Added ForbiddenCity color system

omicverse/bulk/_Enrichment.py

@@ -225,7 +225,7 @@ def geneset_plot(enrich_res,num:int=10,node_size:list=[5,10,15],
                         figsize:tuple=(2,4),cmap:str='YlGnBu',
                         text_knock:int=5,text_maxsize:int=20,
                         bbox_to_anchor_used:tuple=(-0.45, -13),node_diameter:int=10,
-                        custom_ticks:list=[5,10])->matplotlib.axes._axes.Axes:
+                        custom_ticks:list=[5,10],ax=None)->matplotlib.axes._axes.Axes:
     """
     Plot the gene set enrichment result.
 
@@ -247,7 +247,8 @@ def geneset_plot(enrich_res,num:int=10,node_size:list=[5,10,15],
         A matplotlib.axes.Axes object.
     
     """
-    fig, ax = plt.subplots(figsize=figsize)
+    if ax is None:
+        fig, ax = plt.subplots(figsize=figsize)
     plot_data2=enrich_res.sort_values('P-value')[:num].sort_values('logc')
     st=ax.scatter(plot_data2['fraction'],range(len(plot_data2['logc'])),
             s=plot_data2['num']*node_diameter,linewidths=1,edgecolors='black',c=plot_data2['logp'],cmap=cmap)
@@ -258,7 +259,7 @@ def geneset_plot(enrich_res,num:int=10,node_size:list=[5,10,15],
     plt.title(fig_title,fontsize=12)
     plt.xlabel(fig_xlabel,fontsize=12)
 
-    #fig = plt.gcf()
+    fig = plt.gcf()
     cax = fig.add_axes(cax_loc)
     cb=fig.colorbar(st,shrink=0.25,cax=cax,orientation='horizontal')
     cb.set_label(r'$−Log_{10}(P_{adjusted})$',fontdict={'size':cax_fontsize})

omicverse/pl/_cpdb.py

@@ -160,8 +160,9 @@ def cpdb_chord(adata:anndata.AnnData,interaction_edges:pd.DataFrame,
 def cpdb_heatmap(adata:anndata.AnnData,interaction_edges:pd.DataFrame,
                       celltype_key:str,nodecolor_dict=None,ax=None,
                       source_cells=None,target_cells=None,
-                      figsize=(3,3),fontsize=11,rotate=False,
-                      legend_kws={'fontsize':8,'bbox_to_anchor':(5, -0.5),'loc':'center left',},return_table=False,**kwargs):
+                      figsize=(3,3),fontsize=11,rotate=False,legend=True,
+                      legend_kws={'fontsize':8,'bbox_to_anchor':(5, -0.5),'loc':'center left',},
+                      return_table=False,**kwargs):
 
     if nodecolor_dict!=None:
         type_color_all=nodecolor_dict
@@ -297,7 +298,7 @@ def cpdb_heatmap(adata:anndata.AnnData,interaction_edges:pd.DataFrame,
         show_colnames=False,
         row_dendrogram=False,
         col_names_side='left',
-        legend=True,
+        legend=legend,
         **kwargs
         #cmap_legend_kws={'font':12},
     )
@@ -319,7 +320,7 @@ def cpdb_heatmap(adata:anndata.AnnData,interaction_edges:pd.DataFrame,
             show_colnames=False,
             row_dendrogram=False,
             col_names_side='top',
-            legend=True,
+            legend=legend,
             **kwargs
             #cmap_legend_kws={'font':12},
         )

omicverse/pl/_flowsig.py

@@ -60,7 +60,7 @@ def plot_curve_network(G: nx.Graph, G_type_dict: dict, G_color_dict: dict, pos_t
                        label_verticalalignment: str = 'center_baseline', label_fontsize: int = 12,
                        label_fontfamily: str = 'Arial', label_fontweight: str = 'bold', label_bbox=None,
                        legend_bbox: tuple = (0.7, 0.05), legend_ncol: int = 3, legend_fontsize: int = 12,
-                       legend_fontweight: str = 'bold', curve_awarg=None,ylim=(-0.5,0.5),xlim=(-3,3)):
+                       legend_fontweight: str = 'bold', curve_awarg=None,ylim=(-0.5,0.5),xlim=(-3,3),ax=None):
     """
     Plot network graph.
 
