def plotModuleCorr(cyDf, labels, plotLabel, sampleStr='M', dropped=None, compCommVar=None): """Make a corr plot for a module.""" modDf = makeModuleVariables(cyDf[labels.index], labels, dropped=dropped, sampleStr=sampleStr) modVar = '%s%s' % (sampleStr, plotLabel) cyVars = labels2modules(labels, dropped=None)[plotLabel] if not compCommVar is None: cyVars.append(compCommVar) tmpDf = cyDf[cyVars].join(modDf[modVar]).copy() """Rename dropped columns with an asterisk but leave them on the plot""" if not dropped is None: tmpDf.columns = np.array([ c + '*' if c in dropped and dropped[c] else c for c in tmpDf.columns ]) figh = plt.gcf() figh.clf() combocorrplot(tmpDf, method='pearson') axh = plt.gca() axh.annotate('%s%s' % (sampleStr, plotLabel), xy=(0.5, 0.99), xycoords='figure fraction', va='top', ha='center')
def plotInterModuleCorr(cyDf, labels, dropped=None, compCommVar=None): """Make a plot showing inter-module correlation""" modDf = makeModuleVariables(cyDf[labels.index], labels, dropped=dropped) modVars = modDf.columns.tolist() if not compCommVar is None: modDf = modDf.join(cyDf[compCommVar]) modVars += [compCommVar] figh = plt.gcf() figh.clf() combocorrplot(modDf[modVars], method='pearson')
def plotInterModuleCorr(cyDf, labels, dropped = None, compCommVar = None): """Make a plot showing inter-module correlation""" modDf = makeModuleVariables(cyDf[labels.index], labels, dropped = dropped) modVars = modDf.columns.tolist() if not compCommVar is None: modDf = modDf.join(cyDf[compCommVar]) modVars += [compCommVar] figh = plt.gcf() figh.clf() combocorrplot(modDf[modVars], method = 'pearson')
def plotModuleCorr(cyDf, labels, plotLabel, sampleStr='M', dropped=None, compCommVar=None): """Make a corr plot for a module.""" modDf = makeModuleVariables(cyDf[labels.index], labels, dropped=dropped) modVar = '%s%s' % (sampleStr, plotLabel) cyVars = labels2modules(labels, dropped = None)[plotLabel] if not compCommVar is None: cyVars.append(compCommVar) tmpDf = cyDf[cyVars].join(modDf[modVar]).copy() """Rename dropped columns with an asterisk but leave them on the plot""" if not dropped is None: tmpDf.columns = np.array([c + '*' if c in dropped and dropped[c] else c for c in tmpDf.columns]) figh = plt.gcf() figh.clf() combocorrplot(tmpDf, method = 'pearson') axh = plt.gca() axh.annotate('Module %s%s' % (sampleStr, plotLabel), xy=(0.5,0.99), xycoords='figure fraction', va = 'top', ha='center')