CRinGe.py: initial attempt at a generator. Based on arXiv:1411.5928

plotCRinGe.py: plot generated rings

CRinGeView.py: bokeh application to interactively display generator output.

CRinGe_FIP2.py: Unsuccessful attempt to include unsupervised generator outputs by running the following training sequence:

1. initialize unsupervised inputs with random vector;
2. run forward path and calculate loss;
3. update unsupervised parameters using autograd;
4. run forward path and calculate loss;
5. update neural network parameters;

• It might be worth revisiting this, paying more attention to the way the input parameters are updated...

CRinGeGAN.py: implementation of a conditional generative adversarial network, inspired by arXiv:1605.05396, arXiv:1411.1784, ...

plotTrainLog.py: very simple script to plot training progress using the standard stream outputs of the scripts above.

CRinGe_MultiGaus.py/CRinGe_MultiLogNorm.py: multiple peaks with charge PDFs only.

CRinGe_MultiGaus_Time.py/CRinGe_MultiLogNorm_Time.py: multiple peaks with charge PDFs and single peak for timing, charge and timing are independent.

CRinGe_MultiGausTime_Corr.py: mutiple gaussian peaks for correlated charge and timing peaks.

plotCRinGe_MultiGaus_G.py: script to plot charge PDF from multi-gaussian NN outputs for the tube user specified.

plotCRinGe_MultiLogNorm_G.py: script to plot charge PDF from multi-lognorm NN outputs for the tube user specified.