Add precheck for all functions with assertthat

NAMESPACE

@@ -17,6 +17,11 @@ export(x3p_vertical)
 import(dplyr)
 importFrom(Cairo,CairoPNG)
 importFrom(assertthat,assert_that)
+importFrom(assertthat,has_name)
+importFrom(assertthat,is.count)
+importFrom(assertthat,is.flag)
+importFrom(assertthat,is.number)
+importFrom(assertthat,is.string)
 importFrom(assertthat,not_empty)
 importFrom(bulletxtrctr,sig_align)
 importFrom(concaveman,concaveman)
@@ -26,6 +31,7 @@ importFrom(dplyr,filter)
 importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)
 importFrom(dplyr,n)
+importFrom(dplyr,near)
 importFrom(dplyr,rename)
 importFrom(dplyr,select)
 importFrom(dplyr,summarize)

R/df_rmtrend_x3p.R

@@ -6,6 +6,7 @@
 #' @import dplyr
 #' @importFrom x3ptools df_to_x3p
 #' @importFrom stats lm predict
+#' @importFrom assertthat assert_that has_name
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -18,6 +19,11 @@
 #' }
 #'
 df_rmtrend_x3p <- function(insidepoly_df) {
+  assert_that(
+    is.data.frame(insidepoly_df),
+    has_name(insidepoly_df, c("x", "y", "value", "mask", "n_neighbor_val_miss", "sd_not_miss"))
+  )
+
   n_neighbor_val_miss <-
     value <-
     x <-

R/inside_polygon.R

@@ -12,9 +12,10 @@
 #' If center is NULL, the half ranges of x and y are used.
 #' @return dataframe of x and y positions describing the inside of the area
 #' described by the input x and y, variable id describes the order of the points
-#' @importFrom dplyr mutate select rename arrange n
+#' @importFrom dplyr mutate select rename arrange n near
 #' @importFrom concaveman concaveman
 #' @importFrom tidyr pivot_longer
+#' @importFrom assertthat assert_that is.number
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -28,13 +29,18 @@
 #'   geom_polygon(data = polygon)
 #'
 inside_polygon <- function(x, y, concavity, center = NULL) {
-  stopifnot(concavity > 0)
-
+  assert_that(
+    is.numeric(x),
+    is.numeric(y),
+    is.number(concavity), concavity > 0
+  )
   if (is.null(center)) {
     center <- c(diff(range(x, na.rm = TRUE)), diff(range(y, na.rm = TRUE))) / 2
   }
   if (length(center) == 1) center <- rep(center, 2)
-  stopifnot(is.numeric(x), is.numeric(y), is.numeric(center), length(center) == 2)
+  assert_that(
+    is.numeric(center), near(length(center), 2)
+  )
 
   points_inside_out <- data.frame(x, y) %>%
     mutate(x = x - center[1], y = y - center[2]) %>%

R/vec_align_sigs_list.R

@@ -1,8 +1,8 @@
 #' Align signals
 #'
 #' Align signals with plot.
-#' @param sig1 first signal vector
-#' @param sig2 second signal vector
+#' @param sig1 first numeric signal vector
+#' @param sig2 second numeric signal vector
 #' @param min.overlap additional parameter passed on to \code{bulletxtrctr::get_ccf}
 #' @param ifplot whether graphs are displayed
 #' @param name1 name for the first cut
@@ -12,6 +12,7 @@
 #' @return list of aligned signals named \code{ccf}, \code{lag} and \code{lands} followed the output format of \code{bulletxtrctr::sig_align}
 #' @importFrom ggplot2 ggplot aes geom_line labs xlab ylab ggtitle
 #' @importFrom bulletxtrctr sig_align
+#' @importFrom assertthat assert_that not_empty is.count is.flag is.string
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -28,12 +29,27 @@
 vec_align_sigs_list <- function(
     sig1,
     sig2,
-    min.overlap = round(0.75 * min(length(sig1), length(sig2))),
+    min.overlap = NULL,
     ifplot = FALSE,
     name1 = "Cut1",
     name2 = "Cut2",
     legendname = "Signal",
     titlename = NULL) {
+  assert_that(
+    is.numeric(sig1),
+    is.numeric(sig2),
+    is.flag(ifplot),
+    is.string(name1),
+    is.string(name2),
+    is.string(legendname)
+  )
+  if (not_empty(min.overlap)) {
+    is.count(min.overlap)
+  }
+  if (not_empty(titlename)) {
+    is.string(titlename)
+  }
+
   x <- NULL
 
   sigalign <- sig_align(sig1, sig2)

