# Tukey mask - fading effect
tw_x = tukey(n=n_x, r=0.15)
tw_y = tukey(n=n_y, r=0.15)
w = np.tile(((np.outer(tw_y,tw_x))), (N_frame,1,1))
tukey_mask = w.T
# Get Random Clouds
name_ = mc.figpath + name
for seed in [123456 + step for step in range(seeds)]:
name__ = mc.figpath + name + '-seed-' + str(seed) + '-sf0-' + str(sf_0).replace('.', '_') + '-V_X-' + str(V_X).replace('.', '_')
# broadband
z = mc.envelope_gabor(fx, fy, ft, name_, B_sf=Bsf, sf_0=sf_0, theta=theta, B_V=B_V, B_theta = B_theta, alpha=alpha)
movie = mc.figures(z, name=None, vext=vext, seed=seed, masking=True)
for label, mask in zip(['_mask', '_tukey_mask'], [gauss, tukey_mask]):
name_ = name__ + '-cloud-' + label
if anim_exist(name_):
movie = mc.rectif(movie*mask)
mc.anim_save(movie, name_, display=False, vext=vext)
# narrowband
z = mc.envelope(fx, fy, ft, name_, B_sf=B_sf/10., sf_0=sf_0, theta=theta, B_V=B_V, B_theta=B_theta, alpha=alpha)
movie = mc.figures(z, name=None, vext=vext, seed=seed, masking=True)
for label, mask in zip(['_mask', 'tukey_mask'], [gauss, tukey_mask]):
name_ = name__ + '-blob-' + label
if anim_exist(name_):
movie = mc.rectif(movie*mask)
mc.anim_save(movie, name_, display=False, vext=vext)
vext = '.gif'
# show example
table = """
#acl LaurentPerrinet,LaurentPerrinetGroup:read,write,delete,revert All:
#format wiki
-----
= MotionPaids : from MotionClouds components to a plaid-like stimulus =
"""
theta1, theta2, B_theta = np.pi/4., -np.pi/4., np.pi/32
diag1 = mc.envelope_gabor(fx, fy, ft, theta=theta1, V_X=np.cos(theta1), V_Y=np.sin(theta1), B_theta=B_theta)
diag2 = mc.envelope_gabor(fx, fy, ft, theta=theta2, V_X=np.cos(theta2), V_Y=np.sin(theta2), B_theta=B_theta)
name_ = name + '_comp1'
mc.figures(diag1, name_, vext=vext, seed=12234565)
table += '||<width="33%">{{attachment:' + name_ + '.png||width=100%}}||<width="33%">{{attachment:' + name_ + '_cube.png||width=100%}}||<width="33%">{{attachment:' + name_ + '.gif||width=100%}}||\n'
name_ = name + '_comp2'
mc.figures(diag2, name_, vext=vext, seed=12234565)
table += '||{{attachment:' + name_ + '.png||width=100%}}||{{attachment:' + name_ + '_cube.png||width=100%}}||{{attachment:' + name_ + '.gif||width=100%}}||\n'
name_ = name
mc.figures(diag1 + diag2, name, vext=vext, seed=12234565)
table += '||{{attachment:' + name_ + '.png||width=100%}}||{{attachment:' + name_ + '_cube.png||width=100%}}||{{attachment:' + name_ + '.gif||width=100%}}||\n'
table += '||||||<align="justify"> This figure shows how one can create !MotionCloud stimuli that specifically target component and pattern cell. We show in the different lines of this table respectively: Top) one motion cloud component (with a strong selectivity toward the orientation perpendicular to direction) heading in the upper diagonal Middle) a similar motion cloud component following the lower diagonal Bottom) the addition of both components: perceptually, the horizontal direction is predominant. <<BR>> Columns represent isometric projections of a cube. The left column displays iso-surfaces of the spectral envelope by displaying enclosing volumes at 5 different energy values with respect to the peak amplitude of the Fourier spectrum. The middle column shows an isometric view of the faces of the movie cube. The first frame of the movie lies on the x-y plane, the x-t plane lies on the top face and motion direction is seen as diagonal lines on this face (vertical motion is similarly see in the y-t face). The third column displays the actual movie as an animation. ||\n'
table += '\n\n'
table += '== exploring different component angles ==\n'
# make a grid
try:
if mc.notebook: print('we are in the notebook')
except:
import os
import MotionClouds as mc
import numpy as np
#initialize
fx, fy, ft = mc.get_grids(mc.N_X, mc.N_Y, mc.N_frame)
color = mc.envelope_color(fx, fy, ft) #
name = 'speed'
# now selects in preference the plane corresponding to the speed with some thickness
z = color*mc.envelope_speed(fx, fy, ft)
mc.figures(z, name)
# explore parameters
for V_X in [-1.0, -0.5, 0.0, 0.1, 0.5, 1.0, 4.0]:
name_ = name + '-V_X-' + str(V_X).replace('.', '_')
z = color * mc.envelope_speed(fx, fy, ft, V_X=V_X)
mc.figures(z, name_)
for V_Y in [-1.0, -0.5, 0.5, 1.0, 2.0]:
name_ = name + '-V_Y-' + str(V_Y).replace('.', '_')
z = color * mc.envelope_speed(fx, fy, ft, V_X=0.0, V_Y=V_Y)
mc.figures(z, name_)
for B_V in [0.001, 0.01, 0.05, 0.1, 0.5, 1.0, 10.0]:
name_ = name + '-B_V-' + str(B_V).replace('.', '_')
z = color * mc.envelope_speed(fx, fy, ft, B_V=B_V)
#format wiki
-----
= Recruiting different population ratios in V1 using MotionClouds' orientation components =
"""
theta, B_theta_low, B_theta_high = np.pi/4., np.pi/32, 2*np.pi
B_V = 10.
