Plot multiple maps and data at the same time with Python's matplotlib

When doing research on earth and planetary science, I often come across a scene where I want to plot multiple maps and data on one figure at the same time. As a trial, this time, using Python's matplotlib,

--Plot monthly 2D data (global sea surface temperature data) from January to December into one figure at the same time with a map.

The goal is that.

1. Plot multiple maps at the same time

code

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap

xlim = [100, 170]			#Scope of the figure(x-axis direction: longitude)
ylim = [10, 60]				#Scope of the figure(y-axis direction: latitude)
column = 3					#Number of columns
fsizex, fsizey= 16, 18		#Horizontal / vertical length of the figure
line_interval = 15			#Spacing of parallels and meridians drawn on the map
fontsize = 20				#font size

if 12 % column != 0:
    raise ValueError('column must be a divisor of 12!')

row = 12 / column			#Number of rows
months =  [ 'Jan',  'Feb',  'Mar',  'Apr',
            'May',  'Jun',  'Jul',  'Aug',
            'Sep',  'Oct',  'Nov',  'Dec' ]

fig = plt.figure(figsize = (fsizex, fsizey))
plt.rcParams['font.size'] = fontsize

ax = [0] * 12
for i in range(0, 12):
    ax[i] = fig.add_subplot(row, column, 1 + i)
    m = Basemap(projection = 'cyl', llcrnrlat = ylim[0], urcrnrlat = ylim[1], \
                llcrnrlon = xlim[0], urcrnrlon = xlim[1], resolution = 'c', lon_0 = 180)
    m.drawcoastlines(linewidth = 0.5)
    m.drawmapboundary()
    m.fillcontinents(color = '#eeeeee')
    if i == 12 - column:
        label = [1, 1]
    elif i > 12 - column:
        label = [1, 0]
    elif i % column == 0:
        label = [0, 1]
    else:
        label = [0, 0]

    m.drawmeridians(np.arange(0, 360, line_interval), labels = [0, 0, 0, label[0]], linewidth = 0.5)
    m.drawparallels(np.arange(-90, 90, line_interval), labels = [label[1], 0, 0, 0], linewidth = 0.5)
    ax[i].set_xlim(xlim)
    ax[i].set_ylim(ylim)
    ax[i].set_title(months[i])

fig.tight_layout()
plt.show()

Figure

2. Plot multiple maps and data at the same time

Preparation

If you are plotting 2D data for each month, combine each data for 12 months into a single 3D array.

xn = 360			#X-axis of data(longitude)Number of grids in the direction
yn = 155            #Y-axis of data(latitude)Number of grids in the direction
data = np.zeros((12, yn, xn))
for i in range(0, 12):
	data[i, :, :] = .....  # (i+1)Process to get month data

In addition, a one-dimensional array corresponding to the x-axis (longitude) and y-axis (latitude) of the two-dimensional data is acquired. This time, respectively

• xgrid
• ygrid

(Both are numpy.ndarray).

code

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.basemap import Basemap

xlim = [100, 170]			#Scope of the figure(x-axis direction: longitude)
ylim = [10, 60]				#Scope of the figure(y-axis direction: latitude)
column = 3					#Number of columns
fsizex, fsizey= 16, 18		#Horizontal / vertical length of the figure
cb_min, cb_max = -2, 32     #Minimum / maximum color bar
cb_div = 17					#Number of colors used in the color bar
clabel = 'Sea Surface Temperature(deg)' #Label attached to the color bar
line_interval = 15						#Spacing of parallels and meridians drawn on the map
fontsize = 20							#font size

if 12 % column != 0:
    raise ValueError('column must be a divisor of 12!')

row = 12 / column			#Number of rows
months =  [ 'Jan',  'Feb',  'Mar',  'Apr',
            'May',  'Jun',  'Jul',  'Aug',
            'Sep',  'Oct',  'Nov',  'Dec' ]

fig = plt.figure(figsize = (fsizex, fsizey))
plt.rcParams['font.size'] = fontsize

delta = (cb_max - cb_min) / cb_div
interval_of_cf = np.arange(cb_min, abs(cb_max) * 2 + delta, delta)[0:int(cb_div) + 1]

ax = [0] * 12
for i in range(0, 12):
    ax[i] = fig.add_subplot(row, column, 1 + i)
    m = Basemap(projection = 'cyl', llcrnrlat = ylim[0], urcrnrlat = ylim[1], \
                llcrnrlon = xlim[0], urcrnrlon = xlim[1], resolution = 'c', lon_0 = 180)
    m.drawcoastlines(linewidth = 0.5)
    m.drawmapboundary()
    m.fillcontinents(color = '#eeeeee')
    if i == 12 - column:
        label = [1, 1]
    elif i > 12 - column:
        label = [1, 0]
    elif i % column == 0:
        label = [0, 1]
    else:
        label = [0, 0]

    m.drawmeridians(np.arange(0, 360, line_interval), labels = [0, 0, 0, label[0]], linewidth = 0.5)
    m.drawparallels(np.arange(-90, 90, line_interval), labels = [label[1], 0, 0, 0], linewidth = 0.5)

    #Draw color contours
    x, y = np.meshgrid(xgrid, ygrid)
    X, Y = m(x, y)
    CF = ax[i].contourf(X, Y, data[i, :, :], interval_of_cf)

    ax[i].set_xlim(xlim)
    ax[i].set_ylim(ylim)
    ax[i].set_title(months[i])

#Draw a color bar
cax = fig.add_axes([1.00, 0.15, 0.04, 0.7])
cb = fig.colorbar(CF, cax)
cb.set_label(clabel)

fig.tight_layout()
plt.show()

Figure

Succeeded in creating safely. The combination of vertical and horizontal can be freely changed by changing the value of column.

** Reference URL **

http://seesaawiki.jp/met-python/d/matplotlib/plot http://bicycle1885.hatenablog.com/entry/2014/02/14/023734 http://nm-player.blogspot.jp/2012/09/matplotlibbasemap-1.html http://qiita.com/AnchorBlues/items/0dd1499196670fdf1c46