#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import sys
import math
import datetime
import pickle
## from node000:
## mpiexec -machinefile ~/hostfile -n <numavgs*numpulses+1> ~/Python-2.6.4/bin/python2.6 odor_pulses.py
## typical value for numavgs = 9
## (depends on number of available processing nodes and number of odorfiles generated)
## typical value for numpulses = 2*RANDOM_NUM_SEQ = 6.
## nohup mpiexec -machinefile ~/hostfile -n 55 ~/Python-2.6.4/bin/python2.6 odor_pulses.py < /dev/null &
## OR for a single odor run; from any node:
## python2.6 odor_pulses.py
## Set various option like NO_PGs or ONLY_TWO_MITS in simset_odor
sys.path.extend(["..","../networks","../generators","../simulations"])
from moose_utils import * # imports moose
from data_utils import * # has mpi import and variables also
from OBNetwork import *
from sim_utils import *
from stimuliConstants import * # has SETTLETIME, PULSE_RUNTIME, pulsebins
from simset_odor import *
from pylab import * # part of matplotlib that depends on numpy but not scipy
from plot_odor_pulses import *
#-----------------------------------------------------------
class odorResponse:
def __init__(self):
self.mpirank = mpirank
self.context = moose.PyMooseBase.getContext()
def setupStim(self,network,pulse_i,avgnum):
self.setupOdor(network, pulse_i, avgnum)
print "Setup pulse number =",pulse_i,"at",self.mpirank
def setupOdor(self, network, pulse_i, avgnum):
### first figure out which PG belongs to which glom
### PG_glom_map[pgname] returns the glom num of the PG: needed for ORN to PG connections.
PG_glom_map = {}
for projname in network.projectionDict.keys():
if 'PG_mitral' in projname:
for i,proj in enumerate(network.projectionDict[projname][2]):
#get the glomnum from the post path proj[2]
# name of the mitral cell from '/mitrals_2/...'
mitname = string.split(proj[2],'/')[1]
# glomerulus number from 'mitrals_2' by integer division i.e. 2/2 = 1
glomnum = int(string.split(mitname,'_')[1]) / 2
# name of the PG cell from '/PGs_2/...'
pgname = string.split(proj[1],'/')[1]
PG_glom_map[pgname] = glomnum
### Now connect the ORNs
for projname in network.projectionDict.keys():
#### Calling attach_spikes() for each projection, would reconnect files to the same segment multiple times.
#### But attach_files_uniquely() checks whether timetable.tableSize is zero or not
#### i.e. files already attached or not.
### connect ORNs to mitrals
if 'ORN_mitral' in projname:
print "connecting ORN files to mitrals"
for i,proj in enumerate(network.projectionDict[projname][2]):
#get the glomnum from the post path proj[2]
mitname = string.split(proj[2],'/')[1] # name of the mitral cell from '/mitrals_2/...'
glomnum = int(string.split(mitname,'_')[1]) / 2 # glomerulus number from 'mitrals_2' by integer division i.e. 2/2 = 1
filebase = ORNpathseedstr+'firetimes_rndpulse_glom_'+str(glomnum)
self.attach_files_uniquely(filebase,proj[0],proj[2],pulse_i,avgnum)
### connect ORNs to PG
if 'ORN_PG' in projname:
print "connecting ORN files to PGs"
for i,proj in enumerate(network.projectionDict[projname][2]):
pgname = string.split(proj[2],'/')[1] # name of the PG cell from '/PGs_2/...'
glomnum = PG_glom_map[pgname]
filebase = ORNpathseedstr+'firetimes_rndpulse_glom_'+str(glomnum)
self.attach_files_uniquely(filebase,proj[0],proj[2],pulse_i,avgnum)
### connect SAs to PG
if 'SA_PG' in projname:
print "connecting SA files to PGs"
for i,proj in enumerate(network.projectionDict[projname][2]):
pgname = string.split(proj[2],'/')[1] # name of the PG cell from '/PGs_2/...'
