Code Duplication    Length = 547-554 lines in 2 locations

reports/combinedequipmentstatistics.py 1 location

@@ 10-563 (lines=554) @@
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from decimal import *
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class Reporting:
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    @staticmethod
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    def __init__():
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        pass
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    @staticmethod
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    def on_options(req, resp):
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        resp.status = falcon.HTTP_200
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    ####################################################################################################################
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    # PROCEDURES
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    # Step 1: valid parameters
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    # Step 2: query the combined equipment
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    # Step 3: query energy categories
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    # Step 4: query associated points
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    # Step 5: query base period energy input
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    # Step 6: query reporting period energy input
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    # Step 7: query tariff data
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    # Step 8: query associated points data
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    # Step 9: construct the report
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    ####################################################################################################################
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    @staticmethod
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    def on_get(req, resp):
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        print(req.params)
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        combined_equipment_id = req.params.get('combinedequipmentid')
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        period_type = req.params.get('periodtype')
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        base_start_datetime_local = req.params.get('baseperiodstartdatetime')
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        base_end_datetime_local = req.params.get('baseperiodenddatetime')
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        reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime')
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        reporting_end_datetime_local = req.params.get('reportingperiodenddatetime')
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        ################################################################################################################
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        # Step 1: valid parameters
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        ################################################################################################################
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        if combined_equipment_id is None:
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            raise falcon.HTTPError(falcon.HTTP_400,
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                                   title='API.BAD_REQUEST',
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                                   description='API.INVALID_COMBINED_EQUIPMENT_ID')
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        else:
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            combined_equipment_id = str.strip(combined_equipment_id)
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            if not combined_equipment_id.isdigit() or int(combined_equipment_id) <= 0:
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                raise falcon.HTTPError(falcon.HTTP_400,
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                                       title='API.BAD_REQUEST',
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                                       description='API.INVALID_COMBINED_EQUIPMENT_ID')
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        if period_type is None:
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            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
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        else:
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            period_type = str.strip(period_type)
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            if period_type not in ['hourly', 'daily', 'monthly', 'yearly']:
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                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
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        timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6])
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        if config.utc_offset[0] == '-':
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            timezone_offset = -timezone_offset
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        base_start_datetime_utc = None
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        if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0:
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            base_start_datetime_local = str.strip(base_start_datetime_local)
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            try:
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                base_start_datetime_utc = datetime.strptime(base_start_datetime_local,
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                                                            '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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                    timedelta(minutes=timezone_offset)
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            except ValueError:
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                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                       description="API.INVALID_BASE_PERIOD_BEGINS_DATETIME")
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        base_end_datetime_utc = None
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        if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0:
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            base_end_datetime_local = str.strip(base_end_datetime_local)
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            try:
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                base_end_datetime_utc = datetime.strptime(base_end_datetime_local,
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                                                          '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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                    timedelta(minutes=timezone_offset)
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            except ValueError:
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                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                       description="API.INVALID_BASE_PERIOD_ENDS_DATETIME")
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        if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \
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                base_start_datetime_utc >= base_end_datetime_utc:
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            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                   description='API.INVALID_BASE_PERIOD_ENDS_DATETIME')
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        if reporting_start_datetime_local is None:
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            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                   description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
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        else:
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            reporting_start_datetime_local = str.strip(reporting_start_datetime_local)
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            try:
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                reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local,
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                                                                 '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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                    timedelta(minutes=timezone_offset)
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            except ValueError:
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                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                       description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
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        if reporting_end_datetime_local is None:
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            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                   description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
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        else:
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            reporting_end_datetime_local = str.strip(reporting_end_datetime_local)
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            try:
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                reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local,
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                                                               '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
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                    timedelta(minutes=timezone_offset)
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            except ValueError:
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                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                       description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
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        if reporting_start_datetime_utc >= reporting_end_datetime_utc:
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            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
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                                   description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME')
