Merge pull request #34 from fchapoton/many_typos_fixed

fix many typos

EXAMPLES/cubes/makeCube.cpp

@@ -31,9 +31,9 @@ struct QuickFraction
 
 /**
  * Makes a cube, [0, scale]^n, as a latte facet file.
- * @parm filename: output file name
- * @parm dim: dim = n from above.
- * @parm scale: we scale the unit cube.
+ * @param filename: output file name
+ * @param dim: dim = n from above.
+ * @param scale: we scale the unit cube.
  */
 void makeCubeFile(const char *fileName, const long &dim, const QuickFraction& scale)
 {

README-mpl-files

@@ -57,7 +57,7 @@ code/maple/m-knapsack.mpl: top knapsack Maple code
 
  --- was the same as $PISA_PAPERS/knapsack/moreKnapsacks/knapsackwithdualdec.14.04.2012.mpl
 
- done: Now replaced by the better verion from https://www.math.ucdavis.edu/~latte/software/packages/m-knapsack.mpl 
+ done: Now replaced by the better version from https://www.math.ucdavis.edu/~latte/software/packages/m-knapsack.mpl 
 
 code/latte/top-ehrhart/TopEhrhart_lib.mpl: the SL method for finding top Ehrhart coefficients
 

code/latte/ConeInfo.cpp

@@ -521,7 +521,7 @@ ConeInfo::ConeInfo (vec_ZZ *cost, listCone *listCone_pointer, int numOfVars)
 				Coefficient *= -1;
 
 				S_Values[i] *= -1;
-				// sign is the sign of the orginal dot product
+				// sign is the sign of the original dot product
 				signs[i] = 1;
 
 			}
@@ -1374,7 +1374,7 @@ int	ConeInfo::Calculate_Integral_Point (vec_ZZ &Temp_Vector)
 	{
 		for(int j = 0; j < Number_of_Variables; j++)
 		{
-			// sign[] is the sign of the orginal dot product with the cost
+			// sign[] is the sign of the original dot product with the cost
 			Temp_Vector[j] -= signs[i] * temp->first[j] * temp_coefficients[i];
 		}
 		temp = temp->rest;

code/latte/Makefile.am

@@ -244,7 +244,7 @@ ConvertCDDextToLatte_LDADD = $(LDADD)
 
 
 #Run ./valuation/test/integrateHyperrectangleTest.sh 
-#  to start a maple script that will test integration of polynomials over rectangles in many dimentions.
+#  to start a maple script that will test integration of polynomials over rectangles in many dimensions.
 check_PROGRAMS += test-hyperrectangle-integration
 test_hyperrectangle_integration_SOURCES = valuation/test/testIntegrationHyperrectanglesDriver.cpp 
 

code/latte/buildPolytopes/BuildPolytope.cpp

@@ -53,7 +53,7 @@ void BuildPolytope::addPoint(vector<mpq_class> onePoint)
  * The center command keeps important properties like vertices and facets, but some are
  * lost like SIMPLE and SIMPLICIAL.
  *
- * The origional un-centered polytope is lost. Also, we do not automatically re-read vertex and facet information.
+ * The original un-centered polytope is lost. Also, we do not automatically re-read vertex and facet information.
  */
 void BuildPolytope::centerPolytope()
 {

code/latte/integration/benchmark.mpl

@@ -18,14 +18,14 @@ read("integration/createLinear.mpl"):
 #  A linear forms is called alpha, it is  represented by  a vector in Q^d.
 # A monomial m is a list of d integers
 #  A polynomial represented  in a sparse way;
-#  Exemple x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
+#  Example x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
 # Thus a sparse polynomial is represented as a list of lists.
 # 
 # .
 # 
 # Simplex and multiplicities.
 # 
-# INPUT: d an integer, S  list of d+1 lists of lenght d, alpha: list of lenght d . 
+# INPUT: d an integer, S  list of d+1 lists of length d, alpha: list of length d . 
 # OUTPUT: set of lists {[a_S], [m_S]} 
 # MATH: S a simplex of dimension d+1, alpha a linear form, m_S is the list of the number of vertices S where <\alpha,S> = a_S.
 # 
@@ -136,7 +136,7 @@ L:=[seq([j],j=0..m[1])];fi;
 newL;
 end:
 # INPUT: m a list of integers, coe a number
-# OUTPUT: a list of lists of lenght nops(m)
+# OUTPUT: a list of lists of length nops(m)
 # MATH:  The list $m$ represents the monomial x^m=x_1^{m[1]}x_2^{m[2]}\cdots x_d^{m[d].
 # The output is a list of lists. Each element in the list represents a linear form ([1,2]=x+2y). The output exausts all the linear form with exponents M=m[1]+..+m[d] which appear when  expressing   x^m as  linear combinations of linear form with exponent M. The first element is the coefficient multiplied by coe;
 list_and_coeff_for_monome:=proc(m,coe) local M,L,out:
@@ -157,9 +157,9 @@ out;
 end:
 ##integral_monome_via_waring([[0,0],[0,1],[1,0]],2,[9,2]);
 # Integral of a polynomial via Waring.
-# We give a polynomial in a sparse way; Exemple x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
+# We give a polynomial in a sparse way; Example x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
 #  We start by cleaning the sets for example we replace [[1,[1,2]],[1,[1,2]] by [2,[1,2]];
-# Input  L; a list of lists [[a,alpha],[b,beta],...]. here a is a number, alpha is a list. The ouptput is
+# Input  L; a list of lists [[a,alpha],[b,beta],...]. here a is a number, alpha is a list. The output is
 # a set of lists.
 # If alpha=beta, we replace by [a+b,alpha]; if a=0 we skip;
 # The input is a list  L of lists [a,\alpha] where a is a number. The output is of the same kind.
@@ -187,7 +187,7 @@ od;
 Y;
 end:
 # The input is a simplex S, d the dimension, sparse_poly a sparse polynomial. 
-# The ouput is a number; the integral over S of the polynomial.
+# The output is a number; the integral over S of the polynomial.
 integral_via_waring:=proc(S,d,sparse_poly) local output,i, L ;output:=0;
 L:=list_integral_via_waring(sparse_poly);
 for i from 1 to nops(L) do 

