小细节

1.中文乱码

plt.rcParams['font.sans-serif'] = ['SimHei']
plt.rcParams['axes.unicode_minus'] = False

1.简单画图

import matplotlib.pyplot as plt
import numpy as np

# 画一条直线，一张图

# x = np.linspace(-1, 1, 50)
# y = 2 * x + 1
# plt.plot(x,y)
# plt.show()


# 画两条线，两个图

# x = np.linspace(-1, 1, 50)
# y1 = 2 * x + 1
# y2 = x ** 2
#
# plt.figure()
# plt.plot(x, y1)
#
# plt.figure(num=3, figsize=(8, 5))
# plt.plot(x, y2)
# plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--')  # 颜色，宽度，风格
#
# plt.show()

# 设置坐标轴

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1
y2 = x ** 2

plt.figure()

plt.plot(x, y2)
plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--')  # 颜色，宽度，风格
plt.xlim((-1, 2))
plt.ylim((-2, 3))
plt.xlabel('i am x')
plt.ylabel('i am y')

new_ticks = np.linspace(-1, 2, 5)
print(new_ticks)
plt.xticks(new_ticks)
plt.yticks([-2, -1.8, -1, 1.22, 3],
           [r'$really\ bad$', r'$bad \alpha$ ', r'$normal$', r'good', r'really good']
           )
plt.show()

2.设置坐标轴

# 设置坐标轴

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1
y2 = x ** 2

plt.figure()

plt.plot(x, y2)
plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--')  # 颜色，宽度，风格
plt.xlim((-1, 2))
plt.ylim((-2, 3))
plt.xlabel('i am x')
plt.ylabel('i am y')

new_ticks = np.linspace(-1, 2, 5)
print(new_ticks)
plt.xticks(new_ticks)
plt.yticks([-2, -1.8, -1, 1.22, 3],
           [r'$really\ bad$', r'$bad \alpha$ ', r'$normal$', r'good', r'$really\ good$'])
ax = plt.gca()
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
# 移动坐标轴
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()

3.图例

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-3, 3, 50)
y1 = 2 * x + 1
y2 = x ** 2

plt.figure()

plt.xlim((-1, 2))
plt.ylim((-2, 3))
plt.xlabel('i am x')
plt.ylabel('i am y')

new_ticks = np.linspace(-1, 2, 5)
print(new_ticks)
plt.xticks(new_ticks)
plt.yticks([-2, -1.8, -1, 1.22, 3],
           [r'$really\ bad$', r'$bad \alpha$ ', r'$normal$', r'good', r'$really\ good$'])
# plt.plot(x, y2, label='up')
# plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--', label='down')  # 颜色，宽度，风格
# plt.legend(loc='best')  

l1, = plt.plot(x, y2, label='up')
l2, = plt.plot(x, y1, color='red', linewidth=1.0, linestyle='--', label='down')  # 颜色，宽度，风格
plt.legend(handles=[l1, l2], labels=['aaa', 'bbb'], loc='best')  # 别名
plt.show()

4.标注

import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(-3, 3, 50)
y = 2 * x + 1
plt.plot(x, y)
plt.xlim((-3, 3))
plt.ylim((-6, 8))
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=50, color='b')
plt.plot([x0, x0], [0, y0], 'k--', lw=2.5)

# method 1
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'))
# method 2
plt.text(-3.7, 3, r'$This\ is\ the\ some\ text.\ \mu \sigma_i\ \alpha_t$',
         fontdict={'size': 16, 'color': 'r'})
plt.show()

5.散点图

import matplotlib.pyplot as plt
import numpy as np

n = 1024
X = np.random.normal(0, 1, n)  # 平均值是0，方差是1,生成n哥
Y = np.random.normal(0, 1, n)
T = np.arctan2(Y, X)  # 颜色由X，Y的值决定
plt.scatter(X, Y, s=75, c=T, alpha=0.5)

plt.xlim((-1.5, 1.5))
plt.ylim((-1.5, 1.5))

plt.xticks(())
plt.yticks(())  # 隐藏坐标
plt.show()

6.柱状图

import matplotlib.pyplot as plt
import numpy as np

n = 12
X = np.arange(n)
Y1 = (1 - X / float(n)) * np.random.uniform(0.5, 1.0, n)
Y2 = (1 - X / float(n)) * np.random.uniform(0.5, 1.0, n)
plt.bar(X, +Y1, facecolor='#9999ff', edgecolor='white')
plt.bar(X, -Y2, facecolor='#ff9999', edgecolor='white')

for x, y in zip(X, Y1):
    plt.text(x , y + 0.05, '%.2f' % y, ha='center', va='bottom')  # ha:横向对齐方式，va：纵向对齐方方式

for x, y in zip(X, Y2):
    plt.text(x, -y - 0.10, '%.2f' % y, ha='center', va='top')  # ha:横向对齐方式，va：纵向对齐方方式
plt.xlim((-.5, n,))
plt.ylim((-1.5, 1.5))
plt.xticks(())
plt.yticks(())  # 隐藏坐标
plt.show()

7.等高线

import matplotlib.pyplot as plt
import numpy as np


def f(x, y):
    return (1 - x / 2 + x ** 5 + y ** 3) * np.exp(-x ** 2 - y ** 2)


n = 256
x = np.linspace(-3, 3, n)
y = np.linspace(-3, 3, n)
X, Y = np.meshgrid(x, y)

plt.contourf(X, Y, f(X, Y), 8, alpha=0.75, cmap=plt.cm.hot)

C = plt.contour(X, Y, f(X, Y), 8, colors='black', linewidth=.5)
plt.clabel(C, inline=True, fontsize=10)# 把数字嵌入到线上

plt.xticks(())
plt.yticks(())  # 隐藏坐标
plt.show()

7.3D图像

import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

fig = plt.figure()
ax = Axes3D(fig)

X = np.arange(-4, 4, 0.25)
Y = np.arange(-4, 4, 0.25)
X, Y = np.meshgrid(X, Y)
R = np.sqrt(X ** 2 + Y ** 2)
Z = np.sin(R)

ax.plot_surface(X,Y,Z,rstride = 1,cstride =1 ,cmap=plt.get_cmap('rainbow'))
plt.show()

8. 子图

import matplotlib.pyplot as plt
import numpy as np

plt.figure()
plt.subplot(2, 1, 1)
plt.plot([0, 1], [0, 1])
plt.subplot(2, 3, 4)
plt.plot([0, 1], [0, 1])
plt.subplot(2, 3, 5)
plt.plot([0, 1], [0, 1])
plt.subplot(2, 3, 6)
plt.plot([0, 1], [0, 1])
plt.show()