tree module

class ezclimate.tree.TreeModel(decision_times, prob_scale=1.0)

Bases: object

Tree model for the EZ-Climate model. It provides the structure of a non-recombining tree.

Parameters:

• decision_times (ndarray or list) – years in the future where decisions will be made
• prob_scale (float, optional) – scaling constant for probabilities

decision_times

ndarray – years in the future where decisions will be made

prob_scale

float – scaling constant for probabilities

node_prob

ndarray – probability of reaching node from period 0

final_states_prob

ndarray – last periods node_prob

get_node(period, state)

Returns the node in period and state provided.

Parameters:

• period (int) – period
• state (int) – state of the node

Returns:

node number

Return type:

int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_node(1, 1)
2
>>> t.get_node(4, 10)
25
>>> t.get_node(4, 20)
ValueError: No such state in period 4

Raises:ValueError – If period is too large or if the state is too large for the period.

get_nodes_in_period(period)

Returns the first and last nodes in the period.

Parameters:period (int) – period Returns:number of nodes in period Return type:int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_nodes_in_period(0)
(0, 0)
>>> t.get_nodes_in_period(1)
(1, 2)
>>> t.get_nodes_in_period(4)
(15, 30)

get_num_nodes_period(period)

Returns the number of nodes in the period.

Parameters:period (int) – period Returns:number of nodes in period Return type:int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_num_nodes_period(2)
4
>>> t.get_num_nodes_period(5)
32

get_parent_node(child)

Returns the previous or parent node of the given child node.

Parameters:child (int) – the child node Returns:partent node Return type:int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_parent_node(2)
0
>>> t.get_parent_node(4)
1
>>> t.get_parent_node(10)
4

get_path(node, period=None)

Returns the unique path taken to come to given node.

Parameters:node (int) – the node Returns:path to get to node Return type:ndarray

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_path(2)
array([0, 2])
>>> t.get_parent_node(4)
array([0, 1, 4])
>>> t.get_parent_node(62)
array([ 0,  2,  6, 14, 30, 62])

get_period(node)

Returns what period the node is in.

Parameters:node (int) – the node Returns:period Return type:int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_period(0)
0
>>> t.get_period(4)
2

get_probs_in_period(period)

Returns the probabilities to get from period 0 to nodes in period.

Parameters:period (int) – the period Returns:probabilities Return type:ndarray

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_probs_in_period(2)
array([ 0.25,  0.25,  0.25,  0.25])
>>> t.get_probs_in_period(4)
array([ 0.0625,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,
        0.0625,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,  0.0625,
        0.0625,  0.0625])

get_state(node, period=None)

Returns the state the node represents.

Parameters:

• node (int) – the node
• period (int, optional) – the period

Returns:

state

Return type:

int

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.get_state(0)
0
>>> t.get_state(4, 2)
1

num_decision_nodes

int – the number of nodes in tree

num_final_states

int – the number of nodes in the last period

num_periods

int – the number of periods in the tree

reachable_end_states(node, period=None, state=None)

Returns what future end states can be reached from given node.

Parameters:

• node (int) – the node
• period (int, optional) – the period
• state (int, optional) – the state the node is in

Returns:

(worst end state, best end state)

Return type:

tuple

Examples

>>> t = TreeModel([0, 15, 45, 85, 185, 285, 385])
>>> t.reachable_end_states(0)
(0, 31)
>>> t.reachable_end_states(10)
(12, 15)
>>> t.reachable_end_states(32)
(1, 1)