seed=12234565
mc1 = mc.envelope_gabor(fx, fy, ft, V_X=0., V_Y=0., theta=theta, B_V=B_V, B_theta=B_theta_low)
mc2 = mc.envelope_gabor(fx, fy, ft, V_X=0., V_Y=0., theta=theta, B_V=B_V, B_theta=B_theta_high)
name_ = name + '_comp1'
mc.figures(mc1, name_, vext=vext, seed=seed)
table += '||<width="33%">{{attachment:' + name_ + '.png||width=100%}}||<width="33%">{{attachment:' + name_ + '_cube.png||width=100%}}||<width="33%">{{attachment:' + name_ + '.gif||width=100%}}||\n'
name_ = name + '_comp2'
mc.figures(mc2, name_, vext=vext, seed=seed)
table += '||{{attachment:' + name_ + '.png||width=100%}}||{{attachment:' + name_ + '_cube.png||width=100%}}||{{attachment:' + name_ + '.gif||width=100%}}||\n'
table += '||||||<align="justify"> This figure shows how one can create !MotionCloud stimuli that specifically target different population in V1. We show in the two lines of this table motion cloud component with a (Top) narrow orientation bandwith (Bottom) a wide bandwitdh: perceptually, there is no predominant position or speed, just different orientation contents. <<BR>> Columns represent isometric projections of a cube. The left column displays iso-surfaces of the spectral envelope by displaying enclosing volumes at 5 different energy values with respect to the peak amplitude of the Fourier spectrum. The middle column shows an isometric view of the faces of the movie cube. The first frame of the movie lies on the x-y plane, the x-t plane lies on the top face and motion direction is seen as diagonal lines on this face (vertical motion is similarly see in the y-t face). The third column displays the actual movie as an animation. ||\n'
table += '\n\n'
table += '== exploring different orientation bandwidths ==\n'
# make just a line
downscale = 2
fx, fy, ft = mc.get_grids(mc.N_X/downscale, mc.N_Y/downscale, mc.N_frame)
#line1, line2 = '', ''
for B_theta in B_theta_high*2.**-np.arange(7):# np.linspace(B_theta_low, B_theta_high, N_orient):#, endpoint=False):
Superposition of MotionClouds to generate competing motions.
(c) Laurent Perrinet - INT/CNRS
"""
import numpy
import MotionClouds as mc
fx, fy, ft = mc.get_grids(mc.N_X, mc.N_Y, mc.N_frame)
name = 'competing'
name_ = mc.figpath + name
if mc.anim_exist(name_):
z = (.5*mc.envelope_gabor(fx, fy, ft, sf_0=0.2, V_X=-1.5)
+ .1*mc.envelope_gabor(fx, fy, ft, sf_0=0.4, V_X=.5)#, theta=numpy.pi/2.)
)
mc.figures(z, name_)
name = 'two_bands'
name_ = mc.figpath + name
if mc.anim_exist(name_):
# and now selecting blobs:
# one band
one = mc.envelope_gabor(fx, fy, ft, B_theta=10.)
