Source code for openeo.processes


# Do not edit this file directly.
# It is automatically generated.
# Used command line arguments:
#    openeo/internal/processes/generator.py specs/openeo-processes specs/openeo-processes/proposals specs/openeo-processes-legacy --output openeo/processes.py
# Generated on 2024-01-09

from __future__ import annotations

import builtins

from openeo.internal.documentation import openeo_process
from openeo.internal.processes.builder import UNSET, ProcessBuilderBase
from openeo.rest._datacube import build_child_callback


[docs] class ProcessBuilder(ProcessBuilderBase): """ .. include:: api-processbuilder.rst """ _ITERATION_LIMIT = 100 @openeo_process(process_id="add", mode="operator") def __add__(self, other) -> ProcessBuilder: return self.add(other) @openeo_process(process_id="add", mode="operator") def __radd__(self, other) -> ProcessBuilder: return add(other, self) @openeo_process(process_id="subtract", mode="operator") def __sub__(self, other) -> ProcessBuilder: return self.subtract(other) @openeo_process(process_id="subtract", mode="operator") def __rsub__(self, other) -> ProcessBuilder: return subtract(other, self) @openeo_process(process_id="multiply", mode="operator") def __mul__(self, other) -> ProcessBuilder: return self.multiply(other) @openeo_process(process_id="multiply", mode="operator") def __rmul__(self, other) -> ProcessBuilder: return multiply(other, self) @openeo_process(process_id="divide", mode="operator") def __truediv__(self, other) -> ProcessBuilder: return self.divide(other) @openeo_process(process_id="divide", mode="operator") def __rtruediv__(self, other) -> ProcessBuilder: return divide(other, self) @openeo_process(process_id="multiply", mode="operator") def __neg__(self) -> ProcessBuilder: return self.multiply(-1) @openeo_process(process_id="power", mode="operator") def __pow__(self, other) -> ProcessBuilder: return self.power(other) @openeo_process(process_id="array_element", mode="operator") def __getitem__(self, key) -> ProcessBuilder: if isinstance(key, builtins.int): if key > self._ITERATION_LIMIT: raise RuntimeError( "Exceeded ProcessBuilder iteration limit. " "Are you mistakenly using a Python builtin like `sum()` or `all()` in a callback " "instead of the appropriate helpers from the `openeo.processes` module?" ) return self.array_element(index=key) else: return self.array_element(label=key) @openeo_process(process_id="eq", mode="operator") def __eq__(self, other) -> ProcessBuilder: return eq(self, other) @openeo_process(process_id="neq", mode="operator") def __ne__(self, other) -> ProcessBuilder: return neq(self, other) @openeo_process(process_id="lt", mode="operator") def __lt__(self, other) -> ProcessBuilder: return lt(self, other) @openeo_process(process_id="lte", mode="operator") def __le__(self, other) -> ProcessBuilder: return lte(self, other) @openeo_process(process_id="ge", mode="operator") def __ge__(self, other) -> ProcessBuilder: return gte(self, other) @openeo_process(process_id="gt", mode="operator") def __gt__(self, other) -> ProcessBuilder: return gt(self, other)
[docs] @openeo_process def absolute(self) -> ProcessBuilder: """ Absolute value :param self: A number. :return: The computed absolute value. """ return absolute(x=self)
[docs] @openeo_process def add(self, y) -> ProcessBuilder: """ Addition of two numbers :param self: The first summand. :param y: The second summand. :return: The computed sum of the two numbers. """ return add(x=self, y=y)
[docs] @openeo_process def add_dimension(self, name, label, type=UNSET) -> ProcessBuilder: """ Add a new dimension :param self: A data cube to add the dimension to. :param name: Name for the dimension. :param label: A dimension label. :param type: The type of dimension, defaults to `other`. :return: The data cube with a newly added dimension. The new dimension has exactly one dimension label. All other dimensions remain unchanged. """ return add_dimension(data=self, name=name, label=label, type=type)
[docs] @openeo_process def aggregate_spatial(self, geometries, reducer, target_dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Zonal statistics for geometries :param self: A raster data cube with at least two spatial dimensions. The data cube implicitly gets restricted to the bounds of the geometries as if ``filter_spatial()`` would have been used with the same values for the corresponding parameters immediately before this process. :param geometries: Geometries for which the aggregation will be computed. Feature properties are preserved for vector data cubes and all GeoJSON Features. One value will be computed per label in the dimension of type `geometries`, GeoJSON `Feature` or `Geometry`. For a `FeatureCollection` multiple values will be computed, one value per contained `Feature`. No values will be computed for empty geometries. For example, a single value will be computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons. - For **polygons**, the process considers all pixels for which the point at the pixel center intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC). - For **points**, the process considers the closest pixel center. - For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line. Thus, pixels may be part of multiple geometries and be part of multiple aggregations. No operation is applied to geometries that are outside of the bounds of the data. :param reducer: A reducer to be applied on all values of each geometry. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param target_dimension: By default (which is `null`), the process only computes the results and doesn't add a new dimension. If this parameter contains a new dimension name, the computation also stores information about the total count of pixels (valid + invalid pixels) and the number of valid pixels (see ``is_valid()``) for each computed value. These values are added as a new dimension. The new dimension of type `other` has the dimension labels `value`, `total_count` and `valid_count`. Fails with a `TargetDimensionExists` exception if a dimension with the specified name exists. :param context: Additional data to be passed to the reducer. :return: A vector data cube with the computed results. Empty geometries still exist but without any aggregated values (i.e. no-data). The spatial dimensions are replaced by a dimension of type 'geometries' and if `target_dimension` is not `null`, a new dimension is added. """ return aggregate_spatial( data=self, geometries=geometries, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), target_dimension=target_dimension, context=context )
[docs] @openeo_process def aggregate_spatial_window(self, reducer, size, boundary=UNSET, align=UNSET, context=UNSET) -> ProcessBuilder: """ Zonal statistics for rectangular windows :param self: A raster data cube with exactly two horizontal spatial dimensions and an arbitrary number of additional dimensions. The process is applied to all additional dimensions individually. :param reducer: A reducer to be applied on the list of values, which contain all pixels covered by the window. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param size: Window size in pixels along the horizontal spatial dimensions. The first value corresponds to the `x` axis, the second value corresponds to the `y` axis. :param boundary: Behavior to apply if the number of values for the axes `x` and `y` is not a multiple of the corresponding value in the `size` parameter. Options are: - `pad` (default): pad the data cube with the no-data value `null` to fit the required window size. - `trim`: trim the data cube to fit the required window size. Set the parameter `align` to specifies to which corner the data is aligned to. :param align: If the data requires padding or trimming (see parameter `boundary`), specifies to which corner of the spatial extent the data is aligned to. For example, if the data is aligned to the upper left, the process pads/trims at the lower-right. :param context: Additional data to be passed to the reducer. :return: A raster data cube with the newly computed values and the same dimensions. The resolution will change depending on the chosen values for the `size` and `boundary` parameter. It usually decreases for the dimensions which have the corresponding parameter `size` set to values greater than 1. The dimension labels will be set to the coordinate at the center of the window. The other dimension properties (name, type and reference system) remain unchanged. """ return aggregate_spatial_window( data=self, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), size=size, boundary=boundary, align=align, context=context )
[docs] @openeo_process def aggregate_temporal(self, intervals, reducer, labels=UNSET, dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Temporal aggregations :param self: A data cube. :param intervals: Left-closed temporal intervals, which are allowed to overlap. Each temporal interval in the array has exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element, except when using time without date. Otherwise, a `TemporalExtentEmpty` exception is thrown. :param reducer: A reducer to be applied for the values contained in each interval. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Intervals may not contain any values, which for most reducers leads to no-data (`null`) values by default. :param labels: Distinct labels for the intervals, which can contain dates and/or times. Is only required to be specified if the values for the start of the temporal intervals are not distinct and thus the default labels would not be unique. The number of labels and the number of groups need to be equal. :param dimension: The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension. """ return aggregate_temporal( data=self, intervals=intervals, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), labels=labels, dimension=dimension, context=context )
[docs] @openeo_process def aggregate_temporal_period(self, period, reducer, dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Temporal aggregations based on calendar hierarchies :param self: The source data cube. :param period: The time intervals to aggregate. The following pre-defined values are available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month can range from 8 to 11 days. For example, the third dekad of a year spans from January 21 till January 31 (11 days), the fourth dekad spans from February 1 till February 10 (10 days) and the sixth dekad spans from February 21 till February 28 or February 29 in a leap year (8 or 9 days respectively). * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0 decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD) calendar era, from a year ending in a 1 to the next year ending in a 0. :param reducer: A reducer to be applied for the values contained in each period. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Periods may not contain any values, which for most reducers leads to no-data (`null`) values by default. :param dimension: The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the source data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension. The specified temporal dimension has the following dimension labels (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM- DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical- season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1` The dimension labels in the new data cube are complete for the whole extent of the source data cube. For example, if `period` is set to `day` and the source data cube has two dimension labels at the beginning of the year (`2020-01-01`) and the end of a year (`2020-12-31`), the process returns a data cube with 365 dimension labels (`2020-001`, `2020-002`, ..., `2020-365`). In contrast, if `period` is set to `day` and the source data cube has just one dimension label `2020-01-05`, the process returns a data cube with just a single dimension label (`2020-005`). """ return aggregate_temporal_period( data=self, period=period, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def all(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Are all of the values true? :param self: A set of boolean values. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. :return: Boolean result of the logical operation. """ return all(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def and_(self, y) -> ProcessBuilder: """ Logical AND :param self: A boolean value. :param y: A boolean value. :return: Boolean result of the logical AND. """ return and_(x=self, y=y)
[docs] @openeo_process def anomaly(self, normals, period) -> ProcessBuilder: """ Compute anomalies :param self: A data cube with exactly one temporal dimension and the following dimension labels for the given period (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM-DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1` * `single-period` / `climatology-period`: Any ``aggregate_temporal_period()`` can compute such a data cube. :param normals: A data cube with normals, e.g. daily, monthly or yearly values computed from a process such as ``climatological_normal()``. Must contain exactly one temporal dimension with the following dimension labels for the given period: * `hour`: `00` - `23` * `day`: `001` - `365` * `week`: `01` - `52` * `dekad`: `00` - `36` * `month`: `01` - `12` * `season`: `djf` (December - February), `mam` (March - May), `jja` (June - August), `son` (September - November) * `tropical-season`: `ndjfma` (November - April), `mjjaso` (May - October) * `year`: Four-digit year numbers * `decade`: Four-digit year numbers, the last digit being a `0` * `decade-ad`: Four-digit year numbers, the last digit being a `1` * `single-period` / `climatology-period`: A single dimension label with any name is expected. :param period: Specifies the time intervals available in the normals data cube. The following options are available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month can range from 8 to 11 days. For example, the fourth dekad is Feb, 1 - Feb, 10 each year. * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical- season`: Six month periods of the tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0 decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD) calendar era, from a year ending in a 1 to the next year ending in a 0. * `single-period` / `climatology-period`: A single period of arbitrary length :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return anomaly(data=self, normals=normals, period=period)
[docs] @openeo_process def any(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Is at least one value true? :param self: A set of boolean values. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. :return: Boolean result of the logical operation. """ return any(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def apply(self, process, context=UNSET) -> ProcessBuilder: """ Apply a process to each value :param self: A data cube. :param process: A process that accepts and returns a single value and is applied on each individual value in the data cube. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return apply(data=self, process=build_child_callback(process, parent_parameters=['x', 'context']), context=context)
[docs] @openeo_process def apply_dimension(self, process, dimension, target_dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to all values along a dimension :param self: A data cube. :param process: Process to be applied on all values along the given dimension. The specified process needs to accept an array and must return an array with at least one element. A process may consist of multiple sub-processes. :param dimension: The name of the source dimension to apply the process on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param target_dimension: The name of the target dimension or `null` (the default) to use the source dimension specified in the parameter `dimension`. By specifying a target dimension, the source dimension is removed. The target dimension with the specified name and the type `other` (see ``add_dimension()``) is created, if it doesn't exist yet. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values. All dimensions stay the same, except for the dimensions specified in corresponding parameters. There are three cases how the dimensions can change: 1. The source dimension is the target dimension: - The (number of) dimensions remain unchanged as the source dimension is the target dimension. - The source dimension properties name and type remain unchanged. - The dimension labels, the reference system and the resolution are preserved only if the number of values in the source dimension is equal to the number of values computed by the process. Otherwise, all other dimension properties change as defined in the list below. 2. The source dimension is not the target dimension. The target dimension exists with a single label only: - The number of dimensions decreases by one as the source dimension is 'dropped' and the target dimension is filled with the processed data that originates from the source dimension. - The target dimension properties name and type remain unchanged. All other dimension properties change as defined in the list below. 3. The source dimension is not the target dimension and the latter does not exist: - The number of dimensions remain unchanged, but the source dimension is replaced with the target dimension. - The target dimension has the specified name and the type other. All other dimension properties are set as defined in the list below. Unless otherwise stated above, for the given (target) dimension the following applies: - the number of dimension labels is equal to the number of values computed by the process, - the dimension labels are incrementing integers starting from zero, - the resolution changes, and - the reference system is undefined. """ return apply_dimension( data=self, process=build_child_callback(process, parent_parameters=['data', 'context']), dimension=dimension, target_dimension=target_dimension, context=context )
[docs] @openeo_process def apply_kernel(self, kernel, factor=UNSET, border=UNSET, replace_invalid=UNSET) -> ProcessBuilder: """ Apply a spatial convolution with a kernel :param self: A raster data cube. :param kernel: Kernel as a two-dimensional array of weights. The inner level of the nested array aligns with the `x` axis and the outer level aligns with the `y` axis. Each level of the kernel must have an uneven number of elements, otherwise the process throws a `KernelDimensionsUneven` exception. :param factor: A factor that is multiplied to each value after the kernel has been applied. This is basically a shortcut for explicitly multiplying each value by a factor afterwards, which is often required for some kernel-based algorithms such as the Gaussian blur. :param border: Determines how the data is extended when the kernel overlaps with the borders. Defaults to fill the border with zeroes. The following options are available: * *numeric value* - fill with a user-defined constant number `n`: `nnnnnn|abcdefgh|nnnnnn` (default, with `n` = 0) * `replicate` - repeat the value from the pixel at the border: `aaaaaa|abcdefgh|hhhhhh` * `reflect` - mirror/reflect from the border: `fedcba|abcdefgh|hgfedc` * `reflect_pixel` - mirror/reflect from the center of the pixel at the border: `gfedcb|abcdefgh|gfedcb` * `wrap` - repeat/wrap the image: `cdefgh|abcdefgh|abcdef` :param replace_invalid: This parameter specifies the value to replace non-numerical or infinite numerical values with. By default, those values are replaced with zeroes. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return apply_kernel(data=self, kernel=kernel, factor=factor, border=border, replace_invalid=replace_invalid)
[docs] @openeo_process def apply_neighborhood(self, process, size, overlap=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to pixels in a n-dimensional neighborhood :param self: A raster data cube. :param process: Process to be applied on all neighborhoods. :param size: Neighborhood sizes along each dimension. This object maps dimension names to either a physical measure (e.g. 100 m, 10 days) or pixels (e.g. 32 pixels). For dimensions not specified, the default is to provide all values. Be aware that including all values from overly large dimensions may not be processed at once. :param overlap: Overlap of neighborhoods along each dimension to avoid border effects. By default no overlap is provided. For instance a temporal dimension can add 1 month before and after a neighborhood. In the spatial dimensions, this is often a number of pixels. The overlap specified is added before and after, so an overlap of 8 pixels will add 8 pixels on both sides of the window, so 16 in total. Be aware that large overlaps increase the need for computational resources and modifying overlapping data in subsequent operations have no effect. :param context: Additional data to be passed to the process. :return: A raster data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return apply_neighborhood( data=self, process=build_child_callback(process, parent_parameters=['data', 'context']), size=size, overlap=overlap, context=context )
[docs] @openeo_process def apply_polygon(self, polygons, process, mask_value=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to segments of the data cube :param self: A data cube. :param polygons: A vector data cube containing at least one polygon. The provided vector data can be one of the following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. :param process: A process that accepts and returns a single data cube and is applied on each individual sub data cube. The process may consist of multiple sub-processes. :param mask_value: All pixels for which the point at the pixel center **does not** intersect with the polygon are replaced with the given value, which defaults to `null` (no data). It can provide a distinction between no data values within the polygon and masked pixels outside of it. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return apply_polygon( data=self, polygons=polygons, process=build_child_callback(process, parent_parameters=['data', 'context']), mask_value=mask_value, context=context )
[docs] @openeo_process def arccos(self) -> ProcessBuilder: """ Inverse cosine :param self: A number. :return: The computed angle in radians. """ return arccos(x=self)
[docs] @openeo_process def arcosh(self) -> ProcessBuilder: """ Inverse hyperbolic cosine :param self: A number. :return: The computed angle in radians. """ return arcosh(x=self)
[docs] @openeo_process def arcsin(self) -> ProcessBuilder: """ Inverse sine :param self: A number. :return: The computed angle in radians. """ return arcsin(x=self)
[docs] @openeo_process def arctan(self) -> ProcessBuilder: """ Inverse tangent :param self: A number. :return: The computed angle in radians. """ return arctan(x=self)
[docs] @openeo_process def arctan2(self, x) -> ProcessBuilder: """ Inverse tangent of two numbers :param self: A number to be used as the dividend. :param x: A number to be used as the divisor. :return: The computed angle in radians. """ return arctan2(y=self, x=x)
[docs] @openeo_process def ard_normalized_radar_backscatter(self, elevation_model=UNSET, contributing_area=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET, options=UNSET) -> ProcessBuilder: """ CARD4L compliant SAR NRB generation :param self: The source data cube containing SAR input. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility. :param contributing_area: If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters. :param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees. :param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise. :param options: Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability. :return: Backscatter values expressed as gamma0 in linear scale. In addition to the bands `contributing_area` and `ellipsoid_incidence_angle` that can optionally be added with corresponding parameters, the following bands are always added to the data cube: - `mask`: A data mask that indicates which values are valid (1), invalid (0) or contain no-data (null). - `local_incidence_angle`: A band with DEM-based local incidence angles in degrees. The data returned is CARD4L compliant with corresponding metadata. """ return ard_normalized_radar_backscatter( data=self, elevation_model=elevation_model, contributing_area=contributing_area, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal, options=options )
