Why is Decimal.ulp greater than any decimal value itself?

Trying to find the number of decimals in a decimal number, I tried this in a REPL:

 39> Decimal(0.01) > Decimal(1.0) 
$R28: Bool = false
 40> Decimal(0.01).ulp
$R29: Decimal = 0.010000
 41> Decimal(0.01).ulp > Decimal(1.0)
$R30: Bool = true

This doesn't seem to work as expected. In fact, the ulp of even a small Decimal number, or a number with many decimal places, will still be larger than a very large Decimal number with no decimal places:

 105> Decimal(string: "1.01")!.ulp > Decimal(string: "123456789123456789")! 
$R73: Bool = true

According to the documentation, the ulp of Decimal is

The unit in the last place of the decimal.

and the ulp of eg Double is

The unit in the last place of this value.

Some more examples of Decimal's ulp:

value ulp
0.0001234567 0.0000000001
0.001234567 0.000000001
0.01234567 0.00000001
0.1234567 0.0000001
1.234567 0.000001
12.34567 0.00001
123.4567 0.0001
1234.567 0.001
12345.67 0.01
123456.7 0.1
1234567 1
12345670 10
123456700 100

Note that eg:

  var x = Decimal(0.999)
  print(x, x.ulp) // 0.999 0.001
  x = x.nextUp
  print(x, x.ulp) // 1 1

while for eg Double (due to the difference in data format):

  var x = Double(0.999)
  print(x, x.ulp) // 0.999 1.1102230246251565e-16
  x = x.nextUp
  print(x, x.ulp) // 0.9990000000000001 1.1102230246251565e-16

Also note that for Double the printed decimal values above (eg 0.999) are not the exact Double values (they are kind of rounded to the decimal representation with as few decimal digits as possible while still being closer to the actual Double value than to any other Double value, or something like that).


I'm not sure what you mean by

the number of decimals in a decimal number

but if it is the number of digits in the fractional part then beware of things like:

  let x = Decimal(1.234)
  print(x) // 1.234
  let y = x.nextUp
  print(y) // 1.235
  let z = Decimal(1.235)
  print(z) // 1.2350000000000002048
  print(y == z) // false (because the literal `1.235` is a Double in Swift)
  let w = Decimal.init(string: "1.235", locale: Locale.init(identifier: "us"))!
  print(w) // 1.235
  print(y == w) // true

I does look like a bug that Double(0.1).ulp, which should be 0.1 (and prints 0.1), ends up compare greater than Double(1.0). Moreover, things like nextUp.nextDown* fixes that:

import Foundation
let a = Decimal(0.1).ulp, b = Decimal(1.0)

// ???
print(a > b) // true
// OK
print(a.nextUp.nextDown > b) // false

* Ok, that may not recover the original value for some numbers, but most definitely would for Decimal(0.1).

Isn’t this just a consequence of literals being interpreted as Double values in Swift? Ie, Decimal(0.1) is not 0.1, because the 0.1 literal will first be converted to a Double value, which is close to but not exactly 0.1.

I don't think so. I included a string literal-initialised example at the end of my original post as well:

Besides, the rounding errors would not be off by several magnitudes and would rather tend toward a smaller ulp than a larger one.

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Even with rounding, give or take, it most definitely shouldn't be greater than 100 milllion:

Decimal(0.1).ulp > 100_000_000 // true
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Ah, yes, that's most definitely a bug, I missed the > - strangeness (which is not only in the REPL, but also in eg Xcode 12.5.1).

Another example program whose behavior doesn't make sense, but might give a clue about what's going wrong (I have no idea what that _length property is, only that it's different in the value it gets from ulp, and seems to cause unexpected behavior):

let a = Decimal.zero.nextUp
let b = a.ulp
print(a, a._length) // 1 1
print(b, b._length) // 1 8
print(a == b) // false
let x = a.nextDown.nextUp
let y = b.nextDown.nextUp
print(x, x._length) // 1 1
print(y, y._length) // 1 1
print(x == y) // true

It's more than one bug, but the immediate problem can be addressed fairly straightforwardly:

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I would love to have a good equivalent of Builtin.IntLiteral that we could use for floating-point literals and that would persist the exact original value. I suspect that for efficiency it would always need to include a binary floating-point value. There are a lot of corner cases of expressibility, though, which is why we haven't taken it on yet.

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