Create README.md
Signed-off-by: David Rotermund <54365609+davrot@users.noreply.github.com>
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numpy/stack_split/README.md
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# Stack and Split
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{:.no_toc}
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<nav markdown="1" class="toc-class">
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* TOC
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{:toc}
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</nav>
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## The goal
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Questions to [David Rotermund](mailto:davrot@uni-bremen.de)
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{: .topic-optional}
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This is an optional topic!
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## [numpy.column_stack](https://numpy.org/doc/stable/reference/generated/numpy.column_stack.html)
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```python
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numpy.column_stack(tup)
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```
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> Stack 1-D arrays as columns into a 2-D array.
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>
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> Take a sequence of 1-D arrays and stack them as columns to make a single 2-D array. 2-D arrays are stacked as-is, just like with hstack. 1-D arrays are turned into 2-D columns first.
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```python
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import numpy as np
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a = np.arange(0, 10)
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print(a) # -> [0 1 2 3 4 5 6 7 8 9]
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print(a.shape) # -> (10,)
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b = np.column_stack((a, a))
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print(b)
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print(b.shape) # -> (10, 2)
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```
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Output:
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```python
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[[0 0]
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[1 1]
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[2 2]
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[3 3]
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[4 4]
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[5 5]
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[6 6]
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[7 7]
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[8 8]
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[9 9]]
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```
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## [numpy.row_stack](https://numpy.org/doc/stable/reference/generated/numpy.row_stack.html)
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```python
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numpy.row_stack(tup, *, dtype=None, casting='same_kind')
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```
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> Stack arrays in sequence vertically (row wise).
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>
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> This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit.
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>
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> This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions concatenate, stack and block provide more general stacking and concatenation operations.
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>
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> np.row_stack is an alias for vstack. They are the same function.
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```python
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import numpy as np
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a = np.arange(0, 10)
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print(a) # -> [0 1 2 3 4 5 6 7 8 9]
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print(a.shape) # -> (10,)
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b = np.row_stack((a, a))
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print(b)
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print(b.shape) # -> (2, 10)
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```
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Output:
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```python
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[[0 1 2 3 4 5 6 7 8 9]
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[0 1 2 3 4 5 6 7 8 9]]
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```
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