semvec/pypi-packages huggingface dataset:
mrphy 0.2.0
A Pytorch based tool for MR physics simulations
License: MIT
Requires Python: >=3.8

# MRphy.py

A pytorch based MR simulator package.
[![](https://img.shields.io/badge/docs-stable-blue.svg)](https://tianrluo.github.io/MRphy.py/stable/index.html)
[![](https://img.shields.io/badge/docs-dev-blue.svg)](https://tianrluo.github.io/MRphy.py/dev/index.html)
[![codecov](https://codecov.io/gh/tianrluo/MRphy.py/branch/master/graph/badge.svg?token=83sKL5NADl)](https://codecov.io/gh/tianrluo/MRphy.py)
[![Actions Status](https://github.com/tianrluo/MRphy.py/workflows/Python%20package/badge.svg)](https://github.com/tianrluo/MRphy.py/actions)

Infrastructure of:\
[Joint Design of RF and Gradient Waveforms via Auto-Differentiation for 3D Tailored Exitation in MRI](https://ieeexplore.ieee.org/document/9439482)\
(arXiv: [https://arxiv.org/abs/2008.10594](https://arxiv.org/abs/2008.10594))

cite as:

```bib
@article{luo2021joint,
  author={Luo, Tianrui and Noll, Douglas C. and Fessler, Jeffrey A. and Nielsen, Jon-Fredrik},
  journal={IEEE Transactions on Medical Imaging}, 
  title={Joint Design of RF and gradient waveforms via auto-differentiation for 3D tailored excitation in MRI}, 
  year={2021},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TMI.2021.3083104}}
```

For the `interpT` feature, consider citing:
```bib
@inproceedings{luo2021MultiScale,
  title={Multi-scale Accelerated Auto-differentiable Bloch-simulation based joint design of excitation RF and gradient waveforms},
  booktitle={ISMRM},
  pages={3958},
  author={Tianrui Luo and Douglas C. Noll and Jeffrey A. Fessler and Jon-Fredrik Nielsen},
  year={2021}
}
```

## Branches

- `master`: Stable;
- `dev`: Ocassionally `git squash`'d, `git push --force`'d;
- `dev_cache`: Constantly `git push --force`'d.

Developments are mostly done on `dev_cache`; when they have passed local checks, `dev` will be `git rebase`'d to `dev_cache`, and sent for CI tests.
When enough updates have been accumulated, `dev` will be git squashed into one large commit, followed by having `master`-branch `git rebase`'d onto it.

## Installation

```sh
pip install mrphy
```

(The package is not yet sent to `conda`.)

## Demos

Check out files under `./test`.
After installation, one can quickly play with the tests through:

```sh
pytest -s
```

Only basic demo is available in this early version.
platos-closet 1.1.1
Package that tells the user if a planet can be detected by PLATO space mission
License: MIT

 The Planet class requires the following arguments for initialization
	- name (str): Name of the planet.
	- depth (int): Transit depth of the planet in parts per million (ppm).
	- duration (int): Transit duration of the planet in hours.
	- number (int, optional): Number of transits. Defaults to 3 if not provided.

	The Planet class provides the following methods:

	- noise_level(eta=7.1): Calculates the noise level of the planet transit signal at the detector level. The eta parameter is an optional statistical significance value (default: 7.1). Returns the calculated noise level as a float.

	- is_detectable(nsr, nsr_plato=34): Determines if the planet is detectable based on the noise level (nsr). The nsr_plato parameter is an optional threshold noise level for detection (default: 80). Returns a string indicating whether the planet is detectable or not.

	To use the package, create an instance of the Planet class by providing the required arguments (name, depth, and duration). Then, you can call the noise_level method to calculate the noise level and the is_detectable method to determine the detectability of the planet.

	Example usage: 
 
 	from package_name import Planet

	earth = Planet('Earth', 84, 13)
	nsr = earth.noise_level()
	detection_result = earth.is_detectable(nsr)
	print(f"{earth.name}: {detection_result}")