def interpolated_values(self,
start_time,
end_time,
interval,
filter_expression=""):
"""interpolated_values
Return a PISeries of interpolated data.
Data is returned between *start_time* and *end_time* at a fixed
*interval*. All three values are parsed by AF.Time and the first two
allow for time specification relative to "now" by use of the
asterisk.
*filter_expression* is an optional string to filter the returned
values, see OSIsoft PI documentation for more information.
The AF SDK allows for inclusion of filtered data, with filtered
values marked as such. At this point PIconnect does not support this
and filtered values are always left out entirely.
Args:
start_time (str or datetime): Containing the date, and possibly time,
from which to retrieve the values. This is parsed, together
with `end_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
end_time (str or datetime): Containing the date, and possibly time,
until which to retrieve values. This is parsed, together
with `start_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
interval (str): String containing the interval at which to extract
data. This is parsed using
:afsdk:`AF.Time.AFTimeSpan.Parse <M_OSIsoft_AF_Time_AFTimeSpan_Parse_1.htm>`.
filter_expression (str, optional): Defaults to ''. Query on which
data to include in the results. See :ref:`filtering_values`
for more information on filter queries.
Returns:
PISeries: Timeseries of the values returned by the SDK
"""
time_range = to_af_time_range(start_time, end_time)
interval = AF.Time.AFTimeSpan.Parse(interval)
filter_expression = self._normalize_filter_expression(
filter_expression)
pivalues = self._interpolated_values(time_range, interval,
filter_expression)
timestamps, values = [], []
for value in pivalues:
timestamps.append(timestamp_to_index(value.Timestamp.UtcTime))
values.append(value.Value)
return PISeries(
tag=self.name,
timestamp=timestamps,
value=values,
uom=self.units_of_measurement,
)
def summaries(
self,
start_time,
end_time,
interval,
summary_types,
calculation_basis=CalculationBasis.TIME_WEIGHTED,
time_type=TimestampCalculation.AUTO,
):
"""summaries
Return one or more summary values for each interval within a time range
Args:
start_time (str or datetime): Containing the date, and possibly time,
from which to retrieve the values. This is parsed, together
with `end_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
end_time (str or datetime): Containing the date, and possibly time,
until which to retrieve values. This is parsed, together
with `start_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
interval (str): String containing the interval at which to extract
data. This is parsed using
:afsdk:`AF.Time.AFTimeSpan.Parse <M_OSIsoft_AF_Time_AFTimeSpan_Parse_1.htm>`.
summary_types (int or PIConsts.SummaryType): Type(s) of summaries
of the data within the requested time range.
calculation_basis (int or PIConsts.CalculationBasis, optional):
Event weighting within an interval. See :ref:`event_weighting`
and :any:`CalculationBasis` for more information. Defaults to
CalculationBasis.TIME_WEIGHTED.
time_type (int or PIConsts.TimestampCalculation, optional):
Timestamp to return for each of the requested summaries. See
:ref:`summary_timestamps` and :any:`TimestampCalculation` for
more information. Defaults to TimestampCalculation.AUTO.
Returns:
pandas.DataFrame: Dataframe with the unique timestamps as row index
and the summary name as column name.
"""
time_range = to_af_time_range(start_time, end_time)
interval = AF.Time.AFTimeSpan.Parse(interval)
summary_types = int(summary_types)
calculation_basis = int(calculation_basis)
time_type = int(time_type)
pivalues = self._summaries(time_range, interval, summary_types,
calculation_basis, time_type)
df = DataFrame()
for summary in pivalues:
key = SummaryType(summary.Key).name
timestamps, values = zip(
*[(timestamp_to_index(value.Timestamp.UtcTime), value.Value)
for value in summary.Value])
df = df.join(DataFrame(data={key: values}, index=timestamps),
how="outer")
return df
def filtered_summaries(
self,
start_time,
end_time,
interval,
filter_expression,
summary_types,
calculation_basis=None,
filter_evaluation=None,
filter_interval=None,
time_type=None,
):
"""filtered_summaries
Return one or more summary values for each interval within a time range
Args:
start_time (str or datetime): String containing the date, and possibly time,
from which to retrieve the values. This is parsed, together
with `end_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
end_time (str or datetime): String containing the date, and possibly time,
until which to retrieve values. This is parsed, together
with `start_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
interval (str): String containing the interval at which to extract
data. This is parsed using
:afsdk:`AF.Time.AFTimeSpan.Parse <M_OSIsoft_AF_Time_AFTimeSpan_Parse_1.htm>`.
filter_expression (str, optional): Defaults to ''. Query on which
data to include in the results. See :ref:`filtering_values`
for more information on filter queries.
summary_types (int or PIConsts.SummaryType): Type(s) of summaries
of the data within the requested time range.
