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
Caching of internal C data setup is now supported increasing speed of 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.
Added sensitivity auto-differentiation of 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.
Added ability to take more complex conditional expressions, including:
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.Switched to 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.
Added arbitrary function definition to RxODE using rxFun
rxD. When taking deviates without a derivative function, RxODE will use numerical differences.Will error if RxODE does not know of a function that you are trying to use; This could be a breaking change. Currently:
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.
Allowed the following data variables can be accessed (but not assigned or used as a state):
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
Changed in-place sort to a modified radix sort from data.table. The radix search was modified to:
Work directly with RxODE internal solved structures
Assume no infinite values or NA/NaN values of time
Always sort time in ascending order
Changed 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