def pre_test(self):
self.plastic = {}
for s in self.sheets:
self.plastic[s] = topo.sim[s].plastic
topo.sim[s].plastic = False
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
# HACKY
if self.reset_homeo != None:
for s in self.sheets:
topo.sim[s].output_fns[self.reset_homeo].old_a *= 0
def pre_test(self):
self.plastic = {}
for s in self.sheets:
self.plastic[s] = topo.sim[s].plastic
topo.sim[s].plastic = False
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
# HACKY
if self.reset_homeo != None:
for s in self.sheets:
topo.sim[s].output_fns[self.reset_homeo].old_a *= 0
def plot_neural_dynamics(params):
sheet_names=["V1Complex"]
ip = topo.sim['Retina'].input_generator
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=10,scale=1.0,x=0.0,y=0.0,frequency=2.4))
from topo.pattern import OrientationContrast
from topo.command import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.pattern import OrientationContrast
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
import pylab
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
V1Splastic = topo.sim["V1Simple"].plastic
V1Cplastic = topo.sim["V1Complex"].plastic
V1CInhplastic = topo.sim["V1ComplexInh"].plastic
topo.sim["V1Simple"].plastic = False
topo.sim["V1Complex"].plastic = False
topo.sim["V1ComplexInh"].plastic = False
prefix="/home/jan/topographica/ActivityExploration/"
topo.sim.state_push()
from topo.command import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.pattern import OrientationContrast
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
data={}
for key in sheet_names:
data[key] = {}
for i in topo.sim[key].projections().keys():
data[key][i]=[]
data[key]["act"]=[]
(X,Y) = topo.sim["V1Complex"].sheet2matrixidx(0.0,0.0)
LateralOrientationAnnisotropy()
#return
for i in xrange(0,100):
topo.sim.run(0.05)
for key in sheet_names:
for i in topo.sim[key].projections().keys():
data[key][i].append(topo.sim[key].projections()[i].activity.copy())
data[key]["act"].append(topo.sim[key].activity.copy())
acts = topo.sim["V1Simple"].activity.copy()
actc = topo.sim["V1Complex"].activity.copy()
topo.sim.state_pop()
m = numpy.argmax(data["V1Complex"]["act"][-1])
#(X,Y) = numpy.unravel_index(m, data["V1Complex"]["act"][-1].shape)
orr=numpy.pi*topo.sim["V1Complex"].sheet_views["OrientationPreference"].view()[0][X][Y]
phase = 2*numpy.pi*topo.sim["V1Complex"].sheet_views["PhasePreference"].view()[0][X][Y]
print X,Y
pylab.figure(figsize=(20,15))
pylab.subplot(5,3,1)
pylab.title(prefix+sheet_names[0]+" [" + str(X) + "," +str(Y) + "]")
for projname in data[sheet_names[0]].keys():
a = []
for act in data[sheet_names[0]][projname]:
a.append(act[X,Y])
pylab.plot(a,label=projname)
#pylab.legend(loc='upper left')
pylab.subplot(5,3,2)
pylab.imshow(acts)
pylab.colorbar()
pylab.subplot(5,3,3)
pylab.imshow(actc)
pylab.colorbar()
(xx,yy) = topo.sim["V1Complex"].matrixidx2sheet(X,Y)
# now lets collect the size tuning
step_size=0.2
stc_lc = []
stc_aff_lc = []
stc_lr_exc_lc = []
stc_sr_exc_lc = []
stc_sr_inh_lc = []
for i in xrange(0,10):
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=i*step_size,scale=0.3,x=xx,y=yy,frequency=2.4))
topo.sim.state_push()
topo.sim.run(2.0)
stc_lc.append(topo.sim["V1Complex"].activity[X,Y].copy())
stc_aff_lc.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
stc_lr_exc_lc.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
stc_sr_exc_lc.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
stc_sr_inh_lc.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
topo.sim.state_pop()
stc_hc = []
stc_aff_hc = []
