/dports/math/R-cran-raster/raster/R/ |
H A D | text.R | 35 labels <- 1:NROW(x) 39 .haloText(x[,1], x[,2], labels, ...) 41 text(x[,1], x[,2], labels, ...) 59 x <- x[[labels]] 64 .haloText(x[,1], x[,2], labels, ...) 66 text(x[,1], x[,2], labels, ...) 80 if (labels %in% names(x)) { 81 labels <- x@data[, labels] 85 labels <- 1:length(x) 111 labels <- x@data[, labels] [all …]
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/dports/math/py-pymc3/pymc-3.11.4/pymc3/glm/ |
H A D | utils.py | 20 def any_to_tensor_and_labels(x, labels=None): argument 44 labels = [labels] 50 labels = x.columns 58 labels = [x.name] 68 labels = x.columns 103 if labels is None and not isinstance(x, tt.Variable): 104 labels = ["x%d" % i for i in range(x.shape[1])] 112 if not len(labels) == x.shape[1]: 116 "got len(labels)=%d instead of %d" % (len(labels), x.shape[1]) 127 labels = list(labels) [all …]
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/dports/graphics/R-cran-ggplot2/ggplot2/R/ |
H A D | labeller.r | 245 lapply(labels, function(x) { argument 253 is_labeller <- function(x) inherits(x, "labeller") argument 307 force(x) 317 x <- dispatch_args(x, multi_line = multi_line) functionVar 318 x(labels) 320 default(lapply(labels, x)) 322 default(lapply(labels, as_function(x))) 324 default(lapply(labels, function(label) x[label])) 586 x$widths <- unit.c(x$widths[1], width, x$widths[c(-1, -2)]) 587 x$heights <- unit.c(x$heights[1], height, x$heights[c(-1, -2)]) [all …]
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H A D | coord-polar.r | 126 ret[[n]]$labels <- out$labels 137 x.labels = ret$x$labels, y.labels = ret$y$labels, 253 list(a = labels[[1]], b = labels[[n]])) 258 labels <- labels[-1] 288 list(a = labels[[1]], b = labels[[n]])) 293 labels <- labels[-1] 309 labels = function(self, labels, panel_params) { argument 311 list(x = labels$y, y = labels$x) nameattr 313 labels 341 x <- squish_infinite(x, panel_params$theta.range) [all …]
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H A D | scale-.r | 141 labels = labels, 224 labels = labels, 585 self$range$train(x) 602 x <- self$rescale(self$oob(x, range = limits), limits) 604 uniq <- unique(x) 821 x 857 rescale(x, match(as.character(x), limits), from = range) 999 self$range$train(x) 1011 x 1016 x <- self$rescale(self$oob(x, range = limits), limits) [all …]
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/dports/math/R-cran-memisc/memisc/man/ |
H A D | labels.Rd | 28 using \code{labels(x)} and 30 using labels(x) <- value 37 labels(x) <- value 47 x <- as.item(rep(1:5,4), 59 labels(x) 60 labels(x) <- labels(x) - c("Second"=2) 61 labels(x) 62 labels(x) <- labels(x) + c("Second"=2) 63 labels(x) 67 x [all …]
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/dports/math/R-cran-memisc/memisc/R/ |
H A D | tibbles.R | 32 labels <- labels[!dup] 40 labels <- attr(x,"labels",exact=TRUE) functionVar 41 labels <- sanitize_labels(labels) 43 as.item(x,labels=labels, 64 labels <- attr(x,"labels",exact=TRUE) functionVar 67 as.item(x,labels=labels, 90 labels <- attr(x,"labels",exact=TRUE) functionVar 98 as.item(x,labels=labels, 137 labels(x) <- NULL 138 if(length(labels(x))){ [all …]
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/dports/misc/py-onnx/onnx-1.10.2/onnx/backend/test/case/node/ |
H A D | softmaxcrossentropy.py | 111 sce = softmaxcrossentropy(x, labels, reduction='none') 114 expect(node, inputs=[x, labels], outputs=[sce], name='test_sce_none') 156 sce = softmaxcrossentropy(x, labels, weight=weights, reduction='none') 201 sce = softmaxcrossentropy(x, labels, reduction='sum') 204 expect(node, inputs=[x, labels], outputs=[sce], name='test_sce_sum') 245 sce = softmaxcrossentropy(x, labels) 248 expect(node, inputs=[x, labels], outputs=[sce], name='test_sce_mean') 267 loss, log_prob = softmaxcrossentropy(x, labels, get_log_prob=True) 334 sce = softmaxcrossentropy(x, labels, weight=weights) 434 sce = softmaxcrossentropy(x, labels, ignore_index=ignore_index) [all …]
