Calculate average moods from average daily moods
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1 changed files with 14 additions and 5 deletions
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@ -46,13 +46,22 @@ def closest_mood(context, value):
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return found
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return found
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@register.simple_tag(takes_context=True)
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@register.simple_tag(takes_context=True)
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def average_mood(context, start, end=None):
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def average_mood(context, start, end=None, daily_averages=True):
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status_list = context["user"].status_set.filter(timestamp__gte=start.date(), timestamp__lte=(end.date() if end else start.date()))
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status_list = context["user"].status_set.filter(timestamp__gte=start.date(), timestamp__lte=(end.date() if end else start.date()))
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moods = list()
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moods = list() if not daily_averages else dict()
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for status in status_list:
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for status in status_list:
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if status.mood:
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if status.mood:
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moods.append(status.mood.value)
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if daily_averages:
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if not status.timestamp.date() in moods.keys():
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moods[status.timestamp.date()] = [status.mood.value]
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else:
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moods[status.timestamp.date()].append(status.mood.value)
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else:
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moods.append(status.mood.value)
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if daily_averages:
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moods = [sum(entries) / len(entries) for date, entries in moods.items()]
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try:
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try:
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average = sum(moods) / len(moods)
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average = sum(moods) / len(moods)
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@ -62,11 +71,11 @@ def average_mood(context, start, end=None):
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return average
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return average
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@register.simple_tag(takes_context=True)
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@register.simple_tag(takes_context=True)
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def average_mood_weekly(context):
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def average_mood_weekly(context, daily_averages=True):
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now = timezone.now()
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now = timezone.now()
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start = now - timezone.timedelta(days=7)
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start = now - timezone.timedelta(days=7)
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return average_mood(context, start, now)
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return average_mood(context, start, now, daily_averages)
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@register.simple_tag(takes_context=True)
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@register.simple_tag(takes_context=True)
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def most_common_activity(context, start, end=None):
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def most_common_activity(context, start, end=None):
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