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# Source code for pywws.Process

    #!/usr/bin/env python
    # -*- coding: utf-8 -*-

    # pywws - Python software for USB Wireless Weather Stations
    # http://github.com/jim-easterbrook/pywws
    # Copyright (C) 2008-13  Jim Easterbrook  jim@jim-easterbrook.me.uk

    # This program is free software; you can redistribute it and/or
    # modify it under the terms of the GNU General Public License
    # as published by the Free Software Foundation; either version 2
    # of the License, or (at your option) any later version.

    # This program is distributed in the hope that it will be useful,
    # but WITHOUT ANY WARRANTY; without even the implied warranty of
    # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
    # GNU General Public License for more details.

    # You should have received a copy of the GNU General Public License
    # along with this program; if not, write to the Free Software
    # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.

    """Generate hourly, daily & monthly summaries of raw weather station
    data
    ::

    %s

    This module takes raw weather station data (typically sampled every
    five or ten minutes) and generates hourly, daily and monthly summary
    data, which is useful when creating tables and graphs.

    Before computing the data summaries, raw data is "calibrated" using a
    user-programmable function. See :doc:`pywws.calib` for details.

    The hourly data is derived from all the records in one hour, e.g. from
    18:00:00 to 18:59:59, and is given the index of the last complete
    record in that hour.

    The daily data summarises the weather over a 24 hour period typically
    ending at 2100 or 0900 hours, local (non DST) time, though midnight is
    another popular convention. It is also indexed by the last complete
    record in the period. Daytime and nightime, as used when computing
    maximum and minimum temperatures, are assumed to start at 0900 and
    2100 local time, or 1000 and 2200 when DST is in effect, regardless of
    the meteorological day.

    To adjust the meteorological day to your preference, or that used by
    your local official weather station, edit the "day end hour" line in
    your ``weather.ini`` file, then run Reprocess.py to regenerate the
    summaries.

    Monthly summary data is computed from the daily summary data. If the
    meteorological day does not end at midnight, then each month may begin
    and end up to 12 hours before or after midnight.

    Wind speed data is averaged over the hour (or day) and the maximum
    gust speed during the hour (or day) is recorded. The predominant wind
    direction is calculated using vector arithmetic.

    Rainfall is converted from the raw "total since last reset" figure to
    a more useful total in the last hour, day or month.

    """

    __docformat__ = "restructuredtext en"
    __usage__ = """
     usage: python RunModule.py Process [options] data_dir
     options are:
      -h or --help     display this help
      -v or --verbose  increase number of informative messages
     data_dir is the root directory of the weather data
    """
    __doc__ %= __usage__
    __usage__ = __doc__.split('\n')[0] + __usage__

    from collections import deque
    from datetime import date, datetime, timedelta
    import getopt
    import logging
    import math
    import os
    import sys

    from .calib import Calib
    from . import DataStore
    from .Logger import ApplicationLogger
    from .TimeZone import Local, utc
    from . import WeatherStation

    SECOND = timedelta(seconds=1)
    TIME_ERR = timedelta(seconds=45)
    HOUR = timedelta(hours=1)
    HOURx3 = timedelta(hours=3)
    DAY = timedelta(hours=24)
    WEEK = timedelta(days=7)

    class Average(object):
        """Compute average of multiple data values."""
        def __init__(self):
            self.acc = 0.0
            self.count = 0

        def add(self, value):
            if value is None:
                return
            self.acc += value
            self.count += 1

        def result(self):
            if self.count == 0:
                return None
            return self.acc / float(self.count)

    class Minimum(object):
        """Compute minimum value and timestamp of multiple data values."""
        def __init__(self):
            self.value = None
            self.time = None

        def add(self, value, time):
            if not self.time or value <= self.value:
                self.value = value
                self.time = time

        def result(self):
            if self.time:
                return self.value, self.time
            return None, None

    class Maximum(object):
        """Compute maximum value and timestamp of multiple data values."""
        def __init__(self):
            self.value = None
            self.time = None

        def add(self, value, time):
            if not self.time or value > self.value:
                self.value = value
                self.time = time

        def result(self):
            if self.time:
                return self.value, self.time
            return None, None

    sin_LUT = map(
        lambda x: math.sin(math.radians(float(x * 360) / 16.0)), range(16))
    cos_LUT = map(
        lambda x: math.cos(math.radians(float(x * 360) / 16.0)), range(16))

    class HourAcc(object):
        """'Accumulate' raw weather data to produce hourly summary.

