I have a problem when I use math.Floor with a floating-point variable (round down/truncate the precision part). How can I do it correctly?
package main
import (
"fmt"
"math"
)
func main() {
var st float64 = 1980
var salePrice1 = st * 0.1 / 1.1
fmt.Printf("%T:%v\n", salePrice1, salePrice1) // 179.9999
var salePrice2 = math.Floor(st * 0.1 / 1.1)
fmt.Printf("%T:%v\n", salePrice2, salePrice2) // 179
}
Playground: https://play.golang.org/p/49TjJwwEdEJ
Output:
float64:179.99999999999997
float64:179
I expect the output of 1980 * 0.1 / 1.1 to be 180, but the actual output is 179.
The original question:
Incorrect floor number in golang
I have problem when use Math.Floor with float variable (round
down/truncate the precision part). How can i do it correctly?
package main
import (
"fmt"
"math"
)
func main() {
var st float64 = 1980
var salePrice1 = st * 0.1 / 1.1
fmt.Printf("%T:%v\n", salePrice1, salePrice1)
var salePrice2 = math.Floor(st * 0.1 / 1.1)
fmt.Printf("%T:%v\n", salePrice2, salePrice2)
}
I expect the output of 1980 * 0.1 / 1.1 to be 180, but the actual
output is 179.”
Playground:
Output:
float64:179.99999999999997
float64:179
The XY problem is asking about your attempted solution rather than your actual problem: The XY Problem.
Clearly, this is a money calculation for salePrice1. Money calculations use precise decimal calculations, not imprecise binary floating-point calculations.
For money calculations use integers. For example,
package main
import "fmt"
func main() {
var st int64 = 198000 // $1980.00 as cents
fmt.Printf("%[1]T:%[1]v\n", st)
fmt.Printf("$%d.%02d\n", st/100, st%100)
var n, d int64 = 1, 11
fmt.Printf("%d, %d\n", n, d)
var salePrice1 int64 = (st * n) / d // round down
fmt.Printf("%[1]T:%[1]v\n", salePrice1)
fmt.Printf("$%d.%02d\n", salePrice1/100, salePrice1%100)
var salePrice2 int64 = ((st*n)*10/d + 5) / 10 // round half up
fmt.Printf("%[1]T:%[1]v\n", salePrice2)
fmt.Printf("$%d.%02d\n", salePrice2/100, salePrice2%100)
var salePrice3 int64 = (st*n + (d - 1)) / d // round up
fmt.Printf("%[1]T:%[1]v\n", salePrice1)
fmt.Printf("$%d.%02d\n", salePrice3/100, salePrice3%100)
}
Playground: https://play.golang.org/p/HbqVJUXXR-N
Output:
int64:198000
$1980.00
1, 11
int64:18000
$180.00
int64:18000
$180.00
int64:18000
$180.00
References:
What Every Computer Scientist Should Know About Floating-Point Arithmetic
How should we calc money (decimal, big.Float)
General Decimal Arithmetic
Try this:
st := 1980.0
f := 0.1 / 1.1
salePrice1 := st * f
salePrice2 := math.Floor(salePrice1)
fmt.Println(salePrice2) // 180
It is a big topic:
For accounting systems: the answer is Floating point error mitigation.
(Note: one mitigation technique is to use int64, uint64, or big.Int)
And see:
What Every Computer Scientist Should Know About Floating-Point Arithmetic
https://en.wikipedia.org/wiki/Double-precision_floating-point_format
https://en.wikipedia.org/wiki/IEEE_floating_point
Let's start with:
fmt.Println(1.0 / 3.0) // 0.3333333333333333
IEEE 754 binary representation:
fmt.Printf("%#X\n", math.Float64bits(1.0/3.0)) // 0X3FD5555555555555
IEEE 754 binary representation of 1.1:
fmt.Printf("%#X\n", math.Float64bits(1.1)) // 0X3FF199999999999A
fmt.Printf("%#X\n", math.Float64bits(st*0.1/1.1)) // 0X40667FFFFFFFFFFF
Now, let:
st := 1980.0
f := 0.1 / 1.1
IEEE 754 binary representation of f is:
fmt.Printf("%#X\n", math.Float64bits(f)) // 0X3FB745D1745D1746
And:
salePrice1 := st * f
fmt.Println(salePrice1) // 180
fmt.Printf("%#X\n", math.Float64bits(salePrice1)) // 0X4066800000000000
salePrice2 := math.Floor(salePrice1)
fmt.Printf("%#X\n", math.Float64bits(salePrice2)) // 0X4066800000000000
Working with the floating-point numbers on the computer is not same as with pen and paper (Floating-point calculation errors):
var st float64 = 1980
var salePrice1 = st * 0.1 / 1.1
fmt.Println(salePrice1) // 179.99999999999997
salePrice1 is 179.99999999999997 not 180.0 so integer value less than or equal to 179.99999999999997 is 179:
See documents for func Floor(x float64) float64:
Floor returns the greatest integer value less than or equal to x.
