cocopp.pproc
module documentationcocopp
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. |
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
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.
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.
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.
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
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.
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.
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.
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.
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.