From cfb5f524c75cfb023e996865179e353071b1097b Mon Sep 17 00:00:00 2001 From: Kristin Cowalcijk Date: Sat, 4 Sep 2021 19:02:36 +0800 Subject: [PATCH] Migrated python examples to Python 3 --- example/h3/h3demo.ipynb | 42 +++--- example/notebook/fmm_example.ipynb | 163 +++++++++++++++++------ example/notebook/post_processing.ipynb | 87 ++++++------ example/notebook/stmatch_example.ipynb | 67 +++++----- example/osmnx_example/map_matching.ipynb | 78 +++++------ example/python/fmm_test.py | 10 +- example/web_demo/mapmatcher.py | 42 +++--- 7 files changed, 291 insertions(+), 198 deletions(-) diff --git a/example/h3/h3demo.ipynb b/example/h3/h3demo.ipynb index b65c3f3..c9ffc21 100644 --- a/example/h3/h3demo.ipynb +++ b/example/h3/h3demo.ipynb @@ -48,15 +48,15 @@ "output_type": "stream", "text": [ "0\n", - "[618737091877535743, 618737091842146303, 618737091929178111, 618737091479863295, 618737091474358271]\n", - "MULTIPOLYGON(((18.0228898614 59.3354770125,18.0215924168 59.3365311866,18.0216285645 59.3383172704,18.0229621748 59.3390492484,18.0242596721 59.3379950872,18.0242235064 59.3362089351,18.0228898614 59.3354770125)),((18.0375257823 59.3417433897,18.0362279618 59.3427977119,18.036264136 59.3445842599,18.0375981486 59.3453165539,18.0388960218 59.3442622446,18.0388598297 59.3424756284,18.0375257823 59.3417433897)),((18.0430068757 59.3518196531,18.0417088444 59.3528739237,18.0417449583 59.3546607271,18.0430791214 59.3553933281,18.0443772054 59.3543390705,18.0443410735 59.3525521988,18.0430068757 59.3518196531)),((18.057648911 59.3580921665,18.0563505038 59.3591465851,18.056386644 59.3609338529,18.0577212093 59.3616667704,18.0590196693 59.3606123647,18.0589835112 59.3588250286,18.057648911 59.3580921665)),((18.065330875 59.3464027176,18.0640324062 59.3474574216,18.0640686964 59.349244775,18.0654034733 59.3499774928,18.0667019948 59.3489228018,18.0666656867 59.3471353801,18.065330875 59.3464027176)))\n" + "[617143120668917759, 617143120671277055, 617143120852942847, 617143120855302143, 617143120799465471]\n", + "MULTIPOLYGON(((18.0211916733 59.3369815178,18.0212055052 59.3355269148,18.0240881588 59.3348632699,18.0269570804 59.3356541999,18.0269434066 59.3371088063,18.0240606532 59.3377724792,18.0211916733 59.3369815178)),((18.0355106845 59.3438444663,18.0355241243 59.3423900552,18.0384070386 59.3417261983,18.0412766128 59.3425167245,18.0412633312 59.3439711389,18.0383803171 59.3446350238,18.0355106845 59.3438444663)),((18.0382867688 59.3548145103,18.038300135 59.3533604315,18.0411836259 59.3526966904,18.0440538504 59.353487,18.0440406424 59.3549410822,18.0411570517 59.3556048513,18.0382867688 59.3548145103)),((18.052613227 59.3616733077,18.0526262008 59.3602194209,18.0555099521 59.3595554677,18.0583808293 59.3603453732,18.0583680137 59.3617992633,18.0554841627 59.3624632446,18.052613227 59.3616733077)),((18.0613409429 59.3509568719,18.061353674 59.349502646,18.0642367705 59.3488383211,18.0671072356 59.3496281941,18.0670946627 59.3510824233,18.0642114666 59.3517467763,18.0613409429 59.3509568719)))\n" ] } ], "source": [ - "print result.traj_id\n", - "print list(result.hexs)\n", - "print hexs2wkt(result.hexs)" + "print(result.traj_id)\n", + "print(list(result.hexs))\n", + "print(hexs2wkt(result.hexs))" ] }, { @@ -81,7 +81,7 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -106,12 +106,12 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 7, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -134,12 +134,12 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 8, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -161,12 +161,12 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 9, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -188,12 +188,12 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 10, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -237,7 +237,7 @@ "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", "text/plain": [ "