[docs] @openeo_process def ard_surface_reflectance(self, atmospheric_correction_method, cloud_detection_method, elevation_model=UNSET, atmospheric_correction_options=UNSET, cloud_detection_options=UNSET) -> ProcessBuilder: """ CARD4L compliant Surface Reflectance generation :param self: The source data cube containing multi-spectral optical top of the atmosphere (TOA) reflectances. There must be a single dimension of type `bands` available. :param atmospheric_correction_method: The atmospheric correction method to use. :param cloud_detection_method: The cloud detection method to use. Each method supports detecting different atmospheric disturbances such as clouds, cloud shadows, aerosols, haze, ozone and/or water vapour in optical imagery. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility. :param atmospheric_correction_options: Proprietary options for the atmospheric correction method. Specifying proprietary options will reduce portability. :param cloud_detection_options: Proprietary options for the cloud detection method. Specifying proprietary options will reduce portability. :return: Data cube containing bottom of atmosphere reflectances for each spectral band in the source data cube, with atmospheric disturbances like clouds and cloud shadows removed. No-data values (null) are directly set in the bands. Depending on the methods used, several additional bands will be added to the data cube: Data cube containing bottom of atmosphere reflectances for each spectral band in the source data cube, with atmospheric disturbances like clouds and cloud shadows removed. Depending on the methods used, several additional bands will be added to the data cube: - `date` (optional): Specifies per-pixel acquisition timestamps. - `incomplete-testing` (required): Identifies pixels with a value of 1 for which the per-pixel tests (at least saturation, cloud and cloud shadows, see CARD4L specification for details) have not all been successfully completed. Otherwise, the value is 0. - `saturation` (required) / `saturation_{band}` (optional): Indicates where pixels in the input spectral bands are saturated (1) or not (0). If the saturation is given per band, the band names are `saturation_{band}` with `{band}` being the band name from the source data cube. - `cloud`, `shadow` (both required),`aerosol`, `haze`, `ozone`, `water_vapor` (all optional): Indicates the probability of pixels being an atmospheric disturbance such as clouds. All bands have values between 0 (clear) and 1, which describes the probability that it is an atmospheric disturbance. - `snow-ice` (optional): Points to a file that indicates whether a pixel is assessed as being snow/ice (1) or not (0). All values describe the probability and must be between 0 and 1. - `land-water` (optional): Indicates whether a pixel is assessed as being land (1) or water (0). All values describe the probability and must be between 0 and 1. - `incidence-angle` (optional): Specifies per-pixel incidence angles in degrees. - `azimuth` (optional): Specifies per-pixel azimuth angles in degrees. - `sun-azimuth:` (optional): Specifies per- pixel sun azimuth angles in degrees. - `sun-elevation` (optional): Specifies per-pixel sun elevation angles in degrees. - `terrain-shadow` (optional): Indicates with a value of 1 whether a pixel is not directly illuminated due to terrain shadowing. Otherwise, the value is 0. - `terrain-occlusion` (optional): Indicates with a value of 1 whether a pixel is not visible to the sensor due to terrain occlusion during off-nadir viewing. Otherwise, the value is 0. - `terrain-illumination` (optional): Contains coefficients used for terrain illumination correction are provided for each pixel. The data returned is CARD4L compliant with corresponding metadata. """ return ard_surface_reflectance( data=self, atmospheric_correction_method=atmospheric_correction_method, cloud_detection_method=cloud_detection_method, elevation_model=elevation_model, atmospheric_correction_options=atmospheric_correction_options, cloud_detection_options=cloud_detection_options )
[docs] @openeo_process def array_append(self, value, label=UNSET) -> ProcessBuilder: """ Append a value to an array :param self: An array. :param value: Value to append to the array. :param label: If the given array is a labeled array, a new label for the new value should be given. If not given or `null`, the array index as string is used as the label. If in any case the label exists, a `LabelExists` exception is thrown. :return: The new array with the value being appended. """ return array_append(data=self, value=value, label=label)
[docs] @openeo_process def array_apply(self, process, context=UNSET) -> ProcessBuilder: """ Apply a process to each array element :param self: An array. :param process: A process that accepts and returns a single value and is applied on each individual value in the array. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``. :param context: Additional data to be passed to the process. :return: An array with the newly computed values. The number of elements are the same as for the original array. """ return array_apply( data=self, process=build_child_callback(process, parent_parameters=['x', 'index', 'label', 'context']), context=context )
[docs] @openeo_process def array_concat(self, array2) -> ProcessBuilder: """ Merge two arrays :param self: The first array. :param array2: The second array. :return: The merged array. """ return array_concat(array1=self, array2=array2)
[docs] @openeo_process def array_contains(self, value) -> ProcessBuilder: """ Check whether the array contains a given value :param self: List to find the value in. :param value: Value to find in `data`. If the value is `null`, this process returns always `false`. :return: `true` if the list contains the value, false` otherwise. """ return array_contains(data=self, value=value)
[docs] @openeo_process def array_create(self=UNSET, repeat=UNSET) -> ProcessBuilder: """ Create an array :param self: A (native) array to fill the newly created array with. Defaults to an empty array. :param repeat: The number of times the (native) array specified in `data` is repeatedly added after each other to the new array being created. Defaults to `1`. :return: The newly created array. """ return array_create(data=self, repeat=repeat)
[docs] @openeo_process def array_create_labeled(self, labels) -> ProcessBuilder: """ Create a labeled array :param self: An array of values to be used. :param labels: An array of labels to be used. :return: The newly created labeled array. """ return array_create_labeled(data=self, labels=labels)
[docs] @openeo_process def array_element(self, index=UNSET, label=UNSET, return_nodata=UNSET) -> ProcessBuilder: """ Get an element from an array :param self: An array. :param index: The zero-based index of the element to retrieve. :param label: The label of the element to retrieve. Throws an `ArrayNotLabeled` exception, if the given array is not a labeled array and this parameter is set. :param return_nodata: By default this process throws an `ArrayElementNotAvailable` exception if the index or label is invalid. If you want to return `null` instead, set this flag to `true`. :return: The value of the requested element. """ return array_element(data=self, index=index, label=label, return_nodata=return_nodata)
[docs] @openeo_process def array_filter(self, condition, context=UNSET) -> ProcessBuilder: """ Filter an array based on a condition :param self: An array. :param condition: A condition that is evaluated against each value, index and/or label in the array. Only the array elements for which the condition returns `true` are preserved. :param context: Additional data to be passed to the condition. :return: An array filtered by the specified condition. The number of elements are less than or equal compared to the original array. """ return array_filter( data=self, condition=build_child_callback(condition, parent_parameters=['x', 'index', 'label', 'context']), context=context )
[docs] @openeo_process def array_find(self, value, reverse=UNSET) -> ProcessBuilder: """ Get the index for a value in an array :param self: List to find the value in. :param value: Value to find in `data`. If the value is `null`, this process returns always `null`. :param reverse: By default, this process finds the index of the first match. To return the index of the last match instead, set this flag to `true`. :return: The index of the first element with the specified value. If no element was found, `null` is returned. """ return array_find(data=self, value=value, reverse=reverse)
[docs] @openeo_process def array_find_label(self, label) -> ProcessBuilder: """ Get the index for a label in a labeled array :param self: List to find the label in. :param label: Label to find in `data`. :return: The index of the element with the specified label assigned. If no such label was found, `null` is returned. """ return array_find_label(data=self, label=label)
[docs] @openeo_process def array_interpolate_linear(self) -> ProcessBuilder: """ One-dimensional linear interpolation for arrays :param self: An array of numbers and no-data values. If the given array is a labeled array, the labels must have a natural/inherent label order and the process expects the labels to be sorted accordingly. This is the default behavior in openEO for spatial and temporal dimensions. :return: An array with no-data values being replaced with interpolated values. If not at least 2 numerical values are available in the array, the array stays the same. """ return array_interpolate_linear(data=self)
[docs] @openeo_process def array_labels(self) -> ProcessBuilder: """ Get the labels for an array :param self: An array. :return: The labels or indices as array. """ return array_labels(data=self)
[docs] @openeo_process def array_modify(self, values, index, length=UNSET) -> ProcessBuilder: """ Change the content of an array (remove, insert, update) :param self: The array to modify. :param values: The values to insert into the `data` array. :param index: The index in the `data` array of the element to insert the value(s) before. If the index is greater than the number of elements in the `data` array, the process throws an `ArrayElementNotAvailable` exception. To insert after the last element, there are two options: 1. Use the simpler processes ``array_append()`` to append a single value or ``array_concat()`` to append multiple values. 2. Specify the number of elements in the array. You can retrieve the number of elements with the process ``count()``, having the parameter `condition` set to `true`. :param length: The number of elements in the `data` array to remove (or replace) starting from the given index. If the array contains fewer elements, the process simply removes all elements up to the end. :return: An array with values added, updated or removed. """ return array_modify(data=self, values=values, index=index, length=length)
[docs] @openeo_process def arsinh(self) -> ProcessBuilder: """ Inverse hyperbolic sine :param self: A number. :return: The computed angle in radians. """ return arsinh(x=self)
[docs] @openeo_process def artanh(self) -> ProcessBuilder: """ Inverse hyperbolic tangent :param self: A number. :return: The computed angle in radians. """ return artanh(x=self)
[docs] @openeo_process def atmospheric_correction(self, method, elevation_model=UNSET, options=UNSET) -> ProcessBuilder: """ Apply atmospheric correction :param self: Data cube containing multi-spectral optical top of atmosphere reflectances to be corrected. :param method: The atmospheric correction method to use. To get reproducible results, you have to set a specific method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce reproducibility as you *may* get different results if you run the processes multiple times. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility. :param options: Proprietary options for the atmospheric correction method. Specifying proprietary options will reduce portability. :return: Data cube containing bottom of atmosphere reflectances. """ return atmospheric_correction(data=self, method=method, elevation_model=elevation_model, options=options)
[docs] @openeo_process def between(self, min, max, exclude_max=UNSET) -> ProcessBuilder: """ Between comparison :param self: The value to check. :param min: Lower boundary (inclusive) to check against. :param max: Upper boundary (inclusive) to check against. :param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`. :return: `true` if `x` is between the specified bounds, otherwise `false`. """ return between(x=self, min=min, max=max, exclude_max=exclude_max)
[docs] @openeo_process def ceil(self) -> ProcessBuilder: """ Round fractions up :param self: A number to round up. :return: The number rounded up. """ return ceil(x=self)
[docs] @openeo_process def climatological_normal(self, period, climatology_period=UNSET) -> ProcessBuilder: """ Compute climatology normals :param self: A data cube with exactly one temporal dimension. The data cube must span at least the temporal interval specified in the parameter `climatology-period`. Seasonal periods may span two consecutive years, e.g. temporal winter that includes months December, January and February. If the required months before the actual climate period are available, the season is taken into account. If not available, the first season is not taken into account and the seasonal mean is based on one year less than the other seasonal normals. The incomplete season at the end of the last year is never taken into account. :param period: The time intervals to aggregate the average value for. The following pre-defined frequencies are supported: * `day`: Day of the year * `month`: Month of the year * `climatology- period`: The period specified in the `climatology-period`. * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical- season`: Six month periods of the tropical seasons (November - April, May - October). :param climatology_period: The climatology period as a closed temporal interval. The first element of the array is the first year to be fully included in the temporal interval. The second element is the last year to be fully included in the temporal interval. The default climatology period is from 1981 until 2010 (both inclusive) right now, but this might be updated over time to what is commonly used in climatology. If you don't want to keep your research to be reproducible, please explicitly specify a period. :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the temporal dimension. The temporal dimension has the following dimension labels: * `day`: `001` - `365` * `month`: `01` - `12` * `climatology-period`: `climatology-period` * `season`: `djf` (December - February), `mam` (March - May), `jja` (June - August), `son` (September - November) * `tropical- season`: `ndjfma` (November - April), `mjjaso` (May - October) """ return climatological_normal(data=self, period=period, climatology_period=climatology_period)
[docs] @openeo_process def clip(self, min, max) -> ProcessBuilder: """ Clip a value between a minimum and a maximum :param self: A number. :param min: Minimum value. If the value is lower than this value, the process will return the value of this parameter. :param max: Maximum value. If the value is greater than this value, the process will return the value of this parameter. :return: The value clipped to the specified range. """ return clip(x=self, min=min, max=max)
[docs] @openeo_process def cloud_detection(self, method, options=UNSET) -> ProcessBuilder: """ Create cloud masks :param self: The source data cube containing multi-spectral optical top of the atmosphere (TOA) reflectances on which to perform cloud detection. :param method: The cloud detection method to use. To get reproducible results, you have to set a specific method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce reproducibility as you *may* get different results if you run the processes multiple times. :param options: Proprietary options for the cloud detection method. Specifying proprietary options will reduce portability. :return: A data cube with bands for the atmospheric disturbances. Each of the masks contains values between 0 and 1. The data cube has the same spatial and temporal dimensions as the source data cube and a dimension that contains a dimension label for each of the supported/considered atmospheric disturbance. """ return cloud_detection(data=self, method=method, options=options)
[docs] @openeo_process def constant(self) -> ProcessBuilder: """ Define a constant value :param self: The value of the constant. :return: The value of the constant. """ return constant(x=self)
[docs] @openeo_process def cos(self) -> ProcessBuilder: """ Cosine :param self: An angle in radians. :return: The computed cosine of `x`. """ return cos(x=self)
[docs] @openeo_process def cosh(self) -> ProcessBuilder: """ Hyperbolic cosine :param self: An angle in radians. :return: The computed hyperbolic cosine of `x`. """ return cosh(x=self)
[docs] @openeo_process def count(self, condition=UNSET, context=UNSET) -> ProcessBuilder: """ Count the number of elements :param self: An array with elements of any data type. :param condition: A condition consists of one or more processes, which in the end return a boolean value. It is evaluated against each element in the array. An element is counted only if the condition returns `true`. Defaults to count valid elements in a list (see ``is_valid()``). Setting this parameter to boolean `true` counts all elements in the list. `false` is not a valid value for this parameter. :param context: Additional data to be passed to the condition. :return: The counted number of elements. """ return count(data=self, condition=condition, context=context)
[docs] @openeo_process def create_data_cube(self) -> ProcessBuilder: """ Create an empty data cube :return: An empty data cube with no dimensions. """ return create_data_cube()
[docs] @openeo_process def cummax(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative maxima :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative maxima. """ return cummax(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cummin(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative minima :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative minima. """ return cummin(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cumproduct(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative products :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative products. """ return cumproduct(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cumsum(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative sums :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative sums. """ return cumsum(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def date_between(self, min, max, exclude_max=UNSET) -> ProcessBuilder: """ Between comparison for dates and times :param self: The value to check. :param min: Lower boundary (inclusive) to check against. :param max: Upper boundary (inclusive) to check against. :param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`. :return: `true` if `x` is between the specified bounds, otherwise `false`. """ return date_between(x=self, min=min, max=max, exclude_max=exclude_max)
[docs] @openeo_process def date_difference(self, date2, unit=UNSET) -> ProcessBuilder: """ Computes the difference between two time instants :param self: The base date, optionally with a time component. :param date2: The other date, optionally with a time component. :param unit: The unit for the returned value. The following units are available: - millisecond - second - leap seconds are ignored in computations. - minute - hour - day - month - year :return: Returns the difference between date1 and date2 in the given unit (seconds by default), including a fractional part if required. For comparison purposes this means: - If `date1` < `date2`, the returned value is positive. - If `date1` = `date2`, the returned value is 0. - If `date1` > `date2`, the returned value is negative. """ return date_difference(date1=self, date2=date2, unit=unit)
[docs] @openeo_process def date_shift(self, value, unit) -> ProcessBuilder: """ Manipulates dates and times by addition or subtraction :param self: The date (and optionally time) to manipulate. If the given date doesn't include the time, the process assumes that the time component is `00:00:00Z` (i.e. midnight, in UTC). The millisecond part of the time is optional and defaults to `0` if not given. :param value: The period of time in the unit given that is added (positive numbers) or subtracted (negative numbers). The value `0` doesn't have any effect. :param unit: The unit for the value given. The following pre-defined units are available: - millisecond: Milliseconds - second: Seconds - leap seconds are ignored in computations. - minute: Minutes - hour: Hours - day: Days - changes only the the day part of a date - week: Weeks (equivalent to 7 days) - month: Months - year: Years Manipulations with the unit `year`, `month`, `week` or `day` do never change the time. If any of the manipulations result in an invalid date or time, the corresponding part is rounded down to the next valid date or time respectively. For example, adding a month to `2020-01-31` would result in `2020-02-29`. :return: The manipulated date. If a time component was given in the parameter `date`, the time component is returned with the date. """ return date_shift(date=self, value=value, unit=unit)
[docs] @openeo_process def dimension_labels(self, dimension) -> ProcessBuilder: """ Get the dimension labels :param self: The data cube. :param dimension: The name of the dimension to get the labels for. :return: The labels as an array. """ return dimension_labels(data=self, dimension=dimension)
[docs] @openeo_process def divide(self, y) -> ProcessBuilder: """ Division of two numbers :param self: The dividend. :param y: The divisor. :return: The computed result. """ return divide(x=self, y=y)
[docs] @openeo_process def drop_dimension(self, name) -> ProcessBuilder: """ Remove a dimension :param self: The data cube to drop a dimension from. :param name: Name of the dimension to drop. :return: A data cube without the specified dimension. The number of dimensions decreases by one, but the dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return drop_dimension(data=self, name=name)
[docs] @openeo_process def e(self) -> ProcessBuilder: """ Euler's number (e) :return: The numerical value of Euler's number. """ return e()
[docs] @openeo_process def eq(self, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder: """ Equal to comparison :param self: First operand. :param y: Second operand. :param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation. This option is basically an alias for the following computation: `lte(abs(minus([x, y]), delta)` :param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `x` is equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return eq(x=self, y=y, delta=delta, case_sensitive=case_sensitive)
[docs] @openeo_process def exp(self) -> ProcessBuilder: """ Exponentiation to the base e :param self: The numerical exponent. :return: The computed value for *e* raised to the power of `p`. """ return exp(p=self)
[docs] @openeo_process def extrema(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Minimum and maximum values :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with two `null` values is returned if any value is such a value. :return: An array containing the minimum and maximum values for the specified numbers. The first element is the minimum, the second element is the maximum. If the input array is empty both elements are set to `null`. """ return extrema(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def filter_bands(self, bands=UNSET, wavelengths=UNSET) -> ProcessBuilder: """ Filter the bands by names :param self: A data cube with bands. :param bands: A list of band names. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands). If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. :param wavelengths: A list of sub-lists with each sub-list consisting of two elements. The first element is the minimum wavelength and the second element is the maximum wavelength. Wavelengths are specified in micrometers (μm). The order of the specified array defines the order of the bands in the data cube. If multiple bands match the wavelengths, all matched bands are included in the original order. :return: A data cube limited to a subset of its original bands. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the dimension of type `bands` has less (or the same) dimension labels. """ return filter_bands(data=self, bands=bands, wavelengths=wavelengths)
[docs] @openeo_process def filter_bbox(self, extent) -> ProcessBuilder: """ Spatial filter using a bounding box :param self: A data cube. :param extent: A bounding box, which may include a vertical axis (see `base` and `height`). :return: A data cube restricted to the bounding box. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels. """ return filter_bbox(data=self, extent=extent)
[docs] @openeo_process def filter_labels(self, condition, dimension, context=UNSET) -> ProcessBuilder: """ Filter dimension labels based on a condition :param self: A data cube. :param condition: A condition that is evaluated against each dimension label in the specified dimension. A dimension label and the corresponding data is preserved for the given dimension, if the condition returns `true`. :param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the condition. :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the given dimension has less (or the same) dimension labels. """ return filter_labels( data=self, condition=build_child_callback(condition, parent_parameters=['value', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def filter_spatial(self, geometries) -> ProcessBuilder: """ Spatial filter raster data cubes using geometries :param self: A raster data cube. :param geometries: One or more geometries used for filtering, given as GeoJSON or vector data cube. If multiple geometries are provided, the union of them is used. Empty geometries are ignored. Limits the data cube to the bounding box of the given geometries. No implicit masking gets applied. To mask the pixels of the data cube use ``mask_polygon()``. :return: A raster data cube restricted to the specified geometries. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels. """ return filter_spatial(data=self, geometries=geometries)
