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1. UNIX for Beginners Questions & Answers
Hi,
I want to compare same column in two files, if values match then display the column or display "NA".
Ex :
File 1 :
123
abc
xyz
pqr
File 2:
122
aab
fdf
pqr
fff
qqq
rrr (1 Reply)
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2. What is on Your Mind?
Hello.
I have redesigned our "similar threads" for a more "clean style" in both the desktop view and the mobile view for the forum "show thread".
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Hi,
I have been thinking of how to script this but i have no clue at all..
Could someone please help me out or give me some idea on this?
I would like to group those lines with the same first variable in each line, joining the 2nd variables with commas.
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hi,
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Patrick (2 Replies)
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5. Shell Programming and Scripting
I have a file which contains data as below:
nbk1j7o pageName=/jsp/RMBS/RMBSHome.jsf
nbk1j7o pageName=/jsp/RMBS/RMBSHome.jsf
nbk1j7o pageName=/jsp/RMBS/RMBSHome.jsf
nbk1j7o pageName=/jsp/RMBS/RMBSHome.jsf
nbk1j7o pageName=/jsp/common/index.jsf
nbk1j7o pageName=/jsp/common/index.jsf
nbk1wqe... (6 Replies)
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6. Programming
Hi,
I am windows programer. I have very basic knowledge of Unix OS.
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Hey people,
at first: I'm from Germany, so my english isn't very good, okay?;)
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8. UNIX for Dummies Questions & Answers
Hi,
I am trying to quickly learn Unix because I am going to be using HP-UX soon.
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9. News, Links, Events and Announcements
Note the new feature on UNIX.COM, many thread at the bottom of the page have a new feature:
Similiar Threads
Here is an example on one of Perderabo's posts:
https://www.unix.com/showthread.php?t=16337
Kudos to the vB folks for this built-in feature!!
Neo (0 Replies)
Discussion started by: Neo
0 Replies
tensor(2rheolef) rheolef-6.1 tensor(2rheolef)
NAME
tensor - a N*N tensor, N=1,2,3
SYNOPSYS
The tensor class defines a 3*3 tensor, as the value of a tensorial valued field. Basic algebra with scalars, vectors of R^3 (i.e. the point
class) and tensor objects are supported.
IMPLEMENTATION
template<class T>
class tensor_basic {
public:
typedef size_t size_type;
typedef T element_type;
// allocators:
tensor_basic (const T& init_val = 0);
tensor_basic (T x[3][3]);
tensor_basic (const tensor_basic<T>& a);
// affectation:
tensor_basic<T>& operator = (const tensor_basic<T>& a);
tensor_basic<T>& operator = (const T& val);
// modifiers:
void fill (const T& init_val);
void reset ();
void set_row (const point_basic<T>& r, size_t i, size_t d = 3);
void set_column (const point_basic<T>& c, size_t j, size_t d = 3);
// accessors:
T& operator()(size_type i, size_type j);
T operator()(size_type i, size_type j) const;
point_basic<T> row(size_type i) const;
point_basic<T> col(size_type i) const;
size_t nrow() const; // = 3, for template matrix compatibility
size_t ncol() const;
// inputs/outputs:
std::ostream& put (std::ostream& s, size_type d = 3) const;
std::istream& get (std::istream&);
// algebra:
bool operator== (const tensor_basic<T>&) const;
bool operator!= (const tensor_basic<T>& b) const { return ! operator== (b); }
template <class U>
friend tensor_basic<U> operator- (const tensor_basic<U>&);
template <class U>
friend tensor_basic<U> operator+ (const tensor_basic<U>&, const tensor_basic<U>&);
template <class U>
friend tensor_basic<U> operator- (const tensor_basic<U>&, const tensor_basic<U>&);
