#!/usr/bin/env python
# -*- coding: utf-8 -*-
########## You need to run: python2.6 average_tuft_inhibition.py <tuftADIresults_foldername>
import os
import sys
import math
import pickle
sys.path.extend(["..","../networks","../generators","../simulations"])
from moose.utils import * # imports moose
from data_utils import *
from stimuliConstants import * # has SETTLETIME
from simset_activinhibition import * # has oninject_ext
from plot_mitral_connectivity_NetworkML import * # get connectivity from netfile
from pylab import * # part of matplotlib that depends on numpy but not scipy
## override sim time settings of stimuliConstants.py (has stimuliConstantsMinimal.py)
## Here in tuftADI, unlike activdep inh,
## ASYM_TEST puts same ORN frate into B as A, rather than const.
ASYM_TEST = False#True
DIRECTED = True
FRAC_DIRECTED = 0.01#0.03
IN_VIVO = True
onInject = oninject_ext # in Hz, from simset_activinhibition_minimal
REVERSED_ADI = False
NONLINEAR_ORNS = False
## if ODORINH, sims used 1x granule bgnd (ensure extraexc_factor=1 in stimuliConstants.py)
## and 10Hz ORN to mitB, else 1x and 5Hz.
## I'm using this to just deliver 0.5x and 1x lat i/p, to show linearity of lat inh.
ODORINH = True#False
if IN_VIVO: invivo_str = '_invivo'
else: invivo_str = ''
if DIRECTED: dirt_str = '_directed'+str(FRAC_DIRECTED)
else: dirt_str = ''
if REVERSED_ADI: rev_str = '_reversed'
else: rev_str = ''
if ASYM_TEST: asym_str = '_asym'
else: asym_str = ''
if ODORINH: odorinh_str = '_odorinh'
else: odorinh_str = '_airinh'
## inh = (no_singles,no_joints,no_PGs)
inh = (False,False,False)
print "Using NOSINGLES =",inh[0],"NOJOINTS =",inh[1],"NOPGS =",inh[2]
netseeds = [100.0,200.0,300.0,400.0,500.0,600.0,700.0,800.0,900.0,1000.0]
if IN_VIVO:
mit_distance_list = [50.0,200.0,400.0,600.0,800.0,1000.0,1200.0,1400.0,1600.0,1800.0,1850.0,1900.0] # microns
else:
mit_distance_list = [50.0] # microns
## whether to calculate and print the number of joint granules connected
SHOW_CONN = False
if len(sys.argv)<2:
print 'Specify folder name where tuftADI results reside.'
sys.exit(1)
else:
filebase = sys.argv[1]
## eg: choose '_aug17_2' from '../results/tuftADI_aug17_2/'
dirextns = filebase.split('/')
if dirextns[-1]=='': dirextn = dirextns[-2]
else: dirextn = dirextns[-1]
dirextn = dirextn.split('tuftADI')[-1]
def get_filename(netseed,inh,mitdistance,lat_mitnum=3,
_directed=DIRECTED,_frac_directed=FRAC_DIRECTED,
_asym_str=asym_str,_rev_str=rev_str,_odorinh_str=odorinh_str,
directed_str=dirt_str,filebase='../results/tuftADI'):
### read filename from the output file of automated run
## construct the filename
if inh[0]: singles_str = '_NOSINGLES'
else: singles_str = '_SINGLES'
if inh[1]: joints_str = '_NOJOINTS'
else: joints_str = '_JOINTS'
if inh[2]: pgs_str = '_NOPGS'
else: pgs_str = '_PGS'
## stable enough that time tags are not needed
outfilename = filebase+'/tuftADI_'+str(lat_mitnum)+\
'_seed'+str(netseed)+'_mitdist'+str(mitdistance)+\
singles_str+joints_str+pgs_str+invivo_str+directed_str+\
_rev_str+_asym_str+_odorinh_str+'.pickle'
return outfilename, (singles_str, joints_str, pgs_str)
def get_rates_inh(filename):
f = open(filename,'r')
Ainjectarray, both_firingratearrays = pickle.load(f)
f.close()
mit_alone = array(both_firingratearrays[0])
mit_inhibited = array(both_firingratearrays[1])
diff_frates = mit_alone - mit_inhibited
max_redux = max(diff_frates)
avg_redux = mean(diff_frates)
return Ainjectarray, both_firingratearrays, max_redux, avg_redux
def plot_avg_inh_lat(mit_distance,_rev_str,manyplots=False,directed_str=dirt_str):
## load the data
full_firingratearray = []
half_firingratearray = []
redux_frate_array = []
max_redux_frate_array = []
avg_redux_frate_array = []
for netseed in netseeds:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
directed_str=directed_str,filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename):
print "File not found",filename
continue
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
full_firingratearray.append(both_firingratearrays)
max_redux_frate_array.append(max_redux)
avg_redux_frate_array.append(avg_redux)
