emodelrunner.load¶
Functions mainly for loading params for run.py.
Functions
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Return the final parameters. |
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Get experimental rin voltage base from feature file when having MainProtocol. |
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Load json files and return syn_setup_params dict. |
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Returns the validated configuration file. |
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Get optimized parameters. |
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Define mechanisms. |
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Load synapse mechanisms. |
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Load synapse configuration data into dict[command]=list(ids). |
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Load synapse data from tsv. |
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Load unoptimized parameters as BluePyOpt parameters. |
- emodelrunner.load.get_release_params(config, precell=False)[source]¶
Return the final parameters.
- Parameters
config (configparser.ConfigParser) – configuration
precell (bool) – True to load precell optimized parameters. False to get usual parameters.
- Returns
optimized parameters
- Return type
dict
- emodelrunner.load.get_rin_exp_voltage_base(features_path)[source]¶
Get experimental rin voltage base from feature file when having MainProtocol.
- emodelrunner.load.get_syn_setup_params(syn_extra_params_path, cpre_cpost_path, fit_params_path, gid, invivo)[source]¶
Load json files and return syn_setup_params dict.
- Parameters
syn_extra_params_path (str) – path to the glusynapses related extra parameters file
cpre_cpost_path (str) – path to the c_pre and c_post related file c_pre (resp. c_post) is the calcium amplitude during isolated presynaptic (resp. postsynaptic) activation
fit_params_path (str) – path to the file containing the glusynapse fitted parameters The fitted parameters are time constant of calcium integrator, depression rate, potentiation rate, and factors used in plasticity threshold computation.
gid (int) – ID of the postsynaptic cell
invivo (bool) – whether to run the simulation in ‘in vivo’ conditions
- Returns
glusynapse setup related parameters
- Return type
dict
- emodelrunner.load.load_config(config_path)[source]¶
Returns the validated configuration file.
- Parameters
config_path (str or Path) – path to the configuration file.
- Returns
loaded config object
- Return type
configparser.ConfigParser
- emodelrunner.load.load_emodel_params(emodel, params_path)[source]¶
Get optimized parameters.
- Parameters
emodel (str) – name of the emodel
params_path (str) – path to the optimized parameters json file
- Returns
optimized parameters for the given emodel
- Return type
dict
- emodelrunner.load.load_mechanisms(mechs_path)[source]¶
Define mechanisms.
- Parameters
mechs_path (str) – path to the unoptimized parameters json file
- Returns
list of ephys.mechanisms.NrnMODMechanism from file
- emodelrunner.load.load_syn_mechs(seed, rng_settings_mode, syn_data_path, syn_conf_path, pre_mtypes=None, stim_params=None, use_glu_synapse=False, syn_setup_params=None)[source]¶
Load synapse mechanisms.
- Parameters
seed (int) – random number generator seed number
rng_settings_mode (str) – mode of the random number generator Can be “Random123” or “Compatibility”
syn_data_path (str) – path to the (tsv) synapses data file
syn_conf_path (str) – path to the synapse configuration data file
pre_mtypes (list of ints) – activate only synapses whose pre_mtype is in this list. if None, all synapses are activated
stim_params (dict or None) – dict with pre_mtype as key, and netstim params list as item. netstim params list is [start, interval, number, noise]
use_glu_synapse (bool) – if True, instantiate synapses to use GluSynapse
syn_setup_params (dict) – contains extra parameters to setup synapses when using GluSynapseCustom
- Returns
the synapses mechanisms
- Return type
- emodelrunner.load.load_synapse_configuration_data(synconf_path)[source]¶
Load synapse configuration data into dict[command]=list(ids).
- Parameters
synconf_path (str) – path to the synapse configuration data file
- Returns
configuration data
each key contains a command to execute using hoc, and each value contains a list of synapse id on which to execute the command
- Return type
dict
- emodelrunner.load.load_synapses_tsv_data(tsv_path)[source]¶
Load synapse data from tsv.
- Parameters
tsv_path (str) – path to the tsv synapses data file
- Returns
list of dicts containing each data for one synapse
- emodelrunner.load.load_unoptimized_parameters(params_path, v_init, celsius)[source]¶
Load unoptimized parameters as BluePyOpt parameters.
- Parameters
params_path (str) – path to the json file containing the non-optimised parameters
v_init (int) – initial voltage (mV). Will override v_init value from parameter file
celsius (int) – cell temperature in celsius. Will override celsius value from parameter file
- Returns
list of parameters