In [1]:
%matplotlib inline
import os
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
# folium
import folium
print('folium:', folium.__version__)
#cartopy
import cartopy
import cartopy.crs as ccrs
from cartopy.io.img_tiles import OSM
print('cartopy:', cartopy.__version__)
#plotly
import plotly
plotly.offline.init_notebook_mode()
from plotly.offline import download_plotlyjs, init_notebook_mode, iplot
print('plotly:', plotly.__version__)
#basemap
from mpl_toolkits.basemap import Basemap
In [2]:
plt.rcParams['figure.figsize'] = (12, 10)
In [3]:
def haversine(lon1, lat1, lon2, lat2):
# Distance between two points
# assuming that the input is in WGS84 and is equivalent
# to SIRGAS 2000
lon1, lat1, lon2, lat2 = map(np.radians, [lon1, lat1, lon2, lat2])
# haversine formula
a = np.sin((lat2 - lat1 )/2.)**2 + np.cos(lat1) * np.cos(lat2) * np.sin((lon2 - lon1)/2.)**2
c = 2. * np.arcsin