## load for 0.5x (_airinh) firing rate in B too.
if not ASYM_TEST:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_airinh',
directed_str=directed_str,filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
half_firingratearray.append(both_firingratearrays)
## calculate means and std errs
full_firingratearray = array(full_firingratearray)
mean_firingratearray = mean(full_firingratearray, axis=0)
std_firingratearray = std(full_firingratearray, axis=0)
half_firingratearray = array(half_firingratearray)
mean_half_firingratearray = mean(half_firingratearray, axis=0)
std_half_firingratearray = std(half_firingratearray, axis=0)
if manyplots:
## plot the lone vs inhibited firing rate vs input (Hz) curves
mainfig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
mainaxes = mainfig.add_subplot(111,frameon=False)
for mitralBinject in [0,1]:
if ASYM_TEST:
if mitralBinject == 0: mitB_str = '0.0 Hz'
else: mitB_str = 'as for A'
else: mitB_str = str(mitralBinject*onInject)+' Hz'
mainaxes.errorbar(x=Ainjectarray,\
y=mean_firingratearray[mitralBinject],\
yerr=std_firingratearray[mitralBinject],\
color=['k','b'][mitralBinject], marker=['s','o'][mitralBinject],\
markersize=marker_size, label="mitB i/p = "+mitB_str, linewidth=linewidth)
if not ASYM_TEST and 'reverse' not in _rev_str:
mitB_str = str(0.5*onInject)+' Hz'
mainaxes.errorbar(x=Ainjectarray,\
y=mean_half_firingratearray[1],\
yerr=std_half_firingratearray[1],\
color='r', marker='d', markersize=marker_size,\
label="mitB i/p = "+mitB_str, linewidth=linewidth)
mainaxes.get_yaxis().set_ticks_position('left')
mainaxes.get_xaxis().set_ticks_position('bottom')
xmin, xmax = mainaxes.get_xaxis().get_view_interval()
ymin, ymax = mainaxes.get_yaxis().get_view_interval()
mainaxes.set_xlim([0,xmax])
mainaxes.set_ylim([0,ymax])
mainaxes.set_xticks([0,xmax])
mainaxes.set_yticks([0,ymax])
mainaxes.add_artist(Line2D((0, 0), (0, ymax), color='black', linewidth=axes_linewidth))
mainaxes.add_artist(Line2D((0, xmax), (0, 0), color='black', linewidth=axes_linewidth))
##biglegend("lower right")
#biglegend("upper left")
axes_labels(mainaxes,"mitral A ORN rate (Hz)","mitral A firing rate (Hz)")
mainfig.tight_layout()
figfilename = '../figures/tuftADI/tuftADI'+'_mitdist'+str(mit_distance) \
+invivo_str+dirt_str+_rev_str+asym_str+dirextn
mainfig.savefig(figfilename+'.png', dpi=mainfig.dpi)
mainfig.savefig(figfilename+'.svg', dpi=mainfig.dpi)
return max_redux_frate_array, avg_redux_frate_array
def plot_avg_inh_lat_all(mit_distance,_rev_str,manyplots=False):
mainfig = figure(figsize=(columnwidth*2.0,linfig_height),dpi=300,facecolor='w')
ax1 = mainfig.add_subplot(1,5,1)
ax2 = mainfig.add_subplot(1,5,2)
ax3 = mainfig.add_subplot(1,5,3)
ax4 = mainfig.add_subplot(1,5,4)
ax5 = mainfig.add_subplot(1,5,5)
## inh = (no_singles,no_joints,no_PGs)
inh_options = [
('../results/tuftADI/',(False,False,False),ax1),
('../results/tuftADI/',(False,False,True),ax2),
('../results/tuftADI/',(True,True,False),ax3),
('../results/tuftADI_aug17_2_PGmod/',(False,False,False),ax4),
('../results/tuftADI_aug17_4_PGmod/',(False,False,False),ax5)]
maxy = 0.0
for axnum,(filebase,inh,mainaxes) in enumerate(inh_options):
## load the data
full_firingratearray = []
half_firingratearray = []
redux_frate_array = []
max_redux_frate_array = []
avg_redux_frate_array = []
for netseed in netseeds:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
full_firingratearray.append(both_firingratearrays)
max_redux_frate_array.append(max_redux)
avg_redux_frate_array.append(avg_redux)