[docs] @openeo_process def filter_temporal(self, extent, dimension=UNSET) -> ProcessBuilder: """ Temporal filter based on temporal intervals :param self: A data cube. :param extent: Left-closed temporal interval, i.e. an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports unbounded intervals by setting one of the boundaries to `null`, but never both. :param dimension: The name of the temporal dimension to filter on. If no specific dimension is specified, the filter applies to all temporal dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :return: A data cube restricted to the specified temporal extent. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the temporal dimensions (determined by `dimensions` parameter) may have less dimension labels. """ return filter_temporal(data=self, extent=extent, dimension=dimension)
[docs] @openeo_process def filter_vector(self, geometries, relation=UNSET) -> ProcessBuilder: """ Spatial vector filter using geometries :param self: A vector data cube with the candidate geometries. :param geometries: One or more base geometries used for filtering, given as vector data cube. If multiple base geometries are provided, the union of them is used. :param relation: The spatial filter predicate for comparing the geometries provided through (a) `geometries` (base geometries) and (b) `data` (candidate geometries). :return: A vector data cube restricted to the specified geometries. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the geometries dimension has less (or the same) dimension labels. """ return filter_vector(data=self, geometries=geometries, relation=relation)
[docs] @openeo_process def first(self, ignore_nodata=UNSET) -> ProcessBuilder: """ First element :param self: An array with elements of any data type. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the first value is such a value. :return: The first element of the input array. """ return first(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def fit_curve(self, parameters, function, ignore_nodata=UNSET) -> ProcessBuilder: """ Curve fitting :param self: A labeled array, the labels correspond to the variable `y` and the values correspond to the variable `x`. :param parameters: Defined the number of parameters for the model function and provides an initial guess for them. At least one parameter is required. :param function: The model function. It must take the parameters to fit as array through the first argument and the independent variable `x` as the second argument. It is recommended to store the model function as a user-defined process on the back-end to be able to re-use the model function with the computed optimal values for the parameters afterwards. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is passed to the model function. :return: An array with the optimal values for the parameters. """ return fit_curve( data=self, parameters=parameters, function=build_child_callback(function, parent_parameters=['x', 'parameters']), ignore_nodata=ignore_nodata )
[docs] @openeo_process def flatten_dimensions(self, dimensions, target_dimension, label_separator=UNSET) -> ProcessBuilder: """ Combine multiple dimensions into a single dimension :param self: A data cube. :param dimensions: The names of the dimension to combine. The order of the array defines the order in which the dimension labels and values are combined (see the example in the process description). Fails with a `DimensionNotAvailable` exception if at least one of the specified dimensions does not exist. :param target_dimension: The name of the new target dimension. A new dimensions will be created with the given names and type `other` (see ``add_dimension()``). Fails with a `TargetDimensionExists` exception if a dimension with the specified name exists. :param label_separator: The string that will be used as a separator for the concatenated dimension labels. To unambiguously revert the dimension labels with the process ``unflatten_dimension()``, the given string must not be contained in any of the dimension labels. :return: A data cube with the new shape. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return flatten_dimensions(data=self, dimensions=dimensions, target_dimension=target_dimension, label_separator=label_separator)
[docs] @openeo_process def floor(self) -> ProcessBuilder: """ Round fractions down :param self: A number to round down. :return: The number rounded down. """ return floor(x=self)
[docs] @openeo_process def gt(self, y) -> ProcessBuilder: """ Greater than comparison :param self: First operand. :param y: Second operand. :return: `true` if `x` is strictly greater than `y` or `null` if any operand is `null`, otherwise `false`. """ return gt(x=self, y=y)
[docs] @openeo_process def gte(self, y) -> ProcessBuilder: """ Greater than or equal to comparison :param self: First operand. :param y: Second operand. :return: `true` if `x` is greater than or equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return gte(x=self, y=y)
[docs] @openeo_process def if_(self, accept, reject=UNSET) -> ProcessBuilder: """ If-Then-Else conditional :param self: A boolean value. :param accept: A value that is returned if the boolean value is `true`. :param reject: A value that is returned if the boolean value is **not** `true`. Defaults to `null`. :return: Either the `accept` or `reject` argument depending on the given boolean value. """ return if_(value=self, accept=accept, reject=reject)
[docs] @openeo_process def inspect(self, message=UNSET, code=UNSET, level=UNSET) -> ProcessBuilder: """ Add information to the logs :param self: Data to log. :param message: A message to send in addition to the data. :param code: A label to help identify one or more log entries originating from this process in the list of all log entries. It can help to group or filter log entries and is usually not unique. :param level: The severity level of this message, defaults to `info`. :return: The data as passed to the `data` parameter without any modification. """ return inspect(data=self, message=message, code=code, level=level)
[docs] @openeo_process def int(self) -> ProcessBuilder: """ Integer part of a number :param self: A number. :return: Integer part of the number. """ return int(x=self)
[docs] @openeo_process def is_infinite(self) -> ProcessBuilder: """ Value is an infinite number :param self: The data to check. :return: `true` if the data is an infinite number, otherwise `false`. """ return is_infinite(x=self)
[docs] @openeo_process def is_nan(self) -> ProcessBuilder: """ Value is not a number :param self: The data to check. :return: Returns `true` for `NaN` and all non-numeric data types, otherwise returns `false`. """ return is_nan(x=self)
[docs] @openeo_process def is_nodata(self) -> ProcessBuilder: """ Value is a no-data value :param self: The data to check. :return: `true` if the data is a no-data value, otherwise `false`. """ return is_nodata(x=self)
[docs] @openeo_process def is_valid(self) -> ProcessBuilder: """ Value is valid data :param self: The data to check. :return: `true` if the data is valid, otherwise `false`. """ return is_valid(x=self)
[docs] @openeo_process def last(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Last element :param self: An array with elements of any data type. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the last value is such a value. :return: The last element of the input array. """ return last(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def linear_scale_range(self, inputMin, inputMax, outputMin=UNSET, outputMax=UNSET) -> ProcessBuilder: """ Linear transformation between two ranges :param self: A number to transform. The number gets clipped to the bounds specified in `inputMin` and `inputMax`. :param inputMin: Minimum value the input can obtain. :param inputMax: Maximum value the input can obtain. :param outputMin: Minimum value of the desired output range. :param outputMax: Maximum value of the desired output range. :return: The transformed number. """ return linear_scale_range(x=self, inputMin=inputMin, inputMax=inputMax, outputMin=outputMin, outputMax=outputMax)
[docs] @openeo_process def ln(self) -> ProcessBuilder: """ Natural logarithm :param self: A number to compute the natural logarithm for. :return: The computed natural logarithm. """ return ln(x=self)
[docs] @openeo_process def load_collection(self, spatial_extent, temporal_extent, bands=UNSET, properties=UNSET) -> ProcessBuilder: """ Load a collection :param self: The collection id. :param spatial_extent: Limits the data to load from the collection to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube if the geometry is fully *within* the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load from the collection to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports unbounded intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :param properties: Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against the collection metadata, see the example. :return: A data cube for further processing. The dimensions and dimension properties (name, type, labels, reference system and resolution) correspond to the collection's metadata, but the dimension labels are restricted as specified in the parameters. """ return load_collection(id=self, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
[docs] @openeo_process def load_geojson(self, properties=UNSET) -> ProcessBuilder: """ Converts GeoJSON into a vector data cube :param self: A GeoJSON object to convert into a vector data cube. The GeoJSON type `GeometryCollection` is not supported. Each geometry in the GeoJSON data results in a dimension label in the `geometries` dimension. :param properties: A list of properties from the GeoJSON file to construct an additional dimension from. A new dimension with the name `properties` and type `other` is created if at least one property is provided. Only applies for GeoJSON Features and FeatureCollections. Missing values are generally set to no-data (`null`). Depending on the number of properties provided, the process creates the dimension differently: - Single property with scalar values: A single dimension label with the name of the property and a single value per geometry. - Single property of type array: The dimension labels correspond to the array indices. There are as many values and labels per geometry as there are for the largest array. - Multiple properties with scalar values: The dimension labels correspond to the property names. There are as many values and labels per geometry as there are properties provided here. :return: A vector data cube containing the geometries, either one or two dimensional. """ return load_geojson(data=self, properties=properties)
[docs] @openeo_process def load_ml_model(self) -> ProcessBuilder: """ Load a ML model :param self: The STAC Item to load the machine learning model from. The STAC Item must implement the `ml-model` extension. :return: A machine learning model to be used with machine learning processes such as ``predict_random_forest()``. """ return load_ml_model(id=self)
[docs] @openeo_process def load_result(self, spatial_extent=UNSET, temporal_extent=UNSET, bands=UNSET) -> ProcessBuilder: """ Load batch job results :param self: The id of a batch job with results. :param spatial_extent: Limits the data to load from the batch job result to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube of the geometry is fully within the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load from the batch job result to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval. 2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval. The specified temporal strings follow [RFC 3339](https://www.rfc-editor.org/rfc/rfc3339.html). Also supports open intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :return: A data cube for further processing. """ return load_result(id=self, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands)
[docs] @openeo_process def load_stac(self, spatial_extent=UNSET, temporal_extent=UNSET, bands=UNSET, properties=UNSET) -> ProcessBuilder: """ Loads data from STAC :param self: The URL to a static STAC catalog (STAC Item, STAC Collection, or STAC Catalog) or a specific STAC API Collection that allows to filter items and to download assets. This includes batch job results, which itself are compliant to STAC. For external URLs, authentication details such as API keys or tokens may need to be included in the URL. Batch job results can be specified in two ways: - For Batch job results at the same back-end, a URL pointing to the corresponding batch job results endpoint should be provided. The URL usually ends with `/jobs/{id}/results` and `{id}` is the corresponding batch job ID. - For external results, a signed URL must be provided. Not all back-ends support signed URLs, which are provided as a link with the link relation `canonical` in the batch job result metadata. :param spatial_extent: Limits the data to load to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube if the geometry is fully within the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval. 2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports open intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :param properties: Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against a STAC API. This parameter is not supported for static STAC. :return: A data cube for further processing. """ return load_stac(url=self, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
[docs] @openeo_process def load_uploaded_files(self, format, options=UNSET) -> ProcessBuilder: """ Load files from the user workspace :param self: The files to read. Folders can't be specified, specify all files instead. An exception is thrown if a file can't be read. :param format: The file format to read from. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*. :param options: The file format parameters to be used to read the files. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: A data cube for further processing. """ return load_uploaded_files(paths=self, format=format, options=options)
[docs] @openeo_process def load_url(self, format, options=UNSET) -> ProcessBuilder: """ Load data from a URL :param self: The URL to read from. Authentication details such as API keys or tokens may need to be included in the URL. :param format: The file format to use when loading the data. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*. :param options: The file format parameters to use when reading the data. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: A data cube for further processing. """ return load_url(url=self, format=format, options=options)
[docs] @openeo_process def log(self, base) -> ProcessBuilder: """ Logarithm to a base :param self: A number to compute the logarithm for. :param base: The numerical base. :return: The computed logarithm. """ return log(x=self, base=base)
[docs] @openeo_process def lt(self, y) -> ProcessBuilder: """ Less than comparison :param self: First operand. :param y: Second operand. :return: `true` if `x` is strictly less than `y`, `null` if any operand is `null`, otherwise `false`. """ return lt(x=self, y=y)
[docs] @openeo_process def lte(self, y) -> ProcessBuilder: """ Less than or equal to comparison :param self: First operand. :param y: Second operand. :return: `true` if `x` is less than or equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return lte(x=self, y=y)
[docs] @openeo_process def mask(self, mask, replacement=UNSET) -> ProcessBuilder: """ Apply a raster mask :param self: A raster data cube. :param mask: A mask as a raster data cube. Every pixel in `data` must have a corresponding element in `mask`. :param replacement: The value used to replace masked values with. :return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return mask(data=self, mask=mask, replacement=replacement)
[docs] @openeo_process def mask_polygon(self, mask, replacement=UNSET, inside=UNSET) -> ProcessBuilder: """ Apply a polygon mask :param self: A raster data cube. :param mask: A GeoJSON object or a vector data cube containing at least one polygon. The provided vector data can be one of the following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. :param replacement: The value used to replace masked values with. :param inside: If set to `true` all pixels for which the point at the pixel center **does** intersect with any polygon are replaced. :return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return mask_polygon(data=self, mask=mask, replacement=replacement, inside=inside)
[docs] @openeo_process def max(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Maximum value :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The maximum value. """ return max(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def mean(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Arithmetic mean (average) :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed arithmetic mean. """ return mean(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def median(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Statistical median :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed statistical median. """ return median(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def merge_cubes(self, cube2, overlap_resolver=UNSET, context=UNSET) -> ProcessBuilder: """ Merge two data cubes :param self: The base data cube. :param cube2: The other data cube to be merged with the base data cube. :param overlap_resolver: A reduction operator that resolves the conflict if the data overlaps. The reducer must return a value of the same data type as the input values are. The reduction operator may be a single process such as ``multiply()`` or consist of multiple sub-processes. `null` (the default) can be specified if no overlap resolver is required. :param context: Additional data to be passed to the overlap resolver. :return: The merged data cube. See the process description for details regarding the dimensions and dimension properties (name, type, labels, reference system and resolution). """ return merge_cubes( cube1=self, cube2=cube2, overlap_resolver=(build_child_callback(overlap_resolver, parent_parameters=['x', 'y', 'context']) if overlap_resolver not in [None, UNSET] else overlap_resolver), context=context )
[docs] @openeo_process def min(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Minimum value :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The minimum value. """ return min(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def mod(self, y) -> ProcessBuilder: """ Modulo :param self: A number to be used as the dividend. :param y: A number to be used as the divisor. :return: The remainder after division. """ return mod(x=self, y=y)
[docs] @openeo_process def multiply(self, y) -> ProcessBuilder: """ Multiplication of two numbers :param self: The multiplier. :param y: The multiplicand. :return: The computed product of the two numbers. """ return multiply(x=self, y=y)
[docs] @openeo_process def nan(self) -> ProcessBuilder: """ Not a Number (NaN) :return: Returns `NaN`. """ return nan()
[docs] @openeo_process def ndvi(self, nir=UNSET, red=UNSET, target_band=UNSET) -> ProcessBuilder: """ Normalized Difference Vegetation Index :param self: A raster data cube with two bands that have the common names `red` and `nir` assigned. :param nir: The name of the NIR band. Defaults to the band that has the common name `nir` assigned. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. :param red: The name of the red band. Defaults to the band that has the common name `red` assigned. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. :param target_band: By default, the dimension of type `bands` is dropped. To keep the dimension specify a new band name in this parameter so that a new dimension label with the specified name will be added for the computed values. :return: A raster data cube containing the computed NDVI values. The structure of the data cube differs depending on the value passed to `target_band`: * `target_band` is `null`: The data cube does not contain the dimension of type `bands`, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. * `target_band` is a string: The data cube keeps the same dimensions. The dimension properties remain unchanged, but the number of dimension labels for the dimension of type `bands` increases by one. The additional label is named as specified in `target_band`. """ return ndvi(data=self, nir=nir, red=red, target_band=target_band)
[docs] @openeo_process def neq(self, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder: """ Not equal to comparison :param self: First operand. :param y: Second operand. :param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the non-equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation. This option is basically an alias for the following computation: `gt(abs(minus([x, y]), delta)` :param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `x` is *not* equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return neq(x=self, y=y, delta=delta, case_sensitive=case_sensitive)
[docs] @openeo_process def normalized_difference(self, y) -> ProcessBuilder: """ Normalized difference :param self: The value for the first band. :param y: The value for the second band. :return: The computed normalized difference. """ return normalized_difference(x=self, y=y)
[docs] @openeo_process def not_(self) -> ProcessBuilder: """ Inverting a boolean :param self: Boolean value to invert. :return: Inverted boolean value. """ return not_(x=self)
[docs] @openeo_process def or_(self, y) -> ProcessBuilder: """ Logical OR :param self: A boolean value. :param y: A boolean value. :return: Boolean result of the logical OR. """ return or_(x=self, y=y)
[docs] @openeo_process def order(self, asc=UNSET, nodata=UNSET) -> ProcessBuilder: """ Get the order of array elements :param self: An array to compute the order for. :param asc: The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`. :param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first. :return: The computed permutation. """ return order(data=self, asc=asc, nodata=nodata)
[docs] @openeo_process def pi(self) -> ProcessBuilder: """ Pi (π) :return: The numerical value of Pi. """ return pi()
[docs] @openeo_process def power(self, p) -> ProcessBuilder: """ Exponentiation :param self: The numerical base. :param p: The numerical exponent. :return: The computed value for `base` raised to the power of `p`. """ return power(base=self, p=p)
[docs] @openeo_process def predict_curve(self, function, dimension, labels=UNSET) -> ProcessBuilder: """ Predict values :param self: A data cube with optimal values, e.g. computed by the process ``fit_curve()``. :param function: The model function. It must take the parameters to fit as array through the first argument and the independent variable `x` as the second argument. It is recommended to store the model function as a user-defined process on the back-end. :param dimension: The name of the dimension for predictions. :param labels: The labels to predict values for. If no labels are given, predicts values only for no- data (`null`) values in the data cube. :return: A data cube with the predicted values with the provided dimension `dimension` having as many labels as provided through `labels`. """ return predict_curve( parameters=self, function=build_child_callback(function, parent_parameters=['x', 'parameters']), dimension=dimension, labels=labels )
[docs] @openeo_process def predict_random_forest(self, model) -> ProcessBuilder: """ Predict values based on a Random Forest model :param self: An array of numbers. :param model: A model object that can be trained with the processes ``fit_regr_random_forest()`` (regression) and ``fit_class_random_forest()`` (classification). :return: The predicted value. Returns `null` if any of the given values in the array is a no-data value. """ return predict_random_forest(data=self, model=model)
[docs] @openeo_process def product(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Compute the product by multiplying numbers :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed product of the sequence of numbers. """ return product(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def quantiles(self, probabilities=UNSET, q=UNSET, ignore_nodata=UNSET) -> ProcessBuilder: """ Quantiles :param self: An array of numbers. :param probabilities: Quantiles to calculate. Either a list of probabilities or the number of intervals: * Provide an array with a sorted list of probabilities in ascending order to calculate quantiles for. The probabilities must be between 0 and 1 (inclusive). If not sorted in ascending order, an `AscendingProbabilitiesRequired` exception is thrown. * Provide an integer to specify the number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals. :param q: Number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals. This parameter has been **deprecated**. Please use the parameter `probabilities` instead. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with `null` values is returned if any element is such a value. :return: An array with the computed quantiles. The list has either * as many elements as the given list of `probabilities` had or * *`q`-1* elements. If the input array is empty the resulting array is filled with as many `null` values as required according to the list above. See the 'Empty array' example for an example. """ return quantiles(data=self, probabilities=probabilities, q=q, ignore_nodata=ignore_nodata)
