* using log directory 'd:/Rcompile/CRANpkg/local/3.5/RxODE.Rcheck' * using R version 3.5.3 (2019-03-11) * using platform: x86_64-w64-mingw32 (64-bit) * using session charset: ISO8859-1 * checking for file 'RxODE/DESCRIPTION' ... OK * this is package 'RxODE' version '0.9.1-9' * package encoding: UTF-8 * checking package namespace information ... OK * checking package dependencies ... NOTE Package suggested but not available for checking: 'SnakeCharmR' * checking if this is a source package ... OK * checking if there is a namespace ... OK * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking whether package 'RxODE' can be installed ... OK * checking installed package size ... NOTE installed size is 6.7Mb sub-directories of 1Mb or more: libs 5.5Mb * checking package directory ... OK * checking 'build' directory ... OK * checking DESCRIPTION meta-information ... OK * checking top-level files ... OK * checking for left-over files ... 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OK ** checking whether the namespace can be unloaded cleanly ... OK ** checking loading without being on the library search path ... OK ** checking use of S3 registration ... OK * checking dependencies in R code ... OK * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK * checking R code for possible problems ... [27s] OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd cross-references ... OK * checking for missing documentation entries ... WARNING Undocumented code objects: 'type_sum.rxRateDur' All user-level objects in a package should have documentation entries. See chapter 'Writing R documentation files' in the 'Writing R Extensions' manual. * checking for code/documentation mismatches ... OK * checking Rd \usage sections ... OK * checking Rd contents ... OK * checking for unstated dependencies in examples ... OK * checking line endings in shell scripts ... 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ERROR Running examples in 'RxODE-Ex.R' failed The error most likely occurred in: > ### Name: RxODE > ### Title: Create an ODE-based model specification > ### Aliases: RxODE > ### Keywords: models nonlinear > > ### ** Examples > > # Step 1 - Create a model specification > ode <- " + # A 4-compartment model, 3 PK and a PD (effect) compartment + # (notice state variable names 'depot', 'centr', 'peri', 'eff') + + 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; + " > > m1 <- RxODE(model = ode) > print(m1) RxODE 0.9.1-9 model named rx_a5af0dfe0cd9b3b2b376195f83d75e38_i38 model (ready). m1$state: depot, centr, peri, eff m1$params: V2, V3, KA, CL, Q, Kin, Kout, EC50 m1$lhs: C2, C3 > > # Step 2 - Create the model input as an EventTable, > # including dosing and observation (sampling) events > > # QD (once daily) dosing for 5 days. > > qd <- eventTable(amount.units = "ug", time.units = "hours") > qd$add.dosing(dose = 10000, nbr.doses = 5, dosing.interval = 24) > > # Sample the system hourly during the first day, every 8 hours > # then after > > qd$add.sampling(0:24) > qd$add.sampling(seq(from = 24+8, to = 5*24, by = 8)) > > # Step 3 - set starting parameter estimates and initial > # values of the state > > theta <- + c(KA = .291, CL = 18.6, + V2 = 40.2, Q = 10.5, V3 = 297.0, + Kin = 1.0, Kout = 1.0, EC50 = 200.0) > > # init state variable > inits <- c(0, 0, 0, 1); > > # Step 4 - Fit the model to the data > > qd.cp <- m1$solve(theta, events = qd, inits) Warning in rxSolve_(object, .ctl, .nms, .xtra, params, events, inits, setupOnly = .setupOnly) : Assumed order of inputs: depot, centr, peri, eff > > head(qd.cp) time C2 C3 depot centr peri eff [1,] 0 0.00000 0.0000000 10000.000 0.000 0.0000 1.000000 [2,] 1 43.99334 0.9113641 7475.157 1768.532 270.6751 1.083968 [3,] 2 54.50866 2.6510696 5587.797 2191.248 787.3677 1.179529 [4,] 3 51.65163 4.4243597 4176.966 2076.396 1314.0348 1.227523 [5,] 4 44.37513 5.9432612 3122.347 1783.880 1765.1486 1.233503 [6,] 5 36.46382 7.1389804 2334.004 1465.845 2120.2772 1.214084 > > # This returns a matrix. Note that you can also > # solve using name initial values. For example: > > inits <- c(eff = 1); > > qd.cp <- solve(m1, theta, events = qd, inits); > > print(qd.cp) ______________________________ Solved RxODE object _____________________________ -- Parameters (qd.cp$params): -------------------------------------------------- V2 V3 KA CL Q Kin Kout EC50 40.200 297.000 0.291 18.600 10.500 1.000 1.000 200.000 -- Initial Conditions (qd.cp$inits): ------------------------------------------- depot centr peri eff 0 0 0 1 -- First part of data (object): ------------------------------------------------ # A tibble: 37 x 7 time C2 C3 depot centr peri eff [h] 1 0 0 0 10000 0 0 1 2 1 44.0 0.911 7475. 