cocopp.pproc module documentation

Part of cocopp 
Raw post-processing routines.

This module implements class :py:class:`DataSet`, unit element in the
post-processing and class :py:class:`DataSetList`, sequence of instances
of :py:class:`DataSet`.

Futhermore it implements methods for dealing with a third data structure
which is a dictionary of :py:class:`DataSetList` which is handy when
dealing with :py:class:`DataSetList` instances from multiple algorithms
for comparisons.
Function cocofy Replaces cocopp references in pickles files with coco_pproc This could become necessary for future backwards compatibility, however rather should become a class method.
Function asTargetValues Undocumented
Class TargetValues store and retrieve a list of target function values:
Class RunlengthBasedTargetValues a class instance call returns f-target values based on reference runlengths:
Class DataSet Unit element for the COCO post-processing.
Class DataSetList List of instances of :py:class:`DataSet`.
Function parseinfoold Deprecated: Extract data from a header line in an index entry.
Function parseinfo Extract data from a header line in an index entry.
Function align_list Undocumented
Function set_unique_algId on return, elements in ds_list do not have an algId attribute value from taken_ids or from ds_list_reference if taken_ids is None.
Function processInputArgs Process command line arguments.
Function process_arguments Undocumented
Function store_reference_values Undocumented
Class DictAlg Undocumented
Function dictAlgByDim Returns a dictionary with problem dimension as key from a dictionary of DataSet lists.
Function dictAlgByDim2 Returns a dictionary with problem dimension as key.
Function dictAlgByFun Returns a dictionary with function id as key.
Function dictAlgByNoi Returns a dictionary with noise group as key.
Function dictAlgByFuncGroup Returns a dictionary with function group as key.
Function _DataSet_complement_data insert a line for each target value.
def _DataSet_complement_data(self, step=10**0.2, final_target=1e-08):

insert a line for each target value.

To be resolved: old data sets don't have this method, therefore it must be global in the module

def cocofy(filename):
Replaces cocopp references in pickles files with coco_pproc This could become necessary for future backwards compatibility, however rather should become a class method.
def asTargetValues(target_values):
Undocumented
def parseinfoold(s): 
Deprecated: Extract data from a header line in an index entry.

Older but verified version of :py:meth:`parseinfo`

The header line should be a string of comma-separated pairs of
key=value, for instance: key = value, key = 'value'

Keys should not use comma or quote characters.
def parseinfo(s): 
Extract data from a header line in an index entry.

Use a 'smarter' regular expression than :py:meth:`parseinfoold`.
The header line should be a string of comma-separated pairs of
key=value, for instance: key = value, key = 'value'

Keys should not use comma or quote characters.
def align_list(list_to_process, evals):
Undocumented
def set_unique_algId(ds_list, ds_list_reference, taken_ids=None):

on return, elements in ds_list do not have an algId attribute value from taken_ids or from ds_list_reference if taken_ids is None.

In case, BFGS becomes BFGS 2 etc.

def processInputArgs(args, process_background_algorithms=False): 
Process command line arguments.

Returns several instances of :py:class:`DataSetList`, and a list of 
algorithms from a list of strings representing file and folder names,
see below for details. This command operates folder-wise: one folder 
corresponds to one algorithm.

It is recommended that if a folder listed in args contain both
:file:`info` files and the associated :file:`pickle` files, they be
kept in different locations for efficiency reasons.

:keyword list args: string arguments for folder names
:keyword bool process_background_algorithms: option to process also background algorithms

:returns (all_datasets, pathnames, datasetlists_by_alg):
  all_datasets
    a list containing all DataSet instances, this is to
    prevent the regrouping done in instances of DataSetList.
    Caveat: algorithms with the same name are overwritten!?
  pathnames
    a list of keys of datasetlists_per_alg with the ordering as
    given by the input argument args
  datasetlists_by_alg
    a dictionary which associates each algorithm via its input path
    name to a DataSetList
def process_arguments(args, current_hash, dictAlg, dsList, sortedAlgs):
Undocumented
def store_reference_values(ds_list):
Undocumented
def dictAlgByDim(dictAlg): 
Returns a dictionary with problem dimension as key from
a dictionary of DataSet lists. 

The input argument is a dictionary with algorithm names as 
keys and a list of :py:class:`DataSet` instances as values.
The resulting dictionary will have dimension as key and as values
dictionaries with algorithm names as keys.
def dictAlgByDim2(dictAlg, remove_empty=False): 
Returns a dictionary with problem dimension as key.

The difference with :py:func:`dictAlgByDim` is that there is an
entry for each algorithm even if the resulting
:py:class:`DataSetList` is empty.

This function is meant to be used with an input argument which is a
dictionary with algorithm names as keys and which has list of
:py:class:`DataSet` instances as values.
The resulting dictionary will have dimension as key and as values
dictionaries with algorithm names as keys.
def dictAlgByFun(dictAlg): 
Returns a dictionary with function id as key.

This method is meant to be used with an input argument which is a
dictionary with algorithm names as keys and which has list of
:py:class:`DataSet` instances as values.
The resulting dictionary will have function id as key and as values
dictionaries with algorithm names as keys.
def dictAlgByNoi(dictAlg): 
Returns a dictionary with noise group as key.

This method is meant to be used with an input argument which is a
dictionary with algorithm names as keys and which has list of
:py:class:`DataSet` instances as values.
The resulting dictionary will have a string denoting the noise group
('noiselessall' or 'nzall') and as values dictionaries with
algorithm names as keys.
def dictAlgByFuncGroup(dictAlg): 
Returns a dictionary with function group as key.

This method is meant to be used with an input argument which is a
dictionary with algorithm names as keys and which has list of
:py:class:`DataSet` instances as values.
The resulting dictionary will have a string denoting the function
group and as values dictionaries with algorithm names as keys.
API Documentation for cocopp, generated by pydoctor at 2020-01-21 16:27:37.