Pair

Pair#

Bases: Set

Class of two-products pair

__init__(reference_paths: list | str | CloudPath | Path | Mosaic, secondary_paths: list | str | CloudPath | Path | Mosaic | None = None, id: str | None = None, output_path: str | CloudPath | Path | None = None, remove_tmp: bool = True, overlap_check: GeometryCheck | str = GeometryCheck.EXTENT, contiguity_check: GeometryCheck | str = GeometryCheck.EXTENT, **kwargs)[source]#: Output path of the pairs.

clean_tmp()[source]#: Clean the temporary directory of the current pair

clear()[source]#: Clear this pair’s cache

condensed_name#: Mosaic condensed name, a mix based on the dates and constellations of the components of the mosaic.

constellations#: List of unique constellations constituting the set

crs#: CRS of the mosaic. If not provided in kwargs, using the first product’s crs.

extent = <methodtools._LruCacheWire object>[source]#

footprint = <methodtools._LruCacheWire object>[source]#

full_name: str#: Mosaic full name.

get_attr(attr: str, **kwargs) → Any#

Get attribute, either from kwargs or from the first product (default)

Parameters:

attr (str) – Wanted attribute
**kwargs – Other args

Returns:

Attribute result

Return type:

Any

get_bands_to_load(bands, out_suffix='tif') -> (<class 'list'>, <class 'dict'>)#

get_first_prod() → Product#

Get first product, which should be coherent with all others

Returns:: First reference product
Return type:: Product

get_prods() → list[source]#

Get all the products as a list.

Returns:: Products list
Return type:: list

has_band(band: BandNames | str) → bool#

Does this moasic have products with the specified band ?

By band, we mean:

satellite band
index
DEM band
cloud band

Parameters:: band (Union[BandNames, str]) – EOReader band (optical, SAR, clouds, DEM)
Returns:: True if the products has the specified band
Return type:: bool

has_bands(bands: list | BandNames | str) → bool#

Does this moasic have products with the specified bands ?

By band, we mean:

satellite band
index
DEM band
cloud band

See has_band for a code example.

Parameters:: bands (Union[list, BandNames, str]) – EOReader bands (optical, SAR, clouds, DEM)
Returns:: True if the products has the specified band
Return type:: bool

has_secondary#: Does the pair have a secondary mosaic? (Pair with only one reference is allowed)

id: str#: ID of the reference product, given by the creator of the mosaic. If not, a mix based on the dates and constellations of its components.

is_homogeneous(attr: str) → bool#

Check if the given attribute is the same for all products constituting the mosaic.

Parameters:: attr (str) – Attribute to be checked. Must be available in EOReader’s Product
Returns:: True if this attribute is the same for all products constituting the mosaic.
Return type:: bool

load(reference_bands: list | ~eoreader.bands.band_names.BandNames | str | None = None, secondary_bands: list | ~eoreader.bands.band_names.BandNames | str | None = None, diff_bands: list | ~eoreader.bands.band_names.BandNames | str | None = None, pixel_size: float | None = None, diff_method: ~eosets.pair.DiffMethod = DiffMethod.REFERENCE_SECONDARY, resampling: ~rasterio.enums.Resampling = Resampling.bilinear, **kwargs) -> (<class 'xarray.core.dataset.Dataset'>, <class 'xarray.core.dataset.Dataset'>, <class 'xarray.core.dataset.Dataset'>)[source]#

Load the bands and compute the wanted spectral indices for reference, secondary and diff.

Parameters:

reference_bands (Union[list, BandNames, str]) – Wanted reference bands
secondary_bands (Union[list, BandNames, str]) – Wanted secondary bands
diff_bands (Union[list, BandNames, str]) – Wanted diff bands
pixel_size (float) – Pixel size of the returned Datasets. If not specified, use the pair’s pixel size.
diff_method (DiffMethod) – Difference method for the computation of diff_bands
resampling (Resampling) – Resampling method
kwargs – Other arguments used to load bands

Returns:

Reference, secondary and diff wanted bands as xr.Datasets

Return type:

(xr.Dataset, xr.Dataset, xr.Dataset)

nodata#: Nodata of the mosaic. If not provided in kwargs, using the first product’s nodata.

nof_prods: int#: Number of products.

property output: CloudPath | Path#

Output directory of the set

Returns:: Output path of the set
Return type:: AnyPathType

pixel_size#: Pixel size of the set. If not provided in kwargs, using the first product’s pixel size.

read_mtd()[source]#: Read the pair’s metadata, but not implemented for now.

reference_id#: ID of the reference product

reference_mosaic#: Reference mosaic (unique date and contiguous). The one on which the secondary will be aligned.

same_constellation#: Is the mosaic constituted of the same constellation?

same_crs#: Is the mosaic constituted of the same sensor type?

secondary_id#: ID of the secondary product

secondary_mosaic#: Secondary mosaic (unique date and contiguous). The one which will be aligned on the reference.

Stack bands and index of a pair.

Parameters:

reference_bands (Union[list, BandNames, str]) – Bands and index combination for the reference mosaic
secondary_bands (Union[list, BandNames, str]) – Bands and index combination for the secondary mosaic
diff_bands (Union[list, BandNames, str]) – Bands and index combination for the difference between reference and secondary mosaic
pixel_size (float) – Stack pixel size. If not specified, use the pair’s pixel size.
stack_path (Union[str, AnyPathType]) – Stack path
save_as_int (bool) – Convert stack to uint16 to save disk space (and therefore multiply the values by 10.000)
**kwargs – Other arguments passed to load or rioxarray.to_raster() (such as compress)

Returns:

Stack as a DataArray

Return type:

xr.DataArray

Pair

Contents

Pair#