def delayplotter(aircrafttype, ATA, begin,end,interval): # interval in months
k = core.unpickle("./Data.txt")
k = core.getbyType(k,aircrafttype) #getting the data ready
k = core.sortata(k, 2)
delay, date = core.getdelaylist([begin,end],interval,k)
newdate = []
newdelay = []
years = []
final = []
mini = []
maxi = []
for i in range(len(delay)):
for j in range(len(delay[i])):
for l in range(len(ATA)):
if delay[i][j][0] == ATA[l]:
newdate.append(date[i])
newdelay.append(delay[i][j])
for x in range(len(newdate)):
year = newdate[x]
year = year[-4:]
years.append(year)
average = round(float(newdelay[x][1])/float(newdelay[x][2]),2)
minimum = min(newdelay[x][5])
maximum = max(newdelay[x][5])
newdelay[x].append(average)
newdelay[x].append(minimum)
newdelay[x].append(maximum)
# print newdelay[x]
# now we create a list with [ata, total delay, delay freq., average delay, min delay, max delay]
del newdelay[x][3]
del newdelay[x][3]
del newdelay[x][3]
# print newdelay
for z in range(len(newdate)):
final.append(newdelay[z][3])
mini.append(newdelay[z][4])
maxi.append(newdelay[z][5])
# print final
final = np.array(final)
mini = np.array(mini)
maxi = np.array(maxi)
return years,final,mini,maxi
def graphthis(year, ata, actype, data):
k = core.getbyType(data, actype)
canc_freq = []
labels = []
for m in range(len(ata)):
canc_freq.append([0])
print canc_freq, "initial"
yearlst = []
no_of_yrs = year[1] - year[0] + 1
for p in range(no_of_yrs):
yearlst.append(int(year[0] + p))
for i in range(len(ata)):
int_canc_freq = []
labels.append(ata[i])
delay, date = core.getdelaylist([year[0], year[1]], 12, k)
for j in range(no_of_yrs):
#if j not in yearlst:
# yearlst.append(year[0]+j)
for n in range(len(delay[j])):
if delay[j][n][0] == ata[i]:
int_canc_freq.append(delay[j][n][3])
print int_canc_freq, "intermediate, per ata"
canc_freq[i] = int_canc_freq
"""
plt.xlabel('Year')
plt.ylabel('Cancellation Frequency')
plt.plot(yearlst, canc_freq[i])
plt.legend()
plt.show()"""
print canc_freq, "cancel frequency"
print yearlst, "yearlist"
plt.xlabel('Year')
plt.ylabel('Cancellation Frequency')
for q, label in zip(range(len(ata)), labels):
plt.plot(yearlst, canc_freq[q], marker='o', label=label)
plt.xticks(yearlst)
plt.legend()
plt.savefig('Results/hopefullyitworks.png', dpi=200)
plt.show()
# -*- coding: utf-8 -*-
"""
Created on Thu May 24 09:48:10 2018
@author: Laurens
"""
import lib.core as core
k = core.unpickle("./Data.txt") #getting the data ready
k = core.sortata(k, 4)
delay, date = core.getdelaylist([1988, 2015], 36,
k) #getting the data ready till here
output = core.ThreeDgraph(delay, 3, 0)
Created on Mon Apr 23 14:17:44 2018
@author: Laurens
"""
#Tijd tot failure
#Verwachte delay
#Kans cancellation als het faalt
#per aircraft values
import matplotlib.pyplot as plt
import lib.core as core
interval = 36
k = core.unpickle("./Data.txt") #getting the data ready
k = core.sortata(k, 3)
final, date = core.getdelaylist([1988, 2015], interval, k)
final_delay = []
final_rel_year = []
final_rel_allyears = []
temp_rel = []
temp2_rel = []
final2_rel_allyears = []
#----------------------------------------------------------------------------------------actual program starts
for i in range(len(final)): #relation loop
for j in range(len(final[i])):
if final[i][j][2] != 0:
a = int(
round(float((float(interval) / 12) * 365 / final[i][j][2]),
0)) #amount of days average delay
b = round(float(final[i][j][1]) / final[i][j][2],
for atalevel in range(2, 5):
for beginyear in [1988, 2011, 2014]:
for actype in range(1, 4):
for interval in [3, 6, 12, 36]:
newl = []
intl = []
if actype == 3 and beginyear < 1995:
beginyear = 1995
if (beginyear == 1988 or
(actype == 3 and beginyear == 1995)) and interval <= 6:
continue
a = core.getbyType(k, actype)
a = core.sortata(a, atalevel)
final, datelist = core.getdelaylist([beginyear, 2015],
interval, a)
for w in range(len(final)):
for l in range(10):
#print w, k
intl.append(final[w][l][0])
intl.append(l + 1)
intl.append(datelist[w])
newl.append(intl)
intl = []
filename = "DelayTop%d_ata%d_ac%d_%d-2015_interv%d" % (
top, atalevel, actype, beginyear, interval)
with open(os.path.join('Top10csv', filename + '.csv'),
'wb') as myfile:
wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
actype = 1
atalevel = 2
interval = 36
with open("./Data.txt", "rb") as fp: # Unpickling list all types
b = pickle.load(fp)
a = copy.deepcopy(b)
a = core.getbyType(a, actype)
a = core.sortata(a, atalevel)
# importing the final top 10 lists
# from DelayTop10 import getdelaylist
# arguments are the atalevel, year range and interval in months. More are possible, check the function
final_delay, datelist = core.getdelaylist(timeframe = [1988,2015], interval = 28*12, k = a) # 28*12 are the months included on the total year range
delaycutoff = 15 # min aatime to actually consider something a delay
#binsize = 5 # unused at the moment, was used for debugging
#actype = 1 # all this was used for debugging
#atalevel = 3 # 2 means chapter. higher number means more detailed ata level
#atatest = 52
#timeframe = [2011,2012]
#c = core.getbyType(b,actype) # filter by type
#c = core.getbyDate(c, timeframe)
#c = core.getbyCancelled(c, 0)
### Section on fitting stuff to the delay time distributions