[docs] @openeo_process def rearrange(self, order) -> ProcessBuilder: """ Sort an array based on a permutation :param self: The array to rearrange. :param order: The permutation used for rearranging. :return: The rearranged array. """ return rearrange(data=self, order=order)
[docs] @openeo_process def reduce_dimension(self, reducer, dimension, context=UNSET) -> ProcessBuilder: """ Reduce dimensions :param self: A data cube. :param reducer: A reducer to apply on the specified dimension. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A data cube with the newly computed values. It is missing the given dimension, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return reduce_dimension( data=self, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def reduce_spatial(self, reducer, context=UNSET) -> ProcessBuilder: """ Reduce spatial dimensions 'x' and 'y' :param self: A raster data cube. :param reducer: A reducer to apply on the horizontal spatial dimensions. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param context: Additional data to be passed to the reducer. :return: A data cube with the newly computed values. It is missing the horizontal spatial dimensions, the number of dimensions decreases by two. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return reduce_spatial(data=self, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), context=context)
[docs] @openeo_process def rename_dimension(self, source, target) -> ProcessBuilder: """ Rename a dimension :param self: The data cube. :param source: The current name of the dimension. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param target: A new Name for the dimension. Fails with a `DimensionExists` exception if a dimension with the specified name exists. :return: A data cube with the same dimensions, but the name of one of the dimensions changes. The old name can not be referred to any longer. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return rename_dimension(data=self, source=source, target=target)
[docs] @openeo_process def rename_labels(self, dimension, target, source=UNSET) -> ProcessBuilder: """ Rename dimension labels :param self: The data cube. :param dimension: The name of the dimension to rename the labels for. :param target: The new names for the labels. If a target dimension label already exists in the data cube, a `LabelExists` exception is thrown. :param source: The original names of the labels to be renamed to corresponding array elements in the parameter `target`. It is allowed to only specify a subset of labels to rename, as long as the `target` and `source` parameter have the same length. The order of the labels doesn't need to match the order of the dimension labels in the data cube. By default, the array is empty so that the dimension labels in the data cube are expected to be enumerated. If the dimension labels are not enumerated and the given array is empty, the `LabelsNotEnumerated` exception is thrown. If one of the source dimension labels doesn't exist, the `LabelNotAvailable` exception is thrown. :return: The data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that for the given dimension the labels change. The old labels can not be referred to any longer. The number of labels remains the same. """ return rename_labels(data=self, dimension=dimension, target=target, source=source)
[docs] @openeo_process def resample_cube_spatial(self, target, method=UNSET) -> ProcessBuilder: """ Resample the spatial dimensions to match a target data cube :param self: A raster data cube. :param target: A raster data cube that describes the spatial target resolution. :param method: Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``. :return: A raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the spatial dimensions. """ return resample_cube_spatial(data=self, target=target, method=method)
[docs] @openeo_process def resample_cube_temporal(self, target, dimension=UNSET, valid_within=UNSET) -> ProcessBuilder: """ Resample temporal dimensions to match a target data cube :param self: A data cube with one or more temporal dimensions. :param target: A data cube that describes the temporal target resolution. :param dimension: The name of the temporal dimension to resample, which must exist with this name in both data cubes. If the dimension is not set or is set to `null`, the process resamples all temporal dimensions that exist with the same names in both data cubes. The following exceptions may occur: * A dimension is given, but it does not exist in any of the data cubes: `DimensionNotAvailable` * A dimension is given, but one of them is not temporal: `DimensionMismatch` * No specific dimension name is given and there are no temporal dimensions with the same name in the data: `DimensionMismatch` :param valid_within: Setting this parameter to a numerical value enables that the process searches for valid values within the given period of days before and after the target timestamps. Valid values are determined based on the function ``is_valid()``. For example, the limit of `7` for the target timestamps `2020-01-15 12:00:00` looks for a nearest neighbor after `2020-01-08 12:00:00` and before `2020-01-22 12:00:00`. If no valid value is found within the given period, the value will be set to no- data (`null`). :return: A data cube with the same dimensions and the same dimension properties (name, type, labels, reference system and resolution) for all non-temporal dimensions. For the temporal dimension, the name and type remain unchanged, but the dimension labels, resolution and reference system may change. """ return resample_cube_temporal(data=self, target=target, dimension=dimension, valid_within=valid_within)
[docs] @openeo_process def resample_spatial(self, resolution=UNSET, projection=UNSET, method=UNSET, align=UNSET) -> ProcessBuilder: """ Resample and warp the spatial dimensions :param self: A raster data cube. :param resolution: Resamples the data cube to the target resolution, which can be specified either as separate values for x and y or as a single value for both axes. Specified in the units of the target projection. Doesn't change the resolution by default (`0`). :param projection: Warps the data cube to the target projection, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). By default (`null`), the projection is not changed. :param method: Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``. :param align: Specifies to which corner of the spatial extent the new resampled data is aligned to. :return: A raster data cube with values warped onto the new projection. It has the same dimensions and the same dimension properties (name, type, labels, reference system and resolution) for all non-spatial or vertical spatial dimensions. For the horizontal spatial dimensions the name and type remain unchanged, but reference system, labels and resolution may change depending on the given parameters. """ return resample_spatial(data=self, resolution=resolution, projection=projection, method=method, align=align)
[docs] @openeo_process def round(self, p=UNSET) -> ProcessBuilder: """ Round to a specified precision :param self: A number to round. :param p: A positive number specifies the number of digits after the decimal point to round to. A negative number means rounding to a power of ten, so for example *-2* rounds to the nearest hundred. Defaults to *0*. :return: The rounded number. """ return round(x=self, p=p)
[docs] @openeo_process def run_udf(self, udf, runtime, version=UNSET, context=UNSET) -> ProcessBuilder: """ Run a UDF :param self: The data to be passed to the UDF. :param udf: Either source code, an absolute URL or a path to a UDF script. :param runtime: A UDF runtime identifier available at the back-end. :param version: An UDF runtime version. If set to `null`, the default runtime version specified for each runtime is used. :param context: Additional data such as configuration options to be passed to the UDF. :return: The data processed by the UDF. The returned value can be of any data type and is exactly what the UDF code returns. """ return run_udf(data=self, udf=udf, runtime=runtime, version=version, context=context)
[docs] @openeo_process def run_udf_externally(self, url, context=UNSET) -> ProcessBuilder: """ Run an externally hosted UDF container :param self: The data to be passed to the UDF. :param url: Absolute URL to a remote UDF service. :param context: Additional data such as configuration options to be passed to the UDF. :return: The data processed by the UDF. The returned value can in principle be of any data type, but it depends on what is returned by the UDF code. Please see the implemented UDF interface for details. """ return run_udf_externally(data=self, url=url, context=context)
[docs] @openeo_process def sar_backscatter(self, coefficient=UNSET, elevation_model=UNSET, mask=UNSET, contributing_area=UNSET, local_incidence_angle=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET, options=UNSET) -> ProcessBuilder: """ Computes backscatter from SAR input :param self: The source data cube containing SAR input. :param coefficient: Select the radiometric correction coefficient. The following options are available: * `beta0`: radar brightness * `sigma0-ellipsoid`: ground area computed with ellipsoid earth model * `sigma0-terrain`: ground area computed with terrain earth model * `gamma0-ellipsoid`: ground area computed with ellipsoid earth model in sensor line of sight * `gamma0-terrain`: ground area computed with terrain earth model in sensor line of sight (default) * `null`: non-normalized backscatter :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back-end to choose, which will improve portability, but reduce reproducibility. :param mask: If set to `true`, a data mask is added to the bands with the name `mask`. It indicates which values are valid (1), invalid (0) or contain no-data (null). :param contributing_area: If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters. :param local_incidence_angle: If set to `true`, a DEM-based local incidence angle band named `local_incidence_angle` is added. The values are given in degrees. :param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees. :param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise. :param options: Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability. :return: Backscatter values corresponding to the chosen parametrization. The values are given in linear scale. """ return sar_backscatter( data=self, coefficient=coefficient, elevation_model=elevation_model, mask=mask, contributing_area=contributing_area, local_incidence_angle=local_incidence_angle, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal, options=options )
[docs] @openeo_process def save_result(self, format, options=UNSET) -> ProcessBuilder: """ Save processed data :param self: The data to deliver in the given file format. :param format: The file format to use. It must be one of the values that the server reports as supported output file formats, which usually correspond to the short GDAL/OGR codes. This parameter is *case insensitive*. * If the data cube is empty and the file format can't store empty data cubes, a `DataCubeEmpty` exception is thrown. * If the file format is otherwise not suitable for storing the underlying data structure, a `FormatUnsuitable` exception is thrown. :param options: The file format parameters to be used to create the file(s). Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: Always returns `true` as in case of an error an exception is thrown which aborts the execution of the process. """ return save_result(data=self, format=format, options=options)
[docs] @openeo_process def sd(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Standard deviation :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sample standard deviation. """ return sd(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def sgn(self) -> ProcessBuilder: """ Signum :param self: A number. :return: The computed signum value of `x`. """ return sgn(x=self)
[docs] @openeo_process def sin(self) -> ProcessBuilder: """ Sine :param self: An angle in radians. :return: The computed sine of `x`. """ return sin(x=self)
[docs] @openeo_process def sinh(self) -> ProcessBuilder: """ Hyperbolic sine :param self: An angle in radians. :return: The computed hyperbolic sine of `x`. """ return sinh(x=self)
[docs] @openeo_process def sort(self, asc=UNSET, nodata=UNSET) -> ProcessBuilder: """ Sort data :param self: An array with data to sort. :param asc: The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`. :param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first. :return: The sorted array. """ return sort(data=self, asc=asc, nodata=nodata)
[docs] @openeo_process def sqrt(self) -> ProcessBuilder: """ Square root :param self: A number. :return: The computed square root. """ return sqrt(x=self)
[docs] @openeo_process def subtract(self, y) -> ProcessBuilder: """ Subtraction of two numbers :param self: The minuend. :param y: The subtrahend. :return: The computed result. """ return subtract(x=self, y=y)
[docs] @openeo_process def sum(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Compute the sum by adding up numbers :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sum of the sequence of numbers. """ return sum(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def tan(self) -> ProcessBuilder: """ Tangent :param self: An angle in radians. :return: The computed tangent of `x`. """ return tan(x=self)
[docs] @openeo_process def tanh(self) -> ProcessBuilder: """ Hyperbolic tangent :param self: An angle in radians. :return: The computed hyperbolic tangent of `x`. """ return tanh(x=self)
[docs] @openeo_process def text_begins(self, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text begins with another text :param self: Text in which to find something at the beginning. :param pattern: Text to find at the beginning of `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` begins with `pattern`, false` otherwise. """ return text_begins(data=self, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def text_concat(self, separator=UNSET) -> ProcessBuilder: """ Concatenate elements to a single text :param self: A set of elements. Numbers, boolean values and null values get converted to their (lower case) string representation. For example: `1` (integer), `-1.5` (number), `true` / `false` (boolean values) :param separator: A separator to put between each of the individual texts. Defaults to an empty string. :return: A string containing a string representation of all the array elements in the same order, with the separator between each element. """ return text_concat(data=self, separator=separator)
[docs] @openeo_process def text_contains(self, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text contains another text :param self: Text in which to find something in. :param pattern: Text to find in `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` contains the `pattern`, false` otherwise. """ return text_contains(data=self, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def text_ends(self, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text ends with another text :param self: Text in which to find something at the end. :param pattern: Text to find at the end of `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` ends with `pattern`, false` otherwise. """ return text_ends(data=self, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def trim_cube(self) -> ProcessBuilder: """ Remove dimension labels with no-data values :param self: A data cube to trim. :return: A trimmed data cube with the same dimensions. The dimension properties name, type, reference system and resolution remain unchanged. The number of dimension labels may decrease. """ return trim_cube(data=self)
[docs] @openeo_process def unflatten_dimension(self, dimension, target_dimensions, label_separator=UNSET) -> ProcessBuilder: """ Split a single dimensions into multiple dimensions :param self: A data cube that is consistently structured so that operation can execute flawlessly (e.g. the dimension labels need to contain the `label_separator` exactly 1 time for two target dimensions, 2 times for three target dimensions etc.). :param dimension: The name of the dimension to split. :param target_dimensions: The names of the new target dimensions. New dimensions will be created with the given names and type `other` (see ``add_dimension()``). Fails with a `TargetDimensionExists` exception if any of the dimensions exists. The order of the array defines the order in which the dimensions and dimension labels are added to the data cube (see the example in the process description). :param label_separator: The string that will be used as a separator to split the dimension labels. :return: A data cube with the new shape. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return unflatten_dimension(data=self, dimension=dimension, target_dimensions=target_dimensions, label_separator=label_separator)
[docs] @openeo_process def variance(self, ignore_nodata=UNSET) -> ProcessBuilder: """ Variance :param self: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sample variance. """ return variance(data=self, ignore_nodata=ignore_nodata)
[docs] @openeo_process def vector_buffer(self, distance) -> ProcessBuilder: """ Buffer geometries by distance :param self: Geometries to apply the buffer on. Feature properties are preserved. :param distance: The distance of the buffer in meters. A positive distance expands the geometries, resulting in outward buffering (dilation), while a negative distance shrinks the geometries, resulting in inward buffering (erosion). If the unit of the spatial reference system is not meters, a `UnitMismatch` error is thrown. Use ``vector_reproject()`` to convert the geometries to a suitable spatial reference system. :return: Returns a vector data cube with the computed new geometries of which some may be empty. """ return vector_buffer(geometries=self, distance=distance)
[docs] @openeo_process def vector_reproject(self, projection, dimension=UNSET) -> ProcessBuilder: """ Reprojects the geometry dimension :param self: A vector data cube. :param projection: Coordinate reference system to reproject to. Specified as an [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). :param dimension: The name of the geometry dimension to reproject. If no specific dimension is specified, the filter applies to all geometry dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :return: A vector data cube with geometries projected to the new coordinate reference system. The reference system of the geometry dimension changes, all other dimensions and properties remain unchanged. """ return vector_reproject(data=self, projection=projection, dimension=dimension)
[docs] @openeo_process def vector_to_random_points(self, geometry_count=UNSET, total_count=UNSET, group=UNSET, seed=UNSET) -> ProcessBuilder: """ Sample random points from geometries :param self: Input geometries for sample extraction. :param geometry_count: The maximum number of points to compute per geometry. Points in the input geometries can be selected only once by the sampling. :param total_count: The maximum number of points to compute overall. Throws a `CountMismatch` exception if the specified value is less than the provided number of geometries. :param group: Specifies whether the sampled points should be grouped by input geometry (default) or be generated as independent points. * If the sampled points are grouped, the process generates a `MultiPoint` per geometry given which keeps the original identifier if present. * Otherwise, each sampled point is generated as a distinct `Point` geometry without identifier. :param seed: A randomization seed to use for random sampling. If not given or `null`, no seed is used and results may differ on subsequent use. :return: Returns a vector data cube with the sampled points. """ return vector_to_random_points(data=self, geometry_count=geometry_count, total_count=total_count, group=group, seed=seed)
[docs] @openeo_process def vector_to_regular_points(self, distance, group=UNSET) -> ProcessBuilder: """ Sample regular points from geometries :param self: Input geometries for sample extraction. :param distance: Defines the minimum distance in meters that is required between two samples generated *inside* a single geometry. If the unit of the spatial reference system is not meters, a `UnitMismatch` error is thrown. Use ``vector_reproject()`` to convert the geometries to a suitable spatial reference system. - For **polygons**, the distance defines the cell sizes of a regular grid that starts at the upper-left bound of each polygon. The centroid of each cell is then a sample point. If the centroid is not enclosed in the polygon, no point is sampled. If no point can be sampled for the geometry at all, the first coordinate of the geometry is returned as point. - For **lines** (line strings), the sampling starts with a point at the first coordinate of the line and then walks along the line and samples a new point each time the distance to the previous point has been reached again. - For **points**, the point is returned as given. :param group: Specifies whether the sampled points should be grouped by input geometry (default) or be generated as independent points. * If the sampled points are grouped, the process generates a `MultiPoint` per geometry given which keeps the original identifier if present. * Otherwise, each sampled point is generated as a distinct `Point` geometry without identifier. :return: Returns a vector data cube with the sampled points. """ return vector_to_regular_points(data=self, distance=distance, group=group)
[docs] @openeo_process def xor(self, y) -> ProcessBuilder: """ Logical XOR (exclusive or) :param self: A boolean value. :param y: A boolean value. :return: Boolean result of the logical XOR. """ return xor(x=self, y=y)
# Public shortcut process = ProcessBuilder.process # Private shortcut that has lower chance to collide with a process argument named `process` _process = ProcessBuilder.process
[docs] @openeo_process def absolute(x) -> ProcessBuilder: """ Absolute value :param x: A number. :return: The computed absolute value. """ return _process('absolute', x=x)
[docs] @openeo_process def add(x, y) -> ProcessBuilder: """ Addition of two numbers :param x: The first summand. :param y: The second summand. :return: The computed sum of the two numbers. """ return _process('add', x=x, y=y)
[docs] @openeo_process def add_dimension(data, name, label, type=UNSET) -> ProcessBuilder: """ Add a new dimension :param data: A data cube to add the dimension to. :param name: Name for the dimension. :param label: A dimension label. :param type: The type of dimension, defaults to `other`. :return: The data cube with a newly added dimension. The new dimension has exactly one dimension label. All other dimensions remain unchanged. """ return _process('add_dimension', data=data, name=name, label=label, type=type)
[docs] @openeo_process def aggregate_spatial(data, geometries, reducer, target_dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Zonal statistics for geometries :param data: A raster data cube with at least two spatial dimensions. The data cube implicitly gets restricted to the bounds of the geometries as if ``filter_spatial()`` would have been used with the same values for the corresponding parameters immediately before this process. :param geometries: Geometries for which the aggregation will be computed. Feature properties are preserved for vector data cubes and all GeoJSON Features. One value will be computed per label in the dimension of type `geometries`, GeoJSON `Feature` or `Geometry`. For a `FeatureCollection` multiple values will be computed, one value per contained `Feature`. No values will be computed for empty geometries. For example, a single value will be computed for a `MultiPolygon`, but two values will be computed for a `FeatureCollection` containing two polygons. - For **polygons**, the process considers all pixels for which the point at the pixel center intersects with the corresponding polygon (as defined in the Simple Features standard by the OGC). - For **points**, the process considers the closest pixel center. - For **lines** (line strings), the process considers all the pixels whose centers are closest to at least one point on the line. Thus, pixels may be part of multiple geometries and be part of multiple aggregations. No operation is applied to geometries that are outside of the bounds of the data. :param reducer: A reducer to be applied on all values of each geometry. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param target_dimension: By default (which is `null`), the process only computes the results and doesn't add a new dimension. If this parameter contains a new dimension name, the computation also stores information about the total count of pixels (valid + invalid pixels) and the number of valid pixels (see ``is_valid()``) for each computed value. These values are added as a new dimension. The new dimension of type `other` has the dimension labels `value`, `total_count` and `valid_count`. Fails with a `TargetDimensionExists` exception if a dimension with the specified name exists. :param context: Additional data to be passed to the reducer. :return: A vector data cube with the computed results. Empty geometries still exist but without any aggregated values (i.e. no-data). The spatial dimensions are replaced by a dimension of type 'geometries' and if `target_dimension` is not `null`, a new dimension is added. """ return _process('aggregate_spatial', data=data, geometries=geometries, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), target_dimension=target_dimension, context=context )
