nmmn 0.8.1

Miscellaneous methods for astronomy, dealing with arrays, statistical distributions and computing goodness-of-fit

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 submodules 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

• 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 modules.

# 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:

` python setup.py install `

3. Install the package with a symlink, so that changes to the source files will be immediately available:

` python setup.py develop `

This last method is preferred to sync with changes in the repo. You may need to run the last command with sudo.

To upgrade the package to the latest stable version, try

pip install –upgrade nmmn

if you installed with pip. If you installed with the setup.py script and the develop option, try

cd /path/to/nmmn git pull

# Usage

Example 1: Remove all nan and inf elements from a numpy array.

`python import nmmn.lsd, numpy x=numpy.array([1,2,numpy.nan,numpy.inf]) xok=nmmn.lsd.delweird(x) `

Example 2: Reads SED generated by [grmonty](https://github.com/rsnemmen/grmonty).

`python import nmmn.sed s=nmmn.sed.SED() s.grmonty('grmonty.spec') plot(s.lognu, s.ll) `

Now it is easy to compute the bolometric luminosity: s.bol().

TBD

# TODO

• [ ] need more examples of how to use the modules

• [ ] add IFU data cubes method

# 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) 2018 [Rodrigo Nemmen](http://rodrigonemmen.com)

[Visit the author’s web page](http://rodrigonemmen.com/) and/or follow him on twitter ([@nemmen](https://twitter.com/nemmen)).