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pgleesonpgleeson
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Adding initial analysis of cells
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‎.gitignore‎

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@@ -37,3 +37,15 @@ ChannelTest/*.log
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/NMC/NeuroML2/ManyCells.net.png
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/NMC/Connectome/BBP.net.png
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/NMC/Connectome/cons_locs_pathways_mc0_Column.tar
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/NMC/NeuroML2/nmllite/*.mod
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*.gv
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*.gv.png
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/NMC/NeuroML2/nmllite/IClamp_*.json
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/NMC/NeuroML2/nmllite/ParamSweep_*
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/NMC/NeuroML2/nmllite/IClamp_*.net.nml
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/NMC/NeuroML2/nmllite/*.hoc
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/NMC/NeuroML2/nmllite/*.dat
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/NMC/NeuroML2/nmllite/LEMS_Sim_IClamp_*.xml
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/NMC/NeuroML2/nmllite/Sim_IClamp_*.json
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report.*.txt
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*_nrn.py

‎NMC/NeuroML2/nmllite/GenerateExamples.py‎

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from neuromllite import *
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from neuromllite.NetworkGenerator import *
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from neuromllite.utils import create_new_model
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import sys
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sys.path.append("..")
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'''
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bAC217_L4_MC_5fa0a62bd0_0_0.cell.nml cADpyr229_L23_PC_c292d67a2e_0_0.cell.nml cADpyr231_L6_TPC_L4_117b9dfb71_0_0.cell.nml cNAC187_L1_HAC_f8c9772d9d_0_0.cell.nml Soma_AllNML2.cell.nml
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bNAC219_L1_DAC_a9ae5cbbf5_0_0.cell.nml cADpyr230_L4_SS_1afeb14f17_0_0.cell.nml cADpyr232_L5_TTPC1_0fb1ca4724_0_0.cell.nml cNAC187_L23_NBC_9d37c4b1f8_0_0.cell.nml
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cADpyr229_L23_PC_5ecbf9b163_0_0.cell.nml cADpyr231_L6_TPC_L1_44f2206f70_0_0.cell.nml cADpyr232_L5_UTPC_d736225429_0_0.cell.nml cSTUT189_L23_LBC_e6e8f83407_0_0.cell.nml
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'''
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colors = {'RS':'0 0 0.8', 'FS':'0.8 0 0', 'LTS':'0 0 0.8', 'IB':'0.8 0 0', 'IBR':'0.8 0 0'}
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colors = {'cADpyr229_L23_PC_c292d67a2e_0_0':'0 0 0.8', 'cNAC187_L23_NBC_9d37c4b1f8_0_0':'0.8 0 0'}
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def generate(cell, duration=3000, config='IClamp',parameters = None):
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reference = "%s_%s"%(config, cell)
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cell_id = '%s'%cell
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cell_nmll = Cell(id=cell_id, neuroml2_source_file='../%s.cell.nml'%(cell))
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################################################################################
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### Add some inputs
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if 'IClamp' in config:
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if not parameters:
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parameters = {}
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parameters['stim_amp'] = '350pA'
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input_source = InputSource(id='iclamp_0',
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neuroml2_input='PulseGenerator',
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parameters={'amplitude':'stim_amp', 'delay':'500ms', 'duration':'2000ms'})
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else:
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if not parameters:
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parameters = {}
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parameters['average_rate'] = '100 Hz'
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parameters['number_per_cell'] = '10'
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input_source = InputSource(id='pfs0',
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neuroml2_input='PoissonFiringSynapse',
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parameters={'average_rate':'average_rate',
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'synapse':syn_exc.id,
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'spike_target':"./%s"%syn_exc.id})
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sim, net = create_new_model(reference,
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duration,
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dt=0.025, # ms
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temperature=34, # degC
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default_region='Cortex',
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parameters = parameters,
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cell_for_default_population=cell_nmll,
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color_for_default_population=colors[cell],
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input_for_default_population=input_source)
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return sim, net
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if __name__ == "__main__":
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if '-all' in sys.argv:
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for cell in colors:
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generate(cell, 3000, config="IClamp")
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else:
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#sim, net = generate('cADpyr229_L23_PC_c292d67a2e_0_0', 3000, config="IClamp")
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sim, net = generate('cNAC187_L23_NBC_9d37c4b1f8_0_0', 3000, config="IClamp",parameters={'stim_amp':'30pA'})
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check_to_generate_or_run(sys.argv, sim)
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‎NMC/NeuroML2/nmllite/README.md‎

