Question

我试图将数组中的条件值插入到精确位置的空数组中。

empty_array = np.zeros([40,100])
for x in range (1,24):
    array[x,:,:] #which is also sized 40x100
    if the_values_in_the_array < 0.25:
         the_values_in_the_array = 0
    empty_array = empty_array + array [x,:,:]

我应该将哪种语法用于此逻辑？我应该如何扫描the_values_in_the_array以找到条件值？

Answer 1

empty_array = np.zeros([40,100])
array = np.random.rand(24,40,100)

array[array<0.25]=0 # change all the values which is <0.25 to 0
for x in range(1,24):
    empty_array += array[x,:,:]

Answer 2

我认为这是你要做的操作。我建议使用np.where例程将小于0.25的值设置为零。然后，您可以只计算数组的第一个维度，以获得您正在寻找的输出数组。我减少了示例中问题的维度。

import numpy as np

vals = np.random.random([24, 2, 3])
vals_filtered = np.where(vals < 0.25, 0.0, vals)
out = vals_filtered.sum(axis=0)
print("First sample array has the slice vals[0,:,:]:\n{}\n".format(vals[0, :, :]))
print("First sample array with vals>0.25 set to 0.0:\n{}\n".format(vals_filtered[0, :, :]))
print("Output array is the sum over the first dimension:\n{}\n".format(out))

返回以下输出。

First sample array has the slice vals[0, :, :]: 
[[ 0.16272567  0.13695067  0.5954866 ]
 [ 0.50367823  0.8519252   0.3000367 ]]

First sample array with vals>0.25 set to 0.0: 
[[ 0.          0.          0.5954866 ]
 [ 0.50367823  0.8519252   0.3000367 ]]

Output array is the sum over the first dimension: 
[[ 11.12707813  12.04175706  11.5812803 ]
 [ 13.73036272   9.3988165   12.41808745]]

这是您要找的计算吗？调用vals.sum(axis=0)是一种更快速的操作方式。调用numpy的内置数组例程通常更好，而不是显式的for循环。

在数组中查找特定值

2 个答案: