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%load_ext autoreload
%autoreload 2
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import matplotlib
matplotlib.use('nbagg')
%matplotlib inline
matplotlib.rcParams['figure.max_open_warning'] = 400
%matplotlib inline
%config InlineBackend.figure_format='retina'
import matplotlib.pyplot as plt
#%config InlineBackend.figure_format = 'svg'
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name = 'waves'
vext = '.mp4'
import os
import numpy as np
import MotionClouds as mc
mc.N_X, mc.N_Y, mc.N_frame = 128, 32, 512
fx, fy, ft = mc.get_grids(mc.N_X, mc.N_Y, mc.N_frame)
theta, B_theta, B_wave = 0., np.pi/8., .5
#alpha, sf_0, B_sf, B_V = 2., .25, .3, 2.
alpha, sf_0, B_sf, B_V = 2., .2, .1, 3.
seed = 1234565
#V_X, V_Y, g = .5, 0., .1
V_X, V_Y, g = .5, 0., 2
loggabor=True
B_v = .025
def envelope_gravity(fx, fy, ft, B_wave, g=.1):
"""
Gravitational envelope:
selects the plane corresponding to the speed (V_X, V_Y) with some thickness B_V
"""
k = fx*V_X+fy*V_Y
env = np.exp(-.5*(((ft/.5)**2-g*np.sqrt(((k/.5)**2)))**2/(B_wave*mc.frequency_radius(fx, fy, ft, ft_0=np.inf))**2))
env *= (ft*k) < 0
return env
def envelope_gabor_wave(fx, fy, ft, B_wave, V_X=mc.V_X, V_Y=mc.V_Y,
B_V=mc.B_V, B_v=1., sf_0=mc.sf_0, B_sf=mc.B_sf, loggabor=mc.loggabor,
theta=mc.theta, B_theta=mc.B_theta, alpha=mc.alpha):
"""
Returns the Motion Cloud kernel
"""
envelope = mc.envelope_gabor(fx, fy, ft, V_X=V_X, V_Y=V_Y,
B_V=B_V, sf_0=sf_0, B_sf=B_sf, loggabor=loggabor,
theta=theta, B_theta=B_theta, alpha=alpha)
envelope *= envelope_gravity(fx, fy, ft, B_wave=B_wave)
return envelope
name_ = name + '_low'
mc_wave = envelope_gabor_wave(fx, fy, ft, V_X=1., V_Y=0., B_wave=B_v, B_V=B_V, theta=theta, B_theta=B_theta, sf_0=sf_0, B_sf=B_sf, alpha=alpha)
mc_wave = mc.envelope_gabor(fx, fy, ft, V_X=1., V_Y=0., B_V=B_V, theta=theta, B_theta=B_theta, sf_0=sf_0, B_sf=B_sf, alpha=alpha)
mc.figures(mc_wave, name_, vext=vext, seed=seed)
mc.in_show_video(name_)
Saving the corrresponding cloud as a nd.array:
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vague_dense = mc.rectif(mc.random_cloud(mc_wave), contrast=1)
print(vague_dense.shape)
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#mc_wave = envelope_gabor_wave(fx, fy, ft, V_X, V_Y, B_V, B_wave, sf_0, B_sf, theta, B_theta, alpha, g)
mc.figures(mc_wave, 'waves_impulse', seed=seed, impulse=True)
mc.in_show_video('waves_impulse')
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vague_solo = mc.rectif(mc.random_cloud(mc_wave, seed=seed, impulse=True), contrast=1)
print(vague_solo.shape)
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def vague_animate(z, x_offset=0, y_offset=0, N_lame = 25, t_offset=0, N_steps = 512):
import matplotlib.pyplot as plt
import matplotlib.animation as animation
from IPython.display import HTML
fig, ax = plt.subplots(figsize=(15, 3))
x = np.arange(0, N_lame) # x-array
def vague(i):
return z[x_offset:(x_offset+N_lame), y_offset, t_offset+i]
def animate(i):
line.set_ydata(vague(i)) # update the data
return line,
#Init only required for blitting to give a clean slate.