See:
fmt.Println(math.Floor(179.999)) // 179
fmt.Println(math.Floor(179.5 + 0.5)) // 180
fmt.Println(math.Floor(179.999 + 0.5)) // 180
fmt.Println(math.Floor(180.0)) // 180
Some relevant QAs:
Golang floating point precision float32 vs float64
How to change a float64 number to uint64 in a right way?
Golang converting float64 to int error
Is floating point math broken?
Go float comparison
What does "%b" do in fmt.Printf for float64 and what is Min subnormal positive double in float64 in binary format?
Is there any standard library to convert float64 to string with fix width with maximum number of significant digits?
fmt.Printf with width and precision fields in %g behaves unexpectedly
Why is there a difference between floating-point multiplication with literals vs. variables in Go?
Golang Round to Nearest 0.05
I use the following code in my test:
package main
import "fmt"
import "math/big"
func main() {
input := "3333333333333333333.......tested with 100'000x3 , tested with 1'000'0000x3, tested with 10'000'000x3"
bi := big.NewInt(0)
if _, ok := bi.SetString(input, 10); ok {
fmt.Printf("number = %v\n", bi)
testval := new(big.Int)
testval.SetString("3", 10)
resultat, isGanzzahl := myDiv(bi, testval)
fmt.Printf("isGanzzahl = %v, resultat = %v\n", isGanzzahl, resultat)
} else {
fmt.Printf("error parsing line %#v\n", input)
}
}
func myDiv(minuend *big.Int, subtrahend *big.Int) (*big.Int, bool) {
zerotest := big.NewInt(0)
modulus := new(big.Int)
modulus = modulus.Mod(minuend, subtrahend)
if zerotest.Cmp(modulus) == 0 {
res := big.NewInt(0)
res.Quo(minuend, subtrahend)
return res, true
} else {
return big.NewInt(0), false
}
}
100'000 x 3 / 3 == not even a quater second
1'000'000 x 3 / 3 == 9.45 seconds
10'000'000 x 3 / 3 == 16.1 minute
Im looking for a way to make this happens much much faster. If i would like to do this multithreaded in go how do i do this with go-routines? Is there a faster way to do a division with larger numbers?
As this is just for testing i planned to use Numbers in the range of 100'000'000 - 1'000'000'000 digits (which would then be 1GB of ram usage). But 1 billion digits would not work because it would take years to complete.
What would then happen if it is N / M ? Where N=1billion digit, M=10million digit. Is this even possible on a powerful home computer?
How would it look / or what do i have to change to being able to distribute this work to multiple small computer (for example AWS)?
If your number is more than 100000 digits long, you need to use Fast Fourier Transform for multiplication and division: https://en.wikipedia.org/wiki/Multiplication_algorithm#Fourier_transform_methods . The basic idea is to treat numbers as polynomials with x being power of 10 (or power of 2 if you want binary system). Multiply polynomials using Fast Fourier Transform and then propagate carry to get a number from a polynomial. I.e. if we need to multiply 19 by 19 and we use x = 101, we will have (1 * x + 9) * (1 * x + 9) = x2 + 18 * x + 81. Now we propagate carry to convert polynomial back to number: x2 + 18 * x + 81 = x2 + (18 + 8) * x + 1 = x2 + 26 * x + 1 = (1 + 2) * x2 + 6 * x + 1 = 3 * x2 + 6 * x + 1 = 361. The trick is that polynomials can be multiplied efficiently (O(N*log(N) time) using Fast Fourier Transform. The coefficients of the product polynomial are larger than digits, so you need to choose x carefully in order to avoid integer overflow or precision problems.
There unlikely to be a golang library for that so you will need to write it yourself. Here are a few short FFT implementations you can use as a starting point:
http://codeforces.com/contest/632/submission/16449753 http://codeforces.com/contest/632/submission/16445979 http://codeforces.com/contest/632/submission/16449040
http://codeforces.com/contest/632/submission/16448169
If you decide to use FFT modulo prime, see this post for a good choice of the modulo: http://petr-mitrichev.blogspot.com/2015/04/this-week-in-competitive-programming.html
I'm doing the Go tutorials and am wondering whether there is a more elegant way to compute a square root using Newton's method on Exercise: Loops and Functions than this:
func Sqrt(x float64) float64 {
count := 0
var old_z, z float64 = 0, 1
for ; math.Abs(z-old_z) > .001; count++ {
old_z, z = z, z - (z*z - x) / 2*z
}
fmt.Printf("Ran %v iterations\n", count)
return z
}
(Part of the specification is to provide the number of iterations.) Here is the full program, including package statement, imports, and main.