## load for 0.5x (_airinh) firing rate in B too.
if not ASYM_TEST:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_airinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
half_firingratearray.append(both_firingratearrays)
## calculate means and std errs
full_firingratearray = array(full_firingratearray)
mean_firingratearray = mean(full_firingratearray, axis=0)
std_firingratearray = std(full_firingratearray, axis=0)
half_firingratearray = array(half_firingratearray)
mean_half_firingratearray = mean(half_firingratearray, axis=0)
std_half_firingratearray = std(half_firingratearray, axis=0)
if manyplots:
## plot the lone vs inhibited firing rate vs input (Hz) curves
for mitralBinject in [0,1]:
if ASYM_TEST:
if mitralBinject == 0: mitB_str = '0.0 Hz'
else: mitB_str = 'as for A'
else: mitB_str = str(mitralBinject*onInject)+' Hz'
mainaxes.errorbar(x=Ainjectarray,\
y=mean_firingratearray[mitralBinject],\
yerr=std_firingratearray[mitralBinject],\
color=['k','b'][mitralBinject], marker=['s','o'][mitralBinject],\
markersize=marker_size, label="mitB i/p = "+mitB_str, linewidth=linewidth)
if not ASYM_TEST and 'reverse' not in _rev_str:
mitB_str = str(0.5*onInject)+' Hz'
mainaxes.errorbar(x=Ainjectarray,\
y=mean_half_firingratearray[1],\
yerr=std_half_firingratearray[1],\
color='r', marker='d', markersize=marker_size,\
label="mitB i/p = "+mitB_str, linewidth=linewidth)
xmin,xmax,ymin,ymax = \
beautify_plot(mainaxes,x0min=True,y0min=True,xticksposn='bottom',yticksposn='left')
maxy = max(maxy,ymax)
if axnum==0:
axes_labels(mainaxes,"","mitral A firing rate (Hz)")
elif axnum==2:
axes_labels(mainaxes,"mitral A ORN rate (Hz)","")
for ax in [ax1,ax2,ax3,ax4,ax5]:
ax.set_ylim([0,maxy])
ax.set_yticks([0,maxy])
#mainfig.tight_layout()
mainfig.subplots_adjust(top=0.95,left=0.07,right=0.95,bottom=0.15,wspace=0.25,hspace=0.4)
figfilename = '../figures/tuftADI/tuftADI_alllat_'+'_mitdist'+str(mit_distance) \
+invivo_str+dirt_str+_rev_str+asym_str+dirextn
mainfig.savefig(figfilename+'.png', dpi=mainfig.dpi)
mainfig.savefig(figfilename+'.svg', dpi=mainfig.dpi)
return
def plot_avg_inh_self(mit_distance,_rev_str,manyplots=False):
## plot the lone vs self-inhibited firing rate vs input (Hz) curves
mainfig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
mainaxes = mainfig.add_subplot(111)
## inh = (no_singles,no_joints,no_PGs)
inh_list = [(True,True,True),(False,False,True),(True,True,False),(False,False,False)]
labels_list = ['no PGs+granules','only granules','only PGs','both']
for inh_i,inh in enumerate(inh_list):
full_firingratearray = []
dashes = [(1.5,0.5),(0.5,0.5),(1.5,0.5,0.5,0.5),(1.0,0.0)]
for netseed in netseeds:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
## load the data
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
## not interested in lateral inhibition here, so leave that out
full_firingratearray.append(both_firingratearrays[0])
## calculate means and std errs
full_firingratearray = array(full_firingratearray)
mean_firingratearray = mean(full_firingratearray, axis=0)
