Metadata-Version: 2.4
Name: topaztrainmetrics
Version: 1.3
Summary: Plot metrics from a Topaz training run
Home-page: https://codeberg.org/Guillawme/topaztrainmetrics
Author: Guillaume Gaullier
Author-email: contact@gaullier.org
Project-URL: Bug Reports, https://codeberg.org/Guillawme/topaztrainmetrics/issues
Project-URL: Source, https://codeberg.org/Guillawme/topaztrainmetrics
Keywords: cryo-EM particle-picking Topaz visualization
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Environment :: Console
Classifier: Natural Language :: English
Requires-Python: >=3.9.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click>=8.0.3
Requires-Dist: matplotlib>=3.4.3
Requires-Dist: pandas>=1.3.3
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: keywords
Dynamic: license-file
Dynamic: project-url
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# topaztrainmetrics

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4451826.svg)](https://doi.org/10.5281/zenodo.4451826)

Plot metrics from a [Topaz](https://github.com/tbepler/topaz) training run.

## Installation

```
$ pip install topaztrainmetrics
```

## Usage

```
$  topaztrainmetrics --help
Usage: topaztrainmetrics [OPTIONS] <file>

  Plot validation metrics from a Topaz training run.

  <file> is the results.txt file from standalone Topaz or the
  model_plot.star file from Topaz run within RELION.

Options:
  -l, --loss                Plot loss.
  -g, --gepenalty           Plot GE penalty.
  -p, --precision           Plot precision.
  -t, --tpr                 Plot true/false positive rates.
  -c, --auprc               Plot area under precision/recall curve (default).
  -x, --xaxis [iter|epoch]  X axis (iter or epoch; default: iter).
  -o, --output TEXT         File name to save the plot (optional: with no file
                            name, simply display plot on screen without saving
                            it; recommended file formats: .png, .pdf, .svg or
                            any format supported by matplotlib).

  -h, --help                Show this message and exit.
```