First, you algorithm is not correct. The formula is:
You modelled this with:
z - (z*z - x) / 2*z
But it should be:
z - (z*z - x)/2/z
Or
z - (z*z - x)/(2*z)
(Your incorrect formula had to run like half a million iterations even to just get as close as 0.001! The correct formula uses like 4 iterations to get as close as 1e-6 in case of x = 2.)
Next, initial value of z=1 is not the best for a random number (it might work well for a small number like 2). You can kick off with z = x / 2 which is a very simple initial value and takes you closer to the result with fewer steps.
Further options which do not necessarily make it more readable or elegant, it's subjective:
You can name the result to z so the return statement can be "bare". Also you can create a loop variable to count the iterations if you move the current "exit" condition into the loop which if met you print the iterations count and can simply return. You can also move the calculation to the initialization part of the if:
func Sqrt(x float64) (z float64) {
z = x / 2
for i, old := 1, 0.0; ; i++ {
if old, z = z, z-(z*z-x)/2/z; math.Abs(old-z) < 1e-5 {
fmt.Printf("Ran %v iterations\n", i)
return
}
}
}
You can also move the z = x / 2 to the initialization part of the for but then you can't have named result (else a local variant of z would be created which would shadow the named return value):
func Sqrt(x float64) float64 {
for i, z, old := 1, x/2, 0.0; ; i++ {
if old, z = z, z-(z*z-x)/2/z; math.Abs(old-z) < 1e-5 {
fmt.Printf("Ran %v iterations\n", i)
return z
}
}
}
Note: I started my iteration counter with 1 because the "exit" condition in my case is inside the for and is not the condition of for.
package main
import (
"fmt"
"math"
)
func Sqrt(x float64) float64 {
z := 1.0
// First guess
z -= (z*z - x) / (2*z)
// Iterate until change is very small
for zNew, delta := z, z; delta > 0.00000001; z = zNew {
zNew -= (zNew * zNew - x) / (2 * zNew)
delta = z - zNew
}
return z
}
func main() {
fmt.Println(Sqrt(2))
fmt.Println(math.Sqrt(2))
}
I have three numbers x, y , z.
For a range between numbers x and y.
How can i find the total numbers whose % with z is 0 i.e. how many numbers between x and y are divisible by z ?
It can be done in O(1): find the first one, find the last one, find the count of all other.
I'm assuming the range is inclusive. If your ranges are exclusive, adjust the bounds by one:
find the first value after x that is divisible by z. You can discard x:
x_mod = x % z;
if(x_mod != 0)
x += (z - x_mod);
find the last value before y that is divisible by y. You can discard y:
y -= y % z;
find the size of this range:
if(x > y)
return 0;
else
return (y - x) / z + 1;
If mathematical floor and ceil functions are available, the first two parts can be written more readably. Also the last part can be compressed using math functions:
x = ceil (x, z);
y = floor (y, z);
return max((y - x) / z + 1, 0);
if the input is guaranteed to be a valid range (x >= y), the last test or max is unneccessary:
x = ceil (x, z);
y = floor (y, z);
return (y - x) / z + 1;
(2017, answer rewritten thanks to comments)
The number of multiples of z in a number n is simply n / z
/ being the integer division, meaning decimals that could result from the division are simply ignored (for instance 17/5 => 3 and not 3.4).
Now, in a range from x to y, how many multiples of z are there?
Let see how many multiples m we have up to y
0----------------------------------x------------------------y
-m---m---m---m---m---m---m---m---m---m---m---m---m---m---m---
You see where I'm going... to get the number of multiples in the range [ x, y ], get the number of multiples of y then subtract the number of multiples before x, (x-1) / z
Solution: ( y / z ) - (( x - 1 ) / z )
Programmatically, you could make a function numberOfMultiples
function numberOfMultiples(n, z) {
return n / z;
}
to get the number of multiples in a range [x, y]
numberOfMultiples(y) - numberOfMultiples(x-1)
The function is O(1), there is no need of a loop to get the number of multiples.