[docs] @openeo_process def aggregate_spatial_window(data, reducer, size, boundary=UNSET, align=UNSET, context=UNSET) -> ProcessBuilder: """ Zonal statistics for rectangular windows :param data: A raster data cube with exactly two horizontal spatial dimensions and an arbitrary number of additional dimensions. The process is applied to all additional dimensions individually. :param reducer: A reducer to be applied on the list of values, which contain all pixels covered by the window. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param size: Window size in pixels along the horizontal spatial dimensions. The first value corresponds to the `x` axis, the second value corresponds to the `y` axis. :param boundary: Behavior to apply if the number of values for the axes `x` and `y` is not a multiple of the corresponding value in the `size` parameter. Options are: - `pad` (default): pad the data cube with the no-data value `null` to fit the required window size. - `trim`: trim the data cube to fit the required window size. Set the parameter `align` to specifies to which corner the data is aligned to. :param align: If the data requires padding or trimming (see parameter `boundary`), specifies to which corner of the spatial extent the data is aligned to. For example, if the data is aligned to the upper left, the process pads/trims at the lower-right. :param context: Additional data to be passed to the reducer. :return: A raster data cube with the newly computed values and the same dimensions. The resolution will change depending on the chosen values for the `size` and `boundary` parameter. It usually decreases for the dimensions which have the corresponding parameter `size` set to values greater than 1. The dimension labels will be set to the coordinate at the center of the window. The other dimension properties (name, type and reference system) remain unchanged. """ return _process('aggregate_spatial_window', data=data, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), size=size, boundary=boundary, align=align, context=context )
[docs] @openeo_process def aggregate_temporal(data, intervals, reducer, labels=UNSET, dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Temporal aggregations :param data: A data cube. :param intervals: Left-closed temporal intervals, which are allowed to overlap. Each temporal interval in the array has exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element, except when using time without date. Otherwise, a `TemporalExtentEmpty` exception is thrown. :param reducer: A reducer to be applied for the values contained in each interval. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Intervals may not contain any values, which for most reducers leads to no-data (`null`) values by default. :param labels: Distinct labels for the intervals, which can contain dates and/or times. Is only required to be specified if the values for the start of the temporal intervals are not distinct and thus the default labels would not be unique. The number of labels and the number of groups need to be equal. :param dimension: The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension. """ return _process('aggregate_temporal', data=data, intervals=intervals, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), labels=labels, dimension=dimension, context=context )
[docs] @openeo_process def aggregate_temporal_period(data, period, reducer, dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Temporal aggregations based on calendar hierarchies :param data: The source data cube. :param period: The time intervals to aggregate. The following pre-defined values are available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month can range from 8 to 11 days. For example, the third dekad of a year spans from January 21 till January 31 (11 days), the fourth dekad spans from February 1 till February 10 (10 days) and the sixth dekad spans from February 21 till February 28 or February 29 in a leap year (8 or 9 days respectively). * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0 decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD) calendar era, from a year ending in a 1 to the next year ending in a 0. :param reducer: A reducer to be applied for the values contained in each period. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. Periods may not contain any values, which for most reducers leads to no-data (`null`) values by default. :param dimension: The name of the temporal dimension for aggregation. All data along the dimension is passed through the specified reducer. If the dimension is not set or set to `null`, the source data cube is expected to only have one temporal dimension. Fails with a `TooManyDimensions` exception if it has more dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A new data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the given temporal dimension. The specified temporal dimension has the following dimension labels (`YYYY` = four- digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM-DD-00` - `YYYY-MM- DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1` The dimension labels in the new data cube are complete for the whole extent of the source data cube. For example, if `period` is set to `day` and the source data cube has two dimension labels at the beginning of the year (`2020-01-01`) and the end of a year (`2020-12-31`), the process returns a data cube with 365 dimension labels (`2020-001`, `2020-002`, ..., `2020-365`). In contrast, if `period` is set to `day` and the source data cube has just one dimension label `2020-01-05`, the process returns a data cube with just a single dimension label (`2020-005`). """ return _process('aggregate_temporal_period', data=data, period=period, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def all(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Are all of the values true? :param data: A set of boolean values. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. :return: Boolean result of the logical operation. """ return _process('all', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def and_(x, y) -> ProcessBuilder: """ Logical AND :param x: A boolean value. :param y: A boolean value. :return: Boolean result of the logical AND. """ return _process('and', x=x, y=y)
[docs] @openeo_process def anomaly(data, normals, period) -> ProcessBuilder: """ Compute anomalies :param data: A data cube with exactly one temporal dimension and the following dimension labels for the given period (`YYYY` = four-digit year, `MM` = two-digit month, `DD` two-digit day of month): * `hour`: `YYYY-MM-DD-00` - `YYYY-MM-DD-23` * `day`: `YYYY-001` - `YYYY-365` * `week`: `YYYY-01` - `YYYY-52` * `dekad`: `YYYY-00` - `YYYY-36` * `month`: `YYYY-01` - `YYYY-12` * `season`: `YYYY-djf` (December - February), `YYYY-mam` (March - May), `YYYY-jja` (June - August), `YYYY-son` (September - November). * `tropical-season`: `YYYY-ndjfma` (November - April), `YYYY-mjjaso` (May - October). * `year`: `YYYY` * `decade`: `YYY0` * `decade-ad`: `YYY1` * `single-period` / `climatology-period`: Any ``aggregate_temporal_period()`` can compute such a data cube. :param normals: A data cube with normals, e.g. daily, monthly or yearly values computed from a process such as ``climatological_normal()``. Must contain exactly one temporal dimension with the following dimension labels for the given period: * `hour`: `00` - `23` * `day`: `001` - `365` * `week`: `01` - `52` * `dekad`: `00` - `36` * `month`: `01` - `12` * `season`: `djf` (December - February), `mam` (March - May), `jja` (June - August), `son` (September - November) * `tropical-season`: `ndjfma` (November - April), `mjjaso` (May - October) * `year`: Four-digit year numbers * `decade`: Four-digit year numbers, the last digit being a `0` * `decade-ad`: Four-digit year numbers, the last digit being a `1` * `single-period` / `climatology- period`: A single dimension label with any name is expected. :param period: Specifies the time intervals available in the normals data cube. The following options are available: * `hour`: Hour of the day * `day`: Day of the year * `week`: Week of the year * `dekad`: Ten day periods, counted per year with three periods per month (day 1 - 10, 11 - 20 and 21 - end of month). The third dekad of the month can range from 8 to 11 days. For example, the fourth dekad is Feb, 1 - Feb, 10 each year. * `month`: Month of the year * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the tropical seasons (November - April, May - October). * `year`: Proleptic years * `decade`: Ten year periods ([0-to-9 decade](https://en.wikipedia.org/wiki/Decade#0-to-9_decade)), from a year ending in a 0 to the next year ending in a 9. * `decade-ad`: Ten year periods ([1-to-0 decade](https://en.wikipedia.org/wiki/Decade#1-to-0_decade)) better aligned with the anno Domini (AD) calendar era, from a year ending in a 1 to the next year ending in a 0. * `single-period` / `climatology- period`: A single period of arbitrary length :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('anomaly', data=data, normals=normals, period=period)
[docs] @openeo_process def any(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Is at least one value true? :param data: A set of boolean values. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. :return: Boolean result of the logical operation. """ return _process('any', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def apply(data, process, context=UNSET) -> ProcessBuilder: """ Apply a process to each value :param data: A data cube. :param process: A process that accepts and returns a single value and is applied on each individual value in the data cube. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('apply', data=data, process=build_child_callback(process, parent_parameters=['x', 'context']), context=context)
[docs] @openeo_process def apply_dimension(data, process, dimension, target_dimension=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to all values along a dimension :param data: A data cube. :param process: Process to be applied on all values along the given dimension. The specified process needs to accept an array and must return an array with at least one element. A process may consist of multiple sub-processes. :param dimension: The name of the source dimension to apply the process on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param target_dimension: The name of the target dimension or `null` (the default) to use the source dimension specified in the parameter `dimension`. By specifying a target dimension, the source dimension is removed. The target dimension with the specified name and the type `other` (see ``add_dimension()``) is created, if it doesn't exist yet. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values. All dimensions stay the same, except for the dimensions specified in corresponding parameters. There are three cases how the dimensions can change: 1. The source dimension is the target dimension: - The (number of) dimensions remain unchanged as the source dimension is the target dimension. - The source dimension properties name and type remain unchanged. - The dimension labels, the reference system and the resolution are preserved only if the number of values in the source dimension is equal to the number of values computed by the process. Otherwise, all other dimension properties change as defined in the list below. 2. The source dimension is not the target dimension. The target dimension exists with a single label only: - The number of dimensions decreases by one as the source dimension is 'dropped' and the target dimension is filled with the processed data that originates from the source dimension. - The target dimension properties name and type remain unchanged. All other dimension properties change as defined in the list below. 3. The source dimension is not the target dimension and the latter does not exist: - The number of dimensions remain unchanged, but the source dimension is replaced with the target dimension. - The target dimension has the specified name and the type other. All other dimension properties are set as defined in the list below. Unless otherwise stated above, for the given (target) dimension the following applies: - the number of dimension labels is equal to the number of values computed by the process, - the dimension labels are incrementing integers starting from zero, - the resolution changes, and - the reference system is undefined. """ return _process('apply_dimension', data=data, process=build_child_callback(process, parent_parameters=['data', 'context']), dimension=dimension, target_dimension=target_dimension, context=context )
[docs] @openeo_process def apply_kernel(data, kernel, factor=UNSET, border=UNSET, replace_invalid=UNSET) -> ProcessBuilder: """ Apply a spatial convolution with a kernel :param data: A raster data cube. :param kernel: Kernel as a two-dimensional array of weights. The inner level of the nested array aligns with the `x` axis and the outer level aligns with the `y` axis. Each level of the kernel must have an uneven number of elements, otherwise the process throws a `KernelDimensionsUneven` exception. :param factor: A factor that is multiplied to each value after the kernel has been applied. This is basically a shortcut for explicitly multiplying each value by a factor afterwards, which is often required for some kernel-based algorithms such as the Gaussian blur. :param border: Determines how the data is extended when the kernel overlaps with the borders. Defaults to fill the border with zeroes. The following options are available: * *numeric value* - fill with a user- defined constant number `n`: `nnnnnn|abcdefgh|nnnnnn` (default, with `n` = 0) * `replicate` - repeat the value from the pixel at the border: `aaaaaa|abcdefgh|hhhhhh` * `reflect` - mirror/reflect from the border: `fedcba|abcdefgh|hgfedc` * `reflect_pixel` - mirror/reflect from the center of the pixel at the border: `gfedcb|abcdefgh|gfedcb` * `wrap` - repeat/wrap the image: `cdefgh|abcdefgh|abcdef` :param replace_invalid: This parameter specifies the value to replace non-numerical or infinite numerical values with. By default, those values are replaced with zeroes. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('apply_kernel', data=data, kernel=kernel, factor=factor, border=border, replace_invalid=replace_invalid)
[docs] @openeo_process def apply_neighborhood(data, process, size, overlap=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to pixels in a n-dimensional neighborhood :param data: A raster data cube. :param process: Process to be applied on all neighborhoods. :param size: Neighborhood sizes along each dimension. This object maps dimension names to either a physical measure (e.g. 100 m, 10 days) or pixels (e.g. 32 pixels). For dimensions not specified, the default is to provide all values. Be aware that including all values from overly large dimensions may not be processed at once. :param overlap: Overlap of neighborhoods along each dimension to avoid border effects. By default no overlap is provided. For instance a temporal dimension can add 1 month before and after a neighborhood. In the spatial dimensions, this is often a number of pixels. The overlap specified is added before and after, so an overlap of 8 pixels will add 8 pixels on both sides of the window, so 16 in total. Be aware that large overlaps increase the need for computational resources and modifying overlapping data in subsequent operations have no effect. :param context: Additional data to be passed to the process. :return: A raster data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('apply_neighborhood', data=data, process=build_child_callback(process, parent_parameters=['data', 'context']), size=size, overlap=overlap, context=context )
[docs] @openeo_process def apply_polygon(data, polygons, process, mask_value=UNSET, context=UNSET) -> ProcessBuilder: """ Apply a process to segments of the data cube :param data: A data cube. :param polygons: A vector data cube containing at least one polygon. The provided vector data can be one of the following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. :param process: A process that accepts and returns a single data cube and is applied on each individual sub data cube. The process may consist of multiple sub-processes. :param mask_value: All pixels for which the point at the pixel center **does not** intersect with the polygon are replaced with the given value, which defaults to `null` (no data). It can provide a distinction between no data values within the polygon and masked pixels outside of it. :param context: Additional data to be passed to the process. :return: A data cube with the newly computed values and the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('apply_polygon', data=data, polygons=polygons, process=build_child_callback(process, parent_parameters=['data', 'context']), mask_value=mask_value, context=context )
[docs] @openeo_process def arccos(x) -> ProcessBuilder: """ Inverse cosine :param x: A number. :return: The computed angle in radians. """ return _process('arccos', x=x)
[docs] @openeo_process def arcosh(x) -> ProcessBuilder: """ Inverse hyperbolic cosine :param x: A number. :return: The computed angle in radians. """ return _process('arcosh', x=x)
[docs] @openeo_process def arcsin(x) -> ProcessBuilder: """ Inverse sine :param x: A number. :return: The computed angle in radians. """ return _process('arcsin', x=x)
[docs] @openeo_process def arctan(x) -> ProcessBuilder: """ Inverse tangent :param x: A number. :return: The computed angle in radians. """ return _process('arctan', x=x)
[docs] @openeo_process def arctan2(y, x) -> ProcessBuilder: """ Inverse tangent of two numbers :param y: A number to be used as the dividend. :param x: A number to be used as the divisor. :return: The computed angle in radians. """ return _process('arctan2', y=y, x=x)
[docs] @openeo_process def ard_normalized_radar_backscatter(data, elevation_model=UNSET, contributing_area=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET, options=UNSET) -> ProcessBuilder: """ CARD4L compliant SAR NRB generation :param data: The source data cube containing SAR input. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back- end to choose, which will improve portability, but reduce reproducibility. :param contributing_area: If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters. :param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees. :param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise. :param options: Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability. :return: Backscatter values expressed as gamma0 in linear scale. In addition to the bands `contributing_area` and `ellipsoid_incidence_angle` that can optionally be added with corresponding parameters, the following bands are always added to the data cube: - `mask`: A data mask that indicates which values are valid (1), invalid (0) or contain no-data (null). - `local_incidence_angle`: A band with DEM-based local incidence angles in degrees. The data returned is CARD4L compliant with corresponding metadata. """ return _process('ard_normalized_radar_backscatter', data=data, elevation_model=elevation_model, contributing_area=contributing_area, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal, options=options )
[docs] @openeo_process def ard_surface_reflectance(data, atmospheric_correction_method, cloud_detection_method, elevation_model=UNSET, atmospheric_correction_options=UNSET, cloud_detection_options=UNSET) -> ProcessBuilder: """ CARD4L compliant Surface Reflectance generation :param data: The source data cube containing multi-spectral optical top of the atmosphere (TOA) reflectances. There must be a single dimension of type `bands` available. :param atmospheric_correction_method: The atmospheric correction method to use. :param cloud_detection_method: The cloud detection method to use. Each method supports detecting different atmospheric disturbances such as clouds, cloud shadows, aerosols, haze, ozone and/or water vapour in optical imagery. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back- end to choose, which will improve portability, but reduce reproducibility. :param atmospheric_correction_options: Proprietary options for the atmospheric correction method. Specifying proprietary options will reduce portability. :param cloud_detection_options: Proprietary options for the cloud detection method. Specifying proprietary options will reduce portability. :return: Data cube containing bottom of atmosphere reflectances for each spectral band in the source data cube, with atmospheric disturbances like clouds and cloud shadows removed. No-data values (null) are directly set in the bands. Depending on the methods used, several additional bands will be added to the data cube: Data cube containing bottom of atmosphere reflectances for each spectral band in the source data cube, with atmospheric disturbances like clouds and cloud shadows removed. Depending on the methods used, several additional bands will be added to the data cube: - `date` (optional): Specifies per-pixel acquisition timestamps. - `incomplete-testing` (required): Identifies pixels with a value of 1 for which the per-pixel tests (at least saturation, cloud and cloud shadows, see CARD4L specification for details) have not all been successfully completed. Otherwise, the value is 0. - `saturation` (required) / `saturation_{band}` (optional): Indicates where pixels in the input spectral bands are saturated (1) or not (0). If the saturation is given per band, the band names are `saturation_{band}` with `{band}` being the band name from the source data cube. - `cloud`, `shadow` (both required),`aerosol`, `haze`, `ozone`, `water_vapor` (all optional): Indicates the probability of pixels being an atmospheric disturbance such as clouds. All bands have values between 0 (clear) and 1, which describes the probability that it is an atmospheric disturbance. - `snow-ice` (optional): Points to a file that indicates whether a pixel is assessed as being snow/ice (1) or not (0). All values describe the probability and must be between 0 and 1. - `land-water` (optional): Indicates whether a pixel is assessed as being land (1) or water (0). All values describe the probability and must be between 0 and 1. - `incidence-angle` (optional): Specifies per-pixel incidence angles in degrees. - `azimuth` (optional): Specifies per-pixel azimuth angles in degrees. - `sun- azimuth:` (optional): Specifies per-pixel sun azimuth angles in degrees. - `sun-elevation` (optional): Specifies per-pixel sun elevation angles in degrees. - `terrain-shadow` (optional): Indicates with a value of 1 whether a pixel is not directly illuminated due to terrain shadowing. Otherwise, the value is 0. - `terrain-occlusion` (optional): Indicates with a value of 1 whether a pixel is not visible to the sensor due to terrain occlusion during off-nadir viewing. Otherwise, the value is 0. - `terrain-illumination` (optional): Contains coefficients used for terrain illumination correction are provided for each pixel. The data returned is CARD4L compliant with corresponding metadata. """ return _process('ard_surface_reflectance', data=data, atmospheric_correction_method=atmospheric_correction_method, cloud_detection_method=cloud_detection_method, elevation_model=elevation_model, atmospheric_correction_options=atmospheric_correction_options, cloud_detection_options=cloud_detection_options )
[docs] @openeo_process def array_append(data, value, label=UNSET) -> ProcessBuilder: """ Append a value to an array :param data: An array. :param value: Value to append to the array. :param label: If the given array is a labeled array, a new label for the new value should be given. If not given or `null`, the array index as string is used as the label. If in any case the label exists, a `LabelExists` exception is thrown. :return: The new array with the value being appended. """ return _process('array_append', data=data, value=value, label=label)
[docs] @openeo_process def array_apply(data, process, context=UNSET) -> ProcessBuilder: """ Apply a process to each array element :param data: An array. :param process: A process that accepts and returns a single value and is applied on each individual value in the array. The process may consist of multiple sub-processes and could, for example, consist of processes such as ``absolute()`` or ``linear_scale_range()``. :param context: Additional data to be passed to the process. :return: An array with the newly computed values. The number of elements are the same as for the original array. """ return _process('array_apply', data=data, process=build_child_callback(process, parent_parameters=['x', 'index', 'label', 'context']), context=context )
[docs] @openeo_process def array_concat(array1, array2) -> ProcessBuilder: """ Merge two arrays :param array1: The first array. :param array2: The second array. :return: The merged array. """ return _process('array_concat', array1=array1, array2=array2)
