# composite multiple plots into one figure
# using subplot2grid function

import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

T = np.linspace(-np.pi, np.pi, 256)
grid_size = (4,2)

print(help(plt.subplot2grid))  # Get the docstring of the function subplot2grid

plt.subplot2grid(grid_size, (0,0), rowspan=2, colspan=1)
plt.plot(np.sin(2*T), np.cos(0.5 *T), c='k')

plt.subplot2grid(grid_size, (0,1), rowspan=3, colspan=1)
plt.plot(np.sin(2*T), np.cos(T), c='k')

plt.subplot2grid(grid_size, (2,0), rowspan=1, colspan=1)
plt.plot(np.sin(2*T), np.cos(3*T), c='k')

plt.subplot2grid(grid_size, (3,0), rowspan=1, colspan=2)
plt.plot(np.exp(-T), c='k')

plt.tight_layout() #to prevent plots overlapping 
plt.show()

Help on function subplot2grid in module matplotlib.pyplot:

subplot2grid(shape, loc, rowspan=1, colspan=1, **kwargs)
    Create a subplot in a grid.  The grid is specified by *shape*, at
    location of *loc*, spanning *rowspan*, *colspan* cells in each
    direction.  The index for loc is 0-based. ::
    
      subplot2grid(shape, loc, rowspan=1, colspan=1)
    
    is identical to ::
    
      gridspec=GridSpec(shape[0], shape[1])
      subplotspec=gridspec.new_subplotspec(loc, rowspan, colspan)
      subplot(subplotspec)

None

# add titles to the subfigures

import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

T = np.linspace(-np.pi, np.pi, 256)
grid_size = (4,2)

for i in range(1,5):
    axes = plt.subplot2grid(grid_size, (i-1,0), rowspan=1, colspan=4)
    axes.get_yaxis().set_visible(False)  # remove the y axis ticks
    plt.plot(np.sin(i * T), c='k')
    plt.title('{}Hz'.format(i))


plt.tight_layout() #to prevent plots overlapping 
plt.show()

# composite multiple plots into one figure
# using subplot function
import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

time = np.linspace(0,4,200)

fig, (ax0,ax1) = plt.subplots(ncols=2)
ax0.plot(time, np.sin(time), c='g')
ax1.plot(time, np.cos(time), c='r')

plt.show()

# To scale the axes we need the pyplot API and the Axes object 
import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

time = np.linspace(0,4,200)

# print(help(plt.axes().set_aspect))

fig, (ax0,ax1) = plt.subplots(ncols=2)

ax0.plot(time, np.sin(time), c='g')
ax0.set_aspect('equal') #the actual ratio
ax1.plot(time, np.cos(time), c='r')
ax1.set_aspect('3')  # the hight is three times the width
plt.show()

# Set the aspect ratio of a figure using figsize
import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

time = np.linspace(0,4,200)

plt.figure(figsize=(10.24,2.56))

plt.plot(time, np.sin(time), c='g')
plt.show()

# Set a limit on the axes
import numpy as np
from matplotlib import pyplot as plt
% matplotlib inline

time = np.linspace(0,4,200)

plt.plot(time, np.sin(time), c='g')
plt.ylim(0,0.5)  # limit the y axis 
plt.xlim(0,3.5)  # limit the x axis 
plt.show()

import numpy as np
from matplotlib import pyplot as plt

%matplotlib inline

X = np.linspace(-6, 6, 1024)
Y = np.sinc(X)

X_detail = np.linspace(-3, 3, 1024)
Y_detail = np.sinc(X_detail)


plt.plot(X, Y, c = 'k')

# set the position of the zoomed up plot
#([bottom left corner (.57,.6), width (0.3), hight(0.2)])
sub_axes = plt.axes([.57, .6, .3, .2])

sub_axes.plot(X_detail, Y_detail, c = 'k')

# remove the Y axis labels
sub_axes.get_yaxis().set_visible(False)

# insert the zoomed up plot
# plt.setp(sub_axes)
plt.show()