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Convert this Fortran block to Java, preserving its control flow and logic.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Change the following Fortran code into Java without altering its purpose.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Convert this Fortran block to Python, preserving its control flow and logic.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Rewrite the snippet below in Python so it works the same as the original Fortran code.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Generate an equivalent VB version of this Fortran code.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Convert this Fortran snippet to VB and keep its semantics consistent.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Generate a PHP translation of this Fortran snippet without changing its computational steps.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
<?php class Vector { private $values; public function setValues(array $values) { if (count($values) != 3) throw new Exception('Values must contain exactly 3 values'); foreach ($values as $value) if (!is_int($value) && !is_float($value)) throw new Exception('Value "' . $value . '" has an invalid type'...
Maintain the same structure and functionality when rewriting this code in PHP.
program VectorProducts real, dimension(3) :: a, b, c a = (/ 3, 4, 5 /) b = (/ 4, 3, 5 /) c = (/ -5, -12, -13 /) print *, dot_product(a, b) print *, cross_product(a, b) print *, s3_product(a, b, c) print *, v3_product(a, b, c) contains function cross_product(a, b) real, dimension(3) :: cross_...
<?php class Vector { private $values; public function setValues(array $values) { if (count($values) != 3) throw new Exception('Values must contain exactly 3 values'); foreach ($values as $value) if (!is_int($value) && !is_float($value)) throw new Exception('Value "' . $value . '" has an invalid type'...
Port the following code from Groovy to C with equivalent syntax and logic.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Write a version of this Groovy function in C with identical behavior.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Write the same algorithm in C# as shown in this Groovy implementation.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Rewrite the snippet below in C# so it works the same as the original Groovy code.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Rewrite this program in C++ while keeping its functionality equivalent to the Groovy version.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Rewrite the snippet below in C++ so it works the same as the original Groovy code.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Maintain the same structure and functionality when rewriting this code in Java.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Write a version of this Groovy function in Java with identical behavior.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Write a version of this Groovy function in Python with identical behavior.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Produce a language-to-language conversion: from Groovy to Python, same semantics.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Maintain the same structure and functionality when rewriting this code in VB.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Write the same code in VB as shown below in Groovy.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Please provide an equivalent version of this Groovy code in Go.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Convert this Groovy block to Go, preserving its control flow and logic.
def pairwiseOperation = { x, y, Closure binaryOp -> assert x && y && x.size() == y.size() [x, y].transpose().collect(binaryOp) } def pwMult = pairwiseOperation.rcurry { it[0] * it[1] } def dotProduct = { x, y -> assert x && y && x.size() == y.size() pwMult(x, y).sum() }
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Can you help me rewrite this code in C instead of Haskell, keeping it the same logically?
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Change the programming language of this snippet from Haskell to C without modifying what it does.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Preserve the algorithm and functionality while converting the code from Haskell to C#.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Write the same code in C# as shown below in Haskell.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Port the provided Haskell code into C++ while preserving the original functionality.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Port the following code from Haskell to C++ with equivalent syntax and logic.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Generate an equivalent Java version of this Haskell code.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Please provide an equivalent version of this Haskell code in Java.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Produce a language-to-language conversion: from Haskell to Python, same semantics.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Convert this Haskell block to Python, preserving its control flow and logic.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Rewrite the snippet below in VB so it works the same as the original Haskell code.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Convert this Haskell snippet to VB and keep its semantics consistent.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Translate this program into Go but keep the logic exactly as in Haskell.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Rewrite the snippet below in Go so it works the same as the original Haskell code.