code/latte/integration/burstTrie.hpp

@@ -349,6 +349,6 @@ class BurstTrie
 
 	friend class BTrieIterator<T, S> ;
 private:
-	S* range; //S can be a class or a primitve
+	S* range; //S can be a class or a primitive
 	trieElem *firstElem; //first element in the trie
 }; //BurstTrie

code/latte/integration/integrationTestsLib.mpl

@@ -36,14 +36,14 @@ read("integration/createLinear.mpl"):
 #  A linear forms is called alpha, it is  represented by  a vector in Q^d.
 # A monomial m is a list of d integers
 #  A polynomial represented  in a sparse way;
-#  Exemple x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
+#  Example x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
 # Thus a sparse polynomial is represented as a list of lists.
 # 
 # .
 # 
 # Simplex and multiplicities.
 # 
-# INPUT: d an integer, S  list of d+1 lists of lenght d, alpha: list of lenght d . 
+# INPUT: d an integer, S  list of d+1 lists of length d, alpha: list of length d . 
 # OUTPUT: set of lists {[a_S], [m_S]} 
 # MATH: S a simplex of dimension d+1, alpha a linear form, m_S is the list of the number of vertices S where <\alpha,S> = a_S.
 # 
@@ -154,7 +154,7 @@ L:=[seq([j],j=0..m[1])];fi;
 newL;
 end:
 # INPUT: m a list of integers, coe a number
-# OUTPUT: a list of lists of lenght nops(m)
+# OUTPUT: a list of lists of length nops(m)
 # MATH:  The list $m$ represents the monomial x^m=x_1^{m[1]}x_2^{m[2]}\cdots x_d^{m[d].
 # The output is a list of lists. Each element in the list represents a linear form ([1,2]=x+2y). The output exausts all the linear form with exponents M=m[1]+..+m[d] which appear when  expressing   x^m as  linear combinations of linear form with exponent M. The first element is the coefficient multiplied by coe;
 list_and_coeff_for_monome:=proc(m,coe) local M,L,out:
@@ -175,9 +175,9 @@ out;
 end:
 ##integral_monome_via_waring([[0,0],[0,1],[1,0]],2,[9,2]);
 # Integral of a polynomial via Waring.
-# We give a polynomial in a sparse way; Exemple x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
+# We give a polynomial in a sparse way; Example x*y^2+2*x^2 with be given as a list of lists [[1,[1,2]],[2,[2,0]]. Each list represents a monomial with his coefficients. 
 #  We start by cleaning the sets for example we replace [[1,[1,2]],[1,[1,2]] by [2,[1,2]];
-# Input  L; a list of lists [[a,alpha],[b,beta],...]. here a is a number, alpha is a list. The ouptput is
+# Input  L; a list of lists [[a,alpha],[b,beta],...]. here a is a number, alpha is a list. The output is
 # a set of lists.
 # If alpha=beta, we replace by [a+b,alpha]; if a=0 we skip;
 # The input is a list  L of lists [a,\alpha] where a is a number. The output is of the same kind.
@@ -205,7 +205,7 @@ od;
 Y;
 end:
 # The input is a simplex S, d the dimension, sparse_poly a sparse polynomial. 
-# The ouput is a number; the integral over S of the polynomial.
+# The output is a number; the integral over S of the polynomial.
 integral_via_waring:=proc(S,d,sparse_poly) local output,i, L ;output:=0;
 L:=list_integral_via_waring(sparse_poly);
 for i from 1 to nops(L) do 

code/latte/integration/newIntegration.cpp

@@ -85,7 +85,7 @@ void convertToSimplex(simplexZZ &mySimplex, string line)
 /**
  * Integrate a simplex over a linear form.
  *
- * @parm a, b: ouput parameters, we return a/b += integration answer.
+ * @parm a, b: output parameters, we return a/b += integration answer.
  * @parm l: a linear form.
  * @parm mySimplex: integer simplex
  * @parm m: the power the linear form is raised to
@@ -340,7 +340,7 @@ RationalNTL integrateLinFormProducts(PolyIterator<RationalNTL, ZZ>* it, const si
 		++i;
 		lenM += temp->degree; //add the power
 
