semvec/pypi-packages huggingface dataset:
numerical_function_spaces 0.5.0
An attempt to numerically study the geometry of the Orlicz function spaces
License: MIT
Requires Python: <4.0,>=3.11

# numerical_function_spaces

An attempt to numerically study the geometry of the Orlicz function spaces

## Installation

```bash
$ pip install numerical_function_spaces
```
or 
```bash
git clone https://github.com/DyonOylloug/numerical_function_spaces
cd numerical_function_spaces
pip install .
```

## Usage
- Online documentation on [readthedocs.](https://numerical-function-spaces.readthedocs.io/en/latest/index.html)

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`numerical_function_spaces` was created by Adam Bohonos. It is licensed under the terms of the MIT license.

## Credits

`numerical_function_spaces` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
cython-fortran-file 0.2.7
An efficient package to read fortran-record files in Python.
License: MIT
Requires Python: >=3.9

# Cython fortran-file

[![Build and Test](https://github.com/cphyc/cython_fortran_file/actions/workflows/build-test.yaml/badge.svg)](https://github.com/cphyc/cython_fortran_file/actions/workflows/build-test.yaml)
[![PyPI](https://img.shields.io/pypi/v/cython_fortran_file)](https://pypi.org/project/cython_fortran_file)
[![Conda-forge](https://img.shields.io/conda/vn/conda-forge/cython-fortran-file.svg)](https://anaconda.org/conda-forge/cython-fortran-file)

This package is a fast and easy reader for record-based binary format, as written by Fortran.

## Installation

This packages requires a compiler to be installed on you system. If you're using Linux or MacOSX you should be fine. If you're using Windows, please get in touch with me or open an issue.
```
pip install cython_fortran_file
```
That's all!

## Using it
Here is a simple demonstration:

```python
from cython_fortran_file import FortranFile as FF

f = FF("/path/to/my/fortran/file.dat", mode="r")

# Skip 5 records
f.skip(5)

# Read one record (an array of `double`)
data = f.read_vector("d")
assert data.dtype == np.float64

# Read one record (an array of signed `int`)
data = f.read_vector("i")
assert data.dtype == np.int32

# Read one *single* int. This will fail if there is more to read!
v = f.read_int()

# f _looks_ like a regular file descriptor
f.tell()
f.seek(0)
f.close()
```

It also supports `with` statement so that you can't forget to close the file handler
```python
with FF("/path/to/my/fortran/file.dat") as f:
    f.skip(5)

    data = f.read_vector("d")  # Read a vector of doubles (as usual)
```

## Data types

The argument of `read_vector` follows the convention of the python struct package (C convention). See https://docs.python.org/3.5/library/struct.html#format-characters for the full list. Here is a shorter version:

Argument | Fortran type | C type     | Numpy dtype
---------|--------------|------------|--------------
`d`      | `real(8)`    | `double`   | `np.float64`
`f`      | `real(4)`    | `float`    | `np.float32`
`i`      | `integer`    | `int`      | `np.int32`
`l`      | `integer(8)` | `long`     | `np.int64`