在for循环python中使用数组

I am trying to run all the elements in just_test_data to all the elements in just_train_data, and return the lowest number, then run the new just_test_data through all the just_train_data, and so on until all the just_test_data has been run.

我试图将just_test_data中的所有元素运行到just_train_data中的所有元素,并返回最小的数字,然后通过所有just_train_data运行新的just_test_data,依此类推,直到所有的just_test_data都已运行。

The error I keep getting is in the line

我不断得到的错误就在于此

step_1 = (abs(just_test_data[i] - just_train_data[n]) ** 2)

IndexError: arrays used as indices must be of integer (or boolean) type

When I first try to run the loop.

当我第一次尝试运行循环时。

import numpy as np
testing_data = np.genfromtxt("C:\Users\zkrumlinde\Desktop\Statistical Programming\Week 3\iris-testing-data.csv", delimiter= ',')
training_data = np.genfromtxt("C:\Users\zkrumlinde\Desktop\Statistical Programming\Week 3\iris-training-data.csv", delimiter= ',')

#create 4 arrays, the first two with the measurements of training and testing data
#the last two have the labels of each line
just_test_data = np.array(testing_data[:, 0:4])
just_train_data = np.array(training_data[:, 0:4])
testing_labels = np.array(testing_data[:, 4])
training_labels = np.array(training_data[:, 4])

n = 0
while n < len(just_train_data):
    for i in just_test_data:
        old_distance = 'inf'
        step_1 = (abs(just_test_data[i] - just_train_data[n]) ** 2)
        step_2 = sum(step_1)
        new_distance = np.sqrt(step_2)
        if new_distance < old_distance:
            old_distance = new_distance
            index = n
        n = n + 1
print(training_labels[index])

2 个解决方案

#1

By using for i in just_test_data you're iterating through all the elements in the just_test_data array and not and index between 0 and the array length.

通过在just_test_data中使用for i,您将遍历just_test_data数组中的所有元素,而不是在0和数组长度之间进行索引。

Also, it seems that your n = n + 1 line is not indented correctly.

此外,您的n = n + 1行似乎没有正确缩进。

Here's my guess for an updated version of your code:

以下是我对代码更新版本的猜测:

import numpy as np
testing_data = np.genfromtxt("C:\Users\zkrumlinde\Desktop\Statistical Programming\Week 3\iris-testing-data.csv", delimiter= ',')
training_data = np.genfromtxt("C:\Users\zkrumlinde\Desktop\Statistical Programming\Week 3\iris-training-data.csv", delimiter= ',')

#create 4 arrays, the first two with the measurements of training and testing data
#the last two have the labels of each line
just_test_data = np.array(testing_data[:, 0:4])
just_train_data = np.array(training_data[:, 0:4])
testing_labels = np.array(testing_data[:, 4])
training_labels = np.array(training_data[:, 4])

n = 0
while n < len(just_train_data):
    for i in range(len(just_test_data)):
        old_distance = 'inf'
        step_1 = (abs(just_test_data[i] - just_train_data[n]) ** 2)
        step_2 = sum(step_1)
        new_distance = np.sqrt(step_2)
        if new_distance < old_distance:
            old_distance = new_distance
            index = n
    n = n + 1
print(training_labels[index])

#2

when you say for i in just_test_data: i will be the element itself, not the index.

当你在just_test_data中为我说:我将是元素本身,而不是索引。

you probably want something like for i in range(len(just_test_data)) this will have i as a number from 0 to the length of just_test_data - 1.

你可能想要像我在范围内的东西(len(just_test_data))这将有一个从0到just_test_data - 1长度的数字。

edit: a few weird things in your code:

编辑:代码中的一些奇怪的东西:

step_1 = (abs(just_test_data[i] - just_train_data[n]) ** 2)
step_2 = sum(step_1)
new_distance = np.sqrt(step_2)

this just returns abs(just_test_data[i] - just_train_data[n]). are you meaning to add a ton of step_1 up and then eventually take the sqrt? you need to check your indents.

这只是返回abs(just_test_data [i] - just_train_data [n])。你是想增加一大步step_1然后最终采取sqrt?你需要检查你的缩进。

old_distance = 'inf' is a string (pretty sure). you are probably looking for either np.inf or float('inf'). Also because you set this inside the for loop, it is getting reset for every i. you probably want it above 'for i in just_test_data:'

old_distance ='inf'是一个字符串(非常肯定)。你可能正在寻找np.inf或float('inf')。另外因为你在for循环中设置了它,它会被重置为每个i。你可能想要它在'just_test_data:'我

a quick pass at your code:

快速通过您的代码:

min_distance = np.inf
for n in range(len(just_train_data)):
    step_2 = 0
    for i in range(len(just_test_data)):
        step_1 = (just_test_data[i] - just_train_data[n]) ** 2
        step_2 += step_1
    distance = np.sqrt(step_2)
    if distance < min_distance:
        min_distance = distance
        index = n
print(training_labels[index])

This compares a point in just_train_data to all the points in just_test_data to compute a distance. It will print the minimum of these distances.

这将just_train_data中的点与just_test_data中的所有点进行比较以计算距离。它将打印这些距离的最小值。

#1