semvec/pypi-packages huggingface dataset:
CAKED 0.1.7
A dataloader abstract package
Requires Python: >=3.8

# CAKED

[![Actions Status][actions-badge]][actions-link]
[![PyPI version][pypi-version]][pypi-link]
[![PyPI platforms][pypi-platforms]][pypi-link]

A package to load tomograms and subtomograms from different sources into a
[PyTorch DataLoader](https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader)
class.

The DiskDataLoader and DiskDataset classes were initially developed for
[Affinity-VAE](https://github.com/alan-turing-institute/affinity-vae) by Marjan
Famili (@marjanfamili), Jola Mirecka (@jolaem) and Camila Rangel-Smith
(@crangelsmith). These authors have also prepared and curated the corresponding
test data.

## Installation

```bash
python -m venv env
source env/bin/activate
python -m pip install --upgrade pip
python -m pip install caked
```

From source:

```bash
git clone https://github.com/alan-turing-institute/CAKED
cd CAKED
python -m pip install .
```

## Usage

## Contributing

See [CONTRIBUTING.md](CONTRIBUTING.md) for instructions on how to contribute.

## License

Distributed under the terms of the [MIT license](LICENSE).

This packaged was based on this very useful and well built
[project template](https://github.com/alan-turing-institute/python-project-template).

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[actions-link]:             https://github.com/alan-turing-institute/CAKED/actions
[pypi-link]:                https://pypi.org/project/CAKED/
[pypi-platforms]:           https://img.shields.io/pypi/pyversions/CAKED
[pypi-version]:             https://img.shields.io/pypi/v/CAKED
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pydotthz 1.0.1
This Python Package allows interfacing with dotThz files.
Requires Python: >=3.7

# Interface with dotTHz files using Python

[![PEP8](https://github.com/dotTHzTAG/pydotthz/actions/workflows/format.yml/badge.svg)](https://github.com/dotTHzTAG/pydotthz/actions/workflows/format.yml)
[![PyPI](https://img.shields.io/pypi/v/pydotthz?label=pypi%20package)](https://pypi.org/project/pydotthz/)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/pydotthz)](https://pypi.org/project/pydotthz/)

This crate provides an easy way to interface with [dotTHz](https://github.com/dotTHzTAG) files in Python.

Install it

```shell
pip install pydotthz
```

or

```shell
pip3 install pydotthz
```

and then use like specified in the following example:

```python
from pathlib import Path
import numpy as np
from pydotthz import DotthzFile, DotthzMetaData

if __name__ == "__main__":
    # Sample data
    time = np.linspace(0, 1, 100)  # your time array
    data = np.random.rand(100)  # example 3D data array

    # save the file
    path1 = Path("test1.thz")
    with DotthzFile(path1, "w") as file:
        file.create_measurement("Measurement 1")

        # create meta-data
        metadata = DotthzMetaData()
        metadata.user = "John Doe"
        metadata.version = "1.00"
        metadata.instrument = "Toptica TeraFlash Pro"
        metadata.mode = "THz-TDS/Transmission"

        file["Measurement 1"].set_metadata(metadata)

        # for thzVer 1.00, we need to transpose the array!
        # important: do not manipulate keys on the `dataset` field, otherwise it won't be written to the file.
        file["Measurement 1"]["Sample"] = np.array([time, data]).T

```

Further examples (e.g. THz image scans) can be found in the [examples](https://github.com/dotTHzTAG/pydotthz/examples) directory.

### Requirements

Requires [hdf5](https://www.hdfgroup.org/solutions/hdf5/) to be installed.
arclength-continuation 0.1.7
Python script that demonstrates how to use pseudo-arclength continuation.
Requires Python: >=3.7
Keywords: math, continuation, numerical methods

[![DOI](https://zenodo.org/badge/557482325.svg)](https://doi.org/10.5281/zenodo.15733515)
[![pip](https://img.shields.io/pypi/v/arclength_continuation)](https://pypi.org/project/arclength_continuation/)

# Pseudo-Arclength Continuation Example

This repository contains a Python script (`arclength_continuation.py`) that demonstrates how to use Newton's method in conjunction with a pseudo-arclength continuation technique to find points on the unit circle. This approach can handle singular points where naive continuation might fail.

## Installation


`arclength-continuation` can be installed via `pip` or an equivalent via:

```console
pip install arclength-continuation
```

## Usage

```console
arclength_continuation -d -0.2 -n 30 -t 1e-9 --no-predictor
```