从1D阵列创建3D阵列的有效方式

Question

我有一个2D数组，它的前3列表示x、y、z坐标，最后一列包含一些数据。我正在尝试使用最后一列的数据创建一个三维阵列。我为此编写的代码有3个for循环。如果有人能对此代码提出改进建议，或者有其他更好的方法来获得相同的解决方案，我将不胜感激。

tempData = np.loadtxt(cwd+'/T_t0-t20.txt', comments='%', usecols=(0,1,2,3))   
x = np.sort(np.unique(tempData[:, 0]))
y = np.sort(np.unique(tempData[:, 1]))
z = np.sort(np.unique(tempData[:, 2]))
temp = np.zeros((len(x),len(y),len(z)))
for i in range(len(x)):
for j in range(len(y)):
for k in range(len(z)):            
xind = np.where(tempData[:,0]==x[i])[0]
yind = np.where(tempData[:,1]==y[j])[0]
zind = np.where(tempData[:,2]==z[k])[0]                
Tind = np.intersect1d(np.intersect1d(xind, yind), zind)[0]                          
temp[i,j,k] = tempData[:,3][Tind]

以下是示例输入2D阵列(tempData(：

[[ 0.0000e+00 -2.1429e-02  0.0000e+00  8.5963e+02]
[ 2.0202e-02 -2.1429e-02  0.0000e+00  8.1597e+02]
[ 4.0404e-02 -2.1429e-02  0.0000e+00  7.7315e+02]
[ 0.0000e+00  0.0000e+00  0.0000e+00  9.1180e+02]
[ 2.0202e-02  0.0000e+00  0.0000e+00  8.5293e+02]
[ 4.0404e-02  0.0000e+00  0.0000e+00  7.9282e+02]
[ 0.0000e+00  2.1429e-02  0.0000e+00  8.2700e+02]
[ 2.0202e-02  2.1429e-02  0.0000e+00  8.1224e+02]
[ 4.0404e-02  2.1429e-02  0.0000e+00  7.7315e+02]
[ 0.0000e+00 -2.1429e-02 -2.2222e-02  8.5946e+02]
[ 2.0202e-02 -2.1429e-02 -2.2222e-02  8.1589e+02]
[ 4.0404e-02 -2.1429e-02 -2.2222e-02  7.7315e+02]
[ 0.0000e+00  0.0000e+00 -2.2222e-02  9.1153e+02]
[ 2.0202e-02  0.0000e+00 -2.2222e-02  8.5278e+02]
[ 4.0404e-02  0.0000e+00 -2.2222e-02  7.9278e+02]
[ 0.0000e+00  2.1429e-02 -2.2222e-02  8.2689e+02]
[ 2.0202e-02  2.1429e-02 -2.2222e-02  8.1216e+02]
[ 4.0404e-02  2.1429e-02 -2.2222e-02  7.7315e+02]
[ 0.0000e+00 -2.1429e-02 -4.4444e-02  8.3552e+02]
[ 2.0202e-02 -2.1429e-02 -4.4444e-02  8.0395e+02]
[ 4.0404e-02 -2.1429e-02 -4.4444e-02  7.7315e+02]
[ 0.0000e+00  0.0000e+00 -4.4444e-02  8.7343e+02]
[ 2.0202e-02  0.0000e+00 -4.4444e-02  8.3067e+02]
[ 4.0404e-02  0.0000e+00 -4.4444e-02  7.8726e+02]
[ 0.0000e+00  2.1429e-02 -4.4444e-02  8.1191e+02]
[ 2.0202e-02  2.1429e-02 -4.4444e-02  8.0125e+02]
[ 4.0404e-02  2.1429e-02 -4.4444e-02  7.7315e+02]]

这是预期输出数组(温度(：

[[[835.52 859.46 859.63]
[873.43 911.53 911.8 ]
[811.91 826.89 827.  ]]
[[803.95 815.89 815.97]
[830.67 852.78 852.93]
[801.25 812.16 812.24]]
[[773.15 773.15 773.15]
[787.26 792.78 792.82]
[773.15 773.15 773.15]]]

Answer 1

我发现了一种使用Numpy的lexsort的更好(高效(的方法。这完全避免了的循环。这里执行多列排序，先沿"x"，然后沿"y"，再沿"z"。这是代码：

x = np.sort(np.unique(tempData[:, 0]))
y = np.sort(np.unique(tempData[:, 1]))
z = np.sort(np.unique(tempData[:, 2]))
tempData = tempData[np.lexsort(np.transpose(tempData)[::-1])]
temp = np.array(tempData[:, 3]).reshape((len(x),len(y),len(z)))