output_data.index = pd.MultiIndex.from_tuples( zip(output_data.index.values, range(1, len(output_data.index.values) + 1)), names=['Sample']) if not isinstance(output_data.columns, pd.MultiIndex): output_data.columns = pd.MultiIndex.from_tuples( zip(output_data.columns.values, range(1, len(output_data.columns.values) + 1)), names=['Label', 'Measurement']) # Fill in header defaults where items are missing if any([c is None for c in output_data.index.names]): labels = config['row_header_defaults'].split(',') output_data.index.names = [l if l is not None else labels[n] for n, l in enumerate(output_data.index.names)] if any([c is None for c in output_data.columns.names]): labels = config['column_header_defaults'].split(',') output_data.columns.names = [l if l is not None else labels[n] for n, l in enumerate(output_data.columns.names)] # If we get here and don't have a sample Class entry on the index, create it if 'Class' not in output_data.index.names: output_data['Class'] = [''] * output_data.shape[0] output_data.set_index(['Class'], append=True, inplace=True) # Generate simple result figure (using pathomx libs) from pathomx.figures import spectra, heatmap Spectra = spectra(output_data, styles=styles) Heatmap = heatmap(output_data)
# Generate simple result figure (using pathomx libs) from pathomx.figures import heatmap View = heatmap(input_data, styles=styles);
zip(output_data.columns.values, range(1, len(output_data.columns.values) + 1))), names=['Label', 'Measurement']) # Fill in header defaults where items are missing if any([c is None for c in output_data.index.names]): labels = config['row_header_defaults'].split(',') output_data.index.names = [ l if l is not None else labels[n] for n, l in enumerate(output_data.index.names) ] if any([c is None for c in output_data.columns.names]): labels = config['column_header_defaults'].split(',') output_data.columns.names = [ l if l is not None else labels[n] for n, l in enumerate(output_data.columns.names) ] # If we get here and don't have a sample Class entry on the index, create it if 'Class' not in output_data.index.names: output_data['Class'] = [''] * output_data.shape[0] output_data.set_index(['Class'], append=True, inplace=True) # Generate simple result figure (using pathomx libs) from pathomx.figures import spectra, heatmap Spectra = spectra(output_data, styles=styles) Heatmap = heatmap(output_data)
# Generate simple result figure (using pathomx libs) from pathomx.figures import heatmap View = heatmap(input_data, styles=styles)