
         for reaction in reactions:
             index = reactions.index(reaction)
             if reaction in removed_reactions:
                reactions[index] = None
- 
-    fig = px.imshow(corr_matrix, 
+
+    fig = px.imshow(corr_matrix,
                     color_continuous_scale = sns_colormap,
                     x = reactions, y = reactions, origin="upper")
-    
+
     fig.update_layout(
     xaxis=dict(tickfont=dict(size=5)),
     yaxis=dict(tickfont=dict(size=5)),
     width=900, height=900, plot_bgcolor="rgba(0,0,0,0)")
-    
+
     fig.update_traces(xgap=1, ygap=1,   hoverongaps=False)
-    
+
     fig.show()
-    
+
     fig_name = "CorrelationMatrix." + format
     pio.write_image(fig, fig_name, scale=2)
 
@@ -141,18 +141,18 @@ def plot_dendrogram(dissimilarity_matrix, reactions , plot_labels=False, t=2.0,
     dissimilarity_matrix -- A matrix produced from the "cluster_corr_reactions" function
     reactions -- A list with the model's reactions
     plot_labels -- A boolean variable that if True plots the reactions labels in the dendrogram
-    t -- A threshold that defines a threshold that cuts the dendrogram 
+    t -- A threshold that defines a threshold that cuts the dendrogram
          at a specific height and colors the occuring clusters accordingly
-    linkage -- linkage defines the type of linkage. 
+    linkage -- linkage defines the type of linkage.
                Available linkage types are: single, average, complete, ward.
     """
 
     fig = ff.create_dendrogram(dissimilarity_matrix,
                                labels=reactions,
-                               linkagefun=lambda x: hierarchy.linkage(x, linkage),                           
+                               linkagefun=lambda x: hierarchy.linkage(x, linkage),
                                color_threshold=t)
     fig.update_layout(width=800, height=800)
-    
+
     if plot_labels == False:
         fig.update_layout(
             xaxis=dict(
@@ -166,9 +166,9 @@ def plot_dendrogram(dissimilarity_matrix, reactions , plot_labels=False, t=2.0,
         yaxis=dict(
             title_font=dict(size=10),
             tickfont=dict(size=8) ) )
-        
+
     fig.show()
-    
+
 
 
 def plot_graph(G, pos):
@@ -184,24 +184,24 @@ def plot_graph(G, pos):
     for u, v, data in G.edges(data=True):
         x0, y0 = pos[u]
         x1, y1 = pos[v]
-        
+
         edge_color = 'blue' if data['weight'] > 0 else 'red'
-        
-        fig.add_trace(go.Scatter(x=[x0, x1], y=[y0, y1], mode='lines', 
-                                    line=dict(width=abs(data['weight']) * 1, 
+
+        fig.add_trace(go.Scatter(x=[x0, x1], y=[y0, y1], mode='lines',
+                                    line=dict(width=abs(data['weight']) * 1,
                                     color=edge_color), hoverinfo='none',
                                     showlegend=False))
 
     for node in G.nodes():
         x, y = pos[node]
         node_name = G.nodes[node].get('name', f'Node {node}')
-  
-        fig.add_trace(go.Scatter(x=[x], y=[y], mode='markers', 
+
+        fig.add_trace(go.Scatter(x=[x], y=[y], mode='markers',
                                     marker=dict(size=10),
                                     text=[node_name],
                                     textposition='top center',
                                     name = node_name,
                                     showlegend=False))
-        
+
     fig.update_layout(width=800, height=800)
-    fig.show()
+    fig.show()

dingo/loading_models.py

@@ -23,7 +23,7 @@ def read_json_file(input_file):
     input_file -- a json file that contains the information about a mettabolic network, for example see http://bigg.ucsd.edu/models
     """
 
-    try: 
+    try:
         cobra.io.load_matlab_model( input_file )
     except:
         cobra_config = cobra.Configuration()
@@ -45,7 +45,7 @@ def read_mat_file(input_file):
     Keyword arguments:
     input_file -- a mat file that contains a MATLAB structure with the information about a mettabolic network, for example see http://bigg.ucsd.edu/models
     """
-    try: 
+    try:
         cobra.io.load_matlab_model( input_file )
     except:
         cobra_config = cobra.Configuration()
@@ -56,8 +56,8 @@ def read_mat_file(input_file):
     return (parse_cobra_model( model ))
 
 def read_sbml_file(input_file):
-    """A Python function, based on the cobra.io.read_sbml_model() function of cabrapy  
-    and the extract_polytope() function of PolyRound 
+    """A Python function, based on the cobra.io.read_sbml_model() function of cabrapy
+    and the extract_polytope() function of PolyRound
     (https://gitlab.com/csb.ethz/PolyRound/-/blob/master/PolyRound/static_classes/parse_sbml_stoichiometry.py)
     to read an SBML file (.xml) and return:
     (a) lower/upper flux bounds
@@ -68,10 +68,10 @@ def read_sbml_file(input_file):
     (f) the objective function to maximize the biomass pseudoreaction
 
     Keyword arguments:
-    input_file -- a xml file that contains an SBML  model with the information about a mettabolic network, for example see: 
+    input_file -- a xml file that contains an SBML  model with the information about a mettabolic network, for example see:
     https://github.com/VirtualMetabolicHuman/AGORA/blob/master/CurrentVersion/AGORA_1_03/AGORA_1_03_sbml/Abiotrophia_defectiva_ATCC_49176.xml
     """
-    try: 
+    try:
         cobra.io.read_sbml_model( input_file )
     except:
         cobra_config = cobra.Configuration()