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compare nml and netpy
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<Lems>
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<!--
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This LEMS file has been automatically generated using PyNeuroML v1.3.15 (libNeuroML v0.6.5)
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-->
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<!-- Specify which component to run -->
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<Target component="RE_reduced_cell_step_test"/>
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<!-- Include core NeuroML2 ComponentType definitions -->
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<Include file="Cells.xml"/>
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<Include file="Networks.xml"/>
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<Include file="Simulation.xml"/>
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<Include file="RE_reduced_cell.net.nml"/>
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<Include file="cadad.channel.nml"/>
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<Include file="hh2_k.channel.nml"/>
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<Include file="hh2_na.channel.nml"/>
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<Include file="itre.channel.nml"/>
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<Include file="kl.channel.nml"/>
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<Include file="pas.channel.nml"/>
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<Simulation id="RE_reduced_cell_step_test" length="2000.0ms" step="0.01ms" target="RE_reduced_cell_net" seed="12345"> <!-- Note seed: ensures same random numbers used every run -->
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<Display id="DispPop__RE_reduced_cell_pop" title="Membrane potentials of cells in RE_reduced_cell_pop" timeScale="1ms" xmin="-200.0" xmax="2200.0" ymin="-90" ymax="50">
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<Line id="RE_reduced_cell_pop[0]: v" quantity="RE_reduced_cell_pop[0]/v" scale="1mV" color="#d54f33" timeScale="1ms"/>
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</Display>
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<OutputFile id="Volts_file__RE_reduced_cell_pop" fileName="RE_reduced_cell_step_test.RE_reduced_cell_pop.v.dat">
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<OutputColumn id="v_RE_reduced_cell_pop_0__v" quantity="RE_reduced_cell_pop[0]/v"/>
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</OutputFile>
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<OutputFile id="caConc_dat" fileName="caConc.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__caConc" quantity="RE_reduced_cell_pop[0]/caConc"/>
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</OutputFile>
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<OutputFile id="caConcExt_dat" fileName="caConcExt.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__caConcExt" quantity="RE_reduced_cell_pop[0]/caConcExt"/>
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</OutputFile>
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<OutputFile id="h_itre_state_dat" fileName="h_itre_state.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__biophys_membraneProperties_itre_soma_itre_h_q" quantity="RE_reduced_cell_pop[0]/biophys/membraneProperties/itre_soma/itre/h/q"/>
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</OutputFile>
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<OutputFile id="itre_erev_dat" fileName="itre_erev.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__biophys_membraneProperties_itre_soma_erev" quantity="RE_reduced_cell_pop[0]/biophys/membraneProperties/itre_soma/erev"/>
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</OutputFile>
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<OutputFile id="itre_iDensity_dat" fileName="itre_iDensity.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__biophys_membraneProperties_itre_soma_iDensity" quantity="RE_reduced_cell_pop[0]/biophys/membraneProperties/itre_soma/iDensity"/>
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</OutputFile>
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<OutputFile id="m_itre_state_dat" fileName="m_itre_state.dat">
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<OutputColumn id="RE_reduced_cell_pop_0__biophys_membraneProperties_itre_soma_itre_m_q" quantity="RE_reduced_cell_pop[0]/biophys/membraneProperties/itre_soma/itre/m/q"/>
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</OutputFile>
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<EventOutputFile id="Spikes_file__RE_reduced_cell_pop" fileName="RE_reduced_cell_step_test.RE_reduced_cell_pop.spikes" format="ID_TIME">
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<EventSelection id="0" select="RE_reduced_cell_pop[0]" eventPort="spike"/>
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</EventOutputFile>
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</Simulation>
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</Lems>

NeuroML2/compare_MC/RE/RE_netpy.py

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netParams.popParams['RE'] = {'cellType': 'RE_HH_reduced', 'numCells': 1}
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netParams.stimSourceParams['Input'] = {'type': 'IClamp', 'dur': 1600, 'del': 200, 'amp': 0.02}
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netParams.stimSourceParams['Input'] = {'type': 'IClamp', 'dur': 400, 'del': 500, 'amp': 0.02}
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netParams.stimTargetParams['Input->RE'] = {'source': 'Input', 'sec': 'soma', 'loc': 0.5, 'conds': {'cellType': 'RE_HH_reduced'}}
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netParams.defaultThreshold = 5.0
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# Simulation options

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