semvec/pypi-packages huggingface dataset:
plotdelice 0.2
A package for creating old school style plots
Requires Python: >=3.6

# plotdelice 📊
A collection of functions to plot old school style graphs with significance bars and automated stat testing (still verify it is the adequate test for your data).
## Install
```python
pip install plotdelice
```
## Gallery
**Violin plot**

```python
from plotdelice.graphs import violinplot_delice, scatterplot_delice, markerplot_delice, barplot_delice
import pandas as pd

# read data
df = pd.read_csv("path_to_your_file.csv")

# define what you want to plot
x_group = "genotype"
y_variable = "angle"
y_label = r'Somite Angle [°]'

# plot
violinplot_delice(df,x_group,y_variable,violin_width=0.8,y_label=y_label,palette="Greens_d",point_size=40,jitter=0.09)
```


![alt text](assets/image.png)

**Scatter plot**
![alt text](assets/scatter.png)
**Custom marker plot**
```python
from svgpath2mpl import parse_path

# df['coords'] contains an svg path for each custom marker
df['coords'] = df['coords'].apply(parse_path)
fig, axs = markerplot_delice(df,"solidity","eccentricity","kmeans","coords",add_regression='logx',palette='Set2',figsize=(10,5))
```
![alt text](assets/marker.png)
sphereob 0.1.2
A description of your project
Requires Python: >=3.6

Sphere-ob Airborne EM modelling 
====

Sphere-ob (sphere-overburden) is a python program developed to calculate and plot the airborne TDEM response of a sphere or â€˜dipping sphereâ€™ underlying conductive overburden. 
The response is calculated using the semi-analytic solution set presented in Desmerais & Smith (2016), this solution set is computationally efficient and allows the user to model a thin sheet in addition to a sphere, by artificially restricting current flow to parallel planes within an anisotropic sphere.

Installation
====

If python is installed on your system, Sphereob can be installed with pip + git by opening command prompt in administrator and using::

	pip install git+https://github.com/anonseg2023/sphereob

Alternatively, the repository can be manually downloaded and installed using the install script, i.e., by navigating to the SPHERE-OB folder, opening a python / anaconda prompt in administrator and running::

	python setup.py install


Dependencies
====

* matplotlib
* numpy
* scipy
* pyqt5
* pandas

Installing SPHERE-OB through pip + git will result in these libraries being installed in your current python environment.

Getting Started
====

Once installed, the GUI can be launched from the command line as::

	sphereob

The program will launch and the user can now begin plotting airborne EM responses for varying survey configurations and geologic models.

Documentation
====

Documentation, including explanations of the model parameters and data importers is included in SPHERE-OB.pdf
mosaic-stats 0.1.3
Statistics generation script for astrophotography mosaic projects
Requires Python: >=3.6

# Mosaic Stats

This project contains scripts for generating statistics from FITS files for astrophotography projects. The scripts can generate overall statistics, detailed panel statistics, and session statistics.

## Features

-   **Overall Statistics**: Generate overall exposure statistics across multiple panels and sessions.
-   **Detailed Panel Statistics**: Generate detailed statistics for each panel, including session details.
-   **Session Statistics**: Generate statistics per session, optionally filtered by panel.

## Requirements

-   Python 3.6+
-   Astropy library for reading FITS files

## Installation

You can install the package via pip:

```bash
pip install mosaic-stats
```

## Usage

You can run the statistics generator and follow the prompts in the application.

```bash
mosaic-stats [dir_for_lights]
```
samuelcolvin-aicli 0.8.0
OpenAI powered AI CLI in just a few lines of code.
Requires Python: >=3.7

# aicli

[![pypi](https://img.shields.io/pypi/v/samuelcolvin-aicli.svg)](https://pypi.python.org/pypi/samuelcolvin-aicli)
[![versions](https://img.shields.io/pypi/pyversions/samuelcolvin-aicli.svg)](https://github.com/samuelcolvin/aicli)
[![license](https://img.shields.io/github/license/samuelcolvin/aicli.svg)](https://github.com/samuelcolvin/aicli/blob/main/LICENSE)

## Installation

```bash
pip install samuelcolvin-aicli
```

## Usage

You'll need to set the `OPENAI_API_KEY` environment variable to use `aicli` which you can generate from
[platform.openai.com](https://platform.openai.com/), you'll have to add some credit to use the API.

```bash
export OPENAI_API_KEY='...'
```

Then usage is as simple as:

```bash
aicli
```

## Example

https://github.com/samuelcolvin/aicli/assets/4039449/53a30d7f-79ae-452e-ac81-e94c8cd4032b