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)