        Compute average wind speed and maximum wind gust, find dominant
        wind direction and compute total rainfall.

        """
        def __init__(self, last_rain):
            self.logger = logging.getLogger('pywws.Process.HourAcc')
            self.last_rain = last_rain
            self.wind_dir = list()
            for i in range(16):
                self.wind_dir.append(0.0)
            self.copy_keys = ['idx', 'hum_in', 'temp_in', 'hum_out', 'temp_out',
                              'abs_pressure', 'rel_pressure']
            self.reset()

        def reset(self):
            for i in range(16):
                self.wind_dir[i] = 0.0
            self.wind_acc = 0.0
            self.wind_gust = (-2.0, None)
            self.rain = 0.0
            self.wind_count = 0
            self.retval = dict()

        def add_raw(self, data):
            idx = data['idx']
            wind_ave = data['wind_ave']
            if wind_ave is not None:
                wind_dir = data['wind_dir']
                if wind_dir is not None:
                    self.wind_dir[wind_dir] += wind_ave
                self.wind_acc += wind_ave
                self.wind_count += 1
            wind_gust = data['wind_gust']
            if wind_gust is not None and wind_gust > self.wind_gust[0]:
                self.wind_gust = (wind_gust, idx)
            rain = data['rain']
            if rain is not None:
                if self.last_rain is not None:
                    diff = rain - self.last_rain
                    if diff < -0.001:
                        self.logger.warning(
                            '%s rain reset %.1f -> %.1f', str(idx), self.last_rain, rain)
                    elif diff > float(data['delay'] * 5):
                        # rain exceeds 5mm / minute, assume corrupt data and ignore it
                        self.logger.warning(
                            '%s rain jump %.1f -> %.1f', str(idx), self.last_rain, rain)
                    else:
                        self.rain += max(0.0, diff)
                self.last_rain = rain
            # copy some current readings
            if 'illuminance' in data and not 'illuminance' in self.copy_keys:
                self.copy_keys.append('illuminance')
                self.copy_keys.append('uv')
            # if near the end of the hour, ignore 'lost contact' readings
            if data['idx'].minute < 45 or data['temp_out'] is not None:
                for key in self.copy_keys:
                    self.retval[key] = data[key]

        def result(self):
            if not self.retval:
                return None
            if self.wind_count > 0:
                # convert weighted wind directions to a vector
                Ve = 0.0
                Vn = 0.0
                for dir in range(16):
                    val = self.wind_dir[dir]
                    Ve -= val * sin_LUT[dir]
                    Vn -= val * cos_LUT[dir]
                # get direction of total vector
                dir_ave = (math.degrees(math.atan2(Ve, Vn)) + 180.0) * 16.0 / 360.0
                self.retval['wind_dir'] = int(dir_ave + 0.5) % 16
                wind_ave = self.wind_acc / float(self.wind_count)
                self.retval['wind_ave'] = wind_ave
            else:
                self.retval['wind_dir'] = None
                self.retval['wind_ave'] = None
            if self.wind_gust[1]:
                self.retval['wind_gust'] = self.wind_gust[0]
            else:
                self.retval['wind_gust'] = None
            self.retval['rain'] = self.rain
            return self.retval

    class DayAcc(object):
        """'Accumulate' weather data to produce daily summary.

        Compute average wind speed, maximum wind gust and daytime max &
        nighttime min temperatures, find dominant wind direction and
        compute total rainfall.