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/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/nodes/ |
H A D | classifier_nodes.py | 41 def _check_train_args(self, x, labels): argument 43 len(labels) != x.shape[0]): 51 if (not numx.all(map(lambda x: abs(x) == 1, labels))): 55 def _train(self, x, labels): argument 115 len(labels) != x.shape[0]): 123 def _train(self, x, labels): argument 377 len(labels) != x.shape[0]): 387 def _train(self, x, labels): argument 500 def _train(self, x, labels): argument 526 len(labels) != x.shape[0]): [all …]
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/dports/math/R-cran-haven/haven/R/ |
H A D | labelled.R | 41 labelled <- function(x = double(), labels = NULL, label = NULL) { argument 43 labels <- vec_cast_named(labels, x, x_arg = "labels", to_arg = "x") 44 validate_labelled(new_labelled(x, labels = labels, label = label)) 47 new_labelled <- function(x = double(), labels = NULL, label = NULL, argument 52 if (!is.null(labels) && !vec_is(labels, x)) { 60 labels = labels, 69 labels <- attr(x, "labels") functionVar 70 if (is.null(labels)) { 186 labels <- attr(x, "labels") functionVar 193 value <- if (is.double(labels)) format_tagged_na(labels) else unname(labels) [all …]
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H A D | as_factor.R | 45 x[] <- lapply(x, as_factor, ...) 48 x 66 labels <- attr(x, "labels") functionVar 70 names(labels) <- paste0("[", labels, "] ", names(labels)) 75 levs <- replace_with(vals, unname(labels), names(labels)) 77 levs <- sort(c(stats::setNames(vals, levs), labels), na.last = TRUE) 80 x <- replace_with(vec_data(x), unname(labels), names(labels)) 84 levs <- unname(labels) 85 labs <- names(labels) 89 if (all(x %in% labels)) { [all …]
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/dports/math/R-cran-terra/terra/R/ |
H A D | plot.R | 180 if (length(labels) != ncell(x)) { 183 i <- which(labels == names(x)) 188 x <- x[[labels]] 189 labels <- as.data.frame(x)[,1] 210 function(x, labels, halo=FALSE, ...) { argument 212 labels <- 1:nrow(x) 215 labels <- as.data.frame(x)[,labels] 218 if (labels %in% 1:ncol(x)) { 219 labels <- x[[labels]][,1] 221 } else if (labels %in% names(x)) { [all …]
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/dports/science/py-mdp/MDP-3.5/mdp/nodes/ |
H A D | classifier_nodes.py | 45 def _check_train_args(self, x, labels): argument 47 len(labels) != x.shape[0]): 55 if (not numx.all([abs(x) == 1 for x in labels])): 59 def _train(self, x, labels): argument 119 len(labels) != x.shape[0]): 127 def _train(self, x, labels): argument 381 len(labels) != x.shape[0]): 391 def _train(self, x, labels): argument 504 def _train(self, x, labels): argument 530 len(labels) != x.shape[0]): [all …]
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/dports/math/R-cran-car/car/R/ |
H A D | showLabels.R | 18 showLabels <- function(x, y, labels=NULL, method="identify", argument 26 res <- c(res, showLabels1(x, y, labels, meth, n, cex, 32 showLabels1 <- function(x, y, labels=NULL, id.method="identify", argument 36 if (is.null(labels)) labels <- names(x) 37 if (is.null(labels)) labels <- paste(seq_along(x)) 55 all <- list(labels=labels, subs=rep(TRUE, length(labels))) globalVar 56 names(all$labels) <- all$labels 72 result <- labels[identify(x, y, labels, n=length(x), 77 ismissing <- is.na(x) | is.na(y) | is.na(labels) 81 labels <- labels[!ismissing] [all …]
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/dports/math/maxima/maxima-5.43.2/tests/ |
