Instruction
stringlengths
45
106
input_code
stringlengths
1
13.7k
output_code
stringlengths
1
13.7k
Port the provided F# code into Python while preserving the original functionality.
> open Microsoft.FSharp.Math;; > let a = complex 1.0 1.0;; val a : complex = 1r+1i > let b = complex 3.14159 1.25;; val b : complex = 3.14159r+1.25i > a + b;; val it : Complex = 4.14159r+2.25i {Conjugate = 4.14159r-2.25i; ImaginaryPart = 2.25; Mag...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Keep all operations the same but rewrite the snippet in Go.
> open Microsoft.FSharp.Math;; > let a = complex 1.0 1.0;; val a : complex = 1r+1i > let b = complex 3.14159 1.25;; val b : complex = 3.14159r+1.25i > a + b;; val it : Complex = 4.14159r+2.25i {Conjugate = 4.14159r-2.25i; ImaginaryPart = 2.25; Mag...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Port the provided Factor code into C while preserving the original functionality.
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Produce a functionally identical C# code for the snippet given in Factor.
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Can you help me rewrite this code in C++ instead of Factor, keeping it the same logically?
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Write the same code in Java as shown below in Factor.
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Transform the following Factor implementation into Python, maintaining the same output and logic.
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Generate a Go translation of this Factor snippet without changing its computational steps.
USING: combinators kernel math math.functions prettyprint ; C{ 1 2 } C{ 0.9 -2.78 } { [ + . ] [ - . ] [ * . ] [ / . ] [ ^ . ] } 2cleave C{ 1 2 } { [ neg . ] [ recip . ] [ conjugate . ] [ sin ....
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Transform the following Forth implementation into C, maintaining the same output and logic.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Keep all operations the same but rewrite the snippet in C#.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Write a version of this Forth function in C++ with identical behavior.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Generate an equivalent Java version of this Forth code.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Change the following Forth code into Python without altering its purpose.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Rewrite the snippet below in Go so it works the same as the original Forth code.
S" fsl-util.fs" REQUIRED S" complex.fs" REQUIRED zvariable x zvariable y 1e 1e x z! pi 1.2e y z! x z@ y z@ z+ z. x z@ y z@ z* z. 1e 0e zconstant 1+0i 1+0i x z@ z/ z. x z@ znegate z.
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Preserve the algorithm and functionality while converting the code from Fortran to C#.
program cdemo complex :: a = (5,3), b = (0.5, 6.0) complex :: absum, abprod, aneg, ainv absum = a + b abprod = a * b aneg = -a ainv = 1.0 / a end program cdemo
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Convert this Fortran snippet to C++ and keep its semantics consistent.
program cdemo complex :: a = (5,3), b = (0.5, 6.0) complex :: absum, abprod, aneg, ainv absum = a + b abprod = a * b aneg = -a ainv = 1.0 / a end program cdemo
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Generate a C translation of this Fortran snippet without changing its computational steps.
program cdemo complex :: a = (5,3), b = (0.5, 6.0) complex :: absum, abprod, aneg, ainv absum = a + b abprod = a * b aneg = -a ainv = 1.0 / a end program cdemo
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Produce a functionally identical Java code for the snippet given in Fortran.
program cdemo complex :: a = (5,3), b = (0.5, 6.0) complex :: absum, abprod, aneg, ainv absum = a + b abprod = a * b aneg = -a ainv = 1.0 / a end program cdemo
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Rewrite the snippet below in Python so it works the same as the original Fortran code.
program cdemo complex :: a = (5,3), b = (0.5, 6.0) complex :: absum, abprod, aneg, ainv absum = a + b abprod = a * b aneg = -a ainv = 1.0 / a end program cdemo
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Maintain the same structure and functionality when rewriting this code in C.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Produce a language-to-language conversion: from Groovy to C#, same semantics.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Transform the following Groovy implementation into C++, maintaining the same output and logic.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Preserve the algorithm and functionality while converting the code from Groovy to Java.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Rewrite the snippet below in Python so it works the same as the original Groovy code.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Please provide an equivalent version of this Groovy code in Go.