[docs] @openeo_process def array_contains(data, value) -> ProcessBuilder: """ Check whether the array contains a given value :param data: List to find the value in. :param value: Value to find in `data`. If the value is `null`, this process returns always `false`. :return: `true` if the list contains the value, false` otherwise. """ return _process('array_contains', data=data, value=value)
[docs] @openeo_process def array_create(data=UNSET, repeat=UNSET) -> ProcessBuilder: """ Create an array :param data: A (native) array to fill the newly created array with. Defaults to an empty array. :param repeat: The number of times the (native) array specified in `data` is repeatedly added after each other to the new array being created. Defaults to `1`. :return: The newly created array. """ return _process('array_create', data=data, repeat=repeat)
[docs] @openeo_process def array_create_labeled(data, labels) -> ProcessBuilder: """ Create a labeled array :param data: An array of values to be used. :param labels: An array of labels to be used. :return: The newly created labeled array. """ return _process('array_create_labeled', data=data, labels=labels)
[docs] @openeo_process def array_element(data, index=UNSET, label=UNSET, return_nodata=UNSET) -> ProcessBuilder: """ Get an element from an array :param data: An array. :param index: The zero-based index of the element to retrieve. :param label: The label of the element to retrieve. Throws an `ArrayNotLabeled` exception, if the given array is not a labeled array and this parameter is set. :param return_nodata: By default this process throws an `ArrayElementNotAvailable` exception if the index or label is invalid. If you want to return `null` instead, set this flag to `true`. :return: The value of the requested element. """ return _process('array_element', data=data, index=index, label=label, return_nodata=return_nodata)
[docs] @openeo_process def array_filter(data, condition, context=UNSET) -> ProcessBuilder: """ Filter an array based on a condition :param data: An array. :param condition: A condition that is evaluated against each value, index and/or label in the array. Only the array elements for which the condition returns `true` are preserved. :param context: Additional data to be passed to the condition. :return: An array filtered by the specified condition. The number of elements are less than or equal compared to the original array. """ return _process('array_filter', data=data, condition=build_child_callback(condition, parent_parameters=['x', 'index', 'label', 'context']), context=context )
[docs] @openeo_process def array_find(data, value, reverse=UNSET) -> ProcessBuilder: """ Get the index for a value in an array :param data: List to find the value in. :param value: Value to find in `data`. If the value is `null`, this process returns always `null`. :param reverse: By default, this process finds the index of the first match. To return the index of the last match instead, set this flag to `true`. :return: The index of the first element with the specified value. If no element was found, `null` is returned. """ return _process('array_find', data=data, value=value, reverse=reverse)
[docs] @openeo_process def array_find_label(data, label) -> ProcessBuilder: """ Get the index for a label in a labeled array :param data: List to find the label in. :param label: Label to find in `data`. :return: The index of the element with the specified label assigned. If no such label was found, `null` is returned. """ return _process('array_find_label', data=data, label=label)
[docs] @openeo_process def array_interpolate_linear(data) -> ProcessBuilder: """ One-dimensional linear interpolation for arrays :param data: An array of numbers and no-data values. If the given array is a labeled array, the labels must have a natural/inherent label order and the process expects the labels to be sorted accordingly. This is the default behavior in openEO for spatial and temporal dimensions. :return: An array with no-data values being replaced with interpolated values. If not at least 2 numerical values are available in the array, the array stays the same. """ return _process('array_interpolate_linear', data=data)
[docs] @openeo_process def array_labels(data) -> ProcessBuilder: """ Get the labels for an array :param data: An array. :return: The labels or indices as array. """ return _process('array_labels', data=data)
[docs] @openeo_process def array_modify(data, values, index, length=UNSET) -> ProcessBuilder: """ Change the content of an array (remove, insert, update) :param data: The array to modify. :param values: The values to insert into the `data` array. :param index: The index in the `data` array of the element to insert the value(s) before. If the index is greater than the number of elements in the `data` array, the process throws an `ArrayElementNotAvailable` exception. To insert after the last element, there are two options: 1. Use the simpler processes ``array_append()`` to append a single value or ``array_concat()`` to append multiple values. 2. Specify the number of elements in the array. You can retrieve the number of elements with the process ``count()``, having the parameter `condition` set to `true`. :param length: The number of elements in the `data` array to remove (or replace) starting from the given index. If the array contains fewer elements, the process simply removes all elements up to the end. :return: An array with values added, updated or removed. """ return _process('array_modify', data=data, values=values, index=index, length=length)
[docs] @openeo_process def arsinh(x) -> ProcessBuilder: """ Inverse hyperbolic sine :param x: A number. :return: The computed angle in radians. """ return _process('arsinh', x=x)
[docs] @openeo_process def artanh(x) -> ProcessBuilder: """ Inverse hyperbolic tangent :param x: A number. :return: The computed angle in radians. """ return _process('artanh', x=x)
[docs] @openeo_process def atmospheric_correction(data, method, elevation_model=UNSET, options=UNSET) -> ProcessBuilder: """ Apply atmospheric correction :param data: Data cube containing multi-spectral optical top of atmosphere reflectances to be corrected. :param method: The atmospheric correction method to use. To get reproducible results, you have to set a specific method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce reproducibility as you *may* get different results if you run the processes multiple times. :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back- end to choose, which will improve portability, but reduce reproducibility. :param options: Proprietary options for the atmospheric correction method. Specifying proprietary options will reduce portability. :return: Data cube containing bottom of atmosphere reflectances. """ return _process('atmospheric_correction', data=data, method=method, elevation_model=elevation_model, options=options)
[docs] @openeo_process def between(x, min, max, exclude_max=UNSET) -> ProcessBuilder: """ Between comparison :param x: The value to check. :param min: Lower boundary (inclusive) to check against. :param max: Upper boundary (inclusive) to check against. :param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`. :return: `true` if `x` is between the specified bounds, otherwise `false`. """ return _process('between', x=x, min=min, max=max, exclude_max=exclude_max)
[docs] @openeo_process def ceil(x) -> ProcessBuilder: """ Round fractions up :param x: A number to round up. :return: The number rounded up. """ return _process('ceil', x=x)
[docs] @openeo_process def climatological_normal(data, period, climatology_period=UNSET) -> ProcessBuilder: """ Compute climatology normals :param data: A data cube with exactly one temporal dimension. The data cube must span at least the temporal interval specified in the parameter `climatology-period`. Seasonal periods may span two consecutive years, e.g. temporal winter that includes months December, January and February. If the required months before the actual climate period are available, the season is taken into account. If not available, the first season is not taken into account and the seasonal mean is based on one year less than the other seasonal normals. The incomplete season at the end of the last year is never taken into account. :param period: The time intervals to aggregate the average value for. The following pre-defined frequencies are supported: * `day`: Day of the year * `month`: Month of the year * `climatology-period`: The period specified in the `climatology-period`. * `season`: Three month periods of the calendar seasons (December - February, March - May, June - August, September - November). * `tropical-season`: Six month periods of the tropical seasons (November - April, May - October). :param climatology_period: The climatology period as a closed temporal interval. The first element of the array is the first year to be fully included in the temporal interval. The second element is the last year to be fully included in the temporal interval. The default climatology period is from 1981 until 2010 (both inclusive) right now, but this might be updated over time to what is commonly used in climatology. If you don't want to keep your research to be reproducible, please explicitly specify a period. :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the temporal dimension. The temporal dimension has the following dimension labels: * `day`: `001` - `365` * `month`: `01` - `12` * `climatology-period`: `climatology-period` * `season`: `djf` (December - February), `mam` (March - May), `jja` (June - August), `son` (September - November) * `tropical-season`: `ndjfma` (November - April), `mjjaso` (May - October) """ return _process('climatological_normal', data=data, period=period, climatology_period=climatology_period)
[docs] @openeo_process def clip(x, min, max) -> ProcessBuilder: """ Clip a value between a minimum and a maximum :param x: A number. :param min: Minimum value. If the value is lower than this value, the process will return the value of this parameter. :param max: Maximum value. If the value is greater than this value, the process will return the value of this parameter. :return: The value clipped to the specified range. """ return _process('clip', x=x, min=min, max=max)
[docs] @openeo_process def cloud_detection(data, method, options=UNSET) -> ProcessBuilder: """ Create cloud masks :param data: The source data cube containing multi-spectral optical top of the atmosphere (TOA) reflectances on which to perform cloud detection. :param method: The cloud detection method to use. To get reproducible results, you have to set a specific method. Set to `null` to allow the back-end to choose, which will improve portability, but reduce reproducibility as you *may* get different results if you run the processes multiple times. :param options: Proprietary options for the cloud detection method. Specifying proprietary options will reduce portability. :return: A data cube with bands for the atmospheric disturbances. Each of the masks contains values between 0 and 1. The data cube has the same spatial and temporal dimensions as the source data cube and a dimension that contains a dimension label for each of the supported/considered atmospheric disturbance. """ return _process('cloud_detection', data=data, method=method, options=options)
[docs] @openeo_process def constant(x) -> ProcessBuilder: """ Define a constant value :param x: The value of the constant. :return: The value of the constant. """ return _process('constant', x=x)
[docs] @openeo_process def cos(x) -> ProcessBuilder: """ Cosine :param x: An angle in radians. :return: The computed cosine of `x`. """ return _process('cos', x=x)
[docs] @openeo_process def cosh(x) -> ProcessBuilder: """ Hyperbolic cosine :param x: An angle in radians. :return: The computed hyperbolic cosine of `x`. """ return _process('cosh', x=x)
[docs] @openeo_process def count(data, condition=UNSET, context=UNSET) -> ProcessBuilder: """ Count the number of elements :param data: An array with elements of any data type. :param condition: A condition consists of one or more processes, which in the end return a boolean value. It is evaluated against each element in the array. An element is counted only if the condition returns `true`. Defaults to count valid elements in a list (see ``is_valid()``). Setting this parameter to boolean `true` counts all elements in the list. `false` is not a valid value for this parameter. :param context: Additional data to be passed to the condition. :return: The counted number of elements. """ return _process('count', data=data, condition=condition, context=context)
[docs] @openeo_process def create_data_cube() -> ProcessBuilder: """ Create an empty data cube :return: An empty data cube with no dimensions. """ return _process('create_data_cube', )
[docs] @openeo_process def cummax(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative maxima :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative maxima. """ return _process('cummax', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cummin(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative minima :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative minima. """ return _process('cummin', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cumproduct(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative products :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative products. """ return _process('cumproduct', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def cumsum(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Cumulative sums :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not and ignores them by default. Setting this flag to `false` considers no-data values so that `null` is set for all the following elements. :return: An array with the computed cumulative sums. """ return _process('cumsum', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def date_between(x, min, max, exclude_max=UNSET) -> ProcessBuilder: """ Between comparison for dates and times :param x: The value to check. :param min: Lower boundary (inclusive) to check against. :param max: Upper boundary (inclusive) to check against. :param exclude_max: Exclude the upper boundary `max` if set to `true`. Defaults to `false`. :return: `true` if `x` is between the specified bounds, otherwise `false`. """ return _process('date_between', x=x, min=min, max=max, exclude_max=exclude_max)
[docs] @openeo_process def date_difference(date1, date2, unit=UNSET) -> ProcessBuilder: """ Computes the difference between two time instants :param date1: The base date, optionally with a time component. :param date2: The other date, optionally with a time component. :param unit: The unit for the returned value. The following units are available: - millisecond - second - leap seconds are ignored in computations. - minute - hour - day - month - year :return: Returns the difference between date1 and date2 in the given unit (seconds by default), including a fractional part if required. For comparison purposes this means: - If `date1` < `date2`, the returned value is positive. - If `date1` = `date2`, the returned value is 0. - If `date1` > `date2`, the returned value is negative. """ return _process('date_difference', date1=date1, date2=date2, unit=unit)
[docs] @openeo_process def date_shift(date, value, unit) -> ProcessBuilder: """ Manipulates dates and times by addition or subtraction :param date: The date (and optionally time) to manipulate. If the given date doesn't include the time, the process assumes that the time component is `00:00:00Z` (i.e. midnight, in UTC). The millisecond part of the time is optional and defaults to `0` if not given. :param value: The period of time in the unit given that is added (positive numbers) or subtracted (negative numbers). The value `0` doesn't have any effect. :param unit: The unit for the value given. The following pre-defined units are available: - millisecond: Milliseconds - second: Seconds - leap seconds are ignored in computations. - minute: Minutes - hour: Hours - day: Days - changes only the the day part of a date - week: Weeks (equivalent to 7 days) - month: Months - year: Years Manipulations with the unit `year`, `month`, `week` or `day` do never change the time. If any of the manipulations result in an invalid date or time, the corresponding part is rounded down to the next valid date or time respectively. For example, adding a month to `2020-01-31` would result in `2020-02-29`. :return: The manipulated date. If a time component was given in the parameter `date`, the time component is returned with the date. """ return _process('date_shift', date=date, value=value, unit=unit)
[docs] @openeo_process def dimension_labels(data, dimension) -> ProcessBuilder: """ Get the dimension labels :param data: The data cube. :param dimension: The name of the dimension to get the labels for. :return: The labels as an array. """ return _process('dimension_labels', data=data, dimension=dimension)
[docs] @openeo_process def divide(x, y) -> ProcessBuilder: """ Division of two numbers :param x: The dividend. :param y: The divisor. :return: The computed result. """ return _process('divide', x=x, y=y)
[docs] @openeo_process def drop_dimension(data, name) -> ProcessBuilder: """ Remove a dimension :param data: The data cube to drop a dimension from. :param name: Name of the dimension to drop. :return: A data cube without the specified dimension. The number of dimensions decreases by one, but the dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return _process('drop_dimension', data=data, name=name)
[docs] @openeo_process def e() -> ProcessBuilder: """ Euler's number (e) :return: The numerical value of Euler's number. """ return _process('e', )
[docs] @openeo_process def eq(x, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder: """ Equal to comparison :param x: First operand. :param y: Second operand. :param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation. This option is basically an alias for the following computation: `lte(abs(minus([x, y]), delta)` :param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `x` is equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return _process('eq', x=x, y=y, delta=delta, case_sensitive=case_sensitive)
[docs] @openeo_process def exp(p) -> ProcessBuilder: """ Exponentiation to the base e :param p: The numerical exponent. :return: The computed value for *e* raised to the power of `p`. """ return _process('exp', p=p)
[docs] @openeo_process def extrema(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Minimum and maximum values :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with two `null` values is returned if any value is such a value. :return: An array containing the minimum and maximum values for the specified numbers. The first element is the minimum, the second element is the maximum. If the input array is empty both elements are set to `null`. """ return _process('extrema', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def filter_bands(data, bands=UNSET, wavelengths=UNSET) -> ProcessBuilder: """ Filter the bands by names :param data: A data cube with bands. :param bands: A list of band names. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands). If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. :param wavelengths: A list of sub-lists with each sub-list consisting of two elements. The first element is the minimum wavelength and the second element is the maximum wavelength. Wavelengths are specified in micrometers (μm). The order of the specified array defines the order of the bands in the data cube. If multiple bands match the wavelengths, all matched bands are included in the original order. :return: A data cube limited to a subset of its original bands. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the dimension of type `bands` has less (or the same) dimension labels. """ return _process('filter_bands', data=data, bands=bands, wavelengths=wavelengths)
[docs] @openeo_process def filter_bbox(data, extent) -> ProcessBuilder: """ Spatial filter using a bounding box :param data: A data cube. :param extent: A bounding box, which may include a vertical axis (see `base` and `height`). :return: A data cube restricted to the bounding box. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels. """ return _process('filter_bbox', data=data, extent=extent)
[docs] @openeo_process def filter_labels(data, condition, dimension, context=UNSET) -> ProcessBuilder: """ Filter dimension labels based on a condition :param data: A data cube. :param condition: A condition that is evaluated against each dimension label in the specified dimension. A dimension label and the corresponding data is preserved for the given dimension, if the condition returns `true`. :param dimension: The name of the dimension to filter on. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the condition. :return: A data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the given dimension has less (or the same) dimension labels. """ return _process('filter_labels', data=data, condition=build_child_callback(condition, parent_parameters=['value', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def filter_spatial(data, geometries) -> ProcessBuilder: """ Spatial filter raster data cubes using geometries :param data: A raster data cube. :param geometries: One or more geometries used for filtering, given as GeoJSON or vector data cube. If multiple geometries are provided, the union of them is used. Empty geometries are ignored. Limits the data cube to the bounding box of the given geometries. No implicit masking gets applied. To mask the pixels of the data cube use ``mask_polygon()``. :return: A raster data cube restricted to the specified geometries. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the spatial dimensions have less (or the same) dimension labels. """ return _process('filter_spatial', data=data, geometries=geometries)
[docs] @openeo_process def filter_temporal(data, extent, dimension=UNSET) -> ProcessBuilder: """ Temporal filter based on temporal intervals :param data: A data cube. :param extent: Left-closed temporal interval, i.e. an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports unbounded intervals by setting one of the boundaries to `null`, but never both. :param dimension: The name of the temporal dimension to filter on. If no specific dimension is specified, the filter applies to all temporal dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :return: A data cube restricted to the specified temporal extent. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the temporal dimensions (determined by `dimensions` parameter) may have less dimension labels. """ return _process('filter_temporal', data=data, extent=extent, dimension=dimension)
[docs] @openeo_process def filter_vector(data, geometries, relation=UNSET) -> ProcessBuilder: """ Spatial vector filter using geometries :param data: A vector data cube with the candidate geometries. :param geometries: One or more base geometries used for filtering, given as vector data cube. If multiple base geometries are provided, the union of them is used. :param relation: The spatial filter predicate for comparing the geometries provided through (a) `geometries` (base geometries) and (b) `data` (candidate geometries). :return: A vector data cube restricted to the specified geometries. The dimensions and dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that the geometries dimension has less (or the same) dimension labels. """ return _process('filter_vector', data=data, geometries=geometries, relation=relation)
[docs] @openeo_process def first(data, ignore_nodata=UNSET) -> ProcessBuilder: """ First element :param data: An array with elements of any data type. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the first value is such a value. :return: The first element of the input array. """ return _process('first', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def fit_curve(data, parameters, function, ignore_nodata=UNSET) -> ProcessBuilder: """ Curve fitting :param data: A labeled array, the labels correspond to the variable `y` and the values correspond to the variable `x`. :param parameters: Defined the number of parameters for the model function and provides an initial guess for them. At least one parameter is required. :param function: The model function. It must take the parameters to fit as array through the first argument and the independent variable `x` as the second argument. It is recommended to store the model function as a user-defined process on the back-end to be able to re-use the model function with the computed optimal values for the parameters afterwards. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is passed to the model function. :return: An array with the optimal values for the parameters. """ return _process('fit_curve', data=data, parameters=parameters, function=build_child_callback(function, parent_parameters=['x', 'parameters']), ignore_nodata=ignore_nodata )
