Util – utility module

This is the utility module, with some utility functions of general use, like list item swap, random utilities and etc.

class Util.ErrorAccumulator

An accumulator for the Root Mean Square Error (RMSE) and the Mean Square Error (MSE)

append(target, evaluated)

Add value to the accumulator

Parameters:
  • target – the target value
  • evaluated – the evaluated value
getAdjusted()

Returns the adjusted fitness This fitness is calculated as 1 / (1 + standardized fitness)

getMSE()

Return the mean square error

Return type:float MSE
getMean()

Return the mean of the non-squared accumulator

getNonSquared()

Returns the non-squared accumulator

getRMSE()

Return the root mean square error

Return type:float RMSE
getSquared()

Returns the squared accumulator

reset()

Reset the accumulator

Util.G1DListGetEdges(individual)

Get the edges of a G1DList individual

Parameters:individual – the G1DList individual
Return type:the edges dictionary
Util.G1DListGetEdgesComposite(mom, dad)

Get the edges and the merge between the edges of two G1DList individuals

Parameters:
  • mom – the mom G1DList individual
  • dad – the dad G1DList individual
Return type:

a tuple (mom edges, dad edges, merge)
Util.G1DListMergeEdges(eda, edb)

Get the merge between the two individual edges

Parameters:
  • eda – the edges of the first G1DList genome
  • edb – the edges of the second G1DList genome
Return type:

the merged dictionary
class Util.Graph

The Graph class

Example:
>>> g = Graph()
>>> g.addEdge("a", "b")
>>> g.addEdge("b", "c")
>>> for node in g:
...    print node
a
b
c

New in version 0.6: The Graph class.

addEdge(a, b)

Add an edge between two nodes, if the nodes doesn’t exists, they will be created

Parameters:
  • a – the first node
  • b – the second node
addNode(node)

Add the node

Parameters:node – the node to add
getNeighbors(node)

Returns the neighbors of the node

Parameters:node – the node
getNodes()

Returns all the current nodes on the graph

Return type:the list of nodes
reset()

Deletes all nodes of the graph

Util.cmp_individual_raw(a, b)

Compares two individual raw scores

Example:
>>> GPopulation.cmp_individual_raw(a, b)
Parameters:
  • a – the A individual instance
  • b – the B individual instance
Return type:

0 if the two individuals raw score are the same, -1 if the B individual raw score is greater than A and 1 if the A individual raw score is greater than B.

Note

this function is used to sorte the population individuals

Util.cmp_individual_scaled(a, b)

Compares two individual fitness scores, used for sorting population

Example:
>>> GPopulation.cmp_individual_scaled(a, b)
Parameters:
  • a – the A individual instance
  • b – the B individual instance
Return type:

0 if the two individuals fitness score are the same, -1 if the B individual fitness score is greater than A and 1 if the A individual fitness score is greater than B.

Note

this function is used to sorte the population individuals

Util.importSpecial(name)

This function will import the name module, if fails, it will raise an ImportError exception and a message

Parameters:name – the module name
Return type:the module object

New in version 0.6: The import_special function

Util.list2DSwapElement(lst, indexa, indexb)

Swaps elements A and B in a 2D list (matrix).

Example:
>>> l = [ [1,2,3], [4,5,6] ] 
>>> Util.list2DSwapElement(l, (0,1), (1,1) )
>>> l
[[1, 5, 3], [4, 2, 6]]
Parameters:
  • lst – the list
  • indexa – the swap element A
  • indexb – the swap element B
Return type:

None
Util.listSwapElement(lst, indexa, indexb)

Swaps elements A and B in a list.

Example:
>>> l = [1, 2, 3]
>>> Util.listSwapElement(l, 1, 2)
>>> l
[1, 3, 2]
Parameters:
  • lst – the list
  • indexa – the swap element A
  • indexb – the swap element B
Return type:

None
Util.raiseException(message, expt=None)

Raise an exception and logs the message.

Example:
>>> Util.raiseException('The value is not an integer', ValueError)
Parameters:
  • message – the message of exception
  • expt – the exception class
Return type:

None
Util.rand_random()

random() -> x in the interval [0, 1).

Util.randomFlipCoin(p)

Returns True with the p probability. If the p is 1.0, the function will always return True, or if is 0.0, the function will return always False.

Example:
>>> Util.randomFlipCoin(1.0)
True
Parameters:p – probability, between 0.0 and 1.0
Return type:True or False