class Complex { final Number real, imag static final Complex i = [0,1] as Complex Complex(Number r, Number i = 0) { (real, imag) = [r, i] } Complex(Map that) { (real, imag) = [that.real ?: 0, that.imag ?: 0] } Complex plus (Complex c) { [real + c.real, imag + c.imag] as Complex } Complex...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Translate the given Haskell code snippet into C without altering its behavior.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Please provide an equivalent version of this Haskell code in C#.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Generate a C++ translation of this Haskell snippet without changing its computational steps.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Write a version of this Haskell function in Java with identical behavior.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Transform the following Haskell implementation into Python, maintaining the same output and logic.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Convert this Haskell snippet to Go and keep its semantics consistent.
import Data.Complex main = do let a = 1.0 :+ 2.0 let b = 4 putStrLn $ "Add: " ++ show (a + b) putStrLn $ "Subtract: " ++ show (a - b) putStrLn $ "Multiply: " ++ show (a * b) putStrLn $ "Divide: " ++ show (a / b) putStrLn $ "Negate: " ++ show (-a) putStrLn $ "Inverse: " ...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Rewrite the snippet below in C so it works the same as the original Icon code.
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Keep all operations the same but rewrite the snippet in C#.
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Generate a C++ translation of this Icon snippet without changing its computational steps.
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Translate this program into Java but keep the logic exactly as in Icon.
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Can you help me rewrite this code in Python instead of Icon, keeping it the same logically?
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Transform the following Icon implementation into Go, maintaining the same output and logic.
procedure main() SetupComplex() a := complex(1,2) b := complex(3,4) c := complex(&pi,1.5) d := complex(1) e := complex(,1) every v := !"abcde" do write(v," := ",cpxstr(variable(v))) write("a+b := ", cpxstr(cpxadd(a,b))) write("a-b := ", cpxstr(cpxsub(a,b))) write("a*b := ", cpxstr(cpxmul(a,b))) write("a/b := ", ...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Preserve the algorithm and functionality while converting the code from J to C.
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Can you help me rewrite this code in C# instead of J, keeping it the same logically?
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Can you help me rewrite this code in C++ instead of J, keeping it the same logically?
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Produce a language-to-language conversion: from J to Java, same semantics.
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Transform the following J implementation into Python, maintaining the same output and logic.
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Change the following J code into Go without altering its purpose.
x=: 1j1 y=: 3.14159j1.2 x+y 4.14159j2.2 x*y 1.94159j4.34159 %x 0.5j_0.5 -x _1j_1 +x 1j_1
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Can you help me rewrite this code in C instead of Julia, keeping it the same logically?
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Write a version of this Julia function in C# with identical behavior.
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Ensure the translated C++ code behaves exactly like the original Julia snippet.
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Port the following code from Julia to Java with equivalent syntax and logic.
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Convert this Julia snippet to Python and keep its semantics consistent.
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Convert this Julia block to Go, preserving its control flow and logic.
julia> z1 = 1.5 + 3im julia> z2 = 1.5 + 1.5im julia> z1 + z2 3.0 + 4.5im julia> z1 - z2 0.0 + 1.5im julia> z1 * z2 -2.25 + 6.75im julia> z1 / z2 1.5 + 0.5im julia> - z1 -1.5 - 3.0im julia> conj(z1), z1' (1.5 - 3.0im,1.5 - 3.0im) julia> abs(z1) 3.3541019662496847 julia> z1^z2 -1.102482955327779 - 0.38306415117199305i...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Rewrite this program in C while keeping its functionality equivalent to the Lua version.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Change the following Lua code into C# without altering its purpose.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Rewrite the snippet below in C++ so it works the same as the original Lua code.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Convert this Lua block to Java, preserving its control flow and logic.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Port the following code from Lua to Python with equivalent syntax and logic.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Rewrite this program in Go while keeping its functionality equivalent to the Lua version.