import Data.Monoid ((<>)) type Vector a = [a] type Scalar a = a a, b, c, d :: Vector Int a = [3, 4, 5] b = [4, 3, 5] c = [-5, -12, -13] d = [3, 4, 5, 6] dot :: (Num t) => Vector t -> Vector t -> Scalar t dot u v | length u == length v = sum $ zipWith (*) u v | otherwise = error "Dotted Vectors must be of...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Write a version of this Icon function in C with identical behavior.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Write the same code in C as shown below in Icon.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Transform the following Icon implementation into C#, maintaining the same output and logic.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Generate an equivalent C# version of this Icon code.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Translate this program into C++ but keep the logic exactly as in Icon.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Generate a C++ translation of this Icon snippet without changing its computational steps.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Convert this Icon snippet to Java and keep its semantics consistent.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Transform the following Icon implementation into Java, maintaining the same output and logic.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Write the same code in Python as shown below in Icon.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Change the following Icon code into Python without altering its purpose.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Can you help me rewrite this code in VB instead of Icon, keeping it the same logically?
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Convert this Icon snippet to VB and keep its semantics consistent.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Keep all operations the same but rewrite the snippet in Go.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Port the provided Icon code into Go while preserving the original functionality.
record Vector3D(x, y, z) procedure toString (vector) return "(" || vector.x || ", " || vector.y || ", " || vector.z || ")" end procedure dotProduct (a, b) return a.x * b.x + a.y * b.y + a.z * b.z end procedure crossProduct (a, b) x := a.y * b.z - a.z * b.y y := a.z * b.x - a.x * b.z z := a.x * b.y - a.y ...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Translate this program into C but keep the logic exactly as in J.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Change the programming language of this snippet from J to C without modifying what it does.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Write the same algorithm in C# as shown in this J implementation.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Write a version of this J function in C# with identical behavior.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Write the same code in C++ as shown below in J.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Preserve the algorithm and functionality while converting the code from J to C++.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Can you help me rewrite this code in Java instead of J, keeping it the same logically?
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Change the programming language of this snippet from J to Java without modifying what it does.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Convert this J block to Python, preserving its control flow and logic.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Transform the following J implementation into Python, maintaining the same output and logic.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Translate this program into VB but keep the logic exactly as in J.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Write a version of this J function in VB with identical behavior.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Ensure the translated Go code behaves exactly like the original J snippet.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Convert this J block to Go, preserving its control flow and logic.
cross=: (1&|.@[ * 2&|.@]) - 2&|.@[ * 1&|.@]
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Rewrite this program in C while keeping its functionality equivalent to the Julia version.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Write a version of this Julia function in C with identical behavior.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Produce a functionally identical C# code for the snippet given in Julia.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Maintain the same structure and functionality when rewriting this code in C#.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Rewrite the snippet below in C++ so it works the same as the original Julia code.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Generate a C++ translation of this Julia snippet without changing its computational steps.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Port the provided Julia code into Java while preserving the original functionality.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Can you help me rewrite this code in Java instead of Julia, keeping it the same logically?
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Can you help me rewrite this code in Python instead of Julia, keeping it the same logically?
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Generate a Python translation of this Julia snippet without changing its computational steps.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Port the provided Julia code into VB while preserving the original functionality.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Write the same algorithm in VB as shown in this Julia implementation.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Convert this Julia block to Go, preserving its control flow and logic.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Preserve the algorithm and functionality while converting the code from Julia to Go.
using LinearAlgebra const a = [3, 4, 5] const b = [4, 3, 5] const c = [-5, -12, -13] println("Test Vectors:") @show a b c println("\nVector Products:") @show a ⋅ b @show a × b @show a ⋅ (b × c) @show a × (b × c)
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Port the following code from Lua to C with equivalent syntax and logic.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Keep all operations the same but rewrite the snippet in C.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Generate a C# translation of this Lua snippet without changing its computational steps.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Maintain the same structure and functionality when rewriting this code in C#.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Generate a C++ translation of this Lua snippet without changing its computational steps.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Write a version of this Lua function in C++ with identical behavior.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Write the same algorithm in Java as shown in this Lua implementation.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Produce a functionally identical Java code for the snippet given in Lua.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Transform the following Lua implementation into Python, maintaining the same output and logic.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Translate the given Lua code snippet into Python without altering its behavior.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
def crossp(a, b): assert len(a) == len(b) == 3, 'For 3D vectors only' a1, a2, a3 = a b1, b2, b3 = b return (a2*b3 - a3*b2, a3*b1 - a1*b3, a1*b2 - a2*b1) def dotp(a,b): assert len(a) == len(b), 'Vector sizes must match' return sum(aterm * bterm for aterm,bterm in zip(a, b)) def scal...