def init():
line.set_ydata(np.ma.array(x, mask=True))
return line,
line, = ax.plot(x, vague(0))
ax.set_xlim([0, N_lame-1])
ax.set_ylim([0, 1])
anim = animation.FuncAnimation(fig, animate, np.arange(1, N_steps), init_func=init,
interval=25, blit=True)
return HTML(anim.to_html5_video())
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vague_animate(vague_dense)
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vague_animate(vague_solo, x_offset=vague_solo.shape[0]//2-25//2, y_offset=vague_solo.shape[1]//2, t_offset=0, N_steps = vague_solo.shape[-1])
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In [10]:
vague_animate(vague_solo, x_offset=vague_solo.shape[0]//2-25//2, y_offset=vague_solo.shape[1]//2, t_offset=vague_solo.shape[-1]//4, N_steps=vague_solo.shape[-1]//2)
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In [11]:
vague_animate(vague_solo, x_offset=vague_solo.shape[0]//2-25//2, y_offset=vague_solo.shape[1]//2,
t_offset=vague_solo.shape[-1]*3//8, N_steps=vague_solo.shape[-1]//4)
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%%writefile ../scenario_line_vague.py
#!/usr/bin/env python
# -*- coding: utf8 -*-
import elasticite as el
import numpy as np
def make_vague(impulse=False):
name = 'waves'
import os
import numpy as np
import MotionClouds as mc
mc.N_X, mc.N_Y, mc.N_frame = 128, 32, 512
fx, fy, ft = mc.get_grids(mc.N_X, mc.N_Y, mc.N_frame)
theta, B_theta, B_wave = 0., np.pi/8., .1
alpha, sf_0, B_sf, B_V = 2., .25, .3, 2.
alpha, sf_0, B_sf, B_V = 1., .1, .3, 2.
seed = 1234565
V_X, V_Y, g = .5, 0., .1
V_X, V_Y, g = .5, 0., 2
loggabor=True
B_v = .025
def envelope_gravity(fx, fy, ft, B_wave, g=.1):
"""
Gravitational envelope:
selects the plane corresponding to the speed (V_X, V_Y) with some thickness B_V
"""
k = fx*V_X+fy*V_Y
env = np.exp(-.5*(((ft/.5)**2-g*np.sqrt(((k/.5)**2)))**2/(B_wave*mc.frequency_radius(fx, fy, ft, ft_0=np.inf))**2))
env *= (ft*k) < 0
return env
def envelope_gabor_wave(fx, fy, ft, B_wave, V_X=mc.V_X, V_Y=mc.V_Y,
B_V=mc.B_V, B_v=1., sf_0=mc.sf_0, B_sf=mc.B_sf, loggabor=mc.loggabor,
theta=mc.theta, B_theta=mc.B_theta, alpha=mc.alpha):
"""
Returns the Motion Cloud kernel
"""
envelope = mc.envelope_gabor(fx, fy, ft, V_X=V_X, V_Y=V_Y,
B_V=B_V, sf_0=sf_0, B_sf=B_sf, loggabor=loggabor,
theta=theta, B_theta=B_theta, alpha=alpha)
envelope *= envelope_gravity(fx, fy, ft, B_wave=B_wave)
return envelope
B_v_low, B_v_high = .025, .1
mc_vague = envelope_gabor_wave(fx, fy, ft, V_X=1., V_Y=0., B_wave=B_v_low, B_V=B_V, theta=theta, B_theta=B_theta, sf_0=sf_0, B_sf=B_sf, alpha=alpha)
return mc.rectif(mc.random_cloud(mc_vague, seed=seed, impulse=impulse))
class EdgeGrid(el.EdgeGrid):
def __init__(self, vague, x_offset=0, y_offset=0, t_offset=0, N_steps = 256, damp_tau=5., **kwargs):
#super(el.EdgeGrid.__init__(self))
#super(el.EdgeGrid, self).__init__(**kwargs)
el.EdgeGrid.__init__(self, **kwargs)
#print (self.verb, kwargs)
self.vague = vague
self.x_offset = x_offset
self.y_offset = y_offset
self.t_offset = t_offset