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        ################################################################################################################
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        # Step 2: query the combined equipment
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        ################################################################################################################
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        cnx_system = mysql.connector.connect(**config.myems_system_db)
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        cursor_system = cnx_system.cursor()
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        cnx_energy = mysql.connector.connect(**config.myems_energy_db)
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        cursor_energy = cnx_energy.cursor()
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        cnx_historical = mysql.connector.connect(**config.myems_historical_db)
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        cursor_historical = cnx_historical.cursor()
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        cursor_system.execute(" SELECT id, name, cost_center_id "
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                              " FROM tbl_combined_equipments "
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                              " WHERE id = %s ", (combined_equipment_id,))
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        row_combined_equipment = cursor_system.fetchone()
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        if row_combined_equipment is None:
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            if cursor_system:
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                cursor_system.close()
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            if cnx_system:
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                cnx_system.disconnect()
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            if cursor_energy:
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                cursor_energy.close()
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            if cnx_energy:
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                cnx_energy.disconnect()
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            if cnx_historical:
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                cnx_historical.close()
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            if cursor_historical:
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                cursor_historical.disconnect()
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            raise falcon.HTTPError(falcon.HTTP_404,
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                                   title='API.NOT_FOUND',
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                                   description='API.COMBINED_EQUIPMENT_NOT_FOUND')
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        combined_equipment = dict()
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        combined_equipment['id'] = row_combined_equipment[0]
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        combined_equipment['name'] = row_combined_equipment[1]
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        combined_equipment['cost_center_id'] = row_combined_equipment[2]
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        ################################################################################################################
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        # Step 3: query energy categories
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        ################################################################################################################
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        energy_category_set = set()
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        # query energy categories in base period
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        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
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                              " FROM tbl_combined_equipment_input_category_hourly "
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                              " WHERE combined_equipment_id = %s "
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                              "     AND start_datetime_utc >= %s "
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                              "     AND start_datetime_utc < %s ",
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                              (combined_equipment['id'], base_start_datetime_utc, base_end_datetime_utc))
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        rows_energy_categories = cursor_energy.fetchall()
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        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
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            for row_energy_category in rows_energy_categories:
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                energy_category_set.add(row_energy_category[0])
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        # query energy categories in reporting period
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        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
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                              " FROM tbl_combined_equipment_input_category_hourly "
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                              " WHERE combined_equipment_id = %s "
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                              "     AND start_datetime_utc >= %s "
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                              "     AND start_datetime_utc < %s ",
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                              (combined_equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc))
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        rows_energy_categories = cursor_energy.fetchall()
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        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
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            for row_energy_category in rows_energy_categories:
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                energy_category_set.add(row_energy_category[0])
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        # query all energy categories in base period and reporting period
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        cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e "
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                              " FROM tbl_energy_categories "
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                              " ORDER BY id ", )
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        rows_energy_categories = cursor_system.fetchall()
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        if rows_energy_categories is None or len(rows_energy_categories) == 0:
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            if cursor_system:
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                cursor_system.close()
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            if cnx_system:
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                cnx_system.disconnect()
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            if cursor_energy:
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                cursor_energy.close()
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            if cnx_energy:
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                cnx_energy.disconnect()
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            if cnx_historical:
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                cnx_historical.close()
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            if cursor_historical:
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                cursor_historical.disconnect()
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            raise falcon.HTTPError(falcon.HTTP_404,
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                                   title='API.NOT_FOUND',
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                                   description='API.ENERGY_CATEGORY_NOT_FOUND')
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        energy_category_dict = dict()
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        for row_energy_category in rows_energy_categories:
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            if row_energy_category[0] in energy_category_set:
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                energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1],
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                                                                "unit_of_measure": row_energy_category[2],
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                                                                "kgce": row_energy_category[3],
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                                                                "kgco2e": row_energy_category[4]}
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        ################################################################################################################
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        # Step 4: query associated points
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        ################################################################################################################
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        point_list = list()
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        cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type  "
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                              " FROM tbl_combined_equipments e, tbl_combined_equipments_parameters ep, tbl_points p "
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                              " WHERE e.id = %s AND e.id = ep.combined_equipment_id AND ep.parameter_type = 'point' "
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                              "       AND ep.point_id = p.id "
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                              " ORDER BY p.id ", (combined_equipment['id'],))
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        rows_points = cursor_system.fetchall()
