punpy.mc.mc_propagation.MCPropagation#
- class punpy.mc.mc_propagation.MCPropagation(steps, parallel_cores=0, dtype=None, verbose=False, MCdimlast=True)[source]#
Class to propagate uncertainties using Monte Carlo (MC)
- Parameters:
steps (int) – number of MC iterations
parallel_cores (int) – number of CPU to be used in parallel processing
dtype (numpy dtype) – numpy dtype for output variables
verbose (bool) – bool to set if logging info should be printed
MCdimlast (bool) – bool to set whether the MC dimension should be moved to the last dimension when running through the measurment function (when parallel_cores==0). This can be useful for broadcasting within the measurement function. defaults to False
Methods
__init__
(steps[, parallel_cores, dtype, ...])combine_samples
(MC_samples)Function to combine MC samples from individual runs
generate_MC_sample
(x, u_x, corr_x[, ...])function to generate MC sample for input quantities
generate_MC_sample_cov
(x, cov_x[, ...])function to generate MC sample for input quantities from covariance matrix
process_samples
(MC_x, MC_y[, return_corr, ...])Run the MC-generated samples of input quantities through the measurement function and calculate correlation matrix if required.
propagate_cov
(func, x, cov_x[, param_fixed, ...])Propagate uncertainties with given covariance matrix through measurement function with n input quantities.
propagate_cov_flattened
(func, x, cov_x[, ...])Propagate uncertainties with given covariance matrix through measurement function with n input quantities.
propagate_random
(func, x, u_x[, corr_x, ...])Propagate random uncertainties through measurement function with n input quantities.
propagate_standard
(func, x, u_x, corr_x[, ...])Propagate uncertainties through measurement function with n input quantities.
propagate_systematic
(func, x, u_x[, corr_x, ...])Propagate systematic uncertainties through measurement function with n input quantities.
run_samples
(func, MC_x[, output_vars, ...])process all the MC samples of input quantities through the measurand function