This package provides some extra functionality for plotting baycomp's posteriors.
Project description
Baycomp Plotting
The baycomp_plotting is a python package for building good-looking plots of bayesian posteriors obtained with baycomp.
This package could be useful for scientific purposes, specially in the area of Machine Learning.
Author
- Mario Juez-Gil <mariojg@ubu.es>
Department of Computer Science
Universidad de Burgos
ADMIRABLE Research Group
Installation
This package can be installed using PIP.
pip install baycomp_plotting
Basic Usage
The package can be imported as follows:
import baycomp_plotting as bplt
Two plotting functions (tern
, and dens
), and one class with four matplotlib alternative colors (Color
) are provided.
Colors
Four alternative colors to default matplotlib colors are provided:
Example:
import baycomp_plotting as bplt
print(bplt.Color.BLUE)
Output:
'#008ece'
Density plots
For plotting the comparison of two classifiers on a single dataset, dens
function could be used. It's parameters are the following:
p
: baycomp posterior.label
: label of the density function.ls
: line style (use a matplotlib line style) [default:-
]color
: density function color [default:Color.BLUE
]
Example:
import baycomp_plotting as bplt
import baycomp as bc
posterior = bc.CorrelatedTTest(left_classifier_acc, right_classifier_acc, rope=0.01)
fig = bplt.dens(posterior, label='C1', ls='-', color=bplt.Color.BLUE)
Output:
The output figure will have a new function named add_posterior
so you can add more posteriors to the figure. The parameters are the same as for dens
.
Example:
import baycomp_plotting as bplt
import baycomp as bc
posterior = bc.CorrelatedTTest(left_classifier_1_acc, right_classifier_acc, rope=0.01)
posterior_1 = bc.CorrelatedTTest(left_classifier_2_acc, right_classifier_acc, rope=0.01)
fig = bplt.dens(posterior, label='C1', ls='-', color=bplt.Color.BLUE)
fig.add_posterior(posterior_1, label='C2', ls=(0,(5,1)), color=bplt.Color.GRAY)
fig.legend() # you can show the legend
Output:
Ternary plots
For plotting the comparison of two classifiers on multiple datasets using a ternary plot, tern
function could be used. It's parameters are the following:
p
: baycomp posterior.names
: an array containing Left and Right region labels. [default:["L", "R"]
]
Example:
import baycomp_plotting as bplt
import baycomp as bc
posterior = bc.HierarchicalTest(left_classifier_acc, right_classifier_acc, rope=0.01)
fig = bplt.tern(posterior)
Output:
Comparison against baycomp default plots
Density:
Ternary:
Contribute
Feel free to submit any pull requests 😊
Acknowlegments
This work was supported by the pre-doctoral grant (EDU/1100/2017) of the Consejería de Educación of the Junta de Castilla y León, Spain, and the European Social Fund.
License
This work is licensed under GNU GPL v3.
Citation policy
Please, cite this work as:
@software{baycomp_plotting,
author = {Mario Juez-Gil},
title = {{mjuez/baycomp_plotting}},
month = nov,
year = 2020,
publisher = {Zenodo},
version = {v1.0},
doi = {10.5281/zenodo.4244542},
url = {https://doi.org/10.5281/zenodo.4244542}
}
Project details
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