" ] @@ -283,23 +283,23 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.15" + "pygments_lexer": "ipython3", + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/example/notebook/fmm_example.ipynb b/example/notebook/fmm_example.ipynb index 4cbaf4e..5c4ad85 100644 --- a/example/notebook/fmm_example.ipynb +++ b/example/notebook/fmm_example.ipynb @@ -38,7 +38,7 @@ ], "source": [ "network = Network(\"../data/edges.shp\")\n", - "print \"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count())\n", + "print(\"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count()))\n", "graph = NetworkGraph(network)" ] }, @@ -78,13 +78,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Time takes 0.009seconds\n" + "Status: success\n", + "Time takes 0.01 seconds\n", + "\n" ] } ], "source": [ "status = ubodt_gen.generate_ubodt(\"../data/ubodt.txt\", 4, binary=False, use_omp=True)\n", - "print status" + "print(status)" ] }, { @@ -96,7 +98,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -112,7 +114,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -128,7 +130,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -153,17 +155,15 @@ ] }, { - "cell_type": "code", - "execution_count": 7, + "cell_type": "raw", "metadata": {}, - "outputs": [], "source": [ "wkt = \"LINESTRING(0.200812146892656 2.14088983050848,1.44262005649717 2.14879943502825,3.06408898305084 2.16066384180791,3.06408898305084 2.7103813559322,3.70872175141242 2.97930790960452,4.11606638418078 2.62337570621469)\"" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -172,15 +172,15 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Matched path: [8L, 11L, 13L, 18L, 20L, 24L]\n", - "Matched edge for each point: [8L, 11L, 18L, 18L, 20L, 24L]\n", + "Matched path: [8, 11, 13, 18, 20, 24]\n", + "Matched edge for each point: [8, 11, 18, 18, 20, 24]\n", "Matched edge index [0, 1, 3, 3, 4, 5]\n", "Matched geometry: LINESTRING(0.20081215 2,1 2,2 2,3 2,3 3,4 3,4 2.6233757)\n", "Matched point LINESTRING(0.20081215 2,1.4426201 2,3 2.1606638,3 2.7103814,3.7087218 3,4 2.6233757)\n" @@ -188,11 +188,11 @@ } ], "source": [ - "print \"Matched path: \", list(result.cpath)\n", - "print \"Matched edge for each point: \", list(result.opath)\n", - "print \"Matched edge index \",list(result.indices)\n", - "print \"Matched geometry: \",result.mgeom.export_wkt()\n", - "print \"Matched point \", result.pgeom.export_wkt()" + "print(\"Matched path: \", list(result.cpath))\n", + "print(\"Matched edge for each point: \", list(result.opath))\n", + "print(\"Matched edge index \",list(result.indices))\n", + "print(\"Matched geometry: \",result.mgeom.export_wkt())\n", + "print(\"Matched point \", result.pgeom.export_wkt())" ] }, { @@ -204,7 +204,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -215,7 +215,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 13, "metadata": {}, "outputs": [], "source": [ @@ -226,7 +226,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -284,7 +284,7 @@ " 0.442620\n", " 1.241808\n", " 0.956684\n", - " 0.999980\n", + " 1.000000\n", " \n", " \n", " 2\n", @@ -336,13 +336,13 @@ "\n", " tp \n", "0 0.000000 \n", - "1 0.999980 \n", + "1 1.000000 \n", "2 0.943813 \n", "3 1.000000 \n", "4 0.699640 " ] }, - "execution_count": 19, + "execution_count": 