Infering Emergent Dependency Structures In Survey Responses
Project description
===============
Cognet
===============
.. image:: https://zenodo.org/badge/388924904.svg
:target: https://zenodo.org/badge/latestdoi/388924904
.. image:: http://zed.uchicago.edu/logo/cognet_logo.png
:height: 300px
:scale: 25%
:alt: cognet logo
:align: center
.. class:: no-web no-pdf
:Info: Draft link will be posted here
:Author: ZeD@UChicago <zed.uchicago.edu>
:Description: Application of quasinets (https://pypi.org/project/quasinet/) for analysis of emergent structures in survey responses with application in adversarial contexts.
:Documentation: https://zeroknowledgediscovery.github.io/cognet/
**Usage:**
.. code-block::
from cognet.cognet import cognet as cg
from cognet.dataFormatter import dataFormatter
from cognet.model import model
data = dataFormatter(samples=GSSDATA,
test_size=0.5)
Cognet
===============
.. image:: https://zenodo.org/badge/388924904.svg
:target: https://zenodo.org/badge/latestdoi/388924904
.. image:: http://zed.uchicago.edu/logo/cognet_logo.png
:height: 300px
:scale: 25%
:alt: cognet logo
:align: center
.. class:: no-web no-pdf
:Info: Draft link will be posted here
:Author: ZeD@UChicago <zed.uchicago.edu>
:Description: Application of quasinets (https://pypi.org/project/quasinet/) for analysis of emergent structures in survey responses with application in adversarial contexts.
:Documentation: https://zeroknowledgediscovery.github.io/cognet/
**Usage:**
.. code-block::
from cognet.cognet import cognet as cg
from cognet.dataFormatter import dataFormatter
from cognet.model import model
data = dataFormatter(samples=GSSDATA,
test_size=0.5)
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
cognet-0.0.192.tar.gz
(43.1 MB
view details)
Built Distribution
File details
Details for the file cognet-0.0.192.tar.gz.
File metadata
- Download URL: cognet-0.0.192.tar.gz
- Upload date:
- Size: 43.1 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.42.0 CPython/3.7.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | b5e0d0f45fb62900039584714b6ebe070c3c2881d56f5b8404af3f19f3c5dcbf |
|
| MD5 | 41312c3b89c19b73a5fb878ad1a92066 |
|
| BLAKE2b-256 | f312b2d552f28882f8b8c380acd4d061f3771818ee7effa7f300874ddeb0e9da |
File details
Details for the file cognet-0.0.192-py3-none-any.whl.
File metadata
- Download URL: cognet-0.0.192-py3-none-any.whl
- Upload date:
- Size: 1.6 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.42.0 CPython/3.7.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | fbf920805cedaf6fa8d650eda1867a67880a1fc67c926ab7af83fb18888ba7c3 |
|
| MD5 | 4b1e1ac31bd215a639b1e6f72a39411b |
|
| BLAKE2b-256 | 0c52050af9670530d337a7ab80300bbdad0f12c164484aa7f0bc5373be83f1cd |