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### BBP cell summary
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<table>
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<tr>
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<td width=30><b>cADpyr229_L23_PC_c292d67a2e_0_0</b></td>
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<td><a href="mean_spike_frequency_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="mean_spike_frequency_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<td><a href="firing_rates_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="firing_rates_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<td><a href="heatmap_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="heatmap_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<td><a href="dt_traces_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="dt_traces_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<td><a href="heatmap_dt_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="heatmap_dt_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<td><a href="mean_spike_frequency_dt_cADpyr229_L23_PC_c292d67a2e_0_0.png">
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<img alt="?" src="mean_spike_frequency_dt_cADpyr229_L23_PC_c292d67a2e_0_0.png" height="160"/></a>
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</td>
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<tr>
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<tr>
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<td width=30><b>cNAC187_L23_NBC_9d37c4b1f8_0_0</b></td>
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<td><a href="mean_spike_frequency_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="mean_spike_frequency_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<td><a href="firing_rates_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="firing_rates_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<td><a href="heatmap_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="heatmap_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<td><a href="dt_traces_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="dt_traces_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<td><a href="heatmap_dt_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="heatmap_dt_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<td><a href="mean_spike_frequency_dt_cNAC187_L23_NBC_9d37c4b1f8_0_0.png">
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<img alt="?" src="mean_spike_frequency_dt_cNAC187_L23_NBC_9d37c4b1f8_0_0.png" height="160"/></a>
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</td>
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<tr>

