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kstrempel/CirclesUnionMultipolygon.ipynb

Created June 22, 2018 14:01
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CirclesUnionMultipolygon.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 41,
"metadata": {},
"outputs": [],
"source": [
"import shapely as sp\n",
"import geopandas as gp"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's join two overlapping circles"
]
},
{
"cell_type": "code",
"execution_count": 42,
"metadata": {},
"outputs": [],
"source": [
"circle1 = sp.geometry.Point(1,1).buffer(1.5)\n",
"circle2 = sp.geometry.Point(3,1).buffer(1.5)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x11714fd68>"
]
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs = gp.GeoSeries()\n",
"gs['c1'] = circle1\n",
"gs['c2'] = circle2\n",
"gs.plot(cmap='OrRd')"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"data": {
"image/svg+xml": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"100.0\" height=\"100.0\" viewBox=\"-0.7 -0.7 5.4 3.4000000000000004\" preserveAspectRatio=\"xMinYMin meet\"><g transform=\"matrix(1,0,0,-1,0,2.0)\"><path fill-rule=\"evenodd\" fill=\"#66cc99\" stroke=\"#555555\" stroke-width=\"0.10800000000000001\" opacity=\"0.6\" d=\"M 2.0,-0.11563934674467752 L 1.9515899262454695,-0.15951568004410444 L 1.8333553495294048,-0.2472044184538169 L 1.7070951052389978,-0.32288189652253174 L 1.5740251485476362,-0.38581929876692955 L 1.4354270158816953,-0.4354105035983127 L 1.2926354830241944,-0.4711779206048452 L 1.147025710494343,-0.49277709000829506 L 1.0000000000000024,-0.5 L 0.8529742895056617,-0.4927770900082955 L 0.7073645169758103,-0.4711779206048461 L 0.5645729841183093,-0.43541050359831424 L 0.42597485145236824,-0.38581929876693133 L 0.29290489476100645,-0.3228818965225342 L 0.1666446504705994,-0.24720441845381957 L 0.0484100737545341,-0.15951568004410732 L -0.060660171779819194,-0.06066017177982341 L -0.15951568004410355,0.04841007375452977 L -0.24720441845381647,0.1666446504705945 L -0.3228818965225315,0.29290489476100146 L -0.38581929876692933,0.42597485145236336 L -0.4354105035983127,0.5645729841183046 L -0.4711779206048452,0.7073645169758058 L -0.4927770900082953,0.8529742895056575 L -0.5,0.9999999999999984 L -0.4927770900082953,1.1470257104943395 L -0.4711779206048461,1.2926354830241913 L -0.43541050359831357,1.4354270158816926 L -0.38581929876693044,1.574025148547634 L -0.32288189652253285,1.707095105238996 L -0.24720441845381824,1.8333553495294028 L -0.15951568004410577,1.951589926245468 L -0.060660171779821415,2.060660171779821 L 0.0484100737545311,2.159515680044105 L 0.16664465047059562,2.247204418453817 L 0.292904894761002,2.3228818965225315 L 0.42597485145236325,2.385819298766929 L 0.5645729841183038,2.4354105035983125 L 0.7073645169758044,2.4711779206048448 L 0.8529742895056553,2.492777090008295 L 0.9999999999999958,2.5 L 1.1470257104943362,2.4927770900082957 L 1.292635483024187,2.4711779206048465 L 1.435427015881688,2.435410503598315 L 1.5740251485476289,2.3858192987669327 L 1.7070951052389904,2.322881896522536 L 1.8333553495293973,2.247204418453822 L 1.9515899262454623,2.15951568004411 L 2.0,2.1156393467446777 L 2.048410073754531,2.159515680044105 L 2.1666446504705954,2.247204418453817 L 2.2929048947610022,2.3228818965225315 L 2.4259748514523634,2.385819298766929 L 2.564572984118304,2.4354105035983125 L 2.7073645169758045,2.4711779206048448 L 2.8529742895056556,2.492777090008295 L 2.9999999999999956,2.5 L 3.147025710494336,2.4927770900082957 L 3.292635483024187,2.4711779206048465 L 3.4354270158816878,2.435410503598315 L 3.574025148547629,2.3858192987669327 L 3.7070951052389907,2.322881896522536 L 3.8333553495293975,2.247204418453822 L 3.9515899262454623,2.15951568004411 L 4.060660171779816,2.060660171779827 L 4.1595156800441,1.951589926245475 L 4.247204418453813,1.833355349529411 L 4.322881896522528,1.707095105239005 L 4.3858192987669256,1.5740251485476442 L 4.435410503598311,1.435427015881704 L 4.471177920604843,1.2926354830242035 L 4.492777090008294,1.1470257104943526 L 4.5,1.0000000000000124 L 4.5,1.0 L 4.492777090008295,0.8529742895056592 L 4.471177920604846,0.7073645169758078 L 4.435410503598313,0.5645729841183068 L 4.385819298766931,0.4259748514523659 L 4.322881896522533,0.29290489476100423 L 4.247204418453818,0.1666446504705974 L 4.159515680044106,0.048410073754532545 L 4.060660171779823,-0.060660171779820526 L 3.9515899262454695,-0.15951568004410444 L 3.8333553495294046,-0.2472044184538169 L 3.7070951052389978,-0.32288189652253174 L 3.574025148547636,-0.38581929876692955 L 3.4354270158816953,-0.4354105035983127 L 3.2926354830241946,-0.4711779206048452 L 3.147025710494343,-0.49277709000829506 L 3.000000000000002,-0.5 L 2.852974289505662,-0.4927770900082955 L 2.7073645169758103,-0.4711779206048461 L 2.564572984118309,-0.43541050359831424 L 2.4259748514523682,-0.38581929876693133 L 2.2929048947610067,-0.3228818965225342 L 2.1666446504705994,-0.24720441845381957 L 2.048410073754534,-0.15951568004410732 L 2.0,-0.11563934674467752 z\" /></g></svg>"
],
"text/plain": [
"<shapely.geometry.polygon.Polygon at 0x1171f40b8>"
]
},
"execution_count": 44,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"union = circle1.union(circle2)\n",
"union"
]
},
{
"cell_type": "code",
"execution_count": 45,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Polygon'"
]
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"union.geom_type"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's try two disjunkt circles"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [],
"source": [
"circle1 = sp.geometry.Point(1,1).buffer(1.5)\n",
"circle2 = sp.geometry.Point(4,1).buffer(1.5)"
]
},
{
"cell_type": "code",
"execution_count": 48,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"circle1.intersects(circle2)"
]
},
{
"cell_type": "code",
"execution_count": 49,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1172a6c18>"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs = gp.GeoSeries()\n",
"gs['c1'] = circle1\n",
"gs['c2'] = circle2\n",
"gs['intersection'] = circle1.intersection(circle2)\n",
"gs.plot(cmap='OrRd')"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [],
"source": [
"union = circle1.union(circle2)"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1171cf518>"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs = gp.GeoSeries()\n",
"gs['union'] = union\n",
"gs.plot(cmap='OrRd')"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"data": {
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],
"text/plain": [
"<shapely.geometry.multipolygon.MultiPolygon at 0x11714f518>"
]
},
"execution_count": 56,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"union"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'MultiPolygon'"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"union.geom_type"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"2"
]
},
"execution_count": 53,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(union)"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.axes._subplots.AxesSubplot at 0x1173ffcf8>"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"gs = gp.GeoSeries()\n",
"gs['circle1'] = union[0]\n",
"gs['circle2'] = union[1]\n",
"gs.plot(cmap='OrRd')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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