semvec/pypi-packages huggingface dataset:
check-type-hints 0.0.4
Helps you check type hints when you commit code.

### [check-type-hints](https://github.com/xgkk/check-type-hints)
### [pypi](https://pypi.org/project/check-type-hints/)
### What can it do? 
It is a simple pre-commit plug-in that helps you check type hints in committed python files. Currently, only python is supported

### Main function
#### function 1: `--filter`
It can help you filter folders that you don't want to check, like tests, pytests...
#### function 2: `--method`
It helps you filter function and method names that you don't want to check, such as get, post, put, and delete in Django view
#### function 3: `--ignore/--no-ignore`
By default, the plug-in checks type-hints that are not filled in, breaking the commit code and telling you where there is a problem. If you don't want to interrupt the commit, you can enable `--ignore`, which will only prompt warnings

### Example:
#### First:
`pip install pre-commit`
`pip install check-type-hints`
#### then:
Add file **.pre-commit-config.yaml** to the project root directory.
eg:
```yaml
repos:
  - repo: local
    hooks:
      - id: typehint-check
        name: Typehint Check
        entry: check_type_hints check --no-ignore --filter tests  --filter pytests --method get --method post --method put --method patch --method delete
        language: system
        types: [ python ]
        stages: [ commit ]
        pass_filenames: false
        verbose: true
```
#### and then:
`pre-commit install`
#### and finally:
You can enjoy it!
paramga 0.5.5
Parameter Regression GA tool
Requires Python: >=3.6
Keywords: genetic algorithm,optimization,scientific modelling

# Paramga

Paramga is a Genetic Algorithm tool for optimizing model parameters.

# Updating Version

`bumpversion major|minor|patch`

# Push to pypi

`python3 setup.py sdist bdist_wheel`
`python3 -m twine upload dist/*`
PyArrShow 1.0.8
Python ArrayShow for MRI data visualization.
Requires Python: >=3.8

# PyArrShow

## About

Python is presently the leading language for MRI data processing and reconstruction, such as in fastMRI challenge, etc. Due to MRI data usually containing multiple dimensional aspects, such as width-height-slice-coil-dynamic-modalities(such as different b-values in DWI, and different TE images in multi-echo GRE/SE sequence), visualization of processed or reconstructed results requires checking MRI data along specific dimensions,  and this need can not be simply satisfied by standard matplotlib. Additionally, in the data preparation stage, visually checking multi-dimensional inputs and outputs is quite important and necessary.

PyArrShow attempts to provide a Python tool with a similar functionality as the Matlab arrShow project. 

## Installation

Use the package manager pip to install PyArrShow.

```
pip install PyArrShow
```

#### Installing Directly from Source

If you want to install directly from the GitHub source, clone the repository, navigate to the PyArrShow root directory and run

```
pip install -e .
```

## Examples

Here is a code example for PyArrShow

```
import pyas 
import numpy as np
nparray_5d = np.random.rand(256,344,10,5,8)
pyas.PyArrShow().show(nparray_5d)
nparray_5d_c= np.random.rand(256,344,10,5,8) + 1j*np.random.rand(256,344,10,5,8)
pyas.PyArrShow().show(nparray_5d_c)
```

## License

PyArrShow is MIT licensed, as found in the LICENSE file.