def get_chart(request):
if request.method != 'POST' or not request.is_ajax():
return HttpResponseForbidden()
stop_id = request.POST.get('stop_id', None)
if stop_id in [None, '']:
raise ValueError("stop_id can't be None or empty")
stop = get_object_or_404(Stop, pk=stop_id)
date_from = request.POST.get('date_from')
date_to = request.POST.get('date_to')
frequency = request.POST.get('frequency', '1t')
time_start = request.POST.get('time_start')
time_end = request.POST.get('time_end')
tzname = request.POST.get('timezone', 'America/Toronto')
timezone.activate(pytz.timezone(tzname))
predictions = Prediction.objects.filter(
stop=stop,
posted_at__gt=date_from,
posted_at__lte=date_to,
)
if is_valid_time_format(time_start) and is_valid_time_format(time_end):
predictions = predictions.exclude(posted_at__time__range=(time_end, time_start))
# Converting predictions to Pandas timeseries and resample by frequency
dataframe = predictions.to_timeseries(
fieldnames=['posted_at', 'seconds'],
index='posted_at',
values='seconds',
freq=frequency, # resampling triggers deprecation warning to use .mean()
).dropna(how='any') # Drop nan
predictions_json = dataframe.to_json(date_format='iso', orient='index')
return HttpResponse(predictions_json, content_type='application/json')
def get_hourly_average_chart(request):
if request.method != 'POST' or not request.is_ajax():
return HttpResponseForbidden()
stop_id = request.POST.get('stop_id', None)
if stop_id in [None, '']:
raise ValueError("stop_id can't be None or empty")
stop = get_object_or_404(Stop, pk=stop_id)
time_start = request.POST.get('time_start')
time_end = request.POST.get('time_end')
tzname = request.POST.get('timezone', 'America/Toronto')
timezone.activate(pytz.timezone(tzname))
avg_hourly = {}
for hour in range(0, 24):
prediction_avg = Prediction.objects.filter(
stop=stop,
posted_at__hour=hour
)
if is_valid_time_format(time_start) and is_valid_time_format(time_end):
prediction_avg = prediction_avg.exclude(posted_at__time__range=(time_end, time_start))
prediction_avg = prediction_avg.aggregate(Avg('seconds'))
avg_hourly[hour] = prediction_avg['seconds__avg']
response = {'avg_hourly': avg_hourly}
return HttpResponse(json.dumps(response), content_type='application/json')