pecpy

Optimization-based proximity effect correction

Project description

The pecpy library provides an implementation of the proximity effect correction (PEC) scheme proposed in [1]. Examples are bundled with the source code in

pecpy/examples

If you use this package in your research, please cite the original publication. If you use Windows, I can recommend [2] for obtaining pre-compiled versions of fftw, shapely, and opencv. Note that the latter two packages are only needed for the gds <-> image mapping.

[1] https://doi.org/10.1016/j.mee.2018.07.013

[2] https://www.lfd.uci.edu/~gohlke/pythonlibs/

Project details

Release history Release notifications | RSS feed

This version

0.7

May 4, 2019

0.6

Aug 1, 2018

0.5

Aug 1, 2018

0.0.1

Mar 25, 2018

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pecpy-0.7.tar.gz (15.3 kB view hashes)

Uploaded May 4, 2019 Source

Built Distribution

pecpy-0.7-py3-none-any.whl (15.9 kB view hashes)

Uploaded May 4, 2019 Python 3

Hashes for pecpy-0.7.tar.gz

Hashes for pecpy-0.7.tar.gz
Algorithm	Hash digest
SHA256	`345d6bec206da67c8ccd61038be4ad66ad5b0e5259871eda7f81bbcd474e88d2`
MD5	`0d7024a6f151db3d2e8e19dabcd62281`
BLAKE2b-256	`2d0d719a8b51cb85792731f01518e66a6afb57f9bce51acfeeef081505479cad`

Hashes for pecpy-0.7-py3-none-any.whl

Hashes for pecpy-0.7-py3-none-any.whl
Algorithm	Hash digest
SHA256	`2c1c7a67350215e57e1f01fc5adc6f519410ce59f9378c0a15b5b09f63c07238`
MD5	`f32776300b8ee0fdd818bd0b79188ae1`
BLAKE2b-256	`4468be3081f42c7109d3834e21ede0ba29cce8b3659fc47e01b66aa660e4741d`