pywr.nodes.DelayNode

class pywr.nodes.DelayNode(*args, **kwargs)

A node that delays flow for a given number of timesteps or days.

This is a composite node consisting internally of an Input and an Output node. A FlowDelayParameter is used to delay the flow of the output node for a given period prior to this delayed flow being set as the flow of the input node. Connections to the node are connected to the internal output node and connection from the node are connected to the internal input node node.

Parameters:
modelpywr.model.Model
namestring

Name of the node.

timesteps: int

Number of timesteps to delay the flow.

days: int

Number of days to delay the flow. Specifying a number of days (instead of a number of timesteps) is only valid if the number of days is exactly divisible by the model timestep delta.

initial_flow: float

Flow provided by node for initial timesteps prior to any delayed flow being available. This is constant across all delayed timesteps and any model scenarios. Default is 0.0.

__init__(model, name, **kwargs)

Initialise a new Node object

Parameters:
modelModel

The model the node belongs to

namestring

A unique name for the node

Methods

__init__(model, name, **kwargs)

Initialise a new Node object

after(self, Timestep ts)

before(self, Timestep ts)

Called at the beginning of the timestep

check()

Check the node is valid

commit(self, int scenario_index, double value)

Called once for each route the node is a member of

commit_all(self, double[)

Called once for each route the node is a member of

connect(node[, from_slot, to_slot])

Create an edge from this Node to another Node

disconnect([node, slot_name, all_slots])

Remove a connection from this Node to another Node

finalise_load()

Finish loading a node by converting parameter name references to instance references.

finish(self)

get_all_cost(self, double[)

get_all_max_flow(self, double[)

get_all_min_flow(self, double[)

get_constant_max_flow(self)

Returns max_flow value if it is a constant parameter or fixed value otherwise returns NaN.

get_constant_min_flow(self)

Returns min_flow value if it is a constant parameter or fixed value otherwise returns NaN.

get_conversion_factor(self)

Get the conversion factor

get_cost(self, ScenarioIndex scenario_index)

Get the cost per unit flow at a given timestep

get_fixed_max_flow(self)

Returns max_flow value if it is fixed value otherwise returns NaN.

get_fixed_min_flow(self)

Returns min_flow value if it is a fixed value otherwise returns NaN.

get_max_flow(self, ScenarioIndex scenario_index)

Get the maximum flow at a given timestep

get_min_flow(self, ScenarioIndex scenario_index)

Get the minimum flow at a given timestep

iter_slots([slot_name, is_connector])

Returns the object(s) wich should be connected to given slot_name

pre_load(model, data)

Create a node instance from data.

reset(self)

Called at the beginning of a run

setup(self, model)

Called before the first run of the model

Attributes

allow_isolated

A property to flag whether this Node can be unconnected in a network.

comment

comment: basestring

component_attrs

components

Generator that returns all of the Components attached to the Node

conversion_factor

The conversion between inflow and outflow for the node

cost

The cost per unit flow via the node

domain

flow

Total flow via this node in the current timestep

fully_qualified_name

has_constant_flows

Returns true if both min_flow and max_flow are literal constants or "constant" Parameters.

has_fixed_cost

Returns true if cost is not a Parameter.

has_fixed_flows

Returns true if both min_flow and max_flow are not Parameters.

max_flow

The maximum flow constraint on the node

min_flow

The minimum flow constraint on the node

model

The recorder for the node, e.g. a NumpyArrayRecorder.

name

Name of the node.

parent

The parent Node/Storage of this object.

prev_flow

Total flow via this node in the previous timestep

recorders

Returns a list of pywr.recorders.Recorder objects attached to this node.

virtual

virtual: 'bool'