parameters.optimize submodule

cg_openmm.parameters.optimize.calculate_C_v_fitness(C_v, T_list)[source]
cg_openmm.parameters.optimize.get_fwhm_symmetry(C_v, T_list)[source]
cg_openmm.parameters.optimize.get_num_maxima(C_v)[source]
cg_openmm.parameters.optimize.optimize_force_field_parameters_Cv_FWHM(cgmodel, file_list, temperature_list, param_bounds_dict, frame_begin=0, frame_end=-1, sample_spacing=1, sparsify_stride=1, output_data='output.nc', verbose=False, n_cpu=12, min_eff_samples=50, n_trial_boot=200, num_intermediate_states=0, plotfile='optimize_FWHM_iterations.pdf', min_method='TNC')[source]

Generalized function for optimizating a set of cgmodel force field parameters to minimize the full-width half-maximum (FWHM) of heat capacity as a function of temperature. Energy re-evaluation and MBAR reweighting is used in place of a full simulation whenever possible.

Parameters

  • cgmodel (class) – CGModel() class object used to generate the original simulation energies

  • file_list (list or str) – List of replica trajectory files to evaluate the energies of

  • temperature_list (List( float * simtk.unit.temperature )) – List of temperatures associated with file_list

  • param_bounds_dict (dict{'param_name': (bound_lo * simtk.unit, bound_hi * simtk.unit)}) – dictionary containing force field parameter names and bounds. Parameters not specified will use the fixed values defined in the cgmodel.

  • frame_begin (int) – analyze starting from this frame, discarding all prior as equilibration period (default=0)

  • frame_end (int) – analyze up to this frame only, discarding the rest (default=-1).

  • sample_spacing (int) – spacing of uncorrelated data points, for example determined from pymbar timeseries subsampleCorrelatedData (default=1)

  • sparsify_stride (int) – advance by this many frames between each energy evaluation (default=1)

  • verbose (Boolean) – option to print out detailed per-particle parameter changes (default=False)

  • n_cpu (int) – number of cpus for running parallel energy evaluations (default=1)

  • min_eff_samples (int) – minimum number of effective samples determined from the mbar object, below which a full simulation is needed (default=50)

  • min_method (str) – SciPy minimize method to use (default=’TNC’)

  • num_intermediate_states (int) – The number of states to insert between existing states in ‘temperature_list’ (default=0)

  • plotfile (str) – path to filename to output plot (default=’optimize_FWHM_iterations.pdf’)

Returns

  • opt_param_dict - a dictionary containing the optimized force field parameters

  • opt_results - scipy minimize results summary

  • opt_FWHM - value of heat capacity full-width half-maximum for the optimal parameters

cg_openmm.parameters.optimize.optimize_parameter(cgmodel, optimization_parameter, optimization_range_min, optimization_range_max, steps=None)[source]