def extract_metric(self, trip, metric):
""" method to extract 'metric' from dict 'trip' returned by QPX API
must support all metrics defined in self.supported_metrics """
if metric == 'Sale Total, USD':
return np.float(trip['saleTotal'][3:])
elif metric == 'Number of Layovers':
return len(trip['slice'][0]['segment']) - 1
elif metric == 'Total Flight Duration, Hours':
return trip['slice'][0]['duration'] / 60
elif metric == 'Hours In Air':
set_trace()
elif metric == 'Hours In Layover':
set_trace()
def init_results(self):
""" method to intialize the results tab from currrent selection, runs:
-- when flight-results tab is pressed
-- when flight origin combo is changed
-- when flight metric combo box is changed
"""
# set local hooks for data and selected flight configurations
# (flight data is guaranteed to exist at this point)
data = self.flight_data
config = self.getContents(checked=True)
# update the origin combo box if necessary, unwire the combo action
# temporarily to avoid a recursive call while the combo updates
if len(config[0]) != self.origin_combo.count():
self.origin_combo.currentIndexChanged.disconnect()
self.origin_combo.clear()
self.origin_combo.addItems(config[0])
self.origin_combo.currentIndexChanged.connect(self.init_results)
# get current selected origin, selected dests, selected dates, and
# current selected flight metric
origin = config[0][self.origin_combo.currentIndex()]
dests = config[1]
dates = [time.strftime('%Y-%m-%d', time.strptime(x, self.format)) for x in config[2]]
metric = self.supported_metrics[self.metric_combo.currentIndex()]
# get numpy 3-dimensional array, where each number is the 'metric' for:
# dim-0 -> destination
# dim-1 -> date
# dim-2 -> flight number, from 0 to self.n_flights-1
plot_data = np.full((len(dests), len(dates), self.n_flights), np.nan)
for i, dest in enumerate(dests):
for j, date in enumerate(dates):
trips = data[origin][dest][date]['trips']['tripOption']
for k, trip in enumerate(trips):
plot_data[i, j, k] = self.extract_metric(trip, metric)
# find the maximum number of trip options available for all flights
# set the radio button with the appropriate text label
n = [[len(data[origin][dest][date]['trips']['tripOption']) for dest \
in dests] for date in dates]
n_min = min([min(x) for x in n])
if str(n_min)[-1:] == 1:
n_min = str(n_min) + 'st'
if str(n_min)[-1:] == 2:
n_min = str(n_min) + 'nd'
if str(n_min)[-1:] == 3:
n_min = str(n_min) + 'rd'
else:
n_min = str(n_min) + 'th'
self.radio_button_n.setText('Show 1st to {}\nLeast Expensive Flights'.
format(n_min))
# clear the current figure, create a new axes
self.figure.clf()
self.figure.canvas.draw()
ax = self.figure.add_subplot(111)
# set the x-axis as the dates, set the width of the bars
xdata = np.arange(len(dates))
frac_width = 0.8
width = frac_width / len(dests)
# get a matplotlib color cycle
colors = [plt.cm.gist_heat(x) for x in np.linspace(0, 0.9, len(dests))]
# create a different plot type based on the 1 or 1 to n flight selection
if self.radio_button_1.isChecked():
# initialize a numpy array for the bar plot objects, then create them
bars = np.empty(len(dests), dtype='O')
for i, dest in enumerate(dests):
bars[i] = ax.bar(xdata+width*i, plot_data[i, :, 0], width, color=colors[i])
elif self.radio_button_1.isChecked():
set_trace()
# clean up
ax.set_xlim((xdata[0] - width/2, xdata[-1] + len(dests)*width + width/2))
ax.legend(bars, dests, loc='upper left', bbox_to_anchor=(0.985, 1.025),
title='Flight\nDestination', fontsize=16, fancybox=True,
shadow=True, frameon=True).get_title().set_fontsize(16)
ax.set_title(metric, fontsize=20, fontweight='bold')
ax.set_xticks(xdata + frac_width / 2)
xticks = [time.strftime(r'%-d %b%n%Y', time.strptime(x, self.format)) for x in config[2]]
ax.set_xticklabels(xticks)
self.figure.tight_layout()
ax.grid(False, axis='x')
plt.subplots_adjust(right=0.79, bottom=0.10)
# update the figure canvas
self.figure.canvas.draw()