Matplotlib is a plotting library for the Python programming language and its numerical mathematics extension NumPy.
1 Basic drawing
When there are only two quantities x and y in the plot() function.
import numpy as np
import matplotlib.pyplot as plt
# Generate the x,y coordinates of each point on the curve, and then connect them with straight lines
# Use the linspace function to generate an arithmetic sequence
x = np.linspace(-np.pi, np.pi, 200)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
# Connect the points on the curve with straight lines
plt.plot(x, cos_y)
plt.plot(x, sin_y)
# Show graphics
plt.show()
Note: Basic usage of np.linspace() function
2 Line attribute setting
The attributes of the line are mainly line type, line width and color.
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(-np.pi, np.pi, 200)
cos_y = np.cos(x) / 2
sin_y = np.sin(x)
# Connect the points on the curve with straight lines
plt.plot(x, cos_y, linestyle='--', linewidth=1,color='dodgerblue')
plt.plot(x, sin_y, linestyle=':', linewidth=2.5,color='orangered')
plt.show()
3 Coordinate axis setting
Coordinate axis settings mainly include coordinate axis range, coordinate axis name, coordinate axis scale, cross coordinate, etc.
3.1 Get coordinate axis
Coordinate axis settings must first obtain the coordinate axis, and then operate the coordinate axis
Method to get the coordinate axis: ax = plt.gca()
gca-get current axes
Note that there are four top, bottom, left, and right axes
3.2 Get axis and operate
Get the current axis through gca first, and then operate the axis
# Get the current coordinate axis object
ax = mp.gca()
# Set the upper and right axis to none / None
ax.spines['top'].set_color('none')
ax.spines['right'].set_color('none')
Of course, you can also use ax.spines to capture the bottom and left axes and operate
3.3 Specify the coordinate axis position
Change the position of the spine by set_position( (position type, amount) ); the position of the spine is determined by (position type, amount)
position type (amount)
(1) axis (0.0~1.0): put the spine on the specified axis coordinate (Axes coordinate), the range value is from 0.0 to 1.0 (corresponding coordinate from left to right); 0 means the far left, 1 means the far right, 0.5 means the middle position
(2) data (number): put spine on the specified data coordinate (data coordinate), the range value of number is related to the relationship between bottom and top, 0 indicates the position of 0 value on the coordinate axis
(3) Outward: Move the spine from the data area through the specified number of points.
(3) place the spine out from the data area by the specified number of points. (Negative values specify placing the spine inward.)
E.g
import numpy as np
import matplotlib.pyplot as mp
x = np.linspace(-np.pi, np.pi, 200) # generate an arithmetic sequence
cos_y = np.cos(x)
sin_y = np.sin(x)
ax = mp.gca()
ax.spines['left'].set_position(('axes',0.5))
ax.spines['bottom'].set_position(('data', 0))
# Set the right and top borders to be colorless
ax.spines['right'].set_color('None')
ax.spines['top'].set_color('None')
# Connect the points on the curve with straight lines
mp.plot(x, cos_y, linestyle='--', linewidth=1,color='dodgerblue')
mp.plot(x, sin_y, linestyle=':', linewidth=1.2,color='orangered')
# Show graphics
mp.show()
(A) ax.spines['bottom'].set_position(('data', 0))
(b) ax.spines['bottom'].set_position(('data', -3))
(C) ax.spines['bottom'].set_position(('data', -4))
Error thrown:
raise ValueError('bottom cannot be >= top')
ValueError: bottom cannot be >= top
Here, due to the symmetry in this case, ax.spines['bottom'].set_position(('data', 4)) where 4 and -4 are the same, and -4 is mainly used to explain the reason for the error. bottom cannot be >= top Can't figure out why.
There are two reasons for this:
(1) How is the range value (such as 4) defined? Of course, there are series values between 3 and 4, which are not enumerated here;
(2) The negative value moves down, it should be bottom -> bottom, why there is a top value (bottom cannot be >= top).
3.4 Set the coordinate axis range
Set the x-axis range: plt.xlim (minimum, maximum)
Set the y-axis range: plt.ylim (minimum, maximum)
3.5 Set the axis name
Set the x-axis name: plt.xlabel(' string str')
Set the y-axis name: plt.ylabel(' string str')
Note: If the string is Chinese, it is easy to make mistakes.
3.6 Set the coordinate axis scale
Set the x-axis scale: plt.xticks (scale label position, scale label text)
Set y-axis scale: plt.yticks (scale label position, scale label text)
3.7 Scale positioner
set_major_locator(): Set the main scale locator
set_minor_locator(): Set the minor scale locator
Common parameters
NullLocator() is empty, no tick mark
MaxNLocator() specifies the maximum number of ticks
FixedLocator() specifies the scale by parameters
AutoLocator() by default, automatically selects the most reasonable scale
IndexLocator() locates the scale according to the offset and increment
MultipleLocator() locates the scale according to the specified distance
LinearLocator() locates the scale according to the specified total number of scales
LogLocator() locates the scale according to the specified base and exponent
Specific examples
import numpy as np
import matplotlib.pyplot as plt
plt.figure('Locator')
locators = [
'plt.NullLocator()',
'plt.MaxNLocator(nbins=3,steps=[3,5,7,9])',
'plt.FixedLocator(locs=[0,2.5,5,7.5,10])',
'plt.AutoLocator()',
'plt.IndexLocator(offset=0.5, base=1.5)',
'plt.MultipleLocator()',
'plt.LinearLocator(numticks=21)',
'plt.LogLocator(base=2, subs=[1.0])']
n_locators = len(locators)
for i, locator in enumerate(locators):
plt.subplot(n_locators, 1, i + 1)
plt.xlim(0, 10)
plt.ylim(-1, 1)
plt.yticks(())
ax = plt.gca()
ax.spines['left'].set_color('none')
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.spines['bottom'].set_position(('data', 0))
ax.xaxis.set_major_locator(eval(locator))
ax.xaxis.set_minor_locator(plt.MultipleLocator(0.1))
plt.plot(np.arange(11), np.zeros(11))
plt.text(5, 0.3, locator[3:], ha='center', size=10)
plt.tight_layout()
plt.show()
3.8 Set the scale position
Set the x-axis scale value position (below): ax.xaxis.set_ticks_position('bottom')
Set the scale value position of the y-axis (left side): ax.yaxis.set_ticks_position('left')
Note: ax = mp.gca()
Accepted values (ACCEPTS):: ['left' |'right' |'both' |'default' |'none' | ‘top’ |'bottom']
You can also use top to position the scale value even at the top
