CRAN Package Check Results for Package aRpsDCA

Last updated on 2024-03-28 17:49:21 CET.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.1.1 3.38 37.21 40.59 OK
r-devel-linux-x86_64-debian-gcc 1.1.1 2.79 29.32 32.11 OK
r-devel-linux-x86_64-fedora-clang 1.1.1 53.00 OK
r-devel-linux-x86_64-fedora-gcc 1.1.1 49.71 OK
r-devel-windows-x86_64 1.1.1 5.00 716.00 721.00 ERROR
r-patched-linux-x86_64 1.1.1 4.65 35.88 40.53 OK
r-release-linux-x86_64 1.1.1 3.98 35.54 39.52 OK
r-release-macos-arm64 1.1.1 22.00 OK
r-release-macos-x86_64 1.1.1 28.00 OK
r-release-windows-x86_64 1.1.1 6.00 58.00 64.00 OK
r-oldrel-macos-arm64 1.1.1 22.00 OK
r-oldrel-windows-x86_64 1.1.1 10.00 63.00 73.00 OK

Check Details

Version: 1.1.1
Check: tests
Result: ERROR Running 'fit_and_plot.R' [1s] Running 'fit_and_plot_from_Np.R' [169s] Running 'fit_and_plot_from_Np_with_buildup.R' [1s] Running 'fit_and_plot_from_Np_with_curtailment.R' [1s] Running 'fit_and_plot_from_interval.R' [1s] Running 'fit_and_plot_from_interval_with_buildup.R' [1s] Running 'fit_and_plot_from_interval_with_curtailment.R' [173s] Running 'fit_and_plot_with_buildup.R' [158s] Running 'fit_and_plot_with_curtailment.R' [167s] Running the tests in 'tests/fit_and_plot_from_Np.R' failed. Complete output: > # aRpsDCA > # Copyright (C) 2016 dwt | terminus data science, LLC > # <dwt [at] terminusdatascience.com> > > # This library is free software; you can redistribute it and/or > # modify it under the terms of the GNU Lesser General Public > # License as published by the Free Software Foundation; either > # version 2.1 of the License, or (at your option) any later version. > > # This library is distributed in the hope that it will be useful, > # but WITHOUT ANY WARRANTY; without even the implied warranty of > # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU > # Lesser General Public License for more details. > > # You should have received a copy of the GNU Lesser General Public > # License along with this library; if not, write to the Free Software > # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 > # USA > > library(aRpsDCA) > > fitme.exponential.t <- seq(0, 5, 1 / 12) # 5 years > fitme.exponential.Np <- exponential.Np( + 1000, # Bbl/d + as.nominal(0.70), # / year + fitme.exponential.t + ) > > exponential.fit <- best.exponential.from.Np(fitme.exponential.Np, fitme.exponential.t) > cat(paste("SSE:", exponential.fit$sse)) SSE: 9.01396353260357e-15> dev.new() dev.new(): using pdf(file="Rplots4.pdf") > plot(fitme.exponential.Np ~ fitme.exponential.t, main="Exponential Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(exponential.fit$decline, fitme.exponential.t) ~ fitme.exponential.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyperbolic.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyperbolic.Np <- hyperbolic.Np( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9, + fitme.hyperbolic.t + ) > > hyperbolic.fit <- best.hyperbolic.from.Np(fitme.hyperbolic.Np, fitme.hyperbolic.t) > cat(paste("SSE:", hyperbolic.fit$sse)) SSE: 5.59695874594112e-15> dev.new() dev.new(): using pdf(file="Rplots5.pdf") > plot(fitme.hyperbolic.Np ~ fitme.hyperbolic.t, main="Hyperbolic Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(hyperbolic.fit$decline, fitme.hyperbolic.t) ~ fitme.hyperbolic.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyp2exp.