cwhmisc (version 6.0)

functions: Functions for testing and other

Description

Functions for testing on equality, exactly or with a tolerance, functions usable as parameters in other functions.

Usage

inrange(x,r)
mod( m, n  )
modS( m, n )
modR( x, y )
one ( x )
zero ( x )
onebyx( x )
sqr( x )
powr( a, x )
equal( x, y )
equalFuzzy( x, y, prec=8*.Machine$double.eps, rel=TRUE )
quotmean(x,y)
safeDiv( num, den )
solveQeq(a,b,c)
chsvd(s)
divmod(x,y)
submod(x, v)
dsm( x, w )
chsvd(s)

Arguments

m,n,num,den

Integer

a,b,c,prec,x,y

Real

r

Real vactor

rel

Boolean

s

square matrix, result of svd

v

real vector > 0, preferably cumsum of some other positive vector

w

real vector > 0

Details

mod = m%%n modS : modulo symmetric to 0. modR: modulo for reals, towards negative infinity. zero returns 0.0 on any argument one returns 1.0 on any argument onebyx = 1.0/x sqr = x^2 powr = a^x, with 0^0 := 1, 0^x := 0 equal x == y equalFuzzy One can choose between relative and absolute precision safeDiv Compute quotient, set 0/0 -> 1, and safeguard r/0 <- c3Q otherwise quotmean Compute quotient of means of non-NA elements of x by y solveQeq Solve the quadratic equation given by the coefficients, return two solutions if a != 0, else one solution, possibly NA inrange Check if x is in the range r chsvd Check for svd to reproduce matrix divmod div, mod combined for ease of use submod analog to divmod for unequally spaced data dsm combination of divmod and submod, used in Date

Examples

mod((-3:5),4 ) # 1 2 3 0 1 2 3 0 1
modS((-3:5),4) # -3 -2 -1  0  1  2  3  0  1
x <- 200; y <- x + 0.1
equalFuzzy(x,y,0.1*c(10^(-3:0))) # FALSE  TRUE  TRUE  TRUE
equalFuzzy(x,y,0.1*c(10^(-3:0)),FALSE) # FALSE FALSE FALSE  TRUE
safeDiv(0:3,c(0,0:2)) # 1.552518e+231
solveQeq(0,0,1) # NA NA
solveQeq(0,1,0) # 0
solveQeq(0,1,1) # -1
solveQeq(1,0,0) #  0 0
solveQeq(1,0,1) # 0-1i 0+1i
solveQeq(1,1,0) #  -1  0
solveQeq(1,1,1) #  -0.5-0.866025i  -0.5+0.866025i
solveQeq(sample(1:4,1),sample(1:4,1),sample(1:4,1))
  x <- matrix(rnorm(9),3,3)
  s <- svd(x)
  lV(s$d)
  norm(chsvd(s) - x) # 9.4368957e-16
submod(8.1,c(10.3, 31) )  # 0.0 8.1
submod(18.1,c(10.3, 31) )  # 1.0 7.8