def get_scalar(obs_type, record, db_manager=None):
log.debug('get_scalar(%s)' % obs_type)
if obs_type not in [ 'pm2_5_aqi', 'pm2_5_aqi_color' ]:
raise weewx.UnknownType(obs_type)
log.debug('get_scalar(%s)' % obs_type)
if record is None:
log.debug('get_scalar called where record is None.')
raise weewx.CannotCalculate(obs_type)
if 'pm2_5' not in record:
# Should not see this as pm2_5 is part of the extended schema that is required for this plugin.
# Returning CannotCalculate causes exception in ImageGenerator, return UnknownType instead.
# ERROR weewx.reportengine: Caught unrecoverable exception in generator 'weewx.imagegenerator.ImageGenerator'
log.info('get_scalar called where record does not contain pm2_5. This is unexpected.')
raise weewx.UnknownType(obs_type)
if record['pm2_5'] is None:
# Returning CannotCalculate causes exception in ImageGenerator, return UnknownType instead.
# ERROR weewx.reportengine: Caught unrecoverable exception in generator 'weewx.imagegenerator.ImageGenerator'
# Any archive catchup records will have None for pm2_5.
log.debug('get_scalar called where record[pm2_5] is None: %s. Probably a catchup record.' %
timestamp_to_string(record['dateTime']))
raise weewx.UnknownType(obs_type)
try:
pm2_5 = record['pm2_5']
if obs_type == 'pm2_5_aqi':
value = AQI.compute_pm2_5_aqi(pm2_5)
if obs_type == 'pm2_5_aqi_color':
value = AQI.compute_pm2_5_aqi_color(AQI.compute_pm2_5_aqi(pm2_5))
t, g = weewx.units.getStandardUnitType(record['usUnits'], obs_type)
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, t, g)
except KeyError:
# Don't have everything we need. Raise an exception.
raise weewx.CannotCalculate(obs_type)
def get_scalar(obs_type, record, db_manager=None):
log.debug('get_scalar(%s)' % obs_type)
if obs_type not in ['pm2_5_aqi', 'pm2_5_aqi_color']:
raise weewx.UnknownType(obs_type)
log.debug('get_scalar(%s)' % obs_type)
if record is None:
log.debug('get_scalar called where record is None.')
raise weewx.CannotCalculate(obs_type)
if 'pm2_5' not in record:
# Returning CannotCalculate causes exception in ImageGenerator, return UnknownType instead.
# ERROR weewx.reportengine: Caught unrecoverable exception in generator 'weewx.imagegenerator.ImageGenerator'
log.debug('get_scalar called where record does not contain pm2_5.')
raise weewx.UnknownType(obs_type)
if record['pm2_5'] is None:
# Returning CannotCalculate causes exception in ImageGenerator, return UnknownType instead.
# ERROR weewx.reportengine: Caught unrecoverable exception in generator 'weewx.imagegenerator.ImageGenerator'
# This will happen for any catchup records inserted at weewx startup.
log.debug('get_scalar called where record[pm2_5] is None.')
raise weewx.UnknownType(obs_type)
try:
pm2_5 = record['pm2_5']
if obs_type == 'pm2_5_aqi':
value = AQI.compute_pm2_5_aqi(pm2_5)
if obs_type == 'pm2_5_aqi_color':
value = AQI.compute_pm2_5_aqi_color(
AQI.compute_pm2_5_aqi(pm2_5))
t, g = weewx.units.getStandardUnitType(record['usUnits'], obs_type)
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, t, g)
except KeyError:
# Don't have everything we need. Raise an exception.
raise weewx.CannotCalculate(obs_type)
def get_gts(self, obs_type, sod_ts, soy_ts):
""" read GTS value out of the array """
if obs_type == 'GTS':
# Gruenlandtemperatursumme GTS
try:
if soy_ts is None or soy_ts not in self.gts_values:
__x = None
else:
__x = self.gts_values[soy_ts][dayOfGTSYear(sod_ts, soy_ts)]
return weewx.units.ValueTuple(__x, 'degree_C_day',
'group_degree_day')
except (ValueError, TypeError, IndexError, KeyError):
logerr("soy_ts=%s sod_ts=%s" % (soy_ts, sod_ts))
raise weewx.CannotCalculate(obs_type)
elif obs_type == 'GTSdate':
# date of value 200
if soy_ts is None or soy_ts not in self.gts_date:
return weewx.units.ValueTuple(None, 'unix_epoch', 'group_time')
else:
return weewx.units.ValueTuple(self.gts_date[soy_ts],
'unix_epoch', 'group_time')
else:
# unknown type (should not happen here)
raise weewx.UnknownType(obs_type)
def get_aggregate(obs_type, timespan, aggregate_type, db_manager, **option_dict):
"""Returns an aggregation of an observation type over a given time period, using the
main archive table.
obs_type: The type over which aggregation is to be done (e.g., 'barometer',
'outTemp', 'rain', ...)
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
aggregate_type: The type of aggregation to be done.
db_manager: An instance of weewx.manager.Manager or subclass.
option_dict: Not used in this version.
returns: A ValueTuple containing the result."""
if aggregate_type not in ['sum', 'count', 'avg', 'max', 'min'] \
+ list(ArchiveTable.agg_sql_dict.keys()):
raise weewx.UnknownAggregation(aggregate_type)
interpolate_dict = {
'aggregate_type': aggregate_type,
'obs_type': obs_type,
'table_name': db_manager.table_name,
'start': timespan.start,
'stop': timespan.stop
}
select_stmt = ArchiveTable.agg_sql_dict.get(aggregate_type,
ArchiveTable.simple_agg_sql) % interpolate_dict
try:
row = db_manager.getSql(select_stmt)
except weedb.NoColumnError:
raise weewx.UnknownType(aggregate_type)
value = row[0] if row else None
# Look up the unit type and group of this combination of observation type and aggregation:
u, g = weewx.units.getStandardUnitType(db_manager.std_unit_system, obs_type,
aggregate_type)
# Time derivatives have special rules. For example, the time derivative of watt-hours is
# watts, scaled by the number of seconds in an hour. The unit group also changes to
# group_power.
if aggregate_type == 'tderiv':
if u == 'watt_second':
u = 'watt'
elif u == 'watt_hour':
u = 'watt'
value *= 3600
elif u == 'kilowatt_hour':
u = 'kilowatt'
value *= 3600
g = 'group_power'
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, u, g)
def get_scalar(self, obs_type, record, db_manager):
# We only know how to calculate 'vapor_p'. For everything else, raise an exception
if obs_type != 'vapor_p':
raise weewx.UnknownType(obs_type)
# We need outTemp in order to do the calculation.
if 'outTemp' not in record or record['outTemp'] is None:
raise weewx.CannotCalculate(obs_type)
# We have everything we need. Start by forming a ValueTuple for the outside temperature.
# To do this, figure out what unit and group the record is in ...
unit_and_group = weewx.units.getStandardUnitType(record['usUnits'], 'outTemp')
# ... then form the ValueTuple.
outTemp_vt = weewx.units.ValueTuple(record['outTemp'], *unit_and_group)
# We need the temperature in Kelvin
outTemp_K_vt = weewx.units.convert(outTemp_vt, 'degree_K')
# Now we can use the formula. Results will be in mmHg. Create a ValueTuple out of it:
p_vt = weewx.units.ValueTuple(math.exp(20.386 - 5132.0 / outTemp_K_vt[0]),
'mmHg',
'group_pressure')
# We have the vapor pressure as a ValueTuple. Convert it back to the units used by
# the incoming record and return it
return weewx.units.convertStd(p_vt, record['usUnits'])
def get_series(obs_type,
timespan,
db_manager,
aggregate_type=None,
aggregate_interval=None,
**option_dict):
"""Return a series (aka vector) of, possibly aggregated, values."""
