Standardize

class of dascore.proc.basic
inherits from: PatchProcessor, DascoreBaseModel, pydantic.main.BaseModel

Standardize(
*args ,
dim: str ,
)-> None

Standardize data by removing the mean and scaling to unit variance.

The standard score of a sample x is calculated as:

z = (x - u) / s where u is the mean and s the standard deviation along dim.

NaN values are ignored when computing the mean and standard deviation. They remain NaN in the output but do not affect any other sample.

Parameters

Parameter	Description
dim	The dimension along which the normalization takes place.

Examples

import dascore as dc

patch = dc.get_example_patch()

# standardize along the time axis
standardized_time = patch.standardize('time')

# standardize along the x axis
standardized_distance = patch.standardize('distance')

```

Methods

Name	Description
check	Refuse a patch which does not carry what the operation needs.
get_metadata	Return the metadata as it is, and the axis to standardize along.
kernel	Return the data centred and scaled along its dimension.
model_copy	Copy the model, dropping cached values the update invalidates.
new	Create new instance with some attributed updated.
standardize	Standardize data by removing the mean and scaling to unit variance.
reconcile	Return the result’s metadata once the data are known; default as is.
run	Run the operation: check, get_metadata, kernel, reconcile, record.