calculation_basis (int or PIConsts.CalculationBasis, optional):
Event weighting within an interval. See :ref:`event_weighting`
and :any:`CalculationBasis` for more information. Defaults to
CalculationBasis.TIME_WEIGHTED.
filter_evaluation (int or PIConsts,ExpressionSampleType, optional):
Determines whether the filter is applied to the raw events in
the database, of if it is applied to an interpolated series
with a regular interval. Defaults to
ExpressionSampleType.EXPRESSION_RECORDED_VALUES.
filter_interval (str, optional): String containing the interval at
which to extract apply the filter. This is parsed using
:afsdk:`AF.Time.AFTimeSpan.Parse <M_OSIsoft_AF_Time_AFTimeSpan_Parse_1.htm>`.
time_type (int or PIConsts.TimestampCalculation, optional):
Timestamp to return for each of the requested summaries. See
:ref:`summary_timestamps` and :any:`TimestampCalculation` for
more information. Defaults to TimestampCalculation.AUTO.
Returns:
pandas.DataFrame: Dataframe with the unique timestamps as row index
and the summary name as column name.
"""
time_range = to_af_time_range(start_time, end_time)
interval = AF.Time.AFTimeSpan.Parse(interval)
filter_expression = self._normalize_filter_expression(
filter_expression)
calculation_basis = get_enumerated_value(
enumeration=CalculationBasis,
value=calculation_basis,
default=CalculationBasis.TIME_WEIGHTED,
)
filter_evaluation = get_enumerated_value(
enumeration=ExpressionSampleType,
value=filter_evaluation,
default=ExpressionSampleType.EXPRESSION_RECORDED_VALUES,
)
time_type = get_enumerated_value(
enumeration=TimestampCalculation,
value=time_type,
default=TimestampCalculation.AUTO,
)
filter_interval = AF.Time.AFTimeSpan.Parse(filter_interval)
pivalues = self._filtered_summaries(
time_range,
interval,
filter_expression,
summary_types,
calculation_basis,
filter_evaluation,
filter_interval,
time_type,
)
df = DataFrame()
for summary in pivalues:
key = SummaryType(summary.Key).name
timestamps, values = zip(
*[(timestamp_to_index(value.Timestamp.UtcTime), value.Value)
for value in summary.Value])
df = df.join(DataFrame(data={key: values}, index=timestamps),
how="outer")
return df
def recorded_values(self,
start_time,
end_time,
boundary_type="inside",
filter_expression=""):
"""recorded_values
Return a PISeries of recorded data.
Data is returned between the given *start_time* and *end_time*,
inclusion of the boundaries is determined by the *boundary_type*
attribute. Both *start_time* and *end_time* are parsed by AF.Time and
allow for time specification relative to "now" by use of the asterisk.
By default the *boundary_type* is set to 'inside', which returns from
the first value after *start_time* to the last value before *end_time*.
The other options are 'outside', which returns from the last value
before *start_time* to the first value before *end_time*, and
'interpolate', which interpolates the first value to the given
*start_time* and the last value to the given *end_time*.
*filter_expression* is an optional string to filter the returned
values, see OSIsoft PI documentation for more information.
The AF SDK allows for inclusion of filtered data, with filtered values
marked as such. At this point PIconnect does not support this and
filtered values are always left out entirely.
Args:
start_time (str or datetime): Containing the date, and possibly time,
from which to retrieve the values. This is parsed, together
with `end_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
end_time (str or datetime): Containing the date, and possibly time,
until which to retrieve values. This is parsed, together
with `start_time`, using
:afsdk:`AF.Time.AFTimeRange <M_OSIsoft_AF_Time_AFTimeRange__ctor_1.htm>`.
boundary_type (str, optional): Defaults to 'inside'. Key from the
`__boundary_types` dictionary to describe how to handle the
boundaries of the time range.
filter_expression (str, optional): Defaults to ''. Query on which
data to include in the results. See :ref:`filtering_values`
for more information on filter queries.
Returns:
PISeries: Timeseries of the values returned by the SDK
Raises:
ValueError: If the provided `boundary_type` is not a valid key a
`ValueError` is raised.
"""
time_range = to_af_time_range(start_time, end_time)
boundary_type = self.__boundary_types.get(boundary_type.lower())
filter_expression = self._normalize_filter_expression(
filter_expression)
if boundary_type is None:
raise ValueError(
"Argument boundary_type must be one of " +
", ".join('"%s"' % x
for x in sorted(self.__boundary_types.keys())))
pivalues = self._recorded_values(time_range, boundary_type,
filter_expression)
timestamps, values = [], []
for value in pivalues:
timestamps.append(timestamp_to_index(value.Timestamp.UtcTime))
values.append(value.Value)
return PISeries(
tag=self.name,
timestamp=timestamps,
value=values,
uom=self.units_of_measurement,
)