python遍历数组获取下标_讲解Python3中NumPy数组寻特
定元素下标的两种⽅法
引⼦
Matlab中有⼀个函数叫做find，可以很⽅便地寻数组内特定元素的下标，即：Find indices and values of nonzero elements。
这个函数⾮常有⽤。⽐如，我们想计算图1中点Q(x0, y0)抛物线的最短距离。⼀个可以实施的⽅法是：计算出抛物线上所有点到Q点的距离，到最⼩值，⽤find函数到最⼩值对应的下标，即M点横坐标和纵坐标对应的元素的下标，M点到Q点的距离就是最短距离。
⾸先给出Matlab使⽤find函数实现的代码：
a = linspace(-5,5,1000);
b = a .^2;
x0 = 4;
y0 = 4;
dis = sqrt((a - x0).^2 + (b - y0).^2);
mm = find (dis == min(dis));
a0 = a(mm);
b0 = b(mm);
disMin = sqrt((a0 - x0).^2 + (b0 - y0).^2);
plot(a, b);
hold on;
scatter(x0, y0, 'k*');
scatter(a0, b0, 'k*');
xx = [a0, x0];
yy = [b0, y0];
plot(xx, yy);
NumPy中的where函数
Syntax: np.where(conditions, [x,y])
具体实现代码如下：
import numpy as np
import math
import matplotlib.pyplot as plt
a = np.linspace(-5, 5, 10000)
b = a * a
x0 = 4
y0 =4
num = np.linspace(0, len(a) - 1, len(a))
dis = np.linspace(0, 0, len(a))
for k in num:
k = int(k)
dis[k] = dis[k] + math.sqrt((a[k] -x0) **2 + (b[k] - y0) **2)
disMin = min(dis)
disMinIndex = np.where(dis == disMin)
disMin0 = math.sqrt((a[disMinIndex] - x0) **2 + (b[disMinIndex] - y0) **2) print('The mininum distance:',disMin)
print('The mininum distance:',disMin0)
print(type(dis))
a0 = a[disMinIndex]
b0 = b[disMinIndex]
fig = plt.figure(figsize = (6,6), dpi = 200)
ax1 = plt.subplot(1,1,1)
line11 = ax1.scatter(a,b,s = 1)
line12 = ax1.scatter(x0, y0, s = 100, marker = '*', color = 'darkorange') line13 = ax1.scatter(a0, b0, s = 100, marker = '*', color = 'darkorange') line14 = ax1.plot([x0,a0],[y0,b0], color = 'darkorange')
line15 = (4.2,4,'Q(x0,y0)')
line16 = (0.6,5, 'M(a0,b0)')
line18 = plt.xlim(-5,5)
line17 = plt.ylim(0,25)
plt.savefig('C:/Users/BRIAR/Desktop/index.png')
plt.show()
The mininum distance: 1.943317035
The mininum distance: 1.9433170350024023
class ‘numpy.ndarray'
List中的index函数
Syntax: List.index(aimElement)
注意：此处需将NumPy数组转换成List格式的数据。
具体实现代码如下：
import numpy as np
import math
import matplotlib.pyplot as plt
a = np.linspace(-5, 5, 10000)
b = a * a
x0 = 4
y0 =4
num = np.linspace(0, len(a) - 1, len(a))
dis = np.linspace(0, 0, len(a))
for k in num:
k = int(k)
dis[k] = dis[k] + math.sqrt((a[k] -x0) **2 + (b[k] - y0) **2)
disMin = min(dis)
disList = list()
python获取数组长度
disMinIndex = disList.index(disMin)
disMin0 = math.sqrt((a[disMinIndex] - x0) **2 + (b[disMinIndex] - y0) **2) print('The mininum distance:',disMin)
print('The mininum distance:',disMin0)
print(type(disList))
a0 = a[disMinIndex]
b0 = b[disMinIndex]
fig = plt.figure(figsize = (6,6), dpi = 200)
ax1 = plt.subplot(1,1,1)
line11 = ax1.scatter(a,b,s = 1)
line12 = ax1.scatter(x0, y0, s = 100, marker = '*', color = 'darkorange') line13 = ax1.scatter(a0, b0, s = 100, marker = '*', color = 'darkorange') line14 = ax1.plot([x0,a0],[y0,b0], color = 'darkorange')
line15 = (4.2,4,'Q(x0,y0)')
line16 = (0.6,5, 'M(a0,b0)')
line18 = plt.xlim(-5,5)
line17 = plt.ylim(0,25)
plt.savefig('C:/Users/BRIAR/Desktop/index.png')
plt.show()
The mininum distance: 1.943317035
The mininum distance: 1.9433170350024023
class ‘list'
以上就是本⽂的全部内容，希望对⼤家的学习有所帮助，也希望⼤家多多⽀持我们。本⽂标题: 讲解Python3中NumPy数组寻特定元素下标的两种⽅法

版权声明：本站内容均来自互联网，仅供演示用，请勿用于商业和其他非法用途。如果侵犯了您的权益请与我们联系QQ:729038198，我们将在24小时内删除。