glomnum = PG_glom_map[pgname]
filebase = ORNpathseedstr+'firetimes_SA_rndpulse'
self.attach_files_uniquely(filebase,proj[0],proj[2],pulse_i)
###### I am back to 'extra-connecting' modelled mitral as extra sister mitrals excitation to granules
###### Previously, as below, I was connecting ORNs of the glom to granules
###### which caused inhibition even when the sister mitrals were not even firing!
### connect unmodelled extra sister mitrals as files to granules
#if 'mitral_granule_extra' in projname:
# print "Connecting unmodelled sister excitation files to granules"
# for i,proj in enumerate(network.projectionDict[projname][2]):
# granulename = string.split(proj[2],'/')[1] # name of the granule cell from '/granules_singles_2/...'
# # glomnum from pre_path = proj[1] = 'file[+<glomnum>]_<filenumber1>[_<filenumber2>...]'
# glomstr = proj[1].split('+')[1].split('_',1)[0]
# filebase = '../firefiles/firetimes_rndpulse_glom_'+glomstr
# self.attach_files_uniquely(filebase,proj[0]+'_'+glomstr,proj[2],pulse_i,avgnum)
def attach_files_uniquely(self,filebase,synname,postsegpath,pulse_i,avgnum=None):
ttpath = postsegpath+'/'+synname+'_tt'
if self.context.exists(ttpath):
# timetable already created by networkML reader - just wrap it below.
tt = moose.TimeTable(ttpath) # post_segment_path+'/'+syn_name+'_tt'
else:
# if timetable was not already created by networkML reader,
# it means that the synaptic weights must be zero! (no extra inhibition - only main inhibition)
# hence do not attach spikefiles
return
if tt.tableSize != 0: return # if files are already attached, do nothing!
filebase += '_pulse_'+str(pulse_i)
#### I have separate firefiles for each odor, each glom and each avgnum!
#### avgnum is what decides variability.
if avgnum is not None: filebase += '_avgnum'+str(avgnum)
## attach_spikes() accesses filenumbers to this segment
## from 'fileNumbers' field (of the timetable object in MOOSE)
## which is created while reading in networkML.
attach_spikes(filebase, tt, uniquestr+str(self.mpirank))
def run(self,network, binned):
print "Resetting MOOSE."
## from moose_utils.py sets clocks and resets
resetSim(network.context, SIMDT, PLOTDT)
print "Running at",self.mpirank
network.context.step(PULSE_RUNTIME)
mitral_responses = []
mitral_responses_binned = []
if ONLY_TWO_MITS or NO_LATERAL: num_mits = MIT_SISTERS
else: num_mits = NUM_GLOMS*MIT_SISTERS
for mitnum in range(num_mits):
mitral = network.mitralTable[mitnum]
if binned: mitral_responses_binned.append(
plotBins(mitral._vmTableSoma, pulsebins, PULSE_RUNTIME, 0.0) )
## need to convert to numpy's array(),
## else MOOSE table cannot be pickled for mpi4py send()
mitral_responses.append(array(mitral._vmTableSoma))
return (mitral_responses,mitral_responses_binned)
#----------------------------------------------------------------
if __name__ == "__main__":
if mpisize == 1:
## if only one process is called, plot one odor directly
sim = odorResponse()
## 'PG' includes 'ORN_PG', 'PG_mitral', 'mitral_PG' and 'SA_PG'
if ONLY_TWO_MITS and not NO_PGS: includeProjections = ['PG']
else: includeProjections = []
tweaks = build_tweaks(CLUB_MITRALS, NO_SPINE_INH, NO_SINGLES,\
NO_JOINTS, NO_MULTIS, NO_PGS, ONLY_TWO_MITS,\
includeProjections=includeProjections, nolateral=NO_LATERAL)
BINNED = True#False
## if not BINNED, save the full mitral Vm-s and
## not just their spiketimes by setting spiketable = False below.
uniquestr = 'pulses_'
network = OBNetwork(OBNet_file, synchan_activation_correction, tweaks,\
mpirank, uniquestr, granfilebase+'_noresp_extra', spiketable=BINNED)
#printNetTree() # from moose_utils.py
## monitor those interneurons that are connected to mitral indices 0 and 1
## save only spiketimes by setting spikes=True
extras_spikes_only = False#True
tables = setupTables(network, NO_PGS, NO_SINGLES, NO_JOINTS, NO_MULTIS,\
{'mitrals':[0,1]}, spikes=extras_spikes_only)
