Bayesian statistics plays an important role in data analysis. Particularly in the case of model comparison, Bayesian evidence and Bayes factor determination are well-known methods. This python module can plot beautiful 2D plots, with the x-axis as models and y-axis as log evidence.For determining log evidence you can use pymultinest or nestle.
git clone https://github.com/antolonappan/Bayesian-Evidence-Plotter.git.
cd Bayesian-Evidence-Plotter.
python setup.py install
from evidence_plotter import plotter
fig = plotter('model.txt','evidence.txt','legend_of_plot')
fig.plot()
If no error occurred, plot will be saved as 'legend_of_plot.pdf'

plotter(model_file,evidence_file,plotlabel,lw_ref=0.3,lw_bf=0.2,bf_x=0.2,bf_y=0.2,color='r')
* model_file : File containing model names.
* evidence_file : File containing log evidence values.
* plotlabel : Legend of the plot, for example data used for comparing models.
* lw_ref (optional) : Line width of reference dashed line.
* lw_bf (optional) : Line width of verticle line.
* bf_x (optional) : x-axis correction for placing Bayes factor values.(0.1<bf_x<0.4)
* bf_y (optional) : y-axis correction for placing Bayes factor values.(0.1<bf_y<0.4)
* color (optional) : Color of evidence points('r','g','b')
For a particular model, if the evidence point is above the reference dashed line the Bayes factor tells the evidence of that model against the reference model, else it's the evidence of the reference model against that model. For evidence scale, please refer Jeffrey's scale