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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)
RMmodel
,
in particular R.model
RMmodel
,
in particular R.model
"=="
, "!="
, "<="< code="">, "<"< code="">, ">="
, ">"
kind of isotropy
which is supposed to be present at this model.
It shold always be given if the coordinates are not cartesian.
RMmodel
, except for
RFcalc
that returns a scalar.
Neither vectors nor parentheses are allowed.
For the remaining models see the corresponding C functions for their return value. (For any ‘R.model’ type ‘man model’ under Linux.)
RMmodel
, RFfctn
,
RMtrend
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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