openEO Process MappingΒΆ

The table below maps openEO processes to the corresponding method or function in the openEO Python Client Library.

openEO process

openEO Python Client Method

add

DataCube.add(), DataCube.__add__(), DataCube.__radd__()

add_dimension

DataCube.add_dimension()

aggregate_spatial

DataCube.aggregate_spatial()

aggregate_temporal

DataCube.aggregate_temporal()

aggregate_temporal_period

DataCube.aggregate_temporal_period()

and

DataCube.logical_and(), DataCube.__and__()

apply

DataCube.apply()

apply_dimension

DataCube.apply_dimension()

apply_kernel

DataCube.apply_kernel()

apply_neighborhood

DataCube.apply_neighborhood()

ard_normalized_radar_backscatter

DataCube.ard_normalized_radar_backscatter()

ard_surface_reflectance

DataCube.ard_surface_reflectance()

atmospheric_correction

DataCube.atmospheric_correction()

count

DataCube.count_time()

dimension_labels

DataCube.dimension_labels()

divide

DataCube.divide(), DataCube.__truediv__()

drop_dimension

DataCube.drop_dimension()

eq

DataCube.__eq__()

filter_bands

DataCube.filter_bands()

filter_bbox

DataCube.filter_bbox()

filter_spatial

DataCube.filter_spatial()

filter_temporal

DataCube.filter_temporal()

fit_class_random_forest

DataCube.fit_class_random_forest()

fit_curve

DataCube.fit_curve()

fit_regr_random_forest

DataCube.fit_regr_random_forest()

flatten_dimensions

DataCube.flatten_dimensions()

ge

DataCube.__ge__()

gt

DataCube.__gt__()

le

DataCube.__le__()

linear_scale_range

DataCube.linear_scale_range()

ln

DataCube.ln()

load_collection

DataCube.load_collection()

load_ml_model

MlModel.load_ml_model()

log

DataCube.logarithm(), DataCube.log2(), DataCube.log10()

lt

DataCube.__lt__()

mask

DataCube.mask()

mask_polygon

DataCube.mask_polygon()

max

DataCube.max_time()

mean

DataCube.mean_time()

median

DataCube.median_time()

merge_cubes

DataCube.merge_cubes()

min

DataCube.min_time()

multiply

DataCube.multiply(), DataCube.__neg__(), DataCube.__mul__(), DataCube.__rmul__()

ndvi

DataCube.ndvi()

neq

DataCube.__ne__()

normalized_difference

DataCube.normalized_difference()

not

DataCube.__invert__()

or

DataCube.logical_or(), DataCube.__or__()

power

DataCube.__rpow__(), DataCube.__pow__(), DataCube.power()

predict_curve

DataCube.predict_curve()

predict_random_forest

DataCube.predict_random_forest()

reduce_dimension

DataCube.reduce_dimension(), DataCube.reduce_temporal_udf(), DataCube.reduce_temporal_simple()

rename_dimension

DataCube.rename_dimension()

rename_labels

DataCube.rename_labels()

resample_cube_temporal

DataCube.resample_cube_temporal()

resample_spatial

DataCube.resample_spatial()

resolution_merge

DataCube.resolution_merge()

run_udf

VectorCube.run_udf()

sar_backscatter

DataCube.sar_backscatter()

save_result

VectorCube.save_result(), DataCube.save_result()

subtract

DataCube.subtract(), DataCube.__sub__(), DataCube.__rsub__()

unflatten_dimension

DataCube.unflatten_dimension()

(Table autogenerated on 2022-06-09)