Py.Cafe

import streamlit as st
import numpy as np
import pandas as pd
import ee
import geemap.foliumap as geemap
from google.oauth2 import id_token
from google.auth.transport import requests
from google.auth import compute_engine
import json

st.set_page_config(layout="wide")

st.sidebar.info(
    """
    - Web App URL: <https://streamlit.geemap.org>
    - GitHub repository: <https://github.com/giswqs/streamlit-geospatial>
    """
)

st.sidebar.title("Contact")
st.sidebar.info(
    """
    Qiusheng Wu: <https://wetlands.io>
    [GitHub](https://github.com/giswqs) | [Twitter](https://twitter.com/giswqs) | [YouTube](https://www.youtube.com/c/QiushengWu) | [LinkedIn](https://www.linkedin.com/in/qiushengwu)
    """
)

Map = geemap.Map()

# Define ROI (California coordinates: Latitude and longitude coordinates are: 36.778259, -119.417931.)
regionOfInterest = ee.Geometry.Point(-119.417931, 36.778259)

vegetation_image = None
evapotranspiration_image = None
composite_image = None


def app():
    st.title("Your Streamlit App - Composite - evapotranspiration_image first")


    # Data from the downloaded JSON file
    json_data = '''
    {
    "type": "service_account",
    "project_id": "contactniravv",
    "private_key_id": "2311ce3809826bb550cb098e057ee2e6068a40ff",
    "private_key": "-----BEGIN PRIVATE KEY-----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\nNrXJpx1EflUlNzxEOve2kKr2\n-----END PRIVATE KEY-----\n",
    "client_email": "contactniravv@contactniravv.iam.gserviceaccount.com",
    "client_id": "107657170325250962617",
    "auth_uri": "https://accounts.google.com/o/oauth2/auth",
    "token_uri": "https://oauth2.googleapis.com/token",
    "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
    "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/contactniravv%40contactniravv.iam.gserviceaccount.com",
    "universe_domain": "googleapis.com"
    }
    '''
    # Preparing values
    json_object = json.loads(json_data, strict=False)
    service_account = json_object['client_email']
    json_object = json.dumps(json_object)
    # Authorising the app
    credentials = ee.ServiceAccountCredentials(service_account, key_data=json_object)
    print("credentials = ", credentials)
    ee.Initialize(credentials)

    add_evapotranspiration_layer()
    add_vegetation_layer()

    # Create composite image with above layers
    concat_images()
    # combine_images_method_2()

def add_vegetation_layer():
    print("in add_vegetation_layer")
    global vegetation_image

    # Load the image collection
    dataset = ee.ImageCollection('MODIS/061/MOD13A2') \
        .filterDate('2015-01-01', '2015-01-31') \
        .mean()

    # Select the NDVI band
    ndvi = dataset.select('NDVI')

    # Visualization parameters
    ndviVis = {
        'min': 0,
        'max': 9000,
        'palette': [
            'ffffff', 'ce7e45', 'df923d', 'f1b555', 'fcd163', '99b718', '74a901',
            '66a000', '529400', '3e8601', '207401', '056201', '004c00', '023b01',
            '012e01', '011d01', '011301'
        ]
    }

    # Map = geemap.Map(center=(40.0,-100),zoom=4, width=150,height=500)
    # Map.add_basemap('NSV')
    # Set the map center
    # Map.setCenter(6.746, 46.529, 2)
    # Map.set_center(21.2, 22.2, 2)

    # Map = geemap.Map(center=[40, -100], zoom=4)
    vcolor = st.color_picker('Pick A Color', '#00f900')
    st.write('The current color is', vcolor)

    # st.write(Map)

    translate = {
        "image_collection": "ee.ImageCollection('",
        "image": "ee.Image('",
        "table": "ee.FeatureCollection('",
        "table_collection": "ee.FeatureCollection('",
    }
    ee_assets = geemap.search_ee_data('MODIS/061/MOD13A2')
    print(ee_assets)
    asset_titles = [x["title"] for x in ee_assets]
    print("asset title = ", asset_titles)
    asset_types = [x["type"] for x in ee_assets]
    print("asset type = ", asset_types)
    index = asset_titles.index(asset_titles[0])
    print("index = ", index)
    ee_id = ee_assets[index]["id"]
    print("ee_id = ", ee_id)
    uid = ee_assets[index]["uid"]
    print("uid = ", uid)

    ee_asset = f"{translate[asset_types[index]]}{ee_id}')"
    print("ee_asset = ", ee_asset)

    try:
        print("Adding NDVI vegetation layer/loading to streamlit")
        # Add the NDVI layer to the map
        # vegetation_image = ndvi.filterBounds(regionOfInterest).first()
        vegetation_image = ndvi
        print("vegetation_image:", vegetation_image.getInfo())

        # # Map.addLayer(ndvi, ndviVis, 'NDVI vegetation layer')
        ## Map.addLayer(vegetation_image, ndviVis, 'NDVI vegetation layer')
        # Map.addLayer(eval(ee_asset))
        # st.write(Map)
        # Map.to_streamlit()
    except Exception as e:
        st.error(f"Error adding NDVI vegetation layer/loading to streamlit: {e}")


    # width = 950
    # height = 600
    # row1_col1, row1_col2 = st.columns([3, 1])
    # with row1_col2: 
    #     Map.to_streamlit(width=width, height=height)

