def compute_contrast_for_table(luminance, kernel):
contrast = numpy.ndarray(shape=luminance.shape, dtype=luminance.dtype)
contrast[:]['time'] = luminance[:]['time']
contrast[:]['frame'] = luminance[:]['frame']
contrast[:]['obj_id'] = luminance[:]['obj_id']
num = len(luminance)
pbar = progress_bar('Computing contrast', num)
for i in xrange(num):
pbar.update(i)
y = luminance[i]['value'].astype('float32')
c = intrinsic_contrast(y, kernel)
contrast[i]['value'][:] = c
return contrast
def main():
sigma_deg = 6
kernel1 = get_contrast_kernel(sigma_deg=sigma_deg, eyes_interact=True)
kernel2 = get_contrast_kernel(sigma_deg=sigma_deg, eyes_interact=False) # better
kernel1 = kernel1.astype('float32')
kernel2 = kernel2.astype('float32')
meany = Expectation()
ex1 = Expectation()
ex2 = Expectation()
cp = ClientProcess()
cp.config_use_white_arena()
cp.config_stimulus_xml(example_stim_xml)
#position = [0.15, 0.5, 0.25]
position = [0.35, 0.5, 0.25]
linear_velocity_body = [0, 0, 0]
angular_velocity_body = [0, 0, 0]
#from flydra_render.contrast import intrinsic_contrast
from fast_contrast import intrinsic_contrast #@UnresolvedImport
N = 360
pb = progress_bar('Computing contrast', N)
orientation = numpy.linspace(0, 2 * numpy.pi, N)
for i, theta in enumerate(orientation):
attitude = rotz(theta)
pb.update(i)
res = cp.render(position, attitude,
linear_velocity_body, angular_velocity_body)
y = numpy.array(res['luminance']).astype('float32')
meany.update(y)
#y = numpy.random.rand(1398)
c1 = intrinsic_contrast(y, kernel1)
c2 = intrinsic_contrast(y, kernel2)
ex1.update(c1)
ex2.update(c2)
r = Report()
r.data_rgb('meany', scale(values2retina(meany.get_value())))
r.data_rgb('mean1', plot_contrast(ex1.get_value()))
r.data_rgb('mean2', plot_contrast(ex2.get_value()))
r.data_rgb('one-y', (plot_luminance(y)))
r.data_rgb('one-c1', plot_contrast(c1))
r.data_rgb('one-c2', plot_contrast(c2))
r.data_rgb('kernel', scale(values2retina(kernel2[100, :])))
f = r.figure(shape=(2, 3))
f.sub('one-y', 'One random image')
f.sub('one-c1', 'Contrast of random image')
f.sub('one-c2', 'Contrast of random image')
f.sub('meany', 'Mean luminance')
f.sub('mean1', 'Mean over %s samples' % N)
f.sub('mean2', 'Mean over %s samples' % N)
f.sub('kernel')
filename = 'compute_contrast_demo.html'
print("Writing on %s" % filename)
r.to_html(filename)
def render_saccades_view(saccades, stimulus_xml, host=None, white=False):
client = get_rfsee_client(host)
if white: # before stimulus_xml
client.config_use_white_arena()
client.config_stimulus_xml(stimulus_xml)
num_frames = len(saccades)
dtype = [('time', 'float64'),
('obj_id', 'int'),
('frame', 'int'),
('value', ('float32', 1398))]
view_start = numpy.zeros(shape=(num_frames,), dtype=dtype)
view_stop = numpy.zeros(shape=(num_frames,), dtype=dtype)
view_rstop = numpy.zeros(shape=(num_frames,), dtype=dtype)
view_random = numpy.zeros(shape=(num_frames,), dtype=dtype)
view_sstop = numpy.zeros(shape=(num_frames,), dtype=dtype)
pb = progress_bar('Rendering saccades', num_frames)
for i in range(num_frames):
pb.update(i)
saccade = saccades[i]
orientation_start = numpy.radians(saccade['orientation_start'])
orientation_stop = numpy.radians(saccade['orientation_stop'])
# simulate how it would look like sampling from a random distribution
random_index = numpy.random.randint(0, len(saccades))
random_displacement = \