stc_lr_exc_hc = []
stc_sr_exc_hc = []
stc_sr_inh_hc = []
for i in xrange(0,10):
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=i*step_size,scale=1.0,x=xx,y=yy,frequency=2.4))
topo.sim.state_push()
topo.sim.run(2.0)
stc_hc.append(topo.sim["V1Complex"].activity[X,Y].copy())
stc_aff_hc.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
stc_lr_exc_hc.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
stc_sr_exc_hc.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
stc_sr_inh_hc.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
topo.sim.state_pop()
# lets do the surround contrast analysis
cs = 0.6
scale=1.0
colinear = OrientationContrast(orientationcenter=orr,orientationsurround=orr,sizecenter=cs,sizesurround=4.0,thickness=4.0-cs,scalecenter=scale,scalesurround=scale,x=xx,y=yy,frequency=__main__.__dict__.get('FREQ',2.4),phase=phase)
orthogonal = OrientationContrast(orientationcenter=orr,orientationsurround=orr+numpy.pi/2,sizecenter=cs,sizesurround=4.0,thickness=4.0-cs,scalecenter=scale,scalesurround=scale,x=xx,y=yy,frequency=__main__.__dict__.get('FREQ',2.4),phase=phase)
ortc_or = []
ortc_aff_or = []
ortc_lr_exc_or = []
ortc_sr_exc_or = []
ortc_sr_inh_or = []
inh_ortc_or = []
inh_ortc_lr_exc_or = []
inh_ortc_sr_exc_or = []
inh_ortc_sr_inh_or = []
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
topo.sim['Retina'].set_input_generator(orthogonal)
for i in xrange(0,80):
topo.sim.run(0.05)
ortc_or.append(topo.sim["V1Complex"].activity[X,Y].copy())
ortc_aff_or.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
ortc_lr_exc_or.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
ortc_sr_exc_or.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
ortc_sr_inh_or.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
inh_ortc_or.append(topo.sim["V1ComplexInh"].activity[X,Y].copy())
inh_ortc_lr_exc_or.append(topo.sim["V1ComplexInh"].projections()["LongEI"].activity[X,Y].copy())
inh_ortc_sr_exc_or.append(topo.sim["V1ComplexInh"].projections()["LocalEI"].activity[X,Y].copy())
inh_ortc_sr_inh_or.append(topo.sim["V1ComplexInh"].projections()["LocalII"].activity[X,Y].copy())
ortc_or_V1Complex_act = topo.sim["V1Complex"].activity.copy()
ortc_or_V1Simple_act = topo.sim["V1Simple"].activity.copy()
ortc_or_LGNOn_act = topo.sim["LGNOn"].activity.copy()
inh_ortc_or_V1Complex_act = topo.sim["V1ComplexInh"].activity.copy()
topo.sim.state_pop()
ortc_cl = []
ortc_aff_cl = []
ortc_lr_exc_cl = []
ortc_sr_exc_cl = []
ortc_sr_inh_cl = []
inh_ortc_cl = []
inh_ortc_lr_exc_cl = []
inh_ortc_sr_exc_cl = []
inh_ortc_sr_inh_cl = []
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
topo.sim['Retina'].set_input_generator(colinear)
for i in xrange(0,80):
topo.sim.run(0.05)
ortc_cl.append(topo.sim["V1Complex"].activity[X,Y].copy())
ortc_aff_cl.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
ortc_lr_exc_cl.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
ortc_sr_exc_cl.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
ortc_sr_inh_cl.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
inh_ortc_cl.append(topo.sim["V1ComplexInh"].activity[X,Y].copy())
inh_ortc_lr_exc_cl.append(topo.sim["V1ComplexInh"].projections()["LongEI"].activity[X,Y].copy())
inh_ortc_sr_exc_cl.append(topo.sim["V1ComplexInh"].projections()["LocalEI"].activity[X,Y].copy())
inh_ortc_sr_inh_cl.append(topo.sim["V1ComplexInh"].projections()["LocalII"].activity[X,Y].copy())
ortc_cl_V1Complex_act = topo.sim["V1Complex"].activity.copy()
ortc_cl_V1Simple_act = topo.sim["V1Simple"].activity.copy()
ortc_cl_LGNOn_act = topo.sim["LGNOn"].activity.copy()
