Mathematial C functions: Transformation of coordinate systems

Description

The functions provide mathematical c functions as RMmodels

Usage

RFcalc(model)
R.minus(a, b, factor)
R.plus(a, b, factor)
R.div(a, b, factor)
R.mult(a, b, factor)
R.const(a)
R.c(a, b, c, d, e, f, g, h, i, j, factor)
R.p(proj, new, factor)
R.is(a, is, b)
R.lon()
R.lat()
R.acos(a)
asin(x)
R.asin(a)
atan(x)
R.atan(a)
atan2(y, x)
R.atan2(a, b)
cos(x)
R.cos(a)
sin(x)
R.sin(a)
tan(x)
R.tan(a)
acosh(x)
R.acosh(a)
asinh(x)
R.asinh(a)
atanh(x)
R.atanh(a)
cosh(x)
R.cosh(a)
sinh(x)
R.sinh(a)
tanh(x)
R.tanh(a)
exp(x)
R.exp(a)
log(x)
R.log(a)
expm1(x)
R.expm1(a)
log1p(x)
R.log1p(a)
logb(x)
R.logb(a)
R.exp2(a)
log2(x)
R.log2(a)
R.pow(a, b)
sqrt(x)
R.sqrt(a)
R.hypot(a, b)
R.cbrt(a)
R.ceil(a)
abs(x)
R.fabs(a)
floor(x)
R.floor(a)
R.fmod(a, b)
R.nearbyint(a)
round(x, ...)
R.round(a)
trunc(x)
R.trunc(a)
R.lrint(a)
R.llrint(a)
R.lround(a)
R.llround(a)
R.copysign(a, b)
R.erf(a)
R.erfc(a)
gamma(x)
R.tgamma(a)
lgamma(x)
R.lgamma(a)
R.rint(a)
R.nextafter(a, b)
R.nexttoward(a, b)
R.remainder(a, b)
R.fdim(a, b)
max(...)
R.fmax(a, b)
min(...)
R.fmin(a, b)

Arguments

model

object of class RMmodel, in particular R.model

x,y,a, b, c, d, e, f, g, h, i, j, ...

constant or object of class RMmodel, in particular R.model

one of "==", "!=", "<="< code="">, "<"< code="">, ">=", ">"

factor

constant factor multiplied with the function. This is useful when linear models are built

proj

selection of a component of the vector giving the location. Default value is 1.

new

coordinate system or other kind of isotropy which is supposed to be present at this model. It shold always be given if the coordinates are not cartesian.

Value

Formally, the functions return an object of class RMmodel, except for RFcalc that returns a scalar. Neither vectors nor parentheses are allowed.

Details

For the remaining models see the corresponding C functions for their return value. (For any ‘R.model’ type ‘man model’ under Linux.)

Examples

Run this code

RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again

## simple calculation
RFcalc(3 + R.sin(pi/4))

## calculation performed on a field
RFfctn(R.p(1) + R.p(2), 1:3, 1:3) 
RFfctn(10 + R.p(2), 1:3, 1:3) 

## calculate the distances between two vectors
print(RFfctn(R.p(new="iso"), 1:10, 1:10))

## simulation of a non-stationary field where
## anisotropy by a transform the coordinates (x_1^2, x_2^1.5)
x <- seq(0.1, 6, 0.12)
Aniso <- R.c(R.p(1)^2, R.p(2)^1.5)
z <- RFsimulate(RMexp(Aniso=Aniso), x, x)


## calculating norms can be abbreviated:
x <- seq(-5, 5, 5) #0.1)
z2 <- RFsimulate(RMexp() + -40 + exp(0.5 * R.p(new="isotropic")), x, x)
z1 <- RFsimulate(RMexp() + -40 + exp(0.5 * sqrt(R.p(1)^2 + R.p(2)^2)), x, x)
stopifnot(all.equal(z1, z2))
plot(z1)

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