std_firingratearray = std(full_firingratearray, axis=0)
mainaxes.errorbar(x=Ainjectarray,\
y=mean_firingratearray,\
yerr=std_firingratearray,\
color=['k','b','c','r'][inh_i], marker=['s','^','o','d'][inh_i],\
markersize=marker_size, linewidth=linewidth,\
label=labels_list[inh_i]) # removed dashes=dashes[inh_i]
beautify_plot(mainaxes,x0min=True,y0min=True,\
xticksposn='bottom',yticksposn='left',drawxaxis=True,drawyaxis=True)
### Legend too big
#biglegend('lower right',mainaxes,fontsize=label_fontsize-2,\
# labelspacing=0.1,borderpad=0.1,markerscale=0.1,columnspacing=0.1,frameon=False)
## Legend without the error bars
## get handles
handles, labels = mainaxes.get_legend_handles_labels()
## remove the errorbars
handles = [h[0] for h in handles]
## use them in the legend
leg = mainaxes.legend(handles, labels, loc='upper left',numpoints=1,\
labelspacing=0.0,borderpad=0.01,markerscale=1,columnspacing=0.0,\
handletextpad=0.3,prop={'size':label_fontsize-2},frameon=False)
### modify legend text sizes -- use prop={'size':...} above,
### else below method causes alignment issues of handles with labels
#for t in leg.get_texts():
# t.set_fontsize(label_fontsize-2)
axes_labels(mainaxes,"mitral A ORN rate (Hz)","mitral A firing rate (Hz)",ypad=-6)
mainfig.tight_layout()
figfilename = '../figures/tuftADI/tuftADI'+'_mitdist'+str(mit_distance) \
+invivo_str+dirt_str+_rev_str+asym_str
mainfig.savefig(figfilename+'_selfinh.png', dpi=mainfig.dpi)
mainfig.savefig(figfilename+'_selfinh.svg', dpi=mainfig.dpi)
def plot_avg_diff_inh(mit_distance,_rev_str):
## load the data
full_firingratearray = []
noinh_firingratearray = []
noself_firingratearray = []
redux_frate_array = []
max_redux_frate_array = []
avg_redux_frate_array = []
for netseed in netseeds:
filename,_ = get_filename(netseed,inh,mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
full_firingratearray.append(both_firingratearrays)
max_redux_frate_array.append(max_redux)
avg_redux_frate_array.append(avg_redux)
filename,_ = get_filename(netseed,(True,False,True),mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
noself_firingratearray.append(both_firingratearrays)
filename,_ = get_filename(netseed,(True,True,True),mit_distance,
_asym_str=asym_str,_rev_str=_rev_str,_odorinh_str='_odorinh',
filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
noinh_firingratearray.append(both_firingratearrays)
## calculate means and std errs
full_firingratearray = array(full_firingratearray)
mean_firingratearray = mean(full_firingratearray, axis=0)
std_firingratearray = std(full_firingratearray, axis=0)
noinh_firingratearray = array(noinh_firingratearray)
mean_noinh_firingratearray = mean(noinh_firingratearray, axis=0)
std_noinh_firingratearray = std(noinh_firingratearray, axis=0)
noself_firingratearray = array(noself_firingratearray)
mean_noself_firingratearray = mean(noself_firingratearray, axis=0)
std_noself_firingratearray = std(noself_firingratearray, axis=0)
############## plotting
