siibra.features.tabular.receptor_density_fingerprint

Module Contents

Classes

ReceptorDensityFingerprint

Represents a table of different measures anchored to a brain location.

class siibra.features.tabular.receptor_density_fingerprint.ReceptorDensityFingerprint(tsvfile: str, anchor: siibra.features.anchor.AnatomicalAnchor, datasets: list = [], id: str = None)

Represents a table of different measures anchored to a brain location.

Columns represent different types of values, while rows represent different samples. The number of columns might thus be interpreted as the feature dimension.

As an example, receptor fingerprints use rows to represent different neurotransmitter receptors, and separate columns for the mean and standard deviations measure across multiple tissue samples.

property data

property neurotransmitters: List[str]

property receptors: List[str]

property unit: str

DESCRIPTION = 'Fingerprint of densities (in fmol/mg protein) of receptors for classical neurotransmitters...'

classmethod parse_tsv_data(data: dict)

plot(*args, **kwargs)

Create a bar plot of a columns of the data. :param backend: “matplotlib”, “plotly”, or others supported by pandas DataFrame

plotting backend.

Parameters:

**kwargs – takes Matplotlib.pyplot keyword arguments

polar_plot(*args, backend='matplotlib', **kwargs)

Create a polar plot of the fingerprint. backend: str

“matplotlib” or “plotly”