Merge pull request #45 from ealcobaca/0.1.x

0.1.x

README.md

@@ -112,7 +112,7 @@ You can find in the documentation interesting pages like:
 
 ## Developer notes
 
-* We are glad to accept any contributions, please check [Contributing](CONTRIVUTING.md) and the [Documentation](https://pymfe.readthedocs.io/en/latest/?badge=latest).
+* We are glad to accept any contributions, please check [Contributing](https://github.com/ealcobaca/pymfe/blob/master/CONTRIBUTING.md) and the [Documentation](https://pymfe.readthedocs.io/en/latest/?badge=latest).
 * To submit bugs and feature requests, report at [project issues](https://github.com/ealcobaca/pymfe/issues).
 * In the current version, the meta-feature extractor supports only classification problems. The authors plan to extend the package to add clustering and regression measures and to support MtL evaluation measures. For more specific information on how to extract each group of measures, please refer to the functions documentation page and the examples contained therein. For a general overview of the `pymfe` package, please have a look at the associated documentation.
 

docs/source/new.rst

@@ -1,41 +1,76 @@
 What is new on pymfe package?
 #############################
 
+Version 0.1.1
+-------------
+* Bugs solved
+
+   * False positive of mypy fixed
+
+   * Contributing link now is working
+
+* We added a note about how to add a new meta-feature
+
+* Modified 'verbosity' (from 'extract' method) argument type from boolean to
+  integer. Now the user can choose the desired level of verbosity.
+  Verbosity = 1 means that a progress bar will be shown during the metafeature
+  extraction process. Verbosity = 2 maintains all the previous verbose messages
+  (i.e., it logs every "extract" step) plus additional information about the
+  current percentage of progress done so far.
+
 
 Version 0.1.0
 -------------
-- Meta-feature groups available:
-   - Relative landmarking
-   - Clustering-based
-   - Relative subsampling landmarking
-- Makefile to help developers
+* Meta-feature groups available
+
+   * Relative landmarking
+
+   * Clustering-based
+
+   * Relative subsampling landmarking
+
+* Makefile to help developers
+
+* New Functionalities
+
+   * Now you can list available groups
 
-- New Functionalities
-   - Now you can list available groups
-   - Now you can list available metafeatures
+   * Now you can list available metafeatures
 
-- Documentation
-   - New examples
-   - New README
+* Documentation
 
-- Bugs
-   - Problems in parse categoric metafeatures solved
-   - Categorization of attributes with constant values solved
+   * New examples
 
-- Test
-   - Several new tests added
+   * New README
+
+* Bugs
+
+   * Problems in parse categoric metafeatures solved
+
+   * Categorization of attributes with constant values solved
+
+* Test
+
+   * Several new tests added
 
 Version 0.0.3
 -------------
-- Documentation improvement
-- Setup improvement
+* Documentation improvement
+
+* Setup improvement
 
 
 Initial Release
 ---------------
-- Meta-feature groups available:
-  - Simple
-  - Statistical
-  - Information-theoretic
-  - Model-based
-  - Landmarking
+* Meta-feature groups available:
+
+  * Simple
+
+  * Statistical
+
+  * Information-theoretic
+
+  * Model-based
+
+  * Landmarking
+

examples/03_miscellaneous_examples/plot_listing_metafeatures_groups.py

@@ -9,10 +9,6 @@
 from sklearn.datasets import load_iris
 from pymfe.mfe import MFE
 
-data = load_iris()
-y = data.target
-X = data.data
-
 ###############################################################################
 # Print all available metafeature groups from the ``pymfe`` package.
 model = MFE()

examples/03_miscellaneous_examples/plot_metafeature_description.py

@@ -0,0 +1,26 @@
+"""
+Metafeature description
+=======================
+
+In this example, we will show you how to list the types of metafeatures,
+groups, and summaries available.
+"""
+
+from pymfe.mfe import MFE
+
+
+###############################################################################
+# This function shows the description of all metafeatures.
+MFE.metafeature_description()
+
+###############################################################################
+# You can select a specific group.
+MFE.metafeature_description(groups=["general", "statistical"])
+
+###############################################################################
+# You can sort the metafeatures by name.
+MFE.metafeature_description(sort=True)
+
+###############################################################################
+# You also can get the table instead of printing it.
+MFE.metafeature_description(print_table=False)

pymfe/_internal.py

@@ -86,6 +86,14 @@
 
 VALID_VALUE_PREFIX = "VALID_"
 