## plot the lone vs inh firing rate vs I curves
mainfig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
mainaxes = mainfig.add_subplot(111,frameon=False)
## plot mit cell alone
mainaxes.errorbar(x=Ainjectarray,\
y=mean_noinh_firingratearray[0], yerr=std_noinh_firingratearray[0],\
color='k', marker='s',\
markersize=marker_size, linewidth=linewidth)
## plot mit cell without self inhibition
mainaxes.errorbar(x=Ainjectarray,\
y=mean_noself_firingratearray[0], yerr=std_noself_firingratearray[0],\
color='r', marker='o',\
markersize=marker_size, linewidth=linewidth)
## plot mit cell without self inhibition + lateral odorinh
mainaxes.errorbar(x=Ainjectarray,\
y=mean_noself_firingratearray[1], yerr=std_noself_firingratearray[1],\
color='r', marker='d',\
markersize=marker_size, linewidth=linewidth)
for mitralBinject in [0,1]:
if ASYM_TEST:
if mitralBinject == 0: mitB_str = '0.0 Hz'
else: mitB_str = 'as for A'
else: mitB_str = str(mitralBinject*onInject)+' Hz'
mainaxes.errorbar(x=Ainjectarray,\
y=mean_firingratearray[mitralBinject],\
yerr=std_firingratearray[mitralBinject],\
color=['b','b'][mitralBinject], marker=['x','+'][mitralBinject],\
markersize=marker_size, label="mitB i/p = "+mitB_str, linewidth=linewidth)
mainaxes.get_yaxis().set_ticks_position('left')
mainaxes.get_xaxis().set_ticks_position('bottom')
xmin, xmax = mainaxes.get_xaxis().get_view_interval()
ymin, ymax = mainaxes.get_yaxis().get_view_interval()
mainaxes.set_xlim([0,xmax])
mainaxes.set_ylim([0,ymax])
mainaxes.set_xticks([0,xmax])
mainaxes.set_yticks([0,ymax])
mainaxes.add_artist(Line2D((0, 0), (0, ymax), color='black', linewidth=axes_linewidth))
mainaxes.add_artist(Line2D((0, xmax), (0, 0), color='black', linewidth=axes_linewidth))
##biglegend("lower right")
#biglegend("upper left")
axes_labels(mainaxes,"mitral A ORN frate (Hz)","mitral A firing rate (Hz)")
mainfig.tight_layout()
figfilename = '../figures/tuftADI/tuftADI'+'_mitdist'+str(mit_distance) \
+invivo_str+dirt_str+_rev_str+asym_str
#mainfig.savefig(figfilename+'.png', dpi=mainfig.dpi)
#mainfig.savefig(figfilename+'.svg', dpi=mainfig.dpi)
return max_redux_frate_array, avg_redux_frate_array
def plot_avg_inh_Bconst_BasA(mit_distance,_rev_str=rev_str,asym_list=['_asym','']):
## plot the firing rate vs I curves for lone, BasA, Bconst
mainfig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
mainaxes = mainfig.add_subplot(111,frameon=False)
curvei = 0
max_redux_frate_array = []
avg_redux_frate_array = []
## asym (True/False) specifies whether mitB gets sameasA / const tuft input.
for _asym_str in asym_list:
## load the data
full_firingratearray = []
for netseed in netseeds:
filename,_ = get_filename(netseed,inh,mit_distance,\
_asym_str=_asym_str,_rev_str=_rev_str,filebase=filebase)
## if the result file for these seeds & tweaks doesn't exist,
## then carry on to the next.
if not os.path.exists(filename): continue
print 'Using',filename
Ainjectarray, both_firingratearrays, max_redux, avg_redux = \
get_rates_inh(filename)
full_firingratearray.append(both_firingratearrays)