inh_ortc_cl_V1Complex_act = topo.sim["V1ComplexInh"].activity.copy()
topo.sim.state_pop()
pylab.subplot(5,3,4)
pylab.plot(stc_lc,label='act')
pylab.plot(stc_aff_lc,label='aff')
pylab.plot(stc_lr_exc_lc,label='LongEE')
pylab.plot(stc_sr_exc_lc,label='ShortEE')
pylab.plot(stc_sr_inh_lc,label='ShortIE')
pylab.plot(numpy.array(stc_sr_exc_lc)/(-1.0*numpy.array(stc_sr_inh_lc)+0.01)/10,label='E:I ratio')
pylab.xlim=(0,20)
pylab.legend()
pylab.subplot(5,3,5)
pylab.plot(stc_hc,label='act')
pylab.plot(stc_aff_hc,label='aff')
pylab.plot(stc_lr_exc_hc,label='LongEE')
pylab.plot(stc_sr_exc_hc,label='ShortEE')
pylab.plot(stc_sr_inh_hc,label='ShortIE')
pylab.plot(numpy.array(stc_sr_exc_hc)/(-1.0*numpy.array(stc_sr_inh_hc)+0.01)/10,label='E:I ratio')
pylab.xlim=(0,20)
pylab.legend()
pylab.subplot(5,3,6)
pylab.plot(stc_hc,label='act hc')
pylab.plot(stc_lc,label='act lc')
pylab.xlim=(0,20)
pylab.legend()
pylab.subplot(5,3,7)
pylab.title('collinear')
pylab.plot(ortc_cl,label='act')
pylab.plot(ortc_aff_cl,label='aff')
pylab.plot(ortc_lr_exc_cl,label='LongEE')
pylab.plot(ortc_sr_exc_cl,label='ShortEE')
pylab.plot(ortc_sr_inh_cl,label='ShortIE')
pylab.xlim=(0,60)
pylab.legend()
pylab.subplot(5,3,8)
pylab.title('orthogonal')
pylab.plot(ortc_or,label='act')
pylab.plot(ortc_aff_or,label='aff')
pylab.plot(ortc_lr_exc_or,label='LongEE')
pylab.plot(ortc_sr_exc_or,label='ShortEE')
pylab.plot(ortc_sr_inh_or,label='ShortIE')
pylab.xlim=(0,60)
pylab.legend()
pylab.subplot(5,3,9)
pylab.title('collinear inh')
pylab.plot(inh_ortc_cl,label='act')
pylab.plot(inh_ortc_lr_exc_cl,label='LongEE')
pylab.plot(inh_ortc_sr_exc_cl,label='ShortEE')
pylab.plot(inh_ortc_sr_inh_cl,label='ShortIE')
pylab.xlim=(0,60)
pylab.legend()
pylab.subplot(5,3,10)
pylab.title('orthogonal inh')
pylab.plot(inh_ortc_or,label='act')
pylab.plot(inh_ortc_lr_exc_or,label='LongEE')
pylab.plot(inh_ortc_sr_exc_or,label='ShortEE')
pylab.plot(inh_ortc_sr_inh_or,label='ShortIE')
pylab.xlim=(0,60)
pylab.legend()
pylab.subplot(5,3,11)
pylab.imshow(ortc_cl_V1Complex_act,vmin=0,vmax=1.0)
pylab.subplot(5,3,12)
pylab.imshow(inh_ortc_cl_V1Complex_act,vmin=0,vmax=1.0)
#pylab.subplot(5,3,13)
#pylab.imshow(ortc_cl_LGNOn_act,vmin=0,vmax=1.0)
pylab.subplot(5,3,13)
pylab.imshow(ortc_or_V1Complex_act,vmin=0,vmax=1.0)
pylab.subplot(5,3,14)
pylab.imshow(inh_ortc_or_V1Complex_act,vmin=0,vmax=1.0)
pylab.subplot(5,3,15)
pylab.imshow(ortc_or_LGNOn_act,vmin=0,vmax=1.0)
topo.sim["V1Simple"].plastic = V1Splastic
topo.sim["V1Complex"].plastic = V1Cplastic
topo.sim["V1ComplexInh"].plastic = V1CInhplastic
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(ip)
pylab.savefig(prefix+ sheet_names[0] + params);
def plot_size_tuning(params):
sheet_names=["V1Complex"]
prefix="/home/jan/topographica/ActivityExploration/"
from topo.command.basic import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
import pylab
V1Splastic = topo.sim["V1Simple"].plastic
V1Cplastic = topo.sim["V1Complex"].plastic
V1CInhplastic = topo.sim["V1ComplexInh"].plastic
topo.sim["V1Simple"].plastic = False
topo.sim["V1Complex"].plastic = False
topo.sim["V1ComplexInh"].plastic = False
x = 0
y = 0.06
(X,Y) = topo.sim["V1Complex"].sheet2matrixidx(x,y)
(Xl,Yl) = topo.sim["LGNOn"].sheet2matrixidx(x,y)
#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
#orr=numpy.pi*topo.sim["V1Complex"].sheet_views["OrientationPreference"].view()[0][X][Y]
#phase = 2*numpy.pi*topo.sim["V1Simple"].sheet_views["PhasePreference"].view()[0][X][Y]
orr =0
phase =0
stc_e_hc = []
stc_i_hc = []
stc_LongEE_hc = []
stc_LocalEE_hc = []
stc_LocalIE_hc = []