+DEFAULT_GROUP = (
+    "general",
+    "info-theory",
+    "statistical",
+    "model-based",
+    "landmarking",
+)  # type: t.Tuple[str, ...]
+
 VALID_GROUPS = (
     "landmarking",
     "general",
@@ -243,7 +251,6 @@ def _check_values_in_group(value: t.Union[str, t.Iterable[str]],
         value_set = set(map(str.lower, value))
         if wildcard and wildcard.lower() in value_set:
             in_group = tuple(valid_group)
-
         else:
             in_group = tuple(value_set.intersection(valid_group))
             not_in_group = tuple(value_set.difference(valid_group))
@@ -639,10 +646,32 @@ def check_summary_warnings(value: t.Union[TypeNumeric, t.Sequence, np.ndarray],
             RuntimeWarning)
 
 
+def convert_alias(groups_alias: t.Iterable[t.Iterable],
+                  values: t.Optional[t.Union[t.Iterable[str], str]] = None
+                  ) -> t.List[str]:
+    """Change the values of the alias to the groups.
+    """
+    if not values:
+        values = []
+    elif isinstance(values, str):
+        values = [values]
+    else:
+        values = list(values)
+
+    for alias_name, alias_value in groups_alias:
+        # verifying if the alias is in the set
+        if alias_name in values:
+            values.remove(alias_name)  # remove from values
+            values = list(values) + list(alias_value)  # add real groups
+
+    return values
+
+
 def process_generic_set(
         values: t.Optional[t.Union[t.Iterable[str], str]],
         group_name: str,
         wildcard: t.Optional[str] = "all",
+        groups_alias: t.Iterable[t.Iterable] = None,
         allow_none: bool = False,
         allow_empty: bool = False,
         ) -> t.Tuple[str, ...]:
@@ -660,6 +689,10 @@ def process_generic_set(
             out its prefix. For example, to select ``VALID_CLASSES`` group for
             ``values`` reference, then group_names must be just ``classes``.
 
+        groups_alias (:obj:`iterable` of :obj:`iterable`): a list of tuples of
+            aliases. Each tuple should have in the alias name in the first
+            position and the real groups mapped int he second position.
+
         wildcard (:obj:`str`, optional): special value to ``accept any value``.
 
         allow_none (:obj:`bool`, optional): if True, then :obj:`NoneType` is
@@ -722,6 +755,9 @@ def process_generic_set(
                          "module documentation to verify which ones "
                          "are available for use.".format(group_name))
 
+    if groups_alias:
+        values = convert_alias(groups_alias, values)
+
     in_valid_set, not_in_valid_set = _check_values_in_group(
         value=values,
         valid_group=valid_values,

pymfe/_version.py

@@ -22,4 +22,4 @@
 # 'X.Y.dev0' is the canonical version of 'X.Y.dev'
 
 
-__version__ = '0.1.0'
+__version__ = '0.1.1'

pymfe/dev.py

@@ -91,10 +91,19 @@
 
 >>> make code-check
 
+.. note::
+    This example shows how to create a new group of meta-features. If you want
+    only to add a new meta-feature, you should insert it in the meta-feature
+    group file and create an "ft_" method to it. The new meta-feature will be
+    automatically picked up (as the method "ft_foo" in this example). You
+    should not forget to use the precompute methods to save time.
+
+
 .. note::
     You should not forget to create tests for all new functionalities that
     you implemented. The test can be found in `./tests/` fold.
 
+
 .. note::
     This class is being actualized in GitHub, check this
     `link <https://github.com/ealcobaca/pymfe/blob/master/pymfe/dev.py>`_