[docs] @openeo_process def flatten_dimensions(data, dimensions, target_dimension, label_separator=UNSET) -> ProcessBuilder: """ Combine multiple dimensions into a single dimension :param data: A data cube. :param dimensions: The names of the dimension to combine. The order of the array defines the order in which the dimension labels and values are combined (see the example in the process description). Fails with a `DimensionNotAvailable` exception if at least one of the specified dimensions does not exist. :param target_dimension: The name of the new target dimension. A new dimensions will be created with the given names and type `other` (see ``add_dimension()``). Fails with a `TargetDimensionExists` exception if a dimension with the specified name exists. :param label_separator: The string that will be used as a separator for the concatenated dimension labels. To unambiguously revert the dimension labels with the process ``unflatten_dimension()``, the given string must not be contained in any of the dimension labels. :return: A data cube with the new shape. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return _process('flatten_dimensions', data=data, dimensions=dimensions, target_dimension=target_dimension, label_separator=label_separator)
[docs] @openeo_process def floor(x) -> ProcessBuilder: """ Round fractions down :param x: A number to round down. :return: The number rounded down. """ return _process('floor', x=x)
[docs] @openeo_process def gt(x, y) -> ProcessBuilder: """ Greater than comparison :param x: First operand. :param y: Second operand. :return: `true` if `x` is strictly greater than `y` or `null` if any operand is `null`, otherwise `false`. """ return _process('gt', x=x, y=y)
[docs] @openeo_process def gte(x, y) -> ProcessBuilder: """ Greater than or equal to comparison :param x: First operand. :param y: Second operand. :return: `true` if `x` is greater than or equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return _process('gte', x=x, y=y)
[docs] @openeo_process def if_(value, accept, reject=UNSET) -> ProcessBuilder: """ If-Then-Else conditional :param value: A boolean value. :param accept: A value that is returned if the boolean value is `true`. :param reject: A value that is returned if the boolean value is **not** `true`. Defaults to `null`. :return: Either the `accept` or `reject` argument depending on the given boolean value. """ return _process('if', value=value, accept=accept, reject=reject)
[docs] @openeo_process def inspect(data, message=UNSET, code=UNSET, level=UNSET) -> ProcessBuilder: """ Add information to the logs :param data: Data to log. :param message: A message to send in addition to the data. :param code: A label to help identify one or more log entries originating from this process in the list of all log entries. It can help to group or filter log entries and is usually not unique. :param level: The severity level of this message, defaults to `info`. :return: The data as passed to the `data` parameter without any modification. """ return _process('inspect', data=data, message=message, code=code, level=level)
[docs] @openeo_process def int(x) -> ProcessBuilder: """ Integer part of a number :param x: A number. :return: Integer part of the number. """ return _process('int', x=x)
[docs] @openeo_process def is_infinite(x) -> ProcessBuilder: """ Value is an infinite number :param x: The data to check. :return: `true` if the data is an infinite number, otherwise `false`. """ return _process('is_infinite', x=x)
[docs] @openeo_process def is_nan(x) -> ProcessBuilder: """ Value is not a number :param x: The data to check. :return: Returns `true` for `NaN` and all non-numeric data types, otherwise returns `false`. """ return _process('is_nan', x=x)
[docs] @openeo_process def is_nodata(x) -> ProcessBuilder: """ Value is a no-data value :param x: The data to check. :return: `true` if the data is a no-data value, otherwise `false`. """ return _process('is_nodata', x=x)
[docs] @openeo_process def is_valid(x) -> ProcessBuilder: """ Value is valid data :param x: The data to check. :return: `true` if the data is valid, otherwise `false`. """ return _process('is_valid', x=x)
[docs] @openeo_process def last(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Last element :param data: An array with elements of any data type. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if the last value is such a value. :return: The last element of the input array. """ return _process('last', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def linear_scale_range(x, inputMin, inputMax, outputMin=UNSET, outputMax=UNSET) -> ProcessBuilder: """ Linear transformation between two ranges :param x: A number to transform. The number gets clipped to the bounds specified in `inputMin` and `inputMax`. :param inputMin: Minimum value the input can obtain. :param inputMax: Maximum value the input can obtain. :param outputMin: Minimum value of the desired output range. :param outputMax: Maximum value of the desired output range. :return: The transformed number. """ return _process('linear_scale_range', x=x, inputMin=inputMin, inputMax=inputMax, outputMin=outputMin, outputMax=outputMax)
[docs] @openeo_process def ln(x) -> ProcessBuilder: """ Natural logarithm :param x: A number to compute the natural logarithm for. :return: The computed natural logarithm. """ return _process('ln', x=x)
[docs] @openeo_process def load_collection(id, spatial_extent, temporal_extent, bands=UNSET, properties=UNSET) -> ProcessBuilder: """ Load a collection :param id: The collection id. :param spatial_extent: Limits the data to load from the collection to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube if the geometry is fully *within* the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load from the collection to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified time instant is **included** in the interval. 2. The second element is the end of the temporal interval. The specified time instant is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports unbounded intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :param properties: Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against the collection metadata, see the example. :return: A data cube for further processing. The dimensions and dimension properties (name, type, labels, reference system and resolution) correspond to the collection's metadata, but the dimension labels are restricted as specified in the parameters. """ return _process('load_collection', id=id, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
[docs] @openeo_process def load_geojson(data, properties=UNSET) -> ProcessBuilder: """ Converts GeoJSON into a vector data cube :param data: A GeoJSON object to convert into a vector data cube. The GeoJSON type `GeometryCollection` is not supported. Each geometry in the GeoJSON data results in a dimension label in the `geometries` dimension. :param properties: A list of properties from the GeoJSON file to construct an additional dimension from. A new dimension with the name `properties` and type `other` is created if at least one property is provided. Only applies for GeoJSON Features and FeatureCollections. Missing values are generally set to no-data (`null`). Depending on the number of properties provided, the process creates the dimension differently: - Single property with scalar values: A single dimension label with the name of the property and a single value per geometry. - Single property of type array: The dimension labels correspond to the array indices. There are as many values and labels per geometry as there are for the largest array. - Multiple properties with scalar values: The dimension labels correspond to the property names. There are as many values and labels per geometry as there are properties provided here. :return: A vector data cube containing the geometries, either one or two dimensional. """ return _process('load_geojson', data=data, properties=properties)
[docs] @openeo_process def load_ml_model(id) -> ProcessBuilder: """ Load a ML model :param id: The STAC Item to load the machine learning model from. The STAC Item must implement the `ml- model` extension. :return: A machine learning model to be used with machine learning processes such as ``predict_random_forest()``. """ return _process('load_ml_model', id=id)
[docs] @openeo_process def load_result(id, spatial_extent=UNSET, temporal_extent=UNSET, bands=UNSET) -> ProcessBuilder: """ Load batch job results :param id: The id of a batch job with results. :param spatial_extent: Limits the data to load from the batch job result to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube of the geometry is fully within the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load from the batch job result to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval. 2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval. The specified temporal strings follow [RFC 3339](https://www.rfc-editor.org/rfc/rfc3339.html). Also supports open intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :return: A data cube for further processing. """ return _process('load_result', id=id, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands)
[docs] @openeo_process def load_stac(url, spatial_extent=UNSET, temporal_extent=UNSET, bands=UNSET, properties=UNSET) -> ProcessBuilder: """ Loads data from STAC :param url: The URL to a static STAC catalog (STAC Item, STAC Collection, or STAC Catalog) or a specific STAC API Collection that allows to filter items and to download assets. This includes batch job results, which itself are compliant to STAC. For external URLs, authentication details such as API keys or tokens may need to be included in the URL. Batch job results can be specified in two ways: - For Batch job results at the same back-end, a URL pointing to the corresponding batch job results endpoint should be provided. The URL usually ends with `/jobs/{id}/results` and `{id}` is the corresponding batch job ID. - For external results, a signed URL must be provided. Not all back-ends support signed URLs, which are provided as a link with the link relation `canonical` in the batch job result metadata. :param spatial_extent: Limits the data to load to the specified bounding box or polygons. * For raster data, the process loads the pixel into the data cube if the point at the pixel center intersects with the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). * For vector data, the process loads the geometry into the data cube if the geometry is fully within the bounding box or any of the polygons (as defined in the Simple Features standard by the OGC). Empty geometries may only be in the data cube if no spatial extent has been provided. The GeoJSON can be one of the following feature types: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. Set this parameter to `null` to set no limit for the spatial extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_bbox()`` or ``filter_spatial()`` directly after loading unbounded data. :param temporal_extent: Limits the data to load to the specified left-closed temporal interval. Applies to all temporal dimensions. The interval has to be specified as an array with exactly two elements: 1. The first element is the start of the temporal interval. The specified instance in time is **included** in the interval. 2. The second element is the end of the temporal interval. The specified instance in time is **excluded** from the interval. The second element must always be greater/later than the first element. Otherwise, a `TemporalExtentEmpty` exception is thrown. Also supports open intervals by setting one of the boundaries to `null`, but never both. Set this parameter to `null` to set no limit for the temporal extent. Be careful with this when loading large datasets! It is recommended to use this parameter instead of using ``filter_temporal()`` directly after loading unbounded data. :param bands: Only adds the specified bands into the data cube so that bands that don't match the list of band names are not available. Applies to all dimensions of type `bands`. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. The order of the specified array defines the order of the bands in the data cube. If multiple bands match a common name, all matched bands are included in the original order. It is recommended to use this parameter instead of using ``filter_bands()`` directly after loading unbounded data. :param properties: Limits the data by metadata properties to include only data in the data cube which all given conditions return `true` for (AND operation). Specify key-value-pairs with the key being the name of the metadata property, which can be retrieved with the openEO Data Discovery for Collections. The value must be a condition (user-defined process) to be evaluated against a STAC API. This parameter is not supported for static STAC. :return: A data cube for further processing. """ return _process('load_stac', url=url, spatial_extent=spatial_extent, temporal_extent=temporal_extent, bands=bands, properties=properties)
[docs] @openeo_process def load_uploaded_files(paths, format, options=UNSET) -> ProcessBuilder: """ Load files from the user workspace :param paths: The files to read. Folders can't be specified, specify all files instead. An exception is thrown if a file can't be read. :param format: The file format to read from. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*. :param options: The file format parameters to be used to read the files. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: A data cube for further processing. """ return _process('load_uploaded_files', paths=paths, format=format, options=options)
[docs] @openeo_process def load_url(url, format, options=UNSET) -> ProcessBuilder: """ Load data from a URL :param url: The URL to read from. Authentication details such as API keys or tokens may need to be included in the URL. :param format: The file format to use when loading the data. It must be one of the values that the server reports as supported input file formats, which usually correspond to the short GDAL/OGR codes. If the format is not suitable for loading the data, a `FormatUnsuitable` exception will be thrown. This parameter is *case insensitive*. :param options: The file format parameters to use when reading the data. Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: A data cube for further processing. """ return _process('load_url', url=url, format=format, options=options)
[docs] @openeo_process def log(x, base) -> ProcessBuilder: """ Logarithm to a base :param x: A number to compute the logarithm for. :param base: The numerical base. :return: The computed logarithm. """ return _process('log', x=x, base=base)
[docs] @openeo_process def lt(x, y) -> ProcessBuilder: """ Less than comparison :param x: First operand. :param y: Second operand. :return: `true` if `x` is strictly less than `y`, `null` if any operand is `null`, otherwise `false`. """ return _process('lt', x=x, y=y)
[docs] @openeo_process def lte(x, y) -> ProcessBuilder: """ Less than or equal to comparison :param x: First operand. :param y: Second operand. :return: `true` if `x` is less than or equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return _process('lte', x=x, y=y)
[docs] @openeo_process def mask(data, mask, replacement=UNSET) -> ProcessBuilder: """ Apply a raster mask :param data: A raster data cube. :param mask: A mask as a raster data cube. Every pixel in `data` must have a corresponding element in `mask`. :param replacement: The value used to replace masked values with. :return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('mask', data=data, mask=mask, replacement=replacement)
[docs] @openeo_process def mask_polygon(data, mask, replacement=UNSET, inside=UNSET) -> ProcessBuilder: """ Apply a polygon mask :param data: A raster data cube. :param mask: A GeoJSON object or a vector data cube containing at least one polygon. The provided vector data can be one of the following: * A `Polygon` or `MultiPolygon` geometry, * a `Feature` with a `Polygon` or `MultiPolygon` geometry, or * a `FeatureCollection` containing at least one `Feature` with `Polygon` or `MultiPolygon` geometries. * Empty geometries are ignored. :param replacement: The value used to replace masked values with. :param inside: If set to `true` all pixels for which the point at the pixel center **does** intersect with any polygon are replaced. :return: A masked raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('mask_polygon', data=data, mask=mask, replacement=replacement, inside=inside)
[docs] @openeo_process def max(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Maximum value :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The maximum value. """ return _process('max', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def mean(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Arithmetic mean (average) :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed arithmetic mean. """ return _process('mean', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def median(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Statistical median :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed statistical median. """ return _process('median', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def merge_cubes(cube1, cube2, overlap_resolver=UNSET, context=UNSET) -> ProcessBuilder: """ Merge two data cubes :param cube1: The base data cube. :param cube2: The other data cube to be merged with the base data cube. :param overlap_resolver: A reduction operator that resolves the conflict if the data overlaps. The reducer must return a value of the same data type as the input values are. The reduction operator may be a single process such as ``multiply()`` or consist of multiple sub-processes. `null` (the default) can be specified if no overlap resolver is required. :param context: Additional data to be passed to the overlap resolver. :return: The merged data cube. See the process description for details regarding the dimensions and dimension properties (name, type, labels, reference system and resolution). """ return _process('merge_cubes', cube1=cube1, cube2=cube2, overlap_resolver=(build_child_callback(overlap_resolver, parent_parameters=['x', 'y', 'context']) if overlap_resolver not in [None, UNSET] else overlap_resolver), context=context )
[docs] @openeo_process def min(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Minimum value :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The minimum value. """ return _process('min', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def mod(x, y) -> ProcessBuilder: """ Modulo :param x: A number to be used as the dividend. :param y: A number to be used as the divisor. :return: The remainder after division. """ return _process('mod', x=x, y=y)
[docs] @openeo_process def multiply(x, y) -> ProcessBuilder: """ Multiplication of two numbers :param x: The multiplier. :param y: The multiplicand. :return: The computed product of the two numbers. """ return _process('multiply', x=x, y=y)
[docs] @openeo_process def nan() -> ProcessBuilder: """ Not a Number (NaN) :return: Returns `NaN`. """ return _process('nan', )
[docs] @openeo_process def ndvi(data, nir=UNSET, red=UNSET, target_band=UNSET) -> ProcessBuilder: """ Normalized Difference Vegetation Index :param data: A raster data cube with two bands that have the common names `red` and `nir` assigned. :param nir: The name of the NIR band. Defaults to the band that has the common name `nir` assigned. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. :param red: The name of the red band. Defaults to the band that has the common name `red` assigned. Either the unique band name (metadata field `name` in bands) or one of the common band names (metadata field `common_name` in bands) can be specified. If the unique band name and the common name conflict, the unique band name has a higher priority. :param target_band: By default, the dimension of type `bands` is dropped. To keep the dimension specify a new band name in this parameter so that a new dimension label with the specified name will be added for the computed values. :return: A raster data cube containing the computed NDVI values. The structure of the data cube differs depending on the value passed to `target_band`: * `target_band` is `null`: The data cube does not contain the dimension of type `bands`, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. * `target_band` is a string: The data cube keeps the same dimensions. The dimension properties remain unchanged, but the number of dimension labels for the dimension of type `bands` increases by one. The additional label is named as specified in `target_band`. """ return _process('ndvi', data=data, nir=nir, red=red, target_band=target_band)
[docs] @openeo_process def neq(x, y, delta=UNSET, case_sensitive=UNSET) -> ProcessBuilder: """ Not equal to comparison :param x: First operand. :param y: Second operand. :param delta: Only applicable for comparing two numbers. If this optional parameter is set to a positive non-zero number the non-equality of two numbers is checked against a delta value. This is especially useful to circumvent problems with floating-point inaccuracy in machine-based computation. This option is basically an alias for the following computation: `gt(abs(minus([x, y]), delta)` :param case_sensitive: Only applicable for comparing two strings. Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `x` is *not* equal to `y`, `null` if any operand is `null`, otherwise `false`. """ return _process('neq', x=x, y=y, delta=delta, case_sensitive=case_sensitive)
[docs] @openeo_process def normalized_difference(x, y) -> ProcessBuilder: """ Normalized difference :param x: The value for the first band. :param y: The value for the second band. :return: The computed normalized difference. """ return _process('normalized_difference', x=x, y=y)
[docs] @openeo_process def not_(x) -> ProcessBuilder: """ Inverting a boolean :param x: Boolean value to invert. :return: Inverted boolean value. """ return _process('not', x=x)
[docs] @openeo_process def or_(x, y) -> ProcessBuilder: """ Logical OR :param x: A boolean value. :param y: A boolean value. :return: Boolean result of the logical OR. """ return _process('or', x=x, y=y)
[docs] @openeo_process def order(data, asc=UNSET, nodata=UNSET) -> ProcessBuilder: """ Get the order of array elements :param data: An array to compute the order for. :param asc: The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`. :param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first. :return: The computed permutation. """ return _process('order', data=data, asc=asc, nodata=nodata)
[docs] @openeo_process def pi() -> ProcessBuilder: """ Pi (π) :return: The numerical value of Pi. """ return _process('pi', )
[docs] @openeo_process def power(base, p) -> ProcessBuilder: """ Exponentiation :param base: The numerical base. :param p: The numerical exponent. :return: The computed value for `base` raised to the power of `p`. """ return _process('power', base=base, p=p)
[docs] @openeo_process def predict_curve(parameters, function, dimension, labels=UNSET) -> ProcessBuilder: """ Predict values :param parameters: A data cube with optimal values, e.g. computed by the process ``fit_curve()``. :param function: The model function. It must take the parameters to fit as array through the first argument and the independent variable `x` as the second argument. It is recommended to store the model function as a user-defined process on the back-end. :param dimension: The name of the dimension for predictions. :param labels: The labels to predict values for. If no labels are given, predicts values only for no-data (`null`) values in the data cube. :return: A data cube with the predicted values with the provided dimension `dimension` having as many labels as provided through `labels`. """ return _process('predict_curve', parameters=parameters, function=build_child_callback(function, parent_parameters=['x', 'parameters']), dimension=dimension, labels=labels )
[docs] @openeo_process def predict_random_forest(data, model) -> ProcessBuilder: """ Predict values based on a Random Forest model :param data: An array of numbers. :param model: A model object that can be trained with the processes ``fit_regr_random_forest()`` (regression) and ``fit_class_random_forest()`` (classification). :return: The predicted value. Returns `null` if any of the given values in the array is a no-data value. """ return _process('predict_random_forest', data=data, model=model)
[docs] @openeo_process def product(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Compute the product by multiplying numbers :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed product of the sequence of numbers. """ return _process('product', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def quantiles(data, probabilities=UNSET, q=UNSET, ignore_nodata=UNSET) -> ProcessBuilder: """ Quantiles :param data: An array of numbers. :param probabilities: Quantiles to calculate. Either a list of probabilities or the number of intervals: * Provide an array with a sorted list of probabilities in ascending order to calculate quantiles for. The probabilities must be between 0 and 1 (inclusive). If not sorted in ascending order, an `AscendingProbabilitiesRequired` exception is thrown. * Provide an integer to specify the number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals. :param q: Number of intervals to calculate quantiles for. Calculates q-quantiles with equal-sized intervals. This parameter has been **deprecated**. Please use the parameter `probabilities` instead. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that an array with `null` values is returned if any element is such a value. :return: An array with the computed quantiles. The list has either * as many elements as the given list of `probabilities` had or * *`q`-1* elements. If the input array is empty the resulting array is filled with as many `null` values as required according to the list above. See the 'Empty array' example for an example. """ return _process('quantiles', data=data, probabilities=probabilities, q=q, ignore_nodata=ignore_nodata)
