nd.change package

class nd.change.ChangeDetection(njobs=1)[source]

Bases: nd.algorithm.Algorithm

njobs = 1
class nd.change.OmnibusTest(ml=None, n=1, alpha=0.01, *args, **kwargs)[source]

Bases: nd.change.ChangeDetection

This class implements the change detection algorithm by Conradsen et al. (2015).

Parameters
  • ds (xarray.Dataset) – A (multilooked) dataset in covariance matrix format.

  • ml (int, optional) – Multilooking window size. By default, no multilooking is performed and the dataset is assumed to already be multilooked.

  • n (int, optional) – The number of looks in ds. If ml is specified this parameter is ignored (default: 1).

  • alpha (float (0. ... 1.), optional) – The significance level (default: 0.01).

  • kwargs (dict, optional) – Extra keyword arguments to be applied to ChangeDetection.__init__.

apply(ds)[source]

Must be implemented by derived classes and should be given @parallelize decorator where appropriate.

nd.change.omnibus(ds, ml=None, n=1, alpha=0.01, *args, **kwargs)[source]

Wrapper for nd.change.OmnibusTest.

OmnibusTest

This class implements the change detection algorithm by Conradsen et al. (2015).

Parameters
  • ds (xarray.Dataset) – A (multilooked) dataset in covariance matrix format.

  • ml (int, optional) – Multilooking window size. By default, no multilooking is performed and the dataset is assumed to already be multilooked.

  • n (int, optional) – The number of looks in ds. If ml is specified this parameter is ignored (default: 1).

  • alpha (float (0. ... 1.), optional) – The significance level (default: 0.01).

  • kwargs (dict, optional) – Extra keyword arguments to be applied to ChangeDetection.__init__.