matplotlib tutorial (4) nitta@tsuda.ac.jp

Chapter 4: Specify Title and Axis Labels

4-1: Display titles and axis labels

Set the title, axis label, etc. for the coordinate system (Axes).

• set_title(text) : Title setting
• set_xlabel(text): x-axis label setting
• set_ylabel(text): y-axis label setting

# sample code 4-1-1
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

xs = np.array([0, 1, 2, 3, 4])
ys = xs **2

fig, ax = plt.subplots(1, 1, figsize=(8,6))

ax.plot(xs, ys)

ax.set_title('Center Title', color='blue', size=20, style='italic', family='fantasy', backgroundcolor='gold')
ax.set_title('Left Title', loc='left', color='green')
ax.set_title('Right Title', loc='right', color='red')

ax.set_xlabel('x-label', color='black', size=12)
ax.set_ylabel('y-label', color='orange', size=14, style='italic')

plt.show()

# sample code 4-1-2
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

xs = np.array([0, 1, 2, 3, 4])
ys = xs **2

fig, ax = plt.subplots(1, 1, figsize=(8,6))

ax.plot(xs, ys)

ax.set_title('Center Title', color='blue', size=20, style='italic', backgroundcolor='gold', position=(0.5, 1.1))

plt.show()

# sample code 4-1-3
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

xs = np.array([0, 1, 2, 3, 4])
ys = xs **2

fig, ax = plt.subplots(1, 1, figsize=(8,6))

ax.plot(xs, ys)

ax.set_xlabel('x-label', color='black', size=12, position=(1, 0), rotation=90)
ax.set_ylabel('y-label', color='orange', size=14, position=(0, 1), rotation=0)

plt.show()

4-2: Set Text Styles at once, using fontdict

# sample code 4-2
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

font = {
    'family':'serif',
    'color':'blue',
    'style':'italic',
    'weight':'bold',
    'size':12,
    'rotation': 0
}

xs = np.array([0, 1, 2, 3, 4])
ys = xs **2

fig, ax = plt.subplots(1, 1, figsize=(8,6))

ax.plot(xs, ys)

ax.set_title('Center Title', fontdict=font)

ax.set_xlabel('x-label', fontdict=font)
ax.set_ylabel('y-label', fontdict=font)

plt.show()

4-3: Set axis scales and scale labels

• set_xticks() : x-axis scale value settings
• set_yticks() : y-axis scale value settings
• set_xticklabels() : x-axis tick label setting
• set_yticklabels() : y-axis tick label settings

# sample code 4-3
%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np

xs = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
ys = [5.4, 8.5, 12.8, 15.1, 19.5, 23.2, 24.3, 29.1, 24.2, 17.5, 14.0, 7.7] 

xticks = xs
xticklabels = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
yticks = [0, 5, 10, 15, 20, 25, 30]
yticklabels = ['$0^{\circ}$', '$0^{\circ}$', '$10^{\circ}$', '$15^{\circ}$', '$20^{\circ}$', '$25^{\circ}$', '$30^{\circ}$']

fig, ax = plt.subplots(1, 1, figsize=(12,6))

ax.plot(xs, ys, marker='v')

ax.set_title('Average Temperature', fontdict=font)

ax.set_xlabel('Month')
ax.set_ylabel('Celsius')

ax.set_xticks(xticks)
ax.set_yticks(yticks)

ax.set_xticklabels(xticklabels)
ax.set_yticklabels(yticklabels)

plt.show()

4-4: Move the axis to the center of the graph area, using set_position

The boundaries of the four corners (left, top, right, bottom) of the graph area represented by the Axes object are managed as objects of the Spine class.

Since left represents y-axis and bottom represents the x-axis, each axis can be moved by changing the value of left and bottom key.

# sample code 4-4-1
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

xs = np.linspace(-np.pi, np.pi, 100)
c = np.cos(xs)
s = np.sin(xs)

fig, ax = plt.subplots(1, 1, figsize=(8,6))
ax.plot(xs, c, label='$y=cos(x)$')
ax.plot(xs, s, label='$y=sin(x)$')
ax.legend()

plt.show()

# sample code 4-4-2
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

xs = np.linspace(-np.pi, np.pi, 100)
c = np.cos(xs)
s = np.sin(xs)

fig, ax = plt.subplots(1, 1, figsize=(8,6))
ax.plot(xs, c, label='$y=cos(x)$')
ax.plot(xs, s, label='$y=sin(x)$')
ax.legend()

ax.spines['right'].set_color('none')   # remove
ax.spines['top'].set_color('none')     # remove
ax.spines['bottom'].set_position(('data',0))  # move x-axis to the origin point
ax.spines['left'].set_position(('data',0)) # move y-axis to the origin point

plt.show()

# sample code 4-4-3
%matplotlib inline

import matplotlib.pyplot as plt
import numpy as np

xs = np.linspace(-np.pi, np.pi, 100)
c = np.cos(xs)
s = np.sin(xs)

fig, ax = plt.subplots(1, 1, figsize=(8,6))
ax.plot(xs, c, label='$y=cos(x)$')
ax.plot(xs, s, label='$y=sin(x)$')
ax.legend()

ax.spines['right'].set_color('none')   # remove
ax.spines['top'].set_color('none')     # remove
ax.spines['bottom'].set_position(('data',0))  # move x-axis to the origin point
ax.spines['left'].set_position(('data',0)) # move y-axis to the origin point

#ax.xaxis.set_ticks_position('bottom')  # move xticks to the new x-axis position 
#ax.yaxis.set_ticks_position('left')    # move yticks to the new y-axis position

ax.set_xticks([-np.pi, -np.pi/2, 0, np.pi/2, np.pi])
ax.set_xticklabels(['$-\pi$', '$-\pi/2$', '$0$', '$\pi/2$', '$\pi$'])
ax.set_yticks([-1, 0, 1])
ax.set_yticklabels(['$-1$', '$0$', '$1$'])

plt.show()

4-5: Invert Axis (Axes.set_xlim, Axes.set_ylim)

Invert the x-axis and y-axis.

• Axes.set_xlim($a$,$b$) : Set the x-axis range to [$a$, $b$]. The x-axis is inverted when $a>b$.
• Axes.set_ylim($a$,$b$) : Set the y-axis range to [$a$, $b$]. The y-axis is inverted when $a>b$.

# sample code 4-5-1
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0.01, 5.0, 0.01)
y = np.exp(-x)

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.plot(x, y)
ax.grid(True)

plt.show()

# sample code 4-5-2
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0.01, 5.0, 0.01)
y = np.exp(-x)

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.set_xlim(5, 0)  # invert x-axis

ax.plot(x, y)
ax.grid(True)

plt.show()

# sample code 4-5-3
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt

x = np.arange(0.01, 5.0, 0.01)
y = np.exp(-x)

fig, ax = plt.subplots(1, 1, figsize=(8, 6))

ax.set_ylim(1, 0)  # invert y-axis

ax.plot(x, y)
ax.grid(True)

plt.show()