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

# # Geographic projections
# 
# Here, we'll explore what Python libraries give us map projections. Most libraries that include some form of mapping rely on Google Maps or Open Street Map as a backend that supplies the map tiles, which are displayed using the Mercator projection only. But the world isn't flat, and so when zoomed out enough this massively distorts land area. A projection is a way to take the spherical geometry of the Earth and project it onto a flat surface, i.e. our screens. 
# 
# Our adventure pretty much has to begin with Basemap.

# In[1]:


import numpy as np
import matplotlib.pyplot as plt

from mpl_toolkits.basemap import Basemap
from IPython.display import set_matplotlib_formats


# In[2]:


from mpl_toolkits import basemap
print(basemap.supported_projections)


# In[3]:


# create a Robinson projection that's centered around 
# lon=0, the prime meridian
m = Basemap(projection='robin', lon_0=0.)

fig = plt.figure(figsize=(20,10))

# background color of grey
fig.patch.set_facecolor('#e6e8ec')

# draw white with no boundary line
m.drawmapboundary(color='none', fill_color='white')

# draw continents and countries, with the coastline adding extra definition
#m.drawcoastlines(color='white')
m.fillcontinents(color='black', lake_color='white')
m.drawcountries(linewidth=1, color='white')


# In[4]:


plt.show()


# In[15]:


import geopandas
world = geopandas.read_file(geopandas.datasets.get_path('naturalearth_lowres'))
world.head()


# In[6]:


# world = world[(world.name!="Antarctica")]
mercator = '+proj=merc'
robinson = '+proj=robin'
wgs84 = '+proj=longlat +ellps=WGS84 +datum=WGS84 +no_defs'


# In[16]:


# robinson projection
worldRobinson = world.to_crs(robinson)
worldRobinson.plot(figsize=(20,20), color="black", linewidth=1, edgecolor="white",)
plt.axis('off')
plt.show()


# ### References
# Chris Roach's talk about Basemap: https://www.youtube.com/watch?v=ZIEyHdvF474
# 
# ...and his GitHub repo of the same: https://github.com/croach/oreilly-matplotlib-course/blob/master/07%20-%20Mapping%20in%20matplotlib/0702%20-%20Working%20With%20Maps.ipynb
#