template <class U>
friend tensor_basic<U> operator* (int k, const tensor_basic<U>& a);
template <class U>
friend tensor_basic<U> operator* (const U& k, const tensor_basic<U>& a);
template <class U>
friend tensor_basic<U> operator* (const tensor_basic<U>& a, int k);
template <class U>
friend tensor_basic<U> operator* (const tensor_basic<U>& a, const U& k);
template <class U>
friend tensor_basic<U> operator/ (const tensor_basic<U>& a, int k);
template <class U>
friend tensor_basic<U> operator/ (const tensor_basic<U>& a, const U& k);
template <class U>
friend point_basic<U> operator* (const tensor_basic<U>&, const point_basic<U>&);
template <class U>
friend point_basic<U> operator* (const point_basic<U>& yt, const tensor_basic<U>& a);
point_basic<T> trans_mult (const point_basic<T>& x) const;
template <class U>
friend tensor_basic<U> trans (const tensor_basic<U>& a, size_t d = 3);
template <class U>
friend tensor_basic<U> operator* (const tensor_basic<U>& a, const tensor_basic<U>& b);
template <class U>
friend void prod (const tensor_basic<U>& a, const tensor_basic<U>& b, tensor_basic<U>& result,
size_t di=3, size_t dj=3, size_t dk=3);
template <class U>
friend tensor_basic<U> inv (const tensor_basic<U>& a, size_t d = 3);
template <class U>
friend tensor_basic<U> diag (const point_basic<U>& d);
template <class U>
friend tensor_basic<U> identity (size_t d=3);
template <class U>
friend tensor_basic<U> dyadic (const point_basic<U>& u, const point_basic<U>& v, size_t d=3);
// metric and geometric transformations:
template <class U>
friend U dotdot (const tensor_basic<U>&, const tensor_basic<U>&);
template <class U>
friend U norm2 (const tensor_basic<U>& a) { return dotdot(a,a); }
template <class U>
friend U dist2 (const tensor_basic<U>& a, const tensor_basic<U>& b) { return norm2(a-b); }
template <class U>
friend U norm (const tensor_basic<U>& a) { return ::sqrt(norm2(a)); }
template <class U>
friend U dist (const tensor_basic<U>& a, const tensor_basic<U>& b) { return norm(a-b); }
T determinant (size_type d = 3) const;
template <class U>
friend U determinant (const tensor_basic<U>& A, size_t d = 3);
template <class U>
friend bool invert_3x3 (const tensor_basic<U>& A, tensor_basic<U>& result);
// spectral:
// eigenvalues & eigenvectors:
// a = q*d*q^T
// a may be symmetric
// where q=(q1,q2,q3) are eigenvectors in rows (othonormal matrix)
// and d=(d1,d2,d3) are eigenvalues, sorted in decreasing order d1 >= d2 >= d3
// return d
point_basic<T> eig (tensor_basic<T>& q, size_t dim = 3) const;
point_basic<T> eig (size_t dim = 3) const;
// singular value decomposition:
// a = u*s*v^T
// a can be unsymmetric
// where u=(u1,u2,u3) are left pseudo-eigenvectors in rows (othonormal matrix)
// v=(v1,v2,v3) are right pseudo-eigenvectors in rows (othonormal matrix)
// and s=(s1,s2,s3) are eigenvalues, sorted in decreasing order s1 >= s2 >= s3
// return s
point_basic<T> svd (tensor_basic<T>& u, tensor_basic<T>& v, size_t dim = 3) const;
// data:
T _x[3][3];
};
typedef tensor_basic<Float> tensor;
// inputs/outputs:
template<class T>
inline
std::istream& operator>> (std::istream& in, tensor_basic<T>& a)
{
return a.get (in);
}
template<class T>
inline
std::ostream& operator<< (std::ostream& out, const tensor_basic<T>& a)
{
return a.put (out);
}
// t = a otimes b
template<class T>
tensor_basic<T> otimes (const point_basic<T>& a, const point_basic<T>& b, size_t na = 3);
// t += a otimes b
template<class T>
void cumul_otimes (tensor_basic<T>& t, const point_basic<T>& a, const point_basic<T>& b, size_t na = 3);
template<class T>
void cumul_otimes (tensor_basic<T>& t, const point_basic<T>& a, const point_basic<T>& b, size_t na, size_t nb);
rheolef-6.1 rheolef-6.1 tensor(2rheolef)