Make sure that the object is a uncompressed rxode2 ui for solving with rxSolve (See #661)
Fix #670 by using the last simulated observation residual when there are trailing doses.
Create a function to see if a rxode2 solve is loaded in memory (rxode2::rxSolveSetup())
Create a new function that fixes the rxode2 population values in the model (and drops them in the initial estimates); rxFixPop()
Pendantic no-remap (as requested by CRAN)
gcc USBAN fix (as requested by CRAN)
rxUi compression now defaults to fast compression
Fixes String literal formatting issues as identified by CRAN (#643)
Removes linear compartment solutions with gradients for intel c++ compiler (since they crash the compiler).
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
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:
Instead of the
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 $meta). When the object is uncompressed, it simply assigns it to the environment instead (just like before).
When printing meta information that happens to be a lotri compatible matrix, use lotri to express it instead of the default R expression.
Allow character vectors to be converted to expressions for piping (#552)
rxAppendModel() will now take an arbitrary number of models and append them together; It also has better handling of models with duplicate parameters and models without ini() blocks (#617 / #573 / #575).
keep will now also keep attributes of the input data (with special handling for levels); This means a broader variety of classes will be kept carrying more information with it (for example ordered factors, data frame columns with unit information, etc)
Piping arguments append for ini() and model() have been aligned to perform similarly. Therefore ini(append=) now can take expressions instead of simply strings and model(append=) can also take strings. Also model piping now can specify the integer line number to be modified just like the ini() could. Also model(append=FALSE) has been changed to model(append=NULL). While the behavior is the same when you don’t specify the argument, the behavior has changed to align with ini() when piping. Hence model(append=TRUE) will append and model(append=FALSE) will now pre-pend to the model. model(append=NULL) will modify lines like the behavior of ini(append=NULL). The default of model(line) modifying a line in-place still applies. While this is a breaking change, most code will perform the same.
Labels can now be dropped by ini(param=label(NULL)). Also parameters can be dropped with the idiom model(param=NULL) or ini(param=NULL) changes the parameter to a covariate to align with this idiom of dropping parameters
rxRename has been refactored to run faster
Add as.model() for list expressions, which implies model(ui) <- ui$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
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)
xgxrCRAN requested that FORTRAN kind be changed as it was not portable; This was commented code, and simply removed the comment.
Bug-fix for geom_amt(); also now uses linewidth and at least ggplot2 3.4.0
Some documentation was cleaned up from rxode2 2.0.13
A bug was fixed so that the zeroRe() function works with correlated omega values.
A bug was fixed so that the rename() function works with initial conditions for compartments (cmt(0))
A new function zeroRe() allows simple setting of omega and/or sigma values to zero for a model (#456)
Diagonal zeros in the omega and sigma matrices are treated as zeros in the model. The corresponding omega and sigma matrices drop columns/rows where the diagonals are zero to create a new omega and sigma matrix for simulation. This is the same idiom that NONMEM uses for simulation from these matrices.
Add the ability to pipe model estimates from another model by parentModel %>% ini(modelWithNewEsts)
Add the ability to append model statements with piping using %>% model(x=3, append=d/dt(depot)), still supports appending with append=TRUE and pre-pending with append=NA (the default is to replace lines with append=FALSE)
rxSolve’s keep argument will now maintain character and factor classes from input data with the same class (#190)
Parameter labels may now be modified via ini(param = label("text")) (#351).
Parameter order may be modified via the append argument to ini() when piping a model. For example, ini(param = 1, append = 0) or ini(param = label("text"), append = "param2") (#352).
If lower/upper bounds are outside the required bounds, the adjustment is displayed.
When initial values are piped that break the model’s boundary condition reset the boundary to unbounded and message which boundary was reset.
