davrot/pytutorial
1
0
Fork 0
mirror of https://github.com/davrot/pytutorial.git synced 2025-04-18 21:26:41 +02:00
Code Issues 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 2023-12-15 10:16:33 +01:00 • committed by GitHub
parent 64751246ba
commit 262c80023e
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
1 changed files with 129 additions and 0 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

129
numpy/ndarray/README.md
View file

@ -275,6 +275,135 @@ Output:
[0 1 2 3 4 5]
```
## [numpy.ndarray.flat](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flat.html)
```python
ndarray.flat
```
> A 1-D iterator over the array.
>
> This is a numpy.flatiter instance, which acts similarly to, but is not a subclass of, Python’s built-in iterator object.
```python
import numpy as np
A = np.arange(0, 6)
A = A.reshape((2, 3))
print(A.flat[0]) # -> 0
print(A.flat[1]) # -> 1
print(A.flat[2]) # -> 2
print(A.flat[3]) # -> 3
print(A.flat[4]) # -> 4
print(A.flat[5]) # -> 5
for i in A:
print(i)
print("----")
for i in A.flat:
print(i)
```
Output:
```python
[0 1 2]
[3 4 5]
----
0
1
2
3
4
5
```
## [numpy.ndarray.dtype](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.dtype.html)
```python
ndarray.dtype
```
> Data-type of the array’s elements.
```python
import numpy as np
A = np.zeros((0, 6), dtype=np.float32)
print(A.dtype) # -> float32
B = A.astype(dtype=np.int64)
print(B.dtype) # -> int64
print(np.may_share_memory(A, B)) # -> False
```
## [numpy.ndarray.astype](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.astype.html)
```python
ndarray.astype(dtype, order='K', casting='unsafe', subok=True, copy=True)
```
> Copy of the array, cast to a specified type.
```python
import numpy as np
A = np.zeros((0, 6), dtype=np.float32)
print(A.dtype) # -> float32
B = A.astype(dtype=np.int64)
print(B.dtype) # -> int64
print(np.may_share_memory(A, B)) # -> False
```
## Complex numbers
### [numpy.ndarray.real](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.real.html)
```python
ndarray.real
```
> The real part of the array.
```python
import numpy as np
A = np.array(1 + 0.5j)
print(A.real) # -> 1.0
```
### [numpy.ndarray.imag](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.imag.html)
```python
ndarray.imag
```
> The imaginary part of the array.
```python
import numpy as np
A = np.array(1 + 0.5j)
print(A.imag) # -> 0.5
```
### [numpy.ndarray.conj](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.conj.html)
```python
ndarray.conj()
```
> Complex-conjugate all elements.
```python
import numpy as np
A = np.array(1 + 0.5j)
print(A.conj()) # -> (1-0.5j)
```
## [Array methods](https://numpy.org/doc/stable/reference/arrays.ndarray.html#array-methods)