@@ -91,7 +91,10 @@ def plot_curve_network(G: nx.Graph, G_type_dict: dict, G_color_dict: dict, pos_t
         curve_awarg: dict, arguments for curved graph
     """
     from adjustText import adjust_text
-    fig, ax = plt.subplots(figsize=figsize)
+    if ax is None:
+        fig, ax = plt.subplots(figsize=figsize)
+    else:
+        fig = ax.figure
 
     # Determine node positions
     if pos_type == 'spring':
@@ -202,6 +205,12 @@ def plot_flowsig_network(flow_network,
     gem_li=[i for i in flow_network.nodes if 'GEM' in i]
     receptor_li=[i for i,j in flow_network.edges if ('GEM' in j)and('GEM' not in i)]
     sender_li=[j for i,j in flow_network.edges if ('GEM' in i)and('GEM' not in j)]
+    for g in gem_li:
+        flow_network.nodes[g]['type']='module'
+    for g in receptor_li:
+        flow_network.nodes[g]['type']='inflow'
+    for g in sender_li:
+        flow_network.nodes[g]['type']='outflow'
     #gene_li=[i for i in flow_network.nodes if 'GEM' not in i]
     G_type_dict=dict(zip(gem_li+receptor_li+sender_li,
             ['GEM' for i in range(len(gem_li))]+\
@@ -213,7 +222,10 @@ def plot_flowsig_network(flow_network,
     sender_li=[j for i,j in flow_network.edges if ('GEM' in i)and('GEM' not in j)]
     #gene_li=[i for i in flow_network.nodes if 'GEM' not in i]
     if len(gem_li)<28:
-        from ._palette import sc_color
+        sc_color=['#7CBB5F','#368650','#A499CC','#5E4D9A','#78C2ED','#866017', '#9F987F','#E0DFED',
+            '#EF7B77', '#279AD7','#F0EEF0', '#1F577B', '#A56BA7', '#E0A7C8', '#E069A6', '#941456', '#FCBC10',
+            '#EAEFC5', '#01A0A7', '#75C8CC', '#F0D7BC', '#D5B26C', '#D5DA48', '#B6B812', '#9DC3C3', '#A89C92', '#FEE00C', '#FEF2A1']
+
         G_color_dict=dict(zip(gem_li+receptor_li+sender_li,
                 [sc_color[i] for i in range(len(gem_li))]+\
                             ['#c2c2c2'  for i in range(len(receptor_li))]+\
@@ -227,7 +239,16 @@ def plot_flowsig_network(flow_network,
 
     #G = nx.Graph([(0, 1), (1, 2), (1, 3), (3, 4)])
     import networkx as nx
-    layers = {"layer1": list(set(sender_li)),  "layer3": list(set(receptor_li)),"layer2": list(set(gem_li)),}
+    if len(sender_li)==0 and len(receptor_li)>0:
+        layers = { "layer3": list(set(receptor_li)),
+                  "layer2": list(set(gem_li)),}
+    elif len(sender_li)>0 and len(receptor_li)==0:
+        layers = {"layer1": list(set(sender_li)), 
+                   "layer3": list(set(gem_li))}
+    else:
+        layers = {"layer1": list(set(sender_li)), 
+                   "layer3": list(set(receptor_li)),
+                   "layer2": list(set(gem_li)),}
     pos = nx.multipartite_layout(flow_network, subset_key=layers,align='horizontal',scale=2.0)
 
     #fig, ax = plt.subplots(figsize=(8,8))