Fix notes about no visible binding for global variable

R/get_sig_MSE.R

@@ -14,6 +14,18 @@
 #' @export
 
 get_sig_MSE <- function(x3p, method = "median", ifplot = FALSE, delta = -5:5) {
+  y <-
+    value_nobs <-
+    x <-
+    value <-
+    x_shift_delta_value <-
+    x_shift_delta <-
+    Dat <-
+    value_approx <-
+    mask <-
+    value_summary <-
+    NULL
+
   x3p_df <- x3p %>%
     x3p_to_df()
 

R/get_sig_raw.R

@@ -11,6 +11,11 @@
 #' @export
 
 get_sig_raw <- function(x3p, method = "median", ifplot = FALSE) {
+  x <-
+    value <-
+    value_summary <-
+    NULL
+
   x3p_df <- x3p %>%
     x3p_to_df()
 

R/get_sigalign.R

@@ -22,6 +22,8 @@ get_sigalign <- function(
     name2 = "Cut2",
     legendname = "Signal",
     titlename = NULL) {
+  x <- NULL
+
   sigalign <- sig_align(sig1, sig2)
   if (ifplot) {
     p <- sigalign$lands %>%

R/get_x3p_inner_df.R

@@ -10,9 +10,18 @@
 #' @importFrom stats sd
 #' @importFrom raster raster adjacent ncell
 #' @importFrom wires x3p_surface_polygon
+#' @importFrom rlang .data
 #' @export
 
 get_x3p_inner_df <- function(x3p, mask_col = "#FF0000", concavity = 1.5) {
+  to <-
+    from <-
+    neighbor_val <-
+    x <-
+    y <-
+    n_neighbor_val_miss <-
+    NULL
+
   x3p <- x3p %>%
     x3p_surface_polygon(colour = mask_col, concavity = concavity)
 
@@ -82,7 +91,7 @@ get_x3p_inner_df <- function(x3p, mask_col = "#FF0000", concavity = 1.5) {
         )
     ) %>%
     full_join(
-      .,
+      .data,
       x3p_inner_df_wide_sd_not_miss %>%
         pivot_longer(
           cols = everything(),

R/get_x3p_inner_impute.R

@@ -16,10 +16,17 @@
 #' @importFrom magick image_read image_join image_animate image_write
 #' @importFrom stringr str_detect
 #' @importFrom wires x3p_surface_polygon
+#' @importFrom rlang .data
 #' @export
 
 get_x3p_inner_impute <- function(x3p, mask_col = "#FF0000", concavity = 1.5,
                                  ifsave = FALSE, dir_name = NULL, ifplot = 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")
@@ -133,7 +140,7 @@ get_x3p_inner_impute <- function(x3p, mask_col = "#FF0000", concavity = 1.5,
       path = dir_name,
       full.names = TRUE
     ) %>%
-      .[str_detect(., pattern = ".png")] %>%
+      .data[str_detect(.data, pattern = ".png")] %>%
       file.remove() %>%
       invisible()
   }

R/get_x3p_inner_nomiss_res.R

@@ -7,9 +7,16 @@
 #' @import dplyr
 #' @importFrom x3ptools df_to_x3p
 #' @importFrom stats lm predict
+#' @importFrom rlang .data
 #' @export
 
 get_x3p_inner_nomiss_res <- function(x3p, mask_col = "#FF0000", concavity = 1.5) {
+  n_neighbor_val_miss <-
+    value <-
+    x <-
+    y <-
+    NULL
+
   x3p_inner_df <- get_x3p_inner_df(x3p, mask_col = mask_col, concavity = concavity)
 
   x3p_inner_nomiss_df <- x3p_inner_df %>%
@@ -18,11 +25,11 @@ get_x3p_inner_nomiss_res <- function(x3p, mask_col = "#FF0000", concavity = 1.5)
   ### Remove trend
   x3p_inner_nomiss_lm <- lm(value ~ x + y + I(x^2) + I(y^2) + x:y, data = x3p_inner_nomiss_df)
   x3p_inner_nomiss_res_df <- x3p_inner_nomiss_df %>%
-    mutate(value = value - predict(x3p_inner_nomiss_lm, select(., x, y)))
+    mutate(value = value - predict(x3p_inner_nomiss_lm, select(.data, x, y)))
 
   ### Convert df to x3p
   x3p_inner_nomiss_res <- x3p_inner_nomiss_res_df %>%
-    left_join(x3p_inner_df[, c("x", "y")], .) %>%
+    left_join(x3p_inner_df[, c("x", "y")], .data) %>%
     df_to_x3p()
 
   return(x3p_inner_nomiss_res)

R/get_x3p_rotate_angle_MLE.R

@@ -11,17 +11,25 @@
 #' @importFrom raster raster
 #' @importFrom imager as.cimg hough_line nfline
 #' @importFrom stats loess predict
+#' @importFrom rlang .data
 #' @export
 
 get_x3p_rotate_angle_MLE <- function(x3p, ntheta = 720, min_score_cut = 2,
                                      ifplot = FALSE,
                                      loess_span = 0.2) {
+  theta <-
+    score <-
+    theta_mod <-
+    theta_mod_shift <-
+    rho <-
+    NULL
+
   ### Change to contrast color
   x3p_shift <- x3p$surface.matrix
   NA_val <- -(x3p$surface.matrix %>%
     c() %>%
     summary() %>%
-    .[c("Min.", "Max.")] %>%
+    .data[c("Min.", "Max.")] %>%
     abs() %>%
     max() %>%
     ceiling())

R/get_x3p_rotate_angle_quantile.R

@@ -10,17 +10,25 @@
 #' @importFrom raster raster
 #' @importFrom imager as.cimg hough_line nfline
 #' @importFrom stats quantile median
+#' @importFrom rlang .data
 #' @export
 
 get_x3p_rotate_angle_quantile <- function(x3p, ntheta = 720, min_score_cut = 2,
                                           ifplot = FALSE) {
+  theta <-
+    theta_mod <-
+    theta_mod_shift <-
+    score <-
+    rho <-
+    NULL
+
   ### Change to contrast color
   x3p_shift <- x3p$surface.matrix
   x3p_shift[is.na(x3p$surface.matrix)] <-
     -(x3p$surface.matrix %>%
       c() %>%
       summary() %>%
-      .[c("Min.", "Max.")] %>%
+      .data[c("Min.", "Max.")] %>%
       abs() %>%
       max() %>%
       ceiling())
@@ -63,7 +71,7 @@ get_x3p_rotate_angle_quantile <- function(x3p, ntheta = 720, min_score_cut = 2,
 
   ### How to set a score cutoff line without hardcoding the quantile?
   theta_mod_shift_med <- x3p_hough_df_shift %>%
-    filter(score >= quantile(.$score, 0.99995, na.rm = TRUE)) %>%
+    filter(score >= quantile(.data$score, 0.99995, na.rm = TRUE)) %>%
     summarise(med = median(theta_mod_shift)) %>%
     unlist()