Examples of results you should find
[30, 90] ÷ 13 => 4
[1, 1000] ÷ 6 => 166
[100, 1000000] ÷ 7 => 142843
[777, 777777777] ÷ 7 => 111111001
For the first example, 90 / 13 = 6, (30-1) / 13 = 2, and 6-2 = 4
---26---39---52---65---78---91--
^ ^
30<---(4 multiples)-->90
I also encountered this on Codility. It took me much longer than I'd like to admit to come up with a good solution, so I figured I would share what I think is an elegant solution!
Straightforward Approach 1/2:
O(N) time solution with a loop and counter, unrealistic when N = 2 billion.
Awesome Approach 3:
We want the number of digits in some range that are divisible by K.
Simple case: assume range [0 .. n*K], N = n*K
N/K represents the number of digits in [0,N) that are divisible by K, given N%K = 0 (aka. N is divisible by K)
ex. N = 9, K = 3, Num digits = |{0 3 6}| = 3 = 9/3
Similarly,
N/K + 1 represents the number of digits in [0,N] divisible by K
ex. N = 9, K = 3, Num digits = |{0 3 6 9}| = 4 = 9/3 + 1
I think really understanding the above fact is the trickiest part of this question, I cannot explain exactly why it works.
The rest boils down to prefix sums and handling special cases.
Now we don't always have a range that begins with 0, and we cannot assume the two bounds will be divisible by K.
But wait! We can fix this by calculating our own nice upper and lower bounds and using some subtraction magic :)
First find the closest upper and lower in the range [A,B] that are divisible by K.
Upper bound (easier): ex. B = 10, K = 3, new_B = 9... the pattern is B - B%K
Lower bound: ex. A = 10, K = 3, new_A = 12... try a few more and you will see the pattern is A - A%K + K
Then calculate the following using the above technique:
Determine the total number of digits X between [0,B] that are divisible by K
Determine the total number of digits Y between [0,A) that are divisible by K
Calculate the number of digits between [A,B] that are divisible by K in constant time by the expression X - Y
Website: https://codility.com/demo/take-sample-test/count_div/
class CountDiv {
public int solution(int A, int B, int K) {
int firstDivisible = A%K == 0 ? A : A + (K - A%K);
int lastDivisible = B%K == 0 ? B : B - B%K; //B/K behaves this way by default.
return (lastDivisible - firstDivisible)/K + 1;
}
}
This is my first time explaining an approach like this. Feedback is very much appreciated :)
This is one of the Codility Lesson 3 questions. For this question, the input is guaranteed to be in a valid range. I answered it using Javascript:
function solution(x, y, z) {
var totalDivisibles = Math.floor(y / z),
excludeDivisibles = Math.floor((x - 1) / z),
divisiblesInArray = totalDivisibles - excludeDivisibles;
return divisiblesInArray;
}
https://codility.com/demo/results/demoQX3MJC-8AP/
(I actually wanted to ask about some of the other comments on this page but I don't have enough rep points yet).
Divide y-x by z, rounding down. Add one if y%z < x%z or if x%z == 0.
No mathematical proof, unless someone cares to provide one, but test cases, in Perl:
#!perl
use strict;
use warnings;
use Test::More;
sub multiples_in_range {
my ($x, $y, $z) = #_;
return 0 if $x > $y;
my $ret = int( ($y - $x) / $z);
$ret++ if $y%$z < $x%$z or $x%$z == 0;
return $ret;
}
for my $z (2 .. 10) {
for my $x (0 .. 2*$z) {
for my $y (0 .. 4*$z) {
is multiples_in_range($x, $y, $z),
scalar(grep { $_ % $z == 0 } $x..$y),
"[$x..$y] mod $z";
}
}
}
done_testing;
Output:
$ prove divrange.pl
divrange.pl .. ok
All tests successful.
Files=1, Tests=3405, 0 wallclock secs ( 0.20 usr 0.02 sys + 0.26 cusr 0.01 csys = 0.49 CPU)
Result: PASS
Let [A;B] be an interval of positive integers including A and B such that 0 <= A <= B, K be the divisor.
It is easy to see that there are N(A) = ⌊A / K⌋ = floor(A / K) factors of K in interval [0;A]:
1K 2K 3K 4K 5K
●········x········x··●·····x········x········x···>
0 A
Similarly, there are N(B) = ⌊B / K⌋ = floor(B / K) factors of K in interval [0;B]:
1K 2K 3K 4K 5K
●········x········x········x········x···●····x···>
0 B
Then N = N(B) - N(A) equals to the number of K's (the number of integers divisible by K) in range (A;B]. The point A is not included, because the subtracted N(A) includes this point. Therefore, the result should be incremented by one, if A mod K is zero:
N := N(B) - N(A)
if (A mod K = 0)
N := N + 1
Implementation in PHP
function solution($A, $B, $K) {
if ($K < 1)
return 0;
$c = floor($B / $K) - floor($A / $K);
if ($A % $K == 0)
$c++;
return (int)$c;
}
In PHP, the effect of the floor function can be achieved by casting to the integer type:
$c = (int)($B / $K) - (int)($A / $K);
which, I think, is faster.
