SYMBOL INDEX (118 symbols across 11 files)

FILE: benchmark_layers.py
  function ranges_slices (line 15) | def ranges_slices(batch):
  function diagonal_ranges (line 28) | def diagonal_ranges(batch_x=None, batch_y=None):
  function keops_knn (line 41) | def keops_knn(
  function knn_graph (line 74) | def knn_graph(
  class MyDynamicEdgeConv (line 103) | class MyDynamicEdgeConv(EdgeConv):
    method __init__ (line 106) | def __init__(self, nn, k, aggr="max", **kwargs):
    method forward (line 110) | def forward(self, x, batch=None):
    method __repr__ (line 117) | def __repr__(self):
  class MyXConv (line 121) | class MyXConv(torch.nn.Module):
    method __init__ (line 122) | def __init__(
    method reset_parameters (line 185) | def reset_parameters(self):
    method forward (line 190) | def forward(self, x, source, batch_source, target, batch_target):
    method __repr__ (line 255) | def __repr__(self):

FILE: benchmark_models.py
  function MLP (line 36) | def MLP(channels, batch_norm=True):
  class DGCNN_seg (line 50) | class DGCNN_seg(torch.nn.Module):
    method __init__ (line 51) | def __init__(
    method forward (line 90) | def forward(self, positions, features, batch_indices):
  class SAModule (line 124) | class SAModule(torch.nn.Module):
    method __init__ (line 127) | def __init__(self, ratio, r, nn, max_num_neighbors=64):
    method forward (line 134) | def forward(self, x, pos, batch):
  class GlobalSAModule (line 158) | class GlobalSAModule(torch.nn.Module):
    method __init__ (line 159) | def __init__(self, nn):
    method forward (line 163) | def forward(self, x, pos, batch):
  class FPModule (line 171) | class FPModule(torch.nn.Module):
    method __init__ (line 172) | def __init__(self, k, nn):
    method forward (line 177) | def forward(self, x, pos, batch, x_skip, pos_skip, batch_skip):
  class PointNet2_seg (line 185) | class PointNet2_seg(torch.nn.Module):
    method __init__ (line 186) | def __init__(self, args, in_channels, out_channels):
    method forward (line 218) | def forward(self, positions, features, batch_indices):
  class dMaSIFConv_seg (line 233) | class dMaSIFConv_seg(torch.nn.Module):
    method __init__ (line 234) | def __init__(self, args, in_channels, out_channels, n_layers, radius=9...
    method forward (line 260) | def forward(self, features):
    method load_mesh (line 272) | def load_mesh(self, xyz, triangles=None, normals=None, weights=None, b...

FILE: data.py
  function numpy (line 18) | def numpy(x):
  function iface_valid_filter (line 22) | def iface_valid_filter(protein_pair):
  class RandomRotationPairAtoms (line 39) | class RandomRotationPairAtoms(object):
    method __call__ (line 42) | def __call__(self, data):
    method __repr__ (line 58) | def __repr__(self):
  class CenterPairAtoms (line 62) | class CenterPairAtoms(object):
    method __call__ (line 65) | def __call__(self, data):
    method __repr__ (line 79) | def __repr__(self):
  class NormalizeChemFeatures (line 83) | class NormalizeChemFeatures(object):
    method __call__ (line 86) | def __call__(self, data):
    method __repr__ (line 118) | def __repr__(self):
  function load_protein_npy (line 122) | def load_protein_npy(pdb_id, data_dir, center=False, single_pdb=False):
  class PairData (line 173) | class PairData(Data):
    method __init__ (line 174) | def __init__(
    method __inc__ (line 220) | def __inc__(self, key, value):
    method __cat_dim__ (line 228) | def __cat_dim__(self, key, value):
  function load_protein_pair (line 235) | def load_protein_pair(pdb_id, data_dir,single_pdb=False):
  class ProteinPairsSurfaces (line 271) | class ProteinPairsSurfaces(InMemoryDataset):
    method __init__ (line 274) | def __init__(self, root, ppi=False, train=True, transform=None, pre_tr...
    method raw_file_names (line 281) | def raw_file_names(self):
    method processed_file_names (line 285) | def processed_file_names(self):
    method download (line 302) | def download(self):
    method process (line 316) | def process(self):

FILE: data_analysis/analyse_descriptors_para.py
  function analyse_pdb (line 29) | def analyse_pdb(pdb_id,D):

