import (
"fmt"
"log"
+ "math"
"math/big"
)
// 1344719667586153181419716641724567886890850696275767987106294472017884974410332069524504824747437757
// false
}
+
+// This example shows how to use big.Float to compute the square root of 2 with
+// a precision of 200 bits, and how to print the result as a decimal number.
+func Example_sqrt2() {
+ // We'll do computations with 200 bits of precision in the mantissa.
+ const prec = 200
+
+ // Compute the square root of 2 using Newton's Method. We start with
+ // an initial estimate for sqrt(2), and then iterate:
+ // x_{n+1} = 1/2 * ( x_n + (2.0 / x_n) )
+
+ // Since Newton's Method doubles the number of correct digits at each
+ // iteration, we need at least log_2(prec) steps.
+ steps := int(math.Log2(prec))
+
+ // Initialize values we need for the computation.
+ two := new(big.Float).SetPrec(prec).SetInt64(2)
+ half := new(big.Float).SetPrec(prec).SetFloat64(0.5)
+
+ // Use 1 as the initial estimate.
+ x := new(big.Float).SetPrec(prec).SetInt64(1)
+
+ // We use t as a temporary variable. There's no need to set its precision
+ // since big.Float values with unset (== 0) precision automatically assume
+ // the largest precision of the arguments when used as the result (receiver)
+ // of a big.Float operation.
+ t := new(big.Float)
+
+ // Iterate.
+ for i := 0; i <= steps; i++ {
+ t.Quo(two, x) // t = 2.0 / x_n
+ t.Add(x, t) // t = x_n + (2.0 / x_n)
+ x.Mul(half, t) // x_{n+1} = 0.5 * t
+ }
+
+ // We can use the usual fmt.Printf verbs since big.Float implements fmt.Formatter
+ fmt.Printf("sqrt(2) = %.50f\n", x)
+
+ // Print the error between 2 and x*x.
+ t.Mul(x, x) // t = x*x
+ fmt.Printf("error = %e\n", t.Sub(two, t))
+
+ // Output:
+ // sqrt(2) = 1.41421356237309504880168872420969807856967187537695
+ // error = 0.000000e+00
+}