get_components_roswell
import sys
import networkx as nx
import matplotlib.pyplot as plt
from matplotlib.patches import Patch
from matplotlib.patches import Wedge
import pandas as pd
import seaborn as sns
def read(n):
f = open(n)
f.readline()
edges_AA = []
edges_EA = []
for l in f:
l = l.rstrip("\n")
ll = l.split("\t")
aa_score = float(ll[1])
ea_score = float(ll[2])
edge = ll[0].split("--")
edge[0] = int(edge[0].split()[0])
edge[1] = int(edge[1].split()[0])
if aa_score>ea_score:
edges_AA.append((edge[0], edge[1]))
else:
edges_EA.append((edge[0], edge[1]))
f.close()
return edges_AA, edges_EA
if __name__=="__main__":
e_AA, e_EA = read(sys.argv[1])
G = nx.Graph()
G.add_edges_from(e_AA)
components = list(nx.connected_components(G))
print("AA modules")
for i, component in enumerate(components):
print(f"Component {i+1}: {component}")
# Create side-by-side plots
fig, axes = plt.subplots(2, 2, figsize=(14, 12))
axes = axes.flatten()
pos = nx.spring_layout(G, seed=42) # layout for better visualization
node_color = {}
for c in [2, 6, 9, 14, 15, 8, 19]:
node_color[c] = "red"
for c in [4, 20, 16, 11, 10]:
node_color[c] = "blue"
for c in [5, 7, 17]:
node_color[c] = "green"
node_colors = [node_color[c] for c in G.nodes()]
nx.draw(G, pos, with_labels=True, node_color=node_colors, cmap=plt.cm.Set3, node_size=400, edge_color='gray', ax=axes[0])
#plt.title("Connected Components in Graph")
#plt.show()
# Build legend handles
legend_handles = []
patch = Patch(color="red", label=f"BA Community 1")
legend_handles.append(patch)
patch = Patch(color="blue", label=f"BA Community 2")
legend_handles.append(patch)
patch = Patch(color="green", label=f"BA Community 3")
legend_handles.append(patch)
# Add legend to second plot (or wherever you prefer)
axes[0].legend(handles=legend_handles, title="Legend:", loc='upper left')
axes[0].set_title("BA specific communities")
# Get adjacency matrix (as a NumPy array)
nodes = [15, 9, 6, 8, 2, 14, 19]
Gsub = G.subgraph(nodes).copy()
#Gsub.remove_edges_from([(20,19),]) #remove artificial edges
adj_matrix = nx.to_numpy_array(Gsub, nodelist=nodes)
df_adj = pd.DataFrame(adj_matrix, index=nodes, columns=nodes)
sns.heatmap(df_adj, cmap="Greens", cbar=False, linewidths=0.5, linecolor='gray', square=True, ax=axes[2])
axes[2].set_title("BA-community 1 Adjacency Matrix Heatmap")
#===================================================
G = nx.Graph()
G.add_edges_from(e_EA)
components = list(nx.connected_components(G))
print("EA modules")
for i, component in enumerate(components):
print(f"Component {i+1}: {component}")
special_node = 9
node_color = {}
for c in [14, 15, 16, 18, 10, 17, 1, 9]:
node_color[c] = "red"
for c in [11, 13, 19]:
node_color[c] = "green"
for c in [2, 5, 6, 7, 8]:
node_color[c] = "blue"
for c in [3]:
node_color[c] = "lightblue"
pos = nx.spring_layout(G, seed=4) # layout for better visualization
default_nodes = [n for n in G.nodes if n != special_node]
node_colors = [node_color[c] for c in default_nodes]
nx.draw_networkx_edges(G, pos, edge_color='gray', ax=axes[1])
nx.draw_networkx_nodes(G, pos, nodelist=default_nodes, node_color=node_colors, node_size=400, ax=axes[1])
nx.draw_networkx_labels(G, pos, ax=axes[1])
radius = 0.05
x,y = pos[special_node]
wedge1 = Wedge(center=(x, y), r=radius, theta1=90, theta2=270, facecolor='red', edgecolor='black')
wedge2 = Wedge(center=(x, y), r=radius, theta1=270, theta2=90, facecolor='green', edgecolor='black')
axes[1].add_patch(wedge1)
axes[1].add_patch(wedge2)
axes[1].text(x, y, str(special_node), fontsize=12, ha='center', va='center', color='white')
axes[1].set_title("WA specific communities")
legend_handles = []
patch = Patch(color="red", label=f"WA Community 1")
legend_handles.append(patch)
patch = Patch(color="blue", label=f"WA Community 2")
legend_handles.append(patch)
patch = Patch(color="green", label=f"WA Community 3")
legend_handles.append(patch)
# Add legend to second plot (or wherever you prefer)
axes[1].legend(handles=legend_handles, title="Legend:", loc='lower right')
# Get adjacency matrix (as a NumPy array)
nodes = [1, 17, 10, 9, 16, 18, 15, 14]
Gsub = G.subgraph(nodes).copy()
adj_matrix = nx.to_numpy_array(Gsub, nodelist=nodes)
df_adj = pd.DataFrame(adj_matrix, index=nodes, columns=nodes)
sns.heatmap(df_adj, cmap="Greens", cbar=False, linewidths=0.5, linecolor='gray', square=True, ax=axes[3])
axes[3].set_title("WA-community 1 Adjacency Matrix Heatmap")
#nx.draw(G, pos, with_labels=True, node_color="red", cmap=plt.cm.Set3, node_size=400, edge_color='gray', ax=axes[1])
plt.tight_layout()
plt.show()
Running Command
python3 get_components_roswell.py roswellResults
