mirror of
https://github.com/google/earthengine-api.git
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368 lines
14 KiB
Python
368 lines
14 KiB
Python
#!/usr/bin/env python3
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"""Representation for an Earth Engine ImageCollection."""
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from __future__ import annotations
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from typing import Any, Callable, Dict, Optional, Sequence, Tuple
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from ee import apifunction
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from ee import collection
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from ee import computedobject
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from ee import data
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from ee import ee_exception
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from ee import ee_list
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from ee import ee_types
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from ee import image
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class ImageCollection(collection.Collection):
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"""Representation for an Earth Engine ImageCollection."""
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_initialized = False
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# Tell pytype to not complain about dynamic attributes.
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_HAS_DYNAMIC_ATTRIBUTES = True
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def __init__(self, args: Any):
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"""ImageCollection constructor.
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Args:
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args: ImageCollections can be constructed from the following arguments:
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1) A string: assumed to be the name of a collection,
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2) An array of images, or anything that can be used to construct an
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image.
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3) A single image.
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5) A computed object - reinterpreted as a collection.
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Raises:
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EEException: if passed something other than the above.
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"""
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self.initialize()
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# Wrap single images in an array.
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if isinstance(args, image.Image):
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args = [args]
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if ee_types.isString(args):
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# An ID.
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super().__init__(
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apifunction.ApiFunction.lookup('ImageCollection.load'), {'id': args})
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elif isinstance(args, (list, tuple)):
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# A list of images.
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super().__init__(
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apifunction.ApiFunction.lookup('ImageCollection.fromImages'), {
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'images': [image.Image(i) for i in args]
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})
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elif isinstance(args, ee_list.List):
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# A computed list of images.
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super().__init__(
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apifunction.ApiFunction.lookup('ImageCollection.fromImages'), {
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'images': args
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})
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elif isinstance(args, computedobject.ComputedObject):
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# A custom object to reinterpret as an ImageCollection.
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super().__init__(args.func, args.args, args.varName)
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else:
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raise ee_exception.EEException(
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'Unrecognized argument type to convert to an ImageCollection: %s' %
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args)
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@classmethod
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def initialize(cls) -> None:
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"""Imports API functions to this class."""
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if not cls._initialized:
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super().initialize()
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apifunction.ApiFunction.importApi(
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cls, 'ImageCollection', 'ImageCollection')
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apifunction.ApiFunction.importApi(
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cls, 'reduce', 'ImageCollection')
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cls._initialized = True
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@classmethod
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def reset(cls) -> None:
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"""Removes imported API functions from this class."""
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apifunction.ApiFunction.clearApi(cls)
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cls._initialized = False
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def getMapId(self, vis_params: Optional[Any] = None) -> Dict[str, Any]:
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"""Fetch and return a Map ID.
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This mosaics the collection to a single image and return a map ID suitable
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for building a Google Maps overlay.
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Args:
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vis_params: The visualization parameters.
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Returns:
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A map ID dictionary as described in ee.data.getMapId.
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"""
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mosaic = apifunction.ApiFunction.call_('ImageCollection.mosaic', self)
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return mosaic.getMapId(vis_params)
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# pylint: disable-next=keyword-arg-before-vararg
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def select(
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self, selectors: Any, opt_names: Optional[Any] = None, *args
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) -> ImageCollection:
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"""Select bands from each image in a collection.
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Args:
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selectors: An array of names, regexes or numeric indices specifying
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the bands to select.
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opt_names: An array of strings specifying the new names for the
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selected bands. If supplied, the length must match the number
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of bands selected.
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*args: Selector elements as varargs.
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Returns:
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The image collection with selected bands.
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"""
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return self.map(lambda img: img.select(selectors, opt_names, *args))
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# Disable argument usage check; arguments are accessed using locals().
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# pylint: disable=unused-argument,g-bad-name
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def linkCollection(
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self,
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imageCollection: 'ImageCollection',
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linkedBands: Optional[Sequence[str]] = None,
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linkedProperties: Optional[Sequence[str]] = None,
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matchPropertyName: Optional[str] = None,
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) -> ImageCollection:
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"""Links images in this collection to matching images from imageCollection.
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For each source image in this collection, any specified bands or metadata
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will be added to the source image from the matching image found in
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imageCollection. If bands or metadata are already present, they will be
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overwritten. If matching images are not found, any new or updated bands will
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be fully masked and any new or updated metadata will be null. The output
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footprint will be the same as the source image footprint.
