def main():
cp = ClientProcess()
cp.config_stimulus_xml(example_stim_xml)
position = [0.5, 0.5, 0.5]
linear_velocity_body = [0, 0, 0]
angular_velocity_body = [0, 0, 0]
r = Report('am-I-crazy-test')
f = r.figure('varying theta', shape=(3, 3))
f2 = r.figure('varying x', shape=(3, 3))
f3 = r.figure('varying y', shape=(3, 3))
desc = lambda position, theta: 'At x: %.2f, y: %.2f, z: %.2f, theta: %d deg' % \
(position[0], position[1], position[2], numpy.degrees(theta))
idm = lambda position, theta, t: "%s-x:%.2f,y:%.2f,z:%.2f,th:%.3f" % (t, position[0], position[1], position[2], theta)
for theta in numpy.linspace(0, 2 * numpy.pi, 16):
position = [0.5, 0.5, 0.5]
attitude = rotz(theta)
res = cp.render(position, attitude,
linear_velocity_body, angular_velocity_body)
lum = res['luminance']
id = idm(position, theta, 'theta')
r.data_rgb(id, plot_luminance(lum))
f.sub(id, desc(position, theta))
for x in numpy.linspace(0, 1, 20):
position = [x, 0, 0.1]
theta = 0
res = cp.render(position, attitude,
linear_velocity_body, angular_velocity_body)
id = idm(position, theta, 'x')
r.data_rgb(id, plot_luminance(res['luminance']))
f2.sub(id, desc(position, theta))
for y in numpy.linspace(0, 1, 20):
position = [0, y, 0.1]
theta = 0
res = cp.render(position, attitude,
linear_velocity_body, angular_velocity_body)
id = idm(position, theta, 'y')
r.data_rgb(id, plot_luminance(res['luminance']))
f3.sub(id, desc(position, theta))
filename = 'demo_pipe_rotation_experimenting.html'
print "Writing to %s" % filename
r.to_html(filename)
cp.close()
def create_and_write_report(flydra_db, sample, image_name):
view_start = 'saccades_view_start_%s' % image_name
view_stop = 'saccades_view_stop_%s' % image_name
view_rstop = 'saccades_view_rstop_%s' % image_name
db = FlydraDB(flydra_db, False)
saccades = db.get_saccades(sample)
values_start = db.get_table(sample, view_start)
values_stop = db.get_table(sample, view_stop)
values_rstop = db.get_table(sample, view_rstop)
r = Report(sample)
for i in range(len(saccades)):
ri = r.node("saccade-%04d" % i)
ri.data_rgb('start', plot_luminance(values_start[i]['value']))
ri.data_rgb('stop', plot_luminance(values_stop[i]['value']))
ri.data_rgb('rstop', plot_luminance(values_rstop[i]['value']))
f = ri.figure(shape=(1, 3))
f.sub('start', 'At saccade start')
f.sub('stop', 'At saccade stop')
#f.sub('rstop', '(random stop)')
db.release_table(saccades)
db.release_table(values_start)
db.release_table(values_stop)
db.release_table(values_rstop)
filename = "%s/out/saccade_view_show/%s_%s.html" % (flydra_db, image_name, sample)
print "Writing to %s" % filename
r.to_html(filename)
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)