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyp2exp.Np <- hyp2exp.Np( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9, + as.nominal(0.15), # / year + fitme.hyp2exp.t + ) > > hyp2exp.fit <- best.hyp2exp.from.Np(fitme.hyp2exp.Np, fitme.hyp2exp.t) > cat(paste("SSE:", hyp2exp.fit$sse)) SSE: 331.283072104596> dev.new() dev.new(): using pdf(file="Rplots6.pdf") > plot(fitme.hyp2exp.Np ~ fitme.hyp2exp.t, main="Hyperbolic-to-Exponential Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(hyp2exp.fit$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > overall.best <- best.fit.from.Np(fitme.hyp2exp.Np, fitme.hyp2exp.t) > cat(paste("SSE:", overall.best$sse)) SSE: 211.095248425438> dev.new() dev.new(): using pdf(file="Rplots7.pdf") > plot(fitme.hyp2exp.Np ~ fitme.hyp2exp.t, main="Overall Best Fit (h2e Data)", + col="blue", xlab="Time", ylab="Rate") > lines(arps.Np(overall.best$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > > > proc.time() user system elapsed 0.42 0.15 0.56 Running the tests in 'tests/fit_and_plot_from_interval_with_curtailment.R' failed. Complete output: > # aRpsDCA > # Copyright (C) 2016 dwt | terminus data science, LLC > # <dwt [at] terminusdatascience.com> > > # This library is free software; you can redistribute it and/or > # modify it under the terms of the GNU Lesser General Public > # License as published by the Free Software Foundation; either > # version 2.1 of the License, or (at your option) any later version. > > # This library is distributed in the hope that it will be useful, > # but WITHOUT ANY WARRANTY; without even the implied warranty of > # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU > # Lesser General Public License for more details. > > # You should have received a copy of the GNU Lesser General Public > # License along with this library; if not, write to the Free Software > # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 > # USA > > library(aRpsDCA) > > fitme.exponential.t <- seq(0, 5, 1 / 12) # 5 years > fitme.exponential.Np <- curtailed.Np(arps.decline( + 1000, # Bbl/d + as.nominal(0.70)), # / year + 5 / 12, + fitme.exponential.t + ) > > exponential.fit <- best.exponential.from.interval.with.buildup( + diff(fitme.exponential.Np), fitme.exponential.t[2:length(fitme.exponential.t)]) > cat(paste("SSE:", exponential.fit$sse)) SSE: 332.138599468287> dev.new() dev.new(): using pdf(file="Rplots24.pdf") > plot(fitme.exponential.Np ~ fitme.exponential.t, main="Exponential Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(exponential.fit$decline, fitme.exponential.t) ~ fitme.exponential.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyperbolic.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyperbolic.Np <- curtailed.Np(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9), + 5 / 12, + fitme.hyperbolic.t + ) > > hyperbolic.fit <- best.hyperbolic.from.interval.with.buildup( + diff(fitme.hyperbolic.Np), fitme.hyperbolic.t[2:length(fitme.hyperbolic.t)]) > cat(paste("SSE:", hyperbolic.fit$sse)) SSE: 156.388861199454> dev.new() dev.new(): using pdf(file="Rplots25.pdf") > plot(fitme.hyperbolic.Np ~ fitme.hyperbolic.t, main="Hyperbolic Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(hyperbolic.fit$decline, fitme.hyperbolic.t) ~ fitme.hyperbolic.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyp2exp.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyp2exp.Np <- curtailed.Np(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9, + as.nominal(0.15)), # / year + 5 / 12, + fitme.hyp2exp.t + ) > > hyp2exp.fit <- best.hyp2exp.from.interval.with.buildup( + diff(fitme.hyp2exp.Np), fitme.hyp2exp.t[2:length(fitme.hyp2exp.t)]) > cat(paste("SSE:", hyp2exp.fit$sse)) SSE: 143.897742531685> dev.new() dev.new(): using pdf(file="Rplots26.pdf") > plot(fitme.hyp2exp.Np ~ fitme.hyp2exp.t, main="Hyperbolic-to-Exponential Fit", + col="blue", xlab="Time", ylab="Cumulative Production") > lines(arps.Np(hyp2exp.fit$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > overall.best <- best.fit.from.interval.with.buildup( + diff(fitme.hyp2exp.Np), fitme.hyp2exp.t[2:length(fitme.hyp2exp.t)]) > cat(paste("SSE:", overall.best$sse)) SSE: 143.897742531685> dev.new() dev.new(): using pdf(file="Rplots27.pdf") > plot(fitme.hyp2exp.Np ~ fitme.hyp2exp.t, main="Overall Best Fit (h2e Data)", + col="blue", xlab="Time", ylab="Rate") > lines(arps.Np(overall.best$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > > > proc.time() user system elapsed 0.35 0.26 0.56 Running the tests in 'tests/fit_and_plot_with_buildup.R' failed. Complete output: > # aRpsDCA > # Copyright (C) 2016 dwt | terminus data science, LLC > # <dwt [at] terminusdatascience.com> > > # This library is free software; you can redistribute it and/or > # modify it under the terms of the GNU Lesser General Public > # License as published by the Free Software Foundation; either > # version 2.1 of the License, or (at your option) any later version. > > # This library is distributed in the hope that it will be useful, > # but WITHOUT ANY WARRANTY; without even the implied warranty of > # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU > # Lesser General Public License for more details. > > # You should have received a copy of the GNU Lesser General Public > # License along with this library; if not, write to the Free Software > # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 > # USA > > library(aRpsDCA) > > fitme.exponential.t <- seq(0, 5, 1 / 12) # 5 years > fitme.exponential.q <- arps.q(arps.with.buildup(arps.decline( + 1000, # Bbl/d + as.nominal(0.70) # / year + ), 250, 1.5 / 12), + fitme.exponential.t + ) * rnorm(n=length(fitme.exponential.t), mean=1, sd=0.1) # perturb > > exponential.fit <- best.exponential.with.buildup(fitme.exponential.q, fitme.exponential.t) > cat(paste("SSE:", exponential.fit$sse)) SSE: 36677.811753432> dev.new() dev.new(): using pdf(file="Rplots28.pdf") > plot(fitme.exponential.q ~ fitme.exponential.t, main="Exponential Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(exponential.fit$decline, fitme.exponential.t) ~ fitme.exponential.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyperbolic.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyperbolic.q <- arps.q(arps.with.buildup(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9 + ), 250, 1.5 / 12), + fitme.hyperbolic.t + ) * rnorm(n=length(fitme.hyperbolic.t), mean=1, sd=0.1) # perturb > > hyperbolic.fit <- best.hyperbolic.with.buildup(fitme.hyperbolic.q, fitme.hyperbolic.t) > cat(paste("SSE:", hyperbolic.fit$sse)) SSE: 166902.733982567> dev.new() dev.new(): using pdf(file="Rplots29.pdf") > plot(fitme.hyperbolic.q ~ fitme.hyperbolic.t, main="Hyperbolic Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(hyperbolic.fit$decline, fitme.hyperbolic.t) ~ fitme.hyperbolic.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyp2exp.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyp2exp.q <- arps.q(arps.with.buildup(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9, + as.nominal(0.15) # / year + ), 250, 1.5 / 12), + fitme.hyp2exp.t + ) * rnorm(n=length(fitme.hyp2exp.t), mean=1, sd=0.1) # perturb > > hyp2exp.fit <- best.hyp2exp.with.buildup(fitme.hyp2exp.q, fitme.hyp2exp.t) > cat(paste("SSE:", hyp2exp.fit$sse)) SSE: 152917.750502214> dev.new() dev.new(): using pdf(file="Rplots30.pdf") > plot(fitme.hyp2exp.q ~ fitme.hyp2exp.t, main="Hyperbolic-to-Exponential Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(hyp2exp.fit$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > overall.best <- best.fit.with.buildup(fitme.hyp2exp.q, fitme.hyp2exp.t) > cat(paste("SSE:", overall.best$sse)) SSE: 152917.750502214> dev.new() dev.new(): using pdf(file="Rplots31.pdf") > plot(fitme.hyp2exp.q ~ fitme.hyp2exp.t, main="Overall Best Fit (h2e