问题
I have a numpy.array
, called grid
, with shape:
grid.shape = [N, M_1, M_2, ..., M_N]
The values of N, M_1, M_2, ..., M_N are known only after initialization.
For this example, let's say N=3 and M_1 = 20, M_2 = 17, M_3 = 9:
grid = np.arange(3*20*17*9).reshape(3, 20, 17, 9)
I am trying to loop over this array, as follows:
for indices, val in np.ndenumerate(grid[0]):
print indices
_some_func_with_N_arguments(*grid[:, indices])
At the first iteration, indices = (0, 0, 0) and:
grid[:, indices] # array with shape 3,3,17,9
whereas I want it to be an array of three elements only, much like:
grid[:, indices[0], indices[1], indices[2]] # array([ 0, 3060, 6120])
which however I cannot implement like in the above line, because I don't know a-priori what is the length of indices
.
I am using python 2.7, but a version-agnostic implementation is welcome :-)
回答1:
You can add slice(None)
to the index tuple manually:
>>> grid.shape
(3, 20, 17, 9)
>>> indices
(19, 16, 8)
>>> grid[:,19,16,8]
array([3059, 6119, 9179])
>>> grid[(slice(None),) + indices]
array([3059, 6119, 9179])
See here in the documentation for more.
回答2:
I think you want something like this:
In [134]: x=np.arange(24).reshape(4,3,2)
In [135]: x
Out[135]:
array([[[ 0, 1],
[ 2, 3],
[ 4, 5]],
[[ 6, 7],
[ 8, 9],
[10, 11]],
[[12, 13],
[14, 15],
[16, 17]],
[[18, 19],
[20, 21],
[22, 23]]])
In [136]: for i,j in np.ndindex(x[0].shape):
...: print(i,j,x[:,i,j])
...:
(0, 0, array([ 0, 6, 12, 18]))
(0, 1, array([ 1, 7, 13, 19]))
(1, 0, array([ 2, 8, 14, 20]))
(1, 1, array([ 3, 9, 15, 21]))
(2, 0, array([ 4, 10, 16, 22]))
(2, 1, array([ 5, 11, 17, 23]))
where the 1st line is:
In [142]: x[:,0,0]
Out[142]: array([ 0, 6, 12, 18])
Unpacking the index tuple as i,j
and using that in x[:,i,j]
is the simplest way of doing this index. But to generalize it to other numbers of dimensions I'll have to play with tuples a bit. x[i,j]
is the same as x[(i,j)]
.
In [147]: for ind in np.ndindex(x.shape[1:]):
...: print(ind,x[(slice(None),)+ind])
...:
((0, 0), array([ 0, 6, 12, 18]))
((0, 1), array([ 1, 7, 13, 19]))
...
with enumerate
:
for ind,val in np.ndenumerate(x[0]):
print(ind,x[(slice(None),)+ind])
回答3:
I believe what you are looking for is grid[1:][grid[0]]
.
grid = np.array([
[0, 2, 1], # N
[1, 9, 3, 6], # M_1
[7, 8, 2, 5, 0, 8, 3], # M_2
[4, 8] # M_3
])
np.array([grid[a[0] + 1][n] for a, n in np.ndenumerate(grid[0])])
# array([1, 2, 8])
来源:https://stackoverflow.com/questions/36561777/how-to-mix-numpy-slices-to-list-of-indices