pyneuroml.lems package#

pyneuroml.lems.generate_lems_file_for_neuroml(sim_id: str, neuroml_file: str, target: str, duration: str | float | int, dt: str | float | int, lems_file_name: str, target_dir: str, nml_doc: NeuroMLDocument | None = None, include_extra_files: List[str] = [], gen_plots_for_all_v: bool = True, plot_all_segments: bool = False, gen_plots_for_quantities: Dict[str, List[str]] = {}, gen_plots_for_only_populations: List[str] = [], gen_saves_for_all_v: bool = True, save_all_segments: bool = False, gen_saves_for_only_populations: List[str] = [], gen_saves_for_quantities: Dict[str, List[str]] = {}, gen_spike_saves_for_all_somas: bool = False, gen_spike_saves_for_only_populations: List[str] = [], gen_spike_saves_for_cells: Dict[str, List[str]] = {}, spike_time_format: str = 'ID_TIME', copy_neuroml: bool = True, report_file_name: str | None = None, lems_file_generate_seed: int | None = None, verbose: bool = False, simulation_seed: int = 12345) → Tuple[List[str], LEMSSimulation]#

Generate a LEMS simulation file for a NeuroML model file. This wraps around the LEMSSimulation class and provides an easy interface for creating the LEMS simulation file.

Parameters:

  • sim_id (str) – simulation id

  • neuroml_file (str) – name/path to NeuroML file

  • target (str) – target element

  • duration (str or float or int) – simulation duration

  • dt (str or float or int) – integration time step

  • lems_file_name (str) – name of LEMS file

  • target_dir (str) – directory to place LEMS file in

  • nml_doc (neuroml.Document) – NeuroMLDocument object containing model for simulation Useful if the NeuroML file has already been loaded as it prevents re-loading of the NeuroMLDocument from the file. If this is not provided, the provided NeuroML file will be assumed to be a NeuroMLDocument and loaded.

  • include_extra_files (list) – list of extra files to include in the LEMS simulation file

  • gen_plots_for_all_v (bool) – toggle generation of plots for all membrane potentials

  • plot_all_segments (bool) – toggle whether values for all segments should be plotted

  • gen_plots_for_quantities (dict) – dict of quantities to display the key is the “display” and the value will be the list of quantity paths

  • gen_plots_for_only_populations (list) – list of populations to limit plotting for, If the list is empty, all populations are considered.

  • gen_saves_for_all_v (bool) – toggle whether data files should be saved for all membrane potentials

  • save_all_segments (bool) – toggle whether data files should be saved for all segments

  • gen_saves_for_only_populations (list of populations to save data) – list of populations to save data files for, if list is empty, all populations are considered

  • gen_saves_for_quantities (dict) – dict of quantities to save data files for the key is the filename and the value will be the list of quantitiy paths to save to it

  • gen_spike_saves_for_all_somas (bool) – toggle if spikes should be saved for all somas

  • gen_spike_saves_for_only_populations (list) – list of populations spikes should be saved in data files for

  • gen_spike_saves_for_cells (dict) – dict of cells to save spikes for the key is the name of the file and the value will be the list of quantitiy paths

  • spike_time_format (str) – spike time format

  • copy_neuroml (bool) – toggle whether NeuroML files should be copied to target directory

  • report_file_name (str) – name of report file

  • lems_file_generate_seed (int) – seed to use for LEMS file generation

  • verbose (bool) – toggle verbosity

  • simulation_seed (int) – simulation seed

Returns:

tuple (list of saved quantities, LEMSSimulation object)

Return type:

(list, LEMSSimulation)

pyneuroml.lems.get_pop_index(quantity)#
pyneuroml.lems.load_sim_data_from_lems_file(lems_file_name: str, base_dir: str = '.', get_events: bool = True, get_traces: bool = True) → Tuple[Dict, Dict] | Dict | None#

Load simulation outputs using the LEMS simulation file

Added in version 1.2.2.

Parameters:

  • lems_file_name (str) – name of LEMS file that was used to generate the data

  • base_dir (str) – directory to run in

Returns:

if both get_events and get_traces are selected, a tuple with two dictionaries, one for traces, one for events, is returned.

Otherwise one dictionary for whichever was selected.

The events dictionary has the following format:

{
    '<value of select attribute>': { 'cell id': [<events>] }
}

The traces dictionary has the following format:

{
    't': [<values>],
    'col 1': [<values>]
    'col 2': [<values>]
}

Raises:

  • ValueError – if neither traces nor events are selected for loading

  • ValueError – if no traces are found

  • ValueError – if no events are found

pyneuroml.lems.safe_variable(quantity)#

Make a variable safe.

It replaces [, ], /, . with _.

