Skip to main content

Transformation

Transformation tools to normalise and stabilise the variance of non-normal data.

Build Status

Table of Contents

Overview

normtransform is a high-performance Python package (with Cython/C++ backend) for fitting univariate transformed normal distributions using maximum likelihood or maxium a posteriori (MAP) estimation, with support for left and right censoring. Typically, norm-transform is used to transform variables/data so that they can be used in modelling that assumed normality. The ability to handle scenarios where data may be treated as partially observed (e.g. rainfall) allows significant flexibility in applications.


Interactive Demonstration of normtransform

You can explore an interactive demonstration of the normtransform tool here. This link opens a Jupyter Notebook hosted on the MyBinder platform. Once it loads, click Run-->Run All Cells to execute the code and see the demonstration in action.


Installation

A Python virtual environment is a self-contained directory that includes a specific Python version and any additional packages you install. It helps you isolate dependencies for different projects, ensuring that changes in one environment don’t affect others. This makes it easier to manage project-specific requirements and maintain a clean development setup.

Use the package manager pip to install normtransform.

python -m venv venv # Create a virtual environment
source venv/bin/activate  # Activate the virtual enviroment, on Windows use `venv\Scripts\activate`
pip install normtransform #install normtransform

Once installed users can start with mimicking the demonstration found above within their own environment.


Contributing

Requests are welcome. Please contact the authors below.


License

MIT


Contact

Download files

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

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

normtransform-0.2.4-cp313-cp313-win_amd64.whl (641.2 kB view details)

Uploaded CPython 3.13Windows x86-64

normtransform-0.2.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.5 MB view details)

Uploaded CPython 3.13manylinux: glibc 2.17+ x86-64

normtransform-0.2.4-cp313-cp313-macosx_26_0_arm64.whl (924.3 kB view details)

Uploaded CPython 3.13macOS 26.0+ ARM64

normtransform-0.2.4-cp312-cp312-win_amd64.whl (642.5 kB view details)

Uploaded CPython 3.12Windows x86-64

normtransform-0.2.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.6 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.17+ x86-64

normtransform-0.2.4-cp312-cp312-macosx_26_0_arm64.whl (924.8 kB view details)

Uploaded CPython 3.12macOS 26.0+ ARM64

normtransform-0.2.4-cp311-cp311-win_amd64.whl (648.2 kB view details)

Uploaded CPython 3.11Windows x86-64

normtransform-0.2.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.7 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.17+ x86-64

normtransform-0.2.4-cp311-cp311-macosx_26_0_arm64.whl (917.9 kB view details)

Uploaded CPython 3.11macOS 26.0+ ARM64

File details

Details for the file normtransform-0.2.4-cp313-cp313-win_amd64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 35515072ca5e7c7cc02a4a4386c03c93b437539c3ce5b5389f881113a35f64e6
MD5 716a77db8b95874044d12af1833f4a88
BLAKE2b-256 c833d4da79f8cebe32e11f9ea8b8a89c54bd8847b0bdccde3052a7b99d1af7db

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2fc300f9c0637b0343ede733afebedfb559f99f41b937a6b6a7463d5ad669db7
MD5 77adb59bfcc91ec0bc2ac5971de19760
BLAKE2b-256 3ba59980f2a428adc145dd2ef0c677b47cac50cf488fb1d2011d4bced566b3bc

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp313-cp313-macosx_26_0_arm64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp313-cp313-macosx_26_0_arm64.whl
Algorithm Hash digest
SHA256 b5f3edb0ebf7972cdfa55891d5527312b1f2ea3b9b0d1b9d7d64afcf59176911
MD5 33b6e0cf49c60993d2ab8615676e7c67
BLAKE2b-256 f7fd939900ef134c0f99be47c5b3576a5f65f42f8f38274bc56e887955187599

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 da58f3b34fe1fd3bf18a5c0cccc291d57f68793a46f902d14b7b4636c10c069a
MD5 dca7f51a50d9866f92e2a2ccb5c8d87e
BLAKE2b-256 31bc7ab2345ea12d1f72b2a313b785f6be19ab23a614615ce99a5b1fc915a80b

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 91bd3726ebbbbec25fe1dcfef6da817af144615f53cfb70b4eb271c0f121672b
MD5 6699857f99424332ff99684a84b33256
BLAKE2b-256 9e3bab21184c7a2f73e566ba4e720958e97e35535fc859a1bef954802cd31c18

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp312-cp312-macosx_26_0_arm64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp312-cp312-macosx_26_0_arm64.whl
Algorithm Hash digest
SHA256 94ac73661d511b19b03f2b4dea7ff73de6c1938714ec19289b3620529a120c4e
MD5 ab9c7f8397291350124604c8a4351dfc
BLAKE2b-256 fabc14ed5a0666cfd3a57bfa0b15fd1dd3d8f5d602f7bc4b497cb53369a6bae5

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 d892a8fcaf3e8d86e49e26b32132f2eff680cd4628381b53e86f8dd8f9fb7250
MD5 4fb62c30e26f46c34eeb701dfe42e2bd
BLAKE2b-256 ecab9ec0bf1f36338a95a3c23ffcfe787c52f28092ec8767aff83ad0a4cc688b

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 11750ff840c6381ca5cdde16c621a8d7e33b4f04cc4a53731ab5108822218c21
MD5 d3c4a90c8cec3804911364f2d7755ea0
BLAKE2b-256 b5d8ccd3587670eaa1f2df26280bc49df66d409300640ab17ad2d1869e9b1cb5

See more details on using hashes here.

File details

Details for the file normtransform-0.2.4-cp311-cp311-macosx_26_0_arm64.whl.

File metadata

File hashes

Hashes for normtransform-0.2.4-cp311-cp311-macosx_26_0_arm64.whl
Algorithm Hash digest
SHA256 3906a22734ac4ed834b45cf498ead91ed84027578eb2b2e092e374211fa96260
MD5 df21eb82ee4d6ccd5fd1a2727978db30
BLAKE2b-256 9d070696010ed6fde6ae480e184d4cbcd3c04c4b899e4ebabdec84374de35c93

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

0.2.4 This release

9 files

0.2.1

12 files

0.2.0

12 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page