Updated install docs and moved to headers

A library to leverage python wrapped Community Sensor Models (CSMs) for common spatial/sensor operations and testing.

**References:**

## References:

- CSM (usgscsm): https://github.com/USGS-Astrogeology/usgscsm

- Abstraction Layer for Ephemerides (ALE): https://github.com/USGS-Astrogeology/ale

<hr>

**Overview:**

## Overview

We currently use Knoten to help test our supported CSM implementations against well established [ISIS3 camera models](https://github.com/USGS-Astrogeology/ISIS3). In short, The CSM standard, now at version 3.0.3, is a framework that provides a well-defined application program interface (API) for multiple types of sensors and has been widely adopted by remote sensing software systems (e.g. BAE's Socet GXP, Harris Corp.'s ENVI, Hexagon's ERDAS Imagine, and recently added to the NASA AMES Stereo Pipeline [ASP]). Our support for CSM is explained in this [abstract](https://www.hou.usra.edu/meetings/informatics2018/pdf/6040.pdf) and a recently submitted paper (not yet available). Currently, we support **Framing** and **Pushbroom** (line scanner) types of sensor models in the [usgscsm](https://github.com/USGS-Astrogeology/usgscsm) library. 

<hr>

Installing:

## Installing

1. download knoten's environment.yml

2. Install Anaconda or Miniconda

3. Within an conda terminal, type:

You can install the latest build via conda

```

conda install -c usgs-astrogeology -c conda-forge knoten

```

You can also do a local install using the following steps within a clone of the repository

1. Install the dependencies

```

conda env create -f environment.yml

```

2. Install the package

```

python setup.py install

```

<hr>

**Status Report - November 2019:**

## Status Report - November 2019

For full testing reports and example usage, please see the linked example Jupyter notebooks in the table below.