EpochGenerator¶

class managers.operatorsTranscribe.metadata_epochgenerator.EpochGenerator¶

Available Methods:

Method name	Method type
`epochcontainer()`	class method
`anepoch()`	class method
`forepoch()`	class method
`compute_totalepochs_per_cellregion()`	static method
`an_epoch_stimulus_window()`	static method

classmethod an_epoch(epoch_no_per_region, theregion, parameters)¶

Creates the value for one epoch, i.e, value for one of the epoch-key in the container.

Arguments:

Arguments Value type

first integer for number of epochs per region

second

string for the region name,

i.e, key of chosenmodel.regions = {“soma”: 0.0, “axon”: 0.0}

third

dictionary for either of the two parameters

for run time parameters dictionary has keys "dt",

"celsius", "tstop", "v_init"

Eg: {“dt”: 0.01, “celsius”: 30, “tstop”: 100, “v_init”: 65}
the run time parameter argument is used for cases without

stimulation.

for stimulation parameters dictionary has keys "type"

and "stimlist"

"type" key value is a two element list of strings

<stimulus category> <specific type of that category> The first element is ALWAYS <stimulus category>

Eg: for injecting cell current ["current", "IClamp"]

"stimlist" key value is a list with elements as

dictionary in the form [ {}, {}, … ]

Eg: [ {“amp”: 0.5, “dur”: 100.0, “delay”: 10.0},

{“amp”: 1.0, “dur”: 50.0, “delay”: 10.0+100.0} ]
Eg: [ {“amp_initial”: 0.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 5.0},

{“amp_initial”: 0.5, “amp_final”: 1.0, “dur”: 5.0,

“delay”: 10.0},

{“amp_initial”: 1.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 15.0},

{“amp_initial”: 0.5, “amp_final”: 0.0, “dur”: 5.0,

“delay”: 20.0} ]
"tstop" key value `` = runtimeparameters[“tstop”]``

hence, for the last epoch

Returned Value: Assuming chosenmodel.regions = {'soma': 0.0, 'axon': 0.0} the epoch metadata for a region, say "soma" is a dictionary of the form

{"source": "soma", "start_time": float, "stop_time": float, "description": string, "tags": ( No_epoch_responses, epochID, this_region, modelname, modelscale, epochs<index>region, all_regions ) }

NOTE:

the returned value has these same four-keys regardless of with or without stimulus

static an_epoch_stimulus_window(epoch_no_per_region, theregion, parameters)¶

Returns a dictionary focusing on the stimulation for an epoch.

Arguments:

Arguments Value type

first number of epochs per region

second

string for the region name,

i.e, key of chosenmodel.regions = {“soma”: 0.0, “axon”: 0.0}

third

dictionary for stimulation parameters dictionary

"type" key value is a two element list of strings

<stimulus category> <specific type of that category> The first element is ALWAYS <stimulus category>

Eg: for injecting cell current ["current", "IClamp"]

"stimlist" key value is a list with elements as

dictionary in the form [ {}, {}, … ]

Eg: [ {“amp”: 0.5, “dur”: 100.0, “delay”: 10.0},

{“amp”: 1.0, “dur”: 50.0, “delay”: 10.0+100.0} ]
Eg: [ {“amp_initial”: 0.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 5.0},

{“amp_initial”: 0.5, “amp_final”: 1.0, “dur”: 5.0,

“delay”: 10.0},

{“amp_initial”: 1.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 15.0},

{“amp_initial”: 0.5, “amp_final”: 0.0, “dur”: 5.0,

“delay”: 20.0} ]
"tstop" key value `` = runtimeparameters[“tstop”]``

hence, for the last epoch

Returned value: This is a dictionary with the keys "source", "start_time", "stop_time" and "description".

static compute_totalepochs_per_cellregion(parameters)¶

Returns the “total” number of epochs. Here “total” stands for A region, NOT all regions.

