semvec/pypi-packages huggingface dataset:
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Keywords: sample,setuptools,development

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probat 1.1.0
Battery life saver and reminder
Requires Python: >=3.8

## ProBat
**Battery life saver and reminder**

![Usage Screencap](https://i.imgur.com/Phy7vGM.gif)

*Paraphernalia: [Terminator](https://github.com/gnome-terminator/terminator), [Oh-my-zsh](https://github.com/ohmyzsh/ohmyzsh) with [bullet-train theme](https://github.com/caiogondim/bullet-train.zsh), [zsh-syntax-highlighting](https://github.com/zsh-users/zsh-syntax-highlighting) and [zsh-autosuggestions](https://github.com/zsh-users/zsh-autosuggestions)*

## Getting Started:
Current requirements are:
 - python-termcolor: colorizing the shell on unix

### Install:

    # Via PIP:
    $ pip install probat


    # From Arch AUR repo:
    $ ... -S python-probat

### Run:

    $ probat

### Pro tip:

    # Add this line to your .bashrc so you will see the battery status at login:
    ...
    # Run `probat` if it's found in $PATH
    command -v probat &>/dev/null && probat
    ...

## Contributing

This project welcomes with open arms any intent to contribute in any way :)

**Please leave feedback and ideas on the [issues](https://github.com/codeswhite/waller/issues) page**

Easily set up the project locally for development/testing purposes:

    $ git clone https://github.com/codeswhite/probat
    $ cd ./probat
    $ pipenv install

Note that installing the python requirements can be **alternatively** done via basic `pip`:

    $ pip install -r requirements.txt
wellcompare 2.3.4
A package for doing a well to well analysis of 96 well plates run in an Epoch2 microplate reader
Requires Python: >=3.6

# [GarciaLab](https://www.garcialab.org)

## Info-
Code developed for research on modeling prion growth dynamics in budding yeast.
This package is used to compare 96 well plates that contain groupings of 
experimental and control replicates. This code generates graphs, heatmaps, 
and sumarries of your data, while also performing some basic statistics.

## Usage -
Make a directory every screen that you run (Ex. "Screen1"). Inside of your 
individual screen directory, create another folder called 'Data' and put the 
excel file producefrom the Epoch2 plate reader inside. Then, from outside that
directory, run the package ($ python -m wellcompare) on the terminal. 
The programwill create several directories for you. Some notable ones are 
'Graphs', which contains graphs and data summaries, and 'Heatmaps' 
(if -hm flag added) (temporarily disabled until further updates).

Example Directory Structure:

|- Outer_folder    <- run python -m wellcompare inside this outer directory   
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- Screen1  
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- Data    
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- screen1.xslx   
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- Screen2   
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- Data  
|&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;|- screen2.xslx   


## Requirements -
Also outlined in requirements.txt:
1. Python3
2. Pip3
3. Pandas
4. Numpy
5. Maplotlib
6. Scipy
7. Seaborn
8. ArgParse
9. xlrd

## Setup & Installation (MacOS)-
Download Package (recommended):
- Type the following commands into terminal
1. $ pip install wellcombine
2. $ python -m wellcompare \[options\]

-- OR --

Clone Repo:
- Type the following commands into terminal
1. $ git clone https://github.com/jacobian0208/well_compare.git
2. $ pip install -r requirements.txt
3. $ python -m wellcompare \[options\]

## Files & Directories -
1. process.py : module that coordinates graphs and organizes experiment 
   analysis
2. graph.py : module to graph cleaned data
3. extract.py : module to extract and clean data from Epoch2 microplate reader 
   output
4. __main__.py : main file to run package as script
5. requirements.txt : a list of required packages to install to run this 
   program correctly
6. LICENSE : an MIT license to allow use of this program