This vignette discusses key differences with odin version 1.
Some of these features were present in versions of
odin.dust
and many derive from underlying support in
dust2
.
odin.dust
)constant
argument to
parameter()
)odin.dust
but expanded here)odin.dust
)vignette("debugging")
)This list is incomplete, and we’ll expand it as we work through the tests. We’re not currently quite at MVP stage yet, so expect that most things don’t work!
Things we do plan on implementing:
y_lag <- delay(y, tau)
(mrc-5434
)mrc-5575
)Things that we plan to drop in this version
config()
and options
Note that many errors are not caught as odin errors, and invalid odin code will be accepted and generate C++ code that fails to compile.
user()
becomes parameter()
This might be the largest user-visible change, and we’ll add a translation system for this.
Previously, to support parameters you might write
which says that a
is a user-supplied parameter with a
default value of 4
. In most cases this now simply
becomes
The integer
argument accepted by user
has
now changed:
user(integer = TRUE)
becomes
parameter(type = "integer")
user(integer = FALSE)
becomes
parameter(type = "real")
This translation can be done automatically in most cases, and will be done (with a warning) by default if possible. You should update your code with the suggested fix, however, as this translation will be removed in a future version.
In comparisons such as
The compare
keyword, and the ~
only occur
together. This has been simplified, and is now written as:
which reads as: d
is normally distributed with a mean of
0 and standard deviation of 1.
Previously, if you had a vector parameter you had to write
(though with user()
, as in the previous section).
However, the array index here does not really add anything as we already
know how many dimensions a
has from the dim
call. So now you should write
which makes it clearer that all of a
is
assigned by the parameter call.
rank
argumentWhat a mouthful. Previously you might have written
which means “a
is a matrix whose dimensions are
determined by the input we are given on initialisation”. Because of the
previous change the first line changes to
but that means that we no longer know that a
has two
dimensions. That’s ok because we’ve moved the responsibility for this
into the dim()
assignment line anyway (internally). So for
now you write
which conveys the same intent. We may make this slightly more
friendly in future (see vignette("functions")
).
Previously, if you had an interpolate()
call that
returned a vector (or higher-dimension array) you had to write
but now you should drop the []
, as for the
parameter()
case above, as you are replacing all
of v
at once, writing:
Previously, discrete time models used step
to count
steps forward as unsigned integers, usually from zero. Many models added
a parameter (or constant) dt
representing the timestep and
then a variable time
which represented the time as a
real-valued number. For example you might have dt
of 0.25
and then your model stops at times [0, 0.25, 0.5, 0.75, 1]
for steps [0, 1, 2, 3, 4]
.
We formalise this approach now having discrete time systems be
explicitly in terms of the same time basis as ODE models (that is, some
real valued time axis). When you initialise a model you pass in
dt
, which must be an even divisor of 1 (so 0.5, 0.25, 0.2,
etc). We then take steps of this size. The wrinkle is that (at least for
now) the model will only return control back to you, or state back to
you, at integer-valued times. We may relax this in future to allow
returning at any time value that is a multiple of dt
.
This will cause a few issues for using old code, which we cover below.
dt
You may have models that assign to dt
, either directly
or as a parameter. You can no longer do this as dt
will be
provided by dust
(see
dust2::dust_system_create()
).
We can automatically remove these (with a warning) in some cases.
time
Conventionally, many models would write
which is the linear transformation of time that dust2 now does. We can remove these statements and your model should work as intended.
step
All other uses of step
are problematic and will need
manual fixing. We will try and accumulate migration strategies here, so
please let us know if you have had to do anything not listed.
Access “interpolated” values from a grid: In
sircovid
we used step
as an array index, in
order to support time-varying inputs (e.g., vaccine allocation
schedules, rates of contact). This is no longer supported (at all)
because dt
is changed separately from the inputs. Instead
you should use odin’s interpolation functions.
Periodic resetting: You may have written:
a <- if (step %% freq == 0) b else c
to have some quantity that took different values every
freq
steps, where freq
is usually
1/dt
or m/dt
where m
is an
integer. You should rewrite this to use time
:
a <- if (time * dt / m == 0) b else c
Previously, time was t
but we have moved this to
time
to be a little more explicit. We can automatically
migrate your code in many cases, unless you have defined a variable
time
already.
Previously we used the same names as R’s random-number-drawing
functions, for example rbinom
for drawing from a binomial
distribution. This has changed to use the distribution name instead.
