def menuShow(screen, bg):
sg1 = Sign(290, 260)
sg2 = Sign(690, 260)
pos = (0, 0)
tr = 1
but1 = 0
but2 = 0
while tr:
screen.blit(bg, (0, 0))
sg1.show(screen)
sg2.show(screen)
font = pygame.font.SysFont("comicsansms", 40)
text = font.render("Step by step", True, (100, 100, 255))
screen.blit(text, (290 + (300 - text.get_width()) // 2, 260 + (200 - text.get_height()) // 2))
text = font.render("User case", True, (100, 100, 255))
screen.blit(text, (690 + (300 - text.get_width()) // 2, 260 + (200 - text.get_height()) // 2))
for event in pygame.event.get():
if event.type == pygame.MOUSEMOTION:
pos = event.pos
elif event.type == pygame.MOUSEBUTTONDOWN:
pos = event.pos
if sg1.click(pos) or sg2.click(pos):
but1 = sg1.click(pos)
but2 = sg2.click(pos)
tr = 0
sg1.update(pos)
sg2.update(pos)
pygame.display.update()
#time.sleep(0.005)
if but2:
m, n = inpt(screen, bg)
algo.main(n, m, screen)
elif but1:
algo.main(2, 2, screen)
def UploadAction(event=None):
filez = filedialog.askopenfilenames(parent=r,title='Choose a file')
files_data = r.tk.splitlist(filez)
result = main(files_data)
import operator
sorted_d = dict(sorted(result.items(), key=operator.itemgetter(1),reverse=True))
top_10 = list(sorted_d.keys())[0:10]
re_insert = dict()
list_value = list()
predict_values = list()
for i in top_10:
list_value.append(i)
predict_values.append(float(sorted_d[i]))
re_insert['Algorithms'] = list_value
re_insert['Accuracy'] = predict_values
print(re_insert)
df1 = DataFrame(re_insert,columns=['Algorithms','Accuracy'])
figure1 = plt.Figure(figsize=(30,15), dpi=100)
ax1 = figure1.add_subplot(111)
ax1.set_title('Best algorithms for your model')
bar1 = FigureCanvasTkAgg(figure1, r)
bar1.get_tk_widget().pack(side=tk.LEFT, fill=tk.BOTH)
df1 = df1[['Algorithms','Accuracy']].groupby('Algorithms').sum()
df1.plot(kind='bar', legend=True, ax=ax1)
def post(self):
urlLinks = self.request.get("urllink")
tag = self.request.get("tag")
img = urlLinks
displaygray = self.request.get("grayz")
#if db.GqlQuery('SELECT * FROM CC WHERE tag = tag'):
# dictionary = exists[0].colorcode
# totalpx = exists[0].totalpx
# dominant = exists[0].dominant
dictionary, totalpx, dominant, displaygray = main(img, displaygray)
data_input = CC(tag=tag,
colorcode=str(dictionary),
dominant=str(dominant),
totalpx=totalpx,
confidence=50.0)
data_input.put()
q = db.GqlQuery('SELECT * FROM CC ORDER BY tag')
queryDict = {}
counter = 0
for n in q:
queryDict[counter] = ast.literal_eval(n.colorcode)
counter += 1
self.render("front.html",
dictionary=dictionary,
totalpx=totalpx,
tag=tag,
q=q,
queryDict=queryDict,
displaygray=displaygray)
def main():
ex = algo.main()
# Need to go step by step, python is exploding
for inFile, all_res in ex.items():
with open("analytics_" + inFile + ".csv", 'w') as csvfile:
writer = csv.DictWriter(
csvfile,
fieldnames=[
"Algorithme", "Nombre de camions utilisés",
"Nombre d'accès aux camions",
"Nombre de remplissage des camions",
"Moyenne de remplissage d'un camion",
"% de camions remplis à 1-10%",
"% de camions remplis à 11-20%",
"% de camions remplis à 21-30%",
"% de camions remplis à 31-40%",
"% de camions remplis à 41-50%",
"% de camions remplis à 51-60%",
"% de camions remplis à 61-70%",
"% de camions remplis à 71-80%",
"% de camions remplis à 81-90%",
"% de camions remplis à 91-100%"
])
writer.writeheader()
for res in all_res:
row = {}
row["Algorithme"] = res[0]
bins = res[1]
row["Nombre de camions utilisés"] = len(bins)
row["Nombre d'accès aux camions"] = bins.bin_access
row["Nombre de remplissage des camions"] = bins.bin_change
row["Moyenne de remplissage d'un camion"] = round(
100 * sum(bins) / (len(bins) * bins.bin_size))
for i in range(0, 100, 10):
m_min = i + 1
m_max = i + 10
row["% de camions remplis à {0}-{1}%".format(
m_min, m_max)] = round(
100 * len(
list(
filter(
lambda bin: m_min <= 100 * bin / bins.