14, "metadata": {}, "output_type": "execute_result" } @@ -360,7 +360,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -369,7 +369,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 16, "metadata": {}, "outputs": [], "source": [ @@ -380,7 +380,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -399,12 +399,12 @@ } ], "source": [ - "print input_config.to_string()" + "print(input_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 18, "metadata": {}, "outputs": [ { @@ -420,12 +420,12 @@ "result_config = ResultConfig()\n", "result_config.file = \"../data/mr.txt\"\n", "result_config.output_config.write_opath = True\n", - "print result_config.to_string()" + "print(result_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ @@ -434,22 +434,103 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 20, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Time takes 0.05 seconds\n", + "Status: success\n", + "Time takes 0 seconds\n", "Total points 17 matched 17\n", - "Map match speed 340 points/s \n", + "Total trajectories 3 matched 3\n", + "Map match percentage 1\n", + "Map match speed inf points/s \n", "\n" ] } ], "source": [ - "print status" + "print(status)" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on function add_edge in module fmm:\n", + "\n", + "add_edge(self, edge_id, source, target, geom)\n", + "\n" + ] + } + ], + "source": [ + "help(Network.add_edge)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [], + "source": [ + "import fmm" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [], + "source": [ + "ls = fmm.LineString()" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Help on method add_point in module fmm:\n", + "\n", + "add_point(*args) method of fmm.LineString instance\n", + "\n" + ] + } + ], + "source": [ + "help(ls.add_point)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'LINESTRING()'" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "ls.export_wkt()" ] }, { @@ -462,21 +543,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.16" + "pygments_lexer": "ipython3", + "version": "3.8.5" }, "toc": { "base_numbering": 1, @@ -493,5 +574,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/example/notebook/post_processing.ipynb b/example/notebook/post_processing.ipynb index 6ebb403..c7104ac 100644 --- a/example/notebook/post_processing.ipynb +++ b/example/notebook/post_processing.ipynb @@ -20,7 +20,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -29,7 +29,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -38,7 +38,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -57,7 +57,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -73,7 +73,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -89,7 +89,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 7, "metadata": {}, "outputs": [ { @@ -137,7 +137,7 @@ " 1.0\n", " 2.0\n", " 0.0\n", - " LINESTRING (2 1, 2 0)\n", + " LINESTRING (2.00000 1.00000, 2.00000 0.00000)\n", " \n", " \n", " 1\n", @@ -150,7 +150,7 @@ " 0.0\n", " 2.0\n", " 1.0\n", - " LINESTRING (2 0, 2 1)\n", + " LINESTRING (2.00000 0.00000, 2.00000 1.00000)\n", " \n", " \n", " 2\n", @@ -163,7 +163,7 @@ " 1.0\n", " 2.0\n", " 1.0\n", - " LINESTRING (3 1, 2 1)\n", + " LINESTRING (3.00000 1.00000, 2.00000 1.00000)\n", " \n", " \n", " 3\n", @@ -176,7 +176,7 @@ " 1.0\n", " 3.0\n", " 1.0\n", - " LINESTRING (4 1, 3 1)\n", + " LINESTRING (4.00000 1.00000, 3.00000 1.00000)\n", " \n", " \n", " 4\n", @@ -189,22 +189,29 @@ " 1.0\n", " 2.0\n", " 2.0\n", - " LINESTRING (2 1, 2 2)\n", + " LINESTRING (2.00000 1.00000, 2.00000 2.00000)\n", " \n", " \n", "\n", "" ], "text/plain": [ - " _uid_ id source target cost x1 