Convert API code snippets from JS to Py (img col reduction)

PiperOrigin-RevId: 565071349

samples/python/apidocs/ee_imagecollection_count.py

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+# Copyright 2023 The Google Earth Engine Community Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START earthengine__apidocs__ee_imagecollection_count]
+# Sentinel-2 image collection for July 2021 intersecting a point of interest.
+# Reflectance, cloud probability, and scene classification bands are selected.
+col = (
+    ee.ImageCollection('COPERNICUS/S2_SR')
+    .filterDate('2021-07-01', '2021-08-01')
+    .filterBounds(ee.Geometry.Point(-122.373, 37.448))
+    .select('B.*|MSK_CLDPRB|SCL')
+)
+
+# Visualization parameters for reflectance RGB.
+vis_refl = {'bands': ['B11', 'B8', 'B3'], 'min': 0, 'max': 4000}
+m = geemap.Map()
+m.set_center(-122.373, 37.448, 9)
+m.add_ee_layer(col, vis_refl, 'Collection reference', False)
+
+# Reduce the collection to a single image using a variety of methods.
+mean = col.mean()
+m.add_ee_layer(mean, vis_refl, 'Mean (B11, B8, B3)')
+
+median = col.median()
+m.add_ee_layer(median, vis_refl, 'Median (B11, B8, B3)')
+
+min = col.min()
+m.add_ee_layer(min, vis_refl, 'Min (B11, B8, B3)')
+
+max = col.max()
+m.add_ee_layer(max, vis_refl, 'Max (B11, B8, B3)')
+
+sum = col.sum()
+m.add_ee_layer(
+    sum, {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 500}, 'Sum (MSK_CLDPRB)'
+)
+
+product = col.product()
+m.add_ee_layer(
+    product,
+    {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 1e10},
+    'Product (MSK_CLDPRB)',
+)
+
+# ee.ImageCollection.mode returns the most common value. If multiple mode
+# values occur, the minimum mode value is returned.
+mode = col.mode()
+m.add_ee_layer(
+    mode, {'bands': ['SCL'], 'min': 1, 'max': 11}, 'Mode (pixel class)'
+)
+
+# ee.ImageCollection.count returns the frequency of valid observations. Here,
+# image pixels are masked based on cloud probability to add valid observation
+# variability to the collection. Note that pixels with no valid observations
+# are masked out of the returned image.
+not_cloud_col = col.map(
+    lambda img: img.updateMask(img.select('MSK_CLDPRB').lte(10))
+)
+count = not_cloud_col.count()
+m.add_ee_layer(count, {'min': 1, 'max': 5}, 'Count (not cloud observations)')
+
+# ee.ImageCollection.mosaic composites images according to their position in
+# the collection (priority is last to first) and pixel mask status, where
+# invalid (mask value 0) pixels are filled by preceding valid (mask value >0)
+# pixels.
+mosaic = not_cloud_col.mosaic()
+m.add_ee_layer(mosaic, vis_refl, 'Mosaic (B11, B8, B3)')
+m
+# [END earthengine__apidocs__ee_imagecollection_count]

