imops 0.4.0

No project description provided

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.