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        if rows_points is not None and len(rows_points) > 0:
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            for row in rows_points:
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                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
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        ################################################################################################################
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        # Step 5: query base period energy input
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        ################################################################################################################
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        base = dict()
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        if energy_category_set is not None and len(energy_category_set) > 0:
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            for energy_category_id in energy_category_set:
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                base[energy_category_id] = dict()
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                base[energy_category_id]['timestamps'] = list()
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                base[energy_category_id]['values'] = list()
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                base[energy_category_id]['subtotal'] = Decimal(0.0)
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                base[energy_category_id]['mean'] = None
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                base[energy_category_id]['median'] = None
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                base[energy_category_id]['minimum'] = None
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                base[energy_category_id]['maximum'] = None
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                base[energy_category_id]['stdev'] = None
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                base[energy_category_id]['variance'] = None
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                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
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                                      " FROM tbl_combined_equipment_input_category_hourly "
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                                      " WHERE combined_equipment_id = %s "
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                                      "     AND energy_category_id = %s "
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                                      "     AND start_datetime_utc >= %s "
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                                      "     AND start_datetime_utc < %s "
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                                      " ORDER BY start_datetime_utc ",
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                                      (combined_equipment['id'],
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                                       energy_category_id,
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                                       base_start_datetime_utc,
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                                       base_end_datetime_utc))
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                rows_combined_equipment_hourly = cursor_energy.fetchall()
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                rows_combined_equipment_periodically, \
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                    base[energy_category_id]['mean'], \
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                    base[energy_category_id]['median'], \
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                    base[energy_category_id]['minimum'], \
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                    base[energy_category_id]['maximum'], \
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                    base[energy_category_id]['stdev'], \
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                    base[energy_category_id]['variance'] = \
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                    utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly,
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                                                               base_start_datetime_utc,
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                                                               base_end_datetime_utc,
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                                                               period_type)
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                for row_combined_equipment_periodically in rows_combined_equipment_periodically:
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                    current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
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                                             timedelta(minutes=timezone_offset)
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                    if period_type == 'hourly':
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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                    elif period_type == 'daily':
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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                    elif period_type == 'monthly':
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                        current_datetime = current_datetime_local.strftime('%Y-%m')
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                    elif period_type == 'yearly':
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                        current_datetime = current_datetime_local.strftime('%Y')
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                    actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \
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                        else row_combined_equipment_periodically[1]
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                    base[energy_category_id]['timestamps'].append(current_datetime)
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                    base[energy_category_id]['values'].append(actual_value)
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                    base[energy_category_id]['subtotal'] += actual_value
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        ################################################################################################################
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        # Step 6: query reporting period energy input
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        ################################################################################################################
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        reporting = dict()
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        if energy_category_set is not None and len(energy_category_set) > 0:
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            for energy_category_id in energy_category_set:
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                reporting[energy_category_id] = dict()
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                reporting[energy_category_id]['timestamps'] = list()
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                reporting[energy_category_id]['values'] = list()
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                reporting[energy_category_id]['subtotal'] = Decimal(0.0)
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                reporting[energy_category_id]['mean'] = None
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                reporting[energy_category_id]['median'] = None
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                reporting[energy_category_id]['minimum'] = None
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                reporting[energy_category_id]['maximum'] = None
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                reporting[energy_category_id]['stdev'] = None
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                reporting[energy_category_id]['variance'] = None
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                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
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                                      " FROM tbl_combined_equipment_input_category_hourly "
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                                      " WHERE combined_equipment_id = %s "
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                                      "     AND energy_category_id = %s "
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                                      "     AND start_datetime_utc >= %s "
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                                      "     AND start_datetime_utc < %s "
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                                      " ORDER BY start_datetime_utc ",
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                                      (combined_equipment['id'],
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                                       energy_category_id,
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                                       reporting_start_datetime_utc,
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                                       reporting_end_datetime_utc))
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                rows_combined_equipment_hourly = cursor_energy.fetchall()
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                rows_combined_equipment_periodically, \
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                    reporting[energy_category_id]['mean'], \
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                    reporting[energy_category_id]['median'], \
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                    reporting[energy_category_id]['minimum'], \
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                    reporting[energy_category_id]['maximum'], \
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                    reporting[energy_category_id]['stdev'], \
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                    reporting[energy_category_id]['variance'] = \
