def send(self):
data = dict()
for box in self.boxes:
data[box] = self.boxes[box].text()
if send(**data):
for box in self.boxes:
self.boxes[box].clear()
else:
self.show_failure()
def new_epoch(train_loss, train_accuracy, val_loss, val_accuracy, epoch):
#saving the arrays to a dict
plot_value_dict = {
"train_accuracy": list(train_accuracy),
"train_loss": list(train_loss),
"val_accuracy": list(val_accuracy),
"val_loss": list(val_loss),
"epoch": epoch
}
train_accuracy_string = ','.join(map(str, list(train_accuracy)))
train_loss_string = ','.join(map(str, list(train_loss)))
val_accuracy_string = ','.join(map(str, list(val_accuracy)))
val_loss_string = ','.join(map(str, list(val_loss)))
#send metrics to UI for plotting graph
send('{"type":"train_loss", "value" : train_loss_string}')
send('{"type":"val_loss", "value" : val_loss_string}')
send('{"type":"train_acc", "value": train_accuracy_string}')
send('{"type":"val_acc", "value":val_accuracy_string}')
send('{"type":"epoch", "value":str(epoch)}')
file_path = "./Network/plot_values.json"
json.dump(plot_value_dict,
codecs.open(file_path, 'w',
encoding='utf-8')) #saving the arrays in json format
with open('./Network/train_accuracy.npy', 'wb') as f:
np.save(f, train_accuracy)
with open('./Network/train_loss.npy', 'wb') as f:
np.save(f, train_loss)
with open('./Network/val_accuracy.npy', 'wb') as f:
np.save(f, val_accuracy)
with open('./Network/val_loss.npy', 'wb') as f:
np.save(f, val_loss)
def queue(self, data: dict):
send(**data)
def run(self):
send(**self.data)
from data import send
from numpy.random import randint
import time
def getJSON(val1, val2):
return '{' + '"type":' + '"' + val1 + '"' + ',"value":' + '"' + val2 + '"' + '}'
items = [
'{"type":"train_loss", "value":"10,2,3,4"}',
'{"type":"train_acc", "value":"0.87,1,0.99,0.2"}',
'{"type":"val_acc", "value":"1.2,1.67,0.1,-0.2"}',
'{"type":"val_loss", "value":"-.9, 2, 11, 0"}',
]
params = ["train_loss", "val_loss", "train_acc", "val_acc"]
l = [[], [], [], []]
for j in range(10):
for i in range(len(l)):
l[i].append(randint(-10, 100))
# print(getJSON(params[i], ','.join([str(x) for x in l[i]])))
send(getJSON(params[i], ','.join([str(x) for x in l[i]])))
send(getJSON("ETA", str(10 - j)))
send(getJSON("epoch", str(j)))
#!/usr/bin/env python
import data
if __name__ == "__main__":
N = 100000
while True:
points = [(r, x) for r, x in data.generate(N)]
for i in range(100):
data.send(points, N=1000 * len(points))
for idx in range(len(points)):
r, x = points[idx]
for j in range(1000):
x = r * x * (1 - x)
points[idx] = r, x
#!/usr/bin/env python
import data
class Point(object):
def __init__(self, r, x):
self.r = r
self.x = x
def next(self):
self.x = self.r * self.x * (1 - self.x)
return self.r, self.x
if __name__ == "__main__":
N = 100000
while True:
points = [Point(r, x) for r, x in data.generate(N)]
for i in range(10000):
data.send([p.next() for p in points])
#!/usr/bin/env python
import data
import numpy
if __name__ == "__main__":
N = 100000
while True:
points = [(r, x) for r, x in data.generate(N)]
R = numpy.array([r for r, x in points])
X = numpy.array([x for r, x in points])
for i in range(100):
points = [(R[idx], X[idx]) for idx in range(8000)]
data.send(points, N=1000 * N)
for j in range(1000):
X = R * X * (1 - X)
#!/usr/bin/env python
import data
def next(p):
r, x = p
x = r * x * (1 - x)
return (r, x)
if __name__ == "__main__":
N = 100000
while True:
points = [(r, x) for r, x in data.generate(N)]
for i in range(10000):
data.send(points)
points = [next(p) for p in points]