math_basic module documented and following PEP8 standards. validation…

… module completed.

fda/FDataGrid.py

@@ -254,7 +254,7 @@ def derivative(self, order=1):
 
     def __add__(self, other):
         if not isinstance(other, FDataGrid):
-            raise TypeError("Object type is not FDataGrid.")
+            raise NotImplementedError("Object type is not FDataGrid.")
         if self.data_matrix.shape[1] != other.data_matrix.shape[1]:
             raise ValueError("Error in columns dimensions")
         if self.sample_points != other.sample_points:
@@ -265,7 +265,7 @@ def __add__(self, other):
 
     def __sub__(self, other):
         if not isinstance(other, FDataGrid):
-            raise TypeError("Object type is not FDataGrid.")
+            raise NotImplementedError("Object type is not FDataGrid.")
         if self.data_matrix.shape[1] != other.data_matrix.shape[1]:
             raise ValueError("Error in columns dimensions")
         if self.sample_points != other.sample_points:
@@ -276,7 +276,7 @@ def __sub__(self, other):
 
     def __mul__(self, other):
         if not isinstance(other, FDataGrid):
-            raise TypeError("Object type is not FDataGrid.")
+            raise NotImplementedError("Object type is not FDataGrid.")
         if self.data_matrix.shape[1] != other.data_matrix.shape[1]:
             raise ValueError("Error in columns dimensions")
         if self.sample_points != other.sample_points:
@@ -287,7 +287,7 @@ def __mul__(self, other):
 
     def __truediv__(self, other):
         if not isinstance(other, FDataGrid):
-            raise TypeError("Object type is not FDataGrid.")
+            raise NotImplementedError("Object type is not FDataGrid.")
         if self.data_matrix.shape[1] != other.data_matrix.shape[1]:
             raise ValueError("Error in columns dimensions")
         if self.sample_points != other.sample_points:

fda/math_basic.py

@@ -1,4 +1,5 @@
-"""This module defines the basic mathematic operations for classes defined in this package.
+"""This module defines the basic mathematic operations for classes defined
+in this package.
 
 """
 from fda.FDataGrid import FDataGrid
@@ -15,51 +16,199 @@
 
 
 def mean(fdatagrid):
-    return FDataGrid([numpy.mean(fdatagrid.data_matrix, 0)], fdatagrid.sample_points, fdatagrid.sample_range,
+    """ Computes the mean of all the samples in a FDataGrid object.
+
+    Args:
+        fdatagrid (FDataGrid): Object containing all the samples whose mean
+            is wanted.
+
+    Returns:
+        FDataGrid: A FDataGrid object with just one sample representing the
+        mean of all the samples in the original FDataGrid object.
+
+    """
+    return FDataGrid([numpy.mean(fdatagrid.data_matrix, 0)],
+                     fdatagrid.sample_points, fdatagrid.sample_range,
                      fdatagrid.names)
 
 
 def var(fdatagrid):
-    return FDataGrid([numpy.var(fdatagrid.data_matrix, 0)], fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Computes the variance of a set of samples in a FDataGrid object.
+
+    Args:
+        fdatagrid (FDataGrid): Object containing all the set of samples
+        whose variance is desired.
+
+    Returns:
+        FDataGrid: A FDataGrid object with just one sample representing the
+        mean of all the samples in the original FDataGrid object.
+
+    """
+    return FDataGrid([numpy.var(fdatagrid.data_matrix, 0)],
+                     fdatagrid.sample_points,  fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def gmean(fdatagrid):
-    return FDataGrid([scipy.stats.mstats.gmean(fdatagrid.data_matrix, 0)], fdatagrid.sample_points, fdatagrid.sample_range,
+    """ Computes the geometric mean of all the samples in a FDataGrid object.
+
+    Args:
+        fdatagrid (FDataGrid): Object containing all the samples whose
+            geometric mean is wanted.
+
+    Returns:
+        FDataGrid: A FDataGrid object with just one sample representing the
+        geometric mean of all the samples in the original FDataGrid object.
+
+    """
+    return FDataGrid([scipy.stats.mstats.gmean(fdatagrid.data_matrix, 0)],
+                     fdatagrid.sample_points, fdatagrid.sample_range,
                      fdatagrid.names)
 