Here is my short and simple solution in C++ which got 100/100 on codility. :)
Runs in O(1) time. I hope its not difficult to understand.
int solution(int A, int B, int K) {
// write your code in C++11
int cnt=0;
if( A%K==0 or B%K==0)
cnt++;
if(A>=K)
cnt+= (B - A)/K;
else
cnt+=B/K;
return cnt;
}
(floor)(high/d) - (floor)(low/d) - (high%d==0)
Explanation:
There are a/d numbers divisible by d from 0.0 to a. (d!=0)
Therefore (floor)(high/d) - (floor)(low/d) will give numbers divisible in the range (low,high] (Note that low is excluded and high is included in this range)
Now to remove high from the range just subtract (high%d==0)
Works for integers, floats or whatever (Use fmodf function for floats)
Won't strive for an o(1) solution, this leave for more clever person:) Just feel this is a perfect usage scenario for function programming. Simple and straightforward.
> x,y,z=1,1000,6
=> [1, 1000, 6]
> (x..y).select {|n| n%z==0}.size
=> 166
EDIT: after reading other's O(1) solution. I feel shamed. Programming made people lazy to think...
Division (a/b=c) by definition - taking a set of size a and forming groups of size b. The number of groups of this size that can be formed, c, is the quotient of a and b. - is nothing more than the number of integers within range/interval ]0..a] (not including zero, but including a) that are divisible by b.
so by definition:
Y/Z - number of integers within ]0..Y] that are divisible by Z
and
X/Z - number of integers within ]0..X] that are divisible by Z
thus:
result = [Y/Z] - [X/Z] + x (where x = 1 if and only if X is divisible by Y otherwise 0 - assuming the given range [X..Y] includes X)
example :
for (6, 12, 2) we have 12/2 - 6/2 + 1 (as 6%2 == 0) = 6 - 3 + 1 = 4 // {6, 8, 10, 12}
for (5, 12, 2) we have 12/2 - 5/2 + 0 (as 5%2 != 0) = 6 - 2 + 0 = 4 // {6, 8, 10, 12}
The time complexity of the solution will be linear.
Code Snippet :
int countDiv(int a, int b, int m)
{
int mod = (min(a, b)%m==0);
int cnt = abs(floor(b/m) - floor(a/m)) + mod;
return cnt;
}
here n will give you count of number and will print sum of all numbers that are divisible by k
int a = sc.nextInt();
int b = sc.nextInt();
int k = sc.nextInt();
int first = 0;
if (a > k) {
first = a + a/k;
} else {
first = k;
}
int last = b - b%k;
if (first > last) {
System.out.println(0);
} else {
int n = (last - first)/k+1;
System.out.println(n * (first + last)/2);
}
Here is the solution to the problem written in Swift Programming Language.
Step 1: Find the first number in the range divisible by z.
Step 2: Find the last number in the range divisible by z.
Step 3: Use a mathematical formula to find the number of divisible numbers by z in the range.
func solution(_ x : Int, _ y : Int, _ z : Int) -> Int {
var numberOfDivisible = 0
var firstNumber: Int
var lastNumber: Int
if y == x {
return x % z == 0 ? 1 : 0
}
//Find first number divisible by z
let moduloX = x % z
if moduloX == 0 {
firstNumber = x
} else {
firstNumber = x + (z - moduloX)
}
//Fist last number divisible by z
let moduloY = y % z
if moduloY == 0 {
lastNumber = y
} else {
lastNumber = y - moduloY
}
//Math formula
numberOfDivisible = Int(floor(Double((lastNumber - firstNumber) / z))) + 1
return numberOfDivisible
}
public static int Solution(int A, int B, int K)
{
int count = 0;
//If A is divisible by K
if(A % K == 0)
{
count = (B / K) - (A / K) + 1;
}
//If A is not divisible by K
else if(A % K != 0)
{
count = (B / K) - (A / K);
}
return count;
}
This can be done in O(1).
Here you are a solution in C++.
auto first{ x % z == 0 ? x : x + z - x % z };
auto last{ y % z == 0 ? y : y - y % z };
auto ans{ (last - first) / z + 1 };
Where first is the first number that ∈ [x; y] and is divisible by z, last is the last number that ∈ [x; y] and is divisible by z and ans is the answer that you are looking for.