Giter Club home page Giter Club logo

dcbia-ortholab / mfsda_python Goto Github PK

View Code? Open in Web Editor NEW

This project forked from big-s2/mfsda_python

3.0 3.0 10.0 14.92 MB

Multivariate Functional Shape Data Analysis in Python (MFSDA_Python) is a Python based package for statistical shape analysis. A multivariate varying coefficient model is introduced to build the association between the multivariate shape measurements and demographic information and other clinical, biological variables. Statistical inference, i.e., hypothesis testing, is also included in this package, which can be used in investigating whether some covariates of interest are significantly associated with the shape information. The hypothesis testing results are further used in clustering based analysis, i.e., significant suregion detection. This MFSDA package is developed by Chao Huang and Hongtu Zhu from the BIG-S2 lab.

License: Apache License 2.0

Python 86.66% CMake 13.02% Dockerfile 0.31%
3d-slicer-extension

mfsda_python's People

Contributors

allemangd avatar bpaniagua avatar chaohstat avatar jcfr avatar juanprietob avatar lopezmt avatar mahmoudmostapha avatar sjh26 avatar vicory avatar

Stargazers

 avatar  avatar  avatar

Watchers

 avatar  avatar  avatar  avatar  avatar  avatar

mfsda_python's Issues

Publish tutorial

There is a tutorial powerpoint dangling in #10 from Mahmoud Mostapha, is there a DCBIA google drive where I could upload it as Google slides ?

Or since it corresponds to a tutorial written for SlicerSALT, is there already a public URL for it ?

Motivation: This tutorial would be referenced in the README and help user understand how to use the extension.

Challenge: Because of naming different between the loadable module in SlicerSALT and the default name in the extension, user will likely be confused by reading the tutorial. See #16

image

Code can fail for singular matrices

I've occasionally run into the code failing when trying to invert a singular matrix. Code could check for this error and use a pseudo-inverse instead.

Python requirements need to be updated for latest Slicer python version

Slicer recently upgraded from Python 3.6.7 to Python 3.9.10 in Slicer/Slicer@34e48e8. There are now observed build errors of the MFSDA Slicer extension as seen at https://slicer.cdash.org/viewBuildError.php?buildid=2581568. This is because the python requirements file in the repo is including hashes that are only for Python 3.6 wheels. These need to be updated for Python 3.9 wheels which also means the actual version of packages here will need to be updated as some older versions simply don't have Python 3.9 wheels because that version was released before Python 3.9 was even released.

file(WRITE ${requirements_file} [===[
# Hashes correspond to the following packages:
# - python_dateutil-2.8.1-py2.py3-none-any.whl
python-dateutil==2.8.1 --hash=sha256:75bb3f31ea686f1197762692a9ee6a7550b59fc6ca3a1f4b5d7e32fb98e2da2a
# Hashes correspond to the following packages:
# - pytz-2020.1-py2.py3-none-any.whl
pytz==2020.1 --hash=sha256:a494d53b6d39c3c6e44c3bec237336e14305e4f29bbf800b599253057fbb79ed
# Hashes correspond to the following packages:
# - pandas-1.0.5-cp36-cp36m-win_amd64.whl
# - pandas-1.0.5-cp36-cp36m-macosx_10_9_x86_64.whl
# - pandas-1.0.5-cp36-cp36m-manylinux1_x86_64.whl
pandas==1.0.5 --hash=sha256:35b670b0abcfed7cad76f2834041dcf7ae47fd9b22b63622d67cdc933d79f453 \
--hash=sha256:faa42a78d1350b02a7d2f0dbe3c80791cf785663d6997891549d0f86dc49125e \
--hash=sha256:8778a5cc5a8437a561e3276b85367412e10ae9fff07db1eed986e427d9a674f8
# Hashes correspond to the following packages:
# - patsy-0.5.1-py2.py3-none-any.whl
patsy==0.5.1 --hash=sha256:5465be1c0e670c3a965355ec09e9a502bf2c4cbe4875e8528b0221190a8a5d40
# Hashes correspond to the following packages:
# - statsmodels-0.11.1-cp36-none-win_amd64.whl
# - statsmodels-0.11.1-cp36-cp36m-macosx_10_13_x86_64.whl
# - statsmodels-0.11.1-cp36-cp36m-manylinux1_x86_64.whl
statsmodels==0.11.1 --hash=sha256:49aa8ffbe0b0e2e86afa58dec6bd5c483898e9b8223d8a7d13b69b5ad144b674 \
--hash=sha256:5e7afc596164c1c7464ba3943721a9668aa0ce07853ce9881ac49d3a043784dd \
--hash=sha256:9efd2e27c08077330cecdbfb589cf84d735abface94e9a6387282a6a7c91362d
]===])

MFSDA fails with one covariate

Current code makes assumption that the covariates read from the file has 2d shape (i.e. rows and columns) while the numpy reader will collapse the second dimension if there is only 1 column.

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    ๐Ÿ–– Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. ๐Ÿ“Š๐Ÿ“ˆ๐ŸŽ‰

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google โค๏ธ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.