VectorsΒΆ
The GVector class implements a vector as a one-dimensional array of successive double precision floating point values. You may allocate an vectors as follows
C++
1 2 3 | GVector vector1; // Allocates empty vector
GVector vector2(10); // Allocates vector with 10 elements
GVector vector3 = vector1; // Allocates vector by copying
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Python
1 2 3 | vector1 = gammalib.GVector() # Allocates empty vector
vector2 = gammalib.GVector(10) # Allocates vector with 10 elements
vector3 = vector1.copy() # Allocates vector by copying
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On allocation, all elements of a vector are set to 0.
There are three special constructors which you can use to allocate vectors with 1, 2 or 3 elements:
C++
1 2 3 | GVector vector1(1.0); // Allocates vector [1.0]
GVector vector2(1.0, 2.0); // Allocates vector [1.0, 2.0]
GVector vector3(1.0, 2.0, 3.0); // Allocates vector [1.0, 2.0, 3.0]
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Python
1 2 3 | vector1 = gammalib.GVector(1.0) # Allocates vector [1.0]
vector2 = gammalib.GVector(1.0, 2.0) # Allocates vector [1.0, 2.0]
vector3 = gammalib.GVector(1.0, 2.0, 3.0) # Allocates vector [1.0, 2.0, 3.0]
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You can access vector elements using the GVector::operator[]() operator. As usual in C++ and Python, indices start with 0:
C++
1 2 | std::cout << vector2[1] << std::endl; // Print 2nd element
2.0 // Result
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Python
1 2 | print(vector2[1]) # Print 2nd element
2.0 # Result
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Note that in C++ the GVector::operator[]() operator does not check the validity of the element index. If index checking is needed in C++, use the GVector::at() method:
C++
1 2 | std::cout << vector2.at(1) << std::endl; // Print 2nd element with index checking
2.0 // Result
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In Python, index checking is always performed.
All GammaLib objects are printable, and vectors can be printed using
C++
1 2 | std::cout << vector3 << std::endl; // Print vector
(1, 2, 3) // Result
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Python
1 2 | print(vector3) # Print result
(1, 2, 3) # Result
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You can handle vectors pretty much the same way you handle floating point variables. GVector supports various arithmetic operations:
C++
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | GVector a(1.0, 2.0, 3.0); // A vector
GVector b(2.0, 4.0, 6.0); // Another vector
GVector c; // Result vector
double s = 2.0; // A floating point value
c = a + b; // Vector + Vector addition
c += a; // Unary vector addition
c = a + s; // Vector + Scalar addition
c += s; // Unary scalar addition
c = s + b; // Scalar + Vector addition (only C++)
c = a - b; // Vector - Vector subtraction
c -= a; // Unary vector subtraction
c = a - s; // Vector - Scalar subtraction
c -= s; // Unary scalar subtraction
c = s - b; // Scalar - Vector subtraction (only C++)
s = a * b; // Vector * Vector multiplication (dot product)
c = a * s; // Vector * Scalar multiplication
c *= s; // Unary scalar multiplication
c = s * b; // Scalar * Vector multiplication (only C++)
c = a / s; // Vector * Scalar division
c /= s; // Unary scalar division
c = s; // Assigns scalar to all vector elements
c = -a; // Vector negation
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Python
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | a = gammalib.GVector(1.0, 2.0, 3.0) # A vector
b = gammalib.GVector(2.0, 4.0, 6.0) # Another vector
c = gammalib.GVector() # Result vector
s = 2.0 # A floating point value
c = a + b # Vector + Vector addition
c += a # Unary vector addition
c = a + s # Vector + Scalar addition
c += s # Unary scalar addition
c = a - b # Vector - Vector subtraction
c -= a # Unary vector subtraction
c = a - s # Vector - Scalar subtraction
c -= s # Unary scalar subtraction
s = a * b # Vector * Vector multiplication (dot product)
c = a * s # Vector * Scalar multiplication
c *= s # Unary scalar multiplication
c = a / s # Vector * Scalar division
c /= s # Unary scalar division
c = -a # Vector negation
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Most of these operations operate element-wise. For example, scalar additions or subtractions add or subtract a given scalar value from every vector element. And scalar multiplications and divisions multiply or divide every vector element by a given value. The dot product implements the usual formula
(where \(N\) is the number of vector elements). It is obvious that the dot product, as well as vector addition and subtraction, require vectors of identical dimensions. If vectors are not identical, an GException::vector_mismatch exception will be thrown.
You can compare vectors using
Finally, you can use the comparison operators
C++
1 2 | int equal = (a == b); // True if all elements equal
int unequal = (a != b); // True if at least one elements unequal
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Python
1 2 | equal = (a == b) # True if all elements equal
unequal = (a != b) # True if at least one elements unequal
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In addition to the operators, you can apply the following mathematical functions to vectors
C++
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | c = acos(a); // Vector with acos of all vector elements
c = acosh(a); // Vector with acosh of all vector elements
c = asin(a); // Vector with asin of all vector elements
c = asinh(a); // Vector with asinh of all vector elements
c = atan(a); // Vector with atan of all vector elements
c = atanh(a); // Vector with atanh of all vector elements
c = cos(a); // Vector with cos of all vector elements
c = cosh(a); // Vector with cosh of all vector elements
c = exp(a); // Vector with exp of all vector elements
c = abs(a); // Vector with absolute values of all vector elements
c = log(a); // Vector with natural logarithm of all vector elements
c = log10(a); // Vector with base 10 logarithm of all vector elements
c = sin(a); // Vector with sin of all vector elements
c = sinh(a); // Vector with sinh of all vector elements
c = tan(a); // Vector with tan of all vector elements
c = tanh(a); // Vector with tanh of all vector elements
c = pow(a, 2.7); // Vector with power of 2.7 of all vector elements (only C++)
c = cross(a, b); // Vector with cross product of 3 element vectors
s = norm(a); // Vector norm |a|
s = min(a); // Minimum element of vector
s = max(a); // Maximum element of vector
s = sum(a); // Sum of vector elements
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Python
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | c = a.acos() # Vector with acos of all vector elements
c = a.acosh() # Vector with acosh of all vector elements
c = a.asin() # Vector with asin of all vector elements
c = a.asinh() # Vector with asinh of all vector elements
c = a.atan() # Vector with atan of all vector elements
c = a.atanh() # Vector with atanh of all vector elements
c = a.cos() # Vector with cos of all vector elements
c = a.cosh() # Vector with cosh of all vector elements
c = a.exp() # Vector with exp of all vector elements
c = a.abs() # Vector with absolute values of all vector elements
c = a.log() # Vector with natural logarithm of all vector elements
c = a.log10() # Vector with base 10 logarithm of all vector elements
c = a.sin() # Vector with sin of all vector elements
c = a.sinh() # Vector with sinh of all vector elements
c = a.tan() # Vector with tan of all vector elements
c = a.tanh() # Vector with tanh of all vector elements
c = a.cross(b) # Vector with cross product of 3 element vectors
s = a.norm() # Vector norm |a|
s = a.min() # Minimum element of vector
s = a.max() # Maximum element of vector
s = a.sum() # Sum of vector elements
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Finally, the following methods exist:
C++
1 2 | int size = a.size(); // Returns number of vector elements
int nonzeros = a.non_zeros(); // Returns number of non-zero vector elements
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Python
1 2 | size = a.size(a) # Returns number of vector elements
nonzeros = a.non_zeros() # Returns number of non-zero vector elements
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