# Search the list, looking for a get_series() method that does not raise an UnknownType or
# UnknownAggregation exception
for xtype in xtypes:
try:
# Try this function. Be prepared to catch the TypeError exception if it is a legacy
# style XType that does not accept kwargs.
try:
return xtype.get_series(obs_type, timespan, db_manager,
aggregate_type, aggregate_interval,
**option_dict)
except TypeError:
# We likely have a legacy style XType, so try calling it again, but this time
# without the kwargs.
return xtype.get_series(obs_type, timespan, db_manager,
aggregate_type, aggregate_interval)
except (weewx.UnknownType, weewx.UnknownAggregation):
# This function does not know about the type and/or aggregation.
# Move on to the next one.
pass
# None of the functions worked. Raise an exception with a hopefully helpful error message.
if aggregate_type:
msg = "'%s' or '%s'" % (obs_type, aggregate_type)
else:
msg = obs_type
raise weewx.UnknownType(msg)
def get_series(obs_type,
timespan,
db_manager,
aggregate_type=None,
aggregate_interval=None,
**option_dict):
"""Get a series, possibly with aggregation, for special 'wind vector' types. These are
typically used for the wind vector plots.
"""
# Check to see if the requested type is not 'windvec' or 'windgustvec'
if obs_type not in WindVec.windvec_types:
# The type is not one of the extended wind types. We can't handle it.
raise weewx.UnknownType(obs_type)
# It is an extended wind type. Prepare the lists that will hold the
# final results.
start_vec = list()
stop_vec = list()
data_vec = list()
# Is aggregation requested?
if aggregate_type:
# Yes. Just use the regular series function. When it comes time to do the aggregation,
# the specialized function WindVec.get_aggregate() (defined below), will be used.
return ArchiveTable.get_series(obs_type, timespan, db_manager,
aggregate_type, aggregate_interval)
else:
# No aggregation desired. However, we have will have to assemble the wind vector from
# its flattened types. This SQL select string will select the proper wind types
sql_str = 'SELECT dateTime, %s, %s, usUnits, `interval` FROM %s ' \
'WHERE dateTime >= ? AND dateTime <= ?' \
% (WindVec.windvec_types[obs_type][0], WindVec.windvec_types[obs_type][1],
db_manager.table_name)
std_unit_system = None
for record in db_manager.genSql(sql_str, timespan):
ts, magnitude, direction, unit_system, interval = record
if std_unit_system:
if std_unit_system != unit_system:
raise weewx.UnsupportedFeature(
"Unit type cannot change within a time interval.")
else:
std_unit_system = unit_system
value = weeutil.weeutil.to_complex(magnitude, direction)
start_vec.append(ts - interval * 60)
stop_vec.append(ts)
data_vec.append(value)
unit, unit_group = weewx.units.getStandardUnitType(
std_unit_system, obs_type, aggregate_type)
return (ValueTuple(start_vec, 'unix_epoch', 'group_time'),
ValueTuple(stop_vec, 'unix_epoch',
'group_time'), ValueTuple(data_vec, unit,
unit_group))
def get_series(obs_type, timespan, db_manager, aggregate_type=None, aggregate_interval=None):
"""Get a series, possibly with aggregation, from the main archive database.
The general strategy is that if aggregation is asked for, chop the series up into separate chunks,
calculating the aggregate for each chunk. Then assemble the results.
If no aggregation is called for, just return the data directly out of the database.
"""
startstamp, stopstamp = timespan
start_vec = list()
stop_vec = list()
data_vec = list()
if aggregate_type:
# With aggregation
unit, unit_group = None, None
if aggregate_type == 'cumulative':
total = 0
for stamp in weeutil.weeutil.intervalgen(startstamp, stopstamp, aggregate_interval):
agg_vt = get_aggregate(obs_type, stamp, aggregate_type, db_manager)
if unit:
# It's OK if the unit is unknown (=None).
if agg_vt[1] is not None and (unit != agg_vt[1] or unit_group != agg_vt[2]):
raise weewx.UnsupportedFeature("Cannot change unit groups within an aggregation.")
else:
unit, unit_group = agg_vt[1:]
start_vec.append(stamp.start)
stop_vec.append(stamp.stop)
if aggregate_type == 'cumulative':
total += agg_vt[0]
data_vec.append(total)
else:
data_vec.append(agg_vt[0])
else:
# Without aggregation. We only know how to get series that are in the database schema:
if obs_type not in db_manager.sqlkeys:
raise weewx.UnknownType(obs_type)
# No aggregation
sql_str = "SELECT dateTime, %s, usUnits, `interval` FROM %s " \
"WHERE dateTime >= ? AND dateTime <= ?" % (obs_type, db_manager.table_name)
std_unit_system = None
for record in db_manager.genSql(sql_str, (startstamp, stopstamp)):
if std_unit_system:
if std_unit_system != record[2]:
raise weewx.UnsupportedFeature("Unit type cannot change within an aggregation interval.")
else:
std_unit_system = record[2]
start_vec.append(record[0] - record[3] * 60)
stop_vec.append(record[0])
data_vec.append(record[1])
unit, unit_group = weewx.units.getStandardUnitType(std_unit_system, obs_type, aggregate_type)
return (ValueTuple(start_vec, 'unix_epoch', 'group_time'),
ValueTuple(stop_vec, 'unix_epoch', 'group_time'),
ValueTuple(data_vec, unit, unit_group))
def get_aggregate(obs_type, timespan, aggregate_type, db_manager, **option_dict):
"""Returns an aggregation of pm2_5_aqi over a timespan by using the main archive
table.
obs_type
timespan: An instance of weeutil.Timespan with the time period over which aggregation is to
be done.
aggregate_type: The type of aggregation to be done. For this function, must be 'avg',
'sum', 'count', 'first', 'last', 'min', or 'max'. Anything else will cause
weewx.UnknownAggregation to be raised.
db_manager: An instance of weewx.manager.Manager or subclass.
option_dict: Not used in this version.
returns: A ValueTuple containing the result.
"""
if obs_type not in [ 'pm2_5_aqi', 'pm2_5_aqi_color' ]:
raise weewx.UnknownType(obs_type)
log.debug('get_aggregate(%s, %s, %s, aggregate:%s)' % (
obs_type, timestamp_to_string(timespan.start),
timestamp_to_string(timespan.stop), aggregate_type))
aggregate_type = aggregate_type.lower()
# Raise exception if we don't know about this type of aggregation
if aggregate_type not in list(AQI.agg_sql_dict.keys()):
raise weewx.UnknownAggregation(aggregate_type)
# Form the interpolation dictionary
interpolation_dict = {
'start': timespan.start,
'stop': timespan.stop,
'table_name': db_manager.table_name
}
select_stmt = AQI.agg_sql_dict[aggregate_type] % interpolation_dict
row = db_manager.getSql(select_stmt)
if row:
value, std_unit_system = row
else:
value = None
std_unit_system = None
if value is not None:
if obs_type == 'pm2_5_aqi':
value = AQI.compute_pm2_5_aqi(value)
if obs_type == 'pm2_5_aqi_color':
value = AQI.compute_pm2_5_aqi_color(AQI.compute_pm2_5_aqi(value))
t, g = weewx.units.getStandardUnitType(std_unit_system, obs_type, aggregate_type)
# Form the ValueTuple and return it:
log.debug('get_aggregate(%s, %s, %s, aggregate:%s, select_stmt: %s, returning %s)' % (
obs_type, timestamp_to_string(timespan.start), timestamp_to_string(timespan.stop),
aggregate_type, select_stmt, value))
return weewx.units.ValueTuple(value, t, g)
def get_series(obs_type, timespan, db_manager, aggregate_type=None, aggregate_interval=None):
"""Get a series, possibly with aggregation.
