def find_engulfing_sphere_radius(x):
if True:
cm = x.mean(0)
d_to_cm = np.linalg.norm(x - cm, axis=0)
return max(d_to_cm) / float(len(x) ** 3)
if False:
from csb.bio.utils import radius_of_gyration
return radius_of_gyration(x) / float(len(x) ** 3)
def report_progress(self, samples):
info = (len(samples['s']), len(samples['X'][-1]),
rmsd(*samples['X'][-2:]), float(samples['s'][-1]),
samples['r_min'][-1], samples['eps'][-1],
self.posteriors['X'].sampler.dt,
np.sum(self.posteriors['X'].likelihood.N < 1.),
radius_of_gyration(samples['X'][-1]))
print GibbsSampler.output.format(*info)
def random_sphere(n_particles, Rg):
"""Generate particles within a sphere such that a desired radius of gyration
is matched.
"""
r = np.random.random(n_particles)**(1/3.)
phi = np.random.uniform(0., 2*np.pi, size=n_particles)
theta = np.arccos(np.random.uniform(-1., 1., size=n_particles))
coords = np.transpose([np.cos(phi) * np.sin(theta) * r,
np.sin(phi) * np.sin(theta) * r,
np.cos(theta) * r])
coords -= coords.mean(0)
coords *= Rg / radius_of_gyration(coords)
return coords
def _single_structure_log_prob(self, structure):
"""
Evaluates log-probability for a single structure
:param structure: coordinates of a single structure
:type structure: :class:`numpy.ndarray`
:returns: log-probability
:rtype: float
"""
X = structure.reshape(-1, 3)
rg = radius_of_gyration(X)
return -0.5 * self['k_rog'].value * (self['rog'].value - rg)**2
def _single_structure_gradient(self, structure):
"""
Evaluates the negative log-probability gradient
for a single structure
:param structure: coordinates of a single structure
:type structure: :class:`numpy.ndarray`
:returns: gradient vector
:rtype: :class:`numpy.ndarray`
"""
X = structure.reshape(-1, 3)
r_gyr = radius_of_gyration(X)
k = self['k_rog'].value
target_rog = self['rog'].value
return -k * (target_rog - r_gyr) * (X -
X.mean(0)).ravel() / r_gyr / len(X)
ax = fig.add_subplot(111)
ax.hist([s.variables['norm'] for s in samples],
bins=int(np.sqrt(len(samples))))
ax.set_xlabel('gamma')
ax.set_yticks([])
fig.tight_layout()
if show_plots:
plt.show()
if not True:
from csb.bio.utils import radius_of_gyration
rgs = map(radius_of_gyration, structures)
true1_rg = radius_of_gyration(true1)
true2_rg = radius_of_gyration(true2)
fig = plt.figure()
ax = fig.add_subplot(111)
h = ax.hist(rgs, bins=int(sqrt(len(rgs))))
ax.plot((true1_rg, true1_rg), (0, max(h[0])), c='r', label=label1)
ax.plot((true2_rg, true2_rg), (0, max(h[0])), c='b', label=label2)
ax.set_xlabel('radius of gyration')
ax.set_ylabel('# structures')
ax.set_yticks([])
ax.legend()
if show_plots:
plt.show()
def testRadiusOfGyration(self):
gyradius = cbu.radius_of_gyration(X4)
s2 = 2.0**0.5
self.assertArrayEqual(gyradius, s2 / 2.0)