    # client_id = "882253985203-c0q9uq25mei210cddbu4r7s78kass0kh.apps.googleusercontent.com"  # Replace with your OAuth client ID
    # token = st.text_input("Enter your Google ID token", type="password")
    # if st.button("Authenticate"):
    #     try:
    #         idinfo = id_token.verify_oauth2_token(token, requests.Request(), client_id)
    #         if idinfo['aud'] != client_id:
    #             raise ValueError("Invalid client ID")
    #         st.success(f"Authentication successful: {idinfo['name']}")
    #         # Continue with the rest of your app logic here
    #     except ValueError as e:
    #         st.error("Authentication failed")
    #         st.error(e)

def add_evapotranspiration_layer():
    print("in add_evapotranspiration_layer")
    global evapotranspiration_image

    # Load the image collection
    dataset = ee.ImageCollection("CSIC/SPEI/2_9") \
        .filterDate('2015-01-01', '2015-01-31') \
        .mean()

    # Select the 24-month analysis
    spei24 = dataset.select('SPEI_24_month')

    # Set the visualization parameters
    visParams = {
        'min': -2.33,
        'max': 2.33,
        'palette': [
            '8b1a1a', 'de2929', 'f3641d',
            'fdc404', '9afa94', '03f2fd',
            '12adf3', '1771de', '00008b',
        ]
    }

    try:
        # Display the SPEI 24-month layer
        print("Adding SPEI 24-month evapotranspiration layer/loading to streamlit")
        # evapotranspiration_image = spei24.filterBounds(regionOfInterest).first()
        evapotranspiration_image = spei24
        print("evapotranspiration_image:", evapotranspiration_image.getInfo())

        # Map.addLayer(spei24, visParams, 'SPEI 24 month evapotranspiration layer')
        ##Map.addLayer(evapotranspiration_image, visParams, 'SPEI 24 month evapotranspiration layer')
        # Map.to_streamlit()
    except Exception as e:
        st.error(f"Error adding SPEI 24-month evapotranspiration layer/loading to streamlit: {e}")

def concat_images():
    print("in concat_images")
    global vegetation_image
    global evapotranspiration_image

    try:
        # Create a concat image with vegetation_image and evapotranspiration_image
        composite_image = ee.Image.cat([evapotranspiration_image, vegetation_image])
        print("composite_image =", composite_image)
        Map.addLayer(composite_image, {'bands': ['SPEI_24_month', 'NDVI'], 'min': -1, 'max': 1}, 'Composite Image')
        #Map.addLayer(composite_image, name='Concat Image')

        evapotranspiration_viz_params = {
            'bands': ['SPEI_24_month', 'NDVI'],
            'min': -1,
            'max': 1
            # 'palette': [
            #     '8b1a1a', 'de2929', 'f3641d',
            #     'fdc404', '9afa94', '03f2fd',
            #     '12adf3', '1771de', '00008b',
            # ]
        }

        #Map.addLayer(composite_image, name='Concat Image', viz_params=evapotranspiration_viz_params)        

        Map.to_streamlit()
    except Exception as e:
        st.error(f"Error creating concat image: {e}")

def combine_images():
    print("in combine_images")
    global vegetation_image
    global evapotranspiration_image
    # try:
    # Method 1
    # Create a combined image with vegetation_image and evapotranspiration_image
    composite_image = ee.Image.combine_([evapotranspiration_image, vegetation_image])
    print("Combined image:", composite_image.getInfo())
    # Map.addLayer(composite_image, {'bands': ['SPEI_24_month', 'NDVI']}, name='Composite Image')
    Map.addLayer(composite_image, {'bands': ['SPEI_24_month', 'NDVI'], 'min': -1, 'max': 1}, 'Composite Image')

    # Map.addLayer(composite_image, name='Combined Image')

    Map.to_streamlit()
    # except Exception as e:
    #     st.error(f"Error creating combined image: {e}")

    # Method 2
    # Create a combined image with vegetation_image and evapotranspiration_image
    # print("evapotranspiration_image image:", evapotranspiration_image)
    # print("vegetation_image image:", vegetation_image.getInfo())
    # composite_image = evapotranspiration_image.addBands(vegetation_image)
    # print("Combined image:", composite_image.getInfo())

    # Map.addLayer(composite_image, name='Combined Image')
    # Map.to_streamlit()

def combine_images_method_2():
    print("in combine_images_method_2")
    global vegetation_image
    global evapotranspiration_image
    # try:
    # Method 2
    # try:
    # Create a combined image with vegetation_image and evapotranspiration_image
    print("evapotranspiration_image image:", evapotranspiration_image)
    print("vegetation_image image:", vegetation_image.getInfo())
    # composite_image = evapotranspiration_image.addBands(vegetation_image)
    composite_image = vegetation_image.addBands(evapotranspiration_image)
    # print("Combined image:", composite_image.getInfo())

    viz_params = {
        'bands': ['SPEI_24_month', 'NDVI'],
        'min': -1,
        'max': 1,
        'gamma': [1, 1, 1]  # Adjust gamma if needed
    }

    evapotranspiration_viz_params = {
        'min': -2.33,
        'max': 2.33,
        'palette': [
            '8b1a1a', 'de2929', 'f3641d',
            'fdc404', '9afa94', '03f2fd',
            '12adf3', '1771de', '00008b',
        ]
    }

    Map.addLayer(composite_image, name='Combined Image', viz_params=evapotranspiration_viz_params)
    Map.to_streamlit()
    # except Exception as e:
    #     st.error(f"Error creating combined image: {e}")

app()