"""
if obs_type not in [ 'pm2_5_aqi', 'pm2_5_aqi_color' ]:
raise weewx.UnknownType(obs_type)
log.debug('get_series(%s, %s, %s, aggregate:%s, aggregate_interval:%s)' % (
obs_type, timestamp_to_string(timespan.start), timestamp_to_string(
timespan.stop), aggregate_type, aggregate_interval))
# Prepare the lists that will hold the final results.
start_vec = list()
stop_vec = list()
data_vec = list()
# Is aggregation requested?
if aggregate_type:
# Yes. Just use the regular series function.
return weewx.xtypes.ArchiveTable.get_series(obs_type, timespan, db_manager, aggregate_type,
aggregate_interval)
else:
# No aggregation.
sql_str = 'SELECT dateTime, usUnits, `interval`, pm2_5 FROM %s ' \
'WHERE dateTime >= ? AND dateTime <= ? AND pm2_5 IS NOT NULL' \
% db_manager.table_name
std_unit_system = None
for record in db_manager.genSql(sql_str, timespan):
ts, unit_system, interval, pm2_5 = record
if std_unit_system:
if std_unit_system != unit_system:
raise weewx.UnsupportedFeature(
"Unit type cannot change within a time interval.")
else:
std_unit_system = unit_system
if obs_type == 'pm2_5_aqi':
value = AQI.compute_pm2_5_aqi(pm2_5)
if obs_type == 'pm2_5_aqi_color':
value = AQI.compute_pm2_5_aqi_color(AQI.compute_pm2_5_aqi(pm2_5))
log.debug('get_series(%s): %s - %s - %s' % (obs_type,
timestamp_to_string(ts - interval * 60),
timestamp_to_string(ts), value))
start_vec.append(ts - interval * 60)
stop_vec.append(ts)
data_vec.append(value)
unit, unit_group = weewx.units.getStandardUnitType(std_unit_system, obs_type,
aggregate_type)
return (ValueTuple(start_vec, 'unix_epoch', 'group_time'),
ValueTuple(stop_vec, 'unix_epoch', 'group_time'),
ValueTuple(data_vec, unit, unit_group))
def get_aggregate(self,
obs_type,
timespan,
aggregate_type=None,
aggregate_interval=None):
if obs_type.starts_with('ch'):
"something"
else:
raise weewx.UnknownType(obs_type)
def get_series(obs_type, timespan, db_manager, aggregate_type=None, aggregate_interval=None):
"""Get a series, possibly with aggregation, for special 'wind' types."""
# Check to see if the requested type is not 'windvec' or 'windgustvec'
if obs_type not in Wind.windvec_types:
# The type is not one of the extended wind types. We can't handle it.
raise weewx.UnknownType(obs_type)
# It is an extended wind type. Prepare the lists that will hold the
# final results.
start_vec = list()
stop_vec = list()
data_vec = list()
# Is aggregation requested?
if aggregate_type:
# Yes. Just use the regular series function, but with the special wind aggregate type. It will
# call the proper aggregation function.
return SeriesArchive.get_series(obs_type, timespan, db_manager, aggregate_type, aggregate_interval)
else:
# No aggregation desired. However, we have will have to assemble the wind vector from its flattened types.
# This SQL select string will select the proper wind types
sql_str = 'SELECT dateTime, %s, %s, usUnits, `interval` FROM %s WHERE dateTime >= ? AND dateTime <= ?' \
% (Wind.windvec_types[obs_type][0], Wind.windvec_types[obs_type][1], db_manager.table_name)
std_unit_system = None
for record in db_manager.genSql(sql_str, timespan):
start_vec.append(record[0] - record[4] * 60)
stop_vec.append(record[0])
if std_unit_system:
if std_unit_system != record[3]:
raise weewx.UnsupportedFeature("Unit type cannot change within a time interval.")
else:
std_unit_system = record[3]
# Break the mag and dir down into x- and y-components.
(magnitude, direction) = record[1:3]
if magnitude is None or direction is None:
data_vec.append(None)
else:
x = magnitude * math.cos(math.radians(90.0 - direction))
y = magnitude * math.sin(math.radians(90.0 - direction))
if weewx.debug:
# There seem to be some little rounding errors that
# are driving my debugging crazy. Zero them out
if abs(x) < 1.0e-6: x = 0.0
if abs(y) < 1.0e-6: y = 0.0
data_vec.append(complex(x, y))
unit, unit_group = weewx.units.getStandardUnitType(std_unit_system, obs_type, aggregate_type)
return (ValueTuple(start_vec, 'unix_epoch', 'group_time'),
ValueTuple(stop_vec, 'unix_epoch', 'group_time'),
ValueTuple(data_vec, unit, unit_group))
def get_series(obs_type, timespan, db_manager, aggregate_type=None, aggregate_interval=None):
"""Return a series (aka vector) of, possibly aggregated, values."""
# Search the list, looking for a get_series() method that does not raise an exception
for xtype in xtypes:
try:
# Try this function. It will raise an exception if it does not know about the type.
return xtype.get_series(obs_type, timespan, db_manager, aggregate_type, aggregate_interval)
except weewx.UnknownType:
# This function does not know about the type. Move on to the next one.
pass
# None of the functions worked.
raise weewx.UnknownType(obs_type)
def get_scalar(obs_type, record, db_manager=None):
"""Return a scalar value"""
# Search the list, looking for a get_scalar() method that does not raise an exception
for xtype in xtypes:
try:
# Try this function. It will raise an exception if it does not know about the type.
return xtype.get_scalar(obs_type, record, db_manager)
except weewx.UnknownType:
# This function does not know about the type. Move on to the next one.
pass
# None of the functions worked.
raise weewx.UnknownType(obs_type)
def _check_eligibility(obs_type, timespan, db_manager, aggregate_type):
# It has to be a type we know about
if not hasattr(db_manager, 'daykeys') or obs_type not in db_manager.daykeys:
raise weewx.UnknownType(obs_type)
# We cannot use the day summaries if the starting and ending times of the aggregation
# interval are not on midnight boundaries, and are not the first or last records in the
# database.
if db_manager.first_timestamp is None or db_manager.last_timestamp is None:
raise weewx.UnknownAggregation(aggregate_type)
if not (isStartOfDay(timespan.start) or timespan.start == db_manager.first_timestamp) \
or not (isStartOfDay(timespan.stop) or timespan.stop == db_manager.last_timestamp):
raise weewx.UnknownAggregation(aggregate_type)
def get_value(self, obs_type, record, db_manager):
if obs_type == 'dewpoint':
if record['usUnits'] == weewx.US:
return weewx.wxformulas.dewpointF(record.get('outTemp'),
record.get('outHumidity'))
elif record['usUnits'] == weewx.METRIC or record[
'usUnits'] == weewx.METRICWX:
return weewx.wxformulas.dewpointC(record.get('outTemp'),
record.get('outHumidity'))
else:
raise ValueError("Unknown unit system %s" % record['usUnits'])
else:
raise weewx.UnknownType(obs_type)
def get_scalar(obs_type, record, db_manager=None):
log.debug('get_scalar(%s)' % obs_type)
if obs_type not in [
'pm2_5_aqi', 'pm2_5_aqi_color', 'pm2_5_lrapa',
'pm2_5_lrapa_aqi', 'pm2_5_lrapa_aqi_color', 'pm2_5_unbc',
'pm2_5_unbc_aqi', 'pm2_5_unbc_aqi_color'
]:
raise weewx.UnknownType(obs_type)
log.debug('get_scalar(%s)' % obs_type)
if record is None:
log.debug('get_scalar called where record is None.')
raise weewx.CannotCalculate(obs_type)
if 'pm2_5' not in record:
log.info('get_scalar called where record does not contain pm2_5.')
raise weewx.CannotCalculate(obs_type)
if record['pm2_5'] is None:
log.info('get_scalar called where record[pm2_5] is None.')
raise weewx.CannotCalculate(obs_type)
try:
pm2_5 = record['pm2_5']
if obs_type == 'pm2_5_aqi':
value = AQI.compute_pm2_5_aqi(pm2_5)
if obs_type == 'pm2_5_aqi_color':
value = AQI.compute_pm2_5_aqi_color(
AQI.compute_pm2_5_aqi(pm2_5))
elif obs_type == 'pm2_5_lrapa':
value = AQI.compute_pm2_5_lrapa(pm2_5)
elif obs_type == 'pm2_5_lrapa_aqi':
pm2_5_lrapa = AQI.compute_pm2_5_lrapa(pm2_5)
value = AQI.compute_pm2_5_aqi(pm2_5_lrapa)
elif obs_type == 'pm2_5_lrapa_aqi_color':
value = AQI.compute_pm2_5_aqi_color(
AQI.compute_pm2_5_aqi(AQI.compute_pm2_5_lrapa(pm2_5)))
elif obs_type == 'pm2_5_unbc':
value = AQI.compute_pm2_5_unbc(pm2_5)
elif obs_type == 'pm2_5_unbc_aqi':
pm2_5_unbc = AQI.compute_pm2_5_unbc(pm2_5)
value = AQI.compute_pm2_5_aqi(pm2_5_unbc)
elif obs_type == 'pm2_5_unbc_aqi_color':
value = AQI.compute_pm2_5_aqi_color(
AQI.compute_pm2_5_aqi(AQI.compute_pm2_5_unbc(pm2_5)))
t, g = weewx.units.getStandardUnitType(record['usUnits'], obs_type)
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, t, g)
except KeyError:
# Don't have everything we need. Raise an exception.
raise weewx.CannotCalculate(obs_type)
def get_aggregate(obs_type, timespan, aggregate_type, db_manager,
**option_dict):
"""Optimization for calculating 'avg' aggregations for type 'windvec'. The
timespan must be on a daily boundary."""
