SYMBOL INDEX (76 symbols across 12 files)

FILE: breast-cancer/dataplumbing.py
  function load_cdr3s (line 19) | def load_cdr3s(path_tsv, min_length=4, max_length=32, version='v2'):
  function trim_cdr3s (line 44) | def trim_cdr3s(receptors, trim_front=0, trim_rear=0):
  function cdr3s_to_kmers (line 57) | def cdr3s_to_kmers(cdr3s, kmer_size):
  function cdr3s_to_motifs (line 69) | def cdr3s_to_motifs(cdr3s, window_size, motif_size):
  function flatten_sample (line 90) | def flatten_sample(sequences):
  function normalize_sample (line 93) | def normalize_sample(sequences):
  function merge_samples (line 102) | def merge_samples(samples):
  function debug_insert_sequence (line 112) | def debug_insert_sequence(receptors, sequence, count):

FILE: breast-cancer/dataset.py
  function load_aminoacid_embedding_dict (line 19) | def load_aminoacid_embedding_dict(path_embedding):
  function assemble_samples (line 39) | def assemble_samples(cases, controls, aminoacids_dict):
  function split_samples (line 114) | def split_samples(samples, holdouts):
  function weight_samples (line 124) | def weight_samples(samples):
  function normalize_samples (line 139) | def normalize_samples(samples_train, samples_holdout):
  function debug_permute_labels (line 169) | def debug_permute_labels(samples):

FILE: breast-cancer/train_val.py
  function init_weights (line 122) | def init_weights():
  class MaxSnippetModel (line 133) | class MaxSnippetModel(torch.nn.Module):
    method __init__ (line 134) | def __init__(self):
    method forward (line 139) | def forward(self, x):
  function accuracy (line 168) | def accuracy(ls_block, ys_block):  # The binary accuracy is calculated s...

FILE: cervical-cancer/dataplumbing.py
  function load_cdr3s (line 19) | def load_cdr3s(path_tsv, min_length=4, max_length=32, version='v2'):
  function trim_cdr3s (line 44) | def trim_cdr3s(receptors, trim_front=0, trim_rear=0):
  function cdr3s_to_kmers (line 57) | def cdr3s_to_kmers(cdr3s, kmer_size):
  function cdr3s_to_motifs (line 69) | def cdr3s_to_motifs(cdr3s, window_size, motif_size):
  function flatten_sample (line 90) | def flatten_sample(sequences):
  function normalize_sample (line 93) | def normalize_sample(sequences):
  function merge_samples (line 102) | def merge_samples(samples):
  function debug_insert_sequence (line 112) | def debug_insert_sequence(receptors, sequence, count):

FILE: cervical-cancer/dataset.py
  function load_aminoacid_embedding_dict (line 19) | def load_aminoacid_embedding_dict(path_embedding):
  function assemble_samples (line 39) | def assemble_samples(cases, controls, aminoacids_dict):
  function split_samples (line 114) | def split_samples(samples, holdouts):
  function weight_samples (line 124) | def weight_samples(samples):
  function normalize_samples (line 139) | def normalize_samples(samples_train, samples_holdout):
  function debug_permute_labels (line 169) | def debug_permute_labels(samples):

FILE: cervical-cancer/train_val.py
  function init_weights (line 151) | def init_weights():
  class MaxSnippetModel (line 162) | class MaxSnippetModel(torch.nn.Module):
    method __init__ (line 163) | def __init__(self):
    method forward (line 168) | def forward(self, x):
  function accuracy (line 197) | def accuracy(ls_block, ys_block):  # The binary accuracy is calculated s...

FILE: colorectal-cancer/dataplumbing.py
  function load_cdr3s (line 19) | def load_cdr3s(path_tsv, min_length=4, max_length=32, version='v2'):
  function trim_cdr3s (line 44) | def trim_cdr3s(receptors, trim_front=0, trim_rear=0):
  function cdr3s_to_kmers (line 57) | def cdr3s_to_kmers(cdr3s, kmer_size):
  function cdr3s_to_motifs (line 69) | def cdr3s_to_motifs(cdr3s, window_size, motif_size):
  function flatten_sample (line 90) | def flatten_sample(sequences):
  function normalize_sample (line 93) | def normalize_sample(sequences):
  function merge_samples (line 102) | def merge_samples(samples):
  function debug_insert_sequence (line 112) | def debug_insert_sequence(receptors, sequence, count):

FILE: colorectal-cancer/dataset.py
  function load_aminoacid_embedding_dict (line 19) | def load_aminoacid_embedding_dict(path_embedding):
  function assemble_samples (line 39) | def assemble_samples(cases, controls, aminoacids_dict):
  function split_samples (line 114) | def split_samples(samples, holdouts):
  function weight_samples (line 124) | def weight_samples(samples):
  function normalize_samples (line 139) | def normalize_samples(samples_train, samples_holdout):
  function debug_permute_labels (line 169) | def debug_permute_labels(samples):

FILE: colorectal-cancer/train_val.py
  function init_weights (line 123) | def init_weights():
  class MaxSnippetModel (line 134) | class MaxSnippetModel(torch.nn.Module):
    method __init__ (line 135) | def __init__(self):
    method forward (line 140) | def forward(self, x):
  function accuracy (line 169) | def accuracy(ls_block, ys_block):  # The binary accuracy is calculated s...

FILE: ovarian-cancer/dataplumbing.py
  function load_cdr3s (line 19) | def load_cdr3s(path_tsv, min_length=4, max_length=32, version='v2'):
  function trim_cdr3s (line 44) | def trim_cdr3s(receptors, trim_front=0, trim_rear=0):
  function cdr3s_to_kmers (line 57) | def cdr3s_to_kmers(cdr3s, kmer_size):
  function cdr3s_to_motifs (line 69) | def cdr3s_to_motifs(cdr3s, window_size, motif_size):
  function flatten_sample (line 90) | def flatten_sample(sequences):
  function normalize_sample (line 93) | def normalize_sample(sequences):
  function merge_samples (line 102) | def merge_samples(samples):
  function debug_insert_sequence (line 112) | def debug_insert_sequence(receptors, sequence, count):

FILE: ovarian-cancer/dataset.py
  function load_aminoacid_embedding_dict (line 19) | def load_aminoacid_embedding_dict(path_embedding):
  function assemble_samples (line 39) | def assemble_samples(cases, controls, aminoacids_dict):
  function split_samples (line 114) | def split_samples(samples, holdouts):
  function weight_samples (line 124) | def weight_samples(samples):
  function normalize_samples (line 139) | def normalize_samples(samples_train, samples_holdout):
  function debug_permute_labels (line 169) | def debug_permute_labels(samples):

FILE: ovarian-cancer/train_val.py
  function init_weights (line 125) | def init_weights():
  class MaxSnippetModel (line 136) | class MaxSnippetModel(torch.nn.Module):
    method __init__ (line 137) | def __init__(self):
    method forward (line 142) | def forward(self, x):
  function accuracy (line 171) | def accuracy(ls_block, ys_block):  # The binary accuracy is calculated s...