Added as.rxUi() function to convert the following objects to rxUi objects: rxode2, rxModelVars, function. Converting nlmixr2 fits to rxUi will be placed in the s3 method in the corresponding package.
assertRxUi(x) now uses as.rxUi() so that it can be extended outside of rxode2/nlmixr2.
rxode2 now supports addl with ss doses
Moved rxDerived to rxode2parse (and re-exported it here).
Added test for transit compartment solving in absence of dosing to the transit compartment (fixed in rxode2parse but solving tested here)
Using ini() without any arguments on a rxode2 type function will return the ini() block. Also added a method ini(mod) <- iniBlock to modify the ini block is you wish. iniBlock should be an expression.
Using model() without any arguments on a rxode2 type function will return the model() block. Also added a new method model(mod) <- modelBlock
Added a new method rxode2(mod) <- modFunction which allows replacing the function with a new function while maintaining the meta information about the ui (like information that comes from nonmem2rx models). The modFunction should be the body of the new function, the new function, or a new rxode2 ui.
rxode2 ui objects now have a $sticky item inside the internal (compressed) environment. This $sticky tells what variables to keep if there is a “significant” change in the ui during piping or other sort of model change. This is respected during model piping, or modifying the model with ini(mod)<-, model(mod)<-, rxode2(mod)<-. A significant change is a change in the model block, a change in the number of estimates, or a change to the value of the estimates. Estimate bounds, weather an estimate is fixed or estimate label changes are not considered significant.
Added as.ini() method to convert various formats to an ini expression. It is used internally with ini(mod)<-. If you want to assign something new that you can convert to an ini expression, add a method for as.ini().
Added as.model() method to convert various formats to a model expression. It is used internally with model(mod)<-. If you want to assign something new that you can convert to a model expression, add a method for as.model().
Give a more meaningful error for ‘rxode2’ ui models with only error expressions
Break the ABI requirement between roxde2() and rxode2parse()
The new rxode2parse will fix the sprintf exclusion shown on CRAN.
Time invariant covariates can now contain ‘NA’ values.
When a column has ‘NA’ for the entire id, now ‘rxode2’ warns about both the id and column instead of just the id.
To fix some CRAN issues in ‘nlmixr2est’, make the version dependency explicit.
Remove log likelihoods from ‘rxode2’ to reduce compilation time and increase maintainability of ‘rxode2’. They were transferred to ‘rxode2ll’ (requested by CRAN).
Remove the parsing from ‘rxode2’ and solved linear compartment code and move to ‘rxode2parse’ to reduce the compilation time (as requested by CRAN).
Remove the random number generation from ‘rxode2’ and move to ‘rxode2random’ to reduce the compilation time (as requested by CRAN).
Remove the event table translation and generation from ‘rxode2’ and move to ‘rxode2et’ to reduce the compilation time (as requested by CRAN).
Change the rxode2 ui object so it is a compressed, serialized object by default. This could reduce the C stack size problem that occurs with too many environments in R.
Warn when ignoring items during simulations
Export a method to change ‘rxode2’ solve methods into internal integers
Bug fix for time invariant covariates identified as time variant covariate when the individual’s time starts after 0.
rxgamma now only allows a rate input. This aligns with the internal rxode2 version of rxgamma and clarifies how this will be used. It is also aligned with the llikGamma function used for generalized likelihood estimation.
ui cauchy simulations now follow the ui for normal and t distributions, which means you can combine with transformations. This is because the cauchy is a t distribution with one degree of freedom.
ui dnorm() and norm() are no longer equivalent to add(). Now it allows you to use the loglik llikNorm() instead of the standard nlmixr2 style focei likelihood. This is done by adding dnorm() at the end of the line. It also means dnorm() now doesn’t take any arguments.
Vandercorput normal removed (non-random number generator)
Allow models in the nlmixr2 form without an ini({}) block
Allow model piping of an omega matrix by f %>% ini(omegaMatrix)
Standard models created with rxode2() can no be piped into a model function
Families of log-likelihood were added to rxode2 so that mixed likelihood nonlinear mixed effects models may be specified and run.