# a second band
two = mc.envelope_gabor(fx, fy, ft, sf_0=.9, B_theta=10.)
mc.figures(one + two, name_)
# explore parameters
for sf_0 in [0.0, 0.1 , 0.2, 0.3, 0.8, 0.9]:
name_ = mc.figpath + name + '-sf_0' + str(sf_0).replace('.', '_')
Testing differently colored noises.
"""
try:
if mc.notebook: print('we are in the notebook')
except:
import os
import MotionClouds as mc
import numpy as np
name = 'color'
fx, fy, ft = mc.get_grids(mc.N_X, mc.N_Y, mc.N_frame)
z = mc.envelope_color(fx, fy, ft)
mc.figures(z, name)
# explore parameters
for alpha in [0.0, 0.5, 1.0, 1.5, 2.0]:
# resp. white(0), pink(1), red(2) or brownian noise (see http://en.wikipedia.org/wiki/1/f_noise
name_ = name + '-alpha-' + str(alpha).replace('.', '_')
z = mc.envelope_color(fx, fy, ft, alpha)
mc.figures(z, name_)
for ft_0 in [0.125, 0.25, 0.5, 1., 2., 4., np.inf]:# time space scaling
name_ = name + '-ft_0-' + str(ft_0).replace('.', '_')
z = mc.envelope_color(fx, fy, ft, ft_0=ft_0)
mc.figures(z, name_)
for contrast in [0.1, 0.25, 0.5, 0.75, 1.0, 2.0]:
name_ = name + '-contrast-' + str(contrast).replace('.', '_')
B_sf = .3
B_theta = np.pi/32
# show example
table = """
#acl LaurentPerrinet,LaurentPerrinetGroup:read,write,delete,revert All:read
#format wiki
-----
= SlippingClouds: MotionClouds for exploring the aperture problem =
"""
theta1, theta2 = 0., np.pi/2.
diag = mc.envelope_gabor(fx, fy, ft, theta=theta2, V_X=np.cos(theta1), V_Y=np.sin(theta1), B_sf=B_sf, B_theta=B_theta)
name_ = name + '_iso'
mc.figures(diag, name_, vext=vext, seed=12234565)
table += '||{{attachment:' + name_ + '.png||width=100%}}||{{attachment:' + name_ + '_cube.png||width=100%}}||{{attachment:' + name_ + '.gif||width=100%}}||\n'
theta1, theta2 = 0., np.pi/4.
diag = mc.envelope_gabor(fx, fy, ft, theta=theta2, V_X=np.cos(theta1), V_Y=np.sin(theta1), B_sf=B_sf, B_theta=B_theta)
name_ = name + '_diag'
mc.figures(diag, name_, vext=vext, seed=12234565)
table += '||{{attachment:' + name_ + '.png||width=100%}}||{{attachment:' + name_ + '_cube.png||width=100%}}||{{attachment:' + name_ + '.gif||width=100%}}||\n'
theta1, theta2 = 0., np.pi/2.
diag = mc.envelope_gabor(fx, fy, ft, theta=theta2, V_X=np.cos(theta1), V_Y=np.sin(theta1), B_sf=B_sf, B_theta=B_theta)
name_ = name + '_contra'
mc.figures(diag, name_, vext=vext, seed=12234565)
table += '||<width="33%">{{attachment:' + name_ + '.png||width=100%}}||<width="33%">{{attachment:' + name_ + '_cube.png||width=100%}}||<width="33%">{{attachment:' + name_ + '.gif||width=100%}}||\n'
table += '|||||| This figure shows how one can create !MotionCloud stimuli that have specific direction and orientation which are not necessarily perpendicular, components "slipping" relative to the motion. We generate !MotionClouds components with a strong selectivity toward one orientation. We show in different lines of this table respectively: Top) orientation perpendicular to orientation as in the standard case with a line, Middle) a 45° difference between both, Bottom) orientation and direction are parallel. We created the aperture problem without any aperture! This can be shown by looking at envelopes in the Fourier space. To best infer motion, you would look fro the best speed plane that would go through each envelope. If these envelopes are rather tight, there are many different speed planes that can go through this envelope: motion is ambiguous. <<BR>> Columns represent isometric projections of a cube. The left column displays iso-surfaces of the spectral envelope by displaying enclosing volumes at 5 different energy values with respect to the peak amplitude of the Fourier spectrum. The middle column shows an isometric view of the faces of the movie cube. The first frame of the movie lies on the x-y plane, the x-t plane lies on the top face and motion direction is seen as diagonal lines on this face (vertical motion is similarly see in the y-t face). The third column displays the actual movie as an animation. ||\n'