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Matches are determined if a source image and an image in imageCollection
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have a specific equivalent metadata property. If more than one collection
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image would match, the collection image selected is arbitrary. By default,
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images are matched on their 'system:index' metadata property.
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This linking function is a convenience method for adding bands target images
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based on a specified shared metadata property and is intended to support
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linking collections that apply different processing/product generation to
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the same source imagery. For more expressive linking known as 'joining', see
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https://developers.google.com/earth-engine/guides/joins_intro.
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Args:
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imageCollection: The image collection searched to find matches from this
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collection.
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linkedBands: Optional list of band names to add or update from matching
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images.
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linkedProperties: Optional list of metadata properties to add or
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update from matching images.
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matchPropertyName: The metadata property name to use as a match
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criteria. Defaults to "system:index".
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Returns:
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The linked image collection.
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"""
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kwargs = {
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k: v for k, v in locals().items() if k != 'self' and v is not None}
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def _linkCollection(img):
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return apifunction.ApiFunction.apply_(
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'Image.linkCollection', {'input': img, **kwargs})
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return self.map(_linkCollection)
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# pylint: enable=g-bad-name,unused-argument
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def first(self) -> image.Image:
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"""Returns the first entry from a given collection.
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Returns:
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The first entry from the collection.
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"""
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return image.Image(apifunction.ApiFunction.call_('Collection.first', self))
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@staticmethod
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def name() -> str:
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return 'ImageCollection'
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@staticmethod
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def elementType():
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return image.Image
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def getVideoThumbURL(self, params: Optional[Dict[str, Any]] = None) -> str:
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"""Get the URL for an animated video thumbnail of the given collection.
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Note: Videos can only be created when the image visualization
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creates an RGB or RGBA image. This can be done by mapping a visualization
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onto the collection or specifying three bands in the params.
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Args:
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params: Parameters identical to getMapId, plus, optionally:
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dimensions -
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(a number or pair of numbers in format WIDTHxHEIGHT) Max dimensions of
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the thumbnail to render, in pixels. If only one number is passed, it is
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used as the maximum, and the other dimension is computed by proportional
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scaling.
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crs - a CRS string specifying the projection of the output.
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crs_transform - the affine transform to use for the output pixel grid.
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scale - a scale to determine the output pixel grid; ignored if both crs
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and crs_transform are specified.
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region - (E,S,W,N or GeoJSON) Geospatial region of the result. By default,
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the whole image.
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format - (string) The output format (only 'gif' is currently supported).
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framesPerSecond - Animation speed.
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Visualization parameters - ['bands', 'gain', 'bias', 'min', 'max',
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'gamma', 'palette', 'opacity', 'forceRgbOutput'] see Earth Engine
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API for ee.Image.visualize for more information.
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Returns:
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A URL to download a thumbnail of the specified ImageCollection.
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Raises:
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EEException: If the region parameter is not an array or GeoJSON object.
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"""
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return self._getThumbURL(['gif'], params, thumbType='video')
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def getFilmstripThumbURL(self, params: Optional[Any] = None) -> str:
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"""Get the URL for a "filmstrip" thumbnail of the given collection.
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Args:
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params: Parameters identical to getMapId, plus, optionally:
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dimensions -
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(a number or pair of numbers in format WIDTHxHEIGHT) Max dimensions of
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the thumbnail to render, in pixels. If only one number is passed, it is
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used as the maximum, and the other dimension is computed by proportional
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scaling.
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crs - a CRS string specifying the projection of the output.
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crs_transform - the affine transform to use for the output pixel grid.
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scale - a scale to determine the output pixel grid; ignored if both crs
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and crs_transform are specified.
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region - (E,S,W,N or GeoJSON) Geospatial region of the result. By default,
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the whole image.
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format - (string) The output format (e.g., "png", "jpg").
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Visualization parameters - ['bands', 'gain', 'bias', 'min', 'max',
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'gamma', 'palette', 'opacity', 'forceRgbOutput'] see Earth Engine
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API for ee.Image.visualize for more information.
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Returns:
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A URL to download a thumbnail of the specified ImageCollection.
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Raises:
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EEException: If the region parameter is not an array or GeoJSON object.
