waltlabtools.mosaic module

Functions for analyzing MOSAIC data.

In addition to the dependencies for waltlabtools, waltlabtools.mosaic also requires pandas >= 0.25 and scikit-learn >= 0.21.

class PlateFileCollection(dir_path=None)[source]

Bases: object

aeb(onfrac_gmm, onfrac_sds)[source]
extended_coefs(concs, aebs, corr='c4', cal_curve=None)[source]
gaussians(flat_data, flat_len, means_init, reg_covar=1e-06, threshold_sds=5)[source]
log_transform(flat_data)[source]
mixture_aeb(flat_data, threshold_sds=5)[source]
mixture_orientation(means_, covariances_, threshold_sds=5)[source]

Determine which peak is 'off.'

plate_subsets(dir_path=None, save_aebs_to=None, save_coefs_to=None, log: bool = True, model='4PL', lod_sds=3, subsets: int = 10, sizes=(), corr='c4', threshold_sds=5)[source]
well_to_aeb(well_entry=None, log=True, threshold_sds=5)[source]