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1.np.arange
import numpy as np
x = np.arange(3)#[0 1 2]
print(x)
x = np.arange(3.0)#[0. 1. 2.]
print(x)
x = np.arange(3,7)#[3 4 5 6]
print(x)
x = np.arange(3,7,2)#[3 5]
print(x) -
2.linspace
import numpy as np
x = np.linspace(2.0, 3.0, num=5)
print(x)#[2. 2.25 2.5 2.75 3. ]
#[2. 2.2 2.4 2.6 2.8]
x = np.linspace(2.0, 3.0, num=5, endpoint=False)
print(x)
x = np.linspace(2.0, 3.0, num=5, retstep=True)
print(x)
import matplotlib.pyplot as plt
N = 5
y = np.zeros(N)
x1 = np.linspace(0, 10, N, endpoint=True)
print(“x1”+str(x1))
x2 = np.linspace(0, 10, N, endpoint=False)
print(“x2”+str(x2))
plt.plot(x1, y, ‘o’)
plt.plot(x2, y + 0.5, ‘o’)
plt.ylim([-0.5, 1])
(-0.5, 1)
plt.show() -
3.meshgrid
import numpy as np
#np.meshgrid 从坐标向量返回坐标矩阵
x = np.arange(-2,2)#[-2 -1 0 1]
y = np.arange(0,3)#[0 1 2]
#生成一维数组,其实也是向量
print(“x=”+str(x))
print(“y=”+str(y))
z, s = np.meshgrid(x, y)#将两个一维数组变为二维数组
print(“z=”+str(z))
print(“s=”+str(s))
“”"
z=[[-2 -1 0 1]
[-2 -1 0 1]
[-2 -1 0 1]]
s=[[0 0 0 0]
[1 1 1 1]
[2 2 2 2]]
“”"
“”"
也就是说,它将 x 变成了矩阵 z 的行向量,
y 变成了矩阵 s 的列向量。
反过来,也是一样的:
“”"
z, s = np.meshgrid(y,x)
print(“z=”+str(z))
print(“s=”+str(s))
“”"
z=[[0 1 2]
[0 1 2]
[0 1 2]
[0 1 2]]
s=[[-2 -2 -2]
[-1 -1 -1]
[ 0 0 0]
[ 1 1 1]]
“”"