# # # Nim's Runtime Library # (c) Copyright 2015 Andreas Rumpf # # See the file "copying.txt", included in this # distribution, for details about the copyright. # ## Constructive mathematics is naturally typed. -- Simon Thompson ## ## Basic math routines for Nim. ## This module is available for the `JavaScript target ## `_. include "system/inclrtl" {.push debugger:off .} # the user does not want to trace a part # of the standard library! {.push checks:off, line_dir:off, stack_trace:off.} when defined(Posix) and not defined(haiku): {.passl: "-lm".} when not defined(js): import times const PI* = 3.1415926535897932384626433 ## the circle constant PI (Ludolph's number) E* = 2.71828182845904523536028747 ## Euler's number MaxFloat64Precision* = 16 ## maximum number of meaningful digits ## after the decimal point for Nim's ## ``float64`` type. MaxFloat32Precision* = 8 ## maximum number of meaningful digits ## after the decimal point for Nim's ## ``float32`` type. MaxFloatPrecision* = MaxFloat64Precision ## maximum number of ## meaningful digits ## after the decimal point ## for Nim's ``float`` type. type FloatClass* = enum ## describes the class a floating point value belongs to. ## This is the type that is returned by `classify`. fcNormal, ## value is an ordinary nonzero floating point value fcSubnormal, ## value is a subnormal (a very small) floating point value fcZero, ## value is zero fcNegZero, ## value is the negative zero fcNan, ## value is Not-A-Number (NAN) fcInf, ## value is positive infinity fcNegInf ## value is negative infinity proc classify*(x: float): FloatClass = ## classifies a floating point value. Returns `x`'s class as specified by ## `FloatClass`. # JavaScript and most C compilers have no classify: if x == 0.0: if 1.0/x == Inf: return fcZero else: return fcNegZero if x*0.5 == x: if x > 0.0: return fcInf else: return fcNegInf if x != x: return fcNan return fcNormal # XXX: fcSubnormal is not detected! proc binom*(n, k: int): int {.noSideEffect.} = ## computes the binomial coefficient if k <= 0: return 1 if 2*k > n: return binom(n, n-k) result = n for i in countup(2, k): result = (result * (n + 1 - i)) div i proc fac*(n: int): int {.noSideEffect.} = ## computes the faculty/factorial function. result = 1 for i in countup(2, n): result = result * i proc isPowerOfTwo*(x: int): bool {.noSideEffect.} = ## returns true, if `x` is a power of two, false otherwise. ## Zero and negative numbers are not a power of two. return (x > 0) and ((x and (x - 1)) == 0) proc nextPowerOfTwo*(x: int): int {.noSideEffect.} = ## returns `x` rounded up to the nearest power of two. ## Zero and negative numbers get rounded up to 1. result = x - 1 when defined(cpu64): result = result or (result shr 32) when sizeof(int) > 2: result = result or (result shr 16) when sizeof(int) > 1: result = result or (result shr 8) result = result or (result shr 4) result = result or (result shr 2) result = result or (result shr 1) result += 1 + ord(x<=0) proc countBits32*(n: int32): int {.noSideEffect.} = ## counts the set bits in `n`. var v = n v = v -% ((v shr 1'i32) and 0x55555555'i32) v = (v and 0x33333333'i32) +% ((v shr 2'i32) and 0x33333333'i32) result = ((v +% (v shr 4'i32) and 0xF0F0F0F'i32) *% 0x1010101'i32) shr 24'i32 proc sum*[T](x: openArray[T]): T {.noSideEffect.} = ## computes the sum of the elements in `x`. ## If `x` is empty, 0 is returned. for i in items(x): result = result + i template toFloat(f: float): float = f proc mean*[T](x: openArray[T]): float {.noSideEffect.} = ## computes the mean of the elements in `x`, which are first converted to floats. ## If `x` is empty, NaN is returned. ## ``toFloat(x: T): float`` must be defined. for i in items(x): result = result + toFloat(i) result = result / toFloat(len(x)) proc variance*[T](x: openArray[T]): float {.noSideEffect.} = ## computes the variance of the elements in `x`. ## If `x` is empty, NaN is returned. ## ``toFloat(x: T): float`` must be defined. result = 0.0 var m = mean(x) for i in items(x): var diff = toFloat(i) - m result = result + diff*diff result = result / toFloat(len(x)) proc random*(max: int): int {.benign.