假设我有一个3d（10x3）np.array：
orgArr = [[ 30.1678 -173.569 725.724 ]
[ 29.9895 -173.34 725.76 ]
[ 29.9411 -173.111 725.768 ]
[ 29.9306 -173.016 725.98 ]
[ 29.6754 -172.621 725.795 ]
[ 29.5277 -172.274 725.903 ]
[ 29.585 -171.978 726.111 ]
[ 29.4114 -171.507 726.188 ]
[ 29.3951 -170.947 726.173 ]
[ 29.3577 -170.196 726.384 ]]
对于每一列，我生成rondom数，在各列的最小值和最大值之间，例如，对于第一列：
# Find min/max
colXMin = np.min(orgArr[:, 0])
colXMax = np.max(orgArr[:, 0])
# Generate random number between min/max
size = 12
addRandomToColX = self.create_random_floats(colXMin, colXMax, size)
# Sort the random numbers
sortRandomColX= sorted(addRandomToColX, reverse= True)
print('sortRandomColX:', sortRandomColX)
# Do same for cols y and z
...
# Create 3d array finally
randomArr = np.array([sortRandomColX, sortRandomColY, sortRandomColZ]).T
print('randomArr:', randomArr)
def create_random_floats(low, high, size):
return [random.uniform(low, high) for _ in range(size)]
所以我得到12x3数组，按照给定的顺序排序。 col x减小，但y和z增加：
randomArr:
[[ 30.16564103 -173.45321119 725.74404996]
[ 30.03986524 -173.17110927 725.84951132]
[ 29.97088507 -173.15435901 725.85341553]
[ 29.79273295 -172.76247176 725.97347288]
[ 29.53294671 -170.90169722 726.27944054]
[ 29.53182418 -170.88261603 726.34089036]
[ 29.52163245 -170.72931883 726.34411865]
[ 29.50194557 -170.71866152 726.34946239]
[ 29.45834997 -170.68671434 726.36413176]
[ 29.4426014 -170.57381107 726.37110357]
[ 29.43702889 -170.40826716 726.45476367]
[ 29.3621429 -169.77240546 726.51968671]]
如何在orgArr数据中随机重新插入/混合randomArr并分发整个大小？我的意思是不在randomArr的开头或结尾。否则，单个列的排序顺序将被破坏。
答案 0 :(得分：2)
一种解决方案，主要依靠numpy。但是，对于反转列顺序的部分并不满意。但这不会将数组作为参数。
import numpy as np
orgArr = np.asarray([[ 30.1678, -173.569, 725.724 ],
[ 29.9895, -173.34, 725.76 ],
[ 29.9411, -173.111, 725.768 ],
[ 29.9306, -173.016, 725.98 ],
[ 29.6754, -172.621, 725.795 ],
[ 29.5277, -172.274, 725.903 ],
[ 29.585, -171.978, 726.111 ],
[ 29.4114, -171.507, 726.188 ],
[ 29.3951, -170.947, 726.173 ],
[ 29.3577, -170.196, 726.384 ]])
#number of rows to add
n2add = 12
#min/max for each column
orgMin = np.min(orgArr, axis = 0)
orgMax = np.max(orgArr, axis = 0)
#generate array with random values between min/max of each column
randomArr = (orgMax - orgMin) * np.random.random((n2add + orgArr.shape[0], orgArr.shape[1])) + orgMin
#insert original values
randomArr[:orgArr.shape[0], :] = orgArr
#sort values
randomArr.sort(axis = 0)
#determines for each column, if direction of order in orgArr is the same as in randomArr
#and reverses column order, if not
col_ord = np.sign((orgArr[0,:] - orgArr[-1,:])) * np.sign((randomArr[0,:] - randomArr[-1,:]))
for i in range(orgArr.shape[1]):
if col_ord[i] < 0:
randomArr[:,i] = randomArr[::-1,i]
示例输出：
#randomArr
[[ 30.1678 -173.569 725.724 ]
[ 30.11384713 -173.34 725.76 ]
[ 30.02906243 -173.23713466 725.768 ]
[ 29.9895 -173.111 725.795 ]
[ 29.94555434 -173.016 725.83462631]
[ 29.9411 -172.78230979 725.903 ]
[ 29.9306 -172.6898037 725.95312697]
[ 29.92622676 -172.621 725.98 ]
[ 29.91989733 -172.44033232 726.01484565]
[ 29.91581341 -172.42239247 726.08304636]
[ 29.89624414 -172.30021976 726.08525885]
[ 29.84977922 -172.29533928 726.08784464]
[ 29.80493116 -172.274 726.10620276]
[ 29.6754 -172.03366934 726.111 ]
[ 29.63979452 -171.978 726.14750753]
[ 29.585 -171.67822537 726.1535495 ]
[ 29.5277 -171.507 726.173 ]
[ 29.49315771 -171.33446469 726.18671858]
[ 29.42592778 -171.15097712 726.188 ]
[ 29.4114 -170.947 726.24372921]
[ 29.3951 -170.87844982 726.29369897]
[ 29.3577 -170.196 726.384 ]]
您还可以使用此脚本使用其他分发功能，numpy和scipy提供各种各样的功能。例如。对于np.random.normal(mu, sigma, n)：
randomArr = (orgMax - orgMin) * np.random.normal(0.1, 0.001, (n2add + orgArr.shape[0], orgArr.shape[1])) + orgMin
如果您现在查看输出数组，您会注意到可以在数组的一端找到新生成的值（由更多数字表示）。但请注意不要超过您的分配功能的限制（0,1）。示例mu = 0.1 sigma = 0.001极端显示对最终分布的影响。 0.5/0.2可以正常使用，但您不会收到0.5/5的错误消息，该消息将超出初始范围。