def grid():
if request.method == "POST":
anagram = make_anagram(random.choice(NINE_LETTER_LIST))
middle_letter = anagram[len(anagram) // 2]
answers = puzzle_answers(anagram, DICTIONARY, letter=middle_letter)
answers = plural_filter(answers, DICTIONARY)
print(data(anagram, answers))
return jsonify(data(anagram, answers))
return render_template("grid.html")
def ladder():
if request.method == "POST":
submitted = request.get_json(force=True)
length = submitted["length"]
anagram = make_anagram(get_word(length, FULL_WORD_LIST))
answers = anagram_answers(len(anagram), anagram, DICTIONARY)
print(data(anagram, answers))
return jsonify(data(anagram, answers))
return render_template("ladder.html")
def rack():
if request.method == "POST":
submitted = request.get_json(force=True)
length = int(submitted["length"])
letters = draw_letters(LETTERS, length)
answers = puzzle_answers(letters, DICTIONARY)
high = high_scorer(answers, SCORES, RACK_HIGH)
print(data(letters, answers, high))
return jsonify(data(letters, answers, high))
return render_template("rack.html")
dest="arch",
action="store",
default="densenet121",
type=str)
ap.add_argument('--hidden_units',
type=int,
dest="hidden_units",
action="store",
default=120)
pa = ap.parse_args()
path = pa.save_dir
lr = pa.learning_rate
structure = pa.arch
dropout = pa.dropout
hidden_layer1 = pa.hidden_units
power = pa.gpu
epochs = pa.epochs
trainloader, validationloader, testloader, train_data = functions.data()
model, optimizer, criterion = functions.setup(structure, dropout,
hidden_layer1, lr, power)
functions.train_network(model, criterion, optimizer, trainloader,
validationloader, epochs, 20, power)
functions.save_checkpoint(train_data, epochs, structure, hidden_layer1,
dropout, lr, path)
print("The Model is trained")
ap.add_argument('--category_names',
dest="category_names",
action="store",
default='cat_to_name.json')
ap.add_argument('--gpu', default="gpu", action="store", dest="gpu")
pa = ap.parse_args()
path_image = pa.input_img
number_of_outputs = pa.top_k
power = pa.gpu
input_img = pa.input_img
path = pa.checkpoint
model, _, _ = functions.setup()
training_loader, testing_loader, validation_loader, train_data = functions.data(
)
functions.load_checkpoint(path)
with open('cat_to_name.json', 'r') as json_file:
cat_to_name = json.load(json_file)
probabilities = functions.predict(path_image, model, number_of_outputs, power)
labels = [
cat_to_name[str(index + 1)] for index in np.array(probabilities[1][0])
]
probability = np.array(probabilities[0][0])
i = 0
while i < number_of_outputs:
def showinfostation(self, currentStation=False):
"""
Args:
currentStation: Wordt er op huidige station geklikt dan is varaible station utrecht, anders False
Returns:
Return False als er geen match is, of station als er wel een match is
"""
if currentStation: # huidige station gklikt
station = 'Utrecht'
else: # niet huidige station geklikt en gebruiker klikt op "vertrijktijden station"
station = self.inputStationWindow.inputField.get() # krijg informatie uit de input field
if station == '': # is het leeg laat error box zien
tkinter.messagebox.showerror("Invoerveld leeg", "Gelieve iets in te voeren") # error box
return False # stop met uitvoeren van deze functie
db_conn = database() # database verbinding class
if station == 'update_station_list': # wordt de commando ingetypt dan update station lijst
db_conn.update_station_names() # lees excel bestand uit en stop het in de db
tkinter.messagebox.showinfo("update", "Update compleet") # message complete met uitvoeren
return False # stop met uitvoeren van deze functie
valid_station = db_conn.read_from_db_by_input(station) # kijk of station bekend is in db
station_info = False
if valid_station: # is het een geldige station verkrijg informatie
station_info = functions.data(valid_station) # verkrijg informatie
if station_info != 'conn_error' and not False: # is het niet False ga door
self.showInfoWindow.infoLabel[
"text"] = 'Huidig station: ' + valid_station + '\n' # Huidige station naam ingevuld door gebruiker
for station in station_info: # loop informatie
# station[0] = Tijd
# station[1] = Vertraging
# station[2] = Soort trein
# station[3] = Naar locatie
# station[4] = Spoor
# station[5] = Route
self.showInfoWindow.listbox.insert(END,
'Om {} {} vertrekt een {} naar {} op spoor: {}'.format(station[0],
station[1],
station[2],
station[3],
station[
4])) # insert informatie in scrollbare lijst
if station[5]: # is route meegelverd dan loop
for route in station[5].split(','): # split string naar list bij komma en loop
self.showInfoWindow.listbox.insert(END, ' · {}'.format(route))
self.viewInfoFrame() # laat infoscherm zien
elif station_info == 'conn_error': # geen verbinding show error
tkinter.messagebox.showerror("Error", 'Geen verbinding') # messagebox geen verbinding
else: # station bestaat niet
tkinter.messagebox.showerror("Error", 'Station bestaat niet!') # messagebox geen station
def main():
env_setup()
HEPD, MEPD = data(orbit_no, True, True)
plot(HEPD, MEPD, 'south', 'spacepy', 'plot_combined', 'pdf')