Documentation update

docs/build/html/_modules/index.html

@@ -112,7 +112,6 @@ <h1>All modules for which code is available</h1>
 <li><a href="pyFTS/data/rossler.html">pyFTS.data.rossler</a></li>
 <li><a href="pyFTS/data/sunspots.html">pyFTS.data.sunspots</a></li>
 <li><a href="pyFTS/distributed/spark.html">pyFTS.distributed.spark</a></li>
-<li><a href="pyFTS/hyperparam/GridSearch.html">pyFTS.hyperparam.GridSearch</a></li>
 <li><a href="pyFTS/hyperparam/Util.html">pyFTS.hyperparam.Util</a></li>
 <li><a href="pyFTS/models/chen.html">pyFTS.models.chen</a></li>
 <li><a href="pyFTS/models/cheng.html">pyFTS.models.cheng</a></li>

docs/build/html/modules.html

@@ -164,7 +164,7 @@ <h1>pyFTS<a class="headerlink" href="#pyfts" title="Permalink to this headline">
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam">Module contents</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#submodules">Submodules</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.Util">pyFTS.hyperparam.Util module</a></li>
-<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.GridSearch">pyFTS.hyperparam.GridSearch module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#pyfts-hyperparam-gridsearch-module">pyFTS.hyperparam.GridSearch module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#pyfts-hyperparam-evolutionary-module">pyFTS.hyperparam.Evolutionary module</a></li>
 </ul>
 </li>

pyFTS/common/FuzzySet.py

@@ -121,13 +121,12 @@ def fuzzyfy(data, partitioner, **kwargs):
     :param data: input value to be fuzzyfied
     :param partitioner: a trained pyFTS.partitioners.Partitioner object
     :param kwargs: dict, optional arguments
-
     :keyword alpha_cut: the minimal membership value to be considered on fuzzyfication (only for mode='sets')
     :keyword method: the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)
     :keyword mode: the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership
     values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )
-
     :returns a list with the fuzzyfied values, depending on the mode
+    
     """
     alpha_cut = kwargs.get('alpha_cut', 0.)
     mode = kwargs.get('mode', 'sets')

pyFTS/partitioners/partitioner.py

@@ -127,7 +127,7 @@ def build_index(self):
 
     def fuzzyfy(self, data, **kwargs):
         """
-        A general method for fuzzyfication.
+        Fuzzyfy the input data according to this partitioner fuzzy sets.
 
         :param data: input value to be fuzzyfied
         :keyword alpha_cut: the minimal membership value to be considered on fuzzyfication (only for mode='sets')
@@ -178,6 +178,14 @@ def fuzzyfy(self, data, **kwargs):
             return sets
 
     def check_bounds(self, data):
+        '''
+        Check if the input data is outside the known Universe of Discourse and, if it is, round it to the closest
+        fuzzy set.
+
+        :param data: input data to be verified
+        :return: the index of the closest fuzzy set when data is outside de universe of discourse or None if
+        the data is inside the UoD.
+        '''
         if data < self.min:
             return 0
         elif data > self.max:

pyFTS/probabilistic/Mixture.py

@@ -7,7 +7,7 @@
 
 class Mixture(ProbabilityDistribution.ProbabilityDistribution):
     """
-
+    Mix two or more Probability Distributions smoothing them with weights.
     """
     def __init__(self, type="mixture", **kwargs):
         self.models = []
@@ -21,7 +21,7 @@ def density(self, values):
         if not isinstance(values, list):
             values = [values]
 
-        for ct, m in enumerate(self.models):
+        #for ct, m in enumerate(self.models):
 
-        probs = [m.density(values) ]
+        #probs = [m.density(values) ]