H A D | rtestlabels.mac | 48 (map (lambda ([x], rulep(x)#false or fundefp(x)#false or macrodefp(x)#false), ''labels), 49 my_every (lambda ([x], substring (ensure_string (x), 1, 3) = ensure_string (linechar)), labels) 76 and my_every (lambda ([x], my_some (lambda ([y], buildq ([x, y], 'y = 'x)), labels)), L)); 84 * and each %t labels is on the labels infolist 91 and my_every (lambda ([x], my_some (lambda ([y], buildq ([x, y], 'y = 'x)), labels)), L), 165 /* Now there should be some labels which are not %t labels. 171 (map (lambda ([x], rulep(x)#false or fundefp(x)#false or macrodefp(x)#false), ''labels), 178 labels (inchar) # [] and my_every (?boundp, labels (inchar)) 203 and my_every (lambda ([x], my_some (lambda ([y], buildq ([x, y], 'y = 'x)), labels)), L)); 211 * and each %t labels is on the labels infolist [all …]
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/dports/sysutils/istio/istio-1.6.7/vendor/github.com/antlr/antlr4/scripts/ |
H A D | github_release_notes.py | 17 milestone = [x for x in repo.get_milestones() if x.title==MILESTONE] 26 labels = [l.name for l in x.labels] variable 27 if x.pull_request is None and not ("type:improvement" in labels or "type:feature" in labels): 28 print("* [%s](%s) (%s)" % (x.title, x.html_url, ", ".join([l.name for l in x.labels]))) 34 labels = [l.name for l in x.labels] variable 35 if ("type:improvement" in labels or "type:feature" in labels): 36 print("* [%s](%s) (%s)" % (x.title, x.html_url, ", ".join(labels))) 45 labels = [l.name for l in x.labels] variable 46 if x.pull_request is not None and f"target:{target}" in labels: 47 print("* [%s](%s) (%s)" % (x.title, x.html_url, ", ".join(labels))) [all …]
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/dports/math/R/R-4.1.2/src/library/stats/R/ |
H A D | monthplot.R | 22 function (x, labels = NULL, ylab = choice, choice = "sea", ...) argument 23 monthplot(fitted(x)[, choice], labels = labels, ylab = ylab, ...) 26 function (x, labels = NULL, ylab = choice, choice = "seasonal", ...) argument 27 monthplot(x$time.series[, choice], labels = labels, ylab = ylab, ...) 30 function (x, labels = NULL, times = time(x), phase = cycle(x), argument 36 labels <- 47 monthplot.default(x, labels = labels, times = times, phase = phase, 52 function (x, labels = 1L:12L, argument 62 if (is.null(labels) || (missing(labels) && !missing(phase))) { 73 Call$x <- NA [all …]
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/dports/math/libRmath/R-4.1.1/src/library/stats/R/ |
H A D | monthplot.R | 22 function (x, labels = NULL, ylab = choice, choice = "sea", ...) argument 23 monthplot(fitted(x)[, choice], labels = labels, ylab = ylab, ...) 26 function (x, labels = NULL, ylab = choice, choice = "seasonal", ...) argument 27 monthplot(x$time.series[, choice], labels = labels, ylab = ylab, ...) 30 function (x, labels = NULL, times = time(x), phase = cycle(x), argument 36 labels <- 47 monthplot.default(x, labels = labels, times = times, phase = phase, 52 function (x, labels = 1L:12L, argument 62 if (is.null(labels) || (missing(labels) && !missing(phase))) { 73 Call$x <- NA [all …]
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/dports/math/R/R-4.1.2/src/library/utils/R/ |
H A D | format.R | 23 if(!length(x)) 32 if(!length(x)) 39 len <- length(x) 55 labels <- as.character(as.roman(labels)) 57 labels <- tolower(labels) 59 .format_rl_table(sprintf("%s.", labels), x, offset, width) 63 function(labels, x, offset = 0, width = 0.9 * getOption("width"), argument 70 labels <- format(labels, justify = "right") 71 len <- length(x) 73 x <- strwrap(x, width = width - delta - nchar(sep, "width"), [all …]
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/dports/math/libRmath/R-4.1.1/src/library/utils/R/ |
H A D | format.R | 23 if(!length(x)) 32 if(!length(x)) 39 len <- length(x) 55 labels <- as.character(as.roman(labels)) 57 labels <- tolower(labels) 59 .format_rl_table(sprintf("%s.", labels), x, offset, width) 63 function(labels, x, offset = 0, width = 0.9 * getOption("width"), argument 70 labels <- format(labels, justify = "right") 71 len <- length(x) 73 x <- strwrap(x, width = width - delta - nchar(sep, "width"), [all …]
