58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
import pylab
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import matplotlib
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import networkx as nx
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def plot_corrloads(R, pc1=0,pc2=1,s=20, c='b', zorder=5,expvar=None,ax=None,drawback=True, labels=None):
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""" Correlation loading plot."""
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# backgorund
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if ax==None or drawback==True:
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radius = 1
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center = (0,0)
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c100 = matplotlib.patches.Circle(center,radius=radius,
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facecolor='gray',
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alpha=.1,
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zorder=1)
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c50 = matplotlib.patches.Circle(center, radius=radius/2.0,
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facecolor='gray',
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alpha=.1,
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zorder=2)
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ax = pylab.gca()
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ax.add_patch(c100)
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ax.add_patch(c50)
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ax.axhline(lw=1.5,color='k')
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ax.axvline(lw=1.5,color='k')
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# corrloads
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ax.scatter(R[:,pc1], R[:,pc2], s=s, c=c,zorder=zorder)
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ax.set_xlim([-1,1])
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ax.set_ylim([-1,1])
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if expvar!=None:
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xstring = "Comp: %d expl.var: %.1f " %(pc1+1, expvar[pc1])
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pylab.xlabel(xstring)
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ystring = "Comp: %d expl.var.: %.1f " %(pc2+1, expvar[pc2])
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pylab.ylabel(ystring)
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if labels!=None:
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assert(len(labels)==R.shape[0])
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for name, r in zip(labels, R):
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pylab.text(r[pc1], r[pc2], " " + name)
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#pylab.show()
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def plot_dag(edge_dict, node_color='b', node_size=30,labels=None,nodelist=None,pos=None):
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clean_edges = {}
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for head, neigb in edge_dict.items():
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head = head.replace(":", "_")
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nei = [i.replace(":", "_") for i in neigb]
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clean_edges[head] = nei
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if pos==None:
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G = nx.from_dict_of_lists(clean_edges, nx.DiGraph(name='GO'))
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pos = nx.pydot_layout(G, prog='dot')
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G = nx.from_dict_of_lists(edge_dict, nx.DiGraph(name='GO'))
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if len(node_color)>1:
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assert(len(node_color)==len(nodelist))
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if labels!=None:
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with_labels=True
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nx.draw_networkx(G,pos, with_labels=with_labels, node_size=node_size, node_color=node_color, nodelist=nodelist)
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