semvec/pypi-packages huggingface dataset:
scriptengine-tasks-hpc 1.0.0
ScriptEngine tasks you may need on HPC systems
Requires Python: >=3.8

# ScriptEngine Tasks for HPC

Provides [ScriptEngine](https://github.com/uwefladrich/scriptengine) tasks
useful for the use on High-Performance Computing (HPC) systems.

Check out the [documentation](https://scriptengine-tasks-hpc.readthedocs.io) at
ReadTheDocs!
cxas 0.0.17
Segmentation of 159 anatomical classes for Chest X-Rays.
Requires Python: >=3.9
Keywords: chest x-ray anatomy segmntation pytorch

================================
Chest X-Ray Anatomy Segmentation
================================

--------------
Installation
--------------

The project is available in PyPI. To install run:

``pip install cxas``


--------------------------------------
Running Segmentation from terminal
--------------------------------------

Segment the anatomy of X-Ray images \(.jpg,.png,.dcm\) and store the results \(npy,json,jpg,png,dicom-seg\):

```
cxas_segment -i {desired input directory or file} -o {desired output directory}
```

------------------------------------------
Running Feature Extraction from terminal
------------------------------------------

Extract anatomical features from X-Ray images \(.jpg,.png,.dcm\) and store the results \(.csv\):

``cxas_feat_extract -i {desired input directory or file} -o {desired output directory} -f {desired features to extract}``

----------------------------
Running either from terminal
----------------------------

Extract anatomical features from X-Ray images \(.jpg,.png,.dcm\) and store the results \(.csv\):

``cxas -i {desired input directory or file} -o {desired output directory} -mode {"segment" or "exract"} -f {required if mode == 'extract'}``



--------------
Citation
--------------

If you use this work or dataset, please cite:

.. code:: bibtex

    @inproceedings{Seibold_2022_BMVC,
        author    = {Constantin Marc Seibold and Simon Reiß and M. Saquib Sarfraz and Matthias A. Fink and Victoria Mayer and Jan Sellner and Moon Sung Kim and Klaus H. Maier-Hein and Jens Kleesiek and Rainer Stiefelhagen},
        title     = {Detailed Annotations of Chest X-Rays via CT Projection for Report Understanding},
        booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
        publisher = {{BMVA} Press},
        year      = {2022},
        url       = {https://bmvc2022.mpi-inf.mpg.de/0058.pdf}
    }
    
.. code:: bibtex

    @inproceedings{Seibold_2023_CXAS,
        author    = {Constantin Seibold, Alexander Jaus, Matthias Fink,
        Moon Kim, Simon Reiß, Jens Kleesiek*, Rainer Stiefelhagen*},
        title     = {Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling},
        year      = {2023},
    }
dlmr-tools 0.1.4
Tool to extract data from xlsx files and create graphs
Requires Python: >=3.8

# Dlmr Tools
    
[![PyPI version](https://badge.fury.io/py/dlmr-tools.svg)](https://badge.fury.io/py/dlmr-tools)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

1. [🔧 Usage](#-usage)
2. [📦 Installation](#-installation)
3. [⚖️ License](#️-license)
4. [🔄 Changelog](#-changelog)

## 🔧 Usage

Composed of a set of tools to help you perform some tasks in your project:

1. [Data Tool](#-data-tool)
2. [Graph Tool](#-graph-tool)

### 📚 Data Tool

#### 🔧 Usage

You can use the `Data Tool` to import data from `.xlsx` files.

#### ✏️ Example

```python

```

### 📊 Graph Tool 

#### 🔧 Usage

You can use the `Graph Tool` to create graphs from data.

#### ✏️ Example

```python

```

## 📦 Installation

```bash
pip install dlmr_tools
```

## ⚖️ License

This project is licensed under the MIT License - see the [LICENSE](LICENSE.md) file for details.

## 🔄 Changelog

Check the [CHANGELOG](CHANGELOG.md) file for details.
gtemptsi 0.0.2
A package for displaying global temperature and co2
Requires Python: >=3.8

# gtemptsi

gtemptsi is a PyPI application for visualizing four lines of global surface temperature and total solar irradiance, and their linear-regression lines with R-squared, slope and intercept, and p-value.

NOAA started total solar irradiance (TSI) measurement from 1978. 
The global surface temperature and TSI are publicly available at the NOAA sites. 

TSI (W/m**2): https://www.ncei.noaa.gov/data/total-solar-irradiance/access/monthly/

Global surface temperature (K: Kelvin): https://www.ncei.noaa.gov/data/noaa-global-surface-temperature/v5.1/access/timeseries/

gtemptsi download datasets automatically and save them as tsi.csv (TSI dataset) and noaa.csv (global surface temperature dataset).

# How to install gtemptsi

$ pip install gtemptsi

# How to run gtemptsi
<pre>
$ gtemptsi
Enter the beginning year-month (e.g. 1978-11): 1996-06
Enter the end year-month (e.g. 2023-03): 1998-12

solid line: global surface temperature
dotted line: linear regression of temperature
dashed line: TSI
dashdot line: linear regression of TSI
</pre>
<img src='https://github.com/y-takefuji/gtemptsi/raw/main/199606_199812.png' width=640 height=480>
docs-to-md 0.1.2
Convert readthedocs to markdown
Requires Python: >=3.10

# Docs-to-Markdown [D2M]

---

![PyPI - Version](https://img.shields.io/pypi/v/docs-to-md)
![PyPI - Downloads](https://img.shields.io/pypi/dm/docs-to-md)

---

Docs-to-Markdown[D2M] is a tool using `Jina.ai` api or `openai` api (default: `ollama: reader-lm`) to convert project documentation to `markdown`.

For now, it only supports `readthedocs` project, but it will add more project type in the future.

# Usage

## Install

```bash
pip install docs-to-md
```

## Convert the documentation of a readthedocs project to markdown

```bash
d2m --help
```

```
Usage: d2m [OPTIONS]

Options:
  -u, --url TEXT           Root url of the documentation project
  -p, --project-name TEXT  Name of the project
  -t, --target-path TEXT   Path to save the html and md files
  -nj, --no_jina           Use open-based api (default: ollama reader-lm) to
                           parse html to markdown, if true, --token is
                           required, and will ignore --api and --model
  --api TEXT               Base url of the openai/jina api, only works when
                           --no_jina is false
  --token TEXT             Api key of the openai/jina api
  --model TEXT             Model to use for parsing html to markdown
  --help                   Show this message and exit.
```

### Example:

```bash

# use jina api
d2m -u https://example-sphinx-basic.readthedocs.io/en/latest/ -t saved/demo

# use openai api
# not recommend, seems like ollama reader-lm is not good enough compare to jina api
# make sure you have installed `ollama` and run ollama with `ollama run reader-lm`
d2m -u https://example-sphinx-basic.readthedocs.io/en/latest/ -t saved/demo-local -nj -a http://localhost:11434/v1 -m reader-lm
```


## Jina API Limitation

You can get the `api_key` from [Jina](https://jina.ai/).

[Jina Reader API](https://jina.ai/reader)

| Endpoint  	| Description   	| Rate limit with API key (premium plan) 	| Rate limit with API key 	| Rate limit w/o API key 	|
|-----------	|---------------	|----------------------------------------	|-------------------------	|------------------------	|
| r.jina.ai 	| Reader Read   	| 1000 RPM                               	| 200 RPM                 	| 20 RPM                 	|
| s.jina.ai 	| Reader Search 	| 100 RPM                                	| 40 RPM                  	| 5 RPM                  	|