complex = setmetatable({ __add = function(u, v) return complex(u.real + v.real, u.imag + v.imag) end, __sub = function(u, v) return complex(u.real - v.real, u.imag - v.imag) end, __mul = function(u, v) return complex(u.real * v.real - u.imag * v.imag, u.real * v.imag + u.imag * v.real) end, __div = function(u, v) retu...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Convert the following code from Mathematica to C, ensuring the logic remains intact.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Change the programming language of this snippet from Mathematica to C# without modifying what it does.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Produce a language-to-language conversion: from Mathematica to C++, same semantics.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Maintain the same structure and functionality when rewriting this code in Java.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Transform the following Mathematica implementation into Python, maintaining the same output and logic.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Change the programming language of this snippet from Mathematica to Go without modifying what it does.
x=1+2I y=3+4I x+y => 4 + 6 I x-y => -2 - 2 I y x => -5 + 10 I y/x => 11/5 - (2 I)/5 x^3 => -11 - 2 I y^4 => -527 - 336 I x^y => (1 + 2 I)^(3 + 4 I) N[x^y] => 0.12901 + 0.0339241 I
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Rewrite the snippet below in C so it works the same as the original MATLAB code.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Produce a language-to-language conversion: from MATLAB to C#, same semantics.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Transform the following MATLAB implementation into C++, maintaining the same output and logic.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Generate a Java translation of this MATLAB snippet without changing its computational steps.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Transform the following MATLAB implementation into Python, maintaining the same output and logic.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Convert this MATLAB snippet to Go and keep its semantics consistent.
>> a = 1+i a = 1.000000000000000 + 1.000000000000000i >> b = 3+7i b = 3.000000000000000 + 7.000000000000000i >> a+b ans = 4.000000000000000 + 8.000000000000000i >> a-b ans = -2.000000000000000 - 6.000000000000000i >> a*b ans = -4.000000000000000 +10.000000000000000i >> a/b ans = 0.17241379310...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Write a version of this Nim function in C with identical behavior.
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Write the same algorithm in C# as shown in this Nim implementation.
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Can you help me rewrite this code in C++ instead of Nim, keeping it the same logically?
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Keep all operations the same but rewrite the snippet in Java.
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Generate a Python translation of this Nim snippet without changing its computational steps.
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Preserve the algorithm and functionality while converting the code from Nim to Go.
import complex var a: Complex = (1.0,1.0) var b: Complex = (3.1415,1.2) echo("a  : " & $a) echo("b  : " & $b) echo("a + b: " & $(a + b)) echo("a * b: " & $(a * b)) echo("1/a  : " & $(1/a)) echo("-a  : " & $(-a))
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Translate this program into C but keep the logic exactly as in OCaml.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Translate the given OCaml code snippet into C# without altering its behavior.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Produce a functionally identical C++ code for the snippet given in OCaml.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Convert this OCaml snippet to Java and keep its semantics consistent.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Ensure the translated Python code behaves exactly like the original OCaml snippet.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Preserve the algorithm and functionality while converting the code from OCaml to Go.
open Complex let print_complex z = Printf.printf "%f + %f i\n" z.re z.im let () = let a = { re = 1.0; im = 1.0 } and b = { re = 3.14159; im = 1.25 } in print_complex (add a b); print_complex (mul a b); print_complex (inv a); print_complex (neg a); print_complex (conj a)
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Rewrite this program in C while keeping its functionality equivalent to the Pascal version.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Keep all operations the same but rewrite the snippet in C#.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Transform the following Pascal implementation into C++, maintaining the same output and logic.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Port the provided Pascal code into Java while preserving the original functionality.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Keep all operations the same but rewrite the snippet in Python.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Produce a functionally identical Go code for the snippet given in Pascal.
