semvec/pypi-packages huggingface dataset:
intraCorr 0.0.3
This package calculates the correlation within subjects for repeated observations

# Correlation for Repeated Observation within Subjects in Python

This package applied the statistical technique for estimating the correlation for paired measures assessed on two or more ocassions for multiple subjects.
Pearson correlation is applied when each paired of measurements is independent of one another. This is not the case when you have an observation for the same subject at different times. 

## Installing

You can use PyPi to do so,

```shell
pip install intraCorr
```


## Contributing

You can contribute to this project by forking it through github. 

## Licensing

The code in this project is licensed under GNU General Public License v3.0.

## Authors

* Erika Munoz
* Jose Nandez
jx-libcollection 0.0.17
Jiao's collection libs

# libcollection
common data structures

[![PyPI version](https://badge.fury.io/py/jx-libcollection.svg)](https://badge.fury.io/py/jx-libcollection)


## stack

* ResizingArrayStack
* LinkedStack

## queue

* LinkedQueue
* SimpleLinkedQueue
* ResizingArrayQueue
* FixedCapacityArrayQueue

## Search

* SequentialSearchKVStore
* BinarySearchKVStore
* SeparateChainingHashKVStore
* LinearProbingKVStore
* BSTKVStore

## Sort

* bubble sort
* quick bubble sort
* selection sort
* quick selection sort
* recursive selection sort
* insertion sort
* shell sort
* merge sort
* quick sort
* heap sort

## Priority queue

* fixed size min priority queue
* fixed size max priority queue
* min priority queue
* max priority queue

## Union Find

* quick find union find
* quick union union find
* weighted union find
* union find
swa-cc.secure-s3-storage-bucket 1.3.0
A CDK stack for creating a swa approved s3 bucket
Requires Python: >=3.6

# SWA Secure S3 Storage Bucket Stack Library

Define a S3 bucket that security will be proud of.

`S3StorageBucketStack` exposes the following deploy-time attributes from the underlying `bucket` construct:

* `bucketArn` - the ARN of the bucket (i.e. `arn:aws:s3:::bucket_name`)
* `bucketName` - the name of the bucket (i.e. `bucket_name`)
* `arnForObjects(pattern)` - the ARN of an object or objects within the bucket (i.e.
  `arn:aws:s3:::bucket_name/exampleobject.png` or
  `arn:aws:s3:::bucket_name/Development/*`)
* `urlForObject(key)` - the URL of an object within the bucket (i.e.
  `https://s3.cn-north-1.amazonaws.com.cn/china-bucket/mykey`)

`S3StorageBucketStack` exposes the following deploy-time methods from the underlying `bucket` construct:

* `add_lifecycle_rule`
* `add_metric`
* `add_object_created_notification`
* `add_object_removed_notificationself`
* `add_event_notification`
* `add_to_resource_policy`
* `arn_for_objects`
* `on_cloud_trail_event`
* `on_cloud_trail_put_object`
* `url_for_object`

## Helpfull commands

* Package code for publishing. First increment the version in setup.py then run the following
  `python3 setup.py sdist bdist_wheel`
* Publish code -- you need a valid pypi credentials file
  `python3 -m twine upload  dist/*`
* Generate documentation
  `cd docs && make html`
* Run unit tests
  `pytest --cov . --cov-report=html --html=testreport/report.html`
* upload to sonar
  `sonar-scanner \`
  `-Dsonar.projectKey=swa_cc_secure_s3_storage_bucket \`
  `-Dsonar.sources=source\swa_cc \`
  `-Dsonar.host.url=https://sonar-tools.swacorp.com/EC \`
  `-Dsonar.login=eda1a69701cd879fe142e1c36b2ed3db6769a01c`
scriptax-runtime 0.2.1
Scriptax is a powerful driver for the Apitax framework which exposes an automation first language used to quickly script together automation.
Keywords: scriptax

# Scriptax-Runtime
A means to run Scriptax on its own without the need for the Apitax framework around it.

## Usage
* `pip install scriptax-runtime`
* `pip install scriptaxstd`
* `spm install scriptaxstd`
* `scriptax <file>`
demort 0.2.4
DEmultiplexing MOnitoring Report Tool

`demort` evaluates demultiplexed fastq files by computing various metrics.

# DEPENDENCIES

You need to install [python 3.7](https://www.python.org/download/releases/3.0/) and depencies. Check version by typing on:
```
python3 --version
```
**python3 depencies :**
* [joblib](https://joblib.readthedocs.io/en/latest/installing.html)
* [biopython](https://github.com/biopython/biopython)
* [matplotlib](https://matplotlib.org/3.1.1/faq/installing_faq.html)


# USAGE

`demort` check fastq files into specified folder(s) then count number of reads for each fastq files for each folder and finally return a summary `csv` table and a `pdf` boxplot picture.

(process a list of folder as a strings)
```
demort.py -d folder/folder1,folder/folder2,folder/folder3 \
 -t 8 \
 -p results.pdf \
 -o results.csv
```
(process a list of folder into a file)
```
demort.py -d example/folder_to_process.txt \
 -t 8 \
 -p results.pdf \
 -o results.csv
```

# COMMAND-LINE ARGUMENTS

| complete flag argument | short flag |Default value | Summary |
| --- | --- | --- | --- |
| `--inputFolder` | `-d` | NA |  a string of folderpath separated by coma `,` OR a file containing a list |
| `--threads` | `-t` | 1 | Number of available cores |
| `--output_pdf` | `-p` | NA | path of the file where to write a `pdf` boxplot picture |
| `--output_csv` | `-o` | NA | path of the file where to write a `csv` table |


# INPUT

```
folder/
├── folder1
│   ├── fqfileA.fq.gz
│   ├── fqfileB.fq.gz
│   └── fqfileC.fq.gz
├── folder2
│   ├── fqfileD.fq.gz
│   └── fqfileE.fq.gz
└── folder3
    ├── fqfileF.fq.gz
    ├── fqfileG.fq.gz
    └── fqfileH.fq.gz
```

# OUTPUTS

* summary `csv` table [foldername, filename, number of reads]
* `pdf` boxplot picture

# SYSTEM REQUIREMENTS

Linux (64-bit and 32-bit with slightly limited functionality) and macOS (OS X) are supported.