Python Timeseries.id方法代码示例

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import id [as 别名]
def create_objects(dma, household_identifier, series, force=False):
    """
    When a household is fully parsed then this command is called to create
    database objects thus: user (household owner), household, database time
    series placeholders (for raw data and for processed data), to write actual
    time series data in database and finally to estimate the household
    occupancy.
    """
    print "Processing household %s, user username will be %s as well"%(
            household_identifier, household_identifier)
    # Create user (household owner), household, database series placeholders
    user = create_user(household_identifier)
    household=create_household(household_identifier, user,
            zone=dma.id)
    db_series = create_raw_timeseries(household)
    create_processed_timeseries(household)
    timeseries_data = {}
    # Now we will create timeseries.Timeseries() and we will add
    # parsed values
    for variable in db_series:
        if variable not in ('WaterCold', 'Electricity'):
            continue
        s, e = timeseries_bounding_dates_from_db(db.connection,
                db_series[variable].id)
        if not force and (s or e):
            print 'Raw timeseries id=%s has already data, skipping...'%(
                    db_series[variable].id,)
            continue
        timeseries = TSeries()
        timeseries.id = db_series[variable].id
        total = 0.0
        for timestamp, value in series[variable]:
            if not math.isnan(value):
                total += value
                timeseries[timestamp] = total
            else:
                timeseries[timestamp] = float('NaN')
        timeseries_data[variable] = timeseries
        timeseries.write_to_db(db=db.connection,
                transaction=transaction,
                commit=False)
    if 'WaterCold' in timeseries_data:
        calc_occupancy(timeseries_data['WaterCold'], household)

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import id [as 别名]
def parse_and_save_timeseries(device_id, timeseries_id):
    """
    Reads a RAW timeseries from REST API and saves in our local
    database using the timeseries_id.
    ``device_id`` will be the ``identifier`` used in other functions,
    usualy is the customerID==deviceID
    """
    s, e = timeseries_bounding_dates_from_db(db.connection,
            timeseries_id)
    if s or e:
        print 'Raw timeseries id=%s has already data, skipping...'%(
                timeseries_id,)
        return
    timeseries = TSeries()
    timeseries.id = timeseries_id
    for timestamp, value in ibm_restapi.get_raw_timeseries(device_id):
        timeseries[timestamp] = value
    timeseries.write_to_db(db=db.connection,
            transaction=transaction,
            commit=False)

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import id [as 别名]
def parse_and_save_timeseries(filename, timeseries_id):
    first_line = True
    timeseries = TSeries()
    timeseries.id = timeseries_id
    with open(filename) as fp:
        for line in fp.readlines():
            if first_line:
                first_line = False
                continue
            components = line.split(',')
            date_str = components[1].strip('"')
            value_str = components[2].strip('"')
            value = float(value_str)
            if value<MIN_VALUE or value>=MAX_VALUE:
                value = float('nan')
            tstamp = datetime.strptime(date_str, '%Y-%m-%d %H:%M:%S')
            tstamp = tstamp.replace(second=0)
            timeseries[tstamp] = value
    timeseries.write_to_db(db=db.connection,
            transaction=transaction,
            commit=False)

# 需要导入模块: from pthelma.timeseries import Timeseries [as 别名]
# 或者: from pthelma.timeseries.Timeseries import id [as 别名]
def create_objects(data, usernames, force, z_names, z_dict):
    """

    :param data: meter_id -> consumption_type -> [timestamp, volume]
    :param force: True to overwrite
    :return: True for success
    """
    households = []
    # Create user (household owner), household, database series placeholders
    hh_ids = sorted(data.keys())
    found = False
    for hh_id in hh_ids:
        username = usernames[hh_id]
        if username == "PT94993":
            pass
        try:
            zone_name = z_dict[username]
        except KeyError:
            zone_name = z_names[0]
        zone = DMA.objects.get(name=zone_name)
        user, created = create_user(username, hh_id)
        household, found = create_household(hh_id, user, zone.id)
        households.append(household)
        db_series = create_raw_timeseries(household)
        create_processed_timeseries(household)
        timeseries_data = {}
        # Now we will create timeseries.Timeseries() and we will add
        # parsed values
        for variable in db_series:
            if variable not in ('WaterCold', 'Electricity'):
                continue
            exists = False
            s, e = timeseries_bounding_dates_from_db(db.connection,
                                                     db_series[variable].id)
            latest_ts = e
            ts_id = db_series[variable].id
            # checking to see if timeseries records already exist in order
            # to append
            # d = read_timeseries_tail_from_db(db.connection, ts_id)
            total = 0.0
            # if s or e:
            #     exists = True
            #     timeseries = TSeries(ts_id)
            #     timeseries.read_from_db(db.connection)
            # else:
            #     timeseries = TSeries()
            #     timeseries.id = ts_id
            _dict = data[hh_id]
            arr = _dict[variable]
            series = arr
            if not series:
                continue
            earlier = []
            if (not latest_ts) or (latest_ts < series[0][0]):  # append
                timeseries = TSeries()
                timeseries.id = ts_id
                try:
                    tail = read_timeseries_tail_from_db(db.connection, ts_id)
                    total = float(tail[1])  # keep up from last value
                except Exception as e:
                    log.debug(repr(e))
                    total = 0
                for timestamp, value in series:
                    if (not latest_ts) or (timestamp > latest_ts):
                        if not isnan(value):
                            total += value
                            timeseries[timestamp] = total
                        else:
                            timeseries[timestamp] = float('NaN')
                    elif timestamp < latest_ts:
                        earlier.append((timestamp, value))
                timeseries.append_to_db(db=db.connection,
                                        transaction=transaction,
                                        commit=True)
            elif latest_ts >= series[0][0]:
                if not force:  # ignore
                    continue
                else:  # insert
                    for timestamp, value in series:
                        if timestamp < latest_ts:
                            earlier.append((timestamp, value))
            if earlier and ("GR" in username or "GBA" in username):  # insert (only for athens)
                # print "appending %s items for %s" % (len(earlier), username)
                if variable == "WaterCold":
                    ts15 = household \
                        .timeseries.get(time_step__id=TSTEP_FIFTEEN_MINUTES,
                                        variable__id=VAR_PERIOD)
                    series15 = TSeries(id=ts15.id)
                elif variable == "Electricity":
                    ts15 = household \
                        .timeseries.get(time_step__id=TSTEP_FIFTEEN_MINUTES,
                                        variable__id=VAR_ENERGY_PERIOD)
                    series15 = TSeries(id=ts15.id)
                series15.read_from_db(db.connection)
                for ts, value in earlier:
                    series15[ts] = value
                series15.write_to_db(db=db.connection,
                                     transaction=transaction,
                                     commit=True)

#.........这里部分代码省略.........