openeo_udf.functions package

Submodules

openeo_udf.functions.datacube_map_fabs module

openeo_udf.functions.datacube_map_fabs.hyper_map_fabs(udf_data: openeo_udf.api.udf_data.UdfData)

Compute the absolute values of each hyper cube in the provided data

Parameters:

• udf_data (UdfData) -- The UDF data object that contains raster and vector tiles as well as hypercubes
• structured data. (and) --

Returns:

This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_ndvi module

openeo_udf.functions.datacube_ndvi.hyper_ndvi(udf_data: openeo_udf.api.udf_data.UdfData)

Compute the NDVI based on RED and NIR hypercubes

Hypercubes with ids "red" and "nir" are required. The NDVI computation will be applied to all hypercube dimensions.

Parameters:

• udf_data (UdfData) -- The UDF data object that contains raster and vector tiles as well as hypercubes
• structured data. (and) --

Returns:

This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_pytorch_ml module

openeo_udf.functions.datacube_pytorch_ml.hyper_pytorch_ml(udf_data: openeo_udf.api.udf_data.UdfData)

Apply a pre-trained pytorch machine learn model on a hypercube

The model must be a pytorch model that has expects the input data in the constructor The prediction method must accept a torch.autograd.Variable as input.

Parameters:udf_data (UdfData) -- The UDF data object that hypercubes and vector tiles Returns:This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_reduce_time_mean module

openeo_udf.functions.datacube_reduce_time_mean.hyper_mean(udf_data: openeo_udf.api.udf_data.UdfData)

Compute the mean of the time dimension of a hyper cube

Hypercubes with time dimensions are required. The mean reduction of th time axis will be applied to all hypercube dimensions.

Parameters:

• udf_data (UdfData) -- The UDF data object that contains raster and vector tiles as well as hypercubes
• structured data. (and) --

Returns:

This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_reduce_time_min_median_max module

openeo_udf.functions.datacube_reduce_time_min_median_max.hyper_min_median_max(udf_data: openeo_udf.api.udf_data.UdfData)

Compute the min, median and max of the time dimension of a hyper cube

Hypercubes with time dimensions are required. The min, median and max reduction of th time axis will be applied to all hypercube dimensions.

Parameters:

• udf_data (UdfData) -- The UDF data object that contains raster and vector tiles as well as hypercubes
• structured data. (and) --

Returns:

This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_reduce_time_sum module

openeo_udf.functions.datacube_reduce_time_sum.hyper_sum(udf_data: openeo_udf.api.udf_data.UdfData)

Compute the sum of the time dimension of a hyper cube

Hypercubes with time dimensions are required. The sum reduction of th time axis will be applied to all hypercube dimensions.

Parameters:

• udf_data (UdfData) -- The UDF data object that contains raster and vector tiles as well as hypercubes
• structured data. (and) --

Returns:

This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_sampling module

openeo_udf.functions.datacube_sampling.fct_sampling(udf_data: openeo_udf.api.udf_data.UdfData)

Sample any number of raster collection tiles with a single feature collection (the first if several are provided) and store the samples values in the input feature collection. Each time-slice of a raster collection is stored as a separate column in the feature collection. Hence, the size of the feature collection attributes is (number_of_raster_tile * number_of_xy_slices) x number_of_features. The number of columns is equal to (number_of_raster_tile * number_of_xy_slices).

A single feature collection id stored in the input data object that contains the sample attributes and the original data.

Parameters:udf_data (UdfData) -- The UDF data object that contains raster and vector tiles Returns:This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_sklearn_ml module

openeo_udf.functions.datacube_sklearn_ml.rct_sklearn_ml(udf_data: openeo_udf.api.udf_data.UdfData)

Apply a pre-trained sklearn machine learn model on RED and NIR tiles

The model must be a sklearn model that has a prediction method: m.predict(X) The prediction method must accept a pandas.DataFrame as input.

Tiles with ids "red" and "nir" are required. The machine learn model will be applied to all spatio-temporal pixel of the two input raster collections.

Parameters:udf_data (UdfData) -- The UDF data object that contains raster and vector tiles Returns:This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.datacube_statistics module

openeo_udf.functions.datacube_statistics.rct_stats(udf_data: openeo_udf.api.udf_data.UdfData)

Compute univariate statistics for each hypercube

Parameters:udf_data (UdfData) -- The UDF data object that contains raster and vector tiles Returns:This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

openeo_udf.functions.feature_collections_buffer module

openeo_udf.functions.feature_collections_buffer.fct_buffer(udf_data: openeo_udf.api.udf_data.UdfData)

Compute buffer of size 10 around features

This function creates buffer around all features in the provided feature collection tiles. The resulting geopandas.GeoDataFrame contains the new geometries and a copy of the original attribute data.

Parameters:udf_data (UdfData) -- The UDF data object that contains raster and vector tiles Returns:This function will not return anything, the UdfData object "udf_data" must be used to store the resulting data.

Module contents