semvec/pypi-packages huggingface dataset:
asymmetree 2.2.2
Simulation of phylogenetic trees, sequences and genomes
Requires Python: >=3.7

# AsymmeTree
![Logo](resources/images/logo.png)

[![license: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)
[![pypi version](https://img.shields.io/badge/pypi-v2.2.2-blue.svg)](https://pypi.org/project/asymmetree/)

AsymmeTree is an open-source Python library for the simulation and analysis of phylogenetic scenarios.
It includes a simulator for species and gene trees with heterogeneous evolution rates, nucleotide and amino acid sequences with or without indels, as well as whole genomes/proteomes.

Moreover, it includes a matplotlib-based visualization of the simulated trees as well as tools for the extraction of information from the simulated scenarios such as orthology, best matches, and xenology.

The library is primarily designed to explore and validate mathematical concepts, and to test inference methods for various steps on the way to more realistically-available data, i.e., dated gene trees, additive distances of gene sets, noisy distances and finally sequences.


## Installation

AsymmeTree requires Python 3.7 or higher.

#### Easy installation with pip

The `asymmetree` package is available on PyPI:

    pip install asymmetree

For details about how to install Python packages see [here](https://packaging.python.org/tutorials/installing-packages/).

#### Installation with the setup file

Alternatively, you can download or clone the repo, go to the root folder of package and install it using the command:

    python setup.py install

#### Dependencies

AsymmeTree has several dependencies (which are installed automatically when using `pip`):
* [NetworkX](https://networkx.github.io/)
* [Scipy and Numpy](http://www.scipy.org/install.html)
* [Matplotlib](https://matplotlib.org/)
* [tralda](https://github.com/david-schaller/tralda)

## Usage and description

A user manual with example code can be found in the [Wiki](https://github.com/david-schaller/AsymmeTree/wiki/Manual).
AsymmeTree is divided into several subpackages and modules, see also the following [documentation](https://david-schaller.github.io/docs/asymmetree/) generated from the source code.

## Citation

If you use AsymmeTree in your project or code from it, please consider citing:

* **David Schaller, Marc Hellmuth, and Peter F. Stadler. AsymmeTree: A Flexible Python Package for the Simulation of Complex Gene Family Histories. Software 2022, 1(3), 276-298; doi: 10.3390/software1030013**

Please report any bugs and questions in the [Issues](https://github.com/david-schaller/AsymmeTree/issues) section.
Also, feel free to make suggestions for improvement and/or new functionalities.
datadigitizer 1.4.0
datadigitizer: Data digitizer.
Requires Python: >=3.10

# Introduction

DataDigitizer is a simple graphical tool for digitizing data from images.

In terminal enter the following command:

```bash
python -m datadigitizer
```


The cursor is used to point a specific position in the graph
whereas all operations are done through keyboard combinations or through the main menu.

Legend:

* Red crosses are data points
* Blue crosses are Xmin and Xmax
* Green crosses are Ymin and Ymax

Commands:

* <Ctrl-o> for loading image.
* <Ctrl-a> add data point.
* <Hold a+Left Click> add data point.
* <Left Click> select a data point.
* <Hold Ctrl+Left Click> multiple data point selection.

* <Ctrl-g> set Xmin from last data point or from selected data point.
* <Ctrl-h> set Xmax from last data point or from selected data point.

* <Ctrl-j> set Ymin from last data point or from selected data point.
* <Ctrl-k> set Ymax from last data point or from selected data point

* <Ctrl-l> set all limits from last 4 data points or from last 4 selected data points.
* <Ctrl-n> remove all limits.

* <Ctrl-z> remove last data point.
* <Ctrl-d> remove selected data point.
* <Ctrl-D> remove all data points.

* <Ctrl-m> compute the data points.
* <Ctrl-t> view data table.
* <Ctrl-s> save data points.
* <Ctrl-w> clear all.



# Dependencies

numpy>=1.21, <2 
matplotlib>=3.4.0 
Pillow>=9.0.0


# Installation

```
pip install datadigitizer
```

# License

MIT License