Fix more lints

R/ci.R

@@ -21,7 +21,7 @@ get_ci <- function(
     }
 
     required <- c("estimate", "std.error")
-    if (!inherits(x, "data.frame") || any(!required %in% colnames(x))) {
+    if (!inherits(x, "data.frame") || !all(required %in% colnames(x))) {
         return(x)
     }
 
@@ -116,7 +116,7 @@ get_ci_draws <- function(x, conf_level, draws, model = NULL) {
         insight::check_if_installed("collapse", minimum_version = "1.9.0")
         # Issue #1017
         if (nrow(draws) > 0) {
-            CIs <- collapse::dapply(draws, MARGIN = 1, FUN = collapse::fquantile, probs = c(critical, .5, 1 - critical))
+            CIs <- collapse::dapply(draws, MARGIN = 1, FUN = collapse::fquantile, probs = c(critical, 0.5, 1 - critical))
             x$estimate <- CIs[, 2]
             x$conf.low <- CIs[, 1]
             x$conf.high <- CIs[, 3]

R/comparisons.R

@@ -540,7 +540,7 @@ comparisons <- function(model,
     mfx <- backtransform(mfx, transform)
 
     # save as attribute and not column
-    if (any(!is.na(mfx[["marginaleffects_wts_internal"]]))) {
+    if (!all(is.na(mfx[["marginaleffects_wts_internal"]]))) {
         marginaleffects_wts_internal <- mfx[["marginaleffects_wts_internal"]]
     } else {
         marginaleffects_wts_internal <- NULL

R/deprecated.R

@@ -77,7 +77,7 @@ predictions(mod,
         insight::format_error("The `equivalence` and `p_adjust` arguments cannot be used together.")
     }
 
-    numderiv = sanitize_numderiv(numderiv)
+    numderiv <- sanitize_numderiv(numderiv)
 
     # build call: match.call() doesn't work well in *apply()
     call_attr <- c(list(

R/equivalence.R

@@ -4,7 +4,7 @@ equivalence <- function(x, equivalence = NULL, df = Inf, ...) {
         return(x)
     } 
 
-    if (!is.null(equivalence) && any(!c("estimate", "std.error") %in% colnames(x))) {
+    if (!is.null(equivalence) && !all(c("estimate", "std.error") %in% colnames(x))) {
         msg <- "The `equivalence` argument is not supported with models for which `marginaleffects` does not estimate a standard error (e.g., bayesian)."
         insight::format_error(msg)
     }
@@ -35,4 +35,4 @@ equivalence <- function(x, equivalence = NULL, df = Inf, ...) {
     x$p.value.equiv <- pmax(x$p.value.nonsup, x$p.value.noninf)
 
     return(x)
-}
+}

R/get_contrast_data_character.R

@@ -31,7 +31,7 @@ get_contrast_data_character <- function(model,
     } else if (isTRUE(checkmate::check_atomic_vector(variable$value, len = 2))) {
         if (is.character(variable$value)) {
             tmp <- modeldata[[variable$name]]
-            if (any(!variable$value %in% as.character(tmp))) {
+            if (!all(variable$value %in% as.character(tmp))) {
                 msg <- "Some of the values supplied to the `variables` argument were not found in the dataset."
                 insight::format_error(msg)
             }

R/get_contrast_data_factor.R

@@ -41,7 +41,7 @@ get_contrast_data_factor <- function(model,
     } else if (isTRUE(checkmate::check_atomic_vector(variable$value, len = 2))) {
         if (is.character(variable$value)) {
             tmp <- modeldata[[variable$name]]
-            if (any(!variable$value %in% as.character(tmp))) {
+            if (!all(variable$value %in% as.character(tmp))) {
                 msg <- "Some of the values supplied to the `variables` argument were not found in the dataset."
                 insight::format_error(msg)
             }

R/get_contrast_data_numeric.R

@@ -108,8 +108,8 @@ get_contrast_data_numeric <- function(model,
         lab <- make_label(variable$label, lab)
 
