def test(plot=True):
'''
Tests validity of error/anomaly identification algorithm
Parameters: plot (bool) - True if you want to see a plot of the data, the fitted polynomial, the detrended stream, and error datapoints in 2 plots
Returns: None
'''
#open file
f = open("Error CSV Files/3.12.2015_error.csv")
reader = csv.reader(f)
data = []
for i in reader:
dt = convert_str_to_dt(i[0])
for j in range(1,len(i)):
i[j] = float(i[j])
data.append([dt]+i[1:])
f.close()
#create different datasets
date_data = [i[0] for i in data]
rcmpl_data = [i[1] for i in data]
blocked_data = [i[2] for i in data]
unblocked_data = [i[3] for i in data]
x_vals = [i for i in range(len(rcmpl_data))]
#fit polynomial to RCMPL data
y_vals,y_poly = p_poly.poly_detrend(x_vals,rcmpl_data,degree=6,d_type = "d")
#detect "anomalies"
error_vals = error_detect(y_vals,0,20)
error_x = [i[0] for i in error_vals]
error_y = [i[1] for i in error_vals]
init_error_y = [rcmpl_data[i] for i in error_x]
#plot results
if plot:
plt.figure(1)
plt.subplot(211)
plt.title("{}".format(date_data[0].date()))
plt.plot(x_vals,rcmpl_data,"bo",x_vals,y_poly,"r-",init_error_y)
plt.subplot(212)
plt.plot(x_vals,y_vals,"b",error_x,error_y,"ro")
plt.show()
def main(load_error_to_db = False,load_error_to_dataset = False):
#read in data
f = open("prototype1 (4).csv")
reader = csv.reader(f)
data = []
for i in reader:
dt = poly_test.convert_str_to_dt(i[0])
for j in range(1,len(i)):
i[j] = float(i[j])
data.append([dt]+i[1:])
f.close()
#create different major datasets
date_data = [i[0] for i in data]
rcmpl_data = [i[1] for i in data]
blocked_data = [i[2] for i in data]
unblocked_data = [i[3] for i in data]
error_data = []
index = 0
while index < len(data):
this_dt = data[index][0].replace(hour = 0).replace(minute = 0)
next_dt = this_dt + datetime.timedelta(days = 1)
daily_data = []
#group data by day
while this_dt < next_dt and index < len(data)-1:
daily_data.append([index,data[index][0],data[index][1]])
index += 1
this_dt = data[index][0].replace(hour = 0).replace(minute = 0)
#create relevant lists
x_vals = [i for i in range(len(daily_data))]
y_vals = [i[2] for i in daily_data]
#create/fit polynomial and detrend data
y_new,y_poly = p_poly.poly_detrend(x_vals,y_vals,degree=6,d_type="d")
#detect errors
error_vals = poly_test.error_detect(y_new,0,20)
#build error_data list
for i in range(len(error_vals)):
error_vals[i] = list(error_vals[i])
error_vals[i][0] = daily_data[error_vals[i][0]][1]
error_data.append(error_vals[i])
if index == len(data) - 1:
break
#add relevant information to original dataset loaded in
for i in range(len(data)):
error_flag = False
for j in range(len(error_data)):
if data[i][0] == error_data[j][0]:
#data[i].append(error_data[j][1])
data[i].append(error_data[j][2])
data[i].append(1)
error_flag = True
error_data.pop(j)
break
if not error_flag:
#data[i].append(None)
data[i].append(None)
data[i].append(0)
#create binary (1 for error at timestamp 0 ow) error list
error_binary = [i[-1] for i in data]
#fill in holes for errors
error_binary_new = checkErrors(error_binary)
for i in range(len(error_binary_new)):
data[i].append(error_binary_new[i])
#create error list to write out/upload to db
error_list = []
for i in range(len(data)):
if data[i][-1] == 1:
if data[i][4] != None:
latest_std = data[i][4]
temp = [data[i][0],data[i][4]]
else:
data[i][4] = latest_std
temp = [data[i][0],latest_std]
error_list.append(temp)
if load_error_to_db:
#write out contents
f = open("error_ts_score.csv",'w')
writer = csv.writer(f,lineterminator="\n")
writer.writerows(error_list)
f.close()
#upload data to db
db = MySQLdb.connect("11.120.36.241","internship","Pr3dict!v@","predictiveAnalytics")
c = db.cursor()
sql = "LOAD DATA LOCAL INFILE 'error_ts_score.csv' INTO TABLE order_anomalies FIELDS TERMINATED BY ','"
c.execute(sql)
db.commit()
db.close()
if upload_master_dataset:
#create updated data list
data = [[i[0],i[1],i[2],i[3],i[6],i[4]] for i in data]
#write out contents
f = open("order_dataset.csv",'w')
writer = csv.writer(f,lineterminator="\n")
writer.writerows(data)
f.close()
#upload data to db
db = MySQLdb.connect("11.120.36.241","internship","Pr3dict!v@","predictiveAnalytics")
c = db.cursor()
sql = "LOAD DATA LOCAL INFILE 'order_dataset.csv' INTO TABLE order_dataset FIELDS TERMINATED BY ','"
c.execute(sql)
db.commit()
db.close()
