def test_parse_links(self):
# Make sure that a validate dataloader is added
batch_size = 1
self.links_file = get_data_path('links.txt')
self.fasta_file = get_data_path('prots.fa')
res = parse(self.fasta_file, self.links_file,
training_column=4,
batch_size=batch_size,
num_workers=1, arm_the_gpu=False)
self.assertEqual(len(res), 3)
train, test, valid = res
i = 0
for g, p, n in train:
i+= 1
self.assertEqual(len(train), 83)
i = 0
for g, p, n in test:
i+= 1
self.assertEqual(len(test), 12)
# Make sure that a validate dataloader is added
i = 0
for g, p, n in valid:
i+= 1
self.assertEqual(len(valid), 5)
def setUp(self):
self.fasta_file = get_data_path('prots.fa')
self.links_dir = os.path.abspath('data/links_files')
# TODO:
# 1. load dummy model
# 2. fix simple_ppi with dummy model
# Load dummy model
input_dim = len(dictionary)
hidden_size = 10
self.emb_dimension = 3
self.pretrained_model = DummyModel(input_dim, hidden_size)
# freeze the weights of the pre-trained model
for param in self.pretrained_model.parameters():
param.requires_grad = False
self.sampler = NegativeSampler(self.fasta_file)
self.dataloader = InteractionDataDirectory(self.fasta_file,
self.links_dir,
training_column=4)
self.pos_dataloader = [get_data_path('positives.txt')]
self.neg_dataloader = [get_data_path('negatives.txt')]
# setup model.
self.ppi_model = PPIBinder(hidden_size, self.emb_dimension,
self.pretrained_model)
def setUp(self):
self.links_file = get_data_path('links.txt')
self.fasta_file = get_data_path('prots.fa')
self.seqs = list(SeqIO.parse(self.fasta_file, format='fasta'))
links = pd.read_table(self.links_file, header=None)
truncseqs = list(map(clean, self.seqs))
seqids = list(map(lambda x: x.id, truncseqs))
seqdict = dict(zip(seqids, truncseqs))
self.pairs = preprocess(seqdict, links)
def test_parse_negative(self):
batch_size = 1
self.links_file = get_data_path('negative.txt')
self.fasta_file = get_data_path('prots.fa')
res = parse(self.fasta_file, self.links_file,
training_column=4,
batch_size=batch_size,
num_workers=1, arm_the_gpu=False)
self.assertEqual(len(res), 3)
self.assertIsNone(res[0])
self.assertIsNotNone(res[1])
self.assertIsNotNone(res[2])
self.assertEqual(len(res[2]), 2)
def setUp(self):
self.fasta_file = get_data_path('prots.fa')
self.links_file = os.path.abspath('data/links_files')
self.logging1 = 'logging1'
self.logging2 = 'logging2'
self.modelpath = 'model.pkt'
# not ideal :(
# on popeye
self.checkpoint = '/simons/scratch/jmorton/mgt/checkpoints/uniref90'
self.data_dir = '/simons/scratch/jmorton/mgt/data/uniref50'
# on rusty
# self.checkpoint = '/simons/scratch/jmorton/mgt/checkpoints/uniref50'
# self.data_dir = '/simons/scratch/jmorton/mgt/data/uniref50'
self.checkpoint = '/mnt/home/jmorton/research/gert/data/full/uniref50/checkpoints'
self.data_dir = '/mnt/home/jmorton/research/gert/data/full/uniref50/pretrain_data'
def setUp(self):
self.links_file = get_data_path('links.txt')
self.fasta_file = get_data_path('prots.fa')