R/x3p_MLE_angle_vec.R

@@ -12,6 +12,7 @@
 #' @importFrom raster raster
 #' @importFrom imager as.cimg hough_line nfline
 #' @importFrom stats loess predict
+#' @importFrom assertthat assert_that is.count is.number is.flag
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -26,6 +27,14 @@
 x3p_MLE_angle_vec <- function(x3p, ntheta = 720, min_score_cut = 0.1,
                                      ifplot = FALSE,
                                      loess_span = 0.2) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.count(ntheta),
+    is.number(min_score_cut),
+    is.flag(ifplot),
+    is.number(loess_span), loess_span > 0
+  )
+
   theta <-
     score <-
     theta_mod <-

R/x3p_boundary_points.R

@@ -8,6 +8,7 @@
 #' @importFrom x3ptools x3p_sample x3p_to_df
 #' @importFrom dplyr `%>%` group_by mutate filter summarize select
 #' @importFrom rlang .data
+#' @importFrom assertthat assert_that is.count
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -20,7 +21,11 @@
 #' geom_point()
 #'
 x3p_boundary_points <- function(x3p, sample) {
-  stopifnot("x3p" %in% class(x3p))
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.count(sample)
+  )
+
   x3p_df <- x3p %>%
     x3p_sample(m = sample) %>%
     x3p_to_df()

R/x3p_image_autosize.R

@@ -3,12 +3,13 @@
 #' Plot x3p object as an image with auto-adjusted size based on \code{x3ptools::x3p_image}.
 #' @param x3p x3p object
 #' @param ifhtml logical, whether the image will be put on html
-#' @param zoom numeric value indicating the amount of zoom
+#' @param zoom numeric value indicating the amount of zoom in \code{x3ptools::x3p_image}
 #' @param ... other parameter values except size and zoom used in \code{x3ptools::x3p_image}
 #' @return rgl plot, list of tags when \code{ifhtml = TRUE}
 #' @importFrom x3ptools x3p_image
 #' @importFrom rgl rglwidget
 #' @importFrom htmltools tagList
+#' @importFrom assertthat assert_that is.flag is.number
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -17,6 +18,12 @@
 #' }
 #'
 x3p_image_autosize <- function(x3p, ifhtml = FALSE, zoom = 0.6, ...) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.flag(ifhtml),
+    is.number(zoom), zoom > 0
+  )
+
   x3p_image(x3p, size = dim(x3p$surface.matrix), zoom = zoom, ...)
 
   if (ifhtml) {

R/x3p_impute.R

@@ -9,11 +9,11 @@
 #' @import dplyr
 #' @importFrom x3ptools x3p_delete_mask x3p_extract x3p_average x3p_add_mask
 #' @importFrom ggplot2 ggplot aes geom_raster scale_fill_gradient2 labs ggsave
-#' @importFrom assertthat assert_that not_empty
 #' @importFrom raster raster focal as.data.frame as.matrix
 #' @importFrom purrr map
 #' @importFrom magick image_read image_join image_animate image_write
 #' @importFrom stringr str_detect
+#' @importFrom assertthat assert_that is.flag not_empty is.string
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -27,19 +27,25 @@
 #' }
 #'
 x3p_impute <- function(x3p, ifsave = FALSE, dir_name = NULL, ifplot = FALSE) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.flag(ifsave),
+    is.flag(ifplot)
+  )
+  if (ifsave) {
+    assert_that(
+      not_empty(dir_name), is.string(dir_name)
+    )
+    dir.create(dir_name, showWarnings = FALSE)
+  }
+
   layer <-
     x <-
     y <-
     value <-
     . <-
     NULL
 
-  if (ifsave) {
-    assert_that(not_empty(dir_name), msg = "dir_name must be non-empty")
-    assert_that(is.character(dir_name), msg = "dir_name must be character")
-    dir.create(dir_name, showWarnings = FALSE)
-  }
-
   ### Convert x3p to raster
   x3p_inner_nomiss_res_raster <- t(x3p$surface.matrix) %>%
     raster(xmx = (x3p$header.info$sizeX - 1) * x3p$header.info$incrementX, ymx = (x3p$header.info$sizeY - 1) * x3p$header.info$incrementY)

R/x3p_insidepoly_df.R

@@ -21,6 +21,7 @@
 #' @importFrom stats sd
 #' @importFrom raster raster adjacent ncell
 #' @importFrom ggplot2 ggplot geom_raster scale_fill_gradient2 labs ggtitle geom_boxplot
+#' @importFrom assertthat assert_that is.string is.number is.count is.flag
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -30,6 +31,14 @@
 #'
 x3p_insidepoly_df <- function(x3p, mask_col = "#FF0000", concavity = 1.5, b = 10,
                               ifplot = FALSE) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.string(mask_col),
+    is.number(concavity), concavity > 0,
+    is.count(b),
+    is.flag(ifplot)
+  )
+
   to <-
     from <-
     neighbor_val <-