stc_Aff_hc = []
LGN_hc = []
V1S_hc = []
num_sizes = 50
max_size = 1.3
for size in xrange(0,num_sizes):
size = float(size)/num_sizes*max_size
ip = topo.sim['Retina'].input_generator
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=orr,phase=phase,size=size,scale=1.0,x=x,y=y,frequency=2.4))
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
topo.sim.run(4.0)
stc_e_hc.append(topo.sim["V1Complex"].activity[X,Y].copy())
stc_i_hc.append(topo.sim["V1ComplexInh"].activity[X,Y].copy())
LGN_hc.append(topo.sim["LGNOn"].activity[Xl,Yl].copy())
V1S_hc.append(topo.sim["V1Simple"].activity[X,Y].copy())
stc_Aff_hc.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
stc_LongEE_hc.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
stc_LocalEE_hc.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
stc_LocalIE_hc.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
topo.sim.state_pop()
stc_e_lc = []
stc_i_lc = []
stc_LongEE_lc = []
stc_LocalEE_lc = []
stc_LocalIE_lc = []
stc_Aff_lc = []
LGN_lc = []
V1S_lc = []
sizes=[]
for size in xrange(0,num_sizes):
size = float(size)/num_sizes*max_size
ip = topo.sim['Retina'].input_generator
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=orr,phase=phase,size=size,scale=0.3,x=x,y=y,frequency=2.4))
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim.state_push()
topo.sim.run(4.0)
stc_e_lc.append(topo.sim["V1Complex"].activity[X,Y].copy())
stc_i_lc.append(topo.sim["V1ComplexInh"].activity[X,Y].copy())
LGN_lc.append(topo.sim["LGNOn"].activity[Xl,Yl].copy())
V1S_lc.append(topo.sim["V1Simple"].activity[X,Y].copy())
stc_Aff_lc.append(topo.sim["V1Complex"].projections()["V1SimpleAfferent"].activity[X,Y].copy())
stc_LongEE_lc.append(topo.sim["V1Complex"].projections()["LongEE"].activity[X,Y].copy())
stc_LocalEE_lc.append(topo.sim["V1Complex"].projections()["LocalEE"].activity[X,Y].copy())
stc_LocalIE_lc.append(topo.sim["V1Complex"].projections()["LocalIE"].activity[X,Y].copy())
topo.sim.state_pop()
sizes.append(size)
pylab.figure(figsize=(20,15))
pylab.subplot(6,1,1)
pylab.plot(sizes,stc_e_lc,'ro',label='exc lc')
pylab.plot(sizes,stc_e_lc,'r')
pylab.plot(sizes,stc_i_lc,'bo',label='inh lc')
pylab.plot(sizes,stc_i_lc,'b')
pylab.plot(sizes,stc_e_hc,'r+',label='exc hc')
pylab.plot(sizes,stc_e_hc,'r')
pylab.plot(sizes,stc_i_hc,'b+',label='inh hc')
pylab.plot(sizes,stc_i_hc,'b')
pylab.legend()
pylab.subplot(6,1,2)
pylab.plot(sizes,numpy.array(stc_Aff_lc)+numpy.array(stc_LongEE_lc)+numpy.array(stc_LocalEE_lc),'ro',label='exc lc')
pylab.plot(sizes,numpy.array(stc_Aff_lc)+numpy.array(stc_LongEE_lc)+numpy.array(stc_LocalEE_lc),'r')
pylab.plot(sizes,stc_LocalIE_lc,'bo',label='ing lc')
pylab.plot(sizes,stc_LocalIE_lc,'b')
pylab.plot(sizes,numpy.array(stc_Aff_hc)+numpy.array(stc_LongEE_hc)+numpy.array(stc_LocalEE_hc),'r+',label='exc hc')
pylab.plot(sizes,numpy.array(stc_Aff_hc)+numpy.array(stc_LongEE_hc)+numpy.array(stc_LocalEE_hc),'r')
pylab.plot(sizes,stc_LocalIE_hc,'b+',label='inh hc')
pylab.plot(sizes,stc_LocalIE_hc,'b')
pylab.legend()
pylab.subplot(6,1,3)
pylab.plot(sizes,numpy.array(stc_Aff_lc)+numpy.array(stc_LongEE_lc),'ro',label='exc lc')
pylab.plot(sizes,numpy.array(stc_Aff_lc)+numpy.array(stc_LongEE_lc),'r')
pylab.plot(sizes,stc_LocalIE_lc,'bo',label='ing lc')
pylab.plot(sizes,stc_LocalIE_lc,'b')
pylab.plot(sizes,numpy.array(stc_Aff_hc)+numpy.array(stc_LongEE_hc),'r+',label='exc hc')
pylab.plot(sizes,numpy.array(stc_Aff_hc)+numpy.array(stc_LongEE_hc),'r')
pylab.plot(sizes,stc_LocalIE_hc,'b+',label='inh hc')
pylab.plot(sizes,stc_LocalIE_hc,'b')
pylab.legend()
