agora.track_abc.FeatureCalculator

class FeatureCalculator(feats2use, trapfeats=None, extrafeats=None, aweights=None, pixel_size=None)

Bases: ABC

Base class for making use of regionprops-based features. If no features are offered it uses most of them.

This class is not to be used directly

Attributes

a_ind

ma_ind

x_ind

y_ind

Methods

calc_feats_from_mask(masks[, feats2use, ...])	Calculate feature ndarray from ndarray of cell masks
calc_trapfeats(basefeats)	Calculate trap-based features using basic ones. :basefeats: (n basic outfeats) 1-D array with features outputed by skimage.measure.regionprops_table.
scale_feats(feats, pixel_size)	input

get_outfeats
load_model
set_named_ids

__init__(feats2use, trapfeats=None, extrafeats=None, aweights=None, pixel_size=None)

Methods

__init__(feats2use[, trapfeats, extrafeats, ...])
calc_feats_from_mask(masks[, feats2use, ...])	Calculate feature ndarray from ndarray of cell masks
calc_trapfeats(basefeats)	Calculate trap-based features using basic ones. :basefeats: (n basic outfeats) 1-D array with features outputed by skimage.measure.regionprops_table.
get_outfeats([feats2use])	rtype tuple
load_model(path, fname)
scale_feats(feats, pixel_size)	input
set_named_ids()

Attributes

a_ind
ma_ind
x_ind
y_ind

calc_feats_from_mask(masks, feats2use=None, trapfeats=None, scale=True, pixel_size=None)

Calculate feature ndarray from ndarray of cell masks — input

Masks

ndarray (ncells, x_size, y_size), typically dtype bool

Feats2use

list of strings with the feature properties to extract. If it is None it uses the ones set in self.feats2use.

Trapfeats

List of str with additional features to use calculated immediately after basic features.

Scale

bool, if True scales mask to a defined pixel_size.

Pixel_size

float, used to rescale the object features.

returns

(ncells, nfeats) ndarray of features for input masks

calc_trapfeats(basefeats)

Calculate trap-based features using basic ones. :basefeats: (n basic outfeats) 1-D array with features outputed by

skimage.measure.regionprops_table

requires

self.aind self.aweights self.xind self.yind self.trapfeats

returns (ntrapfeats) 1-D array with

scale_feats(feats, pixel_size)

input

Feats

np.ndarray (ncells * nfeatures)

Pixel_size

float Value used to normalise the images.

returns Rescaled list of feature values