IMPORTANT added linting configuration
linting can be started by clicking Addins in RStudio, then "Lint current file". This commit also contains quick fixes for common linter messages like changing F to FALSE and T to TRUE.
This commit is contained in:
Simon Innerbichler
+42
-42
@@ -45,7 +45,7 @@ library(scales)
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#' Dat <- list()
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#' te <- Fitting_FUNC(dat, TransF)
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#' print(te)
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Fitting_FUNC <- function(ro_new, TransFlag = F) {
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Fitting_FUNC <- function(ro_new, TransFlag = FALSE) {
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CORro <- cor(ro_new[, 1], ro_new[, ncol(ro_new)])
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# browser()
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all_l <- melt(data.frame(ro_new), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
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@@ -268,7 +268,7 @@ plotSingularity <- function(dat) { # sigmoid,det_sig,
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#' Dat <- list()
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#' p <- plot_f(dat, sigmoid, det_sig, TransF)
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#' print(p)
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plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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plot_f <- function(dat, TransFlag = FALSE) { # sigmoid,det_sig,
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CORdat <- cor(dat[, 1], dat[, ncol(dat)])
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# browser()
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all_l <- melt(data.frame(dat), id.vars = "log_dose", variable.name = "replname", value.name = "readout")
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@@ -276,7 +276,7 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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isSample <- rep(c(0, 1), 1, each = nrow(all_l) / 2)
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all_l2 <- cbind(all_l, isRef, isSample)
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# browser()
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MODLS <- Fitting_FUNC(dat, TransFlag = F)
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MODLS <- Fitting_FUNC(dat, TransFlag = FALSE)
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s_mr <- MODLS[[1]]
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a <- s_mr$coefficients["a", 1]
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b <- s_mr$coefficients["b", 1]
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@@ -340,23 +340,23 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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scale_x_continuous(breaks = scales::pretty_breaks(n = 10)) +
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scale_y_continuous(breaks = scales::pretty_breaks(n = 10)) +
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# theme_bw() +
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theme(axis.text.x = element_text(size = 12, angle=90), axis.text.y = element_text(size = 12))
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theme(axis.text.x = element_text(size = 12, angle = 90), axis.text.y = element_text(size = 12))
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p2 <- p + geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = SAMPLE), color = "#C2173F",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = REF), color = "#4545BA",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_vline(xintercept = c(Xbendl3, Xbendu3), col = "#4545BA", linetype = 2) +
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geom_vline(xintercept = c(XbendlT, XbenduT), col = "#C2173F", linetype = 2) +
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@@ -397,11 +397,11 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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pl_df_trans <- cbind(seq_x, SAMPLEtrans, REFtrans)
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p_rt2 <- p_rt + geom_line(
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data = as.data.frame(pl_df_trans), aes(x = seq_x, y = SAMPLEtrans), color = "#C2173F",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df_trans), aes(x = seq_x, y = REFtrans), color = "#4545BA",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_vline(xintercept = c(XbendlTrans, XbenduTrans), col = "#4545BA", linetype = 2) +
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geom_vline(xintercept = c(XbendlTransT, XbenduTransT), col = "#C2173F", linetype = 2) +
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@@ -419,8 +419,8 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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cte <- Sum_u$coefficients["cs", 1] - Sum_u$coefficients["r", 1]
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dst <- Sum_u$coefficients["ds", 1]
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dte <- Sum_u$coefficients["dt", 1]
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REFu <- ast + (dst - ast) / (1 + exp(bst * (cst - seq_x)))
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SAMPLEu <- ate + (dte - ate) / (1 + exp(bte * (cte - seq_x)))
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pl_df2 <- cbind(seq_x, SAMPLEu, REFu)
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@@ -432,12 +432,12 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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theme_bw()
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pu2 <- pu + geom_line(
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data = as.data.frame(pl_df2), aes(x = seq_x, y = SAMPLEu),
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color = "#C2173F", inherit.aes = F
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color = "#C2173F", inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df2), aes(x = seq_x, y = REFu),
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color = "#4545BA", inherit.aes = F,
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show.legend = F
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color = "#4545BA", inherit.aes = FALSE,
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show.legend = FALSE
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)
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pu2_ <- pu2 +
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theme(legend.position = "none", axis.text = element_text(size = 14))
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@@ -465,12 +465,12 @@ plot_f <- function(dat, TransFlag = F) { # sigmoid,det_sig,
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pu2_t <- putrans + geom_line(
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data = as.data.frame(pl_df2u_t), aes(x = seq_x, y = SAMPLEu_trans),
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color = "#C2173F", inherit.aes = F
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color = "#C2173F", inherit.aes = FALSE
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) +
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geom_line(
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data = as.data.frame(pl_df2u_t), aes(x = seq_x, y = REFu_trans),
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color = "#4545BA", inherit.aes = F,
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show.legend = F
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color = "#4545BA", inherit.aes = FALSE,
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show.legend = FALSE
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)
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pu3_t <- pu2_t
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if (TransFlag) grid.arrange(p_rt2, pu3_t, nrow = 1) else grid.arrange(p2, pu2_, nrow = 1)
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@@ -782,19 +782,19 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
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# F-test on regression: MSSreg/MSSE
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if (is.na(F_nonlin)) F_nonlin <- 0
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if (F_nonlin > 0) {
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p_F_nonlin <- round(pf(F_nonlin, 2, dfPureE, lower.tail = F), 5)
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p_F_nonlin <- round(pf(F_nonlin, 2, dfPureE, lower.tail = FALSE), 5)
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} else {
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p_F_nonlin <- "SSnonlin neg or 0"
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}
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# significances
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F_regr <- (SSreg / 1) / (SSRes / dfRes)
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p_F_regr <- round(pf(F_regr, 1, dfRes, lower.tail = F), 3)
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p_F_treat <- round(pf(F_treat, 3, dfRes, lower.tail = F), 3)
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p_F_prep <- round(pf(F_prep, 1, dfRes, lower.tail = F), 3)
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p_F_slope_A <- round(pf(F_slope_A, 1, (nrow(circ_Al) - 2), lower.tail = F), 3)
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p_F_slope_B <- round(pf(F_slope_B, 1, (nrow(circ_Bl) - 2), lower.tail = F), 3)
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p_F_nonp <- round(pf(F_nonpar, 1, dfRes, lower.tail = F), 3)
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p_F_regr <- round(pf(F_regr, 1, dfRes, lower.tail = FALSE), 3)
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p_F_treat <- round(pf(F_treat, 3, dfRes, lower.tail = FALSE), 3)
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p_F_prep <- round(pf(F_prep, 1, dfRes, lower.tail = FALSE), 3)
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p_F_slope_A <- round(pf(F_slope_A, 1, (nrow(circ_Al) - 2), lower.tail = FALSE), 3)
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p_F_slope_B <- round(pf(F_slope_B, 1, (nrow(circ_Bl) - 2), lower.tail = FALSE), 3)
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p_F_nonp <- round(pf(F_nonpar, 1, dfRes, lower.tail = FALSE), 3)
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p_F_LoF <- p_F_nonlin
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res_tab_lin <- data.frame(
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@@ -869,7 +869,7 @@ ANOVAlintests <- function(ro_new, circles, Lim, PureErrFlag) {
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#'
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#' PlotLinPLA_FUNC(circle, sigmoid, all_l2, pl_df, indS, indT)
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PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
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#browser()
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# browser()
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mLin <- gsl_nls(readout ~ (intS + r) * isSample + intS * isRef + k * log_dose,
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data = circle,
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start = list(intS = 0, k = 1, r = 0),
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@@ -901,17 +901,17 @@ PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
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theme_bw()
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p2 <- p + geom_line(
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data = pl_df, aes(x = lnC, y = plotS), color = "#4545BA",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = pl_df, aes(x = lnC, y = plotT), color = "#C2173F",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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{
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if (!is.null(truePL_df)) {
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geom_line(
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data = data.frame(truePL_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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)
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}
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} +
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@@ -919,7 +919,7 @@ PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
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if (!is.null(truePL_df)) {
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geom_line(
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data = data.frame(truePL_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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)
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}
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} +
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@@ -939,17 +939,17 @@ PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
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pr2 <- p + geom_line(
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data = pl_rest, aes(x = lnC, y = plotS), color = "#4545BA",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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geom_line(
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data = pl_rest, aes(x = lnC, y = plotT), color = "#C2173F",
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inherit.aes = F
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inherit.aes = FALSE
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) +
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{
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if (!is.null(truePL_df)) {
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geom_line(
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data = data.frame(truePL_df), aes(x = seq_x, y = SAMPLEtrue), color = "#C2173F", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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)
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}
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} +
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@@ -957,7 +957,7 @@ PlotLinPLA_FUNC <- function(circle, sigmoid, all_l2, pl_df, indS, indT) {
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if (!is.null(truePL_df)) {
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geom_line(
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data = data.frame(truePL_df), aes(x = seq_x, y = REFtrue), color = "#4545BA", linetype = 2, alpha = 0.4,
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inherit.aes = F
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inherit.aes = FALSE
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)
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}
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} +
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@@ -1012,7 +1012,7 @@ pot4plFUNC <- function(ro_new, PureErrFlag) {
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CORdat <- cor(ro_new[, 1], ro_new[, ncol(ro_new)])
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if (CORdat < 0) SLOPE <- -1 else SLOPE <- 1
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#
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FITs <- Fitting_FUNC(ro_new, TransFlag = F)
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FITs <- Fitting_FUNC(ro_new, TransFlag = FALSE)
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if (!PureErrFlag) {
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pot_est <- FITs[[3]]
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potU_est <- FITs[[4]]
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@@ -1205,10 +1205,10 @@ tests_FUNC <- function(ro_new, Lim, PureErrFlag) {
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SSnonlin <- sum((predict(lm(readout ~ factor(Conc) * isSample, all_l)) - predPotU)^2)
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LoF_df <- FitAnova[1, 1] + FitAnova[2, 1]
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F_regr <- (SSregr / AnovaDFs[3]) / ERR
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p_F_regr <- round(pf(F_regr, AnovaDFs[3], ERR_df, lower.tail = F), 5)
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p_F_regr <- round(pf(F_regr, AnovaDFs[3], ERR_df, lower.tail = FALSE), 5)
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if (ncol(ro_new) < 4) F_nonlin <- 0 else F_nonlin <- (SSnonlin / AnovaDFs[6]) / ERR
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if (F_nonlin > 0) {
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p_F_nonlin <- round(pf(F_nonlin, AnovaDFs[6], ERR_df, lower.tail = F), 5)
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p_F_nonlin <- round(pf(F_nonlin, AnovaDFs[6], ERR_df, lower.tail = FALSE), 5)
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} else {
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p_F_nonlin <- "SSnonlin neg or single dilutions"
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}
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@@ -1404,11 +1404,11 @@ ANOVA4plUnresfunc <- function(ro_new) {
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MSE <- RSS / RSS_df
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noConc <- length(unique(all_l$Conc))
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AnovaDFs <- c(noConc - 1, 1, 3, noConc - 4 - 1, nrow(all_l) - noConc, noConc, nrow(all_l) - noConc - noConc, nrow(all_l) - 1)
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p_SStreat <- round(pf((SStreat / AnovaDFs[1]) / MSE, AnovaDFs[1], RSS_df, lower.tail = F), 3)
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p_SSprep <- round(pf((SSprep / AnovaDFs[2]) / MSE, AnovaDFs[2], RSS_df, lower.tail = F), 3)
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p_SSregr <- round(pf((SSregr / AnovaDFs[3]) / MSE, AnovaDFs[3], RSS_df, lower.tail = F), 3)
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p_SSnonp <- round(pf((SSnonparallel / AnovaDFs[4]) / MSE, AnovaDFs[3], RSS_df, lower.tail = F), 3)
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p_SSLoF <- round(pf((SSnonlin / LoF_df) / (SSE / SSE_df), LoF_df, SSE_df, lower.tail = F), 5)
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p_SStreat <- round(pf((SStreat / AnovaDFs[1]) / MSE, AnovaDFs[1], RSS_df, lower.tail = FALSE), 3)
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p_SSprep <- round(pf((SSprep / AnovaDFs[2]) / MSE, AnovaDFs[2], RSS_df, lower.tail = FALSE), 3)
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p_SSregr <- round(pf((SSregr / AnovaDFs[3]) / MSE, AnovaDFs[3], RSS_df, lower.tail = FALSE), 3)
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p_SSnonp <- round(pf((SSnonparallel / AnovaDFs[4]) / MSE, AnovaDFs[3], RSS_df, lower.tail = FALSE), 3)
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p_SSLoF <- round(pf((SSnonlin / LoF_df) / (SSE / SSE_df), LoF_df, SSE_df, lower.tail = FALSE), 5)
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ANOVAtab <- data.frame(
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Source = c(
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