The memory footprint of a rxode2 solving has been reduced
Piping now allow named strings (issue #249)
rxode2’s symengine would convert sqrt(2) to M_SQRT_2 when it should be M_SQRT2. This has been fixed; it was most noticeable in nlmixr2 log-likelihood estimation methods
rxode2 treats DV as a non-covariate with etTran (last time it would duplicate if it is in the model). This is most noticeable in the nlmixr2 log-likelihood estimation methods.
A new flag (rxFlag) has been created to tell you where in the rxode2 solving process you are. This is useful for debugging. If outputting this variable it will always be 11 or calculating the left handed equations. If you are using in conjunction with the printf() methods, it is a double variable and should be formatted with "%f".
An additional option of fullPrint has been added to rxode2() which allows rprintf() to be used in almost all of rxode2() steps (inductive linearization and matrix exponential are the exception here) instead of just the integration ddt step. It defaults to FALSE.
Removed accidental ^S from news as requested by CRAN.
Bug fix for more complicated mu-referencing.
Change rxode2 md5 to only depend on the C/C++/Fortran code and headers not the R files. That way if there is binary compatibility between nlmixr2est and rxode2, a new version of nlmixr2est will not need to be submitted to CRAN.
The options for rxControl and rxSolve are more strict. camelCase is now always used. Old options like add.cov and transit_abs are no longer supported, only addCov is supported.
A new option, sigdig has been added to rxControl(), which controls some of the more common significant figure options like atol, rtol, ssAtol, ssRtol, with a single option.
For simulations, $simulationSigma now assumes a diagonal matrix. The sigma values are assumed to be standard normal, and uncorrelated between endpoints. Simulation with uncertainty will still draw from this identity diagonal matrix
Parallel solving now seeds each simulation per each individual based on the initial seed plus the simulation id. This makes the simulation reproducible regardless of the number of cores running the simulation.
Solved objects now access the underlying rxode model with $rxode2 instead of $rxode
Since this change names, rxode2, rxode and RxODE all perform the same function.
Options were changed from RxODE.syntax to rxode2.syntax.
Assigning states with rxode2.syntax.assign.state (was RxODE.syntax.assign.state) is no longer supported.
Enforcing “pure” assignment syntax with = syntax is no longer supported so rxode2.syntax.assign is no longer supported (was RxODE.syntax.assign).
Since R supports ** as an exponentiation operator, the pure syntax without ** can no longer be enabled. Hence rxode2.syntax.star.pow (was RxODE.syntax.star.pow) no longer has any effect.
The “pure” syntax that requires a semicolon can no longer be enabled. Therefore rxode2.syntax.require.semicolon (was RxODE.syntax.require.semicolon) no longer has any effect.
The syntax state(0) can no longer be turned off. rxode2.syntax.allow.ini0 (was RxODE.syntax.allow.ini0) has been removed.
Variable with dots in variable and state names like state.name works in R. Therefore, “pure” syntax of excluding . values from variables cannot be enforced with rxode2.syntax.allow.dots (was RxODE.syntax.allow.dots).
The mnemonic et(rate=model) and et(dur=model) mnemonics have been removed. rate needs to be set to -1 and -2 manually instead.
The function rxode2Test() has been removed in favor of using testthat directly.
Transit compartments need to use a new evid, evid=7. That being said, the transitAbs option is no longer supported.
ID columns in input parameter data frames are not sorted or merged with original dataset any more; The underlying assumption of ID order should now be checked outside of rxode2(). Note that the event data frame is still sorted.
The UI functions of nlmixr have been ported to work in rxode2 directly.
rxModelVars({}) is now supported.
You may now combine 2 models in rxode2 with rxAppendModel(). In fact, as long as the first value is a rxode2 evaluated ui model, you can use c/rbind to bind 2 or more models together.
