semvec/pypi-packages huggingface dataset:
vizopt 0.0.1
Add your description here
Requires Python: >=3.13

# vizopt

Mathematical optimization for data visualization, specifically designed for graph layouts with hierarchical inclusion constraints ("bubble layouts").

Uses JAX for automatic differentiation and JIT compilation to efficiently optimize layouts via gradient descent.

## Installation

```bash
pip install vizopt
```

## Quick Start

```python
import networkx as nx
from vizopt.bubblejax import optimize_bubble_layout

# Create a graph
graph = nx.Graph()
graph.add_edges_from([("Munich", "Vienna"), ("Vienna", "Prague")])

# Define inclusion tree (cities in countries)
inclusion_tree = nx.DiGraph()
inclusion_tree.add_edges_from([
    ("Munich", "Germany"),
    ("Vienna", "Austria"),
    ("Prague", "Czechia"),
])

# Optimize layout
result = optimize_bubble_layout(
    graph=graph,
    inclusion_tree=inclusion_tree,
    node_radii={"Munich": 0.3, "Vienna": 0.3, "Prague": 0.3},
)
```

## Features

- Multi-objective optimization (edge lengths, compactness, collision avoidance, inclusion constraints)
- Efficient JAX-based gradient descent with JIT compilation
- Handles arbitrary hierarchical inclusion relationships
- NetworkX integration

## Examples

See [examples/examples_with_bubbles.ipynb](examples/examples_with_bubbles.ipynb) for detailed usage.

## License

MIT
pythonnet314-whl 3.1.0.dev3
Pythonnet wheels for unsupported Python versions.
Requires Python: <4.0.0,~=3.14.0
Keywords: pythonnet314-whl, pythonnet, wheel

pythonnet314-whl
================

Pythonnet wheels for unsupported Python versions.

Overview
========

|package_bold| installs Pythonnet for unsupported Python versions.

`PyPI record`_.

`Documentation`_.

Installation
============

Prerequisites:

+ Python 3.14 or higher

  * https://www.python.org/

+ pip

  * https://pypi.org/project/pip/

To install run:

  .. parsed-literal::

    python -m pip install --upgrade |package|

License
=======

  | |copyright|
  | Copyright (c) 2006-2026 The Contributors of the Python.NET Project
  | Licensed under the MIT License
  | https://opensource.org/license/mit
  | Please refer to the accompanying LICENSE file.

Authors
=======

* The Contributors of the Python.NET Project <pythonnet@python.org>
* Adam Karpierz <adam@karpierz.net>

Sponsoring
==========

| If you would like to sponsor the development of this project, your contribution
  is greatly appreciated.
| As I am now retired, any support helps me dedicate more time to maintaining and
  improving this work.

`Donate`_

.. |package| replace:: pythonnet314-whl
.. |package_bold| replace:: **pythonnet314-whl**
.. |copyright| replace:: Copyright (c) 2026-2026 Adam Karpierz
.. _PyPI record: https://pypi.org/project/pythonnet314-whl/
.. _Documentation: https://pythonnet.github.io/pythonnet/
.. _Donate: https://www.paypal.com/donate/?hosted_button_id=FX8L7CJUGLW7S
geegeogdemo 0.0.1
A simple Google Earth Engine helper package
Requires Python: >=3.6

# GEE Toolkit Demo

This is a starter template for a Google Earth Engine (GEE) Python package.

## Installation

```bash
pip install gee-toolkit-demo
```

## Usage

```python
import gee_toolkit
import ee

# Initialize GEE
gee_toolkit.init_gee()

# Example: Get an image and compute NDVI
image = ee.Image('LANDSAT/LC08/C01/T1_TOA/LC08_044034_20140318')
ndvi_image = gee_toolkit.calculate_ndvi(image, red='B4', nir='B5')

print(ndvi_image.bandNames().getInfo())
```

## Publishing to PyPI

1. Install build tools:
   ```bash
   pip install --upgrade build twine
   ```

2. Build the package:
   ```bash
   python -m build
   ```

3. Upload to PyPI (Test):
   ```bash
   python -m twine upload --repository testpypi dist/*
   ```

4. Upload to PyPI (Production):
   ```bash
   python -m twine upload dist/*
   ```
pymbc 1.2.1
A python package for working with MB Century downhole data.
Requires Python: >=3.11
Keywords: dab, csv, pts, htcc, Century Logger

# MB Century Downhole Data Toolkit

https://www.mbcentury.com/services 

This toolkit provides easy access to data that has been exported from one of MB Century's data logging applications. It is primarily used to access downhole data that has been collected using MB Century's data collection systems.


## Example use

Use pip to import the package.

```ccs
pip import pymbc
```

## Example python code

Open a CSV file containing PTS data, plot it against depth and time, and convert it to Well Test Analysis format.
```css
import pymbc as mbc
from pathlib import Path

csvfile = Path(r'tests\_20230626_PTS__A.csv')
mb = mbc.MbcLog()
mb.ReadMbCsv(csvfile)
fnotes = csvfile.parent / (csvfile.stem + '_notes' + csvfile.suffix)
mb.ReadNotes(fnotes)
mb.CreateRunLogGuess()
plotdef = [mbc.PlotDefinition('TIMEDELTA', 'DEPTH', 'slategray', '-', False),
		   mbc.PlotDefinition('TIMEDELTA', 'PTS_PRES', 'royalblue', '-', False),
		   mbc.PlotDefinition('TIMEDELTA', 'PTS_FREQ', 'limegreen', '-', False),
		   mbc.PlotDefinition('TIMEDELTA', 'PTS_TEMP', 'tomato', '--', True)]
st,figt = mbc.PlotLog(mb, plotdef, title=mb.name, depthaxis=False)

plotdef = [mbc.PlotDefinition('DEPTH', 'TIMEDELTA', 'black', '-', False),
		   mbc.PlotDefinition('DEPTH', 'PTS_FREQ', 'limegreen', '--', True),
		   mbc.PlotDefinition('DEPTH', 'PTS_PRES', 'royalblue', '-', False),
		   mbc.PlotDefinition('DEPTH', 'PTS_TEMP', 'tomato', '-', True)]
sd,figd = mbc.PlotLog(mb, plotdef, title=mb.name, depthaxis=True) 
pts = mb.PtsWellTestAnalysis()
	
```      



# CHANGELOG

## Version 1.2.1 28/1/2026
- Force units to be capital

## Version 1.2.0 27/1/2026
- Can resample data in time or depth
- Export to CSV, LAS and LINEWISE
- Fixes to handle some unusually formatted CSV files

## Version 1.1.4 21/10/2024
- Can work with open file streams.
- rounded TIMEDELTA and TIMESTAMPISO to 10us
- Changed encoding to ISO-8859-1 to avoid problems reading unicode in utf-8

## Version 1.1.3 13/09/2024
- Now works with TIMESTAMPISO when plotting vs. time.
- Updated sample data

## Version 1.1.2 29/07/2024
- Updated sample code in README.md

## Version 1.1.1 19/06/2024
- Improved CreateRunLogGuess method to split log in to multiple runs automatically.

## Version 1.1.0 12/06/2024
- Changed the column names to be consistant with industry norms.
- Added CreateRunLogGuess method to split log in to multiple runs automatically.

## Version 1.0.0 21/05/2024
- Released to PyPI