cellmap_flow.norm.input_normalize

Attributes

logger

Classes

SerializableInterface
InputNormalizer
Dilate
EuclideanDistance
MinMaxNormalizer
LambdaNormalizer
ZScoreNormalizer

Functions

get_input_normalizers(→ list[dict])
deserialize_list(→ list)	Deserialize a list of processors from either dict or list format.
get_normalizations(→ list[InputNormalizer])	Get normalizations from either dict or list format.

Module Contents

cellmap_flow.norm.input_normalize.logger

class cellmap_flow.norm.input_normalize.SerializableInterface

classmethod name()

process(data, **kwargs) → numpy.ndarray

to_dict()

property dtype

class cellmap_flow.norm.input_normalize.InputNormalizer

class cellmap_flow.norm.input_normalize.Dilate(size=1)

size = 1

class cellmap_flow.norm.input_normalize.EuclideanDistance(anisotropy=50, black_border=True, parallel=5, type='edt', activation='tanh')

anisotropy

black_border = True

parallel = 5

activation

property dtype

class cellmap_flow.norm.input_normalize.MinMaxNormalizer(min_value=0.0, max_value=255.0, invert=False)

min_value

max_value

property dtype

class cellmap_flow.norm.input_normalize.LambdaNormalizer(expression: str)

expression

property dtype

class cellmap_flow.norm.input_normalize.ZScoreNormalizer(mean=0.0, std=1.0)

mean

std

property dtype

cellmap_flow.norm.input_normalize.get_input_normalizers() → list[dict]

cellmap_flow.norm.input_normalize.deserialize_list(elms, T: type) → list

Deserialize a list of processors from either dict or list format.

Parameters:

• elms – Either a dict (old format) or list (new ordered format) of processor configs

• T – The base type to deserialize (InputNormalizer or PostProcessor)

Returns:

List of instantiated processor objects in the specified order

cellmap_flow.norm.input_normalize.get_normalizations(elms) → list[InputNormalizer]

Get normalizations from either dict or list format.