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Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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numpy/stack_split/README.md
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@ -269,6 +269,61 @@ Output:
[18 19]]
```
np.split(a, [2, 5, 8, 9], axis=0) can be used for the following corresponding slices​:
||
|---|
|[:2,:]|​
|[2:5,:]|​
|[5:8,:]|​
|[8:9,:]|​
|[9:,:]|
```python
import numpy as np
a = np.arange(0, 20).reshape(10, 2)
print(a.shape) # -> (10, 2)
print()
b = np.split(a, [2, 5, 8, 9], axis=0)
print(len(b)) # -> 5
print(b[0])
print(b[0].shape) # -> (2, 2)
print()
print(b[1])
print(b[1].shape) # -> (3, 2)
print()
print(b[2])
print(b[2].shape) # -> (3, 2)
print()
print(b[3])
print(b[3].shape) # -> (1, 2)
print()
print(b[4])
print(b[4].shape) # -> (1, 2)
```
Output:
```python
[[0 1]
[2 3]]
[[4 5]
[6 7]
[8 9]]
[[10 11]
[12 13]
[14 15]]
[[16 17]]
[[18 19]]
```
```python
numpy.array_split(ary, indices_or_sections, axis=0)
```
@ -277,3 +332,39 @@ numpy.array_split(ary, indices_or_sections, axis=0)
>
> The only difference between these functions is that array_split allows indices_or_sections to be an integer that does not equally divide the axis. For an array of length l that should be split into n sections, it returns l % n sub-arrays of size l//n + 1 and the rest of size l//n.
```python
import numpy as np
a = np.arange(0, 20).reshape(10, 2)
print(a.shape) # -> (10, 2)
print()
b = np.array_split(a, 3, axis=0)
print(len(b)) # -> 3
print(b[0])
print(b[0].shape) # -> (4, 2)
print()
print(b[1])
print(b[1].shape) # -> (3, 2)
print()
print(b[2])
print(b[2].shape) # -> (3, 2)
```
Output:
```python
[[0 1]
[2 3]
[4 5]
[6 7]]
[[ 8 9]
[10 11]
[12 13]]
[[14 15]
[16 17]
[18 19]]
```