Please provide an equivalent version of this Lua code in VB.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Generate a VB translation of this Lua snippet without changing its computational steps.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
Option Base 1 Function dot_product(a As Variant, b As Variant) As Variant dot_product = WorksheetFunction.SumProduct(a, b) End Function Function cross_product(a As Variant, b As Variant) As Variant cross_product = Array(a(2) * b(3) - a(3) * b(2), a(3) * b(1) - a(1) * b(3), a(1) * b(2) - a(2) * b(1)) End Funct...
Port the following code from Lua to Go with equivalent syntax and logic.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Port the following code from Lua to Go with equivalent syntax and logic.
Vector = {} function Vector.new( _x, _y, _z ) return { x=_x, y=_y, z=_z } end function Vector.dot( A, B ) return A.x*B.x + A.y*B.y + A.z*B.z end function Vector.cross( A, B ) return { x = A.y*B.z - A.z*B.y, y = A.z*B.x - A.x*B.z, z = A.x*B.y - A.y*B.x } end function Vector.scal...
package main import "fmt" type vector struct { x, y, z float64 } var ( a = vector{3, 4, 5} b = vector{4, 3, 5} c = vector{-5, -12, -13} ) func dot(a, b vector) float64 { return a.x*b.x + a.y*b.y + a.z*b.z } func cross(a, b vector) vector { return vector{a.y*b.z - a.z*b.y, a.z*b.x - a.x*b.z,...
Write a version of this Mathematica function in C with identical behavior.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Convert this Mathematica block to C, preserving its control flow and logic.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
#include<stdio.h> typedef struct{ float i,j,k; }Vector; Vector a = {3, 4, 5},b = {4, 3, 5},c = {-5, -12, -13}; float dotProduct(Vector a, Vector b) { return a.i*b.i+a.j*b.j+a.k*b.k; } Vector crossProduct(Vector a,Vector b) { Vector c = {a.j*b.k - a.k*b.j, a.k*b.i - a.i*b.k, a.i*b.j - a.j*b.i}; return c; } f...
Transform the following Mathematica implementation into C#, maintaining the same output and logic.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Change the following Mathematica code into C# without altering its purpose.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
using System; using System.Windows.Media.Media3D; class VectorProducts { static double ScalarTripleProduct(Vector3D a, Vector3D b, Vector3D c) { return Vector3D.DotProduct(a, Vector3D.CrossProduct(b, c)); } static Vector3D VectorTripleProduct(Vector3D a, Vector3D b, Vector3D c) { r...
Rewrite this program in C++ while keeping its functionality equivalent to the Mathematica version.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Produce a language-to-language conversion: from Mathematica to C++, same semantics.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
#include <iostream> template< class T > class D3Vector { template< class U > friend std::ostream & operator<<( std::ostream & , const D3Vector<U> & ) ; public : D3Vector( T a , T b , T c ) { x = a ; y = b ; z = c ; } T dotproduct ( const D3Vector & rhs ) { T scalar = x * rhs.x + ...
Translate the given Mathematica code snippet into Java without altering its behavior.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...
Rewrite this program in Java while keeping its functionality equivalent to the Mathematica version.
a={3,4,5}; b={4,3,5}; c={-5,-12,-13}; a.b Cross[a,b] a.Cross[b,c] Cross[a,Cross[b,c]]
public class VectorProds{ public static class Vector3D<T extends Number>{ private T a, b, c; public Vector3D(T a, T b, T c){ this.a = a; this.b = b; this.c = c; } public double dot(Vector3D<?> vec){ return (a.doubleValue() * vec.a.dou...