def validate_eans(eans):
if isinstance(eans, str):
eansSplit = [x.strip() for x in eans.split(',')]
else:
eansSplit = [str(eans)]
valid_eans = []
for ean in eansSplit:
if len(ean) in (8, 13):
try:
ean_digits = [int(x) for x in ean]
except ValueError:
logging.warning("'{}' has non-numeric characters".format(ean))
continue
for i in range(len(ean_digits[:-1])):
if len(ean) == 8:
if i % 2 == 0:
ean_digits[i] = ean_digits[i] * 3
else:
if i % 2 != 0:
ean_digits[i] = ean_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(ean_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(ean_digits[:-1]) == ean_digits[-1]:
valid_eans.append('<EAN>' + ean + '</EAN>')
else:
logging.warning('EAN: Invalid Checkdigit - {}'.format(ean))
elif len(ean) in range(9, 13):
zeroes = ''
add = 13 - len(ean)
for i in range(add):
zeroes += '0'
ean = zeroes + ean
try:
ean_digits = [int(x) for x in ean]
for i in range(len(ean_digits[:-1])):
if i % 2 != 0:
ean_digits[i] = ean_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(ean_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(ean_digits[:-1]) == ean_digits[-1]:
valid_eans.append('<EAN>' + ean + '</EAN>')
else:
logging.warning('EAN: Invalid Length - {}'.format(ean))
except ValueError:
ean = ean[len(zeroes):]
logging.warning(
ean,
'EAN: Invalid Length - Too Many Zeroes? - {}'.format(ean))
elif ean != '':
logging.warning('EAN: Invalid Length')
if len(valid_eans) > 0:
all_eans = "".join(set(valid_eans))
return all_eans
else:
return ''
def validate_upcs(product_id, upcs, broken_gtins, broken_gtin_count):
valid_upcs = []
for upc in upcs:
if len(upc) in (6, 12):
upc_digits = [int(x) for x in upc]
for i in range(len(upc_digits[:-1])):
if i % 2 == 0:
upc_digits[i] = upc_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(upc_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(upc_digits[:-1]) == upc_digits[-1]:
valid_upcs.append(upc)
else:
broken_gtins.writerow(
[product_id, upc, 'UPC: Invalid Checkdigit'])
broken_gtin_count += 1
elif len(upc) in range(7, 12):
zeroes = ''
add = 12 - len(upc)
for i in range(add):
zeroes += '0'
upc = zeroes + upc
try:
upc_digits = [int(x) for x in upc]
for i in range(len(upc_digits[:-1])):
if i % 2 == 0:
upc_digits[i] = upc_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(upc_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(upc_digits[:-1]) == upc_digits[-1]:
valid_upcs.append(upc)
else:
upc = upc[len(zeroes):]
broken_gtins.writerow(
[product_id, upc, 'UPC: Invalid Length'])
broken_gtin_count += 1
except ValueError:
upc = upc[len(zeroes):]
broken_gtins.writerow([product_id, upc, 'UPC: Invalid Length'])
broken_gtin_count += 1
else:
broken_gtins.writerow([product_id, upc, 'UPC: Invalid Length'])
broken_gtin_count += 1
if len(valid_upcs) >= 1:
x_upcs = objectify.SubElement(x_Product, "UPCs")
# product_string_array.append(' ' + '<UPCs>' + '\n')
for upc in valid_upcs:
objectify.SubElement(x_upcs, "UPC")
x_upcs.UPC = upc
# product_string_array.append(' ' + '<UPC>' + upc + '</UPC>' + '\n')
# product_string_array.append(' ' + '</UPCs>' + '\n')
print(broken_gtin_count)
return broken_gtin_count
def validate_eans(product_id, eans, broken_gtins):
valid_eans = []
for ean in eans:
if len(ean) in (8, 13):
# if ean length is 8 or 13, validate
ean_digits = [int(x) for x in ean]
for i in range(len(ean_digits[:-1])):
if len(ean) == 8:
# xxx - what is going on here?
if i % 2 == 0:
ean_digits[i] = ean_digits[i] * 3
else:
if i % 2 != 0:
ean_digits[i] = ean_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(ean_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(ean_digits[:-1]) == ean_digits[-1]:
valid_eans.append(ean)
else:
broken_gtins.writerow(
[product_id, ean, 'EAN: Invalid Checkdigit'])
# if ean length between 9 - 13, add leading zeros
elif len(ean) in range(9, 13):
zeroes = ''
add = 13 - len(ean)
for i in range(add):
zeroes += '0'
ean = zeroes + ean
try:
ean_digits = [int(x) for x in ean]
for i in range(len(ean_digits[:-1])):
if i % 2 != 0:
ean_digits[i] = ean_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(ean_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(ean_digits[:-1]) == ean_digits[-1]:
valid_eans.append(ean)
else:
ean = ean[len(zeroes):]
broken_gtins.writerow(
[product_id, ean, 'EAN: Invalid Length'])
except ValueError:
print(ean, 'too many zeroes?')