pylab.subplot(6,1,4)
pylab.plot(sizes,numpy.array(stc_Aff_lc),'ko',label='aff lc')
pylab.plot(sizes,numpy.array(stc_Aff_lc),'k')
pylab.plot(sizes,numpy.array(stc_LongEE_lc),'kx',label='long lc')
pylab.plot(sizes,numpy.array(stc_LongEE_lc),'k')
pylab.plot(sizes,numpy.array(stc_LocalEE_lc)/10,'k*',label='local lc')
pylab.plot(sizes,numpy.array(stc_LocalEE_lc)/10,'k')
pylab.plot(sizes,numpy.array(stc_Aff_hc),'go',label='aff hc')
pylab.plot(sizes,numpy.array(stc_Aff_hc),'g')
pylab.plot(sizes,numpy.array(stc_LongEE_hc),'gx',label='long hc')
pylab.plot(sizes,numpy.array(stc_LongEE_hc),'g')
pylab.plot(sizes,numpy.array(stc_LocalEE_hc)/10,'g*',label='local hc')
pylab.plot(sizes,numpy.array(stc_LocalEE_hc)/10,'g')
pylab.legend()
pylab.subplot(6,1,5)
pylab.plot(sizes,numpy.array(V1S_lc),'ko',label='V1S lc')
pylab.plot(sizes,numpy.array(V1S_lc),'k')
pylab.plot(sizes,numpy.array(V1S_hc),'go',label='V1S hc')
pylab.plot(sizes,numpy.array(V1S_hc),'g')
pylab.legend()
pylab.subplot(6,1,6)
pylab.plot(sizes,numpy.array(LGN_lc),'ko',label='LGN lc')
pylab.plot(sizes,numpy.array(LGN_lc),'k')
pylab.plot(sizes,numpy.array(LGN_hc),'go',label='LGN hc')
pylab.plot(sizes,numpy.array(LGN_hc),'g')
pylab.legend()
pylab.savefig(prefix+ params);
def make_full_analysis(a,b,c,d,e,f,g,h,i,j,k,l,m):
import topo
print a,b,c,d,e,f,g,h,i,j,k,l,m
#topo.sim["V1Simple"].projections()["V1SimpleFeedbackExc1"].strength=b
#topo.sim["V1Simple"].projections()["V1SimpleFeedbackInh"].strength=c
#topo.sim["V1Complex"].projections()["LongEE"].strength=d
#topo.sim["V1ComplexInh"].projections()["LongEI"].strength=e
#topo.sim["V1Complex"].projections()["LocalIE"].strength=f
#topo.sim["V1ComplexInh"].projections()["LocalII"].strength=g
#topo.sim["V1Complex"].projections()["V1SimpleAfferent"].strength=h
#topo.sim["V1Complex"].projections()["LocalEE"].strength=i
#topo.sim["V1ComplexInh"].projections()["LocalEI"].strength=j
#topo.sim["V1Complex"].output_fns[1].t*=0
#topo.sim["V1Complex"].output_fns[1].t+=k
#topo.sim["V1ComplexInh"].output_fns[1].t*=0
#topo.sim["V1ComplexInh"].output_fns[1].t+=l
#topo.sim["V1ComplexInh"].output_fns[1].gain=m
#topo.sim['V1Simple'].output_fns[0].old_a*=0
#topo.sim['V1Complex'].output_fns[0].old_a*=0
#topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
from topo.analysis.featureresponses import MeasureResponseCommand, FeatureMaps, SinusoidalMeasureResponseCommand,FeatureCurveCommand
FeatureMaps.num_orientation=16
MeasureResponseCommand.scale=1.0
SinusoidalMeasureResponseCommand.frequencies=[2.4]
FeatureCurveCommand.num_orientation=16
MeasureResponseCommand.duration=4.0
FeatureCurveCommand.curve_parameters=[{"contrast":40},{"contrast":50},{"contrast":90}]
V1Splastic = topo.sim["V1Simple"].plastic
V1Cplastic = topo.sim["V1Complex"].plastic
V1CInhplastic = topo.sim["V1ComplexInh"].plastic
topo.sim["V1Simple"].plastic = False
topo.sim["V1Complex"].plastic = False
topo.sim["V1ComplexInh"].plastic = False
wipe_out_activity()
clear_event_queue()
par = 'Analysis:' + str(a)+ "_" + str(b) + "_" + str(c) + "_" + str(d)+ "_" + str(e) + "_" + str(f) + "_" + str(g) + "_" + str(h) + "_" + str(i) + "_" + str(j) + "_" + str(k) + "_" + str(l) + "_" + str(m)
#d = os.path.dirname(par)
if not os.path.exists(par):
os.makedirs(par)
normalize_path.prefix = par
#plot_neural_dynamics('neural_dynamics.png')
import contrib.surround_analysis
from topo.analysis.featureresponses import SinusoidalMeasureResponseCommand,FeatureCurveCommand
from topo.base.projection import ProjectionSheet
from topo.sheet import GeneratorSheet
import contrib.jacommands