## pulse 0 is random air pulse, pulse 1 is odor A,
## pulse 2 is odor B, so on alternately, last pulse is A&B.
pulse_i = 1
sim.setupStim(network, pulse_i, avgnum=0)
## widely different resting potentials of mit0 and mit1
if VARY_MITS_RMP:
tweak_field('/mitrals_0/##[TYPE=Compartment]', 'Em', '-58e-3')
tweak_field('/mitrals_1/##[TYPE=Compartment]', 'Em', '-70e-3')
mit0soma_Im = setupTable('mit0somaIm',network.mitralTable[0].soma,'Im')
## setup a separate Vm table, since the one setup by OBNetwork() stores only spikes.
mit0soma_Vm = setupTable('mit0somaVm',network.mitralTable[0].soma,'Vm')
mitral_responses,mitral_responses_binned = sim.run(network,BINNED)
if not extras_spikes_only:
timevec = arange(0.0,PULSE_RUNTIME+PLOTDT+1e-12,PLOTDT)
plot_extras(timevec, tables, NO_PGS, NO_SINGLES, NO_JOINTS, NO_MULTIS)
else:
pulsebindt = PULSE_RUNTIME/pulsebins
timevec = arange(pulsebindt/2.0,PULSE_RUNTIME,pulsebindt)
plot_extras_spikes(timevec, tables, NO_PGS, NO_SINGLES,
NO_JOINTS, NO_MULTIS, pulsebins, PULSE_RUNTIME, 0.0)
## Plot the Vm, total current, membrane current and axial current in mit0's soma
## Total current in mitral soma = C dV/dt
mit0soma_C = network.mitralTable[0].soma.Cm
mit0soma_Vm = array(mit0soma_Vm)
mit0soma_Itotal = mit0soma_C * (mit0soma_Vm[1:]-mit0soma_Vm[:-1])/PLOTDT
mit0soma_Im = array(mit0soma_Im)
mit0soma_Iaxial = mit0soma_Itotal - mit0soma_Im[1:]
timevec_unbinned = arange(0.0,PULSE_RUNTIME+1e-12,PLOTDT)
## plot mitral 0 soma Vm on left-side y axis
figure(facecolor='w')
title('Vm in mitral 0 soma')
plot(timevec_unbinned,mit0soma_Vm[1:],label='Vm',color='k')
## plot mitral 0 soma I-s on right-side y axis
figure(facecolor='w')
title('Currents in mitral 0 soma')
plot(timevec_unbinned,mit0soma_Itotal,label='Itotal',color='r')
plot(timevec_unbinned,mit0soma_Im[1:],label='Im',color='g')
plot(timevec_unbinned,mit0soma_Iaxial,label='Iaxial',color='b')
legend()
## plot the responses of a glomerulus
figure(facecolor='w')
title('Glomerulus 0')
if BINNED:
mitral_responses = mitral_responses_binned
#plot(timevec,mitral_responses[0],color=(0.0,1.0,0.0))
#plot(timevec,mitral_responses[1],color=(0.0,1.0,0.5))
show()
else:
## if multiple processes are called, average over odor morphs
## pulse 0 is random air pulse, pulses 1 & 2, 3 & 4
## are odors A & B respectively, last pulse 5 is A&B.
numpulses = RANDOM_PULSE_NUMS*2
## construct the results filename
now = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M")
if NO_SINGLES: singles_str = '_NOSINGLES'
else: singles_str = '_SINGLES'
if NO_JOINTS: joints_str = '_NOJOINTS'
else: joints_str = '_JOINTS'
if NO_PGS: pgs_str = '_NOPGS'
else: pgs_str = '_PGS'
if NO_LATERAL: lat_str = '_NOLAT'
else: lat_str = '_LAT'
if VARY_MITS_RMP: varmitstr = '_VARMIT'
else: varmitstr = '_NOVARMIT'
## stable enough that time tags are not needed
now = ''#datetime.datetime.now().strftime("%Y_%m_%d_%H_%M")+'_'
outfilename = '../results/odor_pulses/'+now+'odorpulses'+\
'_netseed'+netseedstr+'_stimseed'+rateseedstr
if NONLINEAR_ORNS: outfilename += '_NL'+NONLINEAR_TYPE
outfilename += singles_str+joints_str+pgs_str+lat_str+varmitstr+\
'_numgloms'+str(NUM_GLOMS)
if DIRECTED: outfilename += '_directed'+str(FRAC_DIRECTED)
outfilename += '.pickle'
