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README.md

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```
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### Call Graph
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**Generates a PNG image of call graph with highlighted bottlenecks.**
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#### Generates a PNG image of call graph with highlighted bottlenecks:
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```python
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# $ pip3 install pycallgraph
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```
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### Broadcasting
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**Broadcasting is a set of rules by which NumPy functions operate on arrays of different sizes and/or dimensions:**
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**Broadcasting is a set of rules by which NumPy functions operate on arrays of different sizes and/or dimensions.**
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```python
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left = [[0.1], [0.6], [0.8]] # Shape: (3, 1)
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right = [ 0.1 , 0.6 , 0.8 ] # Shape: (3)
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```
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**1. If array shapes differ, left-pad the smaller shape with ones.**
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#### 1. If array shapes differ, left-pad the smaller shape with ones:
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```python
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left = [[0.1], [0.6], [0.8]] # Shape: (3, 1)
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right = [[0.1 , 0.6 , 0.8]] # Shape: (1, 3) <- !
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```
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**2. If any dimensions differ in size, expand the ones that have size 1 by duplicating their elements.**
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#### 2. If any dimensions differ in size, expand the ones that have size 1 by duplicating their elements:
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```python
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left = [[0.1, 0.1, 0.1], [0.6, 0.6, 0.6], [0.8, 0.8, 0.8]] # Shape: (3, 3) <- !
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right = [[0.1, 0.6, 0.8], [0.1, 0.6, 0.8], [0.1, 0.6, 0.8]] # Shape: (3, 3) <- !
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```
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**3. If neither non-matching dimension has size 1, rise an error.**
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#### 3. If neither non-matching dimension has size 1, rise an error.
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### Example
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**For each point returns index of its nearest point: `[0.1, 0.6, 0.8] => [1, 2, 1]`.**
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#### For each point returns index of its nearest point: `[0.1, 0.6, 0.8] => [1, 2, 1]`
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```python
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>>> points = np.array([0.1, 0.6, 0.8])

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