plot_figure.py
import numpy as np
import matplotlib.pyplot as plt
Used for line graphs and scatter plots on planes
Line graph
plot_figure.py
x = np.arange(-3,3,0.1)
y = np.sin(x)
plt.plot(x,y)
plt.show()
Graph the value of sin when => x = -3,3,0.1
--np.arange
creates a sequence of numbers on the x-axis
--The first argument of the plot function is the x-axis and the second argument is the y-axis.
--Draw a graph with show ()
Scatter plot
plot_figure.py
x = np.random.randint(0,10,30)
y = np.sin(x) + np.random.randint(0,10,30)
plt.plot(x,y,"o")
plt.show()
--The third argument "o" of plot () is a small circle marker -You can also use "ro" to make it a red marker.
Draw a histogram
plot_fugure.py
plt.hist(np.random.randn(1000))
plt.show()
plot_figure.py
plt.hist(np.random.randn(1000))
plt.title("Histgram")
plt.show()
plot_figure.py
x = np.arange(0,10,0.1)
y = np.exp(x)
plt.plot(x,y)
plt.title("exponential function $ y = e^x $")
plt.ylim(0,5000) #0 on y axis~Designated in the range of 5000
plt.show()
To draw multiple graphs in the same area, simply call them twice. Draw a straight line with y = -1, y = 1 with the hlines function
plot_figure.py
xmin, xmax = -np.pi, np.pi
x = np.arange(xmin, xmax, 0.1)
y_sin = np.sin(x)
y_cos = np.cos(x)
plt.plot(x, y_sin)
plt.plot(x, y_cos)
plt.hlines([-1, 1], xmin, xmax, linestyles="dashed") # y=-1,Draw a dashed line on 1
plt.title(r"$\sin(x)$ and $\cos(x)$")
plt.xlim(xmin, xmax)
plt.ylim(-1.3, 1.3)
plt.show()
Specify the number of rows, columns, and plot number of the plot you want to fit in one figure
plt.subplot(Number of rows, number of columns, number of plots)
Let's divide the two functions in the previous figure into upper and lower parts. Since it is divided into upper and lower parts, the number of lines is 2. The number of columns is 1
plot_figure.py
xmin, xmax = -np.pi, np.pi
x = np.arange(xmin, xmax, 0.1)
y_sin = np.sin(x)
y_cos = np.cos(x)
#sin plot
plt.subplot(2,1,1)
plt.plot(x,y_sin)
plt.title(r"$\sin x$")
plt.xlim(xmin,xmax)
plt.ylim(-1.3,1.3)
#cos plot
plt.subplot(2,1,2)
plt.plot(x,y_cos)
plt.title(r"$\cos x$")
plt.xlim(xmin,xmax)
plt.ylim(-1.3,1.3)
plt.tight_layout() #Prevent title cover
plt.show()
--You can also write subplot (221) instead of subplot (2,1,1)
I studied with reference to Introduction to matplotlib.
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