samples/python/apidocs/ee_imagecollection_max.py

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+# Copyright 2023 The Google Earth Engine Community Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START earthengine__apidocs__ee_imagecollection_max]
+# Sentinel-2 image collection for July 2021 intersecting a point of interest.
+# Reflectance, cloud probability, and scene classification bands are selected.
+col = (
+    ee.ImageCollection('COPERNICUS/S2_SR')
+    .filterDate('2021-07-01', '2021-08-01')
+    .filterBounds(ee.Geometry.Point(-122.373, 37.448))
+    .select('B.*|MSK_CLDPRB|SCL')
+)
+
+# Visualization parameters for reflectance RGB.
+vis_refl = {'bands': ['B11', 'B8', 'B3'], 'min': 0, 'max': 4000}
+m = geemap.Map()
+m.set_center(-122.373, 37.448, 9)
+m.add_ee_layer(col, vis_refl, 'Collection reference', False)
+
+# Reduce the collection to a single image using a variety of methods.
+mean = col.mean()
+m.add_ee_layer(mean, vis_refl, 'Mean (B11, B8, B3)')
+
+median = col.median()
+m.add_ee_layer(median, vis_refl, 'Median (B11, B8, B3)')
+
+min = col.min()
+m.add_ee_layer(min, vis_refl, 'Min (B11, B8, B3)')
+
+max = col.max()
+m.add_ee_layer(max, vis_refl, 'Max (B11, B8, B3)')
+
+sum = col.sum()
+m.add_ee_layer(
+    sum, {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 500}, 'Sum (MSK_CLDPRB)'
+)
+
+product = col.product()
+m.add_ee_layer(
+    product,
+    {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 1e10},
+    'Product (MSK_CLDPRB)',
+)
+
+# ee.ImageCollection.mode returns the most common value. If multiple mode
+# values occur, the minimum mode value is returned.
+mode = col.mode()
+m.add_ee_layer(
+    mode, {'bands': ['SCL'], 'min': 1, 'max': 11}, 'Mode (pixel class)'
+)
+
+# ee.ImageCollection.count returns the frequency of valid observations. Here,
+# image pixels are masked based on cloud probability to add valid observation
+# variability to the collection. Note that pixels with no valid observations
+# are masked out of the returned image.
+not_cloud_col = col.map(
+    lambda img: img.updateMask(img.select('MSK_CLDPRB').lte(10))
+)
+count = not_cloud_col.count()
+m.add_ee_layer(count, {'min': 1, 'max': 5}, 'Count (not cloud observations)')
+
+# ee.ImageCollection.mosaic composites images according to their position in
+# the collection (priority is last to first) and pixel mask status, where
+# invalid (mask value 0) pixels are filled by preceding valid (mask value >0)
+# pixels.
+mosaic = not_cloud_col.mosaic()
+m.add_ee_layer(mosaic, vis_refl, 'Mosaic (B11, B8, B3)')
+m
+# [END earthengine__apidocs__ee_imagecollection_max]

samples/python/apidocs/ee_imagecollection_mean.py

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+# Copyright 2023 The Google Earth Engine Community Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START earthengine__apidocs__ee_imagecollection_mean]
+# Sentinel-2 image collection for July 2021 intersecting a point of interest.
+# Reflectance, cloud probability, and scene classification bands are selected.
+col = (
+    ee.ImageCollection('COPERNICUS/S2_SR')
+    .filterDate('2021-07-01', '2021-08-01')
+    .filterBounds(ee.Geometry.Point(-122.373, 37.448))
+    .select('B.*|MSK_CLDPRB|SCL')
+)
+
+# Visualization parameters for reflectance RGB.
+vis_refl = {'bands': ['B11', 'B8', 'B3'], 'min': 0, 'max': 4000}
+m = geemap.Map()
+m.set_center(-122.373, 37.448, 9)
+m.add_ee_layer(col, vis_refl, 'Collection reference', False)
+
+# Reduce the collection to a single image using a variety of methods.
+mean = col.mean()
+m.add_ee_layer(mean, vis_refl, 'Mean (B11, B8, B3)')
+
+median = col.median()
+m.add_ee_layer(median, vis_refl, 'Median (B11, B8, B3)')
+
+min = col.min()
+m.add_ee_layer(min, vis_refl, 'Min (B11, B8, B3)')
+
+max = col.max()
+m.add_ee_layer(max, vis_refl, 'Max (B11, B8, B3)')
+
+sum = col.sum()
+m.add_ee_layer(
+    sum, {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 500}, 'Sum (MSK_CLDPRB)'
+)
+
+product = col.product()
+m.add_ee_layer(
+    product,
+    {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 1e10},
+    'Product (MSK_CLDPRB)',
+)
+
+# ee.ImageCollection.mode returns the most common value. If multiple mode
+# values occur, the minimum mode value is returned.
+mode = col.mode()
+m.add_ee_layer(
+    mode, {'bands': ['SCL'], 'min': 1, 'max': 11}, 'Mode (pixel class)'
+)
+
+# ee.ImageCollection.count returns the frequency of valid observations. Here,
+# image pixels are masked based on cloud probability to add valid observation
+# variability to the collection. Note that pixels with no valid observations
+# are masked out of the returned image.
+not_cloud_col = col.map(
+    lambda img: img.updateMask(img.select('MSK_CLDPRB').lte(10))
+)
+count = not_cloud_col.count()
+m.add_ee_layer(count, {'min': 1, 'max': 5}, 'Count (not cloud observations)')
+
+# ee.ImageCollection.mosaic composites images according to their position in
+# the collection (priority is last to first) and pixel mask status, where
+# invalid (mask value 0) pixels are filled by preceding valid (mask value >0)
+# pixels.
+mosaic = not_cloud_col.mosaic()
+m.add_ee_layer(mosaic, vis_refl, 'Mosaic (B11, B8, B3)')
+m
+# [END earthengine__apidocs__ee_imagecollection_mean]