Parameters:

  • quantity – quantitiy to make safe

  • quantity – str

Returns:

quantity after it was made safe

Return type:

str

pyneuroml.lems.LEMSSimulation module#

Helper class for generating LEMS xml files for simulations

class pyneuroml.lems.LEMSSimulation.LEMSSimulation(sim_id: str, duration: float | str, dt: float | str, target: str | None = None, comment: str = '\n\n        This LEMS file has been automatically generated using PyNeuroML v1.3.19 (libNeuroML v0.6.7)\n\n    ', lems_file_generate_seed: Any | None = None, simulation_seed: int = 12345, meta: Dict[str, str] | None = None)#

Bases: object

Helper class for creating LEMS Simulations for running NeuroML2 models.

TEMPLATE_FILE = '/home/docs/checkouts/readthedocs.org/user_builds/pyneuroml/checkouts/development/pyneuroml/lems/LEMS_TEMPLATE.xml'#
add_column_to_output_file(output_file_id: str, column_id: str, quantity: str) → None#

Add a column to the output file with id output_file_id

Parameters:

  • output_file_id (str) – id of output file (must be created first using create_output_file)

  • column_id (str) – id of column to add

  • quantity (str) – quantity to add

Returns:

None

Raises:

ValueError – if provided output_file_id has not been created yet.

add_line_to_display(display_id: str, line_id: str, quantity: str, scale: str = '1', color: str | None = None, timeScale: str = '1ms') → None#

Add a new line to the display

Parameters:

  • display_id (str) – id of display

  • line_id (str) – id of line

  • quantity – name of quantity being represented

  • scale (str) – scale of line

  • color (str) – color of line, randomly chosen if None

  • timeScale (str) – scale of time axis

Returns:

None

Raises:

ValueError – if provided display_id has not been created yet.

add_selection_to_event_output_file(event_output_file_id: str, event_id: str, select: str, event_port: str) → None#

Add a column to the event output file with id event_output_file_id.

Parameters:

  • event_output_file_id (str) – id of output file (must be created first using create_output_file)

  • event_id (str) – id of event to add

  • select (str) – selection to add

  • event_port (str) – event port to add

Returns:

None

Raises:

ValueError – if provided event_output_file_id has not been created yet.

assign_simulation_target(target: str) → None#

Assign a simulation target.

Parameters:

target (str) – id of target component

Returns:

None

create_display(id: str, title: str, ymin: str, ymax: str, timeScale: str = '1ms') → None#

Create a new display

Parameters:

  • id (str) – id of display

  • title (str) – title of display

  • ymin (str) – min y value of display

  • ymax (str) – max y value of display

  • timeScale (str) – time scale of display

Returns:

None

create_event_output_file(id, file_name, format='ID_TIME')#

Create a new output file for storing events recorded from simulations.

For storing other outputs (not events), please see create_output_file instead.

TODO: list what formats are available

Parameters:

  • id (str) – id of output file

  • file_name (str) – name of output file

  • format (str) – format of file

Returns:

None

create_output_file(id: str, file_name: str)#

Create a new output file for storing values recorded for a simulation.

For storing events, such as spikes, please see create_event_output_file.

Parameters:

  • id (str) – id of output file

  • file_name (str) – name of output file

Returns:

None

include_lems_file(lems_file_name: str, include_included: bool = True) → None#

Include additional LEMS file in the simulation.

Parameters:

  • lems_file_name (str) – name of LEMS file to include

  • include_included (bool) – toggle to include files included by provided LEMS file

Returns:

None

include_neuroml2_file(nml2_file_name: str, include_included: bool = True, relative_to_dir: str = '.') → None#

Include additional NeuroML2 file.

This will only add the provided file if it has not already been included.

Parameters:

  • nml2_file_name (str) – name of NeuroML2 file to include

  • include_included (bool) – toggle to include any files included in the provided file

  • relative_to_dir (str) – directory relative to which the provided nml2_file_name is being provided

Returns:

None

property lems_info#

Return the attributes

my_random = <random.Random object>#
save_to_file(file_name: str | None = None)#

Save LEMSSimulation to a file.

Parameters:

file_name (str) – name of file to store to. LEMS_<some id string>.xml is the suggested format. Leave empty to use LEMS_<sim_id>.xml. If provided, this also sets the lems_file_name attribute of the class so that it can be accessed later.

Returns:

name of file

Return type:

str

set_report_file(report_file_name: str) → None#

Set a report file.

The report file is a short file saved after simulation with run time, simulator version etc.

Parameters:

report_file_name (str) – name of report file

Returns:

None

to_xml() → str#

Export simulation to XML.

Returns:

XML representation

Return type:

str