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                    utilities.statistics_hourly_data_by_period(rows_combined_equipment_hourly,
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                                                               reporting_start_datetime_utc,
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                                                               reporting_end_datetime_utc,
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                                                               period_type)
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                for row_combined_equipment_periodically in rows_combined_equipment_periodically:
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                    current_datetime_local = row_combined_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
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                                             timedelta(minutes=timezone_offset)
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                    if period_type == 'hourly':
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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                    elif period_type == 'daily':
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
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                    elif period_type == 'monthly':
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                        current_datetime = current_datetime_local.strftime('%Y-%m')
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                    elif period_type == 'yearly':
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                        current_datetime = current_datetime_local.strftime('%Y')
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                    actual_value = Decimal(0.0) if row_combined_equipment_periodically[1] is None \
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                        else row_combined_equipment_periodically[1]
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                    reporting[energy_category_id]['timestamps'].append(current_datetime)
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                    reporting[energy_category_id]['values'].append(actual_value)
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                    reporting[energy_category_id]['subtotal'] += actual_value
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        ################################################################################################################
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        # Step 7: query tariff data
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        ################################################################################################################
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        parameters_data = dict()
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        parameters_data['names'] = list()
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        parameters_data['timestamps'] = list()
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        parameters_data['values'] = list()
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        if energy_category_set is not None and len(energy_category_set) > 0:
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            for energy_category_id in energy_category_set:
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                energy_category_tariff_dict = \
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                    utilities.get_energy_category_tariffs(combined_equipment['cost_center_id'],
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                                                          energy_category_id,
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                                                          reporting_start_datetime_utc,
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                                                          reporting_end_datetime_utc)
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                tariff_timestamp_list = list()
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                tariff_value_list = list()
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                for k, v in energy_category_tariff_dict.items():
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                    # convert k from utc to local
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                    k = k + timedelta(minutes=timezone_offset)
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                    tariff_timestamp_list.append(k.isoformat()[0:19][0:19])
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                    tariff_value_list.append(v)
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                parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name'])
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                parameters_data['timestamps'].append(tariff_timestamp_list)
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                parameters_data['values'].append(tariff_value_list)
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        ################################################################################################################
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        # Step 8: query associated points data
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        ################################################################################################################
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        for point in point_list:
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            point_values = []
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            point_timestamps = []
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            if point['object_type'] == 'ANALOG_VALUE':
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                query = (" SELECT utc_date_time, actual_value "
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                         " FROM tbl_analog_value "
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                         " WHERE point_id = %s "
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                         "       AND utc_date_time BETWEEN %s AND %s "
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                         " ORDER BY utc_date_time ")
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                cursor_historical.execute(query, (point['id'],
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                                                  reporting_start_datetime_utc,
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                                                  reporting_end_datetime_utc))
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                rows = cursor_historical.fetchall()
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                if rows is not None and len(rows) > 0:
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                    for row in rows:
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                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
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                                                 timedelta(minutes=timezone_offset)
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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                        point_timestamps.append(current_datetime)
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                        point_values.append(row[1])
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            elif point['object_type'] == 'ENERGY_VALUE':
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                query = (" SELECT utc_date_time, actual_value "
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                         " FROM tbl_energy_value "
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                         " WHERE point_id = %s "
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                         "       AND utc_date_time BETWEEN %s AND %s "
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                         " ORDER BY utc_date_time ")
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                cursor_historical.execute(query, (point['id'],
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                                                  reporting_start_datetime_utc,
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                                                  reporting_end_datetime_utc))
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                rows = cursor_historical.fetchall()
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                if rows is not None and len(rows) > 0:
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                    for row in rows:
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                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
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                                                 timedelta(minutes=timezone_offset)
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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                        point_timestamps.append(current_datetime)
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                        point_values.append(row[1])
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            elif point['object_type'] == 'DIGITAL_VALUE':
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                query = (" SELECT utc_date_time, actual_value "
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                         " FROM tbl_digital_value "
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                         " WHERE point_id = %s "
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                         "       AND utc_date_time BETWEEN %s AND %s ")
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                cursor_historical.execute(query, (point['id'],
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                                                  reporting_start_datetime_utc,
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                                                  reporting_end_datetime_utc))
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                rows = cursor_historical.fetchall()
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                if rows is not None and len(rows) > 0:
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                    for row in rows:
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                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