        Daytime is assumed to be 0900-2100 and nighttime to be 2100-0900,
        local time (1000-2200 and 2200-1000 during DST), regardless of the
        "day end hour" setting.

        """
        def __init__(self, daytime):
            self.logger = logging.getLogger('pywws.Process.DayAcc')
            self._daytime = daytime
            self.has_illuminance = False
            self.wind_dir = list()
            for i in range(16):
                self.wind_dir.append(0.0)
            self.ave = {}
            self.max = {}
            self.min = {}
            self.reset()

        def reset(self):
            for i in range(16):
                self.wind_dir[i] = 0.0
            self.wind_acc = 0.0
            self.wind_count = 0
            self.wind_gust = (-1.0, None)
            self.rain = 0.0
            for i in ('temp_in', 'temp_out', 'hum_in', 'hum_out',
                      'abs_pressure', 'rel_pressure'):
                self.ave[i] = Average()
                self.max[i] = Maximum()
                self.min[i] = Minimum()
            for i in ('illuminance', 'uv'):
                self.ave[i] = Average()
                self.max[i] = Maximum()
            self.retval = dict()

        def add_raw(self, data):
            idx = data['idx']
            wind_gust = data['wind_gust']
            if wind_gust is not None and wind_gust > self.wind_gust[0]:
                self.wind_gust = (wind_gust, idx)
            for i in ('temp_in', 'temp_out'):
                temp = data[i]
                if temp is not None:
                    self.ave[i].add(temp)
                    if self._daytime[idx.hour]:
                        # daytime max temperature
                        self.max[i].add(temp, idx)
                    else:
                        # nighttime min temperature
                        self.min[i].add(temp, idx)
            for i in ('hum_in', 'hum_out', 'abs_pressure', 'rel_pressure'):
                value = data[i]
                if value is not None:
                    self.ave[i].add(value)
                    self.max[i].add(value, idx)
                    self.min[i].add(value, idx)
            if 'illuminance' in data:
                self.has_illuminance = True
                for i in ('illuminance', 'uv'):
                    value = data[i]
                    if value is not None:
                        self.ave[i].add(value)
                        self.max[i].add(value, idx)

        def add_hourly(self, data):
            wind_ave = data['wind_ave']
            if wind_ave is not None:
                wind_dir = data['wind_dir']
                if wind_dir is not None:
                    self.wind_dir[wind_dir] += wind_ave
                self.wind_acc += wind_ave
                self.wind_count += 1
            rain = data['rain']
            if rain is not None:
                self.rain += rain
            self.retval['idx'] = data['idx']

        def result(self):
            if not self.retval:
                return None
            if self.wind_count > 0:
                # convert weighted wind directions to a vector
                Ve = 0.0
                Vn = 0.0
                for dir in range(16):
                    val = self.wind_dir[dir]
                    Ve -= val * sin_LUT[dir]
                    Vn -= val * cos_LUT[dir]
                # get direction of total vector
                dir_ave = (math.degrees(math.atan2(Ve, Vn)) + 180.0) * 16.0 / 360.0
                self.retval['wind_dir'] = int(dir_ave + 0.5) % 16
                wind_ave = self.wind_acc / float(self.wind_count)
                self.retval['wind_ave'] = wind_ave
            else:
                self.retval['wind_dir'] = None
                self.retval['wind_ave'] = None
            if self.wind_gust[1]:
                self.retval['wind_gust'] = self.wind_gust[0]
            else:
                self.retval['wind_gust'] = None
            self.retval['wind_gust_t'] = self.wind_gust[1]
            self.retval['rain'] = self.rain
            for i in ('temp_in', 'temp_out', 'hum_in', 'hum_out',
                      'abs_pressure', 'rel_pressure'):
                self.retval['%s_ave' % i] = self.ave[i].result()
                (self.retval['%s_max' % i],
                 self.retval['%s_max_t' % i]) = self.max[i].result()
                (self.retval['%s_min' % i],
                 self.retval['%s_min_t' % i]) = self.min[i].result()
            if self.has_illuminance:
                for i in ('illuminance', 'uv'):
                    self.retval['%s_ave' % i] = self.ave[i].result()
                    (self.retval['%s_max' % i],
                     self.retval['%s_max_t' % i]) = self.max[i].result()
            return self.retval

    class MonthAcc(object):
        """'Accumulate' daily weather data to produce monthly summary.

