Source code for eolearn.visualization.extra.xarray

This module implements conversion from/to xarray DataArray/Dataset

Copyright (c) 2017-2022 Matej Aleksandrov, Matej Batič, Grega Milčinski, Domagoj Korais, Matic Lubej (Sinergise)
Copyright (c) 2017-2022 Žiga Lukšič, Devis Peressutti, Tomislav Slijepčević, Nejc Vesel, Jovan Višnjić (Sinergise)
Copyright (c) 2017-2022 Anže Zupanc (Sinergise)
Copyright (c) 2017-2019 Blaž Sovdat, Andrej Burja (Sinergise)

This source code is licensed under the MIT license found in the LICENSE
file in the root directory of this source tree.
import re

import numpy as np

    import xarray as xr
except ImportError as exception:
    raise ImportError("This module requires an installation of xarray package") from exception

from sentinelhub import BBox

from eolearn.core import FeatureTypeSet
from eolearn.core.utils.parsing import parse_feature

[docs]def string_to_variable(string, extension=None): """Replaces problematic string characters so that it can be used as xarray variable. :param string: string to be used as python variable name :type string: str :param extension: string to be appended to string :type extension: str :return: valid python variable name :rtype: str """ string = re.sub("[^0-9a-zA-Z_]", "", string) string = re.sub("^[^a-zA-Z_]+", "", string) if extension: string += extension return string
def _get_spatial_coordinates(bbox, data, feature_type): """Returns spatial coordinates (dictionary) for creating xarray DataArray/Dataset Makes sense for data :param bbox: eopatch bbox :type bbox: EOPatch BBox :param data: values for calculating number of coordinates :type data: numpy array :param feature_type: type of the feature :type feature_type: FeatureType :return: spatial coordinates :rtype: dict {'x':, 'y':} """ if not (feature_type.is_spatial() and feature_type.is_raster()): raise ValueError("Data should be raster and have spatial dimension") index_x, index_y = 2, 1 if feature_type.is_timeless(): index_x, index_y = 1, 0 pixel_width = (bbox.max_x - bbox.min_x) / data.shape[index_x] pixel_height = (bbox.max_y - bbox.min_y) / data.shape[index_y] return { "x": np.linspace(bbox.min_x + pixel_width / 2, bbox.max_x - pixel_width / 2, data.shape[index_x]), "y": np.linspace(bbox.max_y - pixel_height / 2, bbox.min_y + pixel_height / 2, data.shape[index_y]), } def _get_temporal_coordinates(timestamps): """Returns temporal-coordinates dictionary for creating xarray DataArray/Dataset :param timestamps: timestamps :type timestamps: EOPatch.timestamp :return: temporal coordinates :rtype: dict {'time': } """ return {"time": timestamps} def _get_depth_coordinates(feature_name, data, names_of_channels=None): """Returns band/channel/dept coordinates for xarray DataArray/Dataset :param feature_name: name of feature of EOPatch :type feature_name: FeatureType :param data: data of EOPatch :type data: numpy.array :param names_of_channels: coordinates for the last (band/dept/chanel) dimension :type names_of_channels: list :return: depth/band coordinates :rtype: dict """ coordinates = {} depth = string_to_variable(feature_name, "_dim") if names_of_channels: coordinates[depth] = names_of_channels elif isinstance(data, np.ndarray): coordinates[depth] = np.arange(data.shape[-1]) return coordinates