# We can only do observation type 'windvec'
if obs_type != 'windvec':
# We can't handle it.
raise weewx.UnknownType(obs_type)
# We can only do 'avg' or 'not_null
if aggregate_type not in ['avg', 'not_null']:
raise weewx.UnknownAggregation(aggregate_type)
# We cannot use the day summaries if the starting and ending times of the aggregation
# interval are not on midnight boundaries, and are not the first or last records in the
# database.
if not (isStartOfDay(timespan.start) or timespan.start == db_manager.first_timestamp) \
or not (isStartOfDay(timespan.stop) or timespan.stop == db_manager.last_timestamp):
raise weewx.UnknownAggregation(aggregate_type)
if aggregate_type == 'not_null':
# Aggregate type 'not_null' is actually run against 'wind'.
return DailySummaries.get_aggregate('wind', timespan, 'not_null',
db_manager, **option_dict)
sql = 'SELECT SUM(xsum), SUM(ysum), SUM(dirsumtime) ' \
'FROM %s_day_wind WHERE dateTime>=? AND dateTime<?;' % db_manager.table_name
row = db_manager.getSql(sql, timespan)
if not row or None in row or not row[2]:
# If no row was returned, or if it contains any nulls (meaning that not
# all required data was available to calculate the requested aggregate),
# then set the resulting value to None.
value = None
else:
value = complex(row[0], row[1]) / row[2]
# Look up the unit type and group of the result:
t, g = weewx.units.getStandardUnitType(db_manager.std_unit_system,
obs_type, aggregate_type)
# Return as a value tuple
return weewx.units.ValueTuple(value, t, g)
def get_scalar(self, obs_type, record, db_manager):
# We only know how to calculate 'vapor_p'. For everything else, raise an exception UnknownType
if obs_type != 'vapor_p':
raise weewx.UnknownType(obs_type)
# We need outTemp in order to do the calculation.
if 'outTemp' not in record or record['outTemp'] is None:
raise weewx.CannotCalculate(obs_type)
# We have everything we need. Start by forming a ValueTuple for the outside temperature.
# To do this, figure out what unit and group the record is in ...
unit_and_group = weewx.units.getStandardUnitType(
record['usUnits'], 'outTemp')
# ... then form the ValueTuple.
outTemp_vt = ValueTuple(record['outTemp'], *unit_and_group)
# Both algorithms need temperature in Celsius, so let's make sure our incoming temperature
# is in that unit. Use function convert(). The results will be in the form of a ValueTuple
outTemp_C_vt = weewx.units.convert(outTemp_vt, 'degree_C')
# Get the first element of the ValueTuple. This will be in Celsius:
outTemp_C = outTemp_C_vt[0]
if self.algorithm == 'simple':
# Use the "Simple" algorithm.
# We need temperature in Kelvin.
outTemp_K = weewx.units.CtoK(outTemp_C)
# Now we can use the formula. Results will be in mmHg. Create a ValueTuple out of it:
p_vt = ValueTuple(math.exp(20.386 - 5132.0 / outTemp_K), 'mmHg',
'group_pressure')
elif self.algorithm == 'tetens':
# Use Teten's algorithm.
# Use the formula. Results will be in kPa:
p_kPa = 0.61078 * math.exp(17.27 * outTemp_C_vt[0] /
(outTemp_C_vt[0] + 237.3))
# Form a ValueTuple
p_vt = ValueTuple(p_kPa, 'kPa', 'group_pressure')
else:
# Don't recognize the exception. Fail hard:
raise ValueError(self.algorithm)
# We have the vapor pressure as a ValueTuple. Convert it back to the units used by
# the incoming record and return it
return weewx.units.convertStd(p_vt, record['usUnits'])
def get_scalar(self, obs_type, record, db_manager):
# We only know how to calculate some sun and moon related stuff. For everything else, raise an exception UnknownType
if obs_type not in ('sun_altitude', 'sun_azimuth'):
raise weewx.UnknownType(obs_type)
# we only report sun values if the sun is above the horizon
almanac = Almanac(record['dateTime'], self.lat, self.lng,
0) # TODO convert alt to meters
sun_altitude = almanac.sun.alt
if obs_type == 'sun_altitude':
value = ValueTuple(sun_altitude if sun_altitude >= 0 else None,
'degree_compass', 'group_direction')
elif obs_type == 'sun_azimuth':
value = ValueTuple(almanac.sun.az if sun_altitude >= 0 else None,
'degree_compass', 'group_direction')
# We have the calculated values as ValueTuples. Convert them back to the units used by
# the incoming record and return it
return weewx.units.convertStd(value, record['usUnits'])
def get_scalar(obs_type, record, db_manager=None, **option_dict):
"""Return a scalar value"""
# Search the list, looking for a get_scalar() method that does not raise an UnknownType
# exception
for xtype in xtypes:
try:
# Try this function. Be prepared to catch the TypeError exception if it is a legacy
# style XType that does not accept kwargs.
try:
return xtype.get_scalar(obs_type, record, db_manager, **option_dict)
except TypeError:
# We likely have a legacy style XType, so try calling it again, but this time
# without the kwargs.
return xtype.get_scalar(obs_type, record, db_manager)
except weewx.UnknownType:
# This function does not know about the type. Move on to the next one.
pass
# None of the functions worked.
raise weewx.UnknownType(obs_type)
def get_scalar(self, obs_type, record, db_manager):
# We only know how to calculate 'makkink'. For everything else, raise an exception UnknownType
if obs_type != 'makkink':
raise weewx.UnknownType(obs_type)
# We need outTemp and the radiation in order to do the calculation.
if 'outTemp' not in record or record['outTemp'] is None:
raise weewx.CannotCalculate(obs_type)
if 'radiation' not in record or record['radiation'] is None:
raise weewx.CannotCalculate(obs_type)
# We have everything we need. Start by forming a ValueTuple for the outside temperature.
# To do this, figure out what unit and group the record is in ...
unit_and_group = weewx.units.getStandardUnitType(
record['usUnits'], 'outTemp')
# ... then form the ValueTuple.
outTemp_vt = ValueTuple(record['outTemp'], *unit_and_group)
# same for radiation
unit_and_group = weewx.units.getStandardUnitType(
record['usUnits'], 'radiation')
# ... then form the ValueTuple.
radiation_vt = ValueTuple(record['radiation'], *unit_and_group)
outTemp_C_vt = weewx.units.convert(outTemp_vt, 'degree_C')
# Get the first element of the ValueTuple. This will be in Celsius:
T = outTemp_C_vt[0]
# just to make sure nothing fancy happens we do this for radiation as well
# even though this is W/m2 in us as well as metric
radiation_Wm2_vt = weewx.units.convert(radiation_vt,
'watt_per_meter_squared')
Kin = radiation_Wm2_vt[0]
makkink = ValueTuple(
self.Eref(T, Kin) * 3600, 'mm_per_hour',
'group_rainrate') # convert from kg/m2*s --> mm/hour
# Convert it back to the units used by
# the incoming record and return it
return weewx.units.convertStd(makkink, record['usUnits'])
def get_scalar(self, obs_type, record, db_manager, **option_dict):
""" mandatory function to be defined for XType extensions """
if obs_type is None:
raise weewx.UnknownType("obs_type is None")
# time offset of local mean time (LMT)
if obs_type == 'utcoffsetLMT':
return weewx.units.ValueTuple(
self.lmt_tz.utcoffset(None).total_seconds(), 'second',
'group_deltatime')
# dateTime as string in local mean time
if obs_type == 'LMTtime':
if record is None:
raise weewx.UnknownType("%s: no record" % obs_type)
return weewx.units.ValueTuple(
datetime.datetime.fromtimestamp(
record['dateTime'], self.lmt_tz).strftime("%H:%M:%S"),
'unix_epoch', 'group_time')
