Nothing
## ------------------------------------------------------------------------
library(bioinactivation)
## ------------------------------------------------------------------------
data(isothermal_inactivation)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
library(ggplot2)
ggplot(data = isothermal_inactivation) +
geom_point(aes(x = time, y = log_diff, col = as.factor(temp))) +
ggtitle("Example dataset: isothermal_inactivation")
## ------------------------------------------------------------------------
data(dynamic_inactivation)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
ggplot(data = dynamic_inactivation) +
geom_point(aes(x = time, y = log10(N))) +
ggtitle("Example dataset: dynamic_inactivation. Observations")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
ggplot(data = dynamic_inactivation) +
geom_point(aes(x = time, y = temperature)) +
ggtitle("Example dataset: dynamic_inactivation. Temperature profile")
## ------------------------------------------------------------------------
data(laterosporus_iso)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
ggplot(data = laterosporus_iso) +
geom_point(aes(x = time, y = log_diff, col = as.factor(temp))) +
ggtitle("Example dataset: laterosporus_iso")
## ------------------------------------------------------------------------
data(laterosporus_dyna)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
ggplot(data = laterosporus_dyna) +
geom_point(aes(x = time, y = logN)) +
ggtitle("Example dataset: laterosporus_dyna. Observations")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
ggplot(data = laterosporus_dyna) +
geom_point(aes(x = time, y = temp)) +
ggtitle("Example dataset: laterosporus_dyna. Temperature profile")
## ---- echo=FALSE, fig.width=6, fig.height=4, fig.align='center'----------
Temperature <- seq(30, 80, length=100)
b <- log( 1 + exp(0.3*(Temperature - 60)))
b_1 <- log( 1 + exp(0.2*(Temperature - 60)))
plot(Temperature, b, type = "l", col="red")
lines(Temperature, b_1, type = "l", col = "blue")
legend("topleft", c("k = 0.3","k = 0.2"), col=c("red", "blue"), lwd=1, cex = 1)
## ------------------------------------------------------------------------
get_model_data()
## ------------------------------------------------------------------------
example_model <- "Geeraerd"
## ------------------------------------------------------------------------
times <- seq(0, 4.5, length=100)
## ------------------------------------------------------------------------
model_data <- get_model_data(example_model)
print(model_data$parameters)
print(model_data$variables)
## ------------------------------------------------------------------------
model_parms <- c(D_R = 3,
z = 10,
N_min = 1e2,
temp_ref = 100,
N0 = 1e5,
C_c0 = 1e1
)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
temperature_profile <- data.frame(time = c(0, 4.5),
temperature = c(70, 120))
plot(temperature_profile, type = "l")
title("Example temperature profile")
## ------------------------------------------------------------------------
prediction_results <- predict_inactivation(example_model, times, model_parms, temperature_profile)
## ------------------------------------------------------------------------
head(prediction_results$simulation)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
p <- plot(prediction_results)
print(p)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
library(ggplot2)
p + theme_light() + xlab("time (min)")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(prediction_results, make_gg = FALSE,
xlab = "Time (min)", ylab = "logN")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
parms_no_shoulder <- c(D_R = 3,
z = 10,
N_min = 100,
temp_ref = 100,
N0 = 100000,
C_c0 = 0
)
prediction_no_shoulder <- predict_inactivation(example_model, times, parms_no_shoulder, temperature_profile)
plot(prediction_no_shoulder)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
parms_no_tail <- c(D_R = 3,
z = 10,
N_min = 0,
temp_ref = 100,
N0 = 100000,
C_c0 = 100
)
prediction_no_tail <- predict_inactivation(example_model, times, parms_no_tail, temperature_profile)
plot(prediction_no_tail)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(prediction_results, plot_temp = TRUE)
## ------------------------------------------------------------------------
data(isothermal_inactivation)
## ------------------------------------------------------------------------
get_isothermal_model_data()
## ------------------------------------------------------------------------
model_name <- "Bigelow"
## ------------------------------------------------------------------------
model_data <- get_isothermal_model_data(model_name)
model_data$params
## ------------------------------------------------------------------------
known_params = list(temp_ref = 100)
## ------------------------------------------------------------------------
starting_point <- list(z = 10,
D_R = 1.5
)
## ------------------------------------------------------------------------
iso_fit <- fit_isothermal_inactivation(model_name, isothermal_inactivation,
starting_point, known_params)
## ------------------------------------------------------------------------
summary(iso_fit$nls)
vcov(iso_fit$nls) # Calculates variance-covariance matrix {stats}
confint(iso_fit$nls) # Calculates confidence intervals {stats}
## ------------------------------------------------------------------------
iso_fit$parameters
## ------------------------------------------------------------------------
iso_fit$model
## ------------------------------------------------------------------------
head(iso_fit$data)
## ------------------------------------------------------------------------
plot(iso_fit, ylab = "Number of logarithmic reductions",
xlab = "Time (min)")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(iso_fit, make_gg = TRUE) +
ylab("Number of logarithmic reductions") +
xlab("Time (min)")
## ------------------------------------------------------------------------
data(dynamic_inactivation)
## ------------------------------------------------------------------------
get_model_data()
## ------------------------------------------------------------------------
simulation_model <- "Mafart"
## ------------------------------------------------------------------------
dummy_temp <- data.frame(time = dynamic_inactivation$time,
temperature = dynamic_inactivation$temperature)
## ------------------------------------------------------------------------
model_data <- get_model_data(simulation_model)
model_data$parameters
model_data$variables
## ------------------------------------------------------------------------
known_params = c(temp_ref = 90)
## ------------------------------------------------------------------------
starting_points <- c(delta_ref = 10,
p = 1,
z = 10,
logN0 = 5)
upper_bounds <- c(delta_ref = 20,
p = 2,
z = 20,
logN0 = Inf)
lower_bounds <- c(delta_ref = 5,
p = .5,
z = 5,
logN0 = 4)
## ------------------------------------------------------------------------
dynamic_fit <- fit_dynamic_inactivation(dynamic_inactivation, simulation_model, dummy_temp,
starting_points, upper_bounds, lower_bounds,
known_params)
## ------------------------------------------------------------------------
summary(dynamic_fit$fit_results)
## ------------------------------------------------------------------------
head(dynamic_fit$data)
## ------------------------------------------------------------------------
dynamic_fit$best_prediction$model_parameters
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
p <- plot(dynamic_fit)
p + theme_light()
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(dynamic_fit, plot_temp = TRUE)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(dynamic_fit, make_gg = FALSE,
xlab = "Time (min)", ylab = "logN")
## ------------------------------------------------------------------------
set.seed(82619)
MCMC_fit <- fit_inactivation_MCMC(dynamic_inactivation, simulation_model, dummy_temp,
starting_points, upper_bounds, lower_bounds,
known_params, niter = 50)
## ------------------------------------------------------------------------
summary(MCMC_fit$modMCMC)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
p <- plot(MCMC_fit)
p + xlab("Time (min)")
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(MCMC_fit, plot_temp = TRUE)
## ---- fig.width=6, fig.height=4, fig.align='center'----------------------
plot(MCMC_fit, make_gg = FALSE,
xlab = "Time (min)", ylab = "logN")
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.