Argument:

Argument Value type

only one

dictionary for either of the two parameters

for run time parameters dictionary has keys "dt",

"celsius", "tstop", "v_init"

Eg: {“dt”: 0.01, “celsius”: 30, “tstop”: 100, “v_init”: 65}
the run time parameter argument is used for cases without

stimulation.

for stimulation parameters dictionary has keys "type",

"stimlist" and "tstop"

"type" key value is a two element list of strings

<stimulus category> <specific type of that category> The first element is ALWAYS <stimulus category>

Eg: for injecting cell current ["current", "IClamp"]

"stimlist" key value is a list with elements as

dictionary in the form [ {}, {}, … ]

Eg: [ {“amp”: 0.5, “dur”: 100.0, “delay”: 10.0},

{“amp”: 1.0, “dur”: 50.0, “delay”: 10.0+100.0} ]
Eg: [ {“amp_initial”: 0.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 5.0},

{“amp_initial”: 0.5, “amp_final”: 1.0, “dur”: 5.0,

“delay”: 10.0},

{“amp_initial”: 1.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 15.0},

{“amp_initial”: 0.5, “amp_final”: 0.0, “dur”: 5.0,

“delay”: 20.0} ]
"tstop" key value `` = runtimeparameters[“tstop”]``

hence, for the last epoch

NOTE:

no_of_regions = len(list(chosenmodel.regions.keys()))
no_of_stimulus = 2
no_of_epochs_per_region = 1 + no_of_stimulus. Thus it includes period/epoch pre-first stimulus
total number of epochs = no_of_regions * no_of_epochs_per_regions

classmethod epochcontainer(chosenmodel, parameters)¶

Creates the container for NWB formatted epoch metadata.

Arguments:

Arguments Value type

first instantiated model

second

dictionary for either of the two parameters

for run time parameters dictionary has keys "dt",

"celsius", "tstop", "v_init"

Eg: {“dt”: 0.01, “celsius”: 30, “tstop”: 100, “v_init”: 65}
the run time parameter argument is used for cases without

stimulation.

for stimulation parameters dictionary has keys "type"

and "stimlist"

"type" key value is a two element list of strings

<stimulus category> <specific type of that category> The first element is ALWAYS <stimulus category>

Eg: for injecting cell current ["current", "IClamp"]

"stimlist" key value is a list with elements as

dictionary in the form [ {}, {}, … ]

Eg: [ {“amp”: 0.5, “dur”: 100.0, “delay”: 10.0},

{“amp”: 1.0, “dur”: 50.0, “delay”: 10.0+100.0} ]
Eg: [ {“amp_initial”: 0.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 5.0},

{“amp_initial”: 0.5, “amp_final”: 1.0, “dur”: 5.0,

“delay”: 10.0},

{“amp_initial”: 1.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 15.0},

{“amp_initial”: 0.5, “amp_final”: 0.0, “dur”: 5.0,

“delay”: 20.0} ]
"tstop" key value `` = runtimeparameters[“tstop”]``

hence, for the last epoch

Returned Value: Assuming chosenmodel.regions = {'soma': 0.0, 'axon': 0.0} and the number of epochs per region = 3 (i.e initial state regardless of stimulus is epoch0), then the returned value is a dictionary of the form

{ "epoch0soma": {"tags": ("3_epoch_responses", "0", "soma", modelname, modelscale,
                          "epoch0soma", "soma axon") },
  "epoch1soma": {"tags": ("3_epoch_responses", "1", "soma", modelname, modelscale,
                          "epoch1soma", "soma axon") },
  "epoch2soma": {"tags": ("3_epoch_responses", "2", "soma", modelname, modelscale,
                          "epoch2soma", "soma axon") },
  "epoch0axon": {"tags": ("3_epoch_responses", "0", "axon", modelname, modelscale,
                          "epoch0axon", "soma axon")},
  "epoch1axon": {"tags": ("3_epoch_responses", "1", "soma", modelname, modelscale,
                          "epoch1axon", "soma axon")},
  "epoch2axon": {"tags": ("3_epoch_responses", "2", "soma", modelname, modelscale,
                          "epoch2axon", "soma axon")} }

However without stimulation, number of epochs per region = 1 (i.e, only epoch0) and the dictionary will look like

{ "epoch0soma": {"tags": ("1_epoch_responses", "0", "soma", modelname, modelscale,
                          "epoch0soma", "soma axon") },
  "epoch0axon": {"tags": ("1_epoch_responses", "0", "soma", modelname, modelscale,
                          "epoch0axon", "soma axon") } }

