Qu

xticks

Builtin index · Plotting

xticks(positions)

Input: positions · Output: no output

What it is

Sets explicit x tick positions from positions (Vec of numbers, data units), paired in order with xticklabels(...) when both are set. xticks(()) (empty) removes ticks entirely.

Overloads

One call shape — this function is not overloaded.

CodeInputOutputDescription
xticks(positions)
positions Vec or numbernot documented yet
no outputxticks(()) (empty) removes ticks entirely.

Examples

From the documentation, and run by the build -- the output and the figure below are what the engine actually produced. Simplest first.

Xc = randn(200, 2, seed = 41)
yc = zeros(200)
for i in 0 to 199
    if Xc[i, 0] + Xc[i, 1] > 0
        yc[i] = 1
    end if
end for
s = train_test_split(Xc, yc, test_size = 0.3, seed = 9)

function accuracy(model)
    yhat = model.predict(s.X_test)
    hit = yhat == s.y_test
    return len(yhat[hit]) / len(yhat)
end function

names = ("knn", "tree", "forest", "bayes")
scores = (
    accuracy(knn_model(s.X_train, s.y_train, 5, kind = "classification")),
    accuracy(tree_model(s.X_train, s.y_train, kind = "classification")),
    accuracy(random_forest_model(s.X_train, s.y_train, 40, seed = 3, kind = "classification")),
    accuracy(naive_bayes_model(s.X_train, s.y_train))
)
for i in 0 to 3
    print("{names[i]}: {round(scores[i], 3)}")
end for
bar(0 to 3, scores, color = "#4169e1", values = true)
xticks(0 to 3)
xticklabels(names)
ylim(0, 1)
ylabel("test accuracy")
title("held-out accuracy, same split")
output
knn: 0.983
tree: 0.95
forest: 0.967
bayes: 0.917
· bar: figure 10 (4 points)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 knn tree forest bayes x=-1.058, y=-0.826 x=0.594, y=0.636 x=0.88, y=1.305 x=-0.379, y=-0.489 x=0.152, y=1.215 x=1.407, y=0.754 x=0.231, y=-0.942 x=-1.291, y=-0.12 x=-0.085, y=-0.627 x=0.304, y=-0.101 x=0.037, y=0.004 x=-0.705, y=-0.429 x=0.241, y=-0.559 x=-0.582, y=-1.167 x=-0.277, y=-0.685 x=-1.636, y=-1.342 x=-0.865, y=-0.799 x=0.131, y=0.029 x=-1.581, y=-1.773 x=-2.048, y=-2.111 x=2.947, y=2.32 x=-0.456, y=-1.875 x=0.908, y=0.097 x=0.85, y=1.1 x=0.517, y=0.032 x=0.003, y=0.246 x=-0.201, y=0.212 x=0.466, y=-0.074 x=0.426, y=1.096 x=-0.066, y=-0.164 x=1.021, y=1.029 x=0.113, y=0.035 x=-0.998, y=-0.494 x=-0.066, y=-0.991 x=2.823, y=0.731 x=-0.046, y=-0.746 x=-0.029, y=-0.9 x=-0.031, y=0.196 x=-0.616, y=0.539 x=-1.349, y=-0.313 x=-1.085, y=-1.65 x=-1.452, y=-1.608 x=0.973, y=0.867 x=0.737, y=0.242 x=-0.185, y=0.468 x=1.175, y=1.485 x=-1.836, y=-0.822 x=-0.157, y=-0.076 x=0.407, y=0.307 x=-1.365, y=-1.022 x=-0.847, y=1.143 x=-0.762, y=0.021 x=-1.044, y=-0.505 x=0.478, y=1.123 x=0.316, y=-0.102 x=0.965, y=0.825 x=-0.751, y=-0.957 x=-0.988, y=-0.033 x=-1.22, y=-0.385 x=-0.681, y=-0.432 x=-0.621, y=0.256 x=0.918, y=0.744 x=1.182, y=-0.477 x=-0.039, y=0.425 x=0.585, y=-0.031 x=0.297, y=-0.535 x=0.112, y=-0.357 