1769. 271. 1.08 3 2 54.5 2.65 5588. 2191. 787. 1.18 4 3 51.7 4.42 4177. 2076. 1314. 1.23 5 4 44.4 5.94 3122. 1784. 1765. 1.23 6 5 36.5 7.14 2334. 1466. 2120. 1.21 # ... with 31 more rows ________________________________________________________________________________ > > plot(qd.cp) Error in get(as.character(FUN), mode = "function", envir = envir) : object 'guide_none' of mode 'function' was not found Calls: ... lapply -> FUN -> f -> lapply -> FUN -> match.fun -> get Execution halted ** running examples for arch 'x64' ... ERROR Running examples in 'RxODE-Ex.R' failed The error most likely occurred in: > ### Name: RxODE > ### Title: Create an ODE-based model specification > ### Aliases: RxODE > ### Keywords: models nonlinear > > ### ** Examples > > # Step 1 - Create a model specification > ode <- " + # A 4-compartment model, 3 PK and a PD (effect) compartment + # (notice state variable names 'depot', 'centr', 'peri', 'eff') + + C2 = centr/V2; + C3 = peri/V3; + d/dt(depot) =-KA*depot; + d/dt(centr) = KA*depot - CL*C2 - Q*C2 + Q*C3; + d/dt(peri) = Q*C2 - Q*C3; + d/dt(eff) = Kin - Kout*(1-C2/(EC50+C2))*eff; + " > > m1 <- RxODE(model = ode) > print(m1) RxODE 0.9.1-9 model named rx_f320152852f29ce97e721bde4c4e81a0_x6 model (ready). m1$state: depot, centr, peri, eff m1$params: V2, V3, KA, CL, Q, Kin, Kout, EC50 m1$lhs: C2, C3 > > # Step 2 - Create the model input as an EventTable, > # including dosing and observation (sampling) events > > # QD (once daily) dosing for 5 days. > > qd <- eventTable(amount.units = "ug", time.units = "hours") > qd$add.dosing(dose = 10000, nbr.doses = 5, dosing.interval = 24) > > # Sample the system hourly during the first day, every 8 hours > # then after > > qd$add.sampling(0:24) > qd$add.sampling(seq(from = 24+8, to = 5*24, by = 8)) > > # Step 3 - set starting parameter estimates and initial > # values of the state > > theta <- + c(KA = .291, CL = 18.6, + V2 = 40.2, Q = 10.5, V3 = 297.0, + Kin = 1.0, Kout = 1.0, EC50 = 200.0) > > # init state variable > inits <- c(0, 0, 0, 1); > > # Step 4 - Fit the model to the data > > qd.cp <- m1$solve(theta, events = qd, inits) Warning in rxSolve_(object, .ctl, .nms, .xtra, params, events, inits, setupOnly = .setupOnly) : Assumed order of inputs: depot, centr, peri, eff > > head(qd.cp) time C2 C3 depot centr peri eff [1,] 0 0.00000 0.0000000 10000.000 0.000 0.0000 1.000000 [2,] 1 43.99334 0.9113641 7475.157 1768.532 270.6751 1.083968 [3,] 2 54.50866 2.6510696 5587.797 2191.248 787.3677 1.179529 [4,] 3 51.65163 4.4243597 4176.966 2076.396 1314.0348 1.227523 [5,] 4 44.37513 5.9432612 3122.347 1783.880 1765.1486 1.233503 [6,] 5 36.46382 7.1389804 2334.004 1465.845 2120.2772 1.214084 > > # This returns a matrix. Note that you can also > # solve using name initial values. For example: > > inits <- c(eff = 1); > > qd.cp <- solve(m1, theta, events = qd, inits); > > print(qd.cp) ______________________________ Solved RxODE object _____________________________ -- Parameters (qd.cp$params): -------------------------------------------------- V2 V3 KA CL Q Kin Kout EC50 40.200 297.000 0.291 18.600 10.500 1.000 1.000 200.000 -- Initial Conditions (qd.cp$inits): ------------------------------------------- depot centr peri eff 0 0 0 1 -- First part of data (object): ------------------------------------------------ # A tibble: 37 x 7 time C2 C3 depot centr peri eff [h] 1 0 0 0 10000 0 0 1 2 1 44.0 0.911 7475. 1769. 271. 1.08 3 2 54.5 2.65 5588. 2191. 787. 1.18 4 3 51.7 4.42 4177. 2076. 1314. 1.23 5 4 44.4 5.94 3122. 1784. 1765. 1.23 6 5 36.5 7.14 2334. 1466. 2120. 1.21 # ... with 31 more rows ________________________________________________________________________________ > > plot(qd.cp) Error in get(as.character(FUN), mode = "function", envir = envir) : object 'guide_none' of mode 'function' was not found Calls: ... lapply -> FUN -> f -> lapply -> FUN -> match.fun -> get Execution halted * checking for unstated dependencies in 'tests' ... OK * checking tests ... ** running tests for arch 'i386' ... [90s] OK Running 'testthat.R' [90s] ** running tests for arch 'x64' ... [82s] OK Running 'testthat.R' [82s] * checking for unstated dependencies in vignettes ... OK * checking package vignettes in 'inst/doc' ... OK * checking re-building of vignette outputs ... [8s] OK * checking PDF version of manual ... OK * DONE Status: 2 ERRORs, 1 WARNING, 2 NOTEs