mXparser - v.3.0.0 - released!

v.3.0.0 (2016-05-18): Major update: Random numbers, Probability distributions & Random variables, Double precision rounding, ULP rounding, epsilon comparison, New special functions.

.NET: since v.3.0.0 dll - different private key used for signing.

Random numbers - new functions

  • rUni(a, b) - Random number from uniform continuous distribution U(a,b)
  • rUnid(a, b) - Random number from uniform discrete distribution U{a,b}
  • rNor(m, s) - Random number from normal distribution N(m,s)
  • rList(a1, a2, ..., an) - Random number from given list of numbers

Probability distributions - new functions

  • pUni(x, a, b) - Probability distribution function - Uniform continuous distribution U(a,b)
  • cUni(x, a, b) - Cumulative distribution function - Uniform continuous distribution U(a,b)
  • qUni(q, a, b) - Quantile function (inverse cumulative distribution function) - Uniform continuous distribution U(a,b)
  • pNor(x, a, b) - Probability distribution function - Normal distribution N(m,s)
  • cNor(x, a, b) - Cumulative distribution function - Normal distribution N(m,s)
  • qNor(q, m, s) - Quantile function (inverse cumulative distribution function) - Normal distribution N(m,s)

Random variables (predefined) - acting as random constant (no parameters)

  • [Int] - Random variable - random integer
  • [Int1] - Random variable - random integer - Uniform discrete distribution U{-10^1, 10^1}
  • [Int2] - Random variable - random integer - Uniform discrete distribution U{-10^2, 10^2}
  • [Int3] - Random variable - random integer - Uniform discrete distribution U{-10^3, 10^3}
  • [Int4] - Random variable - random integer - Uniform discrete distribution U{-10^4, 10^4}
  • [Int5] - Random variable - random integer - Uniform discrete distribution U{-10^5, 10^5}
  • [Int6] - Random variable - random integer - Uniform discrete distribution U{-10^6, 10^6}
  • [Int7] - Random variable - random integer - Uniform discrete distribution U{-10^7, 10^7}
  • [Int8] - Random variable - random integer - Uniform discrete distribution U{-10^8, 10^8}
  • [Int9] - Random variable - random integer - Uniform discrete distribution U{-10^9, 10^9}
  • [nat] - Random variable - random natural number including 0
  • [nat1] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^1}
  • [nat2] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^2}
  • [nat3] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^3}
  • [nat4] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^4}
  • [nat5] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^5}
  • [nat6] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^6}
  • [nat7] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^7}
  • [nat8] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^8}
  • [nat9] - Random variable - random natural number including 0 - Uniform discrete distribution U{0, 10^9}
  • [Nat] - Random variable - random natural number
  • [Nat1] - Random variable - random natural number - Uniform discrete distribution U{1, 10^1}
  • [Nat2] - Random variable - random natural number - Uniform discrete distribution U{1, 10^2}
  • [Nat3] - Random variable - random natural number - Uniform discrete distribution U{1, 10^3}
  • [Nat4] - Random variable - random natural number - Uniform discrete distribution U{1, 10^4}
  • [Nat5] - Random variable - random natural number - Uniform discrete distribution U{1, 10^5}
  • [Nat6] - Random variable - random natural number - Uniform discrete distribution U{1, 10^6}
  • [Nat7] - Random variable - random natural number - Uniform discrete distribution U{1, 10^7}
  • [Nat8] - Random variable - random natural number - Uniform discrete distribution U{1, 10^8}
  • [Nat9] - Random variable - random natural number - Uniform discrete distribution U{1, 10^9}
  • [Nor] - Random variable - Normal distribution N(0,1)

Double precision rounding

  • round(value, places) - decimal rounding (half-up)

New special functions

  • erf(x) - Gauss error function
  • erfc(x) - Gauss complementary error function
  • erfInv(x) - Inverse Gauss error function
  • erfcInv(x) - Inverse Gauss complementary error function

Other functions

  • ulp(x) - Unit in The Last Place

Binary relations - epsilon+ulp comparison - enabled as default

If a rel b then applied epsilon is maximum from epsilon and ulp(b) : i.e. a eq b if a \in [b-eps; b+eps] inclusive

  • mXparser.setExactComparison()
  • mXparser.setEpsilonComparison()
  • mXparser.setEpsilon(double epsilon)
  • mXparser.setDefaultEpsilon()
  • mXparser.getEpsilon()
  • mXparser.checkIfEpsilonMode()
  • mXparser.checkIfExactMode()

Intelligent automatic double ULP rounding - enabled as default

** Try 0.1 + 0.1 + 0.1 - it will give exact 0.3 🙂 **

  • mXparser.enableUlpRounding()
  • mXparser.disableUlpRounding()
  • mXparser.checkIfUlpRounding()

Parser tokens definition now public in API

  • mxparser.parsertokens

Expression after tokenization now public in API

  • Expression.getCopyOfInitialTokens()
  • mxparser.parsertokens
  • mXparser.consolePrintTokens()

Significant reorganization of code

  • Mainly mathcollection & parser tokens

Backwards compatibility

  • is preserved for String API, Expression, Function, Argument, Constnat, ...
  • other public API was reorganized (mainly mxparser.mathcollection)

Bugs fixed

  • bugs related to iterated operators

Other changes

  • Many new regression tests

Enjoy 🙂

7 thoughts on “mXparser - v.3.0.0 - released!

  1. I'm not having much luck using the library via NuGet for a dnx based console project.

    The error I get is, "The dependency MathParser.org-mXparser 3.0.0 in project TestSample does not support framework DNXCore,Version=v5.0"

    Has anyone had a luck getting it to work with the new .Net stuff? I'm currently using RC1 still.

  2. I have one query mXparser - v.3.0.0.
    How can I work on traditional sum and average like
    sum(1,2,3,4,5,6,7)= 28
    avg(6,9,2,3)=5
    can you please send me sample code

    1. Hi,

      "sum" keyword is reserved for SIGMA operator (sum an for n=a to b) - the same in case of "avg". In order to perform variadic sum please use add(1,2,3,4,5,6,7). In case of variadic average you should use mean(6,9,2,3).

      Best regards

  3. Hi ,
    For large values it is not giving proper output. Is there any thing wrong from my inputs

    FYI.
    I am using like
    Expression e1 = new Expression("add(122,32312312,5434543,553112,554332432,566878545,5432433242,99876677,321313,44312132121,31213123,444112313131,441133432234)");
    mXparser.consolePrintln("Res 1: " + e1.getExpressionString() + " = " + e1.calculate());

    output :
    [mXparser-v.3.0.0] Res 1: add(122,32312312,5434543,553112,554332432,566878545,5432433242,99876677,321313,44312132121,31213123,444112313131,441133432234) = 9.36281232907E11

    1. Hi,

      Everything seems to be ok. mXparser performs calculation on double numbers. If you expect integer please do casting to int / long, or simply format the number when displaying.

      9.36281232907E11 = 936281232907

      Best regards

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