Simulator_Setup¶
- class biophysics_fitting.simulator.Simulator_Setup¶
- Class for setting up cells with biophysical details. - This class is an inherent attribute of the - Simulatorclass, and should only be accessed as such. This class concerns with setting up a cell with biophysical details.- Usually, a simulation contains fixed parameters, specific to the cell (e.g. the filename of the morphology) and/or stimulus protocol (e.g. recording sites). Such fixed parameters can be defined by adding - set_fixed_params()to- param_modify_funs. A typical usecase is to use the fixed parameters to specify to soma distance for a voltage trace of the apical dendrite. Make sure that the- Simulator- stim_run_funreads the parameter- recSiteand sets up the stimulus accordingly (see- Simulator).- Example: - >>> def param_modify_function(params): >>> # alter params >>> return params >>> def cell_params_generator(params, template): >>> cell_params = template.copy() >>> # Fill in template with params >>> return cell_params >>> def cell_param_modify_function(cell_params): >>> # alter cell_params >>> return cell_params >>> def cell_generator(cell_params): >>> return single_cell_parser.create_cell(cell_params) >>> def cell_modify_functions(cell): >>> # alter cell >>> return cell >>> s = Simulator() # instantiate simulator object >>> fixed_params = {'stim_1.measure_fun.recSite': 835, 'stim_1.stim_setup.dist': 835} >>> s.setup.params_modify_funs.append([ 'fixed_params', partial(set_fixed_params, fixed_params=fixed_params) ]) >>> s.setup.cell_param_generator = cell_params_generator >>> s.setup.cell_generator = cell_generator >>> s.setup.params_modify_funs.append(['modify_param_1', param_modify_fun]) >>> s.setup.cell_param_modify_funs.append(['modify_cell_param_1', cell_param_modify_fun]) >>> s.setup.cell_modify_funs.append(['modify_cell_1', cell_modify_fun])- Notable methods: - >>> s.setup.get(params) cell, params- Each function that receives the biophysical parameter vector (i.e. - cell_param_modify_funsand- cell_modify_funs) only sees a subset of the parameter vector that is provided by the user. This subset is determined by the name by which the function is registered.- Example: - >>> params = { >>> 'apical_scaling.scale': 2, >>> 'ephys.soma.gKv': 0.001, >>> 'ephys.soma.gNav': 0.01 >>> } >>> def scale_apical(params, **kwargs): >>> params['scale'] = kwargs['scale'] >>> def ephys(cell, **kwargs): >>> cell.soma.gKv = kwargs['soma.gKv'] >>> cell.soma.gNav = kwargs['soma.Nav'] >>> s.setup.params_modify_funs.append([ 'apical_scaling', # name must equal the prefix of the parameter, i.e. 'apical_scaling' partial(scale_apical, 'scale' = 2)]) >>> s.setup.cell_modify_funs.append([ 'ephys', # name must equal the prefix of the parameter, i.e. 'ephys' partial(ephys, 'soma.gKv'=1, 'soma.gNav'=2)])- Attributes:¶
- cell_param_generator¶
- A function that generates a - NTParameterSetcell parameter object.- Type:¶
- callable 
 
 
- Methods:¶
 - check()- Check if the setup is correct. - _check_not_none(var, varname, procedure_description)- Convenience method to check if the output of some method is not None. - _check_first_element_of_name_is_the_same(list1, list2)- Check if the first element of the names of two lists are the same. - Get the names of the stimuli. - Get the stimulus setup function by stimulus name. - get_stim_run_fun_by_stim(stim)- Get the stimulus run function by stimulus name. - Get the stimulus response measure function by stimulus name. - get_params(params)- Get the modified biophysical parameters. - get_cell_params(params)- Get the cell parameters as an - NTParameterSetfrom the parameter vector.- get_cell_params_with_default_sim_prams(params, recordingSites, tStart, tStop, dt, Vinit, T)- Get a neuron parameter object. - get(params)- Get the cell with set up biophysics and params. 
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