def center(self, npoints=all, with_normals=False):
"""Returns center line of the worm
Arguments:
npoints (int or all): number of sample points
Returns:
array (nx2): points along center line
"""
if npoints is all:
points = None
else:
points = np.linspace(0, 1, npoints)
theta = self.theta.get_values(points=points)
return wormgeo.center_from_theta_discrete(theta,
orientation=self.orientation,
xy=self.xy,
length=self.length,
npoints=npoints,
nsamples=all,
resample=False,
smooth=0,
with_normals=with_normals)
def curve(self, mode_amplitudes):
"""Change curvature properties of the worm
Arguments:
mode_amplitudes (number or array): additional power in the first fourier modes of the worms angles
"""
#changes curvature by the mode amplitudes;
#cos = np.cos(self.theta); -> ok to use theta directly
theta, orientation, xy, length = wormgeo.theta_from_center_discrete(self.center);
t = np.fft.rfft(theta);
mode_amplitudes = np.array(mode_amplitudes);
t[:mode_amplitudes.shape[0]] += mode_amplitudes;
theta = np.fft.irfft(t, n = self.npoints-2);
self.center = wormgeo.center_from_theta_discrete(theta, orientation, xy, length);
def center(self, with_normals = False):
"""Returns center line of the worm
Arguments:
with_normals (bool): if true also return normals along center points
Returns:
array (nx2): points along center line
array (nx2): normals along center points
"""
return wormgeo.center_from_theta_discrete(self.theta, orientation = self.orientation,
xy = self.xy, length = self.length,
npoints = all, nsamples = all, resample = False,
smooth = 0, with_normals = with_normals);
def curve(self, mode_amplitudes):
"""Change curvature properties of the worm
Arguments:
mode_amplitudes (number or array): additional power in the first fourier modes of the worms angles
"""
#changes curvature by the mode amplitudes;
#cos = np.cos(self.theta); -> ok to use theta directly
theta, orientation, xy, length = wormgeo.theta_from_center_discrete(
self.center)
t = np.fft.rfft(theta)
mode_amplitudes = np.array(mode_amplitudes)
t[:mode_amplitudes.shape[0]] += mode_amplitudes
theta = np.fft.irfft(t, n=self.npoints - 2)
self.center = wormgeo.center_from_theta_discrete(
theta, orientation, xy, length)
def bend(self, bend, exponent = 4, head = True):
"""Change curvature properties of the worm
Arguments:
bend (number): bending amplitude
exponent (number): expoential modulation of the bending
head (bool): if True bend head side otherwise tail side
"""
#head tail bend profile
theta, orientation, xy, length = wormgeo.theta_from_center_discrete(self.center);
n2 = theta.shape[0]//2;
if head:
theta[:n2-1] += bend * np.exp(-exponent * np.linspace(0,1,n2-1));
else:
theta[-(n2-1):] += bend * np.exp(-exponent * np.linspace(1,0,n2-1));
self.center = wormgeo.center_from_theta_discrete(theta, orientation, xy, length);
def center(self, with_normals=False):
"""Returns center line of the worm
Arguments:
with_normals (bool): if true also return normals along center points
Returns:
array (nx2): points along center line
array (nx2): normals along center points
"""
return wormgeo.center_from_theta_discrete(self.theta,
orientation=self.orientation,
xy=self.xy,
length=self.length,
npoints=all,
nsamples=all,
resample=False,
smooth=0,
with_normals=with_normals)
def center(self, npoints = all, with_normals = False):
"""Returns center line of the worm
Arguments:
npoints (int or all): number of sample points
Returns:
array (nx2): points along center line
"""
if npoints is all:
points = None;
else:
points = np.linspace(0,1,npoints);
theta = self.theta.get_values(points = points);
