def plot_cone_values( values ):
a1_V2 = kb.values_to_color( values , 'r' )
a_V2 = [[x,1.-x,0.,a] for x,_,_,a in a1_V2]
for i in zeros: a_V2[i][3] = 0.1
kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
sigma=model['sigma_spatial'][0] )
NRGC = len(model['RGCs' ])
Ncones = len(model['cones'])
print 'N cones : ', Ncones
print 'N filters : ', len(possible_subunits)
print 'N subunits: ', len(model['subunits'])
print 'N RGCs : ', NRGC
pylab.close('all')
fig = pylab.figure(1)
fig.frameon = False
fig.figurePatch.set_alpha(0.0)
ax = pylab.subplot(1,3,1)
#ax = fig.add_axes((0,0,1,1))
kb.plot_circles( sizes=0.1, offsets=model['cones'],
facecolors=(0.,0.,0.,0.1), edgecolors=(0.,0.,0.,0.3))
pylab.title('Cones')
#pylab.subplot(1,3,2)
#ax = kb.plot_circles( sizes=3*model['sigma_spatial'][0], offsets=possible_subunits,
# facecolors=(0.,0.,0.,0.1), edgecolors=(0.,0.,0.,0.3))
#pylab.title('Filters')
ax = pylab.subplot(1,3,2)
kb.plot_circles( sizes=3*model['sigma_spatial'][0], offsets=model['subunits'],
facecolors=(0.,0.,0.,0.1), edgecolors=(0.,0.,0.,0.3))
pylab.title('Subunits')
ax = pylab.subplot(1,3,3)
kb.plot_circles( sizes=3*model['sigma_spatial'][1], offsets=model['RGCs'],
facecolors=(0.,0.,0.,0.1), edgecolors=(0.,0.,0.,0.3))
pylab.title('RGCs')
pylab.savefig('/Users/kolia/Desktop/retina.pdf',format='pdf')
def plot_params( result , filename ):
import pylab
pylab.clf()
pylab.close('all')
nonlinearity = None
if result.has_key('V2'):
nonlinearity = result['V2']
if result.has_key('nonlinearity'):
nonlinearity = result['nonlinearity']
if nonlinearity is not None:
pylab.figure(2, figsize=(12,10))
zeros = numpy.nonzero( nonlinearity == 0 )[0]
# a1_V2 = kb.values_to_color( nonlinearity , 'r' )
# a_V2 = [[x,1.-x,0.,a] for x,_,_,a in a1_V2]
# for i in zeros: a_V2[i][3] = 0.1
# kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
# facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
# try:
# pylab.savefig('/Users/kolia/Desktop/nonlinearity_%s.pdf'%filename, format='pdf')
# except: pass
# a1_V2 = kb.values_to_uniform_color( numpy.abs(nonlinearity) , 'r' )
# a_V2 = [[x,0.,0.,x*x] for x,_,_,a in a1_V2]
# for i in zeros: a_V2[i] = [0.,0.,0.,0.1]
# kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
# facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
# try:
# pylab.savefig('/Users/kolia/Desktop/nonlinearity_abs_unif_%s.pdf'%filename, format='pdf')
# except: pass
a1_V2 = kb.values_to_uniform_color( nonlinearity , 'r' )
a_V2 = [[x,1.-x,0.,a] for x,_,_,a in a1_V2]
for i in zeros: a_V2[i][3] = 0.1
kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
try:
pylab.savefig('/Users/kolia/Desktop/nonlinearity_unif_%s.pdf'%filename, format='pdf')
except: pass
# if result.has_key('c'):
# a1_V2 = kb.values_to_color( result['c'] , 'r' )
# a_V2 = [[x,1.-x,0.,a] for x,_,_,a in a1_V2]
# for i in zeros: a_V2[i][3] = 0.1
# kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
# facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
# try:
# pylab.savefig('/Users/kolia/Desktop/c_%s.pdf'%filename, format='pdf')
# except: pass
a1_V2 = kb.values_to_uniform_color( result['c'] , 'r' )
a_V2 = [[x,1.-x,0.,a] for x,_,_,a in a1_V2]
for i in zeros: a_V2[i][3] = 0.1
kb.plot_circles( sizes=1.5, offsets=cones, linewidth=0.001,
facecolors=a_V2, edgecolors=(0.,0.,0.,0.3))
try:
pylab.savefig('/Users/kolia/Desktop/c_unif_%s.pdf'%filename, format='pdf')
except: pass
pylab.figure(1, figsize=(10,12))
N = len([1 for v in result.values() if v.size>1 and v.ndim<2])
if N>0:
i = 1
for name,x in result.items():
if x.ndim<2:
ax = pylab.subplot(N,1,i)
ax.yaxis.set_major_locator( LinearLocator(numticks=2) )
if x.size is nodes.size:
print 'Plotting', name
# scale = numpy.max(numpy.abs(x))
pylab.plot(nodes,x,'b-',nodes,x,'ro')
pylab.ylabel(name,size='medium')
# pylab.title(name+': '+', '.join([('%.2f'%(y/scale)) for y in x])+ \
# ' scale:'+('%.2f'%scale))
# pylab.xlabel('nodes: '+', '.join([('%.1f'%y) for y in nodes]))
i += 1
elif x.size>1:
print 'Plotting', name
xx = x[ numpy.nonzero(x) ]
pylab.ylabel(name,size='medium')
pylab.hist(x, bins=80)
i += 1
pylab.savefig('/Users/kolia/Desktop/%s.pdf'%filename, format='pdf')
