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"source": [
"## Vertex Sampling\n",
"Vertex sampling is designed for polygon simplification.\n",
"There is a choice of two implementation algorithms: **Douglas-Peucker** and **Visvalingam-Whyatt**."
]
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"source": [
"import numpy as np\n",
"\n",
"from lets_plot import *"
]
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"text/html": [
"\n",
" \n",
" \n",
" "
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"metadata": {},
"output_type": "display_data"
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"source": [
"LetsPlot.setup_html()"
]
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"source": [
"def f(x, y, n):\n",
" z = np.sin(x * 3 * np.pi / n)\n",
" z += np.sin(y * 3 * np.pi / n)\n",
" z += x * 3 / n\n",
" z += y * 5 / n\n",
" return z\n",
"\n",
"n = 50\n",
"x = np.arange(n)\n",
"y = np.arange(n)\n",
"X, Y = np.meshgrid(x, y)\n",
"Z = f(X, Y, n)\n",
"data = dict(\n",
" x=X.reshape(-1),\n",
" y=Y.reshape(-1),\n",
" z=Z.reshape(-1))"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"execution": {
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"text/html": [
" \n",
" "
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"text/plain": [
""
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"p = ggplot(data, aes('x','y', z='z')) \\\n",
"+ theme_void() + ggsize(200, 200)\n",
"p + geom_contour()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"execution": {
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" \n",
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"text/plain": [
""
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},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"# Douglas-Peucker algorithm in this case works better than others. \n",
"# The lines become ragged but the shape remained unchanged.\n",
"p + geom_contour(sampling=sampling_vertex_dp(200))"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"execution": {
"iopub.execute_input": "2024-04-17T07:27:39.276064Z",
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"data": {
"text/html": [
" \n",
" "
],
"text/plain": [
""
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Visvalingam-Whyatt algorithm is less accurate with rings: they became unclosed.\n",
"p + geom_contour(sampling=sampling_vertex_vw(200))"
]
}
],
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