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"""
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return self._getThumbURL(['png', 'jpg'], params, thumbType='filmstrip')
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def _getThumbURL(
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self,
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valid_formats: Sequence[str],
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# TODO(user): Need to drop the default None and use Dict[str, Any]]
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params: Optional[Any] = None,
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thumbType: Optional[str] = None, # pylint: disable=g-bad-name
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) -> str:
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"""Get the URL for a thumbnail of this collection.
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Args:
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valid_formats: A list of supported formats, the first of which is used as
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a default if no format is supplied in 'params'.
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params: Parameters identical to getMapId, plus, optionally:
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dimensions -
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(a number or pair of numbers in format WIDTHxHEIGHT) Max dimensions of
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the thumbnail to render, in pixels. If only one number is passed, it is
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used as the maximum, and the other dimension is computed by proportional
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scaling.
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crs - a CRS string specifying the projection of the output.
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crs_transform - the affine transform to use for the output pixel grid.
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scale - a scale to determine the output pixel grid; ignored if both crs
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and crs_transform are specified.
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region - (E,S,W,N or GeoJSON) Geospatial region of the result. By default,
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the whole image.
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format - (string) The output format
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thumbType: must be either 'video' or 'filmstrip'.
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Returns:
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A URL to download a thumbnail of the specified ImageCollection.
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Raises:
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EEException: If the region parameter is not an array or GeoJSON object.
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"""
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def map_function(input_image, input_params):
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# pylint: disable=protected-access
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output_image, request = input_image._apply_spatial_transformations(
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input_params)
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output_image, request = output_image._apply_visualization(request)
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# pylint: enable=protected-access
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return output_image, request
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clipped_collection, request = self._apply_preparation_function(
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map_function, params)
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assert params is not None
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request['format'] = params.get('format', valid_formats[0])
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if request['format'] not in valid_formats:
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raise ee_exception.EEException(
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'Invalid format specified for thumbnail. ' + str(params['format']))
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if params and 'framesPerSecond' in params:
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request['framesPerSecond'] = params.get('framesPerSecond')
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request['image'] = clipped_collection
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if params and params.get('dimensions') is not None:
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request['dimensions'] = params.get('dimensions')
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if thumbType not in ['video', 'filmstrip']:
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raise ee_exception.EEException(
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'Invalid thumbType provided to _getThumbURL only \'video\' or '
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'\'filmstrip\' is supported.')
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return data.makeThumbUrl(data.getThumbId(request, thumbType=thumbType))
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def _apply_preparation_function(
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self,
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preparation_function: Callable[[Any, Any], Any],
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params: Dict[str, Any],
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) -> Any:
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"""Applies a preparation function to an ImageCollection.
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Args:
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preparation_function: The preparation function. Takes an image and a
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parameter dict; returns the modified image and a subset of the
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parameter dict, with the parameters it used removed.
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params: The parameters to the preparation function.
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Returns:
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A tuple containing:
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- an ImageCollection that has had many of the parameters applied
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to it
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- any remaining parameters.
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"""
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# The preparation function operates only on a single image and returns a
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# modified parameter set; we need to apply across all the images in this
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# collection via self.map, and also return a modified parameter set, which
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# we can't easily get out of self.map. So we invoke it in two ways: once on
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# a dummy Image to get a modified parameter set, and once via self.map.
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_, remaining_params = preparation_function(self.first(), params)
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if remaining_params == params:
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# Nothing in params affects us; omit the map.
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return self, params
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# Copy params defensively in case it's modified after we return but before
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# the map operation is serialised.
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params = params.copy()
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def apply_params(img):
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prepared_img, _ = preparation_function(img, params)
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return prepared_img
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return self.map(apply_params), remaining_params
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def prepare_for_export(
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self, params: Dict[str, Any]
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) -> Tuple[ImageCollection, Dict[str, Any]]:
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"""Applies all relevant export parameters to an ImageCollection.
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Args:
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params: The export request parameters.
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Returns:
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A tuple containing:
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- an ImageCollection that has had many of the request parameters applied
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to it
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- any remaining parameters.
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"""
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# If the Cloud API is enabled, we can do cleaner handling of the parameters.
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# If it isn't enabled, we have to be bug-for-bug compatible with current
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# behaviour, so we do nothing.
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return self._apply_preparation_function(image.Image.prepare_for_export,
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params)
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