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TO_DO.md

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To be discussed:

  • satellite data
  • periodic variables
  • log10 variables etc.
  • flux constraints
  • for plots: t_0, \Delta t_0, or t_0 - 2456780 ???
  • should version be printed on output?
  • settings for making plot without a fit - how input should look like for best_model?
  • how the output should look like?

Documentation:

  • Delta t_0
  • binary source
  • x_caustic_in etc.
  • ob08092-o4_prior.yaml
  • posterior files
  • print model

List of task to be done:

( boldface - do this before sending e-mail around)

  • some documentation - see above
  • add one more fitting method?
  • corner.py
  • requirements.txt
  • n_walkers for EMCEE - default is x4 and remove from minimal yaml file - "SIMPLIFIES INPUT"
  • Mroz+20 - finish
  • print fixed parameters at begin or "no fixed parameters", so that full model can be extracted without the input file
  • LD coeffs as parameters
  • all_parameters in _get_parameters_ordered() and _check_fixed_parameters() - combine in a single one
  • note that parameters are re-ordered (maybe in future add option for specifying order)
  • datasets - guessing 245/246; plotting as well
  • no_negative_blending_flux - only first dataset, or all datasets? Maybe add one more option
  • trace plot
  • allow plotting multiple models
  • for plot script add printing chi2 and fluxes
  • allow making plots without a fit
  • starting parameters are read from file
  • some of the starting values are calculated based on equation given in yaml file, eg. "s: equation 100 / t_E" and then substitute each value of t_E and then use: "exec('out = 100 / 20.12345')" and use variable 'out'; This requires import from math of log, log10, arcsin etc.; make sure "s" in x_caustic_in is not replaced etc.;
  • if Cassan08 paramaterization is used then make sure times are >2450000.
  • self._plots - check what is there
  • add automatic "obvious" checks on parameters: t_E>0, rho>0, s>0, 1>q>0 - even if they are not provided, then model should be rejected and warning given
  • binary source models - print fluxes of both sources separately
  • Fitting method to be added: scipy.optimize, pymultinest, ???
  • allow plotting many random models from posterior
  • warnings if plots will overwrite existing files
  • MulensData() - use try/except with meaningful error message
  • plot title
  • make plots tighter, i.e., reduce white space
  • Add ln_prior values to blob? At some point we will want to save that information in output files
  • settings['input_file_root'] = input_file_root - in final function and use it for default output files names
  • posterior output: 1) add log(prior), 2) add chi2 or equivalent, 3) add option to add fluxes
  • check if output files (including plots) exists at the begin
  • add check if 't_0' is covered by data and give warning if not
  • print number of models calculated
  • full support of satellite data
  • periodic variables - suggest it for alpha, x_caustic_X
  • check if data files exist
  • allow log10() of parameter
  • Event.get_chi2() - add fit_blending=False option
  • allow turning off flux printing
  • warnings on time plotting and data limits - checks for add/subtract 245/246
  • if code fails during fitting, then it should still print the best model found so far - add try/except in _run_fit()
  • example how to run fits on a grid of (s,q)
  • allow periodic print of best model etc.
  • plot trajectory
  • for parallax models check if t_0_par is fixed and give warning, if not
  • fits with 0 blending flux for first dataset
  • when plotting best model, plot ~100 points based on t_E etc. + all visible epochs in data so that anomalies are not missed etc.
  • add scipy to _check_imports() - requires siginificant code to be added to _check_imports() in order to find out if t_E prior is used
  • if corner could not be imported, then give link to specific file in error message
  • flux constraints for binary source models (note that for plotting it is now set to first dataset)
  • method to be used: https://lmfit.github.io/lmfit-py/
  • allow Model.set_magnification_methods_parameters()
  • methods - if only single string is provided, then this is a default method
  • print all models
  • print current best model - each minute, each nth model etc.
  • print every n-th model