Mathematical precision at 19th decimal place and beyond

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I have the same set of data and am running the same code, but sometimes I get different results at the 19th decimal place and beyond. Although this is not a great concern to me for numbers less than 0.0001, it makes me wonder whether 19th decimal place is Raku's limit of precision?

     Word 104 differ: 
             0.04948872986571077     19 chars 
             0.04948872986571079     19 chars
     Word 105 differ: 
             0.004052062278212545    20 chars 
             0.0040520622782125445   21 chars
precision math raku
1 Answers

TL;DR See the doc's outstanding Numerics page.

(I had forgotten about that page before I wrote the following answer. Consider this answer at best a brief summary of a few aspects of that page.)

There are two aspects to this. Internal precision and printing precision.

100% internal precision until RAM is exhausted

Raku supports arbitrary precision number types. Quoting Wikipedia's relevant page:

digits of precision are limited only by the available memory of the host system

You can direct Raku to use one of its arbitrary precision types.[1] If you do so it will retain 100% precision until it runs out of RAM.

Arbitrary precision type Corresponding type checking[2] Example of value of that type
Int my Int $foo ... 66174449004242214902112876935633591964790957800362273
FatRat my FatRat $foo ... 66174449004242214902112876935633591964790957800362273 / 13234889800848443102075932929798260216894990083844716

Thus you can get arbitrary internal precision for integers and fractions (including arbitrary precision decimals).

Limited internal precision

If you do not direct Raku to use an arbitrary precision number type it will do its best but may ultimately switch to limited precision. For example, Raku will give up on 100% precision if a formula you use calculates a Rat and the number's denominator exceeds 64 bits.[1]

Raku's fall back limited precision number type is Num:

On most platforms, [a Num is] an IEEE 754 64-bit floating point numbers, aka "double precision".

Quoting the Wikipedia page for that standard:

Floating point is used ... when a wider range is needed ... even if at the cost of precision.

The 53-bit significand precision gives from 15 to 17 significant decimal digits precision (2−53 ≈ 1.11 × 10−16).

Printing precision

Separate from internal precision is stringification of numbers.

(It was at this stage that I remembered the doc page on Numerics linked at the start of this answer.)

Quoting Printing rationals:

Keep in mind that output routines like say or put ... may choose to display a Num as an Int or a Rat number. For a more definitive string to output, use the raku method or [for a rational number] .nude

Footnotes

[1] You control the type of a numeric expression via the types of individual numbers in the expression, and the types of the results of numeric operations, which in turn depend on the types of the numbers. Examples:

  • 1 + 2 is 3, an Int, because both 1 and 2 are Ints, and a + b is an Int if both a and b are Ints;

  • 1 / 2 is not an Int even though both 1 and 2 are individually Ints, but is instead 1/2 aka 0.5, a Rat.

  • 1 + 4 / 2 will print out as 3, but the 3 is internally a Rat, not an Int, due to Numeric infectiousness.

[2] All that enforcement does is generate a run-time error if you try to assign or bind a value that is not of the numeric type you've specified as the variable's type constraint. Enforcement doesn't mean that Raku will convert numbers for you. You have to write your formulae to ensure the result you get is what you want.[1] You can use coercion -- but coercion cannot regain precision that's already been lost.

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