numpy.radians(saccades[random_index]['amplitude']) * \
saccades[random_index]['sign']
orientation_rstop = orientation_start + random_displacement
# keep the sign, use random amplitude
srandom_displacement = \
numpy.radians(saccades[random_index]['amplitude']) * \
saccade['sign']
orientation_sstop = orientation_start + srandom_displacement
# finally, a random orientation
orientation_random = numpy.random.rand() * 2 * numpy.pi
position = saccade['position']
attitude_start = rotz(orientation_start)
attitude_stop = rotz(orientation_stop)
attitude_rstop = rotz(orientation_rstop)
attitude_random = rotz(orientation_random)
attitude_sstop = rotz(orientation_sstop)
linear_velocity_body = [0, 0, 0]
angular_velocity_body = [0, 0, 0]
res_start = client.render(position, attitude_start,
linear_velocity_body,
angular_velocity_body)
res_stop = client.render(position, attitude_stop,
linear_velocity_body,
angular_velocity_body)
res_rstop = client.render(position, attitude_rstop,
linear_velocity_body,
angular_velocity_body)
res_random = client.render(position, attitude_random,
linear_velocity_body,
angular_velocity_body)
res_sstop = client.render(position, attitude_sstop,
linear_velocity_body,
angular_velocity_body)
view_start['value'][i] = numpy.array(res_start['luminance'])
view_stop['value'][i] = numpy.array(res_stop['luminance'])
view_rstop['value'][i] = numpy.array(res_rstop['luminance'])
view_random['value'][i] = numpy.array(res_random['luminance'])
view_sstop['value'][i] = numpy.array(res_sstop['luminance'])
# copy other fields
for arr in [view_start, view_stop, view_rstop, view_random]:
arr['frame'][i] = saccades[i]['frame']
arr['obj_id'][i] = saccades[i]['obj_id']
arr['time'][i] = saccades[i]['time_middle']
client.close()
return view_start, view_stop, view_rstop, view_random, view_sstop
def render(rows, stimulus_xml, host=None, compute_mu=False,
white=False):
cp = get_rfsee_client(host)
if white: # before stimulus_xml
cp.config_use_white_arena()
cp.config_stimulus_xml(stimulus_xml)
cp.config_compute_mu(compute_mu)
num_frames = len(rows)
dtype = [('time', 'float64'),
('obj_id', 'int'),
('frame', 'int'),
('value', ('float32', 1398))]
luminance = numpy.zeros(shape=(num_frames,), dtype=dtype)
# copy index fields
copy_fields = ['time', 'frame', 'obj_id']
for field in copy_fields:
luminance[field] = rows[:][field]
if compute_mu:
nearness = numpy.zeros(shape=(num_frames,), dtype=dtype)
dtype = [('time', 'float64'),
('obj_id', 'int'),
('frame', 'int'),
('value', ('float32', (1398, 2)))]
retinal_velocities = numpy.zeros(shape=(num_frames,), dtype=dtype)
for a in [nearness, retinal_velocities]:
for field in copy_fields:
a[field] = rows[:][field]
pb = progress_bar('Rendering', num_frames)
for i in range(num_frames):
pb.update(i)
position = rows[i]['position']
attitude = rows[i]['attitude']
linear_velocity_body = rows[i]['linear_velocity_body']
angular_velocity_body = rows[i]['angular_velocity_body']
res = cp.render(position, attitude, linear_velocity_body,
angular_velocity_body)
luminance['value'][i] = numpy.array(res['luminance'])
if compute_mu:
nearness['value'][i] = numpy.array(res['nearness'])
retinal_velocities['value'][i] = numpy.array(res['retinal_velocities'])
res = {'luminance': luminance}
if compute_mu:
res['retinal_velocities'] = retinal_velocities
res['nearness'] = nearness
cp.close()
return res