# This functions handles 'GTS' and 'GTSdate'.
if obs_type not in [
'GTS', 'GTSdate', 'dayET', 'ET24', 'yearGDD', 'seasonGDD'
]:
raise weewx.UnknownType(obs_type)
#if record is None:
# if self.record_ok:
# logerr("%s: no record (logged only once)" % obs_type)
# self.record_ok=False
# raise weewx.CannotCalculate("%s: no record" % obs_type)
if db_manager is None:
if self.db_manager_ok:
logerr("%s: db_manager is None" & obs_type)
self.db_manager_ok = False
raise weewx.CannotCalculate("%s: no database reference" % obs_type)
#logdbg("obs_type=%s" % obs_type)
# needed timestamps
if record is not None and 'dateTime' in record:
_time_ts = record['dateTime']
else:
# that should never happen but does due to a bug in
# Belchertown skin
if self.record_ok:
logerr("%s: no record (logged only once)" % obs_type)
self.record_ok = False
# to do something we deliver the last available value
_time_ts = time.time()
if obs_type == 'dayET':
# dayET should be comparable to dayRain, so use the same
# time span: not local mean time but archive time
try:
# startOfArchiveDay() considers midnight belonging
# to the previous day. So the time span would be
# always greater than 0.
__x = weeutil.weeutil.startOfArchiveDay(_time_ts)
__x = weeutil.weeutil.TimeSpan(__x, _time_ts)
except (ValueError, TypeError, IndexError):
raise weewx.CannotCalculate("dayET: invalid time")
return weewx.xtypes.get_aggregate('ET', __x, 'sum', db_manager)
if obs_type == 'ET24':
try:
__x = weeutil.weeutil.TimeSpan(_time_ts - 86400, _time_ts)
except:
raise weewx.CannotCalculate("ET24: invalid time")
return weewx.xtypes.get_aggregate('ET', __x, 'sum', db_manager)
_soy_ts = startOfYearTZ(_time_ts, self.lmt_tz)
_sod_ts = startOfDayTZ(_time_ts, _soy_ts) # start of day
# If the start of the year in question is before the first
# record in the database, no value can be calculated. The
# same applies if the given timestamp is in future.
#if _soy_ts<db_manager.first_timestamp or _sod_ts>db_manager.last_timestamp:
# raise weewx.CannotCalculate(obs_type)
# growing degree days == Wachstumsgradtage
# https://de.wikipedia.org/wiki/Wachstumsgradtag
# https://en.wikipedia.org/wiki/Growing_degree-day
if obs_type in ['yearGDD']:
try:
# calculate from the beginning of the year up to the
# end of the current day
__timespan = TimeSpan(_soy_ts, _sod_ts + 86400)
return self.get_aggregate('outTemp', __timespan, 'GDD',
db_manager, **option_dict)
except (ValueError, TypeError, IndexError, KeyError):
raise weewx.CannotCalculate("%s" % obs_type)
# calculate GTS values for the given year
# (if record['dateTime'] is within the current year, the
# value is calculated up to the current day (today))
self.calc_gts(_soy_ts, db_manager)
# growing degree days == Wachstumsgradtage
# https://de.wikipedia.org/wiki/Wachstumsgradtag
# https://en.wikipedia.org/wiki/Growing_degree-day
if obs_type in ['seasonGDD']:
try:
# calculate from the beginning of the year up to the
# end of the current day
__start_ts = self.gts_date[_soy_ts]
if __start_ts and _sod_ts >= __start_ts and _sod_ts < _soy_ts + 26179200:
__timespan = TimeSpan(__start_ts, _sod_ts + 86400)
return self.get_aggregate('outTemp', __timespan, 'GDD',
db_manager, **option_dict)
except (ValueError, TypeError, IndexError, KeyError):
#raise weewx.CannotCalculate("%s" % obs_type)
pass
return weewx.units.ValueTuple(None, 'degree_C_day',
'group_degree_day')
# check if the requested timestamp record['dateTime'] is within
# the current day (today)
# Note: After self.calc_gts() is run, self.last_gts_date
# points to the beginning of the current day, if
# record['dateTime'] is within the current year.
# if record['dateTime'] is _not_ within the current
# year, self.last_gts_date _may_ be None.
if record is None:
# record is not provided, we assume the actual time
# Note: That should not happen but does due to a bug in
# Belchertown skin
if _sod_ts != self.last_gts_date:
raise weewx.CannotCalculate("%s: no record" % obs_type)
__today = True
elif self.last_gts_date is None or self.gts_value is None:
# The current year is not calculated so far, that means,
# record['dateTime'] cannot be within the current day (today).
__today = False
elif _time_ts <= self.last_gts_date:
# record['dateTime'] is before self.last_gts_date.
# As self.last_gts_date points to the beginning of
# the current day, that means, record['dateTime'] is not
# the current day (today).
__today = False
else:
# record['dateTime'] is after the beginning of the
# current day. If it is additionally before
# self.last_gts_date+86400 (1d after), it is within
# the current day (today).
__today = _time_ts <= self.last_gts_date + 86400
# get the result
if __today:
# current value
if obs_type == 'GTS':
# current GTS value
__x = weewx.units.ValueTuple(self.gts_value, 'degree_C_day',
'group_degree_day')
elif obs_type == 'GTSdate':
# current GTSdate value or None, if GTS<200
if _soy_ts in self.gts_date:
__x = self.gts_date[_soy_ts]
else:
__x = None
__x = weewx.units.ValueTuple(__x, 'unix_epoch', 'group_time')
else:
# should not occure
raise weewx.CannotCalculate(obs_type)
else:
# value from memory
__x = self.get_gts(obs_type, _sod_ts, _soy_ts)
"""
try:
a=str(__x[0])
except:
logerr("get_scalar 0")
a=""
try:
b=str(__x[1])
except:
logerr("get_scalar 1")
b=""
try:
c=str(__x[2])
except:
logerr("get_scalar 2")
c=""
loginf("get_scalar %s,%s,%s" % (a,b,c))
"""
if record is None: return __x
return weewx.units.convertStd(__x, record['usUnits'])
def get_aggregate(self, obs_type, timespan, aggregate_type, db_manager,
**option_dict):
if obs_type is None:
raise weewx.UnknownType("obs_type is None")
# time offset of local mean time (LMT)
if obs_type == 'utcoffsetLMT':
return weewx.units.ValueTuple(
self.lmt_tz.utcoffset(None).total_seconds(), 'second',
'group_deltatime')
# energy_integral can be calculated for group_radiation observation
# types like 'radiation' and 'maxSolarRad'
if aggregate_type == 'energy_integral':
if obs_type in weewx.units.obs_group_dict and weewx.units.obs_group_dict[
obs_type] == 'group_radiation':
return self.calc_radiation_integral(obs_type, timespan,
db_manager)
# growing degree days == Wachstumsgradtage
# https://de.wikipedia.org/wiki/Wachstumsgradtag
# https://en.wikipedia.org/wiki/Growing_degree-day
if aggregate_type in ['growdeg', 'GDD']:
# growing degree day can only be calculated for a temperature
if weewx.units.obs_group_dict.get(obs_type,
'') != 'group_temperature':
raise weewx.CannotCalculate(
"%s is not temperature for aggregation %s" %
(obs_type, aggregate_type))
# if the base value is defined in skin.conf or weewx.conf, get
# it for default
units_dict = option_dict.get('skin_dict', {}).get('Units', {})
dd_dict = units_dict.get('DegreeDays', {})
base_vt = dd_dict.get(
'growing_base',
weewx.xtypes.AggregateHeatCool.default_growbase)
# if parameters are specified get them
val = option_dict.get('val')
#loginf("%s" % type(val))
#loginf(val)
if val:
# GDD with parameters
try:
# dict
method = val.get('method', 'integral')
base_vt = val.get('base', base_vt)
limit_vt = val.get('limit', self.GDD_LIMIT_VT)
stop_vt = val.get('stop')
except TypeError:
# tuple used as base temperature
base_vt = weewx.units.ValueTuple(float(val[0]), val[1],
'group_temperature')
limit_vt = None
stop_vt = None
method = 'integral'
else:
# GDD alone: use defaults
method = 'integral'
limit_vt = self.GDD_LIMIT_VT
stop_vt = None
# Convert to a ValueTuple in the same unit system as the database
__base = weewx.units.convertStd(
(float(base_vt[0]), base_vt[1], 'group_temperature'),
db_manager.std_unit_system)[0]
if limit_vt:
try:
__limit = weewx.units.convertStd(
(float(limit_vt[0]), limit_vt[1], 'group_temperature'),
db_manager.std_unit_system)[0]
except IndexError:
if limit_vt.lower() == 'none': __limit = None
else:
__limit = None
if stop_vt:
try:
__stop = weewx.units.convertStd(
(float(stop_vt[0]), stop_vt[1], 'group_temperature'),
db_manager.std_unit_system)[0]
except IndexError:
if stop_vt.lower() == 'none': __stop = None
else:
__stop = None
#loginf("method %s" % method)
#loginf(base_vt)
#loginf(limit_vt)
# calculate GDD sum
if method == 'integral':
# integral over timespan
return self.calc_GDD_integral(obs_type, timespan, db_manager,
__base, __limit, __stop)
if method in ['hiloavgA', 'hiloavgB', 'dayavg']:
# based on daily average or average of high and low.
# Check if day border should be based on Local Mean Time
# or local timezone time
__lmt_tz = option_dict.get('LMT', {}).get('timezone')
if __lmt_tz is None:
__lmt_tz = option_dict.get('dayboundary',
{}).get('timezone')
return self.calc_GDD_avg(obs_type, timespan, db_manager,
method, __base, __limit, __stop,
__lmt_tz)
if method == 'weewx' and obs_type == 'outTemp':
# call builtin method of WeeWX for outTemp
return weewx.xtypes.get_aggregate('growdeg', timespan, 'sum',
db_manager, **option_dict)
raise weewx.CannotCalculate("GDD %s: unknown method" % method)
# accumulated growing degree days
if obs_type == 'yearGDD' or obs_type == 'seasonGDD':
#loginf("GDD %s" % option_dict)
#loginf("GDD %s" % aggregate_type)
if aggregate_type.lower() == 'avg':
if timespan.start > time.time() or (
timespan.start +
timespan.stop) / 2 > time.time() + 90000:
return weewx.units.ValueTuple(None, 'degree_C_day',
'group_degree_days')
return self.get_scalar(
obs_type,
{'dateTime': (timespan.start + timespan.stop) / 2},
db_manager, **option_dict)
if aggregate_type.lower() == 'last':
return self.get_scalar(obs_type, {'dateTime': timespan.stop},
db_manager, **option_dict)
raise weewx.UnknownAggregation("%s undefinded aggregation %s" %
(obs_type, aggregation_type))
# This function handles 'GTS' and 'GTSdate'.
if obs_type != 'GTS' and obs_type != 'GTSdate':
raise weewx.UnknownType(obs_type)
# aggregation types that are defined for those values
if aggregate_type not in [
'avg', 'max', 'min', 'last', 'maxtime', 'mintime', 'lasttime'
]:
raise weewx.UnknownAggregation("%s undefinded aggregation %s" %
(obs_type, aggregation_type))
if timespan is None:
raise weewx.CannotCalculate("%s %s no timespan" %
(obs_type, aggregate_type))
if db_manager is None:
if self.db_manager_ok:
logerr("%s: no database reference" % obs_type)
self.db_manager_ok = False
raise weewx.CannotCalculate("%s: no database reference" % obs_type)
# needed timestamps
_soya_ts = startOfYearTZ(timespan.start + 1, self.lmt_tz)
_soye_ts = startOfYearTZ(timespan.stop, self.lmt_tz)
# calculate GTS values for the years included in timespan
# (if time span is within the current year, the
# value is calculated up to the current day (today))
__max = 0
__maxtime = None
__min = 10000000
__mintime = None
__ts = _soya_ts
# Even if the time span starts after May 31st, the end value
# is needed for some aggregations. So we have to calculate
# that year, too.
while __ts <= _soye_ts:
# calculate GTS values for the year
self.calc_gts(__ts, db_manager)
# update minimum and maximum
if __ts in self.gts_values:
for __i, __val in enumerate(self.gts_values[__ts]):
if __val is not None and __val > __max:
__max = __val
__maxtime = __ts + __i * 86400
if __val is not None and __val < __min:
__min = __val
__mintime = __ts + __i * 86400
# next year
__ts = startOfYearTZ(__ts + 31708800, self.lmt_tz)
if obs_type == 'GTS':
if aggregate_type == 'avg':
# 1 day is 86400s, but once a year it is 90000s or 82800s
# when the daylight savings time is switched on or off.
if timespan.stop - timespan.start <= 90000:
__a = startOfDayTZ(timespan.start, _soya_ts)
__b = startOfDayTZ(timespan.stop, _soye_ts)
if __a != __b:
# begin and end of timespan are different days
# according to timezone self.lmt_tz
# timespan.start <= __b <= timespan.stop
if __b - timespan.start > timespan.stop - __b:
__b = __a
_soye_ts = _soya_ts
if __b >= _soye_ts + 13046400:
__x = weewx.units.ValueTuple(None, 'degree_C_day',
'group_degree_day')
else:
__x = self.get_gts(obs_type, __b, _soye_ts)
elif _soya_ts == _soye_ts and _soya_ts in self.gts_values:
# timespan within the same year but more than one day
# (not much use, but calculated anyway)
__a = dayOfGTSYear(timespan.start, _soya_ts)
__b = dayOfGTSYear(timespan.stop, _soye_ts)
if __a == __b:
__x = self.gts_values[_soya_ts][__a]
else:
__x = 0
for __i in xrange(__a, __b):
if self.gts_values[_soya_ts][__i] is not None:
__x += self.gts_values[_soya_ts][__i]
__x /= __b - __a
else:
raise weewx.CannotCalculate(
"%s %s invalid timespan %s %s" %
(obs_type, aggregate_type,
timespan.stop - timespan.start,
time.strftime("%Y-%m-%d %H:%M:%S",
time.localtime(timespan.start))))
elif aggregate_type == 'lasttime':
if timespan.stop >= self.last_gts_date:
# today or in future
__ts = self.last_gts_date
else:
# before today
if _soye_ts not in self.gts_values:
raise weewx.CannotCalculate("%s %s" %
(obs_type, aggregate_type))
__ts = dayOfGTSYear(timespan.stop, _soye_ts)
for __i, __v in reversed(
enumerate(self.gts_values[_soye_ts])):
if __v is not None and __i <= __ts:
__ts = _soye_ts + 86400 * __i
break
else:
__ts = _soye_ts
__x = weewx.units.ValueTuple(__ts, 'unix_epoch', 'group_time')
elif aggregate_type == 'last':
if timespan.stop >= _soye_ts + 13046400:
# after May 31st
__ts = _soye_ts + 13046400 - 86400
else:
# between Jan 1st and May 31st
__ts = startOfDayTZ(timespan.stop, _soye_ts)
# startOfDay() returns for 24:00 the start of the
# next day. So we need to look for the day before.
if __ts == timespan.stop:
__ts -= 86400
# for today there is no value so far
if __ts == startOfDayTZ(time.time(), _soye_ts):
__ts -= 86400
__x = self.get_gts(obs_type, __ts, _soye_ts)
elif aggregate_type == 'max':
__x = weewx.units.ValueTuple(__max, 'degree_C_day',
'group_degree_day')
elif aggregate_type == 'maxtime':
__x = weewx.units.ValueTuple(__maxtime, 'unix_epoch',
'group_time')
elif aggregate_type == 'min':
__x = weewx.units.ValueTuple(__min, 'degree_C_day',
'group_degree_day')
elif aggregate_type == 'mintime':
__x = weewx.units.ValueTuple(__mintime, 'unix_epoch',
'group_time')
else:
raise weewx.CannotCalculate("%s %s" %
(obs_type, aggregate_type))
"""
try:
a=str(__x[0])
except:
logerr("get_aggregate 0")
a=""
try:
b=str(__x[1])
except:
logerr("get_aggregate 1")
b=""
try:
c=str(__x[2])
except:
logerr("get_aggregate 2")
c=""
loginf("get_aggregate %s,%s,%s" % (a,b,c))
"""
return __x
if obs_type == 'GTSdate':
if aggregate_type == 'last' or aggregate_type == 'max':
if _soye_ts in self.gts_date and self.gts_date[
_soye_ts] is not None and timespan.stop >= self.gts_date[
_soye_ts]:
__x = self.gts_date[_soye_ts]
else:
__x = None
return weewx.units.ValueTuple(__x, 'unix_epoch', 'group_time')
raise weewx.CannotCalculate("%s %s" % (obs_type, aggregate_type))
def get_gdd_series(self, obs_type, timespan, db_manager):
"""Get Growing Degree Days series.
This function returns a list of four ValueTuple vectors:
start_time, stop_time, gdd, and gdd_cumulative.
"""
try:
model = self.metadata[obs_type]
except KeyError:
raise weewx.UnknownType(obs_type)
converter = weewx.units.StdUnitConverters[db_manager.std_unit_system]
self.convert_metadata_to_standard_units(converter, model)
vector_time_stamp = []
vector_temp_min = []
vector_temp_max = []
for day_time_span in weeutil.weeutil.genDaySpans(*timespan):
vector_time_stamp.append(day_time_span)
temp_min = weewx.xtypes.DailySummaries.get_aggregate(
'outTemp', day_time_span, 'min', db_manager)
temp_max = weewx.xtypes.DailySummaries.get_aggregate(
'outTemp', day_time_span, 'max', db_manager)
vector_temp_min.append(temp_min)
vector_temp_max.append(temp_max)
day_count = len(vector_time_stamp)
vector_time_stamp_start = []
vector_time_stamp_stop = []
vector_gdd = []
vector_gdd_cumulative = []
total = ZERO
(threshold_temp, threshold_temp_units) = model['threshold_t'][:2]
(cutoff_temp, cutoff_units) = model['cutoff_t'][:2]
if cutoff_units in ['degree_F']:
scale = 'f'
else:
scale = 'c'
method = user.growing_degrees.__dict__[model['method']]
for (ndx, day_time_span) in enumerate(vector_time_stamp):
try:
(temp_max, temp_max_units) = vector_temp_max[ndx][:2]
(temp_min, temp_min_units) = vector_temp_min[ndx][:2]
if ndx + 1 < day_count:
(temp_min_2,
temp_min_2_units) = vector_temp_min[ndx + 1][:2]
else:
(temp_min_2, temp_min_2_units) = (None, None)
assert temp_max_units == temp_min_units == threshold_temp_units
if None in [temp_max, temp_min]:
gdd = None
else:
gdd = method(
day_max_temp=temp_max,
day_min_temp=temp_min,
threshold_temp=threshold_temp,
cutoff_temp=cutoff_temp,
day_2_min_temp=temp_min_2,
scale=scale,
)
if gdd is None:
pass
else:
(day_time_stamp_start,
day_time_stamp_stop) = day_time_span
vector_time_stamp_start.append(day_time_stamp_start)
vector_time_stamp_stop.append(day_time_stamp_stop)
vector_gdd.append(gdd)
total += gdd
vector_gdd_cumulative.append(total)
except KeyError as e:
LOG.error("Missing model parameters. {}".format(e))
raise weewx.CannotCalculate
except ValueError:
LOG.error("Bad calculation.")
raise weewx.CannotCalculate
except AssertionError:
LOG.error("Mixed units.")
raise weewx.CannotCalculate
(unit, unit_group) = weewx.units.getStandardUnitType(
db_manager.std_unit_system, 'cooldeg', agg_type=None)
result = []
result.append(
weewx.units.ValueTuple(vector_time_stamp_start, 'unix_epoch',
'group_time'))
result.append(
weewx.units.ValueTuple(vector_time_stamp_stop, 'unix_epoch',
'group_time'))
result.append(weewx.units.ValueTuple(vector_gdd, unit, unit_group))
result.append(
weewx.units.ValueTuple(vector_gdd_cumulative, unit, unit_group))
return result
def get_aggregate(obs_type, timespan, aggregate_type, db_manager, **option_dict):
"""Returns an aggregation of a wind vector type over a timespan by using the main archive table.
obs_type: The type over which aggregation is to be done. For this function,
it must be 'windvec' or 'windgustvec'. Anything else will cause weewx.UnknownType
to be raised.
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
aggregate_type: The type of aggregation to be done. For this function, must be
'avg', 'sum', 'count', 'first', 'last', 'min', or 'max'. Anything else will cause
weewx.UnknownAggregation to be raised.
db_manager: An instance of weewx.manager.Manager or subclass.
option_dict: Not used in this version.
returns: A ValueTuple containing the result. Note that the value contained in the ValueTuple
will be a complex number.
"""
if obs_type not in WindVec.windvec_types:
raise weewx.UnknownType(obs_type)
aggregate_type = aggregate_type.lower()
# Raise exception if we don't know about this type of aggregation
if aggregate_type not in ['avg', 'sum'] + list(WindVec.agg_sql_dict.keys()):
raise weewx.UnknownAggregation(aggregate_type)
# Form the interpolation dictionary
interpolation_dict = {
'dir': WindVec.windvec_types[obs_type][1],
'mag': WindVec.windvec_types[obs_type][0],
'start': weeutil.weeutil.startOfDay(timespan.start),
'stop': timespan.stop,
'table_name': db_manager.table_name
}
if aggregate_type in WindVec.agg_sql_dict:
# For these types (e.g., first, last, etc.), we can do the aggregation in a SELECT statement.
select_stmt = WindVec.agg_sql_dict[aggregate_type] % interpolation_dict
row = db_manager.getSql(select_stmt)
if row:
if aggregate_type == 'count':
value, std_unit_system = row
else:
magnitude, direction, std_unit_system = row
value = weeutil.weeutil.to_complex(magnitude, direction)
else:
std_unit_system = db_manager.std_unit_system
value = None
else:
# The result is more complex, requiring vector arithmetic. We will have to do it
# in Python
std_unit_system = None
xsum = ysum = 0.0
count = 0
select_stmt = WindVec.complex_sql_wind % interpolation_dict
for rec in db_manager.genSql(select_stmt, timespan):
# Unpack the record
mag, direction, unit_system = rec
# Ignore rows where magnitude is NULL
if mag is None:
continue
# A good direction is necessary unless the mag is zero:
if mag == 0.0 or direction is not None:
if std_unit_system:
if std_unit_system != unit_system:
raise weewx.UnsupportedFeature("Unit type cannot change within a time interval.")
else:
std_unit_system = unit_system
# An undefined direction is OK (and expected) if the magnitude
# is zero. But, in that case, it doesn't contribute to the sums either.
if direction is None:
# Sanity check
if weewx.debug:
assert (mag == 0.0)
else:
xsum += mag * math.cos(math.radians(90.0 - direction))
ysum += mag * math.sin(math.radians(90.0 - direction))
count += 1
# We've gone through the whole interval. Were there any good data?
if count:
# Form the requested aggregation:
if aggregate_type == 'sum':
value = complex(xsum, ysum)
else:
# Must be 'avg'
value = complex(xsum, ysum) / count
else:
value = None
# Look up the unit type and group of this combination of observation type and aggregation:
t, g = weewx.units.getStandardUnitType(std_unit_system, obs_type, aggregate_type)
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, t, g)
def get_aggregate(obs_type, timespan, aggregate_type, db_manager, **option_dict):
"""Returns heating and cooling degree days over a time period.
obs_type: The type over which aggregation is to be done. Must be one of 'heatdeg', 'cooldeg', or 'growdeg'.
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
aggregate_type: The type of aggregation to be done. Must be 'avg' or 'sum'.
db_manager: An instance of weewx.manager.Manager or subclass.
option_dict: Not used in this version.
returns: A ValueTuple containing the result.
