pywr.parameters.DataFrameParameter

class pywr.parameters.DataFrameParameter(model, dataframe, scenario=None, timestep_offset=0, **kwargs)

Timeseries parameter with automatic alignment and resampling

Parameters:

modelpywr.model.Model

dataframepandas.DataFrame or pandas.Series

scenario: pywr._core.Scenario (optional)

timestep_offsetint (default=0)

Optional offset to apply to the timestep look-up. This can be used to look forward (positive value) or backward (negative value) in the dataset. The offset is applied to dataset after alignment and resampling. If the offset takes the indexing out of the data bounds then the parameter will return the first or last value available.

__init__(*args, **kwargs)

Methods

__init__(*args, **kwargs)
after(self)
before(self)
finish(self)
get_all_values(self)
get_constant_value(self)	Return a constant value.
get_double_lower_bounds(self)
get_double_upper_bounds(self)
get_double_variables(self)
get_integer_lower_bounds(self)
get_integer_upper_bounds(self)
get_integer_variables(self)
get_value(self, ScenarioIndex scenario_index)
load(cls, model, data)
register(cls)
reset(self)
set_double_variables(self, double[)
set_integer_variables(self, int[)
setup(self)
unregister(cls)
value(self, Timestep timestep, ...)

Attributes

children
comment	comment: str
dataframe	dataframe: object
double_size	double_size: 'int'
integer_size	integer_size: 'int'
is_constant
is_variable	is_variable: 'bool'
model
name
parents
scenario	scenario: pywr._core.Scenario
size
tags	tags: dict
timestep_offset	timestep_offset: 'int'