Data)", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(overall.best$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > > proc.time() user system elapsed 0.51 0.15 0.65 Running the tests in 'tests/fit_and_plot_with_curtailment.R' failed. Complete output: > # aRpsDCA > # Copyright (C) 2016 dwt | terminus data science, LLC > # <dwt [at] terminusdatascience.com> > > # This library is free software; you can redistribute it and/or > # modify it under the terms of the GNU Lesser General Public > # License as published by the Free Software Foundation; either > # version 2.1 of the License, or (at your option) any later version. > > # This library is distributed in the hope that it will be useful, > # but WITHOUT ANY WARRANTY; without even the implied warranty of > # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU > # Lesser General Public License for more details. > > # You should have received a copy of the GNU Lesser General Public > # License along with this library; if not, write to the Free Software > # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 > # USA > > library(aRpsDCA) > > fitme.exponential.t <- seq(0, 5, 1 / 12) # 5 years > fitme.exponential.q <- curtailed.q(arps.decline( + 1000, # Bbl/d + as.nominal(0.70) # / year + ), 5 / 12, + fitme.exponential.t + ) * rnorm(n=length(fitme.exponential.t), mean=1, sd=0.1) # perturb > > exponential.fit <- best.exponential.curtailed(fitme.exponential.q, fitme.exponential.t) > cat(paste("SSE:", exponential.fit$sse)) SSE: 55574.963926527> dev.new() dev.new(): using pdf(file="Rplots32.pdf") > plot(fitme.exponential.q ~ fitme.exponential.t, main="Exponential Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(exponential.fit$decline, fitme.exponential.t) ~ fitme.exponential.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyperbolic.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyperbolic.q <- curtailed.q(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9 + ), 5 / 12, + fitme.hyperbolic.t + ) * rnorm(n=length(fitme.hyperbolic.t), mean=1, sd=0.1) # perturb > > hyperbolic.fit <- best.hyperbolic.curtailed(fitme.hyperbolic.q, fitme.hyperbolic.t) > cat(paste("SSE:", hyperbolic.fit$sse)) SSE: 209591.320481539> dev.new() dev.new(): using pdf(file="Rplots33.pdf") > plot(fitme.hyperbolic.q ~ fitme.hyperbolic.t, main="Hyperbolic Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(hyperbolic.fit$decline, fitme.hyperbolic.t) ~ fitme.hyperbolic.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > fitme.hyp2exp.t <- seq(0, 5, 1 / 12) # 5 years > fitme.hyp2exp.q <- curtailed.q(arps.decline( + 1000, # Bbl/d + as.nominal(0.70), # / year + 1.9, + as.nominal(0.15) # / year + ), 5 / 12, + fitme.hyp2exp.t + ) * rnorm(n=length(fitme.hyp2exp.t), mean=1, sd=0.1) # perturb > > hyp2exp.fit <- best.hyp2exp.curtailed(fitme.hyp2exp.q, fitme.hyp2exp.t) > cat(paste("SSE:", hyp2exp.fit$sse)) SSE: 129745.704158372> dev.new() dev.new(): using pdf(file="Rplots34.pdf") > plot(fitme.hyp2exp.q ~ fitme.hyp2exp.t, main="Hyperbolic-to-Exponential Fit", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(hyp2exp.fit$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > overall.best <- best.curtailed.fit(fitme.hyp2exp.q, fitme.hyp2exp.t) > cat(paste("SSE:", overall.best$sse)) SSE: 127961.27029938> dev.new() dev.new(): using pdf(file="Rplots35.pdf") > plot(fitme.hyp2exp.q ~ fitme.hyp2exp.t, main="Overall Best Fit (h2e Data)", + col="blue", log="y", xlab="Time", ylab="Rate") > lines(arps.q(overall.best$decline, fitme.hyp2exp.t) ~ fitme.hyp2exp.t, + col="red") > legend("topright", pch=c(1, NA), lty=c(NA, 1), col=c("blue", "red"), legend=c("Actual", "Fit")) > > > proc.time() user system elapsed 0.32 0.25 0.54 Flavor: r-devel-windows-x86_64