Matplotlib tutorial(3)

Other types of plots

Regular Plots

Starting from the code below, try to reproduce the graphic on the right taking care of filled areas:

import numpy as np
import matplotlib.pyplot as plt

n = 256
X = np.linspace(-np.pi,np.pi,n,endpoint=True)
Y = np.sin(2*X)
plt.plot (X, Y+1, color='blue', alpha=1.00)
plt.fill_between(X, 1, Y+1, color='blue', alpha=.25)

plt.plot (X, Y-1, color='blue', alpha=1.00)
plt.fill_between(X, -1, Y-1, (Y-1) > -1, color='blue', alpha=.25)
plt.fill_between(X, -1, Y-1, (Y-1) < -1, color='red',  alpha=.25)
plt.show()

Scatter Plots

Starting
from the code below, try to reproduce the graphic on the right taking care of marker size, color and transparency.

import numpy as np
import matplotlib.pyplot as plt

n = 1024
X = np.random.normal(0,1,n)
Y = np.random.normal(0,1,n)
T = np.arctan2(Y,X)

plt.axes=([0,0,1,1])
plt.scatter(X,Y,c=T,alpha=.5)
plt.show()

Bar
Plots

Starting
from the code below, try to reproduce the graphic on the right by adding labels for red bars.

import numpy as np
import matplotlib.pyplot as plt

n = 12
X = np.arange(n)
Y1 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)
Y2 = (1-X/float(n)) * np.random.uniform(0.5,1.0,n)
plt.bar(X, +Y1, facecolor='#9999ff', edgecolor='white')
plt.bar(X, -Y2, facecolor='#ff9999', edgecolor='white')

for x, y in zip(X, Y1):
plt.text(x+0.4, y+0.01, '%.2f' % y, ha = 'center', va = 'bottom')
for x, y in zip(X, -Y2):
plt.text(x+0.4, y-0.01, '%.2f' % y, ha = 'center', va = 'top')
plt.xlim(-.5,n), plt.xticks([])
plt.ylim(-1.25, +1.25), plt.yticks([])
plt.show()

Contour
Plots

Starting
from the code below, try to reproduce the graphic on the right taking care of the colormap (see Colormaps below).

import numpy as np
import matplotlib.pyplot as plt

def f(x,y):
return (1-x/2+x**5+y**3)*np.exp(-x**2-y**2)

n = 256
x = np.linspace(-3,3,n)
y = np.linspace(-3,3,n)
X, Y = np.meshgrid(x, y)

plt.axes([0.025,0.025,0.95,0.95])
plt.contourf(X, Y, f(X,Y), 8, alpha=.75, camp=plt.cm.hot)
C = plt.contour(X,Y, f(X,Y),8, colors='black',linewidth=.5)
plt.clabel(C,inline=1,fontsize=10)
plt.xticks([]), plt.yticks([])
plt.show()

Pie
Charts

Starting
from the code below, try to reproduce the graphic on the right taking care of colors and slices size.

import numpy as np
import matplotlib.pyplot as plt

n = 20
Z = np.ones(n)
Z[-1] *= 2
plt.pie(Z,explode=Z*.05,colors=['%f' % (i/float(n)) for i in range(n)])
plt.gca().set_aspect('equal')
plt.xticks([]), plt.yticks([])
plt.show()

Grids

import numpy as np
import matplotlib.pyplot as plt

ax = plt.axes([0.025,0.025,0.95,0.95])

ax.set_xlim(0,4)
ax.set_ylim(0,3)
ax.xaxis.set_major_locator(plt.MultipleLocator(1.0))
ax.xaxis.set_minor_locator(plt.MultipleLocator(0.2))
ax.yaxis.set_major_locator(plt.MultipleLocator(1.0))
ax.yaxis.set_minor_locator(plt.MultipleLocator(0.2))
ax.grid(which='major', axis='x', linewidth=0.75, linestyle='-', color='0.75')
ax.grid(which='minor', axis='x', linewidth=0.25, linestyle='-', color='0.75')
ax.grid(which='major', axis='y', linewidth=0.75, linestyle='-', color='0.75')
ax.grid(which='minor', axis='y', linewidth=0.25, linestyle='-', color='0.75')
ax.set_xticklabels([])
ax.set_yticklabels([])
plt.show()

Multi
Plots

import numpy as np
import matplotlib.pyplot as plt

fig = plt.figure()
fig.subplots_adjust(bottom=0.025, left=0.025, top = 0.975, right=0.975)

plt.subplot(2,1,1)
plt.xticks([]), plt.yticks([])

plt.subplot(2,3,4)
plt.xticks([]), plt.yticks([])

plt.subplot(2,3,5)
plt.xticks([]), plt.yticks([])

plt.subplot(2,3,6)
plt.xticks([]), plt.yticks([])

# plt.savefig('../figures/multiplot_ex.png',dpi=48)
plt.show()