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Add pairwise_linestring_intersection example in user guide #989

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merged 3 commits into from
Mar 21, 2023
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Add pairwise_linestring_intersection example in user guide #989

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9934234
add intersection example
isVoid Mar 11, 2023
f9c1444
address review comments
isVoid Mar 14, 2023
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Merge branch 'branch-23.04' into notebook/intersection_example
isVoid Mar 20, 2023
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188 changes: 181 additions & 7 deletions docs/source/user_guide/cuspatial_api_examples.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -954,6 +954,180 @@
"With some careful grouping, one can reconstruct the original complete polygons that fall within the range."
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]
},
{
"cell_type": "markdown",
"id": "3b33ce2b-965f-42a1-a89e-66d7ca80d907",
"metadata": {},
"source": [
"## Set Operations"
]
},
{
"cell_type": "markdown",
"id": "d73548f3-c9bb-43ff-9788-858f3b7d08e4",
"metadata": {},
"source": [
"### Linestring Intersections\n",
"\n",
"cuSpatial provides a linestring-linestring intersection algorithm to compute the overlapping geometries between two linestrings.\n",
"The API also returns the ids for each returned geometry to help user to trace back the source geometry."
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "cc72a44d-a9bf-4432-9898-de899ac45869",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from cuspatial.core.binops.intersection import pairwise_linestring_intersection\n",
"\n",
"host_dataframe = geopandas.read_file(geopandas.datasets.get_path(\"naturalearth_lowres\"))\n",
"usa_boundary = cuspatial.from_geopandas(host_dataframe[host_dataframe.name == \"United States of America\"].geometry.boundary)\n",
"canada_boundary = cuspatial.from_geopandas(host_dataframe[host_dataframe.name == \"Canada\"].geometry.boundary)\n",
"\n",
"list_offsets, geometries, look_back_ids = pairwise_linestring_intersection(usa_boundary, canada_boundary)"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "1125fd17-afe1-4b9c-b48d-8842dd3700b3",
"metadata": {
"tags": []
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"outputs": [
{
"data": {
"text/plain": [
"<cudf.core.column.numerical.NumericalColumn object at 0x7f7e750a5340>\n",
"[\n",
" 0,\n",
" 144\n",
"]\n",
"dtype: int32"
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},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# The first integer series shows that the result contains 1 row (since we only have 1 pair of linestrings as input).\n",
"# This row contains 144 geometires.\n",
"list_offsets"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "b281e3bb-42d4-4d60-9cb2-b7dcc20b4776",
"metadata": {
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},
"outputs": [
{
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"text/plain": [
"0 POINT (-130.53611 54.80275)\n",
"1 POINT (-130.53611 54.80278)\n",
"2 POINT (-130.53611 54.80275)\n",
"3 POINT (-129.98000 55.28500)\n",
"4 POINT (-130.53611 54.80278)\n",
" ... \n",
"139 LINESTRING (-113.00000 49.00000, -113.00000 49...\n",
"140 LINESTRING (-83.89077 46.11693, -83.61613 46.1...\n",
"141 LINESTRING (-116.04818 49.00000, -116.04818 49...\n",
"142 LINESTRING (-120.00000 49.00000, -117.03121 49...\n",
"143 LINESTRING (-122.84000 49.00000, -120.00000 49...\n",
"Length: 144, dtype: geometry"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# The second element is a geoseries that contains the intersecting geometries, with 144 rows, including points and linestrings.\n",
"geometries"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "e19873b9-2614-4242-ad67-caa47f807d04",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
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"\n",
" .dataframe tbody tr th {\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>lhs_linestring_id</th>\n",
" <th>lhs_segment_id</th>\n",
" <th>rhs_linestring_id</th>\n",
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"text/plain": [
" lhs_linestring_id \\\n",
"0 [8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, ... \n",
"\n",
" lhs_segment_id \\\n",
"0 [18, 16, 18, 15, 17, 137, 14, 16, 13, 15, 14, ... \n",
"\n",
" rhs_linestring_id \\\n",
"0 [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ... \n",
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"execution_count": 21,
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"source": [
"# The third element is a dataframe that contains IDs to the input segments and linestrings, 4 for each result row.\n",
"# Each represents ids to lhs, rhs linestring and segment ids.\n",
"look_back_ids"
]
},
{
"cell_type": "markdown",
"id": "a17bd64a",
Expand All @@ -976,7 +1150,7 @@
},
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Expand All @@ -993,7 +1167,7 @@
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Expand Down Expand Up @@ -1078,7 +1252,7 @@
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Expand Down Expand Up @@ -1142,7 +1316,7 @@
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Expand Down Expand Up @@ -1201,7 +1375,7 @@
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Expand All @@ -1216,7 +1390,7 @@
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Expand Down Expand Up @@ -1301,7 +1475,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.16"
"version": "3.10.9"
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"interpreter": {
Expand Down