bin_size <= m_max, bins))) / len(bins),
2)
writer.writerow(row)
def get(self):
img = "images/sample3.png"
default_tag = "COLOR OF THE DAY"
displaygray = "false"
dictionary, totalpx, dominant, displaygray = main(img, displaygray)
q = db.GqlQuery('SELECT * FROM CC ORDER BY tag')
counter = 0
queryDict = {}
for n in q:
queryDict[counter] = ast.literal_eval(n.colorcode)
counter += 1
self.render("front.html",
dictionary=dictionary,
totalpx=totalpx,
q=q,
tag=default_tag,
queryDict=queryDict)
pagenos,
maxpages=maxpages,
password=password,
caching=caching,
check_extractable=True):
page.rotate = (page.rotate + rotation) % 360
interpreter.process_page(page)
fp.close()
device.close()
outfp.close()
return
if __name__ == '__main__':
#x=int(input("Enter the number of pdf files to be converted :"))
#for i in range(x):
# pdf=raw_input("\nPlease enter the name of the pdf files : \n")
# main(pdf,i+1)
# algo.main('pdf'+str(i+1))
x = sys.argv[1:]
for i in range(len(x)):
main(x[i], i + 1)
results = algo.main('pdf' + str(i + 1))
# Results is a List of Lists
#TODO Convert Results into a CSV for Analysis in Excel
with open('excel' + str(i + 1) + '.csv', 'wb') as myfile:
wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
wr.writerows(results)
limit=datetime.datetime(1, 1, 1, 0, 0, 1)
original=0
final=0
saved_distance=0
end=False
counter=0
while(end==False):
print("processing " + str(counter+1) + "th pool")
counter=counter+1
end,limit,trip_details_dictionary=dataprovider.get_trip_details(limit)
limit=limit+datetime.timedelta(0,3)
pool1=trip_details_dictionary[1]
pool2=trip_details_dictionary[2]
pool3=trip_details_dictionary[3]
pool4=trip_details_dictionary[4]
initial,total,saved,total_distance_after_merging=algo.main(pool1,pool2,pool3,pool4,2)
original=original+initial
final=final+total
saved_distance=saved_distance+saved
print(saved_distance)
print(original-final)
average_original=original/counter
average_final=final/counter
average_saved=saved_distance/counter
total_saved_trips=original-final
print("Total number of trips without ride sharing" + str(original))
print("Total number of trips with ride sharing" + str(final))
print("Average number of trips merged per pool" + str(int((original-final)/counter)))
print("Total number of trips saved: " + str(total_saved_trips))
print("Average number of trips saved: " + str(int(total_saved_trips/counter)))
def resolution():
idDataSet = str(request.json)
result = main(idDataSet)
return str(result)
def debug_algo():
algo.main()
return jsonify({"success": True})
def order_root():
if request.method == "POST":
# expected data [priority, time_to_completion, facility_id, equipment_id]
data = request.get_json()
# sanitization
if not data:
return jsonify({"success": False, "message": "Missing body."}), 400
if not 'priority' in data or not 'time_to_completion' in data or not 'facility_id' in data or not 'equipment_id' in data:
return jsonify({
"success": False,
"message": "Missing body fields."
}), 400
if not isinstance(data['priority'], int) or not isinstance(
data['time_to_completion'], int) or not isinstance(
data['facility_id'], int) or not isinstance(
data['equipment_id'], int):
return jsonify({
"success": False,
"message": "Invalid body fields."
}), 400
if data['priority'] < 1 or data['priority'] > 5:
return jsonify({
"success": False,
"message": "Priority out of range."
}), 400
if data['time_to_completion'] < 1:
return jsonify({
"success": False,
"message": "Time to completion out of range."
}), 400
if not Equipment.query.get(data['equipment_id']):
return jsonify({
"success": False,
"message": "Equipment key not found."
}), 404
if not Facility.query.get(data['facility_id']):
return jsonify({
"success": False,
"message": "Facility key not found."
}), 404
# add to db
order = Order(data['priority'], data['time_to_completion'],
data['facility_id'], data['equipment_id'])
db.session.add(order)
db.session.commit()
# after each call
algo.main()
return jsonify(get_dict(order))
else:
# get orders
orders = Order.query.order_by(Order.created_at.desc()).all()
return jsonify(get_dict_array(orders))
def equipment_type_root():
if request.method == "POST":
# expected data [name, prob, hour_min, hour_max]
data = request.get_json()
# sanitization
if not data:
return jsonify({"success": False, "message": "Missing body."}), 400
if not 'name' in data or not 'prob' in data or not 'hour_min' in data or not 'hour_max' in data:
return jsonify({
"success": False,
"message": "Missing body fields."
}), 400
if not isinstance(data['name'], str) or not isinstance(
data['prob'], (int, float)) or not isinstance(
data['hour_min'], int) or not isinstance(
data['hour_max'], int):
return jsonify({
"success": False,
"message": "Invalid body fields."
}), 400
if len(data['name'].strip()) < 1 or len(data['name']) > 25:
return jsonify({
"success": False,
"message": "Name length out of range."
}), 400
if data['prob'] < 0 or data['prob'] > 1:
return jsonify({
"success": False,
"message": "Probability out of range."
}), 400
if data['hour_min'] < 1:
return jsonify({
"success": False,
"message": "Minimum hour out of range."
}), 400
if data['hour_max'] < 1 or data['hour_max'] < data['hour_min']:
return jsonify({
"success": False,
"message": "Maximum hour out of range."
}), 400
# add to db
e_type = EquipmentType(data['name'], data['prob'], data['hour_min'],
data['hour_max'])
db.session.add(e_type)
db.session.commit()
# main algorithm run
algo.main()
return jsonify(get_dict(e_type))
else:
# get equipments
equipment_types = EquipmentType.query.all()
return jsonify(get_dict_array(equipment_types))