'''
<table class="ee-notebook-buttons" align="left">
    <td><a target="_blank"  href="https://github.com/giswqs/earthengine-py-notebooks/tree/master/Array/array_images.ipynb"><img width=32px src="https://www.tensorflow.org/images/GitHub-Mark-32px.png" /> View source on GitHub</a></td>
    <td><a target="_blank"  href="https://nbviewer.jupyter.org/github/giswqs/earthengine-py-notebooks/blob/master/Array/array_images.ipynb"><img width=26px src="https://upload.wikimedia.org/wikipedia/commons/thumb/3/38/Jupyter_logo.svg/883px-Jupyter_logo.svg.png" />Notebook Viewer</a></td>
    <td><a target="_blank"  href="https://mybinder.org/v2/gh/giswqs/earthengine-py-notebooks/master?filepath=Array/array_images.ipynb"><img width=58px src="https://mybinder.org/static/images/logo_social.png" />Run in binder</a></td>
    <td><a target="_blank"  href="https://colab.research.google.com/github/giswqs/earthengine-py-notebooks/blob/master/Array/array_images.ipynb"><img src="https://www.tensorflow.org/images/colab_logo_32px.png" /> Run in Google Colab</a></td>
</table>
'''

# %%
'''
## Install Earth Engine API
Install the [Earth Engine Python API](https://developers.google.com/earth-engine/python_install) and [geehydro](https://github.com/giswqs/geehydro). The **geehydro** Python package builds on the [folium](https://github.com/python-visualization/folium) package and implements several methods for displaying Earth Engine data layers, such as `Map.addLayer()`, `Map.setCenter()`, `Map.centerObject()`, and `Map.setOptions()`.
The magic command `%%capture` can be used to hide output from a specific cell.
'''


# %%
# %%capture
# !pip install earthengine-api
# !pip install geehydro

# %%
'''
Import libraries
'''


# %%
import ee
import folium
import geehydro

# %%
'''
Authenticate and initialize Earth Engine API. You only need to authenticate the Earth Engine API once. Uncomment the line `ee.Authenticate()` 
if you are running this notebook for this first time or if you are getting an authentication error.  
'''


# %%
# ee.Authenticate()
ee.Initialize()

# %%
'''
## Create an interactive map 
This step creates an interactive map using [folium](https://github.com/python-visualization/folium). The default basemap is the OpenStreetMap. Additional basemaps can be added using the `Map.setOptions()` function. 
The optional basemaps can be `ROADMAP`, `SATELLITE`, `HYBRID`, `TERRAIN`, or `ESRI`.
'''

# %%
Map = folium.Map(location=[40, -100], zoom_start=4)
Map.setOptions('HYBRID')

# %%
'''
## Add Earth Engine Python script 

'''

# %%
# Define an Array of Tasseled Cap coefficients.
coefficients = ee.Array([
  [0.3037, 0.2793, 0.4743, 0.5585, 0.5082, 0.1863],
  [-0.2848, -0.2435, -0.5436, 0.7243, 0.0840, -0.1800],
  [0.1509, 0.1973, 0.3279, 0.3406, -0.7112, -0.4572],
  [-0.8242, 0.0849, 0.4392, -0.0580, 0.2012, -0.2768],
  [-0.3280, 0.0549, 0.1075, 0.1855, -0.4357, 0.8085],
  [0.1084, -0.9022, 0.4120, 0.0573, -0.0251, 0.0238]
])

# Load a Landsat 5 image, select the bands of interest.
image = ee.Image('LANDSAT/LT05/C01/T1_TOA/LT05_044034_20081011') \
  .select(['B1', 'B2', 'B3', 'B4', 'B5', 'B7'])

# Make an Array Image, with a 1-D Array per pixel.
arrayImage1D = image.toArray()

# Make an Array Image with a 2-D Array per pixel, 6x1.
arrayImage2D = arrayImage1D.toArray(1)

# Do a matrix multiplication: 6x6 times 6x1.
componentsImage = ee.Image(coefficients) \
  .matrixMultiply(arrayImage2D) \
  .arrayProject([0]) \
  .arrayFlatten(
    [['brightness', 'greenness', 'wetness', 'fourth', 'fifth', 'sixth']])

# Display the first three bands of the result and the input imagery.
vizParams = {
  'bands': ['brightness', 'greenness', 'wetness'],
  'min': -0.1, 'max': [0.5, 0.1, 0.1]
}
Map.setCenter(-122.3, 37.562, 10)
Map.addLayer(image, {'bands': ['B4', 'B3', 'B2'], 'min': 0, 'max': 0.5}, 'image')
Map.addLayer(componentsImage, vizParams, 'components')



# %%
'''
## Display Earth Engine data layers 

'''


# %%
Map.setControlVisibility(layerControl=True, fullscreenControl=True, latLngPopup=True)
Map