foscat.xarray.statistics#
Functions#
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reference statistics for a single image |
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cross statistics between two images |
Module Contents#
- foscat.xarray.statistics.backend_to_dict(backend)#
- foscat.xarray.statistics.construct_backend(backend, kwargs)#
- foscat.xarray.statistics.stack_other_dims(arr, spatial_dim, batch_dim)#
- foscat.xarray.statistics.reference_statistics(arr, *, parameters, spatial_dim='cells', variances=False, mask=None, norm=None, jmax=None)#
reference statistics for a single image
- Parameters:
arr (
xarray.DataArray) – Input image. For now, only 1D healpix is supported. Every dimension other than the spatial dimension (seespatial_dim) will be stacked.parameters (
Parameters) – The parameters for the scattering covariance transform.spatial_dim (
str, default:"cells") – The spatial dimension.variances (
bool, default:False) – Whether to compute the variances of the statistic values.mask (
xarray.DataArray, optional) – Mask out certain regions. Not implemented yet.norm (
{"auto", "self"}orNone, default:None) – Normalization method: - None: no normalization - “auto”: normalize by the reference S2 - “self”: normalize by the current S2
- foscat.xarray.statistics.cross_statistics(arr1, arr2, *, parameters, spatial_dim='cells', variances=False, mask=None, norm=None)#
cross statistics between two images
- Parameters:
arr1, arr2 (
xarray.DataArray) – Input images. Must align exactly. For now, only 1D healpix is supported. Every dimension other than the spatial dimension (seespatial_dim) will be stacked.parameters (
Parameters) – The parameters for the scattering covariance transform.spatial_dim (
str, default:"cells") – The spatial dimension.variances (
bool, default:False) – Whether to compute the variances of the statistic values.mask (
xarray.DataArray, optional) – Mask out certain regions. Not implemented yet.norm (
{"auto", "self"}orNone, default:None) – Normalization method: - None: no normalization - “auto”: normalize by the reference S2 - “self”: normalize by the current S2