## if NOSHOW, then check if resultfile exists, proceed only if non-existent.
if 'NOSHOW' in sys.argv:
NOSHOW = True
## If NOSHOW, then automatic mode, hence don't overwrite resultfile, if exists beforehand.
if os.path.exists(outfilename):
## activdep_inhibition_repeats.py searches for Wrote in first word,
## and filename in second word. so output that even if not simulating.
if mpirank==boss:
for procnum in range(1,mpisize):
mpicomm.recv(source=procnum,tag=10)
print "ExistsSoNotWrote",outfilename
else:
mpicomm.send('done',dest=boss,tag=10)
sys.exit()
else: NOSHOW = False
if mpirank == boss:
#### collate at boss process
## mitral_responses_list[avgnum][pulsenum][mitnum]
mitral_responses_list = []
mitral_responses_binned_list = []
numavgs = (mpisize-1)/numpulses
for avgnum in range(numavgs):
response_odorset = []
response_odorset_binned = []
for pulsenum in range(numpulses):
procnum = avgnum*numpulses + pulsenum + 1
print 'waiting for process '+str(procnum)+'.'
#### you get a numpy array of rows=NUM_GLOMS*MIT_SISTERS and cols=NUMBINS
#### mitral responses has spike times, mitral_responses_binned has binned firing rates
mitral_responses,mitral_responses_binned = mpicomm.recv(source=procnum, tag=0)
response_odorset.append( mitral_responses )
response_odorset_binned.append( mitral_responses_binned )
mitral_responses_list.append(response_odorset)
mitral_responses_binned_list.append(response_odorset_binned)
## write results to a file
f = open(outfilename,'w')
pickle.dump((mitral_responses_list,mitral_responses_binned_list), f)
f.close()
print "Wrote", outfilename
if not NOSHOW:
plot_pulse_responses(outfilename)
show()
else:
#### run the slave processes
## uniquestr to put in every temp filename to avoid clashing with other processes
if len(sys.argv)>2: uniquestr = sys.argv[2]+'_' # _ necessary, else say 'pulses2'+mpirank is screwed
else: uniquestr = 'pulses_'
sim = odorResponse()
## no respiration tuning
granfilebase += '_noresp'
## If CLUB_MITRAL=False, then extra exc from mitral sisters
## (to certain connected granules as proxy for unmodelled sisters) does NOT get used.
## Instead, here I connect extra baseline excitation to ALL granules if odor is non-zero.
## Ideally, this extra exc should be only during odor period, but
## one doesn't know if suction is comparable to respiration, and also
## I'm only fitting the odor period for kernels,
## so extra exc was generated for the full duration in generate_firefiles_gran_baseline.py.
if not CLUB_MITRALS: granfilebase += '_extra'
## includeProjections gets used only if ONLY_TWO_MITS is True:
## Keep below projections to 'second order cells'
## i.e. to cells (granules) connected to mits0&1.
## The connections between second order cell
## and mits0&1 are automatically retained of course.
## 'PG' includes 'ORN_PG', 'PG_mitral', 'mitral_PG' and 'SA_PG'
includeProjections = ['PG','granule_baseline']
tweaks = build_tweaks(CLUB_MITRALS, NO_SPINE_INH, NO_SINGLES,\
NO_JOINTS, NO_MULTIS, NO_PGS, ONLY_TWO_MITS,\
includeProjections=includeProjections, nolateral=NO_LATERAL)
## unique str = 'pulses_' so that temp files of morphs and pulses etc do not overlap
network = OBNetwork(OBNet_file, synchan_activation_correction, tweaks,
mpirank, uniquestr, granfilebase, spiketable=True)
## widely different resting potentials of mit0 and mit1
if VARY_MITS_RMP:
tweak_field('/mitrals_0/##[TYPE=Compartment]', 'Em', '-58e-3')
tweak_field('/mitrals_1/##[TYPE=Compartment]', 'Em', '-70e-3')
#printNetTree() # from moose_utils.py
avgnum = (mpirank-1)/numpulses
pulsenum = (mpirank-1)%numpulses
sim.setupStim(network, pulsenum, avgnum)
mitral_responses_both = sim.run(network, binned=True)
mpicomm.send( mitral_responses_both, dest=boss, tag=0 )
print 'sent from process',mpirank