You may now append model lines with piping using %>% model(lines, append=TRUE) you can also pre-pend lines by %>% model(lines, append=NA)
You may now rename model variables, states and defined parameters with %>% rxRename(new=old) or if dplyr is loaded: %>% rename(new=old)
You can fix parameters with %>% ini(tcl=fix) or %>% ini(fix(tcl)) as well as unfix parameters with %>% ini(tcl=unfix) or %>% ini(unfix(tcl))
Strict R headers are enforced more places
Since there are many changes that could be incompatible, this version has been renamed to rxode2
rxode2() printout no longer uses rules and centered headings to make it display better on a larger variety of systems.
tad() and related time features only reset at the start of an infusion (as opposed to starting at the beginning and end of an infusion)Fix subject initialization of focei problem (#464)
Fix LHS offset to allow internal threading and more parallel processing in the future.
Remove warnings for duration and rate
Don’t export pillar methods any more (simply register at load if present)
As requested by CRAN, change fortran and C binding for BLAS an LINPACK
Fix the LTO issue that CRAN identified.
Move the omp files so they come first to support clang13, as identified by CRAN.
For now, be a little more conservative in dur() and rate() warnings because linCmt() models in nlmixr currently produce irrelevant warnings.
Always calculate “nolhs” for using numeric differences when the inner problem. This allows the inner problem to fallback to a finite difference approximation to the focei objective function.
Updated the parser C code grammar using latest dparser CRAN package
Added a new cbind function that is used to mix data frame input with simulated individual parameters and residual parameters, rxCbindStudyIndividual().
Now data frame input can be mixed with simulating from omega and sigma matrices (though not yet in nested simulations)
Race conditions when simulating random numbers is solved by chunking each simulation into groups that will always be performed per each thread. This way the simulation is now reproducible regardless of load. Because of the chunking, simulations with random numbers generated inside of it are now threaded by default (though a warning is produced about the simulation only be reproducible when run with the same number of threads)
Simulations were double checked and made sure to use the engine reserved for each core run in parallel; Some of the random generators were not taking random numbers from the correct engine, which was corrected. Therefore, simulations from this version are expected to be different (in parallel) than previous versions.
Added function rxSetSeed() to set the internal RxODE seed instead of grabbing it from a uniform random number tied to the original R seed. This will avoid the possibility of duplicate seeds and is the best practice.
Updating parameter pointers is done once per ID and locked based on ID to remove the recursion in #399, but still have the correct behavior see #430
Parsing updated to retain “param()” in normalized model, #432.
Handle edge case of interpolation at first index correctly, fixes #433
Instead of storing each dose information sequentially, store dose information at the same index of the evid defining the dose. This memory rewrite is to fix the issue #435.
Start using strict headers as it is required for the forthcoming release of Rcpp. Thanks to Dirk Eddelbuettel for some of the fixes and alerting us to this change.
Check arguments for add.dosing() more strictly. See Issue #441
Issue a warning when either dur() or rate() is in the model but the modeled rate and duration is not included in the event table.
When the data requires a modeled rate and modeled duration but it is not in the model, warn about the mismatch in data
Added a back-door for debugging. If you specify options(RxODE.debug=TRUE) then each solve saves the solving information to the file "last-rxode.qs" before actually solving the system.
Only will try to solve RxODE problems on compatible models; If the model is not supported it will throw an error instead of crashing (See #449)
Turn off parallel ODE solving whenever the system needs to sort times based on model dosing. Currently this type of solving is not thread safe.
Update timsort headers to latest version.
At the request of CRAN, stripping the debugging symbols for the CRAN release is no longer performed. This means a larger binary size for RxODE in this release.
At the request of CRAN the liblsoda code has been changed so that the memory in C defined by _C() is now defined by _rxC(). This will be seen in some of the error messages, which will no longer match the error messages of unmodified liblsoda.
iCov behavior has shifted to merge on the input event dataset. See Issue #409; This is more in line with expectations of iCov behavior, and reduces the amount of code needed to maintain iCov.
The iCov in the pipeline is no longer supported because it simply is a merge with the event dataset.
This can be a breaking change depending on the code you use. Note that clinical trial simulations, resampling is likely better than trying to fill out iCov for every individual which was the prior use.
Bug fix for crashes with string covariates or factor covariates, issue #410. Also factor column names are compared with case insensitivity just like the rest of the column names for event tables or data sets in RxODE.
Change syntax vignette to use markdown option screenshot.force=FALSE. This should get rid of the webshot error
Change to depend on dparser 1.3.0, which has some memory fixes
RxODE imports but does not link to checkmate any longer. This change should make recompilation of RxODE to work with different releases of checkmate unnecessary.
Default Solaris solver changed back to “lsoda”
Fix Bug #393, where in certain circumstances rxSolve(...,theta=) did not solve for all subjects.
Will not ignore NEWS and README when building the package so that they will show up on CRAN. You can also access the news by news(package="RxODE")
Changed ODR model names from time id to _rx followed by the md5 hash id and a per-session counter id; For packages the id is _rxp followed by the md5 hash and a per-session counter id.
Changed qs to be more conservative in hash creation. Add a check hash as well as NOT using altrep stringfish representation.
Maintenance release – use std::floor and cast variables to double for internal C functions. This should allow a successful compile on Solaris CRAN.
Changed units from an Imports to a Suggests to allow testing on Solaris rhub
Changed ODR model names from time id to _rx followed by the md5 hash id; For packages the id is _rxp followed by the md5 hash.
Removed AD linear compartment solutions for Windows R 3.6, though they still work for Windows R 4.0 (You can get them back for Windows R 3.6 if you install BH 1.66.0-1 and then recompile from source).
nlmixr to fail with solved systems on Windows 3.6. Currently the Stan Headers do not compile on this system so they are disabled at this time.RxODE imports but does not link to qs any longer; This change should make recompilation of RxODE to work with different releases of qs unnecessary.
RxODE now checks for binary compatibility for Rcpp, dparser, checkmate, and PreciseSums
RxODE can only use supported functions (could be breaking); You may add your own functions with rxFun and their derivatives with rxD
RxODE now uses its own internal truncated multivariate normal simulations based on the threefry sitmo library. Therefore random numbers generated within RxODE like providing rxSolve(...,omega=) will have different results with this new random number generator. This was done to allow internal re-sampling of sigmas/etas with thread-safe random number generators (calling R through mvnfast or R’s simulation engines are not thread safe).
RxODE now moved the precise sum/product type options for sum() and prod() to rxSolve or rxControl
cvPost now will returned a named list of matrices if the input matrix was named
rxSolve will now return an integer id instead of a factor id when id is integer or integerish (as defined by checkmate). Otherwise a factor will be returned.
When mixing ODEs and linCmt() models, the linCmt() compartments are 1 and possibly 2 instead of right after the last internal ODE. This is more aligned with how PK/PD models are typically defined.
EVID=3 and EVID=4 now (possibly) reset time as well. This occurs when the input dataset is sorted before solving.
When EVID=2 is present, an evid column is output to distinguish evid=0 and evid=2
Add the ability to order input parameters with the param() pseudo-function
Add the ability to resample covariates with resample=TRUE or resample=c("SEX", "CRCL"). You can resample all the covariates by ID with resampleID=TRUE or resample the covariates without respect to ID with resampleID=FALSE
Comparison of factors/strings is now supported in RxODE; Therefore ID==“Study-1” is now allowed.
Completion for elements of rxSolve() objects, and et() objects have been added (accessed through $)
Completion of rxSolve() arguments are now included since they are part of the main method
Allow simulation with zero matrices, that provide the simulation without variability. This affects rxSolve as well as rxMvnrnd and cvPost (which will give a zero matrix whenever one is specified)
et() can dose with length(amt) > 1 as long as the other arguments can create a event table.
Rstudio notebook output makes more sense
Printing upgraded to cli 2.0
optim code when:
inits do not change (though you can specify them as cmt(0)=... in the model and change them by parameters)Allow while(logical) statements with ability to break out if them by break. The while has an escape valve controlled by maxwhere which by default is 10000 iterations. It can be change with rxSolve(..., maxwhere = NNN)
Allow accessing different time-varying components of an input dataset for each individual with:
lag(var, #)lead(var, #)first(var)last(var)diff(var)Each of these are similar to the R lag, lead, first, last and diff. However when undefined, it returns NA
Allow sticky left-handed side of the equation; This means for an observation the left handed values are saved for the next observations and then reassigned to the last calculated value.
This allows NONMEM-style of calculating parameters like tad:
mod1 <-RxODE({
KA=2.94E-01;
CL=1.86E+01;
V2=4.02E+01;
Q=1.05E+01;
V3=2.97E+02;
Kin=1;
Kout=1;
EC50=200;
C2 = centr/V2;
C3 = peri/V3;
d/dt(depot) =-KA*depot;
d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
d/dt(peri) = Q*C2 - Q*C3;
d/dt(eff) = Kin - Kout*(1-C2/(EC50+C2))*eff;
if (!is.na(amt)){
tdose <- time
} else {
tad <- time - tdose
}
})It is still simpler to use:
mod1 <-RxODE({
KA=2.94E-01;
CL=1.86E+01;
V2=4.02E+01;
Q=1.05E+01;
V3=2.97E+02;
Kin=1;
Kout=1;
EC50=200;
C2 = centr/V2;
C3 = peri/V3;
d/dt(depot) =-KA*depot;
d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3;
d/dt(peri) = Q*C2 - Q*C3;
d/dt(eff) = Kin - Kout*(1-C2/(EC50+C2))*eff;
tad <- time - tlast
})If the lhs parameters haven’t been defined yet, they are NA
Now the NONMEM-style newind flag can be used to initialize lhs parameters.
Added tad(), tad(cmt) functions for time since last dose and time since last dose for a compartment; Also added time after first dose and time after first dose for a compartment tafd(), tafd(cmt); time of last dose tlast(), tlast(cmt) and dose number dosenum() (currently not for each compartment)
Changed linear solved systems to use “advan” style linCmt() solutions, to allow correct solutions of time-varying covariates values with solved systems; As such, the solutions may be slightly different. Infusions to the depot compartment are now supported.
linCmt() solutions. This allows sensitivities of linCmt() solutions and enables nlmixr focei to support solved systems.
C++14When calculating the empirical Bayesian estimates for with rxInner (used for nlmixr’s ‘focei’) ignore any variable beginning with rx_ and nlmixr_ to hide internal variables from table output. This also added tad=tad() and dosenum=dosenum() to the ebe output allowing grouping by id, dose number and use TAD for individual plot stratification.
Added ability to prune branching with rxPrune. This converts if/else or ifelse to single line statements without any if/then branching within them.
ifelse(expr, yes, no)x = (x==1)*1 + (!(x==1))*2if (logic){ expr} else if (logic) {expr} else {}. The preferred syntax is still only if/else and the corresponding parsed code reflects this preference.
ifelse is not allowed as an ODE compartment or a variable.symengine instead of using sympy
sympy, though some functions in sympy are no longer accessible.Added new ODE solving method “indLin”, or inductive linearization. When the full model is a linear ODE system this becomes simply the matrix exponential solution. Currently this requires a different setup.
rxFun
rxD. When taking deviates without a derivative function, RxODE will use numerical differences.math.h are supportedrxFun and rxDAdded NA, NaN, Inf and +Inf handling to a RxODE model. Can be useful to diagnose problems in models and provide alternate solutions. In addition, added R-like functions is.nan, is.na, is.finite and is.infinite which can be called within the RxODE block.
cmtdvidaddlssamtrateid which requires calling the id as factor ID=="1" for instance.Kept evid and ii as restricted items since they are not part of the covariate table and are restricted in use.
