Set a default value for norm arg in matfaust/pyfaust normlin/col projecctors.

It closes issue #146

misc/test/src/Matlab/FaustFactoryTest.m

@@ -435,7 +435,7 @@ classdef FaustFactoryTest < matlab.unittest.TestCase
 			n = randi([min_n 128], 1);
 			M = rand(m,n);
 			s = rand(1,1)*50;
-			p = normcol([m, n], s);
+			p = normcol([m, n], 's', s);
 			Mp = p(M);
 			for i=1:n
 				this.verifyLessThanOrEqual(norm(Mp(:,i)), s+1e-6)
@@ -450,7 +450,7 @@ classdef FaustFactoryTest < matlab.unittest.TestCase
 			n = randi([min_n 128], 1);
 			M = rand(m,n);
 			s = rand()*50;
-			p = normlin([m, n], s);
+			p = normlin([m, n], 's', s);
 			Mp = p(M);
 			for i=1:m
 				this.verifyLessThanOrEqual(norm(Mp(i,:)), s+1e-6)

wrapper/matlab/+matfaust/+proj/@normcol/normcol.m

@@ -10,17 +10,33 @@ classdef normcol < matfaust.proj.proj_gen
 		%===============================================
 		%> @b Usage
 		%>
-		%> &nbsp;&nbsp;&nbsp; @b normcol(shape, normval): returns a NORMCOL projector (functor), shape defines the size of the input matrix (e.g. [1, 10]), normval defines the sparsity of the output matrix (the 2-norm of each column).<br/>
+		%> &nbsp;&nbsp;&nbsp; @b normcol(shape, s): returns a NORMCOL projector (functor), shape defines the size of the input matrix (e.g. [1, 10]), s defines the sparsity of the output matrix (the 2-norm of each column).<br/>
 		%>
 		%> @param shape: vector of size 2, to define the size of the input matrix.
-		%> @param normval: the sparsity parameter.
+		%> @param 's', value: (optional) the sparsity parameter, the 2-norm of the column (1 by default).
 		%===============================================
-		function proj = normcol(shape, normval)%, varargin)
+		function proj = normcol(shape, varargin)
 			import matfaust.factparams.ConstraintReal
-			if(normval < 0)
-				error('A norm can''t be negative')
+			% TODO: factorize this sparsing with normlin
+			if(length(varargin) > 0)
+				if(strcmp(varargin{1}, 's'))
+					disp('s in varargin')
+
+					if(length(varargin) < 2)
+						error('s value is missing')
+					end
+					s = varargin{2};
+					varargin(1:2) = []; % deleting the used cell
+					if(~ isreal(s) || ~ isscalar(s))
+						error('s must be a real scalar')
+					end
+					if(s < 0)
+						error('A norm can''t be negative')
+					end
+				% else % do nothing (ConstraintReal role)
+				end
 			end
-			proj.constraint = ConstraintReal('normcol', shape(1), shape(2), normval)%, varargin{:});
+			proj.constraint = ConstraintReal('normcol', shape(1), shape(2), s)%, varargin{:});
 		end
 	end
 end

wrapper/matlab/+matfaust/+proj/@normlin/normlin.m

@@ -10,17 +10,34 @@ classdef normlin < matfaust.proj.proj_gen
 		%===============================================
 		%> @b Usage
 		%>
-		%> &nbsp;&nbsp;&nbsp; @b normlin(shape, normval): returns a NORMLIN projector (functor), shape defines the size of the input matrix (e.g. [1, 10]), normval defines the sparsity of the output matrix (the 2-norm of each row).<br/>
+		%> &nbsp;&nbsp;&nbsp; @b normlin(shape, s): returns a NORMLIN projector (functor), shape defines the size of the input matrix (e.g. [1, 10]), s defines the sparsity of the output matrix (the 2-norm of each row).<br/>
 		%>
 		%> @param shape: vector of size 2, to define the size of the input matrix.
-		%> @param normval: the sparsity parameter.
+		%> @param 's', value: (optional) the sparsity parameter, the 2-norm of the row (1 by default).
 		%===============================================
-		function proj = normlin(shape, normval, varargin)
+		function proj = normlin(shape, varargin)
 			import matfaust.factparams.ConstraintReal
-			if(normval < 0)
-				error('A norm can''t be negative')
+			s = 1;
+			if(length(varargin) > 0)
+				if(strcmp(varargin{1}, 's'))
+					disp('s in varargin')
+
+					if(length(varargin) < 2)
+						error('s value is missing')
+					end
+					s = varargin{2};
+					varargin(1:2) = []; % deleting the used cell
+					if(~ isreal(s) || ~ isscalar(s))
+						error('s must be a real scalar')
+					end
+					if(s < 0)
+						error('A norm can''t be negative')
+					end
+				% else % do nothing (ConstraintReal role)
+				end
 			end
-			proj.constraint = ConstraintReal('normlin', shape(1), shape(2), normval, varargin{:});
+
+			proj.constraint = ConstraintReal('normlin', shape(1), shape(2), s, varargin{:});
 		end
 	end
 end

wrapper/python/pyfaust/proj.py

@@ -358,10 +358,11 @@ class normcol(proj_gen):
         Functor for the NORMCOL projector. A, the image matrix, is defined by \f$ \forall j \in \{0,...,shape[1]-1\} \f$ the j-th column \f$ A_{*,j} \f$ is such that \f$\| A_{*,j}\|_2 = s  \f$.
 
     """
-    def __init__(self, shape, s):
+    def __init__(self, shape, s=1):
         """
         Args:
-            s: the column 2-norm.
+            shape: the input matrix shape.
+            s: the column 2-norm (default to 1).
 
         Example:
             >>> from pyfaust.proj import normcol
@@ -398,12 +399,11 @@ class normlin(proj_gen):
             0.01
     """
 
-    def __init__(self, shape, s):
+    def __init__(self, shape, s=1):
         """
         Args:
-            s: the row 2-norm.
-            normalized: True to normalize the projection image according to its Frobenius norm.
-            pos: True to skip negative values (replaced by zero) of the matrix to project.
+            shape: the input matrix shape.
+            s: the row 2-norm (default to 1).
 
         """
         if(s < 0):