} ## returns a random number in the range 0..max-1. The sequence of ## random number is always the same, unless `randomize` is called ## which initializes the random number generator with a "random" ## number, i.e. a tickcount. proc random*(max: float): float {.benign.} ## returns a random number in the range 0..".} proc sqrt*(x: float64): float64 {.importc: "sqrt", header: "".} ## computes the square root of `x`. proc cbrt*(x: float32): float32 {.importc: "cbrt", header: "".} proc cbrt*(x: float64): float64 {.importc: "cbrt", header: "".} ## computes the cubic root of `x` proc ln*(x: float32): float32 {.importc: "log", header: "".} proc ln*(x: float64): float64 {.importc: "log", header: "".} ## computes ln(x). proc log10*(x: float32): float32 {.importc: "log10", header: "".} proc log10*(x: float64): float64 {.importc: "log10", header: "".} proc log2*[T: float32|float64](x: T): T = return ln(x) / ln(2.0) proc exp*(x: float32): float32 {.importc: "exp", header: "".} proc exp*(x: float64): float64 {.importc: "exp", header: "".} ## computes e**x. proc frexp*(x: float32, exponent: var int): float32 {. importc: "frexp", header: "".} proc frexp*(x: float64, exponent: var int): float64 {. importc: "frexp", header: "".} ## Split a number into mantissa and exponent. ## `frexp` calculates the mantissa m (a float greater than or equal to 0.5 ## and less than 1) and the integer value n such that `x` (the original ## float value) equals m * 2**n. frexp stores n in `exponent` and returns ## m. proc round*(x: float32): int {.importc: "lrint", header: "".} proc round*(x: float64): int {.importc: "lrint", header: "".} ## converts a float to an int by rounding. proc arccos*(x: float32): float32 {.importc: "acos", header: "".} proc arccos*(x: float64): float64 {.importc: "acos", header: "".} proc arcsin*(x: float32): float32 {.importc: "asin", header: "".} proc arcsin*(x: float64): float64 {.importc: "asin", header: "".} proc arctan*(x: float32): float32 {.importc: "atan", header: "".} proc arctan*(x: float64): float64 {.importc: "atan", header: "".} proc arctan2*(y, x: float32): float32 {.importc: "atan2", header: "".} proc arctan2*(y, x: float64): float64 {.importc: "atan2", header: "".} ## Calculate the arc tangent of `y` / `x`. ## `atan2` returns the arc tangent of `y` / `x`; it produces correct ## results even when the resulting angle is near pi/2 or -pi/2 ## (`x` near 0). proc cos*(x: float32): float32 {.importc: "cos", header: "".} proc cos*(x: float64): float64 {.importc: "cos", header: "".} proc cosh*(x: float32): float32 {.importc: "cosh", header: "".} proc cosh*(x: float64): float64 {.importc: "cosh", header: "".} proc hypot*(x, y: float32): float32 {.importc: "hypot", header: "".} proc hypot*(x, y: float64): float64 {.importc: "hypot", header: "".} ## same as ``sqrt(x*x + y*y)``. proc sinh*(x: float32): float32 {.importc: "sinh", header: "".} proc sinh*(x: float64): float64 {.importc: "sinh", header: "".} proc sin*(x: float32): float32 {.importc: "sin", header: "".} proc sin*(x: float64): float64 {.importc: "sin", header: "".} proc tan*(x: float32): float32 {.importc: "tan", header: "".} proc tan*(x: float64): float64 {.importc: "tan", header: "".} proc tanh*(x: float32): float32 {.importc: "tanh", header: "".} proc tanh*(x: float64): float64 {.importc: "tanh", header: "".} proc pow*(x, y: float32): float32 {.importc: "pow", header: "".} proc pow*(x, y: float64): float64 {.importc: "pow", header: "".} ## computes x to power raised of y. proc erf*(x: float32): float32 {.importc: "erf", header: "".} proc erf*(x: float64): float64 {.importc: "erf", header: "".} ## The error function proc erfc*(x: float32): float32 {.importc: "erfc", header: "".} proc erfc*(x: float64): float64 {.importc: "erfc", header: "".} ## The complementary error function proc lgamma*(x: float32): float32 {.importc: "lgamma", header: "".} proc lgamma*(x: float64): float64 {.importc: "lgamma", header: "".} ## Natural log of the gamma function proc tgamma*(x: float32): float32 {.importc: "tgamma", header: "".} proc tgamma*(x: float64): float64 {.importc: "tgamma", header: "".