Added the following random number generators; They are thread safe (based on threefry sitmo and c++11) and your simulations with them will depend on the number of cores used in your simulation (Be careful about reproducibility with large number of threads; Also use parallel-solve type of RxODE simulations to avoid the birthday problem).
During ODE solving, the values of these are 0, but while calculating the final output the variable is randomized at least for every output. These are:
rxnorm() and rxnormV() (low discrepancy normal)rxcauchy()rxchisq()rxexp()rxf()rxgamma()rxbeta()rxgeom()rxpois()rxt()rxunif()rxweibull()In addition, while initializing the system, the following values are simulated and retained for each individual:
rinorm() and rinormV() (low discrepancy normal)ricauchy()richisq()riexp()rif()rigamma()ribeta()rigeom()ripois()rit()riunif()riweibull()Added simeta() which simulates a new eta when called based on the possibly truncated normal omega specified by the original simulation. This simulation occurs at the same time as the ODE is initialized or when an ODE is missing, before calculating the final output values. The omega will reflect whatever study is being simulated.
Added simeps() which simulates a new eps from the possibly truncated normal sigma at the same time as calculating the final output values. Before this time, the sigma variables are zero.
All these change the solving to single thread by default to make sure the simulation is reproducible. With high loads/difficult problems the random number generator may be on a different thread and give a different number than another computer/try.
Also please note that the clang and gcc compiler use different methods to create the more complex random numbers. Therefore MacOS random numbers will be different than Linux/Windows at this time (with the exception of uniform numbers).
These numbers are still non-correlated random numbers (based on the sitmo test) with the exception of the vandercorput distributions, so if you increase the number of threads (cores=…) the results should still be valid, though maybe harder to reproduce. The faster the random number generation, the more likely these results will be reproduced across platforms.
Added the ability to integrate standard deviations/errors of omega diagonals and sigma diagonals. This is done by specifying the omega diagonals in the theta matrix and having them represent the variabilities or standard deviations. Then these standard deviations are simulated along with the correlations using the IJK correlation matrix (omega dimension < 10) or a correlation matrix or Inverse Wishart-based correlation matrix (omega dimension > 10). The information about how to simulate this is in the variability simulation vignette.
Now have a method to use lotri to simulate between occasion variability and other levels of nesting.
Added lower gamma functions See Issue #185
Upgraded comparison sort to timsort 2.0.1
data.table. The radix search was modified to:RxODE internal solved structuresNA/NaN values of timeChanged sorting to run in a single thread instead of taking over all the threads like data.table
Changed method for setting/getting number of threads based on data.table’s method
Added function rxDerived which will calculate derived parameters for 1, 2, and 3 compartment models
More descriptive errors when types of input are different than expected
Moved many C functions to C++. CRAN OpenMP support requires C++ only when C and C++ are mixed. See:
https://stackoverflow.com/questions/54056594/cran-acceptable-way-of-linking-to-openmp-some-c-code-called-from-rcpp
No longer produces C code that create the model variables. Instead, use qs to serialize, compress and encode in base91 and then write the string into the C file. The qs package then decodes all of that into the model variables. This also increases the compilation speed for models in RxODE.
Pre-compile RxODE headers once (if cache is enabled), which increases compilation speed for models in RxODE
RxODE’s translation from the mini-language to C has been refactored
Occasionally RxODE misidentified dual lhs/param values. An additional check is performed so that this does not happen.
For solved matrices with similar names (like “tadd” and “tad”) RxODE will now prefer exact matches instead of the first match found when accessing the items with $tad.
A fix where all ID information is kept with keep=c(""..."")
Transit compartment models using the transit ODE or variable are now allowed. Also check for more internally parsed items (see Issue #145).
Bug fix for etSeq and etRep where greater than 2 items were mis-calculated
ggplot2 3.3.0NAs in RxODE datasetNEWS.md file to track changes to the package