     } else if (identical(variable$value, "iqr")) {
-        low <- stats::quantile(xmd, probs = .25, na.rm = TRUE)
-        high <- stats::quantile(xmd, probs = .75, na.rm = TRUE)
+        low <- stats::quantile(xmd, probs = 0.25, na.rm = TRUE)
+        high <- stats::quantile(xmd, probs = 0.75, na.rm = TRUE)
         lab <- make_label(variable$label, c("Q3", "Q1"))
 
     } else if (identical(variable$value, "minmax")) {

R/get_contrasts.R

@@ -404,7 +404,7 @@ get_contrasts <- function(model,
         # if comparison returns a single value, then we padded with NA. That
         # also means we don't want `rowid` otherwise we will merge and have
         # useless duplicates.
-        if (any(!idx)) {
+        if (!all(idx)) {
             if (settings_equal("marginaleffects_safefun_return1", TRUE)) {
                 out[, "rowid" := NULL]
             }

R/get_hypothesis.R

@@ -1,4 +1,3 @@
-
 get_hypothesis <- function(
     x,
     hypothesis,
@@ -42,7 +41,7 @@ get_hypothesis <- function(
 
         argnames <- names(formals(hypothesis))
         if (!"x" %in% argnames) insight::format_error("The `hypothesis` function must accept an `x` argument.")
-        if (any(!argnames %in% c("x", "draws"))) {
+        if (!all(argnames %in% c("x", "draws"))) {
             msg <- "The allowable arguments for the `hypothesis` function are: `x` and `draws`"
             insight::format_error(msg)
         }
@@ -355,9 +354,9 @@ eval_string_hypothesis <- function(x, hypothesis, lab) {
     }
 
     if (!is.null(attr(lab, "names"))) {
-        lab = attr(lab, "names")
+        lab <- attr(lab, "names")
     } else {
-        lab = gsub("\\s+", "", lab)
+        lab <- gsub("\\s+", "", lab)
     }
 
     draws <- attr(x, "posterior_draws")

R/hypotheses.R

@@ -265,7 +265,7 @@ hypotheses <- function(
         }
     }
 
-    numderiv = sanitize_numderiv(numderiv)
+    numderiv <- sanitize_numderiv(numderiv)
 
     # after re-evaluation
     tmp <- sanitize_hypothesis(hypothesis, ...)
@@ -286,7 +286,7 @@ hypotheses <- function(
 
         } else if (inherits(model, "data.frame")) {
             out <- model
-            if (any(!c("term", "estimate") %in% colnames(out))) {
+            if (!all(c("term", "estimate") %in% colnames(out))) {
                 msg <- "`hypothesis` function must return a data.frame with two columns named `term` and `estimate`."
                 insight::format_error(msg)
             }

R/hypothesis_helper.R

@@ -43,10 +43,10 @@ specify_hypothesis <- function(
     } else if (identical(hypothesis, "sequential")) {
         if (comparison == "difference") {
             hypothesis <- function(x) (x - data.table::shift(x))[2:length(x)]
-            label = function(x) sprintf("(%s) - (%s)", x, data.table::shift(x))[2:length(x)]
+            label <- function(x) sprintf("(%s) - (%s)", x, data.table::shift(x))[2:length(x)]
         } else {
             hypothesis <- function(x) (x / data.table::shift(x))[2:length(x)]
-            label = function(x) sprintf("(%s) / (%s)", x, data.table::shift(x))[2:length(x)]
+            label <- function(x) sprintf("(%s) / (%s)", x, data.table::shift(x))[2:length(x)]
         }
     } else if (identical(hypothesis, "meandev")) {
         hypothesis <- function(x) x - mean(x)

R/methods_quantreg.R

@@ -15,15 +15,15 @@ get_predict.rq <- function(model,
                 out <- data.frame(rowid = newdata$rowid, estimate = out)
                 return(out)
             } else {
-                out = data.frame(rowid = seq_len(length(out)), estimate = out)
+                out <- data.frame(rowid = seq_len(length(out)), estimate = out)
             }
         }
     }
     out <- quantreg::predict.rq(model, newdata = newdata, ...)
     if (isTRUE(checkmate::check_numeric(out, len = nrow(newdata)))) {
         out <- data.frame(rowid = newdata$rowid, estimate = out)
     } else {
-        out = data.frame(rowid = seq_len(length(out)), estimate = out)
+        out <- data.frame(rowid = seq_len(length(out)), estimate = out)
     }
     return(out)
 }
@@ -55,4 +55,4 @@ sanitize_model_specific.rqs <- function(model, ...) {
 #         } else {
 #             return(X)
 #         }
-# }
+# }