FILE: data_iteration.py
  function process_single (line 16) | def process_single(protein_pair, chain_idx=1):
  function save_protein_batch_single (line 76) | def save_protein_batch_single(protein_pair_id, P, save_path, pdb_idx):
  function project_iface_labels (line 101) | def project_iface_labels(P, threshold=2.0):
  function process (line 123) | def process(args, protein_pair, net):
  function generate_matchinglabels (line 140) | def generate_matchinglabels(args, P1, P2):
  function compute_loss (line 157) | def compute_loss(args, P1, P2, n_points_sample=16):
  function extract_single (line 218) | def extract_single(P_batch, number):
  function iterate (line 244) | def iterate(
  function iterate_surface_precompute (line 423) | def iterate_surface_precompute(dataset, net, args):

FILE: data_preprocessing/convert_pdb2npy.py
  function load_structure_np (line 9) | def load_structure_np(fname, center):
  function convert_pdbs (line 34) | def convert_pdbs(pdb_dir, npy_dir):

FILE: data_preprocessing/convert_ply2npy.py
  function load_surface_np (line 7) | def load_surface_np(fname, center):
  function convert_plys (line 42) | def convert_plys(ply_dir, npy_dir):

FILE: data_preprocessing/download_pdb.py
  class NotDisordered (line 28) | class NotDisordered(Select):
    method accept_atom (line 29) | def accept_atom(self, atom):
  function find_modified_amino_acids (line 33) | def find_modified_amino_acids(path):
  function extractPDB (line 48) | def extractPDB(
  function protonate (line 86) | def protonate(in_pdb_file, out_pdb_file):
  function get_single (line 108) | def get_single(pdb_id: str,chains: list):

FILE: geometry_processing.py
  function save_vtk (line 21) | def save_vtk(
  function subsample (line 87) | def subsample(x, batch=None, scale=1.0):
  function soft_distances (line 136) | def soft_distances(x, y, batch_x, batch_y, smoothness=0.01, atomtypes=No...
  function atoms_to_points_normals (line 201) | def atoms_to_points_normals(
  function mesh_normals_areas (line 328) | def mesh_normals_areas(vertices, triangles=None, scale=[1.0], batch=None...
  function tangent_vectors (line 418) | def tangent_vectors(normals):
  function curvatures (line 444) | def curvatures(
  class ContiguousBackward (line 557) | class ContiguousBackward(torch.autograd.Function):
    method forward (line 563) | def forward(ctx, input):
    method backward (line 567) | def backward(ctx, grad_output):
  class dMaSIFConv (line 570) | class dMaSIFConv(nn.Module):
    method __init__ (line 571) | def __init__(
    method forward (line 700) | def forward(self, points, nuv, features, ranges=None):

FILE: helper.py
  function ranges_slices (line 15) | def ranges_slices(batch):
  function diagonal_ranges (line 28) | def diagonal_ranges(batch_x=None, batch_y=None):
  function soft_dimension (line 42) | def soft_dimension(features):

FILE: model.py
  function knn_atoms (line 19) | def knn_atoms(x, y, x_batch, y_batch, k):
  function get_atom_features (line 37) | def get_atom_features(x, y, x_batch, y_batch, y_atomtype, k=16):
  class Atom_embedding (line 53) | class Atom_embedding(nn.Module):
    method __init__ (line 54) | def __init__(self, args):
    method forward (line 65) | def forward(self, x, y, y_atomtypes, x_batch, y_batch):
  class AtomNet (line 84) | class AtomNet(nn.Module):
    method __init__ (line 85) | def __init__(self, args):
    method forward (line 99) | def forward(self, xyz, atom_xyz, atomtypes, batch, atom_batch):
  class Atom_embedding_MP (line 104) | class Atom_embedding_MP(nn.Module):
    method __init__ (line 105) | def __init__(self, args):
    method forward (line 125) | def forward(self, x, y, y_atomtypes, x_batch, y_batch):
  class Atom_Atom_embedding_MP (line 145) | class Atom_Atom_embedding_MP(nn.Module):
    method __init__ (line 146) | def __init__(self, args):
    method forward (line 168) | def forward(self, x, y, y_atomtypes, x_batch, y_batch):
  class AtomNet_MP (line 191) | class AtomNet_MP(nn.Module):
    method __init__ (line 192) | def __init__(self, args):
    method forward (line 205) | def forward(self, xyz, atom_xyz, atomtypes, batch, atom_batch):
  function combine_pair (line 215) | def combine_pair(P1, P2):
  function split_pair (line 235) | def split_pair(P1P2):
  function project_iface_labels (line 270) | def project_iface_labels(P, threshold=2.0):
  class dMaSIF (line 289) | class dMaSIF(nn.Module):
    method __init__ (line 290) | def __init__(self, args):
    method features (line 358) | def features(self, P, i=1):
    method embed (line 394) | def embed(self, P):
    method preprocess_surface (line 446) | def preprocess_surface(self, P):
    method forward (line 458) | def forward(self, P1, P2=None):