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

# # Mapboxgl Python Library for location data visualization
# 
# https://github.com/mapbox/mapboxgl-jupyter
# 
# ### Requirements
# 
# These examples require the installation of the following python modules
# 
# ```
# pip install mapboxgl
# ```
# 
# ### Notes
# 
# `ImageViz` object accepts either an url, a local path or a numpy ndarray data as input for an image source

# In[ ]:


import os
import numpy
from matplotlib.pyplot import imread
from mapboxgl.viz import ImageViz


# ## Set your Mapbox access token.  
# Set a  `MAPBOX_ACCESS_TOKEN` environment variable or copy/paste your token  
# If you do not have a Mapbox access token, sign up for an account at https://www.mapbox.com/  
# If you already have an account, you can grab your token at https://www.mapbox.com/account/

# In[ ]:


# Must be a public token, starting with `pk`
token = os.getenv('MAPBOX_ACCESS_TOKEN')


# ## Display an image given an URL

# In[ ]:


img_url = 'https://raw.githubusercontent.com/mapbox/mapboxgl-jupyter/master/examples/data/mosaic.png'

# Coordinates must be an array in the form of [UL, UR, LR, LL]
coordinates = [[-123.40515640309, 38.534294809274336],
               [-115.92938988349292, 38.534294809274336],
               [-115.92938988349292, 32.08296982365502], 
               [-123.40515640309, 32.08296982365502]]

# Create the viz from the dataframe
viz = ImageViz(img_url, 
               coordinates, 
               access_token=token,
               height='600px',
               center=(-119, 35),
               zoom=5,
               below_layer='waterway-label')
viz.show()


# ## Display an image given a numpy.ndarray

# In[ ]:


img = imread(img_url)
img = numpy.mean(img[::10, ::10], axis=2)

# Coordinates must be an array in the form of [UL, UR, LR, LL]
coordinates = [[-123.40515640309, 38.534294809274336],
               [-115.92938988349292, 38.534294809274336],
               [-115.92938988349292, 32.08296982365502], 
               [-123.40515640309, 32.08296982365502]]

# Create the viz from the dataframe
viz = ImageViz(img, 
               coordinates, 
               access_token=token,
               height='600px',
               center=(-119, 35),
               zoom=5,
               below_layer='waterway-label')
viz.show()


# ## Display an image given a local path

# In[ ]:


# Coordinates must be an array in the form of [UL, UR, LR, LL]
coordinates = [[-123.40515640309, 38.534294809274336],
               [-115.92938988349292, 38.534294809274336],
               [-115.92938988349292, 32.08296982365502], 
               [-123.40515640309, 32.08296982365502]]

# Create the viz from the dataframe
viz = ImageViz(img_url, 
               coordinates, 
               access_token=token,
               height='600px',
               center=(-119, 35),
               zoom=5,
               below_layer='waterway-label')
viz.show()


# ## Choose a colormap

# In[ ]:


from matplotlib import cm

img = imread(img_url)
img = numpy.mean(img[::10, ::10], axis=2)
img = cm.magma(img)

# Coordinates must be an array in the form of [UL, UR, LR, LL]
coordinates = [[-123.40515640309, 38.534294809274336],
               [-115.92938988349292, 38.534294809274336],
               [-115.92938988349292, 32.08296982365502], 
               [-123.40515640309, 32.08296982365502]]

# Create the viz from the dataframe
viz = ImageViz(img_url, 
               coordinates, 
               access_token=token,
               height='600px',
               center=(-119, 35),
               zoom=5,
               below_layer='waterway-label')
viz.show()