import contrib.surround_analysis
exec "from topo.analysis.vision import analyze_complexity" in __main__.__dict__
from topo.analysis.featureresponses import PatternPresenter
PatternPresenter.duration=4.0
import topo.command.pylabplot
reload(topo.command.pylabplot)
#contrib.surround_analysis.run_dynamics_analysis(0.0,0.0,0.7,__main__.__dict__.get("analysis_scale",0.3))
#PatternPresenter.duration=4.0
#a = topo.command.pylabplot.measure_or_tuning_fullfield.instance(sheet=topo.sim["V1Complex"])
#a.duration=4.0
#a()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,0]",sheet=topo.sim["V1Complex"],coords=[(0,0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.1,0.1]",sheet=topo.sim["V1Complex"],coords=[(0.1,0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.1,-0.1]",sheet=topo.sim["V1Complex"],coords=[(0.1,-0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.1,0.1]",sheet=topo.sim["V1Complex"],coords=[(-0.1,0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.1,-0.1]",sheet=topo.sim["V1Complex"],coords=[(-0.1,-0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.2,0.2]",sheet=topo.sim["V1Complex"],coords=[(0.2,0.2)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.2,-0.2]",sheet=topo.sim["V1Complex"],coords=[(0.2,-0.2)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.2,0.2]",sheet=topo.sim["V1Complex"],coords=[(-0.2,0.2)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.2,-0.2]",sheet=topo.sim["V1Complex"],coords=[(-0.2,-0.2)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,0.1]",sheet=topo.sim["V1Complex"],coords=[(0.0,0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,-0.1]",sheet=topo.sim["V1Complex"],coords=[(0.0,-0.1)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.1,0]",sheet=topo.sim["V1Complex"],coords=[(-0.1,0.0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.1,0]",sheet=topo.sim["V1Complex"],coords=[(0.1,-0.0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.3,0.3]",sheet=topo.sim["V1Complex"],coords=[(0.3,0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.3,-0.3]",sheet=topo.sim["V1Complex"],coords=[(0.3,-0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.3,0.3]",sheet=topo.sim["V1Complex"],coords=[(-0.3,0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.3,-0.3]",sheet=topo.sim["V1Complex"],coords=[(-0.3,-0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.24,0.24]",sheet=topo.sim["V1Complex"],coords=[(0.25,0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.24,-0.24]",sheet=topo.sim["V1Complex"],coords=[(0.25,-0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.24,0.24]",sheet=topo.sim["V1Complex"],coords=[(-0.25,0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.24,-0.24]",sheet=topo.sim["V1Complex"],coords=[(-0.25,-0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,0.24]",sheet=topo.sim["V1Complex"],coords=[(0.0,0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,-0.24]",sheet=topo.sim["V1Complex"],coords=[(0.0,-0.25)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.24,0]",sheet=topo.sim["V1Complex"],coords=[(-0.25,0.0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.24,0]",sheet=topo.sim["V1Complex"],coords=[(0.25,-0.0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,0.3]",sheet=topo.sim["V1Complex"],coords=[(0.0,0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0,-0.3]",sheet=topo.sim["V1Complex"],coords=[(0.0,-0.3)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[-0.3,0]",sheet=topo.sim["V1Complex"],coords=[(-0.3,0.0)])()
#topo.command.pylabplot.cyclic_tuning_curve.instance(x_axis="orientation",filename="ORTC[0.3,0]",sheet=topo.sim["V1Complex"],coords=[(0.3,-0.0)])()
