-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathdrawfig_rob_randominputs.py
More file actions
156 lines (134 loc) · 7.77 KB
/
drawfig_rob_randominputs.py
File metadata and controls
156 lines (134 loc) · 7.77 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
from pylab import *
import scipy.io
import mytools
from matplotlib.collections import PatchCollection
from os.path import exists
from scipy.ndimage import gaussian_filter1d
#filenames = ['MMNothers_2pm_sep_Nperpop40_paramSD0.3_stimA150_130_gAMPA17.5_30.0_80.0_gNMDA5.827500000000001_9.99_26.64_gGABA35.0_35.0_dep1000_0.0_0.95_tau10.0_10.0_10.0_250.0.mat',
# 'MMNothers_2pm_sep_Nperpop40_paramSD0.3_stimA150_130_gAMPA17.5_30.0_80.0_gNMDA5.827500000000001_9.99_26.64_gGABA35.0_35.0_dep1000_0.0_0.95_tau10.0_10.0_10.0_250.0_seed2.mat']
filenames = ['MMNothers_2pm_sep_noISDIDD_Nperpop40_paramSD0.3_stimA150_130_gAMPA17.5_30.0_80.0_gNMDA5.827500000000001_9.99_26.64_gGABA35.0_35.0_dep1000_0.0_0.9_tau10.0_10.0_10.0_250.0.mat',
'MMNothers_2pm_sep_noISDIDD_Nperpop40_paramSD0.3_stimA150_130_gAMPA17.5_30.0_80.0_gNMDA5.827500000000001_9.99_26.64_gGABA35.0_35.0_dep1000_0.0_0.9_tau10.0_10.0_10.0_250.0_seed2.mat',
'MMNothers_2pm_sep_noISDIDD_Nperpop40_paramSD0.3_stimA150_130_gAMPA17.5_30.0_80.0_gNMDA5.827500000000001_9.99_26.64_gGABA35.0_35.0_dep1000_0.0_0.9_tau10.0_10.0_10.0_250.0_seed3.mat']
Nperpop = 40
Nsamp = 1
def boxoff(ax,whichxoff='top'):
ax.spines[whichxoff].set_visible(False)
ax.spines['right'].set_visible(False)
ax.get_xaxis().tick_bottom()
ax.get_yaxis().tick_left()
def mybar(ax,x,y,facecolor=[],linewidth=0.1,w=0.4):
qs = quantile(y, [0,0.25,0.5,0.75,1])
polygon = Polygon(array([[x-w,x+w,x+w,x-w],[qs[1],qs[1],qs[3],qs[3]]]).T)
p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
if type(facecolor) is not list or len(facecolor) > 0:
p.set_facecolor(facecolor)
p.set_edgecolor('#000000')
p.set_linewidth(0.3)
ax.add_collection(p)
a2 = ax.plot([x-w,x+w,x,x,x-w,x+w,x,x,x-w,x+w],[qs[0],qs[0],qs[0],qs[2],qs[2],qs[2],qs[2],qs[4],qs[4],qs[4]],'k-',lw=linewidth)
return [p,a2]
fig1, axs = subplots(1,4)
axarr = axs.reshape(prod(axs.shape),).tolist()
for iax in range(0,4):
axs[iax].set_position([0.08+0.24*iax, 0.78-0*0.2-0.12,0.18,0.08])
for iax in range(0,len(axarr)):
axarr[iax].tick_params(axis='both', which='major', labelsize=4)
boxoff(axarr[iax])
for axis in ['top','bottom','left','right']:
axarr[iax].spines[axis].set_linewidth(0.2)
axarr[iax].set_xlim([0,3800])
axarr[iax].set_ylim([0,46])
axarr[3].set_visible(False)
#axs[0,0].text(0,Nperpop+7,'Excitatory deviant detecting output (EO)',fontsize=4,ha='left',va='top',fontweight='bold')
#axs[1,0].text(0,Nperpop+7,'Excitatory population for standards (ES)',fontsize=4,ha='left',va='top')
#axs[2,0].text(0,Nperpop+7,'Inhibitory population for standards (IS)',fontsize=4,ha='left',va='top')
#axs[3,0].text(0,Nperpop+7,'Excitatory population for standards, delayed (ESD)',fontsize=4,ha='left',va='top')
#axs[4,0].text(0,Nperpop+7,'Excitatory population for deviants (ED)',fontsize=4,ha='left',va='top')
#axs[5,0].text(0,Nperpop+7,'Inhibitory population for deviants (ID)',fontsize=4,ha='left',va='top')
#axs[6,0].text(0,Nperpop+7,'Excitatory pop. for deviants, delayed (ESD)',fontsize=4,ha='left',va='top')
#axs[7,0].text(0,Nperpop+7,'Exc. timer pop. receiving phase-locked input (EP)',fontsize=4,ha='left',va='top')
#axs[8,0].text(0,Nperpop+7,'Exc. timer pop. receiving phase-locked input, alt. phase (EP2)',fontsize=4,ha='left',va='top')
MMNorder = [0,1,2,3]
axs[MMNorder[0]].set_title('Random auditory input,\nseed 1',fontsize=6,pad=12)
axs[MMNorder[1]].set_title('Random auditory input,\nseed 2',fontsize=6,pad=12)
axs[MMNorder[2]].set_title('Random auditory input,\nseed 3',fontsize=6,pad=12)
axs[MMNorder[3]].set_title('Inv. dur. deviant',fontsize=6,pad=12)
#cols = ['#000000','#AA7700']
cols = ['#000000','#000000','#000000']
#dimcols = ['#FFFF22','#CCCC55','#999999','#77CCCC','#55FFFF']
