UT-CHG / BET

Python package for data-consistent stochastic inverse and forward problems.
http://ut-chg.github.io/BET
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Create better (and simpler) plotting routines for density based approach #405

Open eecsu opened 1 year ago

eecsu commented 1 year ago

2d marginal scatter plots with r values (using get_weights from the sample set) should be made as well as kde approximations in 1 and 2d based on r values.

This should be in a different module since plotP.py was made for plotting based on probability computations not densities. Suggested name of new module: plotDensities.py.

One such 2d scatter plot could be done as simply as follows:

plt.scatter(input_samples.get_values()[:,0], input_samples.get_values()[:,1], c=input_samples.get_weights())

or something to that effect.