pywr.recorders.FlowDurationCurveDeviationRecorder

class pywr.recorders.FlowDurationCurveDeviationRecorder(model, AbstractNode node, percentiles, lower_target_fdc=None, upper_target_fdc=None, scenario=None, **kwargs)

This recorder calculates a Flow Duration Curve (FDC) for each scenario and then calculates their deviation from upper and lower target FDCs. The 2nd dimension of the target duration curves and percentiles list must be of the same length and have the same order (high to low values or low to high values).

Deviation is calculated as positive if actual FDC is above the upper target or below the lower target. If actual FDC falls between the upper and lower targets zero deviation is returned.

Parameters:

modelpywr.core.Model

nodepywr.core.Node

The node to record

percentilesarray

The percentiles to use in the calculation of the flow duration curve. Values must be in the range 0-100.

lower_target_fdcarray, optional

The lower FDC against which the scenario FDCs are compared. If values are not provided then deviations from a lower target FDC are recorded as 0.0. If targets are loaded from an external file this needs to be indexed using the percentile values.

upper_target_fdcarray, optional

The upper FDC against which the scenario FDCs are compared. If values are not provided then deviations from a upper target FDC are recorded as 0.0. If targets are loaded from an external file this needs to be indexed using the percentile values.

agg_func: str, optional

Function used for aggregating the FDC deviations across percentiles. Numpy style functions that support an axis argument are supported.

fdc_agg_func: str, optional

Optional different function for aggregating across scenarios.

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
after(self)
aggregated_value(self)
before(self)
finish(self)
is_constraint_violated(self)	Returns true if the value from this Recorder violates its constraint bounds.
load(cls, model, data)
register(cls)
reset(self)
setup(self)
to_dataframe(self[, return_fdc])	Return a pandas.DataFrame of the deviations from the target FDCs
unregister(cls)
values(self)	Compute a value for each scenario using temporal_agg_func.

Attributes

agg_func
children
comment	comment: unicode
constraint_lower_bounds
constraint_upper_bounds
data
epsilon	epsilon: 'double'
factor	factor: 'float'
fdc
fdc_deviations
ignore_nan	ignore_nan: 'bool'
is_constraint	Returns true if either upper or lower constraint bounds is defined.
is_double_bounded_constraint	Returns true if upper and lower constraint bounds are both defined and not-equal to one another.
is_equality_constraint	Returns true if upper and lower constraint bounds are both defined and equal to one another.
is_lower_bounded_constraint	Returns true if lower constraint bounds is defined and upper constraint bounds is not.
is_objective
is_upper_bounded_constraint	Returns true if upper constraint bounds is defined and lower constraint bounds is not.
model
name
node
parents
scenario	scenario: pywr._core.Scenario
tags	tags: dict
temporal_agg_func