[docs] @openeo_process def rearrange(data, order) -> ProcessBuilder: """ Sort an array based on a permutation :param data: The array to rearrange. :param order: The permutation used for rearranging. :return: The rearranged array. """ return _process('rearrange', data=data, order=order)
[docs] @openeo_process def reduce_dimension(data, reducer, dimension, context=UNSET) -> ProcessBuilder: """ Reduce dimensions :param data: A data cube. :param reducer: A reducer to apply on the specified dimension. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param dimension: The name of the dimension over which to reduce. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param context: Additional data to be passed to the reducer. :return: A data cube with the newly computed values. It is missing the given dimension, the number of dimensions decreases by one. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return _process('reduce_dimension', data=data, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), dimension=dimension, context=context )
[docs] @openeo_process def reduce_spatial(data, reducer, context=UNSET) -> ProcessBuilder: """ Reduce spatial dimensions 'x' and 'y' :param data: A raster data cube. :param reducer: A reducer to apply on the horizontal spatial dimensions. A reducer is a single process such as ``mean()`` or a set of processes, which computes a single value for a list of values, see the category 'reducer' for such processes. :param context: Additional data to be passed to the reducer. :return: A data cube with the newly computed values. It is missing the horizontal spatial dimensions, the number of dimensions decreases by two. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return _process('reduce_spatial', data=data, reducer=build_child_callback(reducer, parent_parameters=['data', 'context']), context=context)
[docs] @openeo_process def rename_dimension(data, source, target) -> ProcessBuilder: """ Rename a dimension :param data: The data cube. :param source: The current name of the dimension. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :param target: A new Name for the dimension. Fails with a `DimensionExists` exception if a dimension with the specified name exists. :return: A data cube with the same dimensions, but the name of one of the dimensions changes. The old name can not be referred to any longer. The dimension properties (name, type, labels, reference system and resolution) remain unchanged. """ return _process('rename_dimension', data=data, source=source, target=target)
[docs] @openeo_process def rename_labels(data, dimension, target, source=UNSET) -> ProcessBuilder: """ Rename dimension labels :param data: The data cube. :param dimension: The name of the dimension to rename the labels for. :param target: The new names for the labels. If a target dimension label already exists in the data cube, a `LabelExists` exception is thrown. :param source: The original names of the labels to be renamed to corresponding array elements in the parameter `target`. It is allowed to only specify a subset of labels to rename, as long as the `target` and `source` parameter have the same length. The order of the labels doesn't need to match the order of the dimension labels in the data cube. By default, the array is empty so that the dimension labels in the data cube are expected to be enumerated. If the dimension labels are not enumerated and the given array is empty, the `LabelsNotEnumerated` exception is thrown. If one of the source dimension labels doesn't exist, the `LabelNotAvailable` exception is thrown. :return: The data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except that for the given dimension the labels change. The old labels can not be referred to any longer. The number of labels remains the same. """ return _process('rename_labels', data=data, dimension=dimension, target=target, source=source)
[docs] @openeo_process def resample_cube_spatial(data, target, method=UNSET) -> ProcessBuilder: """ Resample the spatial dimensions to match a target data cube :param data: A raster data cube. :param target: A raster data cube that describes the spatial target resolution. :param method: Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``. :return: A raster data cube with the same dimensions. The dimension properties (name, type, labels, reference system and resolution) remain unchanged, except for the resolution and dimension labels of the spatial dimensions. """ return _process('resample_cube_spatial', data=data, target=target, method=method)
[docs] @openeo_process def resample_cube_temporal(data, target, dimension=UNSET, valid_within=UNSET) -> ProcessBuilder: """ Resample temporal dimensions to match a target data cube :param data: A data cube with one or more temporal dimensions. :param target: A data cube that describes the temporal target resolution. :param dimension: The name of the temporal dimension to resample, which must exist with this name in both data cubes. If the dimension is not set or is set to `null`, the process resamples all temporal dimensions that exist with the same names in both data cubes. The following exceptions may occur: * A dimension is given, but it does not exist in any of the data cubes: `DimensionNotAvailable` * A dimension is given, but one of them is not temporal: `DimensionMismatch` * No specific dimension name is given and there are no temporal dimensions with the same name in the data: `DimensionMismatch` :param valid_within: Setting this parameter to a numerical value enables that the process searches for valid values within the given period of days before and after the target timestamps. Valid values are determined based on the function ``is_valid()``. For example, the limit of `7` for the target timestamps `2020-01-15 12:00:00` looks for a nearest neighbor after `2020-01-08 12:00:00` and before `2020-01-22 12:00:00`. If no valid value is found within the given period, the value will be set to no-data (`null`). :return: A data cube with the same dimensions and the same dimension properties (name, type, labels, reference system and resolution) for all non-temporal dimensions. For the temporal dimension, the name and type remain unchanged, but the dimension labels, resolution and reference system may change. """ return _process('resample_cube_temporal', data=data, target=target, dimension=dimension, valid_within=valid_within)
[docs] @openeo_process def resample_spatial(data, resolution=UNSET, projection=UNSET, method=UNSET, align=UNSET) -> ProcessBuilder: """ Resample and warp the spatial dimensions :param data: A raster data cube. :param resolution: Resamples the data cube to the target resolution, which can be specified either as separate values for x and y or as a single value for both axes. Specified in the units of the target projection. Doesn't change the resolution by default (`0`). :param projection: Warps the data cube to the target projection, specified as as [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). By default (`null`), the projection is not changed. :param method: Resampling method to use. The following options are available and are meant to align with [`gdalwarp`](https://gdal.org/programs/gdalwarp.html#cmdoption-gdalwarp-r): * `average`: average (mean) resampling, computes the weighted average of all valid pixels * `bilinear`: bilinear resampling * `cubic`: cubic resampling * `cubicspline`: cubic spline resampling * `lanczos`: Lanczos windowed sinc resampling * `max`: maximum resampling, selects the maximum value from all valid pixels * `med`: median resampling, selects the median value of all valid pixels * `min`: minimum resampling, selects the minimum value from all valid pixels * `mode`: mode resampling, selects the value which appears most often of all the sampled points * `near`: nearest neighbour resampling (default) * `q1`: first quartile resampling, selects the first quartile value of all valid pixels * `q3`: third quartile resampling, selects the third quartile value of all valid pixels * `rms` root mean square (quadratic mean) of all valid pixels * `sum`: compute the weighted sum of all valid pixels Valid pixels are determined based on the function ``is_valid()``. :param align: Specifies to which corner of the spatial extent the new resampled data is aligned to. :return: A raster data cube with values warped onto the new projection. It has the same dimensions and the same dimension properties (name, type, labels, reference system and resolution) for all non-spatial or vertical spatial dimensions. For the horizontal spatial dimensions the name and type remain unchanged, but reference system, labels and resolution may change depending on the given parameters. """ return _process('resample_spatial', data=data, resolution=resolution, projection=projection, method=method, align=align)
[docs] @openeo_process def round(x, p=UNSET) -> ProcessBuilder: """ Round to a specified precision :param x: A number to round. :param p: A positive number specifies the number of digits after the decimal point to round to. A negative number means rounding to a power of ten, so for example *-2* rounds to the nearest hundred. Defaults to *0*. :return: The rounded number. """ return _process('round', x=x, p=p)
[docs] @openeo_process def run_udf(data, udf, runtime, version=UNSET, context=UNSET) -> ProcessBuilder: """ Run a UDF :param data: The data to be passed to the UDF. :param udf: Either source code, an absolute URL or a path to a UDF script. :param runtime: A UDF runtime identifier available at the back-end. :param version: An UDF runtime version. If set to `null`, the default runtime version specified for each runtime is used. :param context: Additional data such as configuration options to be passed to the UDF. :return: The data processed by the UDF. The returned value can be of any data type and is exactly what the UDF code returns. """ return _process('run_udf', data=data, udf=udf, runtime=runtime, version=version, context=context)
[docs] @openeo_process def run_udf_externally(data, url, context=UNSET) -> ProcessBuilder: """ Run an externally hosted UDF container :param data: The data to be passed to the UDF. :param url: Absolute URL to a remote UDF service. :param context: Additional data such as configuration options to be passed to the UDF. :return: The data processed by the UDF. The returned value can in principle be of any data type, but it depends on what is returned by the UDF code. Please see the implemented UDF interface for details. """ return _process('run_udf_externally', data=data, url=url, context=context)
[docs] @openeo_process def sar_backscatter(data, coefficient=UNSET, elevation_model=UNSET, mask=UNSET, contributing_area=UNSET, local_incidence_angle=UNSET, ellipsoid_incidence_angle=UNSET, noise_removal=UNSET, options=UNSET) -> ProcessBuilder: """ Computes backscatter from SAR input :param data: The source data cube containing SAR input. :param coefficient: Select the radiometric correction coefficient. The following options are available: * `beta0`: radar brightness * `sigma0-ellipsoid`: ground area computed with ellipsoid earth model * `sigma0-terrain`: ground area computed with terrain earth model * `gamma0-ellipsoid`: ground area computed with ellipsoid earth model in sensor line of sight * `gamma0-terrain`: ground area computed with terrain earth model in sensor line of sight (default) * `null`: non-normalized backscatter :param elevation_model: The digital elevation model to use. Set to `null` (the default) to allow the back- end to choose, which will improve portability, but reduce reproducibility. :param mask: If set to `true`, a data mask is added to the bands with the name `mask`. It indicates which values are valid (1), invalid (0) or contain no-data (null). :param contributing_area: If set to `true`, a DEM-based local contributing area band named `contributing_area` is added. The values are given in square meters. :param local_incidence_angle: If set to `true`, a DEM-based local incidence angle band named `local_incidence_angle` is added. The values are given in degrees. :param ellipsoid_incidence_angle: If set to `true`, an ellipsoidal incidence angle band named `ellipsoid_incidence_angle` is added. The values are given in degrees. :param noise_removal: If set to `false`, no noise removal is applied. Defaults to `true`, which removes noise. :param options: Proprietary options for the backscatter computations. Specifying proprietary options will reduce portability. :return: Backscatter values corresponding to the chosen parametrization. The values are given in linear scale. """ return _process('sar_backscatter', data=data, coefficient=coefficient, elevation_model=elevation_model, mask=mask, contributing_area=contributing_area, local_incidence_angle=local_incidence_angle, ellipsoid_incidence_angle=ellipsoid_incidence_angle, noise_removal=noise_removal, options=options )
[docs] @openeo_process def save_result(data, format, options=UNSET) -> ProcessBuilder: """ Save processed data :param data: The data to deliver in the given file format. :param format: The file format to use. It must be one of the values that the server reports as supported output file formats, which usually correspond to the short GDAL/OGR codes. This parameter is *case insensitive*. * If the data cube is empty and the file format can't store empty data cubes, a `DataCubeEmpty` exception is thrown. * If the file format is otherwise not suitable for storing the underlying data structure, a `FormatUnsuitable` exception is thrown. :param options: The file format parameters to be used to create the file(s). Must correspond to the parameters that the server reports as supported parameters for the chosen `format`. The parameter names and valid values usually correspond to the GDAL/OGR format options. :return: Always returns `true` as in case of an error an exception is thrown which aborts the execution of the process. """ return _process('save_result', data=data, format=format, options=options)
[docs] @openeo_process def sd(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Standard deviation :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sample standard deviation. """ return _process('sd', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def sgn(x) -> ProcessBuilder: """ Signum :param x: A number. :return: The computed signum value of `x`. """ return _process('sgn', x=x)
[docs] @openeo_process def sin(x) -> ProcessBuilder: """ Sine :param x: An angle in radians. :return: The computed sine of `x`. """ return _process('sin', x=x)
[docs] @openeo_process def sinh(x) -> ProcessBuilder: """ Hyperbolic sine :param x: An angle in radians. :return: The computed hyperbolic sine of `x`. """ return _process('sinh', x=x)
[docs] @openeo_process def sort(data, asc=UNSET, nodata=UNSET) -> ProcessBuilder: """ Sort data :param data: An array with data to sort. :param asc: The default sort order is ascending, with smallest values first. To sort in reverse (descending) order, set this parameter to `false`. :param nodata: Controls the handling of no-data values (`null`). By default, they are removed. If set to `true`, missing values in the data are put last; if set to `false`, they are put first. :return: The sorted array. """ return _process('sort', data=data, asc=asc, nodata=nodata)
[docs] @openeo_process def sqrt(x) -> ProcessBuilder: """ Square root :param x: A number. :return: The computed square root. """ return _process('sqrt', x=x)
[docs] @openeo_process def subtract(x, y) -> ProcessBuilder: """ Subtraction of two numbers :param x: The minuend. :param y: The subtrahend. :return: The computed result. """ return _process('subtract', x=x, y=y)
[docs] @openeo_process def sum(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Compute the sum by adding up numbers :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sum of the sequence of numbers. """ return _process('sum', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def tan(x) -> ProcessBuilder: """ Tangent :param x: An angle in radians. :return: The computed tangent of `x`. """ return _process('tan', x=x)
[docs] @openeo_process def tanh(x) -> ProcessBuilder: """ Hyperbolic tangent :param x: An angle in radians. :return: The computed hyperbolic tangent of `x`. """ return _process('tanh', x=x)
[docs] @openeo_process def text_begins(data, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text begins with another text :param data: Text in which to find something at the beginning. :param pattern: Text to find at the beginning of `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` begins with `pattern`, false` otherwise. """ return _process('text_begins', data=data, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def text_concat(data, separator=UNSET) -> ProcessBuilder: """ Concatenate elements to a single text :param data: A set of elements. Numbers, boolean values and null values get converted to their (lower case) string representation. For example: `1` (integer), `-1.5` (number), `true` / `false` (boolean values) :param separator: A separator to put between each of the individual texts. Defaults to an empty string. :return: A string containing a string representation of all the array elements in the same order, with the separator between each element. """ return _process('text_concat', data=data, separator=separator)
[docs] @openeo_process def text_contains(data, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text contains another text :param data: Text in which to find something in. :param pattern: Text to find in `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` contains the `pattern`, false` otherwise. """ return _process('text_contains', data=data, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def text_ends(data, pattern, case_sensitive=UNSET) -> ProcessBuilder: """ Text ends with another text :param data: Text in which to find something at the end. :param pattern: Text to find at the end of `data`. Regular expressions are not supported. :param case_sensitive: Case sensitive comparison can be disabled by setting this parameter to `false`. :return: `true` if `data` ends with `pattern`, false` otherwise. """ return _process('text_ends', data=data, pattern=pattern, case_sensitive=case_sensitive)
[docs] @openeo_process def trim_cube(data) -> ProcessBuilder: """ Remove dimension labels with no-data values :param data: A data cube to trim. :return: A trimmed data cube with the same dimensions. The dimension properties name, type, reference system and resolution remain unchanged. The number of dimension labels may decrease. """ return _process('trim_cube', data=data)
[docs] @openeo_process def unflatten_dimension(data, dimension, target_dimensions, label_separator=UNSET) -> ProcessBuilder: """ Split a single dimensions into multiple dimensions :param data: A data cube that is consistently structured so that operation can execute flawlessly (e.g. the dimension labels need to contain the `label_separator` exactly 1 time for two target dimensions, 2 times for three target dimensions etc.). :param dimension: The name of the dimension to split. :param target_dimensions: The names of the new target dimensions. New dimensions will be created with the given names and type `other` (see ``add_dimension()``). Fails with a `TargetDimensionExists` exception if any of the dimensions exists. The order of the array defines the order in which the dimensions and dimension labels are added to the data cube (see the example in the process description). :param label_separator: The string that will be used as a separator to split the dimension labels. :return: A data cube with the new shape. The dimension properties (name, type, labels, reference system and resolution) for all other dimensions remain unchanged. """ return _process('unflatten_dimension', data=data, dimension=dimension, target_dimensions=target_dimensions, label_separator=label_separator)
[docs] @openeo_process def variance(data, ignore_nodata=UNSET) -> ProcessBuilder: """ Variance :param data: An array of numbers. :param ignore_nodata: Indicates whether no-data values are ignored or not. Ignores them by default. Setting this flag to `false` considers no-data values so that `null` is returned if any value is such a value. :return: The computed sample variance. """ return _process('variance', data=data, ignore_nodata=ignore_nodata)
[docs] @openeo_process def vector_buffer(geometries, distance) -> ProcessBuilder: """ Buffer geometries by distance :param geometries: Geometries to apply the buffer on. Feature properties are preserved. :param distance: The distance of the buffer in meters. A positive distance expands the geometries, resulting in outward buffering (dilation), while a negative distance shrinks the geometries, resulting in inward buffering (erosion). If the unit of the spatial reference system is not meters, a `UnitMismatch` error is thrown. Use ``vector_reproject()`` to convert the geometries to a suitable spatial reference system. :return: Returns a vector data cube with the computed new geometries of which some may be empty. """ return _process('vector_buffer', geometries=geometries, distance=distance)
[docs] @openeo_process def vector_reproject(data, projection, dimension=UNSET) -> ProcessBuilder: """ Reprojects the geometry dimension :param data: A vector data cube. :param projection: Coordinate reference system to reproject to. Specified as an [EPSG code](http://www.epsg-registry.org/) or [WKT2 CRS string](http://docs.opengeospatial.org/is/18-010r7/18-010r7.html). :param dimension: The name of the geometry dimension to reproject. If no specific dimension is specified, the filter applies to all geometry dimensions. Fails with a `DimensionNotAvailable` exception if the specified dimension does not exist. :return: A vector data cube with geometries projected to the new coordinate reference system. The reference system of the geometry dimension changes, all other dimensions and properties remain unchanged. """ return _process('vector_reproject', data=data, projection=projection, dimension=dimension)
[docs] @openeo_process def vector_to_random_points(data, geometry_count=UNSET, total_count=UNSET, group=UNSET, seed=UNSET) -> ProcessBuilder: """ Sample random points from geometries :param data: Input geometries for sample extraction. :param geometry_count: The maximum number of points to compute per geometry. Points in the input geometries can be selected only once by the sampling. :param total_count: The maximum number of points to compute overall. Throws a `CountMismatch` exception if the specified value is less than the provided number of geometries. :param group: Specifies whether the sampled points should be grouped by input geometry (default) or be generated as independent points. * If the sampled points are grouped, the process generates a `MultiPoint` per geometry given which keeps the original identifier if present. * Otherwise, each sampled point is generated as a distinct `Point` geometry without identifier. :param seed: A randomization seed to use for random sampling. If not given or `null`, no seed is used and results may differ on subsequent use. :return: Returns a vector data cube with the sampled points. """ return _process('vector_to_random_points', data=data, geometry_count=geometry_count, total_count=total_count, group=group, seed=seed)
[docs] @openeo_process def vector_to_regular_points(data, distance, group=UNSET) -> ProcessBuilder: """ Sample regular points from geometries :param data: Input geometries for sample extraction. :param distance: Defines the minimum distance in meters that is required between two samples generated *inside* a single geometry. If the unit of the spatial reference system is not meters, a `UnitMismatch` error is thrown. Use ``vector_reproject()`` to convert the geometries to a suitable spatial reference system. - For **polygons**, the distance defines the cell sizes of a regular grid that starts at the upper-left bound of each polygon. The centroid of each cell is then a sample point. If the centroid is not enclosed in the polygon, no point is sampled. If no point can be sampled for the geometry at all, the first coordinate of the geometry is returned as point. - For **lines** (line strings), the sampling starts with a point at the first coordinate of the line and then walks along the line and samples a new point each time the distance to the previous point has been reached again. - For **points**, the point is returned as given. :param group: Specifies whether the sampled points should be grouped by input geometry (default) or be generated as independent points. * If the sampled points are grouped, the process generates a `MultiPoint` per geometry given which keeps the original identifier if present. * Otherwise, each sampled point is generated as a distinct `Point` geometry without identifier. :return: Returns a vector data cube with the sampled points. """ return _process('vector_to_regular_points', data=data, distance=distance, group=group)
[docs] @openeo_process def xor(x, y) -> ProcessBuilder: """ Logical XOR (exclusive or) :param x: A boolean value. :param y: A boolean value. :return: Boolean result of the logical XOR. """ return _process('xor', x=x, y=y)