        Compute daytime max & nighttime min temperatures.

        """
        def __init__(self, rain_day_threshold):
            self.rain_day_threshold = rain_day_threshold
            self.has_illuminance = False
            self.ave = {}
            self.min = {}
            self.max = {}
            self.min_lo = {}
            self.min_hi = {}
            self.min_ave = {}
            self.max_lo = {}
            self.max_hi = {}
            self.max_ave = {}
            self.wind_dir = list()
            for i in range(16):
                self.wind_dir.append(0.0)
            self.reset()

        def reset(self):
            for i in ('temp_in', 'temp_out'):
                self.ave[i] = Average()
                self.min_lo[i] = Minimum()
                self.min_hi[i] = Maximum()
                self.min_ave[i] = Average()
                self.max_lo[i] = Minimum()
                self.max_hi[i] = Maximum()
                self.max_ave[i] = Average()
            for i in ('hum_in', 'hum_out', 'abs_pressure', 'rel_pressure'):
                self.ave[i] = Average()
                self.max[i] = Maximum()
                self.min[i] = Minimum()
            for i in ('illuminance', 'uv'):
                self.ave[i] = Average()
                self.max_lo[i] = Minimum()
                self.max_hi[i] = Maximum()
                self.max_ave[i] = Average()
            for i in range(16):
                self.wind_dir[i] = 0.0
            self.wind_acc = 0.0
            self.wind_count = 0
            self.wind_gust = (-1.0, None)
            self.rain = 0.0
            self.rain_days = 0
            self.valid = False

        def add_daily(self, data):
            self.idx = data['idx']
            for i in ('temp_in', 'temp_out'):
                temp = data['%s_ave' % i]
                if temp is not None:
                    self.ave[i].add(temp)
                temp = data['%s_min' % i]
                if temp is not None:
                    self.min_lo[i].add(temp, data['%s_min_t' % i])
                    self.min_hi[i].add(temp, data['%s_min_t' % i])
                    self.min_ave[i].add(temp)
                temp = data['%s_max' % i]
                if temp is not None:
                    self.max_lo[i].add(temp, data['%s_max_t' % i])
                    self.max_hi[i].add(temp, data['%s_max_t' % i])
                    self.max_ave[i].add(temp)
            for i in ('hum_in', 'hum_out', 'abs_pressure', 'rel_pressure'):
                value = data['%s_ave' % i]
                if value is not None:
                    self.ave[i].add(value)
                value = data['%s_min' % i]
                if value is not None:
                    self.min[i].add(value, data['%s_min_t' % i])
                value = data['%s_max' % i]
                if value is not None:
                    self.max[i].add(value, data['%s_max_t' % i])
            wind_ave = data['wind_ave']
            if wind_ave is not None:
                wind_dir = data['wind_dir']
                if wind_dir is not None:
                    self.wind_dir[wind_dir] += wind_ave
                self.wind_acc += wind_ave
                self.wind_count += 1
            wind_gust = data['wind_gust']
            if wind_gust is not None and wind_gust > self.wind_gust[0]:
                self.wind_gust = (wind_gust, data['wind_gust_t'])
            if 'illuminance_ave' in data:
                self.has_illuminance = True
                for i in ('illuminance', 'uv'):
                    value = data['%s_ave' % i]
                    if value is not None:
                        self.ave[i].add(value)
                    value = data['%s_max' % i]
                    if value is not None:
                        self.max_lo[i].add(value, data['%s_max_t' % i])
                        self.max_hi[i].add(value, data['%s_max_t' % i])
                        self.max_ave[i].add(value)
            self.rain += data['rain']
            if data['rain'] >= self.rain_day_threshold:
                self.rain_days += 1
            self.valid = True