#contrib.surround_analysis.surround_analysis().analyse([(0,0),(1.0,0.0),(0.0,1.0),(-1.0,0.0),(0.0,-1.0),(1.0,1.0),(-1.0,1.0),(1.0,-1.0),(-1.0,-1.0)],12,15)
normalize_path.prefix = './D-with-lowhighcontrast'
if not os.path.exists(normalize_path.prefix):
os.makedirs(normalize_path.prefix)
contrib.surround_analysis.surround_analysis().analyse([(0,0)],12,15)
MeasureResponseCommand.scale=1.0
MeasureResponseCommand.duration=4.0
SinusoidalMeasureResponseCommand.frequencies=[2.4]
FeatureCurveCommand.num_orientation=16
FeatureCurveCommand.curve_parameters=[{"contrast":15},{"contrast":50},{"contrast":90}]
from topo.command import load_snapshot
#load_snapshot('./DATA/LESI/TEST-small/CCSimple_000002.00.typ')
#load_snapshot('./DATA/LESI/TEST/CCSimple_000002.00.typ')
load_snapshot('./DATA/LESI/CCLESIGifLatest/CCSimple_010000.00.typ')
#load_snapshot('./DATA/LESI/CCLESIGif-NEW1/CCSimple_010000.00_with_map.typ')
#load_snapshot('./DATA/LESI/CCLESIGif12-Orig-LARGE_NEWEXPANDER5000/CCSimple_005002.00.typ')
from topo.command import wipe_out_activity, clear_event_queue
wipe_out_activity()
clear_event_queue()
from topo.pattern import SineGrating, Disk
class SineGratingDiskTemp(SineGrating):
mask_shape = param.Parameter(default=Disk(smoothing=0,size=1.0))
def new_set_parameters(a,b,c,d,e,f,g):
print a,b,c,d,e,f,g
topo.sim["LGNOn"].projections()["LateralGC"].strength=a
topo.sim["LGNOff"].projections()["LateralGC"].strength=a
def _divide_with_constant(x, y):
y = numpy.clip(y, 0, 10000)
x = numpy.clip(x, 0, 10000)
def size_tuning_analysis(x,y,scale):
from topo.pattern import OrientationContrast
from topo.command import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.pattern import OrientationContrast
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
(xx,yy) = topo.sim["V1Complex"].sheet2matrixidx(x,y)
orr= numpy.pi*topo.sim["V1Complex"].sheet_views["OrientationPreference"].view()[0][xx][yy]
phase = 2*numpy.pi*topo.sim["V1Complex"].sheet_views["PhasePreference"].view()[0][xx][yy]
activities_s = []
activities_c = []
activities_ci = []
from topo.command import wipe_out_activity,clear_event_queue
for i in xrange(0,40):
pg = SineGratingDiskTemp(orientation=orr,phase=phase,size=(12.0/float(i+1)),scale=1.0,x=x,y=y,frequency=__main__.__dict__.get('FREQ',2.4))
pp = PatternPresenter(pattern_generator=pg,duration=4.0,contrast_parameter="weber_contrast")
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
topo.sim["V1Simple"].plastic = False
topo.sim["V1Complex"].plastic = False
topo.sim["V1ComplexInh"].plastic = False
wipe_out_activity()
clear_event_queue()
for f in PatternDrivenAnalysis.pre_analysis_session_hooks: f()
topo.sim.state_push()
for f in PatternDrivenAnalysis.pre_presentation_hooks: f()
pp({},{})
#topo.guimain.refresh_activity_windows()
activities_c.append(topo.sim["V1Complex"].activity.copy())
activities_ci.append(topo.sim["V1ComplexInh"].activity.copy())
activities_s.append(topo.sim["V1Simple"].activity.copy())
for f in PatternDrivenAnalysis.post_presentation_hooks: f()
topo.sim.state_pop()
for f in PatternDrivenAnalysis.post_analysis_session_hooks: f()
a = []
b = []
c = []
pylab.figure()
pylab.subplot(6,6,1)
for i in xrange(0,40):
pylab.subplot(7,7,i+1)
pylab.imshow(activities_c[i],vmin=0.0,vmax=2.0,interpolation='nearest')
pylab.xticks([], [])
pylab.yticks([], [])
pylab.xlabel(str(12.0-i*0.3),fontsize=8)
#pylab.colorbar(shrink=0.1)
a.append(activities_c[i][xx][yy])
c.append(activities_ci[i][xx][yy])
b.append(12.0-i*0.3)
pylab.figure()