x=0.039, y=0.8 x=0.16, y=0.201 x=1.261, y=-0.955 x=0.95, y=0.238 x=-0.013, y=0.393 x=-1.577, y=-0.343 x=-0.67, y=-0.101 x=-0.631, y=-1.302 x=-0.84, y=-0.949 x=1.692, y=0.99 x=0.389, y=0.473 x=-0.261, y=-0.509 x=-0.491, y=-0.033 x=0.634, y=0.806 x=-0.342, y=0.622 x=-1.674, y=-1.63 x=0.039, y=-0.203 x=0.175, y=-0.688 x=0.206, y=0.293 x=1.405, y=0.994 x=-0.644, y=-0.672 x=-0.623, y=-0.7 x=1.569, y=0.384 x=-0.533, y=-0.154 x=0.682, y=-0.014 x=1.089, y=1.13 x=0.342, y=0.984 x=1.161, y=0.991 x=-0.232, y=0.289 x=-0.607, y=-0.737 x=0.295, y=0.07 x=0.275, y=0.25 x=-1.141, y=-0.456 x=0.461, y=0.554 x=-0.671, y=-0.906 x=0.513, y=1.154 x=0.499, y=-0.224 x=1.753, y=1.474 x=0.103, y=0.61 x=-0.351, y=0.258 x=0.553, y=-0.788 x=0.298, y=0.904 x=0.472, y=0.843 x=-0.94, y=-0.939 x=-1.062, y=-1.629 x=0.467, y=0.806 x=-0.653, y=-1.083 x=1.172, y=1.15 x=0.206, y=0.15 x=-1.077, y=-0.827 x=0.153, y=-0.987 x=0.202, y=0.439 x=0.011, y=-0.385 x=-0.67, y=0.029 x=1.367, y=0.502 x=0.955, y=0.531 x=0.352, y=0.238 x=1.543, y=0.703 x=-1.029, y=-0.474 x=0.104, y=0.508 x=0.877, y=-0.209 x=-1.366, y=-1.921 x=-1.583, y=-1.15 x=1.748, y=0.901 x=0.359, y=0.563 x=0.309, y=-0.002 x=1.322, y=1.929 x=-0.57, y=-0.79 x=-0.857, y=0.127 x=0.177, y=-0.37 x=-1.161, y=-1.563 x=0.371, y=1.281 x=-0.811, y=-1.39 x=0.168, y=1.089 x=-0.599, y=0.823 x=-0.452, y=-1.067 x=-1.241, y=-1.344 x=-0.711, y=-0.72 x=-0.233, y=-0.53 x=-0.344, y=0.761 x=1.152, y=0.27 x=0.989, y=0.896 x=0.308, y=0.67 x=-1.851, y=-1.723 x=0.866, y=0.926 x=-0.586, y=0.32 x=-0.204, y=-0.76 x=1.617, y=1.863 x=-0.897, y=-1.095 x=1.375, y=0.119 x=0.027, y=0.911 x=-0.268, y=-0.958 x=-0.58, y=-0.581 x=1.263, y=0.222 x=0.021, y=0.109 x=0.228, y=-0.664 x=0.002, y=-0.26 x=-0.301, y=0.237 x=0.646, y=0.863 x=0.272, y=-1.038 x=-0.432, y=-0.686 x=-0.123, y=1.22 x=0.844, y=1.163 x=-1.237, y=-1.157 x=2, y=1.132 x=-0.836, y=0.309 x=-0.332, y=-0.738 x=0.17, y=0.198 x=-0.327, y=0.587 x=-1.737, y=-1.131 x=-0.054, y=0.877 x=0.317, y=0.75 x=-1.406, y=-1.905 x=0.04, y=0.092 x=1.456, y=0.878 x=0.373, y=0.985 x=-0.912, y=-0.551 x=-0.104, y=0.042 x=0.349, y=0.549 x=1.098, y=0.24 x=0.588, y=-0.011 x=-0.164, y=-0.854 x=0.235, y=-0.679 x=-0.713, y=0.139 x=0.252, y=-0.404 x=-0.029, y=-0.281 x=-0.988, y=-0.818 x=0.223, y=-0.99 x=-0.591, y=0.839 x=-0.36, y=-0.088 x=-0.006, y=-0.156 x=-0.054, y=-0.158 x=0.644, y=-0.111 x=-3, y=-4.018 x=-2.75, y=-6.388 x=-2.5, y=-5.262 x=-2.25, y=0.293 x=-2, y=1.587 x=-1.75, y=1.194 x=-1.5, y=1.829 x=-1.25, y=2.719 x=-1, y=-0.145 x=-0.75, y=0.779 x=-0.5, y=-0.837 x=-0.25, y=2.101 x=0, y=0.378 x=0.25, y=1.148 x=0.5, y=1.019 x=0.75, y=-3.978 x=1, y=-3.731 x=1.25, y=-0.191 x=1.5, y=-1.178 x=1.75, y=-2.55 x=2, y=-0.452 x=2.25, y=4.657 x=2.5, y=0.591 x=2.75, y=5.418 x=3, y=6.826 x=-4.221, y=-3.675 x=-4.749, y=-4.599 x=-4.378, y=-5.049 x=-4.908, y=-2.938 x=-3.111, y=-4.705 x=-4.7, y=-3.185 x=-4.948, y=-4.24 x=-5.087, y=-4.991 x=-3.755, y=-2.658 x=-4.866, y=-3.893 