} ## The gamma function # C procs: when defined(vcc): # The "secure" random, available from Windows XP # https://msdn.microsoft.com/en-us/library/sxtz2fa8.aspx # Present in some variants of MinGW but not enough to justify # `when defined(windows)` yet proc rand_s(val: var cuint) {.importc: "rand_s", header: "".} # To behave like the normal version proc rand(): cuint = rand_s(result) else: proc srand(seed: cint) {.importc: "srand", header: "".} proc rand(): cint {.importc: "rand", header: "".} when not defined(windows): proc srand48(seed: clong) {.importc: "srand48", header: "".} proc drand48(): float {.importc: "drand48", header: "".} proc random(max: float): float = result = drand48() * max else: when defined(vcc): # Windows with Visual C proc random(max: float): float = # we are hardcoding this because # importc-ing macros is extremely problematic # and because the value is publicly documented # on MSDN and very unlikely to change # See https://msdn.microsoft.com/en-us/library/296az74e.aspx const rand_max = 4294967295 # UINT_MAX result = (float(rand()) / float(rand_max)) * max proc randomize() = discard proc randomize(seed: int) = discard else: # Windows with another compiler proc random(max: float): float = # we are hardcoding this because # importc-ing macros is extremely problematic # and because the value is publicly documented # on MSDN and very unlikely to change const rand_max = 32767 result = (float(rand()) / float(rand_max)) * max when not defined(vcc): # the above code for vcc uses `discard` instead # this is either not Windows or is Windows without vcc proc randomize() = randomize(cast[int](epochTime())) proc randomize(seed: int) = srand(cint(seed)) # rand_s doesn't use srand when declared(srand48): srand48(seed) proc random(max: int): int = result = int(rand()) mod max proc trunc*(x: float32): float32 {.importc: "trunc", header: "".} proc trunc*(x: float64): float64 {.importc: "trunc", header: "".} proc floor*(x: float32): float32 {.importc: "floor", header: "".} proc floor*(x: float64): float64 {.importc: "floor", header: "".} proc ceil*(x: float32): float32 {.importc: "ceil", header: "".} proc ceil*(x: float64): float64 {.importc: "ceil", header: "".} proc fmod*(x, y: float32): float32 {.importc: "fmod", header: "".} proc fmod*(x, y: float64): float64 {.importc: "fmod", header: "".} else: proc mathrandom(): float {.importc: "Math.random", nodecl.} proc floor*(x: float32): float32 {.importc: "Math.floor", nodecl.} proc floor*(x: float64): float64 {.importc: "Math.floor", nodecl.} proc ceil*(x: float32): float32 {.importc: "Math.ceil", nodecl.} proc ceil*(x: float64): float64 {.importc: "Math.ceil", nodecl.} proc random(max: int): int = result = int(floor(mathrandom() * float(max))) proc random(max: float): float = result = float(mathrandom() * float(max)) proc randomize() = discard proc randomize(seed: int) = discard proc sqrt*(x: float32): float32 {.importc: "Math.sqrt", nodecl.} proc sqrt*(x: float64): float64 {.importc: "Math.sqrt", nodecl.} proc ln*(x: float32): float32 {.importc: "Math.log", nodecl.} proc ln*(x: float64): float64 {.importc: "Math.log", nodecl.} proc log10*[T: float32|float64](x: T): T = return ln(x) / ln(10.0) proc log2*[T: float32|float64](x: T): T = return ln(x) / ln(2.0) proc exp*(x: float32): float32 {.importc: "Math.exp", nodecl.} proc exp*(x: float64): float64 {.importc: "Math.exp", nodecl.} proc round*(x: float): int {.importc: "Math.round", nodecl.} proc pow*(x, y: float32): float32 {.importC: "Math.pow", nodecl.} proc pow*(x, y: float64): float64 {.importc: "Math.pow", nodecl.} proc frexp*[T: float32|float64](x: T, exponent: var int): T = if x == 0.0: exponent = 0 result = 0.0 elif x < 0.0: result = -frexp(-x, exponent) else: var ex = floor(log2(x)) exponent = round(ex) result = x / pow(2.0, ex) proc arccos*(x: float32): float32 {.importc: "Math.acos", nodecl.} proc arccos*(x: float64): float64 {.importc: "Math.acos", nodecl.} proc arcsin*(x: float32): float32 {.importc: "Math.asin", nodecl.} proc arcsin*(x: float64): float64 {.importc: "Math.asin", nodecl.} proc arctan*(x: float32): float32 {.importc: "Math.atan", nodecl.