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                                                 timedelta(minutes=timezone_offset)
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                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
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                        point_timestamps.append(current_datetime)
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                        point_values.append(row[1])
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            parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
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            parameters_data['timestamps'].append(point_timestamps)
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            parameters_data['values'].append(point_values)
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        ################################################################################################################
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        # Step 9: construct the report
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        ################################################################################################################
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        if cursor_system:
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            cursor_system.close()
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        if cnx_system:
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            cnx_system.disconnect()
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        if cursor_energy:
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            cursor_energy.close()
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        if cnx_energy:
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            cnx_energy.disconnect()
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        result = dict()
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        result['combined_equipment'] = dict()
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        result['combined_equipment']['name'] = combined_equipment['name']
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        result['base_period'] = dict()
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        result['base_period']['names'] = list()
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        result['base_period']['units'] = list()
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        result['base_period']['timestamps'] = list()
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        result['base_period']['values'] = list()
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        result['base_period']['subtotals'] = list()
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        result['base_period']['means'] = list()
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        result['base_period']['medians'] = list()
473
        result['base_period']['minimums'] = list()
474
        result['base_period']['maximums'] = list()
475
        result['base_period']['stdevs'] = list()
476
        result['base_period']['variances'] = list()
477
478
        if energy_category_set is not None and len(energy_category_set) > 0:
479
            for energy_category_id in energy_category_set:
480
                result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
481
                result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
482
                result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
483
                result['base_period']['values'].append(base[energy_category_id]['values'])
484
                result['base_period']['subtotals'].append(base[energy_category_id]['subtotal'])
485
                result['base_period']['means'].append(base[energy_category_id]['mean'])
486
                result['base_period']['medians'].append(base[energy_category_id]['median'])
487
                result['base_period']['minimums'].append(base[energy_category_id]['minimum'])
488
                result['base_period']['maximums'].append(base[energy_category_id]['maximum'])
489
                result['base_period']['stdevs'].append(base[energy_category_id]['stdev'])
490
                result['base_period']['variances'].append(base[energy_category_id]['variance'])
491
492
        result['reporting_period'] = dict()
493
        result['reporting_period']['names'] = list()
494
        result['reporting_period']['energy_category_ids'] = list()
495
        result['reporting_period']['units'] = list()
496
        result['reporting_period']['timestamps'] = list()
497
        result['reporting_period']['values'] = list()
498
        result['reporting_period']['subtotals'] = list()
499
        result['reporting_period']['means'] = list()
500
        result['reporting_period']['means_increment_rate'] = list()
501
        result['reporting_period']['medians'] = list()
502
        result['reporting_period']['medians_increment_rate'] = list()
503
        result['reporting_period']['minimums'] = list()
504
        result['reporting_period']['minimums_increment_rate'] = list()
505
        result['reporting_period']['maximums'] = list()
506
        result['reporting_period']['maximums_increment_rate'] = list()
507
        result['reporting_period']['stdevs'] = list()
508
        result['reporting_period']['stdevs_increment_rate'] = list()
509
        result['reporting_period']['variances'] = list()
510
        result['reporting_period']['variances_increment_rate'] = list()
511
512
        if energy_category_set is not None and len(energy_category_set) > 0:
513
            for energy_category_id in energy_category_set:
514
                result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
515
                result['reporting_period']['energy_category_ids'].append(energy_category_id)
516
                result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
517
                result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
518
                result['reporting_period']['values'].append(reporting[energy_category_id]['values'])
519
                result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal'])
520
                result['reporting_period']['means'].append(reporting[energy_category_id]['mean'])
521
                result['reporting_period']['means_increment_rate'].append(
522
                    (reporting[energy_category_id]['mean'] - base[energy_category_id]['mean']) /
523
                    base[energy_category_id]['mean'] if (base[energy_category_id]['mean'] is not None and
524
                                                         base[energy_category_id]['mean'] > Decimal(0.0))
525
                    else None)
526
                result['reporting_period']['medians'].append(reporting[energy_category_id]['median'])
527
                result['reporting_period']['medians_increment_rate'].append(
528
                    (reporting[energy_category_id]['median'] - base[energy_category_id]['median']) /
529
                    base[energy_category_id]['median'] if (base[energy_category_id]['median'] is not None and
530
                                                           base[energy_category_id]['median'] > Decimal(0.0))
531
                    else None)
532
                result['reporting_period']['minimums'].append(reporting[energy_category_id]['minimum'])
533
                result['reporting_period']['minimums_increment_rate'].append(
534
                    (reporting[energy_category_id]['minimum'] - base[energy_category_id]['minimum']) /
535
                    base[energy_category_id]['minimum'] if (base[energy_category_id]['minimum'] is not None and
536
                                                            base[energy_category_id]['minimum'] > Decimal(0.0))
537
                    else None)
538
                result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum'])
539
                result['reporting_period']['maximums_increment_rate'].append(
540
                    (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) /
541
                    base[energy_category_id]['maximum'] if (base[energy_category_id]['maximum'] is not None and
542
                                                            base[energy_category_id]['maximum'] > Decimal(0.0))
543
                    else None)
544
                result['reporting_period']['stdevs'].append(reporting[energy_category_id]['stdev'])
545
                result['reporting_period']['stdevs_increment_rate'].append(
546
                    (reporting[energy_category_id]['stdev'] - base[energy_category_id]['stdev']) /
547
                    base[energy_category_id]['stdev'] if (base[energy_category_id]['stdev'] is not None and
548
                                                          base[energy_category_id]['stdev'] > Decimal(0.0))
549
                    else None)
550
                result['reporting_period']['variances'].append(reporting[energy_category_id]['variance'])
551
                result['reporting_period']['variances_increment_rate'].append(
552
                    (reporting[energy_category_id]['variance'] - base[energy_category_id]['variance']) /
553
                    base[energy_category_id]['variance'] if (base[energy_category_id]['variance'] is not None and
554
                                                             base[energy_category_id]['variance'] > Decimal(0.0))
555
                    else None)
556
557
        result['parameters'] = {
558
            "names": parameters_data['names'],
559
            "timestamps": parameters_data['timestamps'],
560
            "values": parameters_data['values']
561
        }
562
563
        resp.body = json.dumps(result)
564

reports/equipmentstatistics.py 1 location

@@ 10-556 (lines=547) @@
7
from decimal import *
8
9
10
class Reporting:
11
    @staticmethod
12
    def __init__():
13
        pass
14
15
    @staticmethod
16
    def on_options(req, resp):
17
        resp.status = falcon.HTTP_200
18
19
    ####################################################################################################################
20
    # PROCEDURES
21
    # Step 1: valid parameters
22
    # Step 2: query the equipment
23
    # Step 3: query energy categories
24
    # Step 4: query associated points
25
    # Step 5: query base period energy input
26
    # Step 6: query reporting period energy input
27
    # Step 7: query tariff data
28
    # Step 8: query associated points data
29
    # Step 9: construct the report
30
    ####################################################################################################################
31
    @staticmethod
32
    def on_get(req, resp):
33
        print(req.params)
34
        equipment_id = req.params.get('equipmentid')
35
        period_type = req.params.get('periodtype')
36
        base_start_datetime_local = req.params.get('baseperiodstartdatetime')
37
