Andy, Richard, Thank you for the feedback. In the graph I have the 2 values as xsd:float so this is how the data is coming
In the SPAQL query I tried to cast the float to decimal by using FILTER (xsd:decimal(?value1)!=xsd:decimal(?value1)). I am not sure if this is correct way, but I am now seeing a difference in the comparison result 0.1001244561 Is different from 0.1001234590 which is OK But these are reported as same 100123456.1 and 100123459.0 If I get the value before the comparison is executed the xsd:decimal of the two values appears to be the same 100123456.0 so this is why != does not reports the difference. Here the decimal does not seem to help, but I guess this falls in the same category that large absolute values are less precise. So same effect as for xsd:float. Best regards Chavdar -----Original Message----- From: Andy Seaborne <[email protected]> Sent: Tuesday, 18 August, 2020 19:07 To: [email protected] Subject: Re: Float comparison On 18/08/2020 10:31, Richard Cyganiak wrote: > The xsd:float datatype represents IEEE 754 single-precision floating point > numbers. > > As with any floating-point datatype, the precision depends on the size of the > number. Numbers close to zero are very precise. Numbers with a large absolute > value (large positive or large negative) are less precise. For the gory > details see for example here: > > https://en.wikipedia.org/wiki/Single-precision_floating-point_format#P > recision_limitations_on_decimal_values_in_[1,_16777216] > > There is rarely a good reason to use xsd:float in RDF. xsd:double is much > more precise at a small increase of storage cost (4 more bytes, which is > negligible given the total size of an RDF triple). xsd:decimal provides > arbitrary precision (in theory), but is more expensive in storage and > computation. > > My general view is that if storage size and performance of mathematical > computations are a major concern for the application, RDF is probably not the > best choice—RDF optimises for other concerns. Therefore the best choice for > representing non-integer numbers in RDF is usually xsd:decimal—more > expensive, but no issues with precision. > > Richard xsd:decimal can record any decimal precision but division may loose precision - otherwise "1/3" is infinite storage. Jena uses 24 digit precision for division for inexact results like 1/3. > > >> On 18 Aug 2020, at 05:48, Dr. Chavdar Ivanov <[email protected]> wrote: >> >> Hello >> >> >> >> I posted the message below to the TopBraid users mailing list and >> already clarified that as sh:equals is based on RDF node equality, >> values such as "1.0"^^xsd:float and "1"^^xsd:float count as distinct. >> So I am keeping this for the interest of others in the list SPARQL has both comparisons. The "sameTerm()" operator for RDF termequality, and SPARQL "=" for value comparison (by op:numeric-equal): Andy >> >> >> >> But on SPARQL float comparison I got an advise to check in this mailing list >> for other opinions. >> >> I understand that SPARQL comparison is mathematically based so 1.0 should be >> equal to 1. However below in item 2 you will see the numbers I compared and >> I am getting confused. Take into account that in the data graph the 2 >> compared properties are typed literals with datatype float. >> >> I wanted to know what is the precision when float is compared. So I >> have 2 questions >> >> * What is the precision? - is it 6th decimal and is it OK to compare >> different forms of float, i.e. one is in scientific form >> * Why I am getting wrong comparison result for bigger values such as >> 100123456.1 and 100123459 which are found as same >> >> >> >> Best regards >> >> Chavdar >> >> >> >> >> >> ======== >> >> >> >> >> >> Dear all, >> >> >> >> I have a very basic question... >> >> I need to compare literals that are floats and tried to use two ways. >> 1) using sh:equals to compare 2 properties and 2) using SPARQL where >> I filter != different values >> >> >> >> For the filter I tried using >> >> FILTER (xsd:float(?value1)!=xsd:float(?value1)). >> >> or >> >> FILTER (?value1!=?value1). >> >> Both give the same outcome. >> >> >> >> Below I listed a summary of the tests I did >> >> >> >> I think sh:equals treats the literals as strings even though they are >> floats. It also gives 2 results. I thing this looks like according to the >> SHACL spec although I didn't if the sh:equals ignores the datatype. >> >> >> >> However In some cases the result form the SPARQL is kind of strange. It >> looks like the precision is 10-6, but for the big numbers and when >> scientific form on float number is used we have something different. >> >> >> >> What is followed to define the difference? >> >> If I use google calculator >> >> 100123456.1-100.123459E+06=-2.90000000596 >> >> >> >> Normally it should be OK to compare different forms of float. >> >> >> >> >> >> 1) using sh:equals in the property shape >> >> Value1 ; value 2 ; comparisson result >> >> 1.123456 ; 1.123456 ; same >> >> 1.1234560 ; 1.1234561 ; different (sh:equals reports it twice) >> >> 31.1234560 ; 31.1234561 ;different (sh:equals reports it twice) >> >> 30 ; 30.0000001 ; different (sh:equals reports it twice) >> >> 30 ; 30.000001 ; different (sh:equals reports it twice) >> >> 100123456.0 ; 100123456.1 ; different (sh:equals reports it twice) >> >> 100123456.0 ; 100123456.0 ; same >> >> 100123456 ; 100.123456E6 ; different (sh:equals reports it twice) >> >> 100123456 ; 100.123456E+06 ; different (sh:equals reports it twice) >> >> -0.123456789 ; -123.456789E-3 ; different (sh:equals reports it >> twice) >> >> -0.123456789 ; -123.456789E-03 ; different (sh:equals reports it >> twice) >> >> 100123456.1 ; 100.123456E+06 ; different (sh:equals reports it twice) >> >> 100123456.1 ; 100.123459E+06 ; different (sh:equals reports it twice) >> >> 100123456.1 ; 100123459 ; different (sh:equals reports it twice) >> >> 100123456.1 ; 100123459.0 ; different (sh:equals reports it twice) >> >> >> >> 2) using SPARQL (in the property shape) >> >> 1.123456 ; 1.123456 ; same >> >> 1.1234560 ; 1.1234561 ; different >> >> 31.1234560 ; 31.1234561 ;different >> >> 30 ; 30.0000001 ; same >> >> 30 ; 30.000001 ; different >> >> 100123456.0 ; 100123456.1 ; same >> >> 100123456.0 ; 100123456.0 ; same >> >> 100123456 ; 100.123456E6 ; same >> >> 100123456 ; 100.123456E+06 ; same >> >> -0.123456789 ; -123.456789E-3 ; same >> >> -0.123456789 ; -123.456789E-03 ; same >> >> 100123456.1 ; 100.123456E+06 ; same >> >> 100123456.1 ; 100.123459E+06 ; same >> >> 100123456.1 ; 100123459 ; same >> >> 100123456.1 ; 100123459.0 ; same >> >> >> >> Best regards >> >> Chavdar >> >> >> >
