#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import sys
import math
import datetime
import pickle
## from node000:
## mpiexec -machinefile ~/hostfile -n <numavgs*numvarinhs+1> ~/Python-2.6.4/bin/python2.6 odor_variedinhibition.py
## nohup mpiexec -machinefile ~/hostfile -n 61 ~/Python-2.6.4/bin/python2.6 odor_variedinhibition.py < /dev/null &
## typical value for numavgs = 10
## (depends on number of available processing nodes and number of odorfiles generated)
## typical value for numvariedinh = 6 (see generate_firerates_variedinhibition.py).
## Set various options like NO_PGs or ONLY_TWO_MITS in simset_odor
## For a single run:
## python2.6 odor_variedinhibition.py
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, inputList and pulseList, GLOMS_ODOR, GLOMS_NIL
from simset_odor import * # has REALRUNTIME, NUMBINS
RUNTIME = REALRUNTIME + SETTLETIME
from pylab import * # part of matplotlib that depends on numpy but not scipy
from plot_odor_variedinhibition import *
#-----------------------------------------------------------
class odorResponse:
def __init__(self):
self.mpirank = mpirank
self.context = moose.PyMooseBase.getContext()
def setupStim(self,network,inhnum,avgnum):
self.setupOdor(network, inhnum, avgnum)
print "Setup inhnum =",inhnum,"at",self.mpirank
def setupOdor(self, network, inhnum, 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]
## 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
filebase = ORNpathINHstr+'firetimes_2sgm_glom_'+str(glomnum)
## same input to glom0, but varied input to other gloms
if glomnum==0: thisinhnum = 0
else: thisinhnum = inhnum
self.attach_files_uniquely(filebase,proj[0],proj[2],thisinhnum,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 = ORNpathINHstr+'firetimes_2sgm_glom_'+str(glomnum)
## same input to glom0, but varied input to other gloms
if glomnum==0: thisinhnum = 0
else: thisinhnum = inhnum
self.attach_files_uniquely(filebase,proj[0],proj[2],thisinhnum,avgnum)
def attach_files_uniquely(self,filebase,synname,postsegpath,inhnum,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 += '_inhnum'+str(inhnum)
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, 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(RUNTIME)
mitral_responses = []
mitral_responses_binned = []
self.mitseg_responses = []
if ONLY_TWO_MITS: mits = [mitralidx, mitralsidekickidx]
else: mits = range(NUM_GLOMS*MIT_SISTERS)
## network.mitralTable is a dictionary.
for mitnum in mits:
## mitralTable is a dict with mitnum as key
mitral = network.mitralTable[mitnum]
## only the last respiration cycle is taken
if binned: mitral_responses_binned.append(
plotBins(mitral._vmTableSoma, NUMBINS, RUNTIME,\
(NUM_RESPS-1)*RESPIRATION+SETTLETIME) )
## need to convert to numpy's array(),
## else MOOSE table cannot be pickled for mpi4py send()
mitral_responses.append(array(mitral._vmTableSoma))
#self.mitseg_responses.append(\
# (array(mitral._vmTableSoma),array(mitral._vmTableDend)))
return (mitral_responses,mitral_responses_binned)
#----------------------------------------------------------------
if __name__ == "__main__":
#### if only one process is called, plot one odor directly
if mpisize == 1:
sim = odorResponse()
## 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, mitralsidekickidx)
BINNED = False
## if not BINNED, save the full mitral Vm-s
## and not just their spiketimes by setting spiketable = False below.
network = OBNetwork(OBNet_file, synchan_activation_correction, tweaks,\
mpirank, granfilebase, spiketable=BINNED)
#printNetTree() # from moose_utils.py
## monitor those interneurons that are connected to mitral indices 0 and 1
## save only spiketimes by setting extras_spikes_only=True
#extras_spikes_only = True
#tables = setupTables(network, NO_PGS, NO_SINGLES, NO_JOINTS,\
# {'mitrals':[0,1]}, spikes=extras_spikes_only)
avgnum = 0
inhnum = 5
sim.setupStim(network, inhnum, avgnum)
mitral_responses,mitral_responses_binned = sim.run(network,binned=BINNED)
#if not extras_spikes_only:
# timevec = arange(0.0,RUNTIME+1e-12,PLOTDT)
# plot_extras(timevec, tables, NO_PGS, NO_SINGLES, NO_JOINTS)
#else:
# deltabin = RESPIRATION/NUMBINS
# ## Only the last respiration cycle
# timevec = arange(SETTLETIME+(NUM_RESPS-1)*RESPIRATION+deltabin/2,RUNTIME,deltabin)
# plot_extras_spikes(timevec, tables, NO_PGS, NO_SINGLES, NO_JOINTS,\
# NUMBINS, RUNTIME, SETTLETIME)
figure()
title('mitrals 0 and 2')
if BINNED:
deltabin = RESPIRATION/NUMBINS
# Take only the last respiration cycle
timevec = arange(SETTLETIME+(NUM_RESPS-1)*RESPIRATION+deltabin/2,RUNTIME,deltabin)
mitral_responses = mitral_responses_binned
else:
timevec = arange(0.0,RUNTIME+1e-12,PLOTDT)
plot(timevec,mitral_responses[0],color=(1.0,0.0,0.0))
plot(timevec,mitral_responses[1],color=(0.0,1.0,0.0))
#figure()
#title('mitral 2')
#plot(timevec,sim.mitseg_responses[1][0],color=(1.0,0.0,0.0))
#plot(timevec,sim.mitseg_responses[1][1],color=(0.0,1.0,0.0))
show()
#### if multiple processes are called, average over odor morphs
else:
numodors = len(inputList)
if mpirank == boss:
#### collate at boss process
mitral_responses_list = []
mitral_responses_binned_list = []
numavgs = (mpisize-1)/NUMINHS
for avgnum in range(numavgs):
response_odorset = []
response_odorset_binned = []
for inhnum in range(NUMINHS):
procnum = avgnum*NUMINHS + inhnum + 1
print 'waiting for process '+str(procnum)+'.'
## below: 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
today = datetime.date.today()
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'
now = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M")
outfilename = '../results/odor_varinh/'+now+'_odorvarinh'+singles_str+\
joints_str+pgs_str+'_numgloms'+str(NUM_GLOMS)+'.pickle'
f = open(outfilename,'w')
pickle.dump((mitral_responses_list,mitral_responses_binned_list), f)
f.close()
print "Wrote", outfilename
plot_varinh(outfilename)
show()
else:
#### run the slave processes
sim = odorResponse()
## 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, mitralsidekickidx)
network = OBNetwork(OBNet_file, synchan_activation_correction, tweaks,\
mpirank, granfilebase, spiketable=True)
#printNetTree() # from moose_utils.py
avgnum = (mpirank-1)/NUMINHS
inhnum = (mpirank-1)%NUMINHS
sim.setupStim(network, inhnum, avgnum)
mitral_responses_both = sim.run(network, binned=True)
mpicomm.send( mitral_responses_both, dest=boss, tag=0 )
print 'sent from process',mpirank