        base_end_datetime_local = req.params.get('baseperiodenddatetime')
38
        reporting_start_datetime_local = req.params.get('reportingperiodstartdatetime')
39
        reporting_end_datetime_local = req.params.get('reportingperiodenddatetime')
40
41
        ################################################################################################################
42
        # Step 1: valid parameters
43
        ################################################################################################################
44
        if equipment_id is None:
45
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_EQUIPMENT_ID')
46
        else:
47
            equipment_id = str.strip(equipment_id)
48
            if not equipment_id.isdigit() or int(equipment_id) <= 0:
49
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_EQUIPMENT_ID')
50
51
        if period_type is None:
52
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
53
        else:
54
            period_type = str.strip(period_type)
55
            if period_type not in ['hourly', 'daily', 'monthly', 'yearly']:
56
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST', description='API.INVALID_PERIOD_TYPE')
57
58
        timezone_offset = int(config.utc_offset[1:3]) * 60 + int(config.utc_offset[4:6])
59
        if config.utc_offset[0] == '-':
60
            timezone_offset = -timezone_offset
61
62
        base_start_datetime_utc = None
63
        if base_start_datetime_local is not None and len(str.strip(base_start_datetime_local)) > 0:
64
            base_start_datetime_local = str.strip(base_start_datetime_local)
65
            try:
66
                base_start_datetime_utc = datetime.strptime(base_start_datetime_local,
67
                                                            '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
68
                    timedelta(minutes=timezone_offset)
69
            except ValueError:
70
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
71
                                       description="API.INVALID_BASE_PERIOD_BEGINS_DATETIME")
72
73
        base_end_datetime_utc = None
74
        if base_end_datetime_local is not None and len(str.strip(base_end_datetime_local)) > 0:
75
            base_end_datetime_local = str.strip(base_end_datetime_local)
76
            try:
77
                base_end_datetime_utc = datetime.strptime(base_end_datetime_local,
78
                                                          '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
79
                    timedelta(minutes=timezone_offset)
80
            except ValueError:
81
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
82
                                       description="API.INVALID_BASE_PERIOD_ENDS_DATETIME")
83
84
        if base_start_datetime_utc is not None and base_end_datetime_utc is not None and \
85
                base_start_datetime_utc >= base_end_datetime_utc:
86
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
87
                                   description='API.INVALID_BASE_PERIOD_ENDS_DATETIME')
88
89
        if reporting_start_datetime_local is None:
90
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
91
                                   description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
92
        else:
93
            reporting_start_datetime_local = str.strip(reporting_start_datetime_local)
94
            try:
95
                reporting_start_datetime_utc = datetime.strptime(reporting_start_datetime_local,
96
                                                                 '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
97
                    timedelta(minutes=timezone_offset)
98
            except ValueError:
99
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
100
                                       description="API.INVALID_REPORTING_PERIOD_BEGINS_DATETIME")
101
102
        if reporting_end_datetime_local is None:
103
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
104
                                   description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
105
        else:
106
            reporting_end_datetime_local = str.strip(reporting_end_datetime_local)
107
            try:
108
                reporting_end_datetime_utc = datetime.strptime(reporting_end_datetime_local,
109
                                                               '%Y-%m-%dT%H:%M:%S').replace(tzinfo=timezone.utc) - \
110
                    timedelta(minutes=timezone_offset)
111
            except ValueError:
112
                raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
113
                                       description="API.INVALID_REPORTING_PERIOD_ENDS_DATETIME")
114
115
        if reporting_start_datetime_utc >= reporting_end_datetime_utc:
116
            raise falcon.HTTPError(falcon.HTTP_400, title='API.BAD_REQUEST',
117
                                   description='API.INVALID_REPORTING_PERIOD_ENDS_DATETIME')
118
119
        ################################################################################################################
120
        # Step 2: query the equipment
121
        ################################################################################################################
122
        cnx_system = mysql.connector.connect(**config.myems_system_db)
123
        cursor_system = cnx_system.cursor()
124
125
        cnx_energy = mysql.connector.connect(**config.myems_energy_db)
126
        cursor_energy = cnx_energy.cursor()
127
128
        cnx_historical = mysql.connector.connect(**config.myems_historical_db)
129
        cursor_historical = cnx_historical.cursor()
130
131
        cursor_system.execute(" SELECT id, name, cost_center_id "
132
                              " FROM tbl_equipments "
133
                              " WHERE id = %s ", (equipment_id,))
134
        row_equipment = cursor_system.fetchone()
135
        if row_equipment is None:
136
            if cursor_system:
137
                cursor_system.close()
138
            if cnx_system:
139
                cnx_system.disconnect()
140
141
            if cursor_energy:
142
                cursor_energy.close()
143
            if cnx_energy:
144
                cnx_energy.disconnect()
145
146
            if cnx_historical:
147
                cnx_historical.close()
148
            if cursor_historical:
149
                cursor_historical.disconnect()
150
            raise falcon.HTTPError(falcon.HTTP_404, title='API.NOT_FOUND', description='API.EQUIPMENT_NOT_FOUND')
151
152
        equipment = dict()
153
        equipment['id'] = row_equipment[0]
154
        equipment['name'] = row_equipment[1]
155
        equipment['cost_center_id'] = row_equipment[2]
156
157
        ################################################################################################################
158
        # Step 3: query energy categories
159
        ################################################################################################################
160
        energy_category_set = set()
161
        # query energy categories in base period
162
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
163
                              " FROM tbl_equipment_input_category_hourly "
164
                              " WHERE equipment_id = %s "
165
                              "     AND start_datetime_utc >= %s "
166
                              "     AND start_datetime_utc < %s ",
167
                              (equipment['id'], base_start_datetime_utc, base_end_datetime_utc))
168
        rows_energy_categories = cursor_energy.fetchall()
169
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
170
            for row_energy_category in rows_energy_categories:
171
                energy_category_set.add(row_energy_category[0])
172
173
        # query energy categories in reporting period
174
        cursor_energy.execute(" SELECT DISTINCT(energy_category_id) "
175
                              " FROM tbl_equipment_input_category_hourly "
176
                              " WHERE equipment_id = %s "
177
                              "     AND start_datetime_utc >= %s "
178
                              "     AND start_datetime_utc < %s ",
179
                              (equipment['id'], reporting_start_datetime_utc, reporting_end_datetime_utc))
180
        rows_energy_categories = cursor_energy.fetchall()
181
        if rows_energy_categories is not None or len(rows_energy_categories) > 0:
182
            for row_energy_category in rows_energy_categories:
183
                energy_category_set.add(row_energy_category[0])
184
185
        # query all energy categories in base period and reporting period
186
        cursor_system.execute(" SELECT id, name, unit_of_measure, kgce, kgco2e "
187
                              " FROM tbl_energy_categories "
188
                              " ORDER BY id ", )
189
        rows_energy_categories = cursor_system.fetchall()
190
        if rows_energy_categories is None or len(rows_energy_categories) == 0:
191
            if cursor_system:
192
                cursor_system.close()
193
            if cnx_system:
194
                cnx_system.disconnect()
195
196
            if cursor_energy:
197
                cursor_energy.close()
198
            if cnx_energy:
199
                cnx_energy.disconnect()
200
201
            if cnx_historical:
202
                cnx_historical.close()
203
            if cursor_historical:
204
                cursor_historical.disconnect()
205
            raise falcon.HTTPError(falcon.HTTP_404,
206
                                   title='API.NOT_FOUND',
207
                                   description='API.ENERGY_CATEGORY_NOT_FOUND')
208
        energy_category_dict = dict()
209
        for row_energy_category in rows_energy_categories:
210
            if row_energy_category[0] in energy_category_set:
211
                energy_category_dict[row_energy_category[0]] = {"name": row_energy_category[1],
212
                                                                "unit_of_measure": row_energy_category[2],
213
                                                                "kgce": row_energy_category[3],
214
                                                                "kgco2e": row_energy_category[4]}
215
216
        ################################################################################################################
217
        # Step 4: query associated points
218
        ################################################################################################################
219
        point_list = list()
220
        cursor_system.execute(" SELECT p.id, p.name, p.units, p.object_type  "
221
                              " FROM tbl_equipments e, tbl_equipments_parameters ep, tbl_points p "
222
                              " WHERE e.id = %s AND e.id = ep.equipment_id AND ep.parameter_type = 'point' "
223
                              "       AND ep.point_id = p.id "
224
                              " ORDER BY p.id ", (equipment['id'],))
