emmi.pipeline.sample_processors.moment_normalization

Classes

MomentNormalizationSampleProcessor

Normalizes a value with its mean and standard deviation (i.e., its moments).

Module Contents

class emmi.pipeline.sample_processors.moment_normalization.MomentNormalizationSampleProcessor(item, mean=None, std=None, logmean=None, logstd=None, logscale=False)

Bases: ksuit.data.pipeline.SampleProcessor

Normalizes a value with its mean and standard deviation (i.e., its moments).

Parameters:

• item (str) – The item to normalize.

• mean (collections.abc.Sequence[float] | None) – The mean of the value. Mandatory if logscale=False.

• std (collections.abc.Sequence[float] | None) – The standard deviation of the value. Mandatory if logscale=False.

• logmean (collections.abc.Sequence[float] | None) – The mean of the value in logscale. Mandatory if logscale=True.

• logstd (collections.abc.Sequence[float] | None) – The standard deviation of the value in logscale. Mandatory if logscale=True.

• logscale (bool) – Whether to convert the value to logscale before normalization.

item

mean_tensor = None

std_tensor = None

logmean_tensor = None

logstd_tensor = None

logscale = False

inverse(key, value)

Inverts the normalization from the __call__ method of a single item in the batch.

Parameters:

• key (str) – The name of the item.

• value (torch.Tensor) – The value of the item.

Returns:

The same name and the denormalized value.

Return type:

(key, value)