## use only those frate reductions that are with same input as A in mitB.
if not _asym_str:
max_redux_frate_array.append(max_redux)
avg_redux_frate_array.append(avg_redux)
## calculate means and std errs
full_firingratearray = array(full_firingratearray)
mean_firingratearray = mean(full_firingratearray, axis=0)
std_firingratearray = std(full_firingratearray, axis=0)
for mitralBinject in [0,1]:
if _asym_str: ## if '', then const i/p to mitB
mitB_str = str(mitralBinject*onInject)+' Hz'
else:
if mitralBinject == 0: mitB_str = '0.0 Hz'
else: mitB_str = 'as for A'
## condition to not plot the lone mitA f-vs-I twice
#if mitralBinject!=0 or _asym_str:
if True:
mainaxes.errorbar(x=Ainjectarray,\
y=mean_firingratearray[mitralBinject],\
yerr=std_firingratearray[mitralBinject],\
color=['k','b','r'][curvei], marker=['s','o','v'][curvei],\
markersize=marker_size, label="mitB i/p = "+mitB_str, linewidth=linewidth)
curvei += 1
mainaxes.get_yaxis().set_ticks_position('left')
mainaxes.get_xaxis().set_ticks_position('bottom')
xmin, xmax = mainaxes.get_xaxis().get_view_interval()
ymin, ymax = mainaxes.get_yaxis().get_view_interval()
mainaxes.set_xlim([0,xmax])
mainaxes.set_ylim([0,ymax])
mainaxes.set_xticks([0,xmax])
mainaxes.set_yticks([0,ymax])
mainaxes.add_artist(Line2D((0, 0), (0, ymax), color='black', linewidth=axes_linewidth))
mainaxes.add_artist(Line2D((0, xmax), (0, 0), color='black', linewidth=axes_linewidth))
##biglegend("lower right")
#biglegend("upper left")
axes_labels(mainaxes,"mitral A ORN frate (Hz)","mitral A firing rate (Hz)")
mainfig.tight_layout()
mainfig.savefig('../figures/tuftADI/tuftADI_both' \
+invivo_str+dirt_str+rev_str+odorinh_str+'.png', \
dpi=mainfig.dpi)
mainfig.savefig('../figures/tuftADI/tuftADI_both' \
+invivo_str+dirt_str+rev_str+odorinh_str+'.svg', \
dpi=mainfig.dpi)
return max_redux_frate_array, avg_redux_frate_array
def plot_avg_inh_distancedep(mit_distance_list):
redux = []
redux_std = []
for i,reverse in enumerate([False,True]):
print "Reversed =", reverse
if reverse:
rev_label = "Reversed"
_rev_str = '_reversed'
else:
rev_label = "Forward"
_rev_str = ''
redux_directed = []
redux_directed_std = []
for mit_distance in mit_distance_list:
print 'Distance =',mit_distance,'microns:'
## the former below, plots for only one of asym=True/False
## (i.e. sameasA/const i/p to mitB) set at the top.
## whereas the latter below, plots for both in the same graph.
max_redux_frate_array, avg_redux_frate_array = \
plot_avg_inh_lat(mit_distance,_rev_str,manyplots=False)
#max_redux_frate_array, avg_redux_frate_array = \
# plot_avg_inh_Bconst_BasA(mit_distance,_rev_str)
redux_directed.append(mean(avg_redux_frate_array))
redux_directed_std.append(std(avg_redux_frate_array))
redux.append((rev_label,redux_directed))
redux_std.append(redux_directed_std)
## plot the reduction-in-frate vs separation-of-mitrals for forward & reverse tuft inh.
fig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
ax = fig.add_subplot(111)
mit_distance_list = array(mit_distance_list)/1000.0
errorbar(mit_distance_list,-array(redux[0][1]),yerr=redux_std[0],\
color=(1,0,0),linewidth=linewidth,marker='o',label=redux[0][0])
errorbar(mit_distance_list,-array(redux[1][1]),yerr=redux_std[1],\
color=(0,0,1),linewidth=linewidth,marker='x',label=redux[1][0])
#biglegend('upper right')#'lower left')
axes_labels(ax,'separation (mm)','mean $\Delta$ rate (Hz)',ypad=-3) # (0 to 1.5nA) in 400ms
ax.xaxis.set_label_position('top')
ax.get_yaxis().set_ticks_position('left')
ax.get_xaxis().set_ticks_position('top')
## set xticks text sizes
for label in ax.get_xticklabels():
label.set_fontsize(label_fontsize)
## hide the top and left axes
for loc, spine in ax.spines.items(): # items() returns [(key,value),...]
spine.set_linewidth(axes_linewidth)
if loc in ['right','bottom']:
spine.set_color('none') # don't draw spine
xmin, xmax = ax.get_xaxis().get_view_interval()
ymin, ymax = ax.get_yaxis().get_view_interval()
ax.set_xlim(0,xmax)
ax.set_ylim(ymin,0)
ax.set_yticks([ymin,0])
ax.set_xticks([0,1,2])
fig_clip_off(fig)
fig.tight_layout()
fig.savefig('../figures/tuftADI/tuftADI_redux'+invivo_str+asym_str+'.svg',\
bbox_inches='tight',dpi=fig.dpi)
fig.savefig('../figures/tuftADI/tuftADI_redux'+invivo_str+asym_str+'.png',\
bbox_inches='tight',dpi=fig.dpi)
def plot_avg_inh_distancedep_v2(mit_distance_list):
redux = []
redux_std = []
mit_distance_list = array(mit_distance_list)
for i,reverse in enumerate([False,True]):
## plot the reduction-in-frate vs separation-of-mitrals for forward & reverse tuft inh.
fig = figure(figsize=(columnwidth/2.0,linfig_height),dpi=300,facecolor='w')
ax = fig.add_subplot(111)
print "Reversed =", reverse
if reverse:
rev_label = "Reversed"
_rev_str = '_reversed'
else:
rev_label = "Forward"
_rev_str = ''
for dirti,directed_str in enumerate(['','_directed0.0','_directed0.01']):
redux_directed = []
redux_directed_std = []
print "Directed str set as",directed_str,"."
for mit_distance in mit_distance_list:
print 'Distance =',mit_distance,'microns:'
## the former below, plots for only one of asym=True/False
## (i.e. sameasA/const i/p to mitB) set at the top.
## whereas the latter below, plots for both in the same graph.
max_redux_frate_array, avg_redux_frate_array = \
plot_avg_inh_lat(mit_distance,_rev_str,manyplots=False,\
directed_str=directed_str)
#max_redux_frate_array, avg_redux_frate_array = \
# plot_avg_inh_Bconst_BasA(mit_distance,_rev_str)
redux_directed.append(mean(avg_redux_frate_array))
redux_directed_std.append(std(avg_redux_frate_array))
redux.append((rev_label,redux_directed))
redux_std.append(redux_directed_std)
errorbar(mit_distance_list/1000.,-array(redux_directed),yerr=redux_directed_std,\
color=['g','b','r'][dirti],linewidth=linewidth,\
marker=['o','x','s'][dirti],label=redux[0][0])
#biglegend('upper right')#'lower left')
axes_labels(ax,'separation (mm)','mean $\Delta$ rate (Hz)',ypad=-3) # (0 to 1.5nA) in 400ms
ax.xaxis.set_label_position('top')
ax.get_yaxis().set_ticks_position('left')
ax.get_xaxis().set_ticks_position('top')
## set xticks text sizes
for label in ax.get_xticklabels():
label.set_fontsize(label_fontsize)
## hide the top and left axes
for loc, spine in ax.spines.items(): # items() returns [(key,value),...]
spine.set_linewidth(axes_linewidth)
if loc in ['right','bottom']:
spine.set_color('none') # don't draw spine
xmin, xmax = ax.get_xaxis().get_view_interval()
ymin, ymax = ax.get_yaxis().get_view_interval()
ax.set_xlim(0,xmax)
ymin = -35 ## hard-coded for my simulations
ax.set_ylim(ymin,1)
ax.set_yticks([ymin,0,2])
ax.set_xticks([0,1,2])
fig_clip_off(fig)
fig.tight_layout()
fig.savefig('../figures/tuftADI/tuftADI_redux'+invivo_str+asym_str+rev_label+'.svg',\
bbox_inches='tight',dpi=fig.dpi)
fig.savefig('../figures/tuftADI/tuftADI_redux'+invivo_str+asym_str+rev_label+'.png',\
bbox_inches='tight',dpi=fig.dpi)
if __name__ == "__main__":
### for single / few test runs...
#plot_avg_inh_Bconst_BasA(600.0,_rev_str='',asym_list=[''])
#plot_avg_diff_inh(400.0,_rev_str='')
## PAPER figure 4: example tuft inh -- lateral
#plot_avg_inh_lat(400.0,_rev_str='',manyplots=True)
## PAPER figure 5 (diff pg inputs) : tuft inh -- lateral
#plot_avg_inh_lat_all(400.0,_rev_str='',manyplots=True)
## For a single plot of lat inh -- air and odor
## set the directory on commandline and the inh_options in the function:
#plot_avg_inh_lat(400.0,_rev_str='',manyplots=True)
## PAPER figure 2: tuft inh -- self
plot_avg_inh_self(400.0,_rev_str='',manyplots=True)
## OBSOLETE PAPER figure 4: tuft inh -- distance dependence
#plot_avg_inh_distancedep(mit_distance_list)
## PAPER figure 4: tuft inh -- distance dependence
#plot_avg_inh_distancedep_v2(mit_distance_list)
show()