ean = ean[len(zeroes):]
broken_gtins.writerow([product_id, ean, 'EAN: Invalid Length'])
else:
broken_gtins.writerow([product_id, ean, 'EAN: Invalid Length'])
if len(valid_eans) >= 1:
x_eans = objectify.SubElement(x_Product, 'EANs')
# product_string_array.append(' ' + '<EANs>' + '\n')
for index, ean in enumerate(valid_eans):
x_ean = objectify.SubElement(x_eans, 'EAN')
x_ean[index] = ean
def validate_upcs(upcs):
if isinstance(upcs, int):
upcsSplit = [str(upcs)]
else:
upcsSplit = [x.strip() for x in upcs.split(',')]
valid_upcs = []
for upc in upcsSplit:
if len(upc) in (6, 12):
try:
upc_digits = [int(x) for x in upc]
except ValueError:
logging.warning("'{}' has non-numeric characters".format(upc))
continue
for i in range(len(upc_digits[:-1])):
if i % 2 == 0:
upc_digits[i] = upc_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(upc_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(upc_digits[:-1]) == upc_digits[-1]:
valid_upcs.append('<UPC>' + upc + '</UPC>')
else:
logging.warning('UPC: Invalid Checkdigit - {}'.format(upc))
elif len(upc) in range(7, 12):
zeroes = ''
add = 12 - len(upc)
for i in range(add):
zeroes += '0'
upc = zeroes + upc
try:
upc_digits = [int(x) for x in upc]
for i in range(len(upc_digits[:-1])):
if i % 2 == 0:
upc_digits[i] = upc_digits[i] * 3
round_nearest_ten = int(
roundup(float(sum(upc_digits[:-1])) / 10) * 10)
if round_nearest_ten - sum(upc_digits[:-1]) == upc_digits[-1]:
valid_upcs.append('<UPC>' + upc + '</UPC>')
else:
upc = upc[len(zeroes):]
logging.warning('UPC: Invalid Length - {}'.format(upc))
except ValueError:
upc = upc[len(zeroes):]
logging.warning('UPC: Invalid Length - {}'.format(upc))
if len(valid_upcs) > 0:
all_upcs = "".join(set(valid_upcs))
return all_upcs
else:
return ''
def train_ann(training_set):
'''Train the anni
'''
#Constants
total_datapoints = len(training_set)
num_inputs = len(training_set[0][0])
num_outputs = len(training_set[0][1])
learning_rate = 0.01
momentum = 0.95
desired_error = 0.0001
iterations_between_reports = 0
maximum_iterations = 10000
num_hiddens1 = roundup(num_inputs * 0.95)
num_hiddens2 = roundup(num_inputs * 0.85)
#Gotta make a training data file
data_file = "../data/validation/training.data"
f = open(data_file, 'w')
f.write("%s %s %s\n" % (total_datapoints, num_inputs, num_outputs))
for datapoint in training_set:
inp = ' '.join(str(x) for x in datapoint[0])
targ = ' '.join(str(x) for x in datapoint[1])
f.write("%s\n" % inp)
f.write("%s\n" % targ)
f.close()
mse = 1
while mse > desired_error:
ann = lf.neural_net()
ann.create_standard_array(
[num_inputs, num_hiddens1, num_hiddens2, num_outputs])
ann.set_learning_rate(learning_rate)
ann.set_learning_momentum(momentum)
ann.set_activation_function_hidden(
lf.SIGMOID_SYMMETRIC
) #This is to ensure negative and positive influences can be detected
ann.set_activation_function_output(
lf.SIGMOID) #Ensure output isnt negative
ann.set_bit_fail_limit(0.01)
#ann.set_train_error_function(lf.ERRORFUNC_TANH)
# Train
ann.train_on_file(data_file, maximum_iterations,
iterations_between_reports, desired_error)
mse = ann.get_MSE()
return ann
def struct(self, address, fmt):
size = calcsize(fmt)
result = []
for _ in range(roundup(size/PyMemory.BUFFER_SIZE)):
self.buffer_load(address, size)
result += unpack(fmt, self.buffer[:size])
return result
def post(self):
"""Mark a scooter as not reserved and return success or fail status boolean. Also charge customer and update scooter location."""
