def no_test_raw_collate():
import matplotlib.pyplot as plt
from test_utils import plot, plot_spec
data_id_path = "data_dir/"
data_path = "data_dir/"
print(hp.seq_len)
with open('{}dataset_ids.pkl'.format(data_id_path), 'rb') as f:
dataset_ids = pickle.load(f)
dataset = AudiobookDataset(data_path)
print(len(dataset))
data_loader = DataLoader(dataset, collate_fn=raw_collate, batch_size=32,
num_workers=0, shuffle=True)
x, m, y = next(iter(data_loader))
print(x.shape, m.shape, y.shape)
plot(x.numpy()[0])
plot(y.numpy()[0])
plot_spec(m.numpy()[0])
title_dict = {'dist': 'Decoy distance', 'rmsd': 'Decoy RMSD'}
sum_dict = {'percent_improved': 'percentage of improved decoys'}
x_dict = {
'pre_dist_sum': 'Initial Cα distance',
'pre_rmsd_sum': 'Initial RMSD'
}
y_dict = {
'post_dist_sum': 'Cα distance after mover',
'post_rmsd_sum': 'RMSD after mover'
}
#title = title_dict[mid] + ' comparison summarized by ' + sum_dict[summary]
title = ''
plt, fig, ax = plot(data,
groups=groups,
xlabel=x_dict[x],
ylabel=y_dict[y],
title=title,
unitline=unitline,
markersize=5)
def on_pick(event):
if not hasattr(event, 'ind'):
return True
ind = event.ind
#for a, b in enumerate(ind):
data = event.artist.get_offsets()
if event.artist.get_label() == 'constrained':
pick_df = df_cst
else:
pick_df = df_uncst
