def lateral_inhibitory(self, src_properties, dest_properties):
"""
Switch to divisive inhibition, otherwise parameters unchanged.
"""
return Model.CFProjection.params(
delay=0.05,
name='LateralInhibitory',
weights_generator=ig.random.GaussianCloud(
gaussian_size=self.latinh_size),
strength=self.inh_strength,
activity_group=(0.6, DivideWithConstant(c=self.division_constant)),
learning_rate=self.inh_lr,
nominal_bounds_template=sheet.BoundingBox(
radius=self.latinh_radius))
def lateral_gain_control(self, src_properties, dest_properties):
#TODO: Are those 0.25 the same as lgnlateral_radius/2.0?
return Model.SharedWeightCFProjection.params(
delay=0.05,
dest_port=('Activity'),
activity_group=(0.6, DivideWithConstant(c=0.11)),
weights_generator=imagen.Gaussian(
size=0.25,
aspect_ratio=1.0,
output_fns=[transferfn.DivisiveNormalizeL1()]),
nominal_bounds_template=sheet.BoundingBox(radius=0.25),
name=('LateralGC' + src_properties['eye']
if 'eye' in src_properties else 'LateralGC'),
strength=0.6 / len(self.attrs.Eyes))
def lateral_gain_control(self, src_properties, dest_properties):
#TODO: Are those 0.25 the same as lgnlateral_radius/2.0?
name='LateralGC'
if 'eye' in src_properties:
name+=src_properties['eye']
if 'SF' in src_properties and self.gain_control_SF:
name+=('SF'+str(src_properties['SF']))
return Model.SharedWeightCFProjection.params(
delay=0.05,
dest_port=('Activity'),
activity_group=(0.6,DivideWithConstant(c=0.11)),
weights_generator=imagen.Gaussian(size=self.gain_control_size,
aspect_ratio=1.0,
output_fns=[transferfn.DivisiveNormalizeL1()]),
nominal_bounds_template=sheet.BoundingBox(radius=self.gain_control_size),
name=name,
strength=0.6/(2 if self['binocular'] else 1))