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/dports/math/R-cran-raster/raster/R/
H A Dtext.R35 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 …]
/dports/math/py-pymc3/pymc-3.11.4/pymc3/glm/
H A Dutils.py20 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 …]
/dports/graphics/R-cran-ggplot2/ggplot2/R/
H A Dlabeller.r245 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 …]
H A Dcoord-polar.r126 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$theta.range)
[all …]
H A Dscale-.r141 labels = labels,
224 labels = labels,
585 self$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 …]
/dports/math/R-cran-memisc/memisc/man/
H A Dlabels.Rd28 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 …]
/dports/math/R-cran-memisc/memisc/R/
H A Dtibbles.R32 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 …]
/dports/misc/py-onnx/onnx-1.10.2/onnx/backend/test/case/node/
H A Dsoftmaxcrossentropy.py111 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 …]
/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/nodes/
H A Dclassifier_nodes.py41 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 …]
/dports/math/R-cran-haven/haven/R/
H A Dlabelled.R41 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 …]
H A Das_factor.R45 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 …]
/dports/math/R-cran-terra/terra/R/
H A Dplot.R180 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 …]
/dports/science/py-mdp/MDP-3.5/mdp/nodes/
H A Dclassifier_nodes.py45 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 …]
/dports/math/R-cran-car/car/R/
H A DshowLabels.R18 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 …]
/dports/math/maxima/maxima-5.43.2/tests/
H A Drtestlabels.mac48 (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 …]
/dports/sysutils/istio/istio-1.6.7/vendor/github.com/antlr/antlr4/scripts/
H A Dgithub_release_notes.py17 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 …]
/dports/math/R/R-4.1.2/src/library/stats/R/
H A Dmonthplot.R22 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$x <- NA
[all …]
/dports/math/libRmath/R-4.1.1/src/library/stats/R/
H A Dmonthplot.R22 function (x, labels = NULL, ylab = choice, choice = "sea", ...) argument
23 monthplot(fitted(x)[, choice], labels = labels, ylab = ylab, ...)
26 function (x, labels = NULL, ylab = choice, choice = "seasonal", ...) argument
27 monthplot(x$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$x <- NA
[all …]
/dports/math/R/R-4.1.2/src/library/utils/R/
H A Dformat.R23 if(!length(x))
32 if(!length(x))
39 len <- length(x)
55 labels <- as.character(as.roman(labels))
57 labels <- tolower(labels)
59 .format_rl_table(sprintf("%s.", labels), x, offset, width)
63 function(labels, x, offset = 0, width = 0.9 * getOption("width"), argument
70 labels <- format(labels, justify = "right")
71 len <- length(x)
73 x <- strwrap(x, width = width - delta - nchar(sep, "width"),
[all …]
/dports/math/libRmath/R-4.1.1/src/library/utils/R/
H A Dformat.R23 if(!length(x))
32 if(!length(x))
39 len <- length(x)
55 labels <- as.character(as.roman(labels))
57 labels <- tolower(labels)
59 .format_rl_table(sprintf("%s.", labels), x, offset, width)
63 function(labels, x, offset = 0, width = 0.9 * getOption("width"), argument
70 labels <- format(labels, justify = "right")
71 len <- length(x)
73 x <- strwrap(x, width = width - delta - nchar(sep, "width"),
[all …]
/dports/graphics/pcl-pointclouds/pcl-pcl-1.12.0/segmentation/include/pcl/segmentation/impl/
H A Dorganized_connected_component_segmentation.hpp73 int x; in findLabeledRegionBoundary() local
78 x = curr_x + directions [dIdx].d_x; in findLabeledRegionBoundary()
81 …if (x >= 0 && x < int(labels->width) && y >= 0 && y < int(labels->height) && (*labels)[index].labe… in findLabeledRegionBoundary()
100 x = curr_x + directions [nIdx].d_x; in findLabeledRegionBoundary()
103 …if (x >= 0 && x < int(labels->width) && y >= 0 && y < int(labels->height) && (*labels)[index].labe… in findLabeledRegionBoundary()
131 if (std::isfinite ((*input_)[0].x)) in segment()
140 if (!std::isfinite ((*input_)[colIdx].x)) in segment()
144 labels[colIdx].label = labels[colIdx - 1].label; in segment()
159 if (std::isfinite ((*input_)[current_row].x)) in segment()
175 if (std::isfinite ((*input_)[current_row + colIdx].x)) in segment()
[all …]
/dports/finance/R-cran-quantmod/quantmod/R/
H A Dadd_Last.R5 xdata <- x$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 …]
/dports/graphics/opencv/opencv-4.5.3/contrib/modules/ximgproc/src/
H A Dseeds.cpp650 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 …]
/dports/graphics/p5-Chart/Chart-2.4.10/Chart/
H A DSplit.pm174 $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 …]
/dports/science/afni/afni-AFNI_21.3.16/src/pkundu/meica.libs/mdp/
H A Dclassifier_node.py82 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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