225
        rows_points = cursor_system.fetchall()
226
        if rows_points is not None and len(rows_points) > 0:
227
            for row in rows_points:
228
                point_list.append({"id": row[0], "name": row[1], "units": row[2], "object_type": row[3]})
229
230
        ################################################################################################################
231
        # Step 5: query base period energy input
232
        ################################################################################################################
233
        base = dict()
234
        if energy_category_set is not None and len(energy_category_set) > 0:
235
            for energy_category_id in energy_category_set:
236
                base[energy_category_id] = dict()
237
                base[energy_category_id]['timestamps'] = list()
238
                base[energy_category_id]['values'] = list()
239
                base[energy_category_id]['subtotal'] = Decimal(0.0)
240
                base[energy_category_id]['mean'] = None
241
                base[energy_category_id]['median'] = None
242
                base[energy_category_id]['minimum'] = None
243
                base[energy_category_id]['maximum'] = None
244
                base[energy_category_id]['stdev'] = None
245
                base[energy_category_id]['variance'] = None
246
247
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
248
                                      " FROM tbl_equipment_input_category_hourly "
249
                                      " WHERE equipment_id = %s "
250
                                      "     AND energy_category_id = %s "
251
                                      "     AND start_datetime_utc >= %s "
252
                                      "     AND start_datetime_utc < %s "
253
                                      " ORDER BY start_datetime_utc ",
254
                                      (equipment['id'],
255
                                       energy_category_id,
256
                                       base_start_datetime_utc,
257
                                       base_end_datetime_utc))
258
                rows_equipment_hourly = cursor_energy.fetchall()
259
260
                rows_equipment_periodically, \
261
                    base[energy_category_id]['mean'], \
262
                    base[energy_category_id]['median'], \
263
                    base[energy_category_id]['minimum'], \
264
                    base[energy_category_id]['maximum'], \
265
                    base[energy_category_id]['stdev'], \
266
                    base[energy_category_id]['variance'] = \
267
                    utilities.statistics_hourly_data_by_period(rows_equipment_hourly,
268
                                                               base_start_datetime_utc,
269
                                                               base_end_datetime_utc,
270
                                                               period_type)
271
272
                for row_equipment_periodically in rows_equipment_periodically:
273
                    current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
274
                                             timedelta(minutes=timezone_offset)
275
                    if period_type == 'hourly':
276
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
277
                    elif period_type == 'daily':
278
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
279
                    elif period_type == 'monthly':
280
                        current_datetime = current_datetime_local.strftime('%Y-%m')
281
                    elif period_type == 'yearly':
282
                        current_datetime = current_datetime_local.strftime('%Y')
283
284
                    actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \
285
                        else row_equipment_periodically[1]
286
                    base[energy_category_id]['timestamps'].append(current_datetime)
287
                    base[energy_category_id]['values'].append(actual_value)
288
                    base[energy_category_id]['subtotal'] += actual_value
289
290
        ################################################################################################################
291
        # Step 6: query reporting period energy input
292
        ################################################################################################################
293
        reporting = dict()
294
        if energy_category_set is not None and len(energy_category_set) > 0:
295
            for energy_category_id in energy_category_set:
296
                reporting[energy_category_id] = dict()
297
                reporting[energy_category_id]['timestamps'] = list()
298
                reporting[energy_category_id]['values'] = list()
299
                reporting[energy_category_id]['subtotal'] = Decimal(0.0)
300
                reporting[energy_category_id]['mean'] = None
301
                reporting[energy_category_id]['median'] = None
302
                reporting[energy_category_id]['minimum'] = None
303
                reporting[energy_category_id]['maximum'] = None
304
                reporting[energy_category_id]['stdev'] = None
305
                reporting[energy_category_id]['variance'] = None
306
307
                cursor_energy.execute(" SELECT start_datetime_utc, actual_value "
308
                                      " FROM tbl_equipment_input_category_hourly "
309
                                      " WHERE equipment_id = %s "
310
                                      "     AND energy_category_id = %s "
311
                                      "     AND start_datetime_utc >= %s "
312
                                      "     AND start_datetime_utc < %s "
313
                                      " ORDER BY start_datetime_utc ",
314
                                      (equipment['id'],
315
                                       energy_category_id,
316
                                       reporting_start_datetime_utc,
317
                                       reporting_end_datetime_utc))
318
                rows_equipment_hourly = cursor_energy.fetchall()
319
320
                rows_equipment_periodically, \
321
                    reporting[energy_category_id]['mean'], \
322
                    reporting[energy_category_id]['median'], \
323
                    reporting[energy_category_id]['minimum'], \
324
                    reporting[energy_category_id]['maximum'], \
325
                    reporting[energy_category_id]['stdev'], \
326
                    reporting[energy_category_id]['variance'] = \
327
                    utilities.statistics_hourly_data_by_period(rows_equipment_hourly,
328
                                                               reporting_start_datetime_utc,
329
                                                               reporting_end_datetime_utc,
330
                                                               period_type)
331
332
                for row_equipment_periodically in rows_equipment_periodically:
333
                    current_datetime_local = row_equipment_periodically[0].replace(tzinfo=timezone.utc) + \
334
                                             timedelta(minutes=timezone_offset)
335
                    if period_type == 'hourly':
336
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
337
                    elif period_type == 'daily':
338
                        current_datetime = current_datetime_local.strftime('%Y-%m-%d')
339
                    elif period_type == 'monthly':
340
                        current_datetime = current_datetime_local.strftime('%Y-%m')
341
                    elif period_type == 'yearly':
342
                        current_datetime = current_datetime_local.strftime('%Y')
343
344
                    actual_value = Decimal(0.0) if row_equipment_periodically[1] is None \
345
                        else row_equipment_periodically[1]
346
                    reporting[energy_category_id]['timestamps'].append(current_datetime)
347
                    reporting[energy_category_id]['values'].append(actual_value)
348
                    reporting[energy_category_id]['subtotal'] += actual_value
349
350
        ################################################################################################################
351
        # Step 7: query tariff data
352
        ################################################################################################################
353
        parameters_data = dict()
354
        parameters_data['names'] = list()
355
        parameters_data['timestamps'] = list()
356
        parameters_data['values'] = list()
357
        if energy_category_set is not None and len(energy_category_set) > 0:
358
            for energy_category_id in energy_category_set:
359
                energy_category_tariff_dict = utilities.get_energy_category_tariffs(equipment['cost_center_id'],
360
                                                                                    energy_category_id,
361
                                                                                    reporting_start_datetime_utc,
362
                                                                                    reporting_end_datetime_utc)
363
                tariff_timestamp_list = list()
364
                tariff_value_list = list()
365
                for k, v in energy_category_tariff_dict.items():
366
                    # convert k from utc to local
367
                    k = k + timedelta(minutes=timezone_offset)
368
                    tariff_timestamp_list.append(k.isoformat()[0:19][0:19])
369
                    tariff_value_list.append(v)
370
371
                parameters_data['names'].append('TARIFF-' + energy_category_dict[energy_category_id]['name'])
372
                parameters_data['timestamps'].append(tariff_timestamp_list)
373
                parameters_data['values'].append(tariff_value_list)
374
375
        ################################################################################################################
376
        # Step 8: query associated points data
377
        ################################################################################################################
378
        for point in point_list:
379
            point_values = []
380
            point_timestamps = []
381
            if point['object_type'] == 'ANALOG_VALUE':
382
                query = (" SELECT utc_date_time, actual_value "
383
                         " FROM tbl_analog_value "
384
                         " WHERE point_id = %s "
385
                         "       AND utc_date_time BETWEEN %s AND %s "
386
                         " ORDER BY utc_date_time ")
387
                cursor_historical.execute(query, (point['id'],
388
                                                  reporting_start_datetime_utc,
389
                                                  reporting_end_datetime_utc))
390