R/x3p_quantile_angle_vec.R

@@ -11,6 +11,7 @@
 #' @importFrom raster raster
 #' @importFrom imager as.cimg hough_line nfline
 #' @importFrom stats quantile median
+#' @importFrom assertthat assert_that is.count is.number is.flag
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -24,6 +25,13 @@
 #'
 x3p_quantile_angle_vec <- function(x3p, ntheta = 720, min_score_cut = 0.1,
                                           ifplot = FALSE) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.count(ntheta),
+    is.number(min_score_cut),
+    is.flag(ifplot)
+  )
+
   theta <-
     theta_mod <-
     theta_mod_shift <-

R/x3p_raw_sig_vec.R

@@ -9,6 +9,7 @@
 #' @importFrom x3ptools x3p_to_df
 #' @importFrom ggplot2 ggplot aes geom_line
 #' @importFrom stats na.omit median
+#' @importFrom assertthat assert_that is.flag
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[2]]
@@ -22,6 +23,12 @@
 #' str()
 #'
 x3p_raw_sig_vec <- function(x3p, method = "median", ifplot = FALSE) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    method %in% c("median", "mean"),
+    is.flag(ifplot)
+  )
+
   x <-
     value <-
     value_summary <-

R/x3p_shift_sig_vec.R

@@ -12,6 +12,7 @@
 #' @importFrom stats na.omit median lm coef approx
 #' @importFrom purrr map_dbl map set_names
 #' @importFrom tidyr nest unnest
+#' @importFrom assertthat assert_that is.flag
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[2]]
@@ -28,6 +29,13 @@
 #' }
 #'
 x3p_shift_sig_vec <- function(x3p, method = "median", ifplot = FALSE, delta = -5:5) {
+  assert_that(
+    "x3p" %in% class(x3p),
+    method %in% c("median", "mean"),
+    is.flag(ifplot),
+    is.numeric(delta), length(delta) >= 3
+  )
+
   y <-
     value_nobs <-
     x <-

R/x3p_surface_polygon.R

@@ -3,7 +3,7 @@
 #' @param x3p x3p file
 #' @param colour colour for the polygon
 #' @param sample strictly positive integer value specifying the amount of
-#' downsampling to be used (see `x3p_sample`) to calculate the boundary points
+#' downsampling to be used (see `x3ptools::x3p_sample`) to calculate the boundary points
 #' of the polygon. Larger values of `sample` will result in faster response times
 #' but results in less accurate polygons.
 #' @param center point on the center of the scan. If NULL, a center will be
@@ -15,6 +15,7 @@
 #' @importFrom png readPNG
 #' @importFrom grDevices as.raster dev.off
 #' @importFrom graphics par plot.default polygon
+#' @importFrom assertthat assert_that is.string is.count is.number
 #' @export
 #' @examples
 #' if (interactive()) {
@@ -24,7 +25,12 @@
 #' }
 #'
 x3p_surface_polygon <- function(x3p, colour = "red", sample = 10, center = NULL, concavity = 1.5) {
-  stopifnot("x3p" %in% class(x3p), is.numeric(concavity), concavity > 0)
+  assert_that(
+    "x3p" %in% class(x3p),
+    is.string(colour),
+    is.count(sample),
+    is.number(concavity), concavity > 0
+  )
 
   boundary <- x3p %>% x3p_boundary_points(sample = sample)
   polygon_inside <- inside_polygon(boundary$x, boundary$y,

R/x3p_vertical.R

@@ -11,6 +11,7 @@
 #' @return x3p object after rotation with vertical striations
 #' @import dplyr
 #' @importFrom x3ptools x3p_bin_stripes x3p_extract x3p_rotate
+#' @importFrom assertthat assert_that is.count is.number is.flag is.number
 #' @export
 #' @examples
 #' x3p <- x3p_subsamples[[1]]
@@ -27,10 +28,20 @@
 #' }
 #'
 x3p_vertical <- function(x3p_inner_impute, freqs = c(0, 0.3, 0.7, 1),
-                               method = "MLE",
-                               ntheta = 720, min_score_cut = 0.1,
-                               ifplot = FALSE,
-                               loess_span = 0.2) {
+                         method = "MLE",
+                         ntheta = 720, min_score_cut = 0.1,
+                         ifplot = FALSE,
+                         loess_span = 0.2) {
+  assert_that(
+    "x3p" %in% class(x3p_inner_impute),
+    is.numeric(freqs), near(length(freqs), 4), near(freqs[1], 0), near(freqs[4], 1),
+    method %in% c("MLE", "quantile"),
+    is.count(ntheta),
+    is.number(min_score_cut),
+    is.flag(ifplot),
+    is.number(loess_span), loess_span > 0
+  )
+
   x3p_bin <- x3p_inner_impute %>%
     x3p_bin_stripes(
       direction = "vertical",