Nothing
## ----setup, include=FALSE-----------------------------------------------------
knitr::opts_chunk$set(echo = TRUE)
## ----install_packages, echo=FALSE, warning=FALSE, results='hide',message=FALSE----
###*****************************
# INITIAL COMMANDS TO RESET THE SYSTEM
seedNo=14159
set.seed(seedNo)
###*****************************
###*****************************
require("sicegar")
require("dplyr")
require("ggplot2")
require("cowplot")
###*****************************
## ----generate_data------------------------------------------------------------
noise_parameter <- 1
reps <- 5
time <- rep(seq(3, 24, 3), reps)
mean_values <- doublesigmoidalFitFormula_h0(time,
finalAsymptoteIntensityRatio = .3,
maximum = 10,
slope1Param = 1,
midPoint1Param = 7,
slope2Param = 1,
midPointDistanceParam = 8,
h0 = 3)
intensity <- rnorm(n = length(mean_values), mean = mean_values, sd = rep(noise_parameter, length(mean_values)))
dataInput <- data.frame(time, intensity)
ggplot(dataInput, aes(time, intensity)) +
geom_point() +
scale_y_continuous(limits = c(-1, 13), expand = expansion(mult = c(0, 0))) +
theme_bw()
## -----------------------------------------------------------------------------
fitObj_zero <- fitAndCategorize(dataInput,
threshold_minimum_for_intensity_maximum = 0.3,
threshold_intensity_range = 0.1,
threshold_t0_max_int = 1E10,
use_h0 = FALSE) # Default
fitObj_free <- fitAndCategorize(dataInput,
threshold_minimum_for_intensity_maximum = 0.3,
threshold_intensity_range = 0.1,
threshold_t0_max_int = 1E10,
use_h0 = TRUE)
## ----zero_free_plots, fig.height=4, fig.width=8-------------------------------
# Double-sigmoidal fit with parameter related lines
fig_a <- figureModelCurves(dataInput = fitObj_zero$normalizedInput,
doubleSigmoidalFitVector = fitObj_zero$doubleSigmoidalModel,
showParameterRelatedLines = TRUE,
use_h0 = FALSE) # Default
fig_b <- figureModelCurves(dataInput = fitObj_free$normalizedInput,
doubleSigmoidalFitVector = fitObj_free$doubleSigmoidalModel,
showParameterRelatedLines = TRUE,
use_h0 = TRUE)
plot_grid(fig_a, fig_b, ncol = 2) # function from the cowplot package
## ----normalize_data-----------------------------------------------------------
normalizedInput_free <- normalizeData(dataInput = dataInput,
dataInputName = "doubleSigmoidalSample")
head(normalizedInput_free$timeIntensityData) # the normalized time and intensity data
## -----------------------------------------------------------------------------
# Fit the double-sigmoidal model
doubleSigmoidalModel_free <- multipleFitFunction_h0(dataInput=normalizedInput_free,
model="doublesigmoidal")
doubleSigmoidalModel_free <- parameterCalculation_h0(doubleSigmoidalModel_free)
## ----plot_raw_fit, echo=TRUE, message=FALSE, warning=FALSE, comment=FALSE, fig.height=4, fig.width=6----
# double-sigmoidal fit
figureModelCurves(dataInput = normalizedInput_free,
doubleSigmoidalFitVector = doubleSigmoidalModel_free,
showParameterRelatedLines = TRUE,
use_h0 = TRUE)
## -----------------------------------------------------------------------------
fitObj_zero$doubleSigmoidalModel |>
dplyr::select(finalAsymptoteIntensityRatio_Estimate, maximum_Estimate, slope1Param_Estimate, midPoint1Param_Estimate,
slope2Param_Estimate, midPointDistanceParam_Estimate) |>
c()
fitObj_free$doubleSigmoidalModel |>
dplyr::select(finalAsymptoteIntensityRatio_Estimate, maximum_Estimate, slope1Param_Estimate, midPoint1Param_Estimate,
slope2Param_Estimate, midPointDistanceParam_Estimate, h0_Estimate) |> c()
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