semvec/pypi-packages huggingface dataset:
adata-query 0.2.1
Fetch and format data matrices from AnnData
Requires Python: >=3.11

# 🔎 AnnDataQuery

[![PyPI pyversions](https://img.shields.io/pypi/pyversions/adata_query.svg)](https://pypi.python.org/pypi/adata_query/)
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[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

Fetch data matrices from AnnData and format as `np.ndarray` or `torch.Tensor`, on any device.

## Installation

### Using UV (Recommended)

```bash
# Install the package
uv add adata-query

# Or for development
uv pip install -e .
```

### Using pip

```bash
pip install adata-query
```

### Development Installation

```bash
# Clone the repository
git clone https://github.com/mvinyard/AnnDataQuery.git
cd AnnDataQuery

# Install with UV (recommended)
uv sync --dev

# Or with pip
pip install -e .
```

## Get started

Example: [notebook](https://colab.research.google.com/github/mvinyard/AnnDataQuery/blob/main/notebooks/anndata_query_tutorial.ipynb)
rl-soumya 0.1
RL utilities and demos.
Requires Python: >=3.9

# rl-soumya

`rl-soumya` provides tiny building blocks for experimenting with reinforcement-learning ideas.  
The current release ships a reference implementation of a simple epsilon-greedy multi-armed
bandit loop and a CLI demo that shows it in action.

## Installation

```bash
pip install rl-soumya
```

## Usage

```python
from rl_soumya import train_epsilon_greedy

# Create reward generators for each arm
def make_generator(mean):
    while True:
        yield mean

arms = [make_generator(0.4), make_generator(0.6), make_generator(0.9)]
rewards = train_epsilon_greedy(arms, epsilon=0.05, steps=500)
print(f"Total reward collected: {rewards[-1]:.2f}")
```

Run the included demo from a shell:

```bash
python -m rl_soumya.main
```

## Development

```bash
python3.11 setup.py sdist bdist_wheel
pip install dist/rl_soumya-0.1-py3-none-any.whl
```

## License

MIT
wordcounter-tool 1.0.1
A versatile word counting tool supporting multiple input methods

# WordCounter Tool

一个多功能单词计数工具包，支持直接粘贴、多行输入和文件读取三种方式。

## 功能特点

- 📝 支持直接粘贴文本统计
- 📄 支持多行文本输入
- 📁 支持从文件读取内容
- 🔢 准确的单词计数算法
- 🖥️ 友好的命令行界面

## 安装

```bash
pip install wordcounter-tool
```

## 使用方法

### 命令行使用

安装后，可以直接在命令行中使用：

```bash
wordcounter
```

然后按照菜单提示选择输入方式。

### 作为 Python 模块使用

```python
from wordcounter_tool import count_words, count_words_from_file

# 直接统计文本
text = "Hello world, this is a test."
result = count_words(text)
print(f"单词数量: {result}")

# 从文件统计
result = count_words_from_file("example.txt")
print(f"文件单词数量: {result}")
```

## 输入方式

1. **直接粘贴**: 快速粘贴单行文本
2. **多行输入**: 支持输入多行文本，以空行结束
3. **文件读取**: 从文本文件读取内容

## 许可证

MIT License
picsl-vtk-affine-demo 0.0.1
UPenn BE5370 Affine Transformations Teaching Tool
Requires Python: >=3.9

# Affine Transformations Teaching Tool

Interactive VTK app (via Trame) to explore affine transformations on a mesh. Used as a teaching aid when teaching about different ways to represent rotations in 3D and how to decompose affine transformations via polar decomposition.

## What it does
- Visualizes a VTK mesh with cube axes and camera controls
- Applies affine transforms:
  - Rotation: Euler angles, Quaternions, Axis–Angle
  - Translation, Scaling, Shear (via Euler-like angles)
- Shows live 3x3 rotation and 4x4 affine matrices
- Mesh controls: representation, color-by array, LUT presets, opacity
- Reset buttons for each transform and global reset

## Requirements
- Python 3.9+
- numpy, scipy, vtk
- trame, trame-vuetify, trame-vtk, trame-components

Install:
```bash
python3 -m pip install picsl_vtk_affine_demo
```

## Run
```bash
python3 -m picsl_vtk_affine_demo
```
Open the URL printed in the terminal (e.g., http://localhost:8080).

## Usage
- Use the drawer to pick a transform card (Rotation, Quaternions, Axis–Angle, Translation, Scaling, Shear).
- Sliders and numeric inputs are synchronized; edits update the view and matrices.
- Use “Reset” buttons to restore defaults.