NOTE:

no_of_regions = len(list(chosenmodel.regions.keys()))
no_of_stimulus = 2
no_of_epochs_per_region = 1 + no_of_stimulus Thus it includes period/epoch pre-first stimulus
total number of epochs = no_of_regions * no_of_epochs_per_regions
and tuple

"tags": ( No_epoch_responses, epochID, this_cellregion, modelname, modelscale, epoch<index>cellregion, all_cellregions )
elements of the tags tuple are “all strings”
the first element of the tuple will always be of the form <No>_epoch_responses the only difference is the <No>, standing for number of epoch responses for this cell regions. It should be pointed out that it does not stand for the total overall number of epochs (for all the regions).
the last element is a string of space separated region names

classmethod forepoch(chosenmodel=None, parameters=None)¶

Creates the NWB formatted metadata forfile.

Keyword arguments:

Key Value type

chosenmodel instantiated model

parameters

dictionary for either of the two parameters

for run time parameters dictionary has keys "dt",

"celsius", "tstop", "v_init"

Eg: {“dt”: 0.01, “celsius”: 30, “tstop”: 100, “v_init”: 65}
the run time parameter argument is used for cases without

stimulation.

for stimulation parameters dictionary has keys "type"

and "stimlist"

"type" key value is a two element list of strings

<stimulus category> <specific type of that category> The first element is ALWAYS <stimulus category>

Eg: for injecting cell current ["current", "IClamp"]

"stimlist" key value is a list with elements as

dictionary in the form [ {}, {}, … ]

Eg: [ {“amp”: 0.5, “dur”: 100.0, “delay”: 10.0},

{“amp”: 1.0, “dur”: 50.0, “delay”: 10.0+100.0} ]
Eg: [ {“amp_initial”: 0.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 5.0},

{“amp_initial”: 0.5, “amp_final”: 1.0, “dur”: 5.0,

“delay”: 10.0},

{“amp_initial”: 1.0, “amp_final”: 0.5, “dur”: 5.0,

“delay”: 15.0},

{“amp_initial”: 0.5, “amp_final”: 0.0, “dur”: 5.0,

“delay”: 20.0} ]
"tstop" key value `` = runtimeparameters[“tstop”]``

hence, for the last epoch

Returned Value: Assuming chosenmodel.regions = {'soma': 0.0, 'axon': 0.0} and number of epochs per region = 2 (i.e initial state regardless of stimulus is epoch0), the returned value is a dictionary of the form

{ 
  "epoch0soma": {"source": "soma", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( No_epoch_responses, epochID, this_region, modelname,
                           modelscale, epochs<index>region, all_regions ) },
  "epoch1soma": {"source": "soma", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( string, string, string, string, string, string,
                           space separated string ) }
  "epoch0axon": {"source": "axon", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( string, string, string, string, string, string,
                           space separated string ) },
  "epoch1axon": {"source": "axon", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( string, string, string, string, string, string,
                           space separated string ) },
  "epoch_tags": ('2_epoch_responses',) }

However without stimulation, number of epochs per region = 1 (i.e, only epoch0) resulting in

{ "epoch0soma": {"source": "soma", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( No_epoch_responses, epochID, this_region, modelname,
                           modelscale, epochs<index>retion, all_regions ) },
  "epoch0axon": {"source": "axon", "start_time": float, "stop_time": float,
                 "description": string,
                 "tags": ( string, string, string, string, string, string,
                           space separated string ) },
  "epoch_tags": ('1_epoch_responses',) }

NOTE:

the first element of the "tags" tuple is always of the form <No>_epoch_responses, such that <No> may vary, representing the total available epochs for this chosen region. It does not stand for the overall number of epochs (for all the regions).

Use case:

>> eg = EpochGenerator()

>> model = Xyz()

>> runtimeparam = {"dt": 0.01, "celsius": 30, "tstop": 100, "v_init": 65}

For simulation without stimulation

>> epochmd = eg.forepoch(chosenmodel = model, parameters = runtimeparam)

For simulation with stimulation

>> stimparameters = {"type": ["current", "IClamp"], "stimlist": [ {"amp": 0.5, "dur": 100.0, "delay": 10.0}, {"amp": 1.0, "dur": 50.0, "delay": 10.0+100.0} ], "tstop": runtimeparam["tstop"]}

>> epochmd = eg.forepoch(chosenmodel = model, parameters = stimparameters)

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