config.yaml

# This config file is used by:
# config.py
# mcrasta.py
# Loglikelihood.py

# identifiers for experimental data
samplename: 'p5866'
section_id: '5866001'

# the section of experimental data defined by start and end times
mintime: 11900.58
maxtime: 11988.5

# spring constant of test machine
k: 0.0005

# characteristic length in microns (e.g. minimum grain size)
lc: 125

# window length for Savitsky-Golay filter used when calculating load point velocity (mcrasta.calc_derivative)
vel_windowlen: 20

# filter_windowlen is the window length for Savitsky-Golay filter used to filter/downsample dataset
# q is the downsample rate (takes every q-th sample) (mcrasta.downsample_dataset)
filter_windowlen: 20
q: 4

# pymc sampler parameters, ndr = number of draws, nch = number of chains, ntune = number of tuning draws, ncores = number of cores to use
ndr: 200000
nch: 4
ntune: 2000
ncores: 4

# acceleration threshold to flag critical times for integration in ODE solver,
# should be determined in advance using rsfdataviewer.py
threshold: 0.13

# prior distribution parameters for PyMC
# mu and sigma are used for LogNormal and HalfNormal distributions
# alpha and beta are used for Weibull distributions
# can add other distributions in mcrasta.get_priors, add any additional parameters needed to config.Prior
# new distribution parameters (e.g. mu, sigma, etc.) must be added to all priors even if not used
# can specify None if parameter is not needed for distribution
a_prior:
  dist_type: 'LogNormal'
  mu: -5
  sigma: 0.8
  alpha: None
  beta: None
b_prior:
  dist_type: 'LogNormal'
  mu: -5
  sigma: 0.8
  alpha: None
  beta: None
Dc_prior:
  dist_type: 'Weibull'
  mu: None
  sigma: None
  alpha: 1.5
  beta: 40
mu0_prior:
  dist_type: 'LogNormal'
  mu: -1
  sigma: 0.3
  alpha: None
  beta: None
s_prior:
  dist_type: 'Weibull'
  mu: None
  sigma: None
  alpha: 1.5
  beta: 0.2

input_data_dir: 'C:\Users\fich146\PycharmProjects\mcmcrsf_xfiles\data\FORGE_DataShare'
output_mcmc_dirname: 'mcmc_out'