                rows = cursor_historical.fetchall()
391
392
                if rows is not None and len(rows) > 0:
393
                    for row in rows:
394
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
395
                                                 timedelta(minutes=timezone_offset)
396
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
397
                        point_timestamps.append(current_datetime)
398
                        point_values.append(row[1])
399
400
            elif point['object_type'] == 'ENERGY_VALUE':
401
                query = (" SELECT utc_date_time, actual_value "
402
                         " FROM tbl_energy_value "
403
                         " WHERE point_id = %s "
404
                         "       AND utc_date_time BETWEEN %s AND %s "
405
                         " ORDER BY utc_date_time ")
406
                cursor_historical.execute(query, (point['id'],
407
                                                  reporting_start_datetime_utc,
408
                                                  reporting_end_datetime_utc))
409
                rows = cursor_historical.fetchall()
410
411
                if rows is not None and len(rows) > 0:
412
                    for row in rows:
413
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
414
                                                 timedelta(minutes=timezone_offset)
415
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
416
                        point_timestamps.append(current_datetime)
417
                        point_values.append(row[1])
418
            elif point['object_type'] == 'DIGITAL_VALUE':
419
                query = (" SELECT utc_date_time, actual_value "
420
                         " FROM tbl_digital_value "
421
                         " WHERE point_id = %s "
422
                         "       AND utc_date_time BETWEEN %s AND %s ")
423
                cursor_historical.execute(query, (point['id'],
424
                                                  reporting_start_datetime_utc,
425
                                                  reporting_end_datetime_utc))
426
                rows = cursor_historical.fetchall()
427
428
                if rows is not None and len(rows) > 0:
429
                    for row in rows:
430
                        current_datetime_local = row[0].replace(tzinfo=timezone.utc) + \
431
                                                 timedelta(minutes=timezone_offset)
432
                        current_datetime = current_datetime_local.strftime('%Y-%m-%dT%H:%M:%S')
433
                        point_timestamps.append(current_datetime)
434
                        point_values.append(row[1])
435
436
            parameters_data['names'].append(point['name'] + ' (' + point['units'] + ')')
437
            parameters_data['timestamps'].append(point_timestamps)
438
            parameters_data['values'].append(point_values)
439
440
        ################################################################################################################
441
        # Step 9: construct the report
442
        ################################################################################################################
443
        if cursor_system:
444
            cursor_system.close()
445
        if cnx_system:
446
            cnx_system.disconnect()
447
448
        if cursor_energy:
449
            cursor_energy.close()
450
        if cnx_energy:
451
            cnx_energy.disconnect()
452
453
        result = dict()
454
455
        result['equipment'] = dict()
456
        result['equipment']['name'] = equipment['name']
457
458
        result['base_period'] = dict()
459
        result['base_period']['names'] = list()
460
        result['base_period']['units'] = list()
461
        result['base_period']['timestamps'] = list()
462
        result['base_period']['values'] = list()
463
        result['base_period']['subtotals'] = list()
464
        result['base_period']['means'] = list()
465
        result['base_period']['medians'] = list()
466
        result['base_period']['minimums'] = list()
467
        result['base_period']['maximums'] = list()
468
        result['base_period']['stdevs'] = list()
469
        result['base_period']['variances'] = list()
470
471
        if energy_category_set is not None and len(energy_category_set) > 0:
472
            for energy_category_id in energy_category_set:
473
                result['base_period']['names'].append(energy_category_dict[energy_category_id]['name'])
474
                result['base_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
475
                result['base_period']['timestamps'].append(base[energy_category_id]['timestamps'])
476
                result['base_period']['values'].append(base[energy_category_id]['values'])
477
                result['base_period']['subtotals'].append(base[energy_category_id]['subtotal'])
478
                result['base_period']['means'].append(base[energy_category_id]['mean'])
479
                result['base_period']['medians'].append(base[energy_category_id]['median'])
480
                result['base_period']['minimums'].append(base[energy_category_id]['minimum'])
481
                result['base_period']['maximums'].append(base[energy_category_id]['maximum'])
482
                result['base_period']['stdevs'].append(base[energy_category_id]['stdev'])
483
                result['base_period']['variances'].append(base[energy_category_id]['variance'])
484
485
        result['reporting_period'] = dict()
486
        result['reporting_period']['names'] = list()
487
        result['reporting_period']['energy_category_ids'] = list()
488
        result['reporting_period']['units'] = list()
489
        result['reporting_period']['timestamps'] = list()
490
        result['reporting_period']['values'] = list()
491
        result['reporting_period']['subtotals'] = list()
492
        result['reporting_period']['means'] = list()
493
        result['reporting_period']['means_increment_rate'] = list()
494
        result['reporting_period']['medians'] = list()
495
        result['reporting_period']['medians_increment_rate'] = list()
496
        result['reporting_period']['minimums'] = list()
497
        result['reporting_period']['minimums_increment_rate'] = list()
498
        result['reporting_period']['maximums'] = list()
499
        result['reporting_period']['maximums_increment_rate'] = list()
500
        result['reporting_period']['stdevs'] = list()
501
        result['reporting_period']['stdevs_increment_rate'] = list()
502
        result['reporting_period']['variances'] = list()
503
        result['reporting_period']['variances_increment_rate'] = list()
504
505
        if energy_category_set is not None and len(energy_category_set) > 0:
506
            for energy_category_id in energy_category_set:
507
                result['reporting_period']['names'].append(energy_category_dict[energy_category_id]['name'])
508
                result['reporting_period']['energy_category_ids'].append(energy_category_id)
509
                result['reporting_period']['units'].append(energy_category_dict[energy_category_id]['unit_of_measure'])
510
                result['reporting_period']['timestamps'].append(reporting[energy_category_id]['timestamps'])
511
                result['reporting_period']['values'].append(reporting[energy_category_id]['values'])
512
                result['reporting_period']['subtotals'].append(reporting[energy_category_id]['subtotal'])
513
                result['reporting_period']['means'].append(reporting[energy_category_id]['mean'])
514
                result['reporting_period']['means_increment_rate'].append(
515
                    (reporting[energy_category_id]['mean'] - base[energy_category_id]['mean']) /
516
                    base[energy_category_id]['mean'] if (base[energy_category_id]['mean'] is not None and
517
                                                         base[energy_category_id]['mean'] > Decimal(0.0))
518
                    else None)
519
                result['reporting_period']['medians'].append(reporting[energy_category_id]['median'])
520
                result['reporting_period']['medians_increment_rate'].append(
521
                    (reporting[energy_category_id]['median'] - base[energy_category_id]['median']) /
522
                    base[energy_category_id]['median'] if (base[energy_category_id]['median'] is not None and
523
                                                           base[energy_category_id]['median'] > Decimal(0.0))
524
                    else None)
525
                result['reporting_period']['minimums'].append(reporting[energy_category_id]['minimum'])
526
                result['reporting_period']['minimums_increment_rate'].append(
527
                    (reporting[energy_category_id]['minimum'] - base[energy_category_id]['minimum']) /
528
                    base[energy_category_id]['minimum'] if (base[energy_category_id]['minimum'] is not None and
529
                                                            base[energy_category_id]['minimum'] > Decimal(0.0))
530
                    else None)
531
                result['reporting_period']['maximums'].append(reporting[energy_category_id]['maximum'])
532
                result['reporting_period']['maximums_increment_rate'].append(
533
                    (reporting[energy_category_id]['maximum'] - base[energy_category_id]['maximum']) /
534
                    base[energy_category_id]['maximum'] if (base[energy_category_id]['maximum'] is not None and
535
                                                            base[energy_category_id]['maximum'] > Decimal(0.0))
536
                    else None)
537
                result['reporting_period']['stdevs'].append(reporting[energy_category_id]['stdev'])
538
                result['reporting_period']['stdevs_increment_rate'].append(
539
                    (reporting[energy_category_id]['stdev'] - base[energy_category_id]['stdev']) /
540
                    base[energy_category_id]['stdev'] if (base[energy_category_id]['stdev'] is not None and
541
                                                          base[energy_category_id]['stdev'] > Decimal(0.0))
542
                    else None)
543
                result['reporting_period']['variances'].append(reporting[energy_category_id]['variance'])
544
                result['reporting_period']['variances_increment_rate'].append(
545
                    (reporting[energy_category_id]['variance'] - base[energy_category_id]['variance']) /
546
                    base[energy_category_id]['variance'] if (base[energy_category_id]['variance'] is not None and
547
                                                             base[energy_category_id]['variance'] > Decimal(0.0))
548
                    else None)
549
550
        result['parameters'] = {
551
            "names": parameters_data['names'],
552
            "timestamps": parameters_data['timestamps'],
553
            "values": parameters_data['values']
554
        }
555
556
        resp.body = json.dumps(result)
557