Setup
Setting up RTKLIB Tools and dependencies
##Installation Notes Before we can use RTKLIB-Tools, we will first need to set up the dependencies in environment variables required. RTKLIB-Tools is a Python oriented tool kit, and is thus a a set of interpreted scrpts, with dependencies involving other Python libraries. Some of RTKLIB-Tools' dependencies however, such as RTKLIB, are binary files that must be compiled from original source code. This setup tutorial will step through installing and configuring a UNIX-based environment, however is entirely reliant upon open source code that should be freely available for alternate operating systems.
RTKLIB is the open source project used by RTKLIB-Tools. This project is maintained by Tomoji Takasu and is hosted at:
Current developmtn code can also be found at the project's github repo:
https://github.com/tomojitakasu/RTKLIB
Once we have downloaded the available source code, we will then need to compile into executable binary file which can later be called upon for batch operations using RTKLIB-Tools. Its also required to install some additional required C compiler and Linear Algebra packs in order to compile RTKLIB from source. These can be installed using the package, for example:
sudo apt-get install build-essential
sudo apt-get install automake
sudo apt-get install checkinstall
sudo apt-get install liblapack3gf
sudo apt-get install libblas3gfOnce we have install the necessary dependencies and downloaded the original source code, we can simply enter the source code's /app directory and execute the makefile script:
cd app/
sudo bash makeall.shThe compiled binary file will simply be generated within /app/<name>/gcc, where <name> is the name for the function. Modifying the file permissions may be necessary to allow the file to be executable: chmod +x <executable name>
RTKLIB-Tools uses a host of other python resorses including but not limited to:
Python 3.3
[IPython](http://ipython.org/): An interactive python environment
[Notebook](http://ipython.org/notebook.html): An IPython addon for web-based interactive computational environment
[matplotlib](http://matplotlib.org/): A python plotting library used to produces quality plots and figures
[NumPy](http://www.numpy.org/): A fundamental package for scientific computing with Python
[pandas](http://pandas.pydata.org/): A library providing high-performance data structures and data analysis tools for python
Setting up each python dependencies mentioned above can be tedious, if not repetitive. An easy alternative is to use a Python distribution tool, perhaps one intended for large-scale data processing, predictive analytics, and scientific computing. This is what Continuum provides for free with:
Anaconda: a convenient python distribution tool
Download the installation file for linux and simply run shell script using this as seen here:
bash <downloaded file>Further documentation can be found at the Conda Into Page
