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

# # Pydeck + Earth Engine: ImageCollection Animation
# 
# This is an example of using [pydeck](https://pydeck.gl) to animate a Google Earth Engine `ImageCollection` object. To install and run this notebook locally, refer to the [Pydeck Earth Engine documentation](https://earthengine-layers.com/docs/developer-guide/pydeck-integration).
# 
# To see this example online, view the [JavaScript version][js-example].
# 
# [js-example]: https://earthengine-layers.com/examples/image-collection

# Import required packages:

# In[1]:


from pydeck_earthengine_layers import EarthEngineLayer
import pydeck as pdk
import ee


# ### Authenticate with Earth Engine
# 
# Using Earth Engine requires authentication. If you don't have a Google account approved for use with Earth Engine, you'll need to request access. For more information and to sign up, go to https://signup.earthengine.google.com/.

# In[2]:


try:
    ee.Initialize()
except Exception as e:
    ee.Authenticate()
    ee.Initialize()


# ### GFS Temperature Forecast Dataset
# 
# This example uses the [Global Forecast System 384-Hour Predicted Atmosphere Data][gfs] dataset, which contains a weather forecast model produced by the National Centers for Environmental Prediction (NCEP)
# 
# [gfs]: https://developers.google.com/earth-engine/datasets/catalog/NOAA_GFS0P25

# Import the dataset by creating an Earth Engine object that references it.

# In[3]:


# Initialize an ee.ImageColllection object referencing the Global Forecast System dataset
image_collection = ee.ImageCollection('NOAA/GFS0P25')

# Select images from December 22, 2018
image_collection = image_collection.filterDate('2018-12-22', '2018-12-23')

# Choose the first 24 images in the ImageCollection
image_collection = image_collection.limit(24)

# Select a single band to visualize
image_collection = image_collection.select('temperature_2m_above_ground')


# Create a `vis_params` object that defines how EarthEngine should style the `ImageCollection`

# In[4]:


# Style temperature values between -40C and 35C, 
# with lower values shades of blue, purple, and cyan, 
# and higher values shades of green, yellow, and red
vis_params = {
    'min': -40.0,
    'max': 35.0,
    'palette': ['blue', 'purple', 'cyan', 'green', 'yellow', 'red']
};


# Create a new `EarthEngineLayer` with this dataset that can then be passed to Pydeck.

# In[5]:


layer = EarthEngineLayer(
    image_collection,
    vis_params,
    animate=True,
    id="global_weather")


# Then just pass this layer to a `pydeck.Deck` instance, and call `.show()` to create a map:

# In[6]:


view_state = pdk.ViewState(latitude=36, longitude=10, zoom=1)
r = pdk.Deck(
    layers=[layer], 
    initial_view_state=view_state
)
r.show()


# In[ ]: