Question

我正在尝试理解python代码，该代码使用$ wine REG QUERY "HKLM\Software\Microsoft\Windows NT\CurrentVersion" /v ProductName HKEY_LOCAL_MACHINE\Software\Microsoft\Windows NT\CurrentVersion ProductName REG_SZ Microsoft Windows 7将4维numpy数组numpy.einsum()转换为2维或3维数组。传递给A的下标如下：

numpy.einsum()

等按照（Understanding NumPy's einsum和（Python - Sum 4D Array）的答案，我尝试使用Mat1 = np.einsum('aabb->ab', A) Mat2 = np.einsum('abab->ab', A) Mat3 = np.einsum('abba->ab', A) T1 = np.einsum('abcb->abc' A) T2 = np.einsum('abbc->abc', A)来理解上述下标的含义，例如numpy.sum()，但我无法复制结果，这是我用Mat1 = np.sum(A, axis=(0,3))获得的。有人可以解释在numpy.einsum()中如何解释这些下标吗？

Answer 1

我建议您阅读Einstein notation on Wikipedia。

这是您问题的简短答案：

np.einsum('aabb->ab', A)

表示：

res = np.empty((max_a, max_b), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    res[a, b] = A[a, a, b, b]
return res

简短说明：
aabb表示索引及其相等性（请参见A[a, a, b, b]）；
->ab表示形状为(max_a, max_b)，并且您不需要在这两个索引上有两个具有和。（如果它们也是c，那么您应将所有内容用c求和，因为它们不会在->之后出现）

其他示例：

np.einsum('abab->ab', A)

# Same as (by logic, not by actual code)

res = np.empty((max_a, max_b), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    res[a, b] = A[a, b, a, b]
return res

np.einsum('abba->ab', A) 

# Same as (by logic, not by actual code)

res = np.empty((max_a, max_b), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    res[a, b] = A[a, b, b, a]
return res

np.einsum('abcb->abc', A)

# Same as (by logic, not by actual code)

res = np.empty((max_a, max_b, max_c), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    for c in range(max_c):
      res[a, b, c] = A[a, b, c, b]
return res

np.einsum('abbc->abc', A)

# Same as (by logic, not by actual code)

res = np.empty((max_a, max_b, max_c), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    for c in range(max_c):
      res[a, b, c] = A[a, b, b, c]
return res

一些代码来检查它是否真实：

import numpy as np


max_a = 2
max_b = 3
max_c = 5

shape_1 = (max_a, max_b, max_c, max_b)
A = np.arange(1, np.prod(shape_1) + 1).reshape(shape_1)

print(A)
print()
print(np.einsum('abcb->abc', A))
print()

res = np.empty((max_a, max_b, max_c), dtype=A.dtype)
for a in range(max_a):
  for b in range(max_b):
    for c in range(max_c):
      res[a, b, c] = A[a, b, c, b]

print(res)
print()

传递给numpy.einsum（）的下标是什么意思？

1 个答案: