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@mattfidler mattfidler released this 11 Dec 23:55
· 591 commits to main since this release
v2.1.0
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mattfidler Matthew Fidler
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rxode2 2.1.0

Breaking changes

  • Steady state with lag times are no longer shifted by the lag time
    and then solved to steady state by default. In addition the steady
    state at the original time of dosing is also back-calculated. If you
    want the old behavior you can bring back the option with
    ssAtDoseTime=FALSE.

  • "dop853" now uses the hmax/h0 values from the rxControl() or
    rxSolve(). This may change some ODE solving using "dop853"

  • When not specified (and xgxr is available), the x axis is no longer
    assumed to be in hours

New features

  • User defined functions can now be R functions. For many of these R
    functions they can be converted to C with rxFun() (you can see the
    C code afterwards with rxC("funName"))

  • Parallel solving of models that require sorting (like modeled lag
    times, modeled duration etc) now solve in parallel instead of downgrading
    to single threaded solving

  • Steady state infusions with a duration of infusions greater than the
    inter-dose interval are now supported.

  • Added $symengineModelNoPrune and $symengineModelPrune for
    loading models into rxode2 with rxS()

  • When plotting and creating confidence intervals for multiple
    endpoint models simulated from a rxode2 ui model, you can
    plot/summarize each endpoint with sim. (ie. confint(model, "sim") or plot(model, sim)).

    If you only want to summarize a subset of endpoints, you can focus
    on the endpoint by pre-pending the endpoint with sim. For example
    if you wanted to plot/summarize only the endpoint eff you would
    use sim.eff. (ie confint(model, "sim.eff") or plot(model, sim.eff))

  • Added model$simulationIniModel which prepend the initial
    conditions in the ini({}) block to the classic rxode2({}) model.

  • Now model$simulationModel and model$simulationIniModel will save
    and use the initialization values from the compiled model, and will
    solve as if it was the original ui model.

  • Allow ini(model) <- NULL to drop ini block and as.ini(NULL)
    gives ini({}) (Issue #523)

  • Add a function modelExtract() to extract model lines to allow
    modifying them and then changing the model by piping or simply
    assigning the modified lines with model(ui) <- newModifiedLines

  • Add Algebraic mu-referencing detection (mu2) that allows you to
    express mu-referenced covariates as:

cl <- exp(tcl + eta.cl + wt_cl * log(WT/70.5))

Instead of the

cl <- exp(tcl + eta.cl + wt_cl * log.WT.div.70.5)

That was previously required (where log.WT.div.70.5 was calculated
in the data) for mu expressions. The ui now has more information to
allow transformation of data internally and transformation to the old
mu-referencing style to run the optimization.

  • Allow steady state infusions with a duration of infusion greater than
    the inter-dose interval to be solved.

  • Solves will now possibly print more information when issuing a
    "could not solve the system" error

  • The function rxSetPipingAuto() is now exported to change the way you
    affect piping in your individual setup

  • Allow covariates to be specified in the model piping, that is mod %>% model(a=var+3, cov="var") will add "var" as a covariate.

  • When calculating confidence intervals for rxode2 simulated objects
    you can now use by to stratify the simulation summary. For
    example you can now stratify by gender and race by: confint(sim, "sim", by=c("race", "gender"))

  • When calculating the intervals for rxode2 simulated objects you
    can now use ci=FALSE so that it only calculates the default
    intervals without bands on each of the percentiles; You can also
    choose not to match the secondary bands limits with levels but use
    your own ci=0.99 for instance

  • A new function was introduced meanProbs() which calculates the
    mean and expected confidence bands under either the normal or t
    distribution

  • A related new function was introduced that calculates the mean and
    confidence bands under the Bernoulli/Binomial distribution
    (binomProbs())

  • When calculating the intervals for rxode2 simulated objects you
    can also use mean=TRUE to use the mean for the first level of
    confidence using meanProbs(). For this confidence interval you can
    override the n used in the confidence interval by using n=#. You
    can also change this to a prediction interval instead using
    pred=TRUE.

  • Also when calculating the intervals for rxode2 simulated object
    you can also use mean="binom" to use the binomial distributional
    information (and ci) for the first level of confidence using
    binomProbs(). For this confidence interval you can override the
    n used in the confidence interval by using n=#. You can also
    change this to a prediction interval instead using pred=TRUE. With
    pred=TRUE you can override the number of predicted samples with
    m=#

  • When plotting the confint derived intervals from an rxode2
    simulation, you can now subset based on a simulated value like
    plot(ci, Cc) which will only plot the variable Cc that you
    summarized even if you also summarized eff (for instance).

  • When the rxode2 ui is a compressed ui object, you can modify the ini
    block with $ini <- or modify the model block with $model <-.
    These are equivalent to ini(model) <- and model(model) <-,
    respectively. Otherwise, the object is added to the user defined
    components in the function (ie $meta). When the object is
    uncompressed, it simply assigns it to the environment instead (just
    like before).

  • When printing meta information that happens to be a lotri
    compatible matrix, use lotri to express it instead of the default
    R expression.

  • Allow character vectors to be converted to expressions for piping
    (#552)

  • rxAppendModel() will now take an arbitrary number of models and
    append them together; It also has better handling of models with
    duplicate parameters and models without ini() blocks (#617 / #573
    / #575).

  • keep will now also keep attributes of the input data (with special
    handling for levels); This means a broader variety of classes will
    be kept carrying more information with it (for example ordered
    factors, data frame columns with unit information, etc)

  • Piping arguments append for ini() and model() have been
    aligned to perform similarly. Therefore ini(append=) now can take
    expressions instead of simply strings and model(append=) can also
    take strings. Also model piping now can specify the integer line
    number to be modified just like the ini() could. Also
    model(append=FALSE) has been changed to model(append=NULL).
    While the behavior is the same when you don't specify the argument,
    the behavior has changed to align with ini() when piping. Hence
    model(append=TRUE) will append and model(append=FALSE) will now
    pre-pend to the model. model(append=NULL) will modify lines like
    the behavior of ini(append=NULL). The default of model(line)
    modifying a line in-place still applies. While this is a breaking
    change, most code will perform the same.

  • Labels can now be dropped by ini(param=label(NULL)). Also
    parameters can be dropped with the idiom model(param=NULL) or
    ini(param=NULL) changes the parameter to a covariate to align with
    this idiom of dropping parameters

  • rxRename has been refactored to run faster

Internal new features

  • Add as.model() for list expressions, which implies model(ui) <- ui$lstExpr will assign model components. It will also more
    robustly work with character vectors

  • Simulated objects from rxSolve now can access the model variables
    with $rxModelVars

  • Simulation models from the UI now use rxerr.endpoint instead of
    err.endpoint for the sigma residual error. This is to align
    with the convention that internally generated variables start with
    rx or nlmixr

  • Sorting only uses timsort now, and was upgraded to the latest
    version from Morwenn

Bug fixes

  • Simulating/solving from functions/ui now prefers params over omega
    and sigma in the model (#632)

  • Piping does not add constants to the initial estimates

  • When constants are specified in the model({}) block (like k <- 1), they will not
    be to the ini block

  • Bug fix for geom_amt() when the aes transformation has x

  • Bug fix for some covariate updates that may affect multiple compartment
    models (like issue #581)

Maintenance fixes

  • Modify plot code to work with development xgxr

What's Changed

New Contributors

Full Changelog: v2.0.14...v2.1.0

Contributors

mattfidler, billdenney, and s0521
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