} proc arctan*(x: float64): float64 {.importc: "Math.atan", nodecl.} proc arctan2*(y, x: float32): float32 {.importC: "Math.atan2", nodecl.} proc arctan2*(y, x: float64): float64 {.importc: "Math.atan2", nodecl.} proc cos*(x: float32): float32 {.importc: "Math.cos", nodecl.} proc cos*(x: float64): float64 {.importc: "Math.cos", nodecl.} proc cosh*(x: float32): float32 = return (exp(x)+exp(-x))*0.5 proc cosh*(x: float64): float64 = return (exp(x)+exp(-x))*0.5 proc hypot*[T: float32|float64](x, y: T): T = return sqrt(x*x + y*y) proc sinh*[T: float32|float64](x: T): T = return (exp(x)-exp(-x))*0.5 proc sin*(x: float32): float32 {.importc: "Math.sin", nodecl.} proc sin*(x: float64): float64 {.importc: "Math.sin", nodecl.} proc tan*(x: float32): float32 {.importc: "Math.tan", nodecl.} proc tan*(x: float64): float64 {.importc: "Math.tan", nodecl.} proc tanh*[T: float32|float64](x: T): T = var y = exp(2.0*x) return (y-1.0)/(y+1.0) {.pop.} proc `mod`*[T: float32|float64](x, y: T): T = ## Computes the modulo operation for float operators. Equivalent ## to ``x - y * floor(x/y)``. Note that the remainder will always ## have the same sign as the divisor. ## ## .. code-block:: nim ## echo (4.0 mod -3.1) # -2.2 result = if y == 0.0: x else: x - y * (x/y).floor proc random*[T](x: Slice[T]): T = ## For a slice `a .. b` returns a value in the range `a .. b-1`. result = random(x.b - x.a) + x.a proc random*[T](a: openArray[T]): T = ## returns a random element from the openarray `a`. result = a[random(a.low..a.len)] type RunningStat* = object ## an accumulator for statistical data n*: int ## number of pushed data sum*, min*, max*, mean*: float ## self-explaining oldM, oldS, newS: float {.deprecated: [TFloatClass: FloatClass, TRunningStat: RunningStat].} proc push*(s: var RunningStat, x: float) = ## pushes a value `x` for processing inc(s.n) # See Knuth TAOCP vol 2, 3rd edition, page 232 if s.n == 1: s.min = x s.max = x s.oldM = x s.mean = x s.oldS = 0.0 else: if s.min > x: s.min = x if s.max < x: s.max = x s.mean = s.oldM + (x - s.oldM)/toFloat(s.n) s.newS = s.oldS + (x - s.oldM)*(x - s.mean) # set up for next iteration: s.oldM = s.mean s.oldS = s.newS s.sum = s.sum + x proc push*(s: var RunningStat, x: int) = ## pushes a value `x` for processing. `x` is simply converted to ``float`` ## and the other push operation is called. push(s, toFloat(x)) proc variance*(s: RunningStat): float = ## computes the current variance of `s` if s.n > 1: result = s.newS / (toFloat(s.n - 1)) proc standardDeviation*(s: RunningStat): float = ## computes the current standard deviation of `s` result = sqrt(variance(s)) {.pop.} {.pop.} proc `^`*[T](x, y: T): T = ## Computes ``x`` to the power ``y`. ``x`` must be non-negative, use ## `pow <#pow,float,float>` for negative exponents. assert y >= 0 var (x, y) = (x, y) result = 1 while y != 0: if (y and 1) != 0: result *= x y = y shr 1 x *= x proc gcd*[T](x, y: T): T = ## Computes the greatest common divisor of ``x`` and ``y``. ## Note that for floats, the result cannot always be interpreted as ## "greatest decimal `z` such that ``z*N == x and z*M == y`` ## where N and M are positive integers." var (x,y) = (x,y) while y != 0: x = x mod y swap x, y abs x proc lcm*[T](x, y: T): T = ## Computes the least common multiple of ``x`` and ``y``. x div gcd(x, y) * y when isMainModule and not defined(JS): proc gettime(dummy: ptr cint): cint {.importc: "time", header: "".} # Verifies random seed initialization. let seed = gettime(nil) randomize(seed) const SIZE = 10 var buf : array[0..SIZE, int] # Fill the buffer with random values for i in 0..SIZE-1: buf[i] = random(high(int)) # Check that the second random calls are the same for each position. randomize(seed) for i in 0..SIZE-1: assert buf[i] == random(high(int)), "non deterministic random seeding" when not defined(testing): echo "random values equal after reseeding" # Check for no side effect annotation proc mySqrt(num: float): float {.noSideEffect.} = return sqrt(num) # check gamma function assert(tgamma(5.0) == 24.0) # 4! assert(lgamma(1.0) == 0.0) # ln(1.0) == 0.0 assert(erf(6.0) > erf(5.0)) assert(erfc(6.0) < erfc(5.0))