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/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/segmentation/include/pcl/segmentation/impl/ |
H A D | organized_connected_component_segmentation.hpp | 73 int x; in findLabeledRegionBoundary() local 78 x = curr_x + directions [dIdx].d_x; in findLabeledRegionBoundary() 81 …if (x >= 0 && x < int(labels->width) && y >= 0 && y < int(labels->height) && (*labels)[index].labe… in findLabeledRegionBoundary() 100 x = curr_x + directions [nIdx].d_x; in findLabeledRegionBoundary() 103 …if (x >= 0 && x < int(labels->width) && y >= 0 && y < int(labels->height) && (*labels)[index].labe… in findLabeledRegionBoundary() 131 if (std::isfinite ((*input_)[0].x)) in segment() 140 if (!std::isfinite ((*input_)[colIdx].x)) in segment() 144 labels[colIdx].label = labels[colIdx - 1].label; in segment() 159 if (std::isfinite ((*input_)[current_row].x)) in segment() 175 if (std::isfinite ((*input_)[current_row + colIdx].x)) in segment() [all …]
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/dports/finance/R-cran-quantmod/quantmod/R/ |
H A D | add_Last.R | 5 xdata <- x$Env$xdata 6 nr <- NROW(x$Env$xdata[x$Env$xsubset]) 11 if(!x$Env$theme$rylab) 45 lenv$plot_axis <- function(x,side,at,labels,tick,font,pos,col) { argument 46 xdata <- x$Env$xdata 50 nr <- NROW(x$Env$xdata[x$Env$xsubset]) 51 if(is.logical(labels) && labels==TRUE) { 54 labels <- labels[-dropped_label] 87 xdata <- x$Env$xdata 91 nr <- NROW(x$Env$xdata[x$Env$xsubset]) [all …]
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/dports/graphics/opencv/opencv-4.5.3/contrib/modules/ximgproc/src/ |
H A D | seeds.cpp | 650 labelA = labels[(y) * width + (x)]; in updatePixels() 651 labelB = labels[(y) * width + (x + 1)]; in updatePixels() 742 labelA = labels[(y) * width + (x)]; in updatePixels() 833 labelA = labels[x]; in updatePixels() 834 labelB = labels[width + x]; in updatePixels() 837 labelA = labels[(height - 1) * width + x]; in updatePixels() 838 labelB = labels[(height - 2) * width + x]; in updatePixels() 1020 count += (labels[y * width + x - 1] == label); in threebyfour() 1021 count += (labels[y * width + x + 2] == label); in threebyfour() 1075 count += (labels[y * width + x - 1] == label); in fourbythree() [all …]
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/dports/graphics/p5-Chart/Chart-2.4.10/Chart/ |
H A D | Split.pm | 174 $x = $x_start + $delta * $_ - ( $w * length( $labels[$_] ) ) / 2; 175 $self->{'gd_obj'}->string( $font, $x, $y_start, $labels[$_], $textcolor ); 185 $x = $x_start + $delta * ($_) - ( $w * length( $labels[$_] ) ) / 2; 186 $self->{'gd_obj'}->string( $font, $x, $y_start, $labels[$_], $textcolor ); 223 $x = $x_start + $delta * $_ - ( $w * ( length( $labels[$_] ) ) ) / 2; 228 $self->{'gd_obj'}->string( $font, $x, $y_start, $labels[$_], $textcolor ); 243 $x = $x_start + $delta * $_ - ( $w * ( length( $labels[$_] ) ) ) / 2; 248 $self->{'gd_obj'}->string( $font, $x, $y_start, $labels[$_], $textcolor ); 269 … $self->{'gd_obj'}->stringUp( $font, $x, $y, $labels[ $_ * $self->{'skip_x_ticks'} ], $textcolor ); 281 $self->{'gd_obj'}->stringUp( $font, $x, $y, $labels[$_], $textcolor ); [all …]
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/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/ |
H A D | classifier_node.py | 82 return x 107 def _check_train_args(self, x, labels): argument 108 super(ClassifierCumulator, self)._check_train_args(x, labels) 110 len(labels) != x.shape[0]): 112 "datapoints (%d != %d)" % (len(labels), x.shape[0])) 115 def _train(self, x, labels): argument 121 if isinstance(labels, (list, tuple, numx.ndarray)): 124 labels = [labels] * x.shape[0] 126 self.labels.extend(labels.ravel().tolist()) 132 self.labels = numx.array(self.labels) [all …]
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