def __init__(self, path, num_neighbours=20, n_jobs=1, cache=True):
ProteinNetKNN.__init__(self,
path,
num_neighbours=num_neighbours,
n_jobs=n_jobs,
cache=cache)
self.backrub = Backrub(n_moves=0)
self.ors = torch.tensor(orientation(self.ters[1].numpy() /
100).transpose(2, 0, 1),
dtype=torch.float)
def __init__(self, path, num_neighbours=20, n_jobs=1, N=64, cache=True):
ProteinNetKNN.__init__(self,
path,
num_neighbours=num_neighbours,
n_jobs=n_jobs,
cache=cache)
self.backrub = Backrub(n_moves=0)
self.ors = torch.tensor(orientation(self.ters[1].numpy() /
100).transpose(2, 0, 1),
dtype=torch.float)
self.N = N
self.valid_indices = [
index for index in range(len(self.index) - 1)
if self.index[index + 1] - self.index[index] >= N
]
def __init__(self, path, num_neighbours=20, n_jobs=1, n_backrub=10, N=200,
phi=0.2 * np.pi, psi=0.2 * np.pi, tau=0.2 * np.pi, cache=True,
pass_mask=False):
super(FoldNet, self).__init__(
path,
num_neighbours=num_neighbours,
n_jobs=n_jobs, cache=cache
)
self.pass_mask = pass_mask
self.N = N
self.backrub = Backrub(n_moves=n_backrub, phi=phi, psi=psi, tau=tau)
self.ors = torch.tensor(
orientation(self.ters[1].numpy() / 100).transpose(2, 0, 1),
dtype=torch.float
)
def __init__(self,
path,
radius=8,
num_neighbours=15,
n_jobs=1,
cache=True):
ProteinNetKNN.__init__(self,
path,
num_neighbours=num_neighbours,
n_jobs=n_jobs,
cache=cache)
self.radius = radius
self.backrub = Backrub(n_moves=0) #10, phi=0.3, psi=0.3, tau=0.3)
self.ors = torch.tensor(orientation(self.ters[1].numpy() /
100).transpose(2, 0, 1),
dtype=torch.float)
