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)