`nmmn` package
================
Tools for astronomy, data analysis, time series, numerical simulations, gamma-ray astronomy and more! These are modules I wrote which I find useful—for whatever reason—in my research.
List of modules available ([more info here](http://rsnemmen.github.io/nmmn/)):
* `astro`: astronomy
* `dsp`: signal processing
* `lsd`: misc. operations on arrays, lists, dictionaries and sets
* `stats`: statistical methods
* [`sed`: spectral energy distributions](./docs/SEDs.ipynb)
* `plots`: custom plots
* `fermi`: Fermi LAT analysis methods
* `bayes`: Bayesian tools for dealing with posterior distributions
* `grmhd`: tools for dealing with GRMHD numerical simulations
Very basic [documentation](http://rsnemmen.github.io/nmmn/) for the package. Generated with Sphinx.
# Installation
You have a couple of options to install the module:
### 1. Install using `pip`:
```
pip install nmmn
```
### 2. Install the module on the system’s python library path:
```
git clone https://github.com/rsnemmen/nmmn.git
cd nmmn
python setup.py install
```
### 3. Install the package with a symlink, so that changes to the source files will be immediately available:
```
git clone https://github.com/rsnemmen/nmmn.git
cd nmmn
python setup.py develop
```
This last method is preferred if you want the latest, bleeding-edge updates in the repo. You may need to run the last command with `sudo`.
## Updating
If you installed with `pip` (method 1), to upgrade the package to the latest stable version use
pip install --upgrade nmmn
If you installed with the `setup.py` script and the `develop` option (method 3), use
cd /path/to/nmmn
git pull
# Usage
First import the specific module that you want to use:
import nmmn.lsd
Then call the method you need. For example, to remove all `nan` and `inf` elements from a `numpy` array:
```python
import numpy as np
# generates some array with nan and inf
x=np.array([1,2,np.nan,np.inf])
# removes strange elements
xok=nmmn.lsd.delweird(x)
```
For more examples, please refer to the [examples doc](examples.md).
# TODO
* [x] need more examples of how to use the modules
* [x] add IFU data cubes method (refer to [ifscube](https://ifscube.readthedocs.io/en/latest/))
# License
See `LICENSE` file.
If you have suggestions of improvements, by all means please contribute with a pull request! :)
The MIT License (MIT). Copyright (c) 2020 [Rodrigo Nemmen](http://rodrigonemmen.com)
[Visit the author's web page](https://rodrigonemmen.com/) and/or follow him on twitter ([@nemmen](https://twitter.com/nemmen)).
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