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1. Install the latest version of R from http://cran.r-project.org/bin/windows/base/ with default settings. Under the default settings, R should be installed in the "C:\Program Files\R" directory.
   

2. Run R in interactive mode by executing R.exe as an Administrator. It would be available at "C:\Program Files\R\R-3.1.1\bin\R.exe" and install the various necessary packages by entering the following commands in the command prompt:
   install.packages("ggplot2",dependencies=T)

   install.packages("gstat",dependencies=T)

   install.packages("moments",dependencies=T)

   install.packages("fields",dependencies=T)

   install.packages("GA",dependencies=T)

   install.packages("spdep",dependencies=T)

   install.packages("rgeos",dependencies=T)

   install.packages("fields",dependencies=T)

   install.packages("gWidgets",dependencies=T)

   install.packages("gridExtra",dependencies=T)

   
   

3. Download the code from https://uofi.box.com/s/g354lm5av36uz0v27q75 Extract the zipped folder and you should be able to see the contents as shown below.
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   Execution
   
   
4. Execute the application by double clicking the 'Triaxus ScriptLaunch Trial' shortcut.
   Image RemovedYou will see an interface as shown below.
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5. Select the main directory for the application where all the files exist as the working directory, by clicking on the Set working directory button. 
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6. Copy all the data file to be used by clicking on the browse button to choose an appropriate source data file.
   Image Removedfiles to the 'Input' folder of the Triaxus script directory.
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7. Select the various Physical and/or Biological features that you want the script to consider, by checking the appropriate boxes adjacent to each of the features.
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8. Click the 'Run script' button to start the script execution. 
9. The Console window would give real time status updates on the script's execution.
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10. Once the script finishes execution, the output files should have been generated in inside the same folder designated as the working directory. An Output file should have been generated for each of the features selected.
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11. Sample Outputs generated from the Triaxus Script for the Temperature and SUNA Nitrate features Triaxus Script Output : Feature = Temperature , Triaxus Script : Feature = SUNA Nitrate

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1. Install Python version 2.7 from https://www.python.org/download/releases/2.7.7/

2. Install the scikit-learn machine learning library available as "scikit‑learn‑0.15.1.win32‑py2.7.exe" at
   http://www.lfd.uci.edu/~gohlke/pythonlibs/#scikit-learn

3. Installing the Scipy stack for python 2.7 available as "Scipy-stack-14.5.30.win32-py2.7.exe" at
   http://www.lfd.uci.edu/~gohlke/pythonlibs/#scipy-stack

4. Download the code from https://uofi.box.com/s/h6pvnackfmvq3kstzjznzz2tniz91fl5lsubebin Extract the zipped folder and you should be able to see the contents as shown below.
   
5. Execute the application by double clicking on the 'Seabird Script' shortcut.
   
6. Choose the directory where all the input data files as the working directory by clicking on the 'Choose working directory' button.
    
7. Enter a threshold value for the Power Spectra method if necessary and Click the 'Run Seabird script' button.
   
8. Once the Script finishes execution, the output files should have been generated in the folder designated as the working directory.
   

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