‎NMC/NeuroML2/nmllite/Sweep.py‎

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import sys
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import pprint; pp = pprint.PrettyPrinter(depth=6)
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from neuromllite.sweep.ParameterSweep import ParameterSweep
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from neuromllite.sweep.ParameterSweep import NeuroMLliteRunner
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from GenerateExamples import colors
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if __name__ == '__main__':
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heatmap_lims=[-110,-20]
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if '-all' in sys.argv:
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print('Generating all plots')
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save_fig_dir = './'
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html = '<table>\n'
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fixed = {'dt':0.025, 'duration':3000}
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vary = {'stim_amp':['%spA'%(i) for i in xrange(-100,1000,50)]}
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#vary = {'stim_amp':['%spA'%(i/10.0) for i in xrange(-10,20,5)]}
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#vary = {'stim_amp':['-100pA','0pA','100pA','200pA','300pA','400pA']}
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cells = colors.keys()
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for type in cells:
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if type!='ec' and type !='ca3':
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run = True
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run = False
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if run:
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nmllr = NeuroMLliteRunner('Sim_IClamp_%s.json'%type,
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simulator='jNeuroML_NEURON')
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ps = ParameterSweep(nmllr,
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vary,
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fixed,
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num_parallel_runs=16,
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save_plot_all_to='firing_rates_%s.png'%type,
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heatmap_all=True,
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save_heatmap_to='heatmap_%s.png'%type,
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heatmap_lims=heatmap_lims,
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plot_all=True,
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show_plot_already=False)
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report = ps.run()
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#ps.plotLines('stim_amp','average_last_1percent',save_figure_to='average_last_1percent_%s.png'%type)
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ps.plotLines('stim_amp','mean_spike_frequency',save_figure_to='mean_spike_frequency_%s.png'%type)
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height = '160'
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html+='<tr>\n'
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html+=' <td width=30><b>'+type+'</b></td>\n'
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html+=' <td><a href="mean_spike_frequency_%s.png'%type+'">\n'
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html+=' <img alt="?" src="mean_spike_frequency_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+=' <td><a href="firing_rates_%s.png'%type+'">\n'
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html+=' <img alt="?" src="firing_rates_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+=' <td><a href="heatmap_%s.png'%type+'">\n'
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html+=' <img alt="?" src="heatmap_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+=' <td><a href="dt_traces_%s.png'%type+'">\n'
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html+=' <img alt="?" src="dt_traces_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+=' <td><a href="heatmap_dt_%s.png'%type+'">\n'
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html+=' <img alt="?" src="heatmap_dt_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+=' <td><a href="mean_spike_frequency_dt_%s.png'%type+'">\n'
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html+=' <img alt="?" src="mean_spike_frequency_dt_%s.png'%type+'" height="'+height+'"/></a>\n'
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html+=' </td>\n'
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html+='<tr>\n'
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import matplotlib.pyplot as plt
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if not '-nogui' in sys.argv:
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print("Showing plots")
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plt.show()
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with open(save_fig_dir+'info.html','w') as f:
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f.write('<html><body>\n%s\n</body></html>'%html)
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with open(save_fig_dir+'README.md','w') as f2:
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f2.write('### BBP cell summary \n%s'%(html.replace('.html','.md')))
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elif '-dt' in sys.argv:
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optimal_stim = {'cADpyr229_L23_PC_c292d67a2e_0_0':'500',
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'cNAC187_L23_NBC_9d37c4b1f8_0_0':'30'}
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vary = {'dt':[0.1,0.05,0.025,0.01,0.005,0.0025,0.001,0.0005,0.00025,0.0001]}
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vary = {'dt':[0.1,0.05,0.025,0.01,0.005,0.0025,0.001]}
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vary = {'dt':[0.05,0.025,0.01,0.005,0.0025]}
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#vary = {'dt':[0.05,0.025,0.01,0.005]}
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#vary = {'dt':[0.05,0.025,0.01]}
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#vary = {'dt':[0.05,0.025,0.01]}
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for type in optimal_stim:
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if type!='ec' and type !='ca3':
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run = True
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if run:
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fixed = {'duration':3000, 'stim_amp':'%spA'%optimal_stim[type]}
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nmllr = NeuroMLliteRunner('Sim_IClamp_%s.json'%type,
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simulator='jNeuroML_NEURON')
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ps = ParameterSweep(nmllr,
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vary,
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fixed,
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num_parallel_runs=16,
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save_plot_all_to='dt_traces_%s.png'%type,
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heatmap_all=True,
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save_heatmap_to='heatmap_dt_%s.png'%type,
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heatmap_lims=heatmap_lims,
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plot_all=True,
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show_plot_already=False)
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report = ps.run()
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#ps.plotLines('stim_amp','average_last_1percent',save_figure_to='average_last_1percent_%s.png'%type)
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ps.plotLines('dt','mean_spike_frequency',save_figure_to='mean_spike_frequency_dt_%s.png'%type, logx=True)
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import matplotlib.pyplot as plt
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if not '-nogui' in sys.argv:
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print("Showing plots")
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plt.show()
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else:
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fixed = {'dt':0.025, 'duration':3000}
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quick = False
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#quick=True
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vary = {'stim_amp':['%spA'%(i/10.0) for i in xrange(-10,20,2)]}
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vary = {'dt':[0.1,0.05,0.025,0.01,0.005,0.0025,0.001,0.0005,0.00025,0.0001]}
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vary = {'dt':[0.1,0.05,0.025,0.01,0.005,0.0025,0.001]}
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vary = {'dt':[0.1,0.05,0.025,0.01,0.005]}
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#vary = {'number_per_cell':[i for i in xrange(0,250,10)]}
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#vary = {'stim_amp':['1pA','1.5pA','2pA']}
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vary = {'stim_amp':['%spA'%(i) for i in xrange(-100,1000,50)]}
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type = 'RS'
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type = 'cADpyr229_L23_PC_c292d67a2e_0_0'
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type = 'cNAC187_L23_NBC_9d37c4b1f8_0_0'
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#type='poolosyn'
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config = 'IClamp'
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#config = 'PoissonFiringSynapse'
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nmllr = NeuroMLliteRunner('Sim_%s_%s.json'%(config,type),
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simulator='jNeuroML_NEURON')
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if quick:
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pass
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ps = ParameterSweep(nmllr, vary, fixed,
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num_parallel_runs=16,
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plot_all=True,
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save_plot_all_to='firing_rates_%s.png'%type,
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heatmap_all=True,
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save_heatmap_to='heatmap_%s.png'%type,
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heatmap_lims=heatmap_lims,
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show_plot_already=False)
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report = ps.run()
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ps.print_report()
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#ps.plotLines('stim_amp','average_last_1percent',save_figure_to='average_last_1percent_%s.png'%type)
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ps.plotLines('stim_amp','mean_spike_frequency',save_figure_to='mean_spike_frequency_%s.png'%type)
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#ps.plotLines('dt','mean_spike_frequency',save_figure_to='mean_spike_frequency_%s.png'%type, logx=True)
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#ps.plotLines('number_per_cell','mean_spike_frequency',save_figure_to='poisson_mean_spike_frequency_%s.png'%type)
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import matplotlib.pyplot as plt
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if not '-nogui' in sys.argv:
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print("Showing plots")
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plt.show()

‎NMC/NeuroML2/nmllite/dt_traces_cADpyr229_L23_PC_c292d67a2e_0_0.png‎

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‎NMC/NeuroML2/nmllite/dt_traces_cNAC187_L23_NBC_9d37c4b1f8_0_0.png‎

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‎NMC/NeuroML2/nmllite/firing_rates_cADpyr229_L23_PC_c292d67a2e_0_0.png‎

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‎NMC/NeuroML2/nmllite/firing_rates_cNAC187_L23_NBC_9d37c4b1f8_0_0.png‎

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‎NMC/NeuroML2/nmllite/heatmap_cADpyr229_L23_PC_c292d67a2e_0_0.png‎

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‎NMC/NeuroML2/nmllite/heatmap_cNAC187_L23_NBC_9d37c4b1f8_0_0.png‎

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