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1. UNIX for Beginners Questions & Answers
Dear UNIX forum members,
I am using macbook pro 13 (2015 edition) with MAC OS Mojave and am trying to write the shell script where when it is run through terminal it asks for an input (in the code below an input variable is domains) and then that input becomes capital letter or letters which... (3 Replies)
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2. UNIX for Dummies Questions & Answers
I have file like below
1|4|OR|OLAP|INT|INT||CONSTANT|2012/08/07|9999/12/31|0|0|0|0|PRL|-358.1684563||||||||||36522|55791|LNR|
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3. Shell Programming and Scripting
I have a file data_1.out which contains:
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4. Programming
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5. Programming
Hi,
I have received an application that stores some properties in a file. The existing struct looks like this:
struct TData
{
UINT uSizeIncludingStrings;
// copy of Telnet data struct
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// basic properties:
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6. Programming
I am trying to work out the best syntax for a relatively simple operation. The goal is to declare an instance of a struct and pass it around to be populated and have the data manipulated. There is an extra wrinkle in that the functions are in different src files.
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Can someone tell me how to do this?
Just a thought that entered my mind when learning about structs.
First thought was:
struct one
{
struct two;
}
struct two
{
three;
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one->two->three
would this be how you would access "three"? (1 Reply)
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9. UNIX for Dummies Questions & Answers
Hi,
I want to check a particular word is in standard error output or not. Can I acheive it in single command?
For example,
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cat error.log
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XXXXXXXXXXXXXXXXX
XXXXXXXXXXXXXXXXX
Successfully deleted
XXXXXXXXXXXXXXXXX
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10. UNIX for Advanced & Expert Users
I write kernel module with kernel threads using
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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)