The motivating reason for this change was that in odin we might write
but if you were writing this in R you would write
rbinom(1, size, prob)
with the first argument being the number of draws from the
distribution in question. This departure in arguments feels needlessly
confusing! If you were using odin
without
odin.dust
then this did compile to a call to one of R’s
underlying random number functions so this connection was reasonable but
from version 2 we use monty’s parallelisable random number
distributions.
The mapping is:
rbeta()
to Beta
rbinom()
to Binomial
rcauchy()
to Cauchy
(unsupported for
now)rchisq()
to ChiSquared
(unsupported for
now)rexp()
to Exponential
rf()
to F
(unsupported for now)rgamma()
to Gamma
rgeometric()
to Geometric
(unsupported for
now)rhyper()
to Hypergeometric
rlogis()
to Logistic
(unsupported for
now)rlnorm()
to Lognormal
(unsupported for
now)rnbinom()
to NegativeBinomial
rnorm()
to Normal
rpois()
to Poisson
rt()
to T
(unsupported for now)runif()
to Uniform
rweibull()
to Weibull
(unsupported for
now)(Not all of these are implemented yet).
This limitation comes from our implementation in dust2
and it is possible to relax it in some settings. However, it is fairly
important for efficiently running the system within a pMCMC context
where we save state periodically.
If your system has a parameter that affects the number of state variables in the system (e.g., the number of age categories that a compartment is stratified by), you may not change this after initialisation. This will be prevented by the parser once arrays are implemented.
The two-argument form of dim()
has been removed, as we
did not believe it was used and it is confusingly different to R.
Previously you could write dim(x, 3)
to get the length of
the third dimension of x
; this is no longer supported.
Please let us know if this is a problem.
This package replaces odin.dust
and will eventually
replace odin
(as in, we’ll copy the entire
odin2
code into odin
to become version 2.0.0
of that package).
The relationship between packages has changed. Previously
mcstate
“knew” about dust
models and so you
had to use odin.dust
practically to use the statistical
machinery in mcstate
. We’ve changed this around now, so
that odin2
“knows” about monty
and can create
systems that will work well with monty
. We now depend on
monty
, so if you have odin2
installed you can
start working towards fitting models immediately.
Because we now compile to C++ via dust2
, the compilation
times have massively increased. Previously, compilation of a simple
model took less than a second, but now this will take 6 seconds or so.
You can alleviate this to a degree during development by specifying
debug = TRUE
when compiling, which reduces this down to
about 3 seconds. These times are from my workstation but I expect the
relative differences to hold (we’re probably 10x slower than previously
but can be “only” 5x slower if you turn off optimisation). If you were
previously using odin.dust
you should notice little change
here.
If you compile odin code that contains any of the changes above, it will try and update the code to the new version and keep going:
gen <- odin2::odin({
initial(x) <- 1
deriv(x) <- x + a / t
a <- user(2)
})
#> Warning in odin2::odin({: Found 2 compatibility issues
#> Replace calls to 'user()' with 'parameter()'
#> ✖ a <- user(2)
#> ✔ a <- parameter(2)
#> Use 'time' and not 't' to refer to time
#> ✖ deriv(x) <- x + a/t
#> ✔ deriv(x) <- x + a/time
This model contains two issues that can be easily rewritten; the solution to this rewriting is printed to screen and the model is compiled as if you had rewritten them.
Not everything can be rewritten, especially changes involving
step
:
gen <- odin2::odin({
initial(x) <- 1
update(x) <- x + a / step
a <- user(2)
})
#> Error in `odin2::odin()`:
#> ! Use of 'step' is no longer allowed
#> ℹ Previously, discrete-time models used 'step' as a measure of time, but we
#> have removed this in odin2
#> ℹ Please see `vignette(odin2::migrating)` for guidance
#> → Context:
#> update(x) <- x + a/step
#> ℹ For more information, run `odin2::odin_error_explain("E1050")`
In this case, odin errors and tries to indicate where you have work to do (and directs you to this document!)
For code saved into a file, you can use odin_migrate
to
migrate code from the old syntax to the new; this will preserve comments
and formatting except for code that is rewritten so it should be fairly
unintrusive.
For example, in path
(a temporary file for this
vignette) we have saved the code from above:
We can migrate this in-place with:
and now the code contains:
user()
becomes
parameter()
rank
argument