        def result(self):
            if not self.valid:
                return None
            result = {}
            result['idx'] = self.idx
            result['rain'] = self.rain
            result['rain_days'] = self.rain_days
            for i in ('temp_in', 'temp_out'):
                result['%s_ave' % i] = self.ave[i].result()
                result['%s_min_ave' % i] = self.min_ave[i].result()
                (result['%s_min_lo' % i],
                 result['%s_min_lo_t' % i]) = self.min_lo[i].result()
                (result['%s_min_hi' % i],
                 result['%s_min_hi_t' % i]) = self.min_hi[i].result()
                result['%s_max_ave' % i] = self.max_ave[i].result()
                (result['%s_max_lo' % i],
                 result['%s_max_lo_t' % i]) = self.max_lo[i].result()
                (result['%s_max_hi' % i],
                 result['%s_max_hi_t' % i]) = self.max_hi[i].result()
            for i in ('hum_in', 'hum_out', 'abs_pressure', 'rel_pressure'):
                result['%s_ave' % i] = self.ave[i].result()
                (result['%s_max' % i],
                 result['%s_max_t' % i]) = self.max[i].result()
                (result['%s_min' % i],
                 result['%s_min_t' % i]) = self.min[i].result()
            if self.wind_count > 0:
                # convert weighted wind directions to a vector
                Ve = 0.0
                Vn = 0.0
                for dir in range(16):
                    val = self.wind_dir[dir]
                    Ve -= val * sin_LUT[dir]
                    Vn -= val * cos_LUT[dir]
                # get direction of total vector
                dir_ave = (math.degrees(math.atan2(Ve, Vn)) + 180.0) * 16.0 / 360.0
                result['wind_dir'] = int(dir_ave + 0.5) % 16
                wind_ave = self.wind_acc / float(self.wind_count)
                result['wind_ave'] = wind_ave
            else:
                result['wind_dir'] = None
                result['wind_ave'] = None
            if self.wind_gust[1]:
                result['wind_gust'] = self.wind_gust[0]
            else:
                result['wind_gust'] = None
            result['wind_gust_t'] = self.wind_gust[1]
            if self.has_illuminance:
                for i in ('illuminance', 'uv'):
                    result['%s_ave' % i] = self.ave[i].result()
                    result['%s_max_ave' % i] = self.max_ave[i].result()
                    (result['%s_max_lo' % i],
                     result['%s_max_lo_t' % i]) = self.max_lo[i].result()
                    (result['%s_max_hi' % i],
                     result['%s_max_hi_t' % i]) = self.max_hi[i].result()
            return result

    def calibrate_data(logger, params, raw_data, calib_data):
        """'Calibrate' raw data, using a user-supplied function."""
        start = calib_data.before(datetime.max)
        if start is None:
            start = datetime.min
        start = raw_data.after(start + SECOND)
        if start is None:
            return start
        del calib_data[start:]
        calibrator = Calib(params)
        count = 0
        for data in raw_data[start:]:
            idx = data['idx']
            count += 1
            if count % 10000 == 0:
                logger.info("calib: %s", idx.isoformat(' '))
            elif count % 500 == 0:
                logger.debug("calib: %s", idx.isoformat(' '))
            calib_data[idx] = calibrator.calib(data)
        return start

    def generate_hourly(logger, calib_data, hourly_data, process_from):
        """Generate hourly summaries from calibrated data."""
        start = hourly_data.before(datetime.max)
        if start is None:
            start = datetime.min
        start = calib_data.after(start + SECOND)
        if process_from:
            if start:
                start = min(start, process_from)
            else:
                start = process_from
        if start is None:
            return start
        start = start.replace(minute=0, second=0)
        del hourly_data[start:]
        # preload pressure history, and find last valid rain
        prev = None
        pressure_history = deque()
        last_rain = None
        for data in calib_data[start - HOURx3:start]:
            if data['rel_pressure']:
                pressure_history.append((data['idx'], data['rel_pressure']))
            if data['rain'] is not None:
                last_rain = data['rain']
            prev = data
        # iterate over data in one hour chunks
        stop = calib_data.before(datetime.max)
        hour_start = start
        acc = HourAcc(last_rain)
        count = 0
        while hour_start <= stop:
            count += 1
            if count % 1008 == 0:
                logger.info("hourly: %s", hour_start.isoformat(' '))
            elif count % 24 == 0:
                logger.debug("hourly: %s", hour_start.isoformat(' '))
            hour_end = hour_start + HOUR
            acc.reset()
            for data in calib_data[hour_start:hour_end]:
                if data['rel_pressure']:
                    pressure_history.append((data['idx'], data['rel_pressure']))
                if prev:
                    err = data['idx'] - prev['idx']
                    if abs(err - timedelta(minutes=data['delay'])) > TIME_ERR:
                        logger.info('unexpected data interval %s %s',
                                    data['idx'].isoformat(' '), str(err))
                acc.add_raw(data)
                prev = data
            new_data = acc.result()
            if new_data and new_data['idx'].minute >= 9:
                # compute pressure trend
                new_data['pressure_trend'] = None
                if new_data['rel_pressure']:
                    target = new_data['idx'] - HOURx3
                    while (len(pressure_history) >= 2 and
                           abs(pressure_history[0][0] - target) >
                           abs(pressure_history[1][0] - target)):
                        pressure_history.popleft()
                    if (pressure_history and
                            abs(pressure_history[0][0] - target) < HOUR):
                        new_data['pressure_trend'] = (
                            new_data['rel_pressure'] - pressure_history[0][1])
                # store new hourly data
                hourly_data[new_data['idx']] = new_data
            hour_start = hour_end
        return start

    def generate_daily(logger, day_end_hour, daytime,
                       calib_data, hourly_data, daily_data, process_from):
        """Generate daily summaries from calibrated and hourly data."""
        start = daily_data.before(datetime.max)
        if start is None:
            start = datetime.min
        start = calib_data.after(start + SECOND)
        if process_from:
            if start:
                start = min(start, process_from)
            else:
                start = process_from
        if start is None:
            return start
        # round to start of this day
        if start.hour < day_end_hour:
            start = start - DAY
        start = start.replace(hour=day_end_hour, minute=0, second=0)
        del daily_data[start:]
        stop = calib_data.before(datetime.max)
        day_start = start
        acc = DayAcc(daytime)
        count = 0
        while day_start <= stop:
            count += 1
            if count % 30 == 0:
                logger.info("daily: %s", day_start.isoformat(' '))
            else:
                logger.debug("daily: %s", day_start.isoformat(' '))
            day_end = day_start + DAY
            acc.reset()
            for data in calib_data[day_start:day_end]:
                acc.add_raw(data)
            for data in hourly_data[day_start:day_end]:
                acc.add_hourly(data)
            new_data = acc.result()
            if new_data:
                new_data['start'] = day_start
                daily_data[new_data['idx']] = new_data
            day_start = day_end
        return start

    def generate_monthly(logger, rain_day_threshold, day_end_hour, time_offset,
                         daily_data, monthly_data, process_from):
        """Generate monthly summaries from daily data."""
        start = monthly_data.before(datetime.max)
        if start is None:
            start = datetime.min
        start = daily_data.after(start + SECOND)
        if process_from:
            if start:
                start = min(start, process_from)
            else:
                start = process_from
        if start is None:
            return start
        # set start to start of first day of month (local time)
        if start.hour < day_end_hour:
            start = start - DAY
        start = start.replace(hour=day_end_hour, minute=0, second=0)
        local_start = start + time_offset
        local_start = local_start.replace(day=1)
        if local_start.hour >= 12:
            # month actually starts on the last day of previous month
            local_start -= DAY
        start = local_start - time_offset
        del monthly_data[start:]
        stop = daily_data.before(datetime.max)
        month_start = start
        acc = MonthAcc(rain_day_threshold)
        count = 0
        while month_start <= stop:
            count += 1
            if count % 12 == 0:
                logger.info("monthly: %s", month_start.isoformat(' '))
            else:
                logger.debug("monthly: %s", month_start.isoformat(' '))
            month_end = month_start + WEEK
            if month_end.month < 12:
                month_end = month_end.replace(month=month_end.month+1)
            else:
                month_end = month_end.replace(month=1, year=month_end.year+1)
            month_end = month_end - WEEK
            acc.reset()
            for data in daily_data[month_start:month_end]:
                acc.add_daily(data)
            new_data = acc.result()
            if new_data:
                new_data['start'] = month_start
                monthly_data[new_data['idx']] = new_data
            month_start = month_end
        return start

    def Process(params, raw_data, calib_data, hourly_data, daily_data, monthly_data):
        """Generate summaries from raw weather station data.

        The meteorological day end (typically 2100 or 0900 local time) is
        set in the preferences file ``weather.ini``. The default value is
        2100 (2200 during DST), following the historical convention for
        weather station readings.

        """
        logger = logging.getLogger('pywws.Process')
        logger.info('Generating summary data')
        # get time of last record
        last_raw = raw_data.before(datetime.max)
        if last_raw is None:
            raise IOError('No data found. Check data directory parameter.')
        # get local time's offset from UTC, without DST
        time_offset = Local.utcoffset(last_raw) - Local.dst(last_raw)
        # set daytime end hour, in UTC
        day_end_hour = eval(params.get('config', 'day end hour', '21'))
        day_end_hour = (day_end_hour - (time_offset.seconds // 3600)) % 24
        # divide 24 hours of UTC day into day and night
        daytime = []
        for i in range(24):
            daytime.append(True)
        night_hour = (21 - (time_offset.seconds // 3600)) % 24
        for i in range(12):
            daytime[night_hour] = False
            night_hour = (night_hour + 1) % 24
        # get other config
        rain_day_threshold = eval(params.get('config', 'rain day threshold', '0.2'))
        # calibrate raw data
        start = calibrate_data(logger, params, raw_data, calib_data)
        # generate hourly data
        start = generate_hourly(logger, calib_data, hourly_data, start)
        # generate daily data
        start = generate_daily(logger, day_end_hour, daytime,
                               calib_data, hourly_data, daily_data, start)
        # generate monthly data
        generate_monthly(logger, rain_day_threshold, day_end_hour, time_offset,
                         daily_data, monthly_data, start)
        return 0

    def main(argv=None):
        if argv is None:
            argv = sys.argv
        try:
            opts, args = getopt.getopt(argv[1:], "hv", ['help', 'verbose'])
        except getopt.error, msg:
            print >>sys.stderr, 'Error: %s\n' % msg
            print >>sys.stderr, __usage__.strip()
            return 1
        # process options
        verbose = 0
        for o, a in opts:
            if o in ('-h', '--help'):
                print __usage__.strip()
                return 0
            elif o in ('-v', '--verbose'):
                verbose += 1
        # check arguments
        if len(args) != 1:
            print >>sys.stderr, 'Error: 1 argument required\n'
            print >>sys.stderr, __usage__.strip()
            return 2
        logger = ApplicationLogger(verbose)
        data_dir = args[0]
        return Process(DataStore.params(data_dir),
                       DataStore.data_store(data_dir),
                       DataStore.calib_store(data_dir),
                       DataStore.hourly_store(data_dir),
                       DataStore.daily_store(data_dir),
                       DataStore.monthly_store(data_dir))

    if __name__ == "__main__":
        sys.exit(main())

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