[docs]def get_coordinates(eopatch, feature, crs): """Creates coordinates for xarray DataArray :param eopatch: eopatch :type eopatch: EOPatch :param feature: feature of eopatch :type feature: (FeatureType, str) :param crs: convert spatial coordinates to crs :type crs: :return: coordinates for xarray DataArray/Dataset :rtype: dict """ feature_type, feature_name = parse_feature(feature) original_crs = if crs and original_crs != crs: bbox = eopatch.bbox.transform(crs) else: bbox = eopatch.bbox data = eopatch[feature_type][feature_name] timestamps = eopatch.timestamp if feature_type in FeatureTypeSet.RASTER_TYPES_4D: return { **_get_temporal_coordinates(timestamps), **_get_spatial_coordinates(bbox, data, feature_type), **_get_depth_coordinates(data=data, feature_name=feature_name), } if feature_type in FeatureTypeSet.RASTER_TYPES_2D: return {**_get_temporal_coordinates(timestamps), **_get_depth_coordinates(data=data, feature_name=feature_name)} if feature_type in FeatureTypeSet.RASTER_TYPES_3D: return { **_get_spatial_coordinates(bbox, data, feature_type), **_get_depth_coordinates(data=data, feature_name=feature_name), } return _get_depth_coordinates(data=data, feature_name=feature_name)
[docs]def get_dimensions(feature): """Returns list of dimensions for xarray DataArray/Dataset :param feature: eopatch feature :type feature: (FeatureType, str) :return: dimensions for xarray DataArray/Dataset :rtype: list(str) """ feature_type, feature_name = parse_feature(feature) depth = string_to_variable(feature_name, "_dim") if feature_type in FeatureTypeSet.RASTER_TYPES_4D: return ["time", "y", "x", depth] if feature_type in FeatureTypeSet.RASTER_TYPES_2D: return ["time", depth] if feature_type in FeatureTypeSet.RASTER_TYPES_3D: return ["y", "x", depth] return [depth]
[docs]def array_to_dataframe(eopatch, feature, remove_depth=True, crs=None, convert_bool=True): """Converts one feature of eopatch to xarray DataArray :param eopatch: eopatch :type eopatch: EOPatch :param feature: feature of eopatch :type feature: (FeatureType, str) :param remove_depth: removes last dimension if it is one :type remove_depth: bool :param crs: converts dimensions to crs :type crs: sentinelhub.CRS :param convert_bool: If True it will convert boolean dtype into uint8 dtype :type convert_bool: bool :return: dataarray :rtype: xarray DataArray """ feature_type, feature_name = parse_feature(feature) bbox = eopatch.bbox data = eopatch[feature_type][feature_name] if isinstance(data, xr.DataArray): data = data.values dimensions = get_dimensions(feature) coordinates = get_coordinates(eopatch, feature, crs=crs) dataframe = xr.DataArray( data=data, coords=coordinates, dims=dimensions, attrs={"crs": str(, "feature_type": feature_type, "feature_name": feature_name}, name=string_to_variable(feature_name), ) if remove_depth and dataframe.values.shape[-1] == 1: dataframe = dataframe.squeeze() dataframe = dataframe.drop(feature_name + "_dim") if convert_bool and dataframe.dtype == bool: dataframe = dataframe.astype(np.uint8) return dataframe
[docs]def eopatch_to_dataset(eopatch, remove_depth=True): """ Converts eopatch to xarray Dataset :param eopatch: An EOPatch :type eopatch: EOPatch :param remove_depth: removes last dimension if it is one :type remove_depth: bool :return: dataset :rtype: xarray Dataset """ dataset = xr.Dataset() for feature in eopatch.get_feature_list(): if not isinstance(feature, tuple): continue feature_type = feature[0] feature_name = feature[1] if feature_type.is_raster(): dataframe = array_to_dataframe(eopatch, (feature_type, feature_name), remove_depth) dataset[feature_name] = dataframe return dataset
[docs]def get_new_coordinates(data, crs, new_crs): """Returns coordinates for xarray DataArray/Dataset in new crs. :param data: data for converting coordinates for :type data: xarray.DataArray or xarray.Dataset :param crs: old crs :type crs: sentinelhub.CRS :param new_crs: new crs :type new_crs: sentinelhub.CRS :return: new x and y coordinates :rtype: (float, float) """ x_values = data.coords["x"].values y_values = data.coords["y"].values bbox = BBox((x_values[0], y_values[0], x_values[-1], y_values[-1]), crs=crs) bbox = bbox.transform(new_crs) xmin, ymin = bbox.lower_left xmax, ymax = bbox.upper_right new_xs = np.linspace(xmin, xmax, len(x_values)) new_ys = np.linspace(ymin, ymax, len(y_values)) return new_xs, new_ys