 
 def cov(fdatagrid):
+    """ Calculates the covariance matrix representing the covariance of the
+    functional samples at the observation points.
+
+    Args:
+        fdatagrid (FDataGrid): Object containing different samples of a
+        functional variable.
+
+    Returns:
+        numpy.darray: Matrix of covariances.
+
+    """
     return numpy.cov(fdatagrid.data_matrix)
 
 
 def sqrt(fdatagrid):
-    return FDataGrid(numpy.sqrt(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Performs a element wise square root operation.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements the square root
+            operations is going to be applied.
+
+    Returns:
+        FDataGrid: Object whose elements are the square roots of the original.
+
+    """
+    return FDataGrid(numpy.sqrt(fdatagrid.data_matrix),
+                     fdatagrid.sample_points,  fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def absolute(fdatagrid):
-    return FDataGrid(numpy.absolute(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Gets the absolute value of all elements in the FDataGrid object.
+
+    Args:
+        fdatagrid (FDataGrid): Object from whose elements the absolute value
+            is going to be retrieved.
+
+    Returns:
+        FDataGrid: Object whose elements are the absolute values of the
+            original.
+
+    """
+    return FDataGrid(numpy.absolute(fdatagrid.data_matrix),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def around(fdatagrid, decimals=0):
-    return FDataGrid(numpy.around(fdatagrid.data_matrix, decimals), fdatagrid.sample_points, fdatagrid.sample_range,
+    """ Rounds all elements of the object.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements are going to be
+            rounded.
+        decimals (int, optional): Number of decimals wanted. Defaults to 0.
+
+    Returns:
+        FDataGrid: Object whose elements are rounded.
+
+    """
+    return FDataGrid(numpy.around(fdatagrid.data_matrix, decimals),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
                      fdatagrid.names)
 
 
 def exp(fdatagrid):
-    return FDataGrid(numpy.exp(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Performs a element wise exponential operation.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements the exponential
+            operations is going to be applied.
+
+    Returns:
+        FDataGrid: Object whose elements are the result of exponentiating
+            the elements of the original.
+
+    """
+    return FDataGrid(numpy.exp(fdatagrid.data_matrix),
+                     fdatagrid.sample_points,  fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def log(fdatagrid):
-    return FDataGrid(numpy.log(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Performs a element wise logarithm operation.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements the logarithm
+            operations is going to be applied.
+
+    Returns:
+        FDataGrid: Object whose elements are the logarithm of the original.
+
+    """
+    return FDataGrid(numpy.log(fdatagrid.data_matrix),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def log10(fdatagrid):
-    return FDataGrid(numpy.log10(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Performs a element wise base 10 logarithm operation.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements the base 10 logarithm
+            operations is going to be applied.
+
+    Returns:
+        FDataGrid: Object whose elements are the base 10 logarithm of the
+            original.
+
+    """
+    return FDataGrid(numpy.log10(fdatagrid.data_matrix),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def log2(fdatagrid):
-    return FDataGrid(numpy.log2(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Performs a element wise binary logarithm operation.
+
+    Args:
+        fdatagrid (FDataGrid): Object to whose elements the binary logarithm
+            operations is going to be applied.
+
+    Returns:
+        FDataGrid: Object whose elements are the binary logarithm of the
+            original.
+
+    """
+    return FDataGrid(numpy.log2(fdatagrid.data_matrix),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
+                     fdatagrid.names)
 
 
 def cumsum(fdatagrid):
-    return FDataGrid(numpy.cumsum(fdatagrid.data_matrix), fdatagrid.sample_points, fdatagrid.sample_range, fdatagrid.names)
+    """ Returns the cumulative sum of the samples.
+
+    Args:
+        fdatagrid (FDataGrid): Object over whose samples the cumulative sum is
+            going to be calculated.
+
+    Returns:
+        FDataGrid: Object with the sample wise cumulative sum.
+
+    """
+    return FDataGrid(numpy.cumsum(fdatagrid.data_matrix, axis=0),
+                     fdatagrid.sample_points, fdatagrid.sample_range,
+                     fdatagrid.names)