Modified cmp_tree.py to first filter away all - (dashed) genes before calculating the statistics. This had a major inpact on how many columns were considered noisy.

Tried out robinson_foulds_distance in dendropy. Seem very robust against noise but also always gave the same distance no matter if noise reduction was made and the same value between different noise sets, i.e. too robust to be able to measure the success of the noise reduction algorithm in this project.

analyse.py: Now outputs the raw data, i.e. distances for filtered and unfiltered for the files parsed.

boxplot.py: Takes the new output and generates a boxplot for each set of data with the additional mean rendered as dots. Gives a better view of the performance of the filter and shows a slight decrease of the median for most cases.
Removed visualise.py that has been replaced by boxplot.py