pylab.subplot(6,6,1)
for i in xrange(0,40):
pylab.subplot(7,7,i+1)
pylab.imshow(activities_s[i],vmin=0.0,vmax=2.0,interpolation='nearest')
pylab.xticks([], [])
pylab.yticks([], [])
pylab.xlabel(str(12.0-i*0.3),fontsize=8)
pylab.figure()
pylab.plot(b,a,'r',label='EXC')
pylab.plot(b,c,'b',label='INH')
pylab.legend()
release_fig("STC_settling_complex")
def plot_neural_dynamics(params):
sheet_names=["V1Complex"]
ip = topo.sim['Retina'].input_generator
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=10,scale=1.0,x=0.0,y=0.0,frequency=2.4))
from topo.pattern import OrientationContrast
from topo.command import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.pattern import OrientationContrast
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
import pylab
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
V1Splastic = topo.sim["V1Simple"].plastic
V1Cplastic = topo.sim["V1Complex"].plastic
V1CInhplastic = topo.sim["V1ComplexInh"].plastic
topo.sim["V1Simple"].plastic = False
topo.sim["V1Complex"].plastic = False
topo.sim["V1ComplexInh"].plastic = False
prefix="/home/antolikjan/topographica/ActivityExploration/"
topo.sim.state_push()
from topo.command import pattern_present
from topo.base.functionfamily import PatternDrivenAnalysis
from topo.pattern import OrientationContrast
from topo.analysis.featureresponses import PatternPresenter
from topo.base.sheet import Sheet
data={}
for key in sheet_names:
data[key] = {}
for i in topo.sim[key].projections().keys():
data[key][i]=[]
data[key]["act"]=[]
for i in xrange(0,100):
topo.sim.run(0.05)
for key in sheet_names:
for i in topo.sim[key].projections().keys():
data[key][i].append(topo.sim[key].projections()[i].activity.copy())
data[key]["act"].append(topo.sim[key].activity.copy())
acts = topo.sim["V1Simple"].activity.copy()
actc = topo.sim["V1Complex"].activity.copy()
topo.sim.state_pop()
m = numpy.argmax(data["V1Complex"]["act"][-1])
(X,Y) = numpy.unravel_index(m, data["V1Complex"]["act"][-1].shape)
print X,Y
pylab.figure(figsize=(20,5))
pylab.subplot(2,3,1)
pylab.title(prefix+sheet_names[0]+" [" + str(X) + "," +str(Y) + "]")
for projname in data[sheet_names[0]].keys():
a = []
for act in data[sheet_names[0]][projname]:
a.append(act[X,Y])
pylab.plot(a,label=projname)
#pylab.legend(loc='upper left')
pylab.subplot(2,3,2)
pylab.imshow(acts)
pylab.colorbar()
pylab.subplot(2,3,3)
pylab.imshow(actc)
pylab.colorbar()
(xx,yy) = topo.sim["V1Complex"].matrixidx2sheet(X,Y)
# now lets collect the size tuning
step_size=0.2
stc_lc = []
for i in xrange(0,20):
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=i*step_size,scale=0.3,x=xx,y=yy,frequency=2.4))
topo.sim.state_push()
topo.sim.run(4.0)
stc_lc.append(topo.sim["V1Complex"].activity[X,Y].copy())
topo.sim.state_pop()
stc_hc = []
for i in xrange(0,20):
topo.sim['V1Simple'].output_fns[0].old_a*=0
topo.sim['V1Complex'].output_fns[0].old_a*=0
topo.sim['V1ComplexInh'].output_fns[0].old_a*=0
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(SineGratingDiskTemp(orientation=0.0,phase=0.0,size=i*step_size,scale=1.0,x=xx,y=yy,frequency=2.4))
topo.sim.state_push()
topo.sim.run(4.0)
stc_hc.append(topo.sim["V1Complex"].activity[X,Y].copy())
topo.sim.state_pop()
pylab.subplot(2,3,4)
pylab.plot(stc_lc,label='30%')
pylab.plot(stc_hc,label='100%')
pylab.legend()
topo.sim["V1Simple"].plastic = V1Splastic
topo.sim["V1Complex"].plastic = V1Cplastic
topo.sim["V1ComplexInh"].plastic = V1CInhplastic
wipe_out_activity()
clear_event_queue()
topo.sim['Retina'].set_input_generator(ip)
pylab.savefig(prefix+ sheet_names[0] + params);