def load_files_and_tracks(path_name):
connect_to_db()
print("Directory: ", end="")
path = str(input())
try:
files = get_files_in_path(path_name=path_name)
for f in files:
try:
file = File()
print('Processing file:{}'.format(f))
file.parse_filename(filename=f)
file.add_raw_file(filename=f)
file.save()
tracks = file.load_local_file(filename=f)
for track in tracks:
track.save()
except AssertionError:
print("Unable to load file:{}".format(f))
finally:
print("File loaded")
except FileNotFoundError:
print("Invalid directory")
disconnect_to_db()
from Networks.diffusion_coefficient_network import DiffusionCoefficientNetworkModel
from Tools.db_connection import disconnect_to_db, connect_to_db
import matplotlib.pyplot as plt
import numpy as np
if __name__ == "__main__":
connect_to_db()
lower_limit = 15
upper_limit = 1500
nets = DiffusionCoefficientNetworkModel.objects(track_length__in=range(
lower_limit, upper_limit),
hiperparams_opt=False)
count = 0
for net in nets:
print(net.id)
epochs = np.arange(1, len(net.history['mse']) + 1)
plt.plot(epochs, net.history['mse'])
if net.history['mse'][-1] >= 0.006:
count += 1
print('Must be retrained:{}'.format(count))
plt.xlabel('Epochs')
plt.ylabel('MSE')
plt.show()
for net in nets:
if net.history['mse'][-1] >= 0.006:
net.net_params['lr'] = 6e-8
# net.net_params['lr'] = 5e-7
net.train_network()