samples/python/apidocs/ee_imagecollection_median.py

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+# Copyright 2023 The Google Earth Engine Community Authors
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    https://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# [START earthengine__apidocs__ee_imagecollection_median]
+# Sentinel-2 image collection for July 2021 intersecting a point of interest.
+# Reflectance, cloud probability, and scene classification bands are selected.
+col = (
+    ee.ImageCollection('COPERNICUS/S2_SR')
+    .filterDate('2021-07-01', '2021-08-01')
+    .filterBounds(ee.Geometry.Point(-122.373, 37.448))
+    .select('B.*|MSK_CLDPRB|SCL')
+)
+
+# Visualization parameters for reflectance RGB.
+vis_refl = {'bands': ['B11', 'B8', 'B3'], 'min': 0, 'max': 4000}
+m = geemap.Map()
+m.set_center(-122.373, 37.448, 9)
+m.add_ee_layer(col, vis_refl, 'Collection reference', False)
+
+# Reduce the collection to a single image using a variety of methods.
+mean = col.mean()
+m.add_ee_layer(mean, vis_refl, 'Mean (B11, B8, B3)')
+
+median = col.median()
+m.add_ee_layer(median, vis_refl, 'Median (B11, B8, B3)')
+
+min = col.min()
+m.add_ee_layer(min, vis_refl, 'Min (B11, B8, B3)')
+
+max = col.max()
+m.add_ee_layer(max, vis_refl, 'Max (B11, B8, B3)')
+
+sum = col.sum()
+m.add_ee_layer(
+    sum, {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 500}, 'Sum (MSK_CLDPRB)'
+)
+
+product = col.product()
+m.add_ee_layer(
+    product,
+    {'bands': ['MSK_CLDPRB'], 'min': 0, 'max': 1e10},
+    'Product (MSK_CLDPRB)',
+)
+
+# ee.ImageCollection.mode returns the most common value. If multiple mode
+# values occur, the minimum mode value is returned.
+mode = col.mode()
+m.add_ee_layer(
+    mode, {'bands': ['SCL'], 'min': 1, 'max': 11}, 'Mode (pixel class)'
+)
+
+# ee.ImageCollection.count returns the frequency of valid observations. Here,
+# image pixels are masked based on cloud probability to add valid observation
+# variability to the collection. Note that pixels with no valid observations
+# are masked out of the returned image.
+not_cloud_col = col.map(
+    lambda img: img.updateMask(img.select('MSK_CLDPRB').lte(10))
+)
+count = not_cloud_col.count()
+m.add_ee_layer(count, {'min': 1, 'max': 5}, 'Count (not cloud observations)')
+
+# ee.ImageCollection.mosaic composites images according to their position in
+# the collection (priority is last to first) and pixel mask status, where
+# invalid (mask value 0) pixels are filled by preceding valid (mask value >0)
+# pixels.
+mosaic = not_cloud_col.mosaic()
+m.add_ee_layer(mosaic, vis_refl, 'Mosaic (B11, B8, B3)')
+m
+# [END earthengine__apidocs__ee_imagecollection_median]