def __call__(self):

        bucket = PeriodCollate(
            self._period_start.date,
            self._period_end.date,
            debit_credit_generator,
            store_credit_debit,
            frequency=self._period_size.frequency,
            interval=self._period_size.interval,
        )

        for account in account_walker(self._income + self._expenses, ignore_list=self._ignore_accounts):
            for split in get_splits(account, self._period_start.date, self._period_end.date):
                bucket.store_value(split)

        return_value = self._generate_result()
        credit_values = []
        debit_values = []
        difference_value = []

        for key, value in bucket.container.iteritems():
            time_value = time.mktime(key.timetuple())

            # Have to switch the signs so that the graph will make sense.  In GNUCash the income accounts are debited
            # when paid, and the expense accounts are 'credited' when purchased.
            credit_values.append(dict(date=time_value, value=-value["credit"]))
            debit_values.append(dict(date=time_value, value=-value["debit"]))
            difference_value.append(dict(date=time_value, value=-(value["debit"] + value["credit"])))

        # Income accounts are the debits, and Expense accounts are the credits.
        return_value["data"]["expenses"] = sorted(credit_values, key=lambda s: s["date"])
        return_value["data"]["income"] = sorted(debit_values, key=lambda s: s["date"])
        return_value["data"]["net"] = sorted(difference_value, key=lambda s: s["date"])

        return return_value
    def __call__(self):

        start_of_trend = self._period_start.date
        end_of_trend = self._period_end.date

        asset_bucket = PeriodCollate(start_of_trend, end_of_trend, decimal_generator, split_summation,
                                     frequency=self._period_size.frequency, interval=self._period_size.interval)
        liability_bucket = PeriodCollate(start_of_trend, end_of_trend, decimal_generator, split_summation,
                                         frequency=self._period_size.frequency, interval=self._period_size.interval)
        net_bucket = PeriodCollate(start_of_trend, end_of_trend, decimal_generator, split_summation,
                                   frequency=self._period_size.frequency, interval=self._period_size.interval)

        currency = get_currency()

        # Calculate the asset balances
        for account in account_walker(self._asset_accounts):
            for key, value in asset_bucket.container.iteritems():
                balance = get_balance_on_date(account, key, currency)
                asset_bucket.container[key] += balance

        # Calculate the liability balances
        for account in account_walker(self._liability_accounts):
            for key, value in liability_bucket.container.iteritems():
                balance = get_balance_on_date(account, key, currency)
                liability_bucket.container[key] += balance

        # Now calculate the net values from the difference.
        for key, value in liability_bucket.container.iteritems():
            net_bucket.container[key] = asset_bucket.container[key] + liability_bucket.container[key]

        result = self._generate_result()
        result['data']['assets'] = sorted([dict(date=time.mktime(key.timetuple()), value=value)
                                           for key, value in asset_bucket.container.iteritems()],
                                          key=lambda s: s['date'])
        result['data']['liabilities'] = sorted([dict(date=time.mktime(key.timetuple()), value=-value)
                                                for key, value in liability_bucket.container.iteritems()],
                                               key=lambda s: s['date'])
        result['data']['net'] = sorted([dict(date=time.mktime(key.timetuple()), value=value)
                                        for key, value in net_bucket.container.iteritems()],
                                       key=lambda s: s['date'])

        inflation = get_monthly_inflation()
        starting_point = None
        inflation_data = []
        for record in result['data']['net']:
            if starting_point:
                starting_point += (starting_point * inflation)
            else:
                starting_point = record['value']

            inflation_data.append(dict(date=record['date'], value=starting_point))

        result['data']['inflation'] = inflation_data

        return result
    def __call__(self):

        investment_value = dict()
        buckets = PeriodCollate(self._period_start.date, self._period_end.date,
                                investment_bucket_generator, store_investment, frequency=self._period_size.frequency,
                                interval=self._period_size.interval)

        start_value = Decimal('0.0')
        start_value_date = self._period_start.date - relativedelta(days=1)
        currency = get_currency()

        for account in account_walker(self._investment_accounts, ignore_list=self._ignore_accounts):
            for split in get_splits(account, self._period_start.date, self._period_end.date):
                buckets.store_value(split)

            start_value += get_balance_on_date(account, start_value_date, currency)