dimcols = ['#EEEEEE','#EEEEEE','#EEEEEE']
for ifile in range(0,len(filenames)):
filename = filenames[ifile]
yfiles = [0,0,0]
print('Loading '+filename)
A = scipy.io.loadmat(filename)
for q in ['standard', 'deviant', 'pacemaker', 'pacemaker2', 'output', 'standardBoost', 'deviantBoost']:
try:
shp = A[q].shape
for iy in range(0,shp[0]):
for ix in range(0,shp[1]):
if A[q][iy,ix].shape[0] == 1 and A[q][iy,ix].shape[1] > 1:
A[q][iy,ix] = A[q][iy,ix][0]
except:
pass
# Plotting the spikes for standardPopulationSpikeMonitor
#stimvec = [stimulusStandard,stimulusPaceMaker,stimulusDeviant]
#for stimind in [0,1,2]:
# thisstim = stimvec[stimind]
# lastval = 0
# dt = thisstim.dt*1000
# vals = thisstim.values
# for itime in range(0,len(vals)):
# axarr[0].plot([itime*dt,itime*dt,(itime+1)*dt],[lastval-150*stimind,vals[itime]-150*stimind,vals[itime]-150*stimind],lw=0.5)
# lastval = vals[itime]
plotteds = []
for iMMN in [3]:
#polygon = Polygon(array([[0,3900,3900,0],[yfiles[ifile],yfiles[ifile],yfiles[ifile]+Nperpop,yfiles[ifile]+Nperpop]]).T)
#p = PatchCollection([polygon], cmap=matplotlib.cm.jet)
#p.set_facecolor(dimcols[ifile])
#p.set_edgecolor(None)
#axarr[0].add_collection(p)
plotteds_this = []
axarr[ifile].plot(A['output'][iMMN,0], A['output'][iMMN,1]+yfiles[ifile], 'r.', lw=0.35, ms=0.35, mew=0.35, color=cols[ifile])
plotteds_this.append(len(A['output'][iMMN,0]))
#axarr[0].text(-500,0.5*20+yfiles[ifile],'Default' if ifile==0 else 'Random',rotation=0,ha='right',va='center',fontsize=5,fontweight='bold' if ifile==2 else 'normal')
standard_xs = [[0+x,400+x,400+x,450+x,450+x,500+x,500+x] for x in [0,500,1000,1500,2000,2500,3000]]
standard_xs_random = [50*i for i in range(1,75)]
for iMMN in [0]:
pm_on = [1,1,1,1,1,1,1]
pm_ys = [[0,0,1*(x>1),1*(x>1),1*(x>0),1*(x>0),0] for x in pm_on]
standard_xs_this_syst = [x for y in standard_xs for x in y]+[3700]
standard_xs_this = [0]+list(kron(standard_xs_random,[1,1]))+[3700]
standard_ys_this = [0] if A['stimListStandard'][0][0] == 0 else [1]
deviant_ys_this = [0] if A['stimListDeviant'][0][0] == 0 else [1]
for iblock in range(0,len(standard_xs_random)):
if (not A['stimListStandard'][0][iblock]) == (not standard_ys_this[-1]):
standard_ys_this = standard_ys_this + [standard_ys_this[-1]]*2
print("iblock = "+str(iblock)+", standard_ys_this[-1] = "+str(standard_ys_this[-1])+", A['stimListStandard'][0][iblock] = "+str(A['stimListStandard'][0][iblock])+", not A['stimListStandard'][0][iblock] = "+str(not A['stimListStandard'][0][iblock])+" ?= not standard_ys_this[-1] = "+str(not standard_ys_this[-1]))
else:
standard_ys_this = standard_ys_this + [standard_ys_this[-1],1-standard_ys_this[-1]]
if (not A['stimListDeviant'][0][iblock]) == (not deviant_ys_this[-1]):
deviant_ys_this = deviant_ys_this + [deviant_ys_this[-1]]*2
else:
deviant_ys_this = deviant_ys_this + [deviant_ys_this[-1],1-deviant_ys_this[-1]]
standard_ys_this = standard_ys_this + [standard_ys_this[-1]]
deviant_ys_this = deviant_ys_this + [deviant_ys_this[-1]]
#standard_ys_this = [x for y in standard_ys for x in y]+[0]
pm_ys_this = [x for y in pm_ys for x in y]+[0]
axarr[ifile].plot(standard_xs_this,[2*y+52 for y in standard_ys_this],'b-',lw=0.3,clip_on=False)
axarr[ifile].plot(standard_xs_this,[2*y+47 for y in deviant_ys_this],'r-',lw=0.3,clip_on=False)
axarr[ifile].plot(standard_xs_this_syst,[2*y+42 for y in pm_ys_this],'g-',lw=0.3,clip_on=False)
pos = axarr[0].get_position()
fig1.text(pos.x0 - 0.05, pos.y1 + 0.02, 'C', fontsize=11)
#pos = axarr[4].get_position()
#fig1.text(pos.x0 - 0.07, pos.y1 - 0.01, 'E', fontsize=11)
axarr[0].plot([3600,4100],[20,20],'k-',lw=0.5)
axarr[0].text(3850,22,'500 ms',ha='center',va='bottom',fontsize=5)
for iax in range(0,4):
axarr[iax].set_yticks([])
axarr[iax].set_xticks([])
for ax in axarr:
for line in ax.yaxis.get_ticklines():
line.set_markeredgewidth(0.3)
line.set_markersize(2)
fig1.savefig('fig_rob_randominputs.pdf')