"""
# Check to see whether heating or cooling degree days are being asked for:
if obs_type not in ['heatdeg', 'cooldeg', 'growdeg']:
raise weewx.UnknownType(obs_type)
# Only summation (total) or average heating or cooling degree days is supported:
if aggregate_type not in ['sum', 'avg']:
raise weewx.UnknownAggregation(aggregate_type)
# Get the base for heating and cooling degree-days
units_dict = option_dict.get('skin_dict', {}).get('Units', {})
dd_dict = units_dict.get('DegreeDays', {})
heatbase = dd_dict.get('heating_base', AggregateHeatCool.default_heatbase)
coolbase = dd_dict.get('cooling_base', AggregateHeatCool.default_coolbase)
growbase = dd_dict.get('growing_base', AggregateHeatCool.default_growbase)
# Convert to a ValueTuple in the same unit system as the database
heatbase_t = weewx.units.convertStd((float(heatbase[0]), heatbase[1], "group_temperature"),
db_manager.std_unit_system)
coolbase_t = weewx.units.convertStd((float(coolbase[0]), coolbase[1], "group_temperature"),
db_manager.std_unit_system)
growbase_t = weewx.units.convertStd((float(growbase[0]), growbase[1], "group_temperature"),
db_manager.std_unit_system)
total = 0.0
count = 0
for daySpan in weeutil.weeutil.genDaySpans(timespan.start, timespan.stop):
# Get the average temperature for the day as a value tuple:
Tavg_t = DailySummaries.get_aggregate('outTemp', daySpan, 'avg', db_manager)
# Make sure it's valid before including it in the aggregation:
if Tavg_t is not None and Tavg_t[0] is not None:
if obs_type == 'heatdeg':
total += weewx.wxformulas.heating_degrees(Tavg_t[0], heatbase_t[0])
elif obs_type == 'cooldeg':
total += weewx.wxformulas.cooling_degrees(Tavg_t[0], coolbase_t[0])
else:
total += weewx.wxformulas.cooling_degrees(Tavg_t[0], growbase_t[0])
count += 1
if aggregate_type == 'sum':
value = total
else:
value = total / count if count else None
# Look up the unit type and group of the result:
t, g = weewx.units.getStandardUnitType(db_manager.std_unit_system, obs_type, aggregate_type)
# Return as a value tuple
return weewx.units.ValueTuple(value, t, g)
def get_aggregate(obs_type, timespan, aggregate_type, db_manager, **option_dict):
"""Returns an aggregation of a statistical type for a given time period,
by using the daily summaries.
obs_type: The type over which aggregation is to be done (e.g., 'barometer',
'outTemp', 'rain', ...)
timespan: An instance of weeutil.Timespan with the time period over which
aggregation is to be done.
aggregate_type: The type of aggregation to be done.
db_manager: An instance of weewx.manager.Manager or subclass.
option_dict: Not used in this version.
returns: A ValueTuple containing the result."""
# Check to see if this is a valid daily summary type:
if not hasattr(db_manager, 'daykeys') or obs_type not in db_manager.daykeys:
raise weewx.UnknownType(obs_type)
aggregate_type = aggregate_type.lower()
# Raise exception if we don't know about this type of aggregation
if aggregate_type not in DailySummaries.daily_sql_dict:
raise weewx.UnknownAggregation(aggregate_type)
# We cannot use the day summaries if the starting and ending times of the aggregation interval are not on
# midnight boundaries, and are not the first or last records in the database.
if not (isStartOfDay(timespan.start) or timespan.start == db_manager.first_timestamp) \
or not (isStartOfDay(timespan.stop) or timespan.stop == db_manager.last_timestamp):
raise weewx.UnknownAggregation(aggregate_type)
val = option_dict.get('val')
if val is None:
target_val = None
else:
# The following is for backwards compatibility when ValueTuples had
# just two members. This hack avoids breaking old skins.
if len(val) == 2:
if val[1] in ['degree_F', 'degree_C']:
val += ("group_temperature",)
elif val[1] in ['inch', 'mm', 'cm']:
val += ("group_rain",)
target_val = weewx.units.convertStd(val, db_manager.std_unit_system)[0]
# Form the interpolation dictionary
interDict = {
'start': weeutil.weeutil.startOfDay(timespan.start),
'stop': timespan.stop,
'obs_key': obs_type,
'aggregate_type': aggregate_type,
'val': target_val,
'table_name': db_manager.table_name
}
# Run the query against the database:
row = db_manager.getSql(DailySummaries.daily_sql_dict[aggregate_type] % interDict)
# Each aggregation type requires a slightly different calculation.
if not row or None in row:
# If no row was returned, or if it contains any nulls (meaning that not
# all required data was available to calculate the requested aggregate),
# then set the resulting value to None.
value = None
elif aggregate_type in ['min', 'maxmin', 'max', 'minmax', 'meanmin', 'meanmax',
'maxsum', 'minsum', 'sum', 'gustdir']:
# These aggregates are passed through 'as is'.
value = row[0]
elif aggregate_type in ['mintime', 'maxmintime', 'maxtime', 'minmaxtime', 'maxsumtime',
'minsumtime', 'count', 'max_ge', 'max_le', 'min_ge', 'min_le',
'sum_ge', 'sum_le']:
# These aggregates are always integers:
value = int(row[0])
elif aggregate_type == 'avg':
value = row[0] / row[1] if row[1] else None
elif aggregate_type == 'rms':
value = math.sqrt(row[0] / row[1]) if row[1] else None
elif aggregate_type == 'vecavg':
value = math.sqrt((row[0] ** 2 + row[1] ** 2) / row[2] ** 2) if row[2] else None
elif aggregate_type == 'vecdir':
if row == (0.0, 0.0):
value = None
deg = 90.0 - math.degrees(math.atan2(row[1], row[0]))
value = deg if deg >= 0 else deg + 360.0
else:
# Unknown aggregation. Should not have gotten this far...
raise ValueError("Unexpected error. Aggregate type '%s'" % aggregate_type)
# Look up the unit type and group of this combination of observation type and aggregation:
t, g = weewx.units.getStandardUnitType(db_manager.std_unit_system, obs_type, aggregate_type)
# Form the ValueTuple and return it:
return weewx.units.ValueTuple(value, t, g)
def get_series(obs_type,
timespan,
db_manager,
aggregate_type=None,
aggregate_interval=None):
"""Get a series, possibly with aggregation, from the main archive database.
The general strategy is that if aggregation is asked for, chop the series up into separate
chunks, calculating the aggregate for each chunk. Then assemble the results.
If no aggregation is called for, just return the data directly out of the database.
"""
startstamp, stopstamp = timespan
start_vec = list()
stop_vec = list()
data_vec = list()
if aggregate_type:
# With aggregation
unit, unit_group = None, None
if aggregate_type == 'cumulative':
do_aggregate = 'sum'
total = 0
else:
do_aggregate = aggregate_type
for stamp in weeutil.weeutil.intervalgen(startstamp, stopstamp,
aggregate_interval):
# Get the aggregate as a ValueTuple
agg_vt = get_aggregate(obs_type, stamp, do_aggregate,
db_manager)
if unit:
# It's OK if the unit is unknown (=None).
if agg_vt[1] is not None and (unit != agg_vt[1]
or unit_group != agg_vt[2]):
raise weewx.UnsupportedFeature(
"Cannot change unit groups "
"within an aggregation.")
else:
unit, unit_group = agg_vt[1], agg_vt[2]
start_vec.append(stamp.start)
stop_vec.append(stamp.stop)
if aggregate_type == 'cumulative':
if agg_vt[0] is not None:
total += agg_vt[0]
data_vec.append(total)
else:
data_vec.append(agg_vt[0])
else:
# No aggregation
sql_str = "SELECT dateTime, %s, usUnits, `interval` FROM %s " \
"WHERE dateTime >= ? AND dateTime <= ?" % (obs_type, db_manager.table_name)
std_unit_system = None
# Hit the database. It's possible the type is not in the database, so be prepared
# to catch a NoColumnError:
try:
for record in db_manager.genSql(sql_str,
(startstamp, stopstamp)):
# Unpack the record
timestamp, value, unit_system, interval = record
if std_unit_system:
if std_unit_system != unit_system:
raise weewx.UnsupportedFeature(
"Unit type cannot change "
"within an aggregation interval.")
else:
std_unit_system = unit_system
start_vec.append(timestamp - interval * 60)
stop_vec.append(timestamp)
data_vec.append(value)
except weedb.NoColumnError:
# The sql type doesn't exist. Convert to an UnknownType error
raise weewx.UnknownType(obs_type)
unit, unit_group = weewx.units.getStandardUnitType(
std_unit_system, obs_type, aggregate_type)
return (ValueTuple(start_vec, 'unix_epoch', 'group_time'),
ValueTuple(stop_vec, 'unix_epoch',
'group_time'), ValueTuple(data_vec, unit,
unit_group))