x=-3.202, y=-4.799 x=-3.536, y=-4.59 x=-4.643, y=-4.655 x=-4.223, y=-3.8 x=-4.771, y=-4.791 x=-5.162, y=-3.624 x=-2.644, y=-3.501 x=-5.565, y=-4.823 x=-3.561, y=-2.64 x=-4.529, y=-4.524 x=-5.6, y=-5.042 x=-3.048, y=-3.184 x=-4.283, y=-4.206 x=-5.239, y=-4.032 x=-2.871, y=-5.062 x=-2.117, y=-2.96 x=-3.794, y=-3.873 x=-3.245, y=-4.153 x=-4.242, y=-4.691 x=-3.935, y=-4.681 x=-2.991, y=-2.757 x=-4.498, y=-3.651 x=-4.482, y=-5.712 x=-3.324, y=-4.723 x=-5.062, y=-5.077 x=-4.34, y=-4.914 x=-4.945, y=-5.731 x=-4.523, y=-3.545 x=-2.907, y=-3.457 x=-4.38, y=-3.659 x=3.22, y=4.412 x=3.089, y=4.062 x=2.827, y=3.584 x=3.848, y=5.345 x=4.196, y=4.669 x=3.111, y=4.336 x=2.961, y=3.91 x=5.036, y=4.596 x=5.339, y=4.031 x=4.874, y=2.505 x=4.357, y=2.791 x=3.318, y=5.241 x=2.544, y=3.948 x=6.731, y=3.889 x=4.101, y=4.456 x=3.18, y=2.902 x=4.415, y=7.292 x=3.9, y=6.008 x=3.342, y=4.252 x=2.138, y=4.074 x=3.304, y=4.752 x=4.53, y=4.152 x=3.264, y=4.913 x=3.885, y=2.94 x=5.542, y=3.917 x=1.488, y=3.061 x=2.847, y=3.236 x=3.93, y=3.488 x=2.913, y=2.598 x=3.839, y=4.13 x=2.508, y=3.961 x=2.846, y=4.195 x=4.278, y=4.197 x=4.971, y=5.339 x=4.568, y=5.297 x=3.797, y=3.895 x=3.459, y=4.494 x=4.285, y=3.369 x=3.836, y=2.999 x=2.123, y=1.312 x=-0.678, y=-0.737 x=-0.734, y=0.333 x=-0.016, y=1.204 x=0.605, y=0.633 x=0.426, y=-0.995 x=-0.383, y=0.403 x=-0.064, y=0.253 x=-1.862, y=-0.361 x=0.298, y=0.52 x=-1.481, y=-1.025 x=0.719, y=0.808 x=1.151, y=-0.726 x=-0.082, y=-0.357 x=-0.401, y=0.791 x=-0.182, y=0.737 x=0.394, y=0.021 x=0.954, y=0.671 x=0.405, y=0.336 x=-1.617, y=-0.65 x=-0.669, y=-1.147 x=-2.452, y=1.586 x=1.709, y=-0.65 x=0.122, y=-0.171 x=1.066, y=-1.195 x=0.053, y=-0.57 x=-0.396, y=-0.235 x=0.819, y=-0.788 x=0.012, y=0.012 x=-2.723, y=0.397 x=1.545, y=0.484 x=-1.119, y=0.98 x=-0.22, y=-0.804 x=-1.564, y=-1.293 x=-1.811, y=-0.276 x=0.774, y=-1.055 x=0.575, y=1.214 x=-0.348, y=-1.078 x=0.015, y=-0.404 x=0.245, y=-1.466 x=0.436, y=1.71 x=0, y=0.983 0.983 x=1, y=0.95 0.95 x=2, y=0.967 0.967 x=3, y=0.917 0.917 held-out accuracy, same split a test accuracy measured cubic fit measured forecast cluster 0 cluster 1 cluster 2 centroids

from statistics-ml

figure()
t = linspace(0, 1, 200)
plot(t, sin(2 * pi * 5 * t))
xticks([0, 0.5, 1])
xticklabels("start", "mid", "end")
yticks([-1, 0, 1])
yticklabels("low", "zero", "high")
fontfamily("sans")
fontsize(tick = 10, label = 12, title = 14)
figure_background("#f7f7f7")
colormap("viridis")
colorbar()
grid()
box()
subplot(1, 1, 1)
xscale("linear")
yscale("linear")
title("Styled panel")
output
· plot: figure 8 (200 points)
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Styled panel

from plotting

How it works

xticks(positions) — explicit tick positions, paired in order with xticklabels(...) when both are set (MATLAB semantics).

From the note above this builtin in the interpreter, where the reasoning was written down as it was built.