imops 0.4.1

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Imops

Efficient parallelizable algorithms for multidimensional arrays to speed up your data pipelines

Install

pip install imops

Features

Fast Radon transform

from imops import radon, inverse_radon

Fast linear/bilinear/trilinear zoom

from imops import zoom
from imops import zoom_to_shape

# fast zoom with optional fallback to scipy's implementation
y = zoom(x, 2, axis=[0, 1])
# a handy function to zoom the array to a given shape 
# without the need to compute the scale factor
z = zoom_to_shape(x, (4, 120, 67))

Works faster only for ndim<=3, dtype=float32 or float64, output=None, order=1, mode='constant', grid_mode=False

Fast 1d linear interpolation

from imops import interp1d  # same as `scipy.interpolate.interp1d`

Works faster only for ndim<=3, dtype=float32 or float64, order=1 or 'linear'

Padding

from imops import pad, pad_to_shape

y = pad(x, 10, axis=[0, 1])
# `ratio` controls how much padding is applied to left side:
# 0 - pad from right
# 1 - pad from left
# 0.5 - distribute the padding equally
z = pad_to_shape(x, (4, 120, 67), ratio=0.25)

Cropping

from imops import crop_to_shape

# `ratio` controls the position of the crop
# 0 - crop from right
# 1 - crop from left
# 0.5 - crop from the middle
z = crop_to_shape(x, (4, 120, 67), ratio=0.25)

Acknowledgements

Some parts of our code for radon/inverse radon transform as well as the code for linear interpolation are inspired by the implementations from scikit-image and scipy.