Initial commit for GSOC 2025

dingo/illustrations.py

@@ -9,10 +9,7 @@
 import matplotlib.pyplot as plt
 import plotly.graph_objects as go
 import plotly.io as pio
-import plotly.express as px
 from dingo.utils import compute_copula
-import plotly.figure_factory as ff
-from scipy.cluster import hierarchy
 
 def plot_copula(data_flux1, data_flux2, n = 5, width = 900 , height = 600, export_format = "svg"):
     """A Python function to plot the copula between two fluxes
@@ -84,124 +81,4 @@ def plot_histogram(reaction_fluxes, reaction, n_bins=40):
     plt.title("Reaction: " + reaction, fontweight="bold", fontsize=18)
     plt.axis([np.amin(reaction_fluxes), np.amax(reaction_fluxes), 0, np.amax(n) * 1.2])
 
-    plt.show()
-
-
-
-def plot_corr_matrix(corr_matrix, reactions, removed_reactions=[], format="svg"):
-    """A Python function to plot the heatmap of a model's pearson correlation matrix.
-
-    Keyword arguments:
-    corr_matrix -- A matrix produced from the "correlated_reactions" function
-    reactions -- A list with the model's reactions
-    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'],
-                    [0.3, '#acc9d2'],
-                    [0.4, '#d1e2e7'],
-                    [0.5, '#f2f2f2'],
-                    [0.6, '#f6cdd0'],
-                    [0.7, '#efa8ad'],
-                    [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, 
-                    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)
-
-
-
-def plot_dendrogram(dissimilarity_matrix, reactions , plot_labels=False, t=2.0, linkage="ward"):
-    """A Python function to plot the dendrogram of a dissimilarity matrix.
-
-    Keyword arguments:
-    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 
-         at a specific height and colors the occuring clusters accordingly
-    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),                           
-                               color_threshold=t)
-    fig.update_layout(width=800, height=800)
-
-    if plot_labels == False:
-        fig.update_layout(
-            xaxis=dict(
-            showticklabels=False,
-            ticks="") )
-    else:
-        fig.update_layout(
-        xaxis=dict(
-            title_font=dict(size=10),
-            tickfont=dict(size=8) ),
-        yaxis=dict(
-            title_font=dict(size=10),
-            tickfont=dict(size=8) ) )
-
-    fig.show()
-
-
-
-def plot_graph(G, pos):
-    """A Python function to plot a graph created from a correlation matrix.
-
-    Keyword arguments:
-    G -- A graph produced from the "graph_corr_matrix" function.
-    pos -- A layout for the corresponding graph.
-    """
-
-    fig = go.Figure()
-
-    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, 
-                                    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', 
-                                    marker=dict(size=10),
-                                    text=[node_name],
-                                    textposition='top center',
-                                    name = node_name,
-                                    showlegend=False))
-
-    fig.update_layout(width=800, height=800)
-    fig.show()
+    plt.show()