R/plot_build.R

@@ -99,12 +99,12 @@ plot_build <- function(
             p <- p + ggplot2::geom_pointrange(
                 data = dat,
                 mapping = aes_obj,
-                position = ggplot2::position_dodge(.15))
+                position = ggplot2::position_dodge(0.15))
         } else {
             p <- p + ggplot2::geom_point(
                 data = dat,
                 mapping = aes_obj,
-                position = ggplot2::position_dodge(.15))
+                position = ggplot2::position_dodge(0.15))
         }
 
     # continuous x-axis
@@ -122,7 +122,7 @@ plot_build <- function(
         aes_args$ymin <- aes_args$ymax <- NULL
         aes_obj <- do.call(ggplot2::aes, aes_args)
         if ("conf.low" %in% colnames(dat)) {
-            p <- p + ggplot2::geom_ribbon(data = dat, aes_obj_ribbon, alpha = .1)
+            p <- p + ggplot2::geom_ribbon(data = dat, aes_obj_ribbon, alpha = 0.1)
             p <- p + ggplot2::geom_line(data = dat, aes_obj)
         }
         p <- p + ggplot2::geom_line(data = dat, aes_obj)
@@ -147,4 +147,4 @@ plot_build <- function(
     }
 
     return(p)
-}
+}

R/sanitize_condition.R

@@ -10,7 +10,7 @@ condition_shortcuts <- function(x, tr, shortcuts) {
             min(x, na.rm = TRUE),
             max(x, na.rm = TRUE))
     } else if (identical(tr, "quartile")) {
-        out <- stats::quantile(x, probs = c(.25, .5, .75), na.rm = TRUE)
+        out <- stats::quantile(x, probs = c(0.25, 0.5, 0.75), na.rm = TRUE)
     }
     return(out)
 }
@@ -189,4 +189,4 @@ sanitize_condition <- function(model, condition, variables = NULL, modeldata = N
         "condition3" = condition3,
         "condition4" = condition4) 
     return(out)
-}
+}

R/sanitize_numderiv.R

@@ -10,16 +10,16 @@ sanitize_numderiv <- function(numderiv) {
 
     if (length(numderiv) > 1) {
         if (numderiv[[1]] %in% c("fdforward", "fdcenter")) {
-            if (any(!names(numderiv)[2:length(numderiv)] %in% "eps")) {
+            if (!all(names(numderiv)[2:length(numderiv)] %in% "eps")) {
                 stop("The only valid argument for this numeric differentiation method is `eps`.")
             }
         } else if (numderiv[[1]] == "richardson") {
             valid <- c("eps", "d", "zero_tol", "size", "r", "v")
-            if (any(!names(numderiv)[2:length(numderiv)] %in% valid)) {
+            if (!all(names(numderiv)[2:length(numderiv)] %in% valid)) {
                 stop(sprintf("The only valid arguments for this numeric differentiation method are: %s. See `?numDeriv::grad` for details.", paste(valid, collapse = ", ")), call. = FALSE)
             }
         }
     }
 
     return(numderiv)
-}
+}

R/sanitize_variables.R

@@ -211,7 +211,7 @@ sanitize_variables <- function(variables,
             } else if (calling_function == "predictions") {
                 # string shortcuts
                 if (identical(predictors[[v]], "iqr")) {
-                    predictors[[v]] <- stats::quantile(modeldata[[v]], probs = c(.25, .75), na.rm = TRUE)
+                    predictors[[v]] <- stats::quantile(modeldata[[v]], probs = c(0.25, 0.75), na.rm = TRUE)
                 } else if (identical(predictors[[v]], "minmax")) {
                     predictors[[v]] <- c(min(modeldata[[v]], na.rm = TRUE), max(modeldata[[v]], na.rm = TRUE))
                 } else if (identical(predictors[[v]], "sd")) {