dataResponse = defaultResponse
q = """ UPDATE scooters
SET is_reserved = false
WHERE id={id.int}
AND is_reserved = true
RETURNING true;
"""
payload, newQuery = Validator.validatePayload(q, request)
if payload:
# End reservation success code
dataResponse = getQueryResponse(payload,
newQuery,
queryType='update')
if dataResponse[0]:
q = """SELECT ST_Distance(location, ST_MakePoint({endlng.float}, {endlat.float})) FROM scooters WHERE id = {id.int}"""
payload, newQuery = Validator.validatePayload(q, request)
if payload:
# Charge customer and update scooter location.
distanceTraveled = getQueryResponse(payload,
newQuery,
queryType='query')[0]
distanceTraveled = distanceTraveled[0]
while type(distanceTraveled) is tuple:
distanceTraveled = distanceTraveled[0]
distanceTraveled = roundup(
distanceTraveled
) if distanceTraveled > 0 else 1 # Min distance traveled is always 1.
pricePerMeter = 1.0 # Ideally, this value is should not be hard coded
fareCost = pricePerMeter * distanceTraveled
q = """UPDATE users
SET (last_fare, fares, scooter_ids, distances_traveled) = ({fareCost}::real, array_append(fares, {fareCost}::real),
array_append(scooter_ids, {id.int}::bigint),
array_append(distances_traveled, {distanceTraveled}::bigint))
WHERE id={userid.int};
UPDATE scooters
SET (lon, lat, distances_traveled, rider_ids, location) = ({endlng.float}, {endlat.float},
array_append(distances_traveled, {distanceTraveled}::bigint),
array_append(rider_ids, {userid.int}::bigint),
ST_POINT({endlng.float}, {endlat.float}))
WHERE id = {id.int};
"""
q = q.replace('{fareCost}', str(fareCost)).replace(
'{distanceTraveled}',
str(distanceTraveled)) # Partial format subtitution
payload, newQuery = Validator.validatePayload(q, request)
if payload:
_ = getQueryResponse(payload, newQuery, queryType='update')
return dataResponse
def Listify(crypt,key): keyl=list(key) length=len(key) #gets numbers of each letter keyln=[] for index in range(len(keyl)): keyln.append(ord(keyl[index])) m = [[] for x in range(length)] #puts crypt into 2D array i = 0 for row in range(int(roundup(len(unshuffledString)/length))+1): for col in range(length): try: m[col].append(crypt[i]) except: continue i+=1 return m
def Listify(crypt, key):
keyl = list(key)
length = len(key)
#gets numbers of each letter
keyln = []
for index in range(len(keyl)):
keyln.append(ord(keyl[index]))
m = [[] for x in range(length)]
#puts crypt into 2D array
i = 0
for row in range(int(roundup(len(unshuffledString) / length)) + 1):
for col in range(length):
try:
m[col].append(crypt[i])
except:
continue
i += 1
return m
saved_net_file = "../data/networks/order_all_averaged_fixed.net"
## Grab the number of inputs, outputs (first line of .data in format #datapoints, inputs, outputs)
f = open(data_file, 'r')
info = (f.readline()).split(' ')
num_inputs = int(info[1])
num_outputs = int(info[2])
f.close()
## Settings
learning_rate = 0.1
momentum = 0.95
desired_error = 0.00001
iterations_between_reports = 100
maximum_iterations = 10000
## Determine number of hidden nodes
num_hiddens1 = roundup(num_inputs * 0.95)
num_hiddens2 = roundup(num_inputs * 0.85)
# Create network
ann = lf.neural_net()
ann.create_standard_array(
[num_inputs, num_hiddens1, num_hiddens2, num_outputs])
ann.set_learning_rate(learning_rate)
ann.set_learning_momentum(momentum)
ann.set_activation_function_hidden(
lf.SIGMOID_SYMMETRIC
) #This is to ensure negative and positive influences can be detected
ann.set_activation_function_output(lf.SIGMOID) #Ensure output isnt negative
ann.set_bit_fail_limit(0.01)
# Train
# print(sin(6.28)) # print(sin(pi*2)) # four = sqrt(4) # print(four) #imported all math functions from Python module #in particular, we noted we imported sin. No need for "math.sin."" Just ".sin" #however, we must note "math." for the rest of the math functions #we can rename Python function; e.g. give "ceil" a new name "roundup" import math from math import sin, pi, ceil as roundup num = 5.6 print(math.ceil(num)) print(roundup(num)) #renamed math.ceil as roundup or math.ceil=roundup print(math.floor(num)) print(math.factorial(4)) print(math.pow(2, 4)) print(2**4) print(math.exp(2)) print(math.log(16, 2)) print(sin(6.28)) #no need for "math." for sin because we noted from import print(sin(pi * 2)) #no need for "math." for pi because we noted from import four = math.sqrt(4) print(four) print(math.degrees(pi * 2)) #a circle 360.0 degrees