bradhilton / numpy_ext

An extension library for NumPy that implements common array operations not present in NumPy

NumPy Extensions

An extension library for NumPy that implements common array operations not present in NumPy.

• npext.fill_na(...)
• npext.drop_na(...)
• npext.rolling(...)
• npext.expanding(...)
• npext.rolling_apply(...)
• npext.expanding_apply(...)
• # etc

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Documentation

• API Reference

Installation

Regular installation:

pip install numpy_ext

For development:

git clone https://github.com/3jane/numpy_ext.git
cd numpy_ext
pip install -e .[dev]  # note: make sure you are using pip>=20

Examples

Here are few common examples of how the library is used. The rest is available in the documentation.

1. Apply a function to a rolling window over the provided array

import numpy as np
import numpy_ext as npext

a = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
window = 3

npext.rolling_apply(np.sum, window, a)

> array([nan, nan,  3.,  6.,  9., 12., 15., 18., 21., 24.])

2. Same as the above, but with a custom function, two input arrays and parallel computation using joblib:

def func(array_first, array_second, param):
    return (np.min(array_first) + np.sum(array_second)) * param


a = np.array([0, 1, 2, 3])
b = np.array([3, 2, 1, 0])

npext.rolling_apply(func, 2, a, b, n_jobs=2, param=-1)

> array([nan, -5., -4., -3.])

3. Same as the first example, but using rolling function:

a = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
window = 3

rolls = npext.rolling(a, window, as_array=True)

np.sum(rolls, axis=1)

> array([nan, nan,  3.,  6.,  9., 12., 15., 18., 21., 24.])

License

The software is distributed under MIT license.