self.N_steps = N_steps
#print(self.x_offset, self.y_offset, self.t_offset)
#print(self.z.shape)
self.damp_tau = damp_tau
def update(self):
if self.structure: N_lame = self.N_lame-self.struct_N
else: N_lame = self.N_lame
damp = lambda t: 1. - np.exp(-np.abs(np.mod(t+self.period/2, self.period)-self.period/2)/self.damp_tau)
N_periods = 1
i = np.mod(np.int(self.t/self.period * self.vague.shape[2] / N_periods), self.vague.shape[2])
surface = np.zeros_like(self.lames[2, :N_lame])
#for k, amp in zip([-2, -1, 0, 1, 2], [.125, .25, .5, .25, .125]):
# surface += amp * self.vague[self.x_offset:(self.x_offset+N_lame), self.y_offset, self.t_offset+i+k]
surface = self.vague[self.x_offset:(self.x_offset+N_lame), self.y_offset, self.t_offset+i]
surface = np.convolve(surface, np.arange(5), mode='same')
dsurface = np.gradient(surface)
dsurface *= np.bartlett(N_lame)
#print(dsurface.mean(), dsurface.max(), damp(self.t))
dsurface /= np.abs(dsurface).max()
dsurface *= np.tan(np.pi/32) # maximum angle achieved
self.lames[2, :N_lame] = np.arctan(dsurface)*damp(self.t)
if __name__ == "__main__":
import sys
if len(sys.argv)>1: mode = sys.argv[1]
else: mode = 'both'
vague_dense = make_vague(impulse=False)
period = 512./30
e = EdgeGrid(N_lame=25, grid_type='line', mode=mode,
verb=False, period=period, filename='mat/line_vague_dense.npy',
vague = vague_dense,
x_offset=0, y_offset=0, t_offset=0, N_steps=512)
# running the code
el.main(e)
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%cd ..
!rm mat/line_vague_dense.npy
%run scenario_line_vague.py writer
%cd posts
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z = np.load('../mat/line_vague_dense.npy')
print(z.shape)
fig, ax = plt.subplots(figsize=(15, 3))
#_ = ax.plot(z[:, 0])
_ = ax.plot(z[:, 0], z[:, 1:])
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%%writefile ../scenario_line_vague_solo.py
#!/usr/bin/env python
# -*- coding: utf8 -*-
import elasticite as el
import numpy as np
from scenario_line_vague import make_vague, EdgeGrid
if __name__ == "__main__":
import sys
if len(sys.argv)>1: mode = sys.argv[1]
else: mode = 'both'
period = 512./30
vague_solo = make_vague(impulse=True)
e_solo = EdgeGrid(N_lame=25, grid_type='line', mode=mode,
verb=False, period=period, filename='mat/line_vague_solo.npy',
vague = vague_solo,
x_offset=vague_solo.shape[0]//2-25//2, y_offset=vague_solo.shape[1]//2,
t_offset=0, N_steps=512)#t_offset=vague_solo.shape[-1]*3//8, N_steps=vague_solo.shape[-1]//4)
# running the code
el.main(e_solo)
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%cd ..
%run scenario_line_vague_solo.py writer
%cd posts
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z = np.load('../mat/line_vague_solo.npy')
fig, ax = plt.subplots(figsize=(15, 3))
#_ = ax.plot(z[:, 0])
_ = ax.plot(z[:, 0], z[:, 1:])
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!git s
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!git commit -am' scenario vague '
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! git push