return wormgeo.center_from_theta_discrete(theta, orientation = self.orientation,
xy = self.xy, length = self.length,
npoints = npoints, nsamples = all, resample = False,
smooth = 0, with_normals = with_normals);
def bend(self, bend, exponent=4, head=True):
"""Change curvature properties of the worm
Arguments:
bend (number): bending amplitude
exponent (number): expoential modulation of the bending
head (bool): if True bend head side otherwise tail side
"""
#head tail bend profile
theta, orientation, xy, length = wormgeo.theta_from_center_discrete(
self.center)
n2 = theta.shape[0] // 2
if head:
theta[:n2 -
1] += bend * np.exp(-exponent * np.linspace(0, 1, n2 - 1))
else:
theta[-(n2 - 1):] += bend * np.exp(
-exponent * np.linspace(1, 0, n2 - 1))
self.center = wormgeo.center_from_theta_discrete(
theta, orientation, xy, length)
#plt.figure(12); plt.clf();
#aplt.plot_pca(theta)
pca = aplt.PCA(theta)
pca_comp = pca.Wt
import worm.model as wm
import worm.geometry as wgeo
w = wm.WormModel(npoints=22)
fig = plt.figure(170)
plt.clf()
for i in range(len(pca_comp)):
tt = pca_comp[i] * 21
cc = wgeo.center_from_theta_discrete(tt, length=95)
dd = np.sum(np.diff(cc, axis=0), axis=0)
oo = np.arctan2(dd[1], dd[0]) + 0 * np.pi
w.center = wgeo.center_from_theta_discrete(tt, length=95, orientation=-oo)
plt.subplot(5, 4, i + 1)
plt.title('PCA %d' % (i + 1))
w.plot(ccolor='b')
plt.axis('equal')
fig.savefig(os.path.join(fig_dir, 'theta_pca_oriented.png'), facecolor='white')
fig = plt.figure(170)
plt.clf()
for i in range(9):
tt = pca_comp[i] * 21
pcas = results.Y;
#%%
#import worm.model as wmod
fig = plt.figure(1); plt.clf();
ax = fig.add_subplot(1,1,1);
ax.set_color_cycle([plt.cm.gray(i) for i in np.linspace(0,1,50)])
k,m = 6,5
for i in range(3000):
#th = pcas[i];# * len(pcas[i]);
th = data_theta[i];
c = wgeo.center_from_theta_discrete(th, length = 120)
#ax = plt.subplot(k,m,i+1);
#c = np.reshape(pcas[i], (2,-1))
plt.plot(*c.T);
plt.xlim(-65,65);
plt.ylim(-65,65);
plt.axis('equal')
cax = plt.gca();
aax = cax.axes
aax.get_xaxis().set_visible(False);
aax.get_yaxis().set_visible(False);
plt.tight_layout()
import worm.model as wm
import worm.geometry as wgeo
w = wm.WormModel(npoints=22)
fig = plt.figure(17)
plt.clf()
for i in range(len(pca_comp)):
tt = pca_comp[i] * 21
tta = tt - np.mean(tt)
if i == 0:
oo = 0.2
elif i == 1:
oo = .9 + np.pi
else:
oo = 0
w.center = wgeo.center_from_theta_discrete(tta, length=95, orientation=oo)
plt.subplot(5, 4, i + 1)
plt.title('PCA %d' % (i + 1))
w.plot()
plt.axis('equal')
fig.savefig(os.path.join(fig_dir, 'theta_pca.png'), facecolor='white')
fig = plt.figure(18)
plt.clf()
for i in range(len(pca_comp)):
tt = pca_comp[i] * 21
tta = tt - np.mean(tt)
plt.subplot(5, 4, i + 1)
plt.plot(tta, linewidth=2, c='r')
plt.title('PCA %d' % (i + 1))
#plt.figure(12); plt.clf();
#aplt.plot_pca(theta)
pca = aplt.PCA(theta)
pca_comp = pca.Wt;
import worm.model as wm
import worm.geometry as wgeo
w = wm.WormModel(npoints = 22)
fig = plt.figure(170); plt.clf();
for i in range(len(pca_comp)):
tt = pca_comp[i] * 21;
cc = wgeo.center_from_theta_discrete(tt, length = 95);
dd = np.sum(np.diff(cc, axis = 0), axis = 0);
oo = np.arctan2(dd[1], dd[0]) + 0* np.pi;
w.center = wgeo.center_from_theta_discrete(tt, length = 95, orientation = -oo);
plt.subplot(5,4,i+1)
plt.title('PCA %d' % (i+1))
w.plot(ccolor='b')
plt.axis('equal')
fig.savefig(os.path.join(fig_dir, 'theta_pca_oriented.png'), facecolor='white')
fig = plt.figure(170); plt.clf();
for i in range(9):
tt = pca_comp[i] * 21;
cc = wgeo.center_from_theta_discrete(tt, length = 95);