Example:5
Dotted line
Lines can be in the form of dots like the image below. Instead of calling plot(x,y) call the scatter(x,y) method. The scatter(x,y) method can also be used to (randomly) plot points onto the chart.
import matplotlib.pyplot as plt import numpy as np n = 1024 X = np.random.normal(0, 1, n) Y = np.random.normal(0, 1, n) T = np.arctan2(X, Y) plt.scatter(np.arange(5), np.arange(5)) plt.xticks(()) plt.yticks(()) plt.show()
Example:6
Line ticks
You can change the ticks on the plot. Set them on the x-axis, y-axis or even change their color. The line can be more thick and have an alpha value.
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-1, 1, 50)
y = 2*x - 1
plt.figure(figsize=(12, 8))
plt.plot(x, y, color='r', linewidth=10.0, alpha=0.5)
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))
for label in ax.get_xticklabels() + ax.get_yticklabels():
label.set_fontsize(12)
label.set_bbox(dict(facecolor='y', edgecolor='None', alpha=0.7))
plt.show()
Example:7
Line with asymptote
An asymptote can be added to the plot. To do that, use plt.annotate(). There’s lso a dotted line in the plot below. You can play around with the code to see how it works.
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-1, 1, 50)
y1 = 2*x + 1
y2 = 2**x + 1
plt.figure(figsize=(12, 8))
plt.plot(x, y2)
plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--')
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))
x0 = 1
y0 = 2*x0 + 1
plt.scatter(x0, y0, s = 66, color = 'b')
plt.plot([x0, x0], [y0, 0], 'k-.', lw= 2.5)
plt.annotate(r'$2x+1=%s$' %
y0,
xy=(x0, y0),
xycoords='data',
xytext=(+30, -30),
textcoords='offset points',
fontsize=16,
arrowprops=dict(arrowstyle='->',connectionstyle='arc3,rad=.2')
)
plt.text(0, 3,
r'$This\ is\ a\ good\ idea.\ \mu\ \sigma_i\ \alpha_t$',
fontdict={'size':16,'color':'r'})
plt.show()
Example:8
Line with text scale
It doesn’t have to be a numeric scale. The scale can also contain textual words like the example below. In plt.yticks() we just pass a list with text values. These values are then show against the y axis.
import matplotlib.pyplot as plt
import numpy as np
x = np.linspace(-1, 1, 50)
y1 = 2*x + 1
y2 = 2**x + 1
plt.figure(num = 3, figsize=(8, 5))
plt.plot(x, y2)
plt.plot(x, y1,
color='red',
linewidth=1.0,
linestyle='--'
)
plt.xlim((-1, 2))
plt.ylim((1, 3))
new_ticks = np.linspace(-1, 2, 5)
plt.xticks(new_ticks)
plt.yticks([-2, -1.8, -1, 1.22, 3],
[r'$really\ bad$', r'$bad$', r'$normal$', r'$good$', r'$readly\ good$'])
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
ax.spines['bottom'].set_position(('data', 0))
ax.spines['left'].set_position(('data', 0))
plt.show()
