semvec/pypi-packages huggingface dataset:
openstb-simulator 0.7.0
Open-source sonar simulation toolbox
Requires Python: >=3.12

<!--

SPDX-FileCopyrightText: openSTB contributors
SPDX-License-Identifier: BSD-2-Clause-Patent

-->

openSTB sonar simulation framework
==================================

The openSTB sonar simulation is a modular framework for simulating the signals received
by a sonar system. It is currently in the early stages of development, so bugs are to be
expected.


License
-------

The simulator is available under the BSD-2-Clause plus patent license, the text of which
can be found in the `LICENSES/` directory or
[online](https://spdx.org/licenses/BSD-2-Clause-Patent.html). Some of the supporting
files are under the Creative Commons Zero v1.0 Universal license (effectively public
domain). Again, the license is available in the `LICENSES/` directory or
[online](https://spdx.org/licenses/CC0-1.0.html).


Documentation
-------------

The documentation for the simulator can be viewed at https://docs.openstb.dev


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

The simulator is published on [PyPI](https://pypi.org) as
[`openstb-simulator`](https://pypi.org/project/openstb-simulator). You can use your
preferred Python environment management tool to install it. For example, with pip:

```console
pip install openstb-simulator
```

For more installation options, see the documentation.


Running the simulator
---------------------

See the `examples/` directory for various examples of how to run the simulator. The
documentation includes more details of these examples.
jarvisplot 1.2.0
JarvisPLOT: YAML-driven plotting engine
Requires Python: >=3.10

# JarvisPLOT

JarvisPLOT is a lightweight, Python/Matplotlib-based plotting framework developed for **Jarvis-HEP**,  
but it can also be used as a **standalone scientific plotting tool**.

It provides a simple command-line interface (CLI) to generate publication-quality figures from YAML configuration files, with most layout and style decisions handled by predefined profiles and style cards.

---

## Installation 

```bash 
pip install jarvisplot
```

## Command-Line Usage

Display help information:

```bash
jplot -h
```

Run JarvisPLOT with one or more YAML configuration files:

```bash
jplot path/to/config.yaml
```

Rebuild local cache for the current project workdir:

```bash
jplot path/to/config.yaml --rebuild-cache
```

### Project Workdir and Cache

- You can set `project.workdir` in YAML.
- If `output.dir` is omitted, JarvisPLOT now defaults to `<workdir>/plots/`.
- Data cache is stored in `<workdir>/.cache/`.
- Profiling pipelines are prebuilt once and reused from cache when source fingerprint and profile settings are unchanged.
- Profiling uses a fast two-stage grid reduction (`pregrid` + render `bin`) for large datasets.

### Example: SUSYRun2 Ternary Plots

```bash
jplot ./bin/SUSYRun2_EWMSSM.yaml
jplot ./bin/SUSYRun2_GEWMSSM.yaml
```

> **Note:** The data file paths inside the YAML files must be updated to match your local setup.

---

## Notes

- Figures are saved automatically to the output paths defined in the YAML configuration.
- Common output formats include PNG and PDF (backend-dependent).
- JarvisPLOT works in headless environments (SSH, batch jobs) without any GUI backend.

---

## Requirements

### Python
- **Python ≥ 3.10** (tested on 3.10–3.13)

### Required Packages
- `numpy`
- `pandas`
- `matplotlib`
- `pyyaml`
- `jsonschema`
- `scipy` — numerical utilities
- `h5py` — required for loading HDF5 data files
- `shapely`
- `scipy`
- `sympy`

### Github Page
[https://github.com/Pengxuan-Zhu-Phys/Jarvis-PLOT](https://github.com/Pengxuan-Zhu-Phys/Jarvis-PLOT)

### Documentation
[https://pengxuan-zhu-phys.github.io/Jarvis-Docs/](https://pengxuan-zhu-phys.github.io/Jarvis-Docs/)

---

## License

MIT License
craft-ai-sdk 0.72.0
Craft AI MLOps platform SDK
Requires Python: >=3.10

# Craft AI Python SDK

This Python SDK lets you interact with Craft AI MLOps Platform.

## Installation
This project relies on **Python 3.10+**. Once a supported version of Python is installed, you can install `craft-ai-sdk` from PyPI with:

```console
pip install craft-ai-sdk
```

## Basic usage
You can configure the SDK by instantiating the `CraftAiSdk` class in this way:

```python
from craft_ai_sdk import CraftAiSdk

CRAFT_AI_SDK_TOKEN =  # your access key obtained from your settings page
CRAFT_AI_ENVIRONMENT_URL =  # url to your environment

sdk = CraftAiSdk(sdk_token=CRAFT_AI_SDK_TOKEN, environment_url=CRAFT_AI_ENVIRONMENT_URL)
```

If using the SDK in interactive mode, some additional feedbacks will be printed. You can force disable or enable those logs by either
* Setting the `verbose_log` SDK parameter
* Or setting the `SDK_VERBOSE_LOG` env var