In [1]:

    

import os
import folium

print(folium.__version__)


    

    




0.3.0.dev

In [2]:

    

import cartopy.crs as ccrs
import matplotlib.pyplot as plt
import cartopy.feature as cfeature

LAND = cfeature.NaturalEarthFeature('physical', 'land', '50m',
                                    edgecolor='face',
                                    facecolor=cfeature.COLORS['land'])


def make_map(bbox, projection=ccrs.Mercator()):
    fig, ax = plt.subplots(figsize=(8, 6),
                           subplot_kw=dict(projection=projection))
    ax.set_extent(bbox)
    ax.add_feature(LAND, facecolor='0.25')
    ax.coastlines(resolution='50m')
    return fig, ax


    

In [3]:

    

import numpy.ma as ma
from scipy.io import loadmat

fname = os.path.join('data', 'mercator_temperature.mat')
merc = loadmat(fname, squeeze_me=True)

x, y = merc['x'], merc['y']
bbox = [x.min(), x.max(), y.min(), y.max()]

level = 10  # 10 meters temperature.
data = ma.masked_invalid(merc['temp'][level, ...])

fig, ax = make_map(bbox=bbox)
cs = ax.pcolormesh(x, y, data, transform=ccrs.PlateCarree())
fig.savefig('GS.png', transparent=True)


    

In [4]:

    

import numpy as np
from PIL import Image, ImageChops


def trim(img):
    border = Image.new(img.mode, img.size, img.getpixel((0, 0)))
    diff = ImageChops.difference(img, border)
    diff = ImageChops.add(diff, diff, 2.0, -100)
    bbox = diff.getbbox()
    if bbox:
        img = img.crop(bbox)
    return np.array(img)

img = Image.open("GS.png")
img = trim(img)


    

In [5]:

    

from folium import plugins


m = folium.Map(location=[y.mean(), x.mean()], zoom_start=5)

plugins.ImageOverlay(img,
                     [[y.min(), x.min()], [y.max(), x.max()]],
                     opacity=0.5).add_to(m)


m.save(os.path.join('results', 'GulfStreamImageOverlay_0.html'))

m


    

    
Out[5]:

In [6]:

    

def colorize(array, cmap='rainbow'):
    normed_data = (array - array.min()) / (array.max() - array.min())
    cm = plt.cm.get_cmap(cmap)
    return cm(normed_data)

colored_data = colorize(data, cmap='rainbow')


    

    




/home/filipe/miniconda3/envs/FOLIUM/lib/python3.5/site-packages/numpy/ma/core.py:852: RuntimeWarning: invalid value encountered in greater_equal
  return umath.absolute(a) * self.tolerance >= umath.absolute(b)

In [7]:

    

m = folium.Map(location=[y.mean(), x.mean()], zoom_start=5)

plugins.ImageOverlay(np.flipud(colored_data),
                     [[y.min(), x.min()], [y.max(), x.max()]],
                     opacity=0.5).add_to(m)

m.save(os.path.join('results', 'GulfStreamImageOverlay_1.html'))

m


    

    
Out[7]: