davrot/pytutorial
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

Update README.md

Browse source 
Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
This commit is contained in:
David Rotermund 2023-12-27 16:47:12 +01:00 committed by GitHub
parent f282e31103
commit 5380cd0421
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 138 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

138
numpy/broadcasting/README.md
View file

@ -84,3 +84,141 @@ A (2d array): 2 x 1
B (3d array): 8 x 4 x 3 # second from last dimensions mismatched
```
## at least
{: .topic-optional}
This is an optional topic!
### [numpy.atleast_1d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_1d.html)
```python
numpy.atleast_1d(*arys)
```
> Convert inputs to arrays with at least one dimension.
>
> Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved.
### [numpy.atleast_2d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_2d.html)
```python
numpy.atleast_2d(*arys)
```
> View inputs as arrays with at least two dimensions.
### [numpy.atleast_3d](https://numpy.org/doc/stable/reference/generated/numpy.atleast_3d.html)
```python
numpy.atleast_3d(*arys)
```
> View inputs as arrays with at least three dimensions.
### Example
```python
import numpy as np
a = np.atleast_1d(5)
print(a.shape) # -> (1,)
a = np.atleast_1d(a)
print(a.shape) # -> (1,)
a = np.atleast_2d(a)
print(a.shape) # -> (1, 1)
a = np.atleast_2d(a)
print(a.shape) # -> (1, 1)
a = np.atleast_3d(a)
print(a.shape) # -> (1, 1, 1)
a = np.atleast_3d(a)
print(a.shape) # -> (1, 1, 1)
a = np.atleast_1d(np.zeros((2)))
print(a.shape) # -> (2,)
a = np.atleast_2d(a)
print(a.shape) # -> (1, 2)
a = np.atleast_3d(a)
print(a.shape) # -> (1, 2, 1)
a = np.atleast_1d(np.zeros((2, 3)))
print(a.shape) # -> (2, 3)
a = np.atleast_2d(a)
print(a.shape) # -> (2, 3)
a = np.atleast_3d(a)
print(a.shape) # -> (2, 3, 1)
```
## Manual broadcast : [numpy.broadcast_to](https://numpy.org/doc/stable/reference/generated/numpy.broadcast_to.html)
{: .topic-optional}
This is an optional topic!
```python
numpy.broadcast_to(array, shape, subok=False)
```
> Broadcast an array to a new shape.
```python
import numpy as np
a = np.arange(0, 3)
print(a) # -> [0 1 2]
print(a.shape) # -> (3,)
b = np.broadcast_to(a, (3,3))
print(b)
print(b.shape) # -> (3,3)
```
Output:
```python
[[0 1 2]
[0 1 2]
[0 1 2]]
```
## Manual broadcast : [numpy.broadcast_arrays](https://numpy.org/doc/stable/reference/generated/numpy.broadcast_arrays.html)
{: .topic-optional}
This is an optional topic!
```python
numpy.broadcast_arrays(*args, subok=False)
```
> Broadcast any number of arrays against each other.
```python
import numpy as np
a = np.arange(0, 3).reshape(3, 1)
b = np.arange(0, 5).reshape(1, 5)
print(a.shape) # -> (3, 1)
print(b.shape) # -> (1, 5)
c, d = np.broadcast_arrays(a, b)
print(c.shape) # -> (3, 5)
print(d.shape) # -> (3, 5)
print(c)
print()
print(d)
```
Output:
```python
[[0 0 0 0 0]
[1 1 1 1 1]
[2 2 2 2 2]]
[[0 1 2 3 4]
[0 1 2 3 4]
[0 1 2 3 4]]
```