-		coef *= temp->coef; // M1! M2! ... MD! * (coefficents ^ powers)
+		coef *= temp->coef; // M1! M2! ... MD! * (coefficients ^ powers)
 
 		monomialCount *= (temp->degree+1); //monomialCount = number of monomials (m1, ..., md) <= (deg1, ..., degD).
 	}
@@ -364,7 +364,7 @@ RationalNTL integrateLinFormProducts(PolyIterator<RationalNTL, ZZ>* it, const si
 	//ok, now we just need to find the coeff of M in the polynomial expansion.
 
 
-	vec_ZZ tVector; //the coefficent vector of ( 1- a_1t_1 - ... - a_Dt_D) (we don't save the leading 1)
+	vec_ZZ tVector; //the coefficient vector of ( 1- a_1t_1 - ... - a_Dt_D) (we don't save the leading 1)
 	int* counter; //current power n
 	tVector.SetLength(productCount);
 	counter = new int[productCount];

code/latte/integration/residue.cpp

@@ -349,7 +349,7 @@ void computeResidueLawrence(const int d, const int M, const LinearLawrenceIntegr
 			continue; //really, at this point, the power should not be zero. It could be negative if this term is a repeat or positive.
 		if (coneTerm.rayDotProducts[i].epsilon == 0)
 		{
-			//cout << "factored anoter term: " << coneTerm.rayDotProducts[i].constant << "^" << coneTerm.rayDotProducts[i].power << endl;
+			//cout << "factored another term: " << coneTerm.rayDotProducts[i].constant << "^" << coneTerm.rayDotProducts[i].power << endl;
 			de *= Power_ZZ(coneTerm.rayDotProducts[i].constant, coneTerm.rayDotProducts[i].power);
 			continue;
 		}//factor the constant out: (a + 0*e)^power.

code/latte/interpolation/PolynomialInterpolation.cpp

@@ -36,7 +36,7 @@ PolynomialInterpolation::PolynomialInterpolation(unsigned int degree):
 
 //A B C D E F G H I J K L M N O P Q R S T U V W X Y Z	
 
-//sets matrix(toRow,:) = matirx(toRow,:) - value * matrix(fromRow, :) (matlab syntax)
+//sets matrix(toRow,:) = matrix(toRow,:) - value * matrix(fromRow, :) (matlab syntax)
 void PolynomialInterpolation::addMultRows(mpq_class  &value, int fromRow, int toRow)
 {
 	value.canonicalize();
@@ -130,11 +130,11 @@ void PolynomialInterpolation::GE()
 
         if(matrix[perfectRow][currentColumn] == 0 )
         {
-            cerr << "GE:assert matirx[perfectRow][currentColumn] != 0" << endl;
+            cerr << "GE:assert matrix[perfectRow][currentColumn] != 0" << endl;
             //cout << "perfectRow = " << perfectRow << ", curCol=" << currentColumn << endl;
             //cout << "row, col size=" << rowSize << ", " << colSize << endl;
             //printMatrix();
-            //cout << "origional matirx\n";
+            //cout << "original matrix\n";
             //copy.printMatrix();
             exit(1);
         }

code/latte/interpolation/testDriver.cpp

@@ -89,8 +89,8 @@ bool isReduced(mpq_class r)
 }//isReduced
 
 
-/*	Randomly generate polynomials, and create the coefficient matirx. Then solves the matrix and
- *  	makes sure the returnd answer is the same as the polynomial we randomly generated.
+/*	Randomly generate polynomials, and create the coefficient matrix. Then solves the matrix and
+ *  	makes sure the returned answer is the same as the polynomial we randomly generated.
  *
  * 	The polynomials have a max degree of MAXDEG and each coefficient is negative with prob. PNEG..
  * 		and coefficients are limited by MAXCOEF.
@@ -114,7 +114,7 @@ void test1Poly()
 	;
 
 	PolynomialInterpolation p(degree);
-	PolynomialInterpolation pCopy(degree); //pCopy is printed as the origional matrix if there is an error.
+	PolynomialInterpolation pCopy(degree); //pCopy is printed as the original matrix if there is an error.
 	vector<mpq_class> allX(degree); //keep track of points added so far.
 
 	//insert degree+1 many unique points (x, f(x)).