Add FaustFactory.rand() in pyfaust and matfaust. Update FaustFactory API doc.

wrapper/matlab/+matfaust/@FaustFactory/FaustFactory.m

+% ======================================================================
+%> @brief     This factory class provides methods for generating a Faust especially by factorization of a dense matrix.
+%>
+%>    This class gives access to the main factorization algorithms of
+%>    FAµST. Those algorithms can factorize a dense matrix to a sparse product
+%>    (i.e. a Faust object).
+%>
+%>    There are two algorithms for factorization.
+%>
+%>    The first one is Palm4MSA :
+%>    which stands for Proximal Alternating Linearized Minimization for
+%>    Multi-layer Sparse Approximation. Note that Palm4MSA is not
+%>    intended to be used directly. You should rather rely on the second algorithm.
+%>
+%>    The second one is the Hierarchical Factorization algorithm:
+%>    this is the central algorithm to factorize a dense matrix to a Faust.
+%>    It makes iterative use of Palm4MSA to proceed with the factorization of a given
+%>    dense matrix.
+%>
+% ======================================================================
 classdef FaustFactory
 	properties (SetAccess = public)
 
@@ -24,7 +44,6 @@ classdef FaustFactory
 		%>  init_facts{1} = zeros(500,32)
 		%>  init_facts{2} = eye(32)
 		%>  M = rand(500, 32)
-		%>  M = data
 		%>  cons = cell(2,1)
 		%>  cons{1} = ConstraintInt(ConstraintName(ConstraintName.SPLIN), 500, 32, 5);
 		%>  cons{2} = ConstraintReal(ConstraintName(ConstraintName.NORMCOL), 32, 32, 1.0);
@@ -33,6 +52,13 @@ classdef FaustFactory
 		%>  F = FaustFactory.fact_palm4msa(M, params)
 		%> @endcode
 		%>
+		%> F =
+		%>
+		%> Faust size 500x32, density 0.22025, nnz_sum 3524, 2 factor(s):
+		%> - FACTOR 0 (real) DENSE, size 500x32, density 0.15625, nnz 2500
+		%> - FACTOR 1 (real) DENSE, size 32x32, density 1, nnz 1024
+		%>
+		%>
 		%==========================================================================================
 		function  F = fact_palm4msa(m, p)
 			import matfaust.Faust
@@ -126,5 +152,15 @@ classdef FaustFactory
 			cell_facts{1} = cell_facts{1}*lambda;
 			F = Faust(cell_facts);
 		end
+
+		%==========================================================================================
+		%> @brief Generates a random Faust.
+		%>
+		%> <p>@b See @b also Faust.rand.
+		%==========================================================================================
+		function F = rand(varargin)
+			import matfaust.Faust
+			F = Faust.rand(varargin{:})
+		end
 	end
 end

wrapper/python/pyfaust.py

@@ -928,11 +928,31 @@ class Faust:
             return np.dtype(np.complex)
 
 class FaustFactory:
+    """
+    This factory class provides methods for generating a Faust especially by factorization of a dense matrix.
+
+    This class gives access to the main factorization algorithms of
+    FAµST. Those algorithms can factorize a dense matrix to a sparse product
+    (i.e. a Faust object).
+
+    There are two algorithms for factorization.
+
+    The first one is Palm4MSA :
+    which stands for Proximal Alternating Linearized Minimization for
+    Multi-layer Sparse Approximation. Note that Palm4MSA is not
+    intended to be used directly. You should rather rely on the second algorithm.
+
+    The second one is the Hierarchical Factorization algorithm:
+    this is the central algorithm to factorize a dense matrix to a Faust.
+    It makes iterative use of Palm4MSA to proceed with the factorization of a given
+    dense matrix.
+
+    """
 
     @staticmethod
     def fact_palm4msa(M, p):
         """
-        Factorizes the matrix M using the parameters set in p.
+        Factorizes the matrix M with Palm4MSA algorithm using the parameters set in p.
 
         Args:
             M: the numpy matrix to factorize.
@@ -981,7 +1001,7 @@ class FaustFactory:
     @staticmethod
     def fact_hierarchical(M, p):
         """
-        Factorizes the matrix M using the parameters set in p.
+        Factorizes the matrix M with Hierarchical Factorization using the parameters set in p.
 
         Args:
             M: the numpy matrix to factorize.
@@ -1034,6 +1054,15 @@ class FaustFactory:
             raise ValueError("p must be a ParamsPalm4MSA object.")
         return Faust(core_obj=FaustCorePy.FaustFact.fact_hierarchical(M, p))
 
+    @staticmethod
+    def rand(*kwargs):
+        """
+        Generates a random Faust.
+
+        <b/> See also Faust.rand
+        """
+        return Faust.rand(*kwargs)
+
 class ParamsFact(object):
 
     def __init__(self, num_facts, is_update_way_R2L, init_lambda, init_facts,