Program ComplexDemo; uses ucomplex; var a, b, absum, abprod, aneg, ainv, acong: complex; function complex(const re, im: real): ucomplex.complex; overload; begin complex.re := re; complex.im := im; end; begin a := complex(5, 3); b := complex(0.5, 6.0); absum := a + b; writeln ('(5 ...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Generate an equivalent C version of this Perl code.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Translate the given Perl code snippet into C# without altering its behavior.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Ensure the translated C++ code behaves exactly like the original Perl snippet.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Convert the following code from Perl to Java, ensuring the logic remains intact.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Maintain the same structure and functionality when rewriting this code in Python.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Preserve the algorithm and functionality while converting the code from Perl to Go.
use Math::Complex; my $a = 1 + 1*i; my $b = 3.14159 + 1.25*i; print "$_\n" foreach $a + $b, $a * $b, -$a, 1 / $a, ~$a;
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Port the provided PowerShell code into C while preserving the original functionality.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Rewrite this program in C# while keeping its functionality equivalent to the PowerShell version.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Produce a functionally identical C++ code for the snippet given in PowerShell.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...
Ensure the translated Java code behaves exactly like the original PowerShell snippet.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
public class Complex { public final double real; public final double imag; public Complex() { this(0, 0); } public Complex(double r, double i) { real = r; imag = i; } public Complex add(Complex b) { return new Complex(this.real + b.real, this.imag + b.imag)...
Port the provided PowerShell code into Python while preserving the original functionality.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
>>> z1 = 1.5 + 3j >>> z2 = 1.5 + 1.5j >>> z1 + z2 (3+4.5j) >>> z1 - z2 1.5j >>> z1 * z2 (-2.25+6.75j) >>> z1 / z2 (1.5+0.5j) >>> - z1 (-1.5-3j) >>> z1.conjugate() (1.5-3j) >>> abs(z1) 3.3541019662496847 >>> z1 ** z2 (-1.1024829553277784-0.38306415117199333j) >>> z1.real 1.5 >>> z1.imag 3.0 >>>
Convert this PowerShell block to Go, preserving its control flow and logic.
class Complex { [Double]$x [Double]$y Complex() { $this.x = 0 $this.y = 0 } Complex([Double]$x, [Double]$y) { $this.x = $x $this.y = $y } [Double]abs2() {return $this.x*$this.x + $this.y*$this.y} [Double]abs() {return [math]::sqrt($this.abs2())} static [Complex]add([Complex]$m,...
package main import ( "fmt" "math/cmplx" ) func main() { a := 1 + 1i b := 3.14159 + 1.25i fmt.Println("a: ", a) fmt.Println("b: ", b) fmt.Println("a + b: ", a+b) fmt.Println("a * b: ", a*b) fmt.Println("-a: ", -a) fmt.Println("1 / a: ", 1/a) fmt.Println("a̅...
Can you help me rewrite this code in C instead of Racket, keeping it the same logically?
#lang racket (define a 3+4i) (define b 8+0i) (+ a b) (- a b) (/ a b) (* a b) (- a) (/ 1 a) (conjugate a)
#include <complex.h> #include <stdio.h> void cprint(double complex c) { printf("%f%+fI", creal(c), cimag(c)); } void complex_operations() { double complex a = 1.0 + 1.0I; double complex b = 3.14159 + 1.2I; double complex c; printf("\na="); cprint(a); printf("\nb="); cprint(b); c = a + b; printf("...
Write the same code in C# as shown below in Racket.
#lang racket (define a 3+4i) (define b 8+0i) (+ a b) (- a b) (/ a b) (* a b) (- a) (/ 1 a) (conjugate a)
namespace RosettaCode.Arithmetic.Complex { using System; using System.Numerics; internal static class Program { private static void Main() { var number = Complex.ImaginaryOne; foreach (var result in new[] { number + number, number * number, -number, 1 / number, C...
Write the same algorithm in C++ as shown in this Racket implementation.
#lang racket (define a 3+4i) (define b 8+0i) (+ a b) (- a b) (/ a b) (* a b) (- a) (/ 1 a) (conjugate a)
#include <iostream> #include <complex> using std::complex; void complex_operations() { complex<double> a(1.0, 1.0); complex<double> b(3.14159, 1.25); std::cout << a + b << std::endl; std::cout << a * b << std::endl; std::cout << 1.0 / a << std::endl; std::cout << -a << std::endl; std::cou...