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script_generate_data.py
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script_generate_data.py
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import os
import argparse
from data.load_data import load_data
import warnings
warnings.filterwarnings("ignore")
argparser = argparse.ArgumentParser("Training")
argparser.add_argument('--idx', type=int, default=8)
argparser.add_argument('--itermax', type=int, default=2500)
argparser.add_argument('--hashcode', type=str, default='100000')
argparser.add_argument('--graph_scale', type=int, default=10000)
argparser.add_argument('--binx', type=int, default=32)
argparser.add_argument('--biny', type=int, default=40)
argparser.add_argument('--app_name', type=str, default='')
argparser.add_argument('--win_x', type=float, default=32)
argparser.add_argument('--win_y', type=float, default=40)
argparser.add_argument('--win_cap', type=int, default=5)
args = argparser.parse_args()
dataset_names = [
'superblue1',
'superblue2',
'superblue3',
'superblue5',
'superblue6',
'superblue7',
'superblue9',
'superblue11',
'superblue14',
'superblue16',
'superblue19',
]
for dataset_name in dataset_names:
for i in range(0, args.itermax):
if os.path.isfile(f'data/{dataset_name}/iter_{i}_node_label_full_{args.hashcode}_.npy'):
print(f'Loading {dataset_name}:')
load_data(f'data/{dataset_name}', i, args.idx, args.hashcode,
graph_scale=args.graph_scale,
bin_x=args.binx, bin_y=args.biny, force_save=True, use_tqdm=True,
app_name=args.app_name,
win_x=args.win_x, win_y=args.win_y, win_cap=args.win_cap)