            for key in buckets.container.keys():
                date_value = key + relativedelta(months=1) - relativedelta(days=1)
                investment_value[key] = investment_value.get(key, Decimal('0.0')) + get_balance_on_date(account,
                                                                                                        date_value,
                                                                                                        currency)

        results = self._generate_result()
        results['data']['start_value'] = start_value

        results['data']['income'] = sorted(
            [(time.mktime(key.timetuple()), value['income']) for key, value in buckets.container.iteritems()],
            key=itemgetter(0))

        results['data']['money_in'] = sorted(
            [(time.mktime(key.timetuple()), value['money_in']) for key, value in buckets.container.iteritems()],
            key=itemgetter(0))

        results['data']['expense'] = sorted(
            [(time.mktime(key.timetuple()), value['expense']) for key, value in buckets.container.iteritems()],
            key=itemgetter(0))

        results['data']['value'] = sorted(
            [[time.mktime(key.timetuple()), value] for key, value in investment_value.iteritems()],
        )

        results['data']['basis'] = sorted(
            [[time.mktime(key.timetuple()), Decimal('0.0')] for key in buckets.container.keys()],
            key=itemgetter(0)
        )

        monthly_start = start_value
        for index, record in enumerate(results['data']['basis']):
            record[1] += (monthly_start + results['data']['income'][index][1] + results['data']['money_in'][index][1] +
                          results['data']['expense'][index][1])
            monthly_start = record[1]

        return results
    def __call__(self):

        bucket = PeriodCollate(self._start.date, self._end.date, decimal_generator, split_summation,
                               frequency=self._size.frequency, interval=self._size.interval)
        record_count = PeriodCollate(self._start.date, self._end.date, integer_generator, count,
                                     frequency=self._size.frequency, interval=self._size.interval)

        for account in account_walker(self.expenses_base, self.ignore_list):
            for split in get_splits(account, self._start.date, self._end.date):
                bucket.store_value(split)
                record_count.store_value(split)

        return_value = self._generate_result()
        sorted_results = []
        sorted_count_results = []

        for key, value in bucket.container.iteritems():
            sorted_results.append(dict(date=time.mktime(key.timetuple()), value=value))

        for key, value in record_count.container.iteritems():
            sorted_count_results.append(dict(date=time.mktime(key.timetuple()), value=value))

        return_value['data']['expenses'] = sorted(sorted_results, key=lambda s: s['date'])

        if self._show_record_count:
            return_value['data']['count'] = sorted(sorted_count_results, key=lambda s: s['date'])

        return return_value
    def __call__(self):

        bucket = PeriodCollate(self._start.date, self._end.date, decimal_generator, split_summation,
                               frequency=self._size.frequency, interval=self._size.interval)

        for account in account_walker(self.expenses_base, self.ignore_list):
            for split in get_splits(account, self._start.date, self._end.date):
                bucket.store_value(split)

        return_value = self._generate_result()
        results = []

        for key, value in bucket.container.iteritems():
            results.append(float(value))

        return_value['data']['low'] = np.percentile(results, 0)
        return_value['data']['high'] = np.percentile(results, 100)
        return_value['data']['q1'] = np.percentile(results, 25)
        return_value['data']['q2'] = np.percentile(results, 50)
        return_value['data']['q3'] = np.percentile(results, 75)

        return return_value
    def __call__(self):

        bucket = PeriodCollate(self._start.date, self._end.date, debit_credit_generator,
                               store_credit_debit, frequency=self._size.frequency, interval=self._size.interval)

        for account in account_walker(self._account_names):
            for split in get_splits(account, self._start.date, self._end.date):
                bucket.store_value(split)

        return_value = self._generate_result()
        credit_values = []
        debit_values = []
        difference_value = []

        for key, value in bucket.container.iteritems():
            credit_values.append(dict(date=time.mktime(key.timetuple()), value=value['credit']))
            debit_values.append(dict(date=time.mktime(key.timetuple()), value=value['debit']))
            difference_value.append(dict(date=time.mktime(key.timetuple()), value=value['credit'] + value['debit']))

        return_value['data']['credits'] = sorted(credit_values, key=lambda s: s['date'])
        return_value['data']['debits'] = sorted(debit_values, key=lambda s: s['date'])
        return_value['data']['gross'] = sorted(debit_values, key=lambda s: ['date'])

        return return_value