#!/usr/bin/env python
# coding: utf-8

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import ee
import geemap
import os


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geemap.show_youtube('_6JOA-iiEGU')


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Map = geemap.Map()
Map


# ## Download an ee.Image

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image = ee.Image('LE7_TOA_5YEAR/1999_2003')

landsat_vis = {
    'bands': ['B4', 'B3', 'B2'], 
    'gamma': 1.4
}
Map.addLayer(image, landsat_vis, "LE7_TOA_5YEAR/1999_2003", True, 0.7)


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# Draw any shapes on the map using the Drawing tools before executing this code block
feature = Map.draw_last_feature
roi = feature.geometry()


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out_dir = os.path.join(os.path.expanduser('~'), 'Downloads')
filename = os.path.join(out_dir, 'landsat.tif')


# ### Exporting all bands as one single image

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image = image.clip(roi).unmask()
geemap.ee_export_image(image, filename=filename, scale=90, region=roi, file_per_band=False)


# ### Exporting each band as one image

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geemap.ee_export_image(image, filename=filename, scale=90, region=roi, file_per_band=True)


# ### Export an image to Google Drive

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geemap.ee_export_image_to_drive(image, description='landsat', folder='export', region=roi, scale=30)


# ## Download an ee.ImageCollection

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import ee
import geemap
import os


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loc = ee.Geometry.Point(-99.2222, 46.7816)
collection = ee.ImageCollection('USDA/NAIP/DOQQ') \
    .filterBounds(loc) \
    .filterDate('2008-01-01', '2020-01-01') \
    .filter(ee.Filter.listContains("system:band_names", "N"))


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out_dir = os.path.join(os.path.expanduser('~'), 'Downloads')


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print(collection.aggregate_array('system:index').getInfo())


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geemap.ee_export_image_collection(collection, out_dir=out_dir)


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geemap.ee_export_image_collection_to_drive(collection, folder='export', scale=10)


# ## Extract pixels as a Numpy array

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import ee
import geemap
import numpy as np
import matplotlib.pyplot as plt

img = ee.Image('LANDSAT/LC08/C01/T1_SR/LC08_038029_20180810') \
  .select(['B4', 'B5', 'B6'])

aoi = ee.Geometry.Polygon(
  [[[-110.8, 44.7],
    [-110.8, 44.6],
    [-110.6, 44.6],
    [-110.6, 44.7]]], None, False)

rgb_img = geemap.ee_to_numpy(img, region=aoi)
print(rgb_img.shape)


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# Scale the data to [0, 255] to show as an RGB image. 
# Adapted from https://bit.ly/2XlmQY8. Credits to Justin Braaten
rgb_img_test = (255*((rgb_img[:, :, 0:3] - 100)/3500)).astype('uint8')
plt.imshow(rgb_img_test)
plt.show()