y1 x2 y2 geometry\n", - "0 1 1 1 2 1.0 2.0 1.0 2.0 0.0 LINESTRING (2 1, 2 0)\n", - "1 2 2 2 1 1.0 2.0 0.0 2.0 1.0 LINESTRING (2 0, 2 1)\n", - "2 3 3 3 1 1.0 3.0 1.0 2.0 1.0 LINESTRING (3 1, 2 1)\n", - "3 4 4 4 3 1.0 4.0 1.0 3.0 1.0 LINESTRING (4 1, 3 1)\n", - "4 5 5 1 5 1.0 2.0 1.0 2.0 2.0 LINESTRING (2 1, 2 2)" + " _uid_ id source target cost x1 y1 x2 y2 \\\n", + "0 1 1 1 2 1.0 2.0 1.0 2.0 0.0 \n", + "1 2 2 2 1 1.0 2.0 0.0 2.0 1.0 \n", + "2 3 3 3 1 1.0 3.0 1.0 2.0 1.0 \n", + "3 4 4 4 3 1.0 4.0 1.0 3.0 1.0 \n", + "4 5 5 1 5 1.0 2.0 1.0 2.0 2.0 \n", + "\n", + " geometry \n", + "0 LINESTRING (2.00000 1.00000, 2.00000 0.00000) \n", + "1 LINESTRING (2.00000 0.00000, 2.00000 1.00000) \n", + "2 LINESTRING (3.00000 1.00000, 2.00000 1.00000) \n", + "3 LINESTRING (4.00000 1.00000, 3.00000 1.00000) \n", + "4 LINESTRING (2.00000 1.00000, 2.00000 2.00000) " ] }, - "execution_count": 8, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -217,7 +224,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -226,7 +233,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -235,7 +242,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -286,7 +293,7 @@ " 0.0\n", " 2.0\n", " 1.0\n", - " LINESTRING (2 0, 2 1)\n", + " LINESTRING (2.00000 0.00000, 2.00000 1.00000)\n", " 2\n", " \n", " \n", @@ -301,7 +308,7 @@ " 1.0\n", " 2.0\n", " 1.0\n", - " LINESTRING (3 1, 2 1)\n", + " LINESTRING (3.00000 1.00000, 2.00000 1.00000)\n", " 2\n", " \n", " \n", @@ -316,7 +323,7 @@ " 1.0\n", " 3.0\n", " 1.0\n", - " LINESTRING (4 1, 3 1)\n", + " LINESTRING (4.00000 1.00000, 3.00000 1.00000)\n", " 2\n", " \n", " \n", @@ -331,7 +338,7 @@ " 1.0\n", " 2.0\n", " 2.0\n", - " LINESTRING (2 1, 2 2)\n", + " LINESTRING (2.00000 1.00000, 2.00000 2.00000)\n", " 2\n", " \n", " \n", @@ -346,7 +353,7 @@ " 2.0\n", " 1.0\n", " 2.0\n", - " LINESTRING (0 2, 1 2)\n", + " LINESTRING (0.00000 2.00000, 1.00000 2.00000)\n", " 2\n", " \n", " \n", @@ -361,15 +368,15 @@ "3 4 5 5 1 5 1.0 2.0 1.0 2.0 2.0 \n", "4 7 8 8 7 8 1.0 0.0 2.0 1.0 2.0 \n", "\n", - " geometry points \n", - "0 LINESTRING (2 0, 2 1) 2 \n", - "1 LINESTRING (3 1, 2 1) 2 \n", - "2 LINESTRING (4 1, 3 1) 2 \n", - "3 LINESTRING (2 1, 2 2) 2 \n", - "4 LINESTRING (0 2, 1 2) 2 " + " geometry points \n", + "0 LINESTRING (2.00000 0.00000, 2.00000 1.00000) 2 \n", + "1 LINESTRING (3.00000 1.00000, 2.00000 1.00000) 2 \n", + "2 LINESTRING (4.00000 1.00000, 3.00000 1.00000) 2 \n", + "3 LINESTRING (2.00000 1.00000, 2.00000 2.00000) 2 \n", + "4 LINESTRING (0.00000 2.00000, 1.00000 2.00000) 2 " ] }, - "execution_count": 11, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -387,7 +394,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -404,23 +411,23 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.15" + "pygments_lexer": "ipython3", + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/example/notebook/stmatch_example.ipynb b/example/notebook/stmatch_example.ipynb index 90fd2bd..e0483a7 100644 --- a/example/notebook/stmatch_example.ipynb +++ b/example/notebook/stmatch_example.ipynb @@ -38,7 +38,7 @@ ], "source": [ "network = Network(\"../data/edges.shp\")\n", - "print \"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count())\n", + "print(\"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count()))\n", "graph = NetworkGraph(network)" ] }, @@ -129,11 +129,11 @@ } ], "source": [ - "print \"Matched path: \", list(result.cpath)\n", - "print \"Matched edge for each point: \", list(result.opath)\n", - "print \"Matched edge index \",list(result.indices)\n", - "print \"Matched geometry: \",result.mgeom.export_wkt()\n", - "print \"Matched point \", result.pgeom.export_wkt()" + "print(\"Matched path: \", list(result.cpath))\n", + "print(\"Matched edge for each point: \", list(result.opath))\n", + "print(\"Matched edge index \",list(result.indices))\n", + "print(\"Matched geometry: \",result.mgeom.export_wkt())\n", + "print(\"Matched point \", result.pgeom.export_wkt())" ] }, { @@ -145,7 +145,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -154,7 +154,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -163,7 +163,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ @@ -175,7 +175,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -184,7 +184,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -193,7 +193,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -208,10 +208,10 @@ } ], "source": [ - "print \"Matched path: \", list(result.cpath)\n", - "print \"Matched edge for each point: \", list(result.opath)\n", - "print \"Matched edge index \",list(result.indices)\n", - "print \"Matched geometry: \",result.mgeom.export_wkt()" + "print(\"Matched path: \", list(result.cpath))\n", + "print(\"Matched edge for each point: \", list(result.opath))\n", + "print(\"Matched edge index \",list(result.indices))\n", + "print(\"Matched geometry: \",result.mgeom.export_wkt())" ] }, { @@ -223,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 14, "metadata": {}, "outputs": [], "source": [ @@ -232,7 +232,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -244,7 +244,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 16, "metadata": {}, "outputs": [ { @@ -263,12 +263,12 @@ } ], "source": [ - "print input_config.to_string()" + "print(input_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -285,12 +285,12 @@ "result_config = ResultConfig()\n", "result_config.file = \"../data/mr.txt\"\n", "result_config.output_config.write_opath = True\n", - "print result_config.to_string()" + "print(result_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -299,22 +299,23 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Time takes 0.001 seconds\n", + "Status: success\n", + "Time takes 0.004 seconds\n", "Total points 17 matched 17\n", - "Map match speed 17000 points/s \n", + "Map match speed 4250 points/s \n", "\n" ] } ], "source": [ - "print status" + "print(status)" ] }, { @@ -327,21 +328,21 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.15" + "pygments_lexer": "ipython3", + "version": "3.8.5" }, "toc": { "base_numbering": 1, @@ -358,5 +359,5 @@ } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/example/osmnx_example/map_matching.ipynb b/example/osmnx_example/map_matching.ipynb index f64e354..4d74621 100644 --- a/example/osmnx_example/map_matching.ipynb +++ b/example/osmnx_example/map_matching.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "metadata": {}, "outputs": [], "source": [ @@ -18,7 +18,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -31,7 +31,7 @@ ], "source": [ "network = Network(\"stockholm/edges.shp\",\"fid\", \"u\", \"v\")\n", - "print \"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count())\n", + "print(\"Nodes {} edges {}\".format(network.get_node_count(),network.get_edge_count()))\n", "graph = NetworkGraph(network)" ] }, @@ -44,7 +44,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "metadata": {}, "outputs": [ { @@ -52,7 +52,7 @@ "output_type": "stream", "text": [ "Status: success\n", - "Time takes 0.587 seconds\n", + "Time takes 0.332 seconds\n", "\n" ] } @@ -64,7 +64,7 @@ "status = ubodt_gen.generate_ubodt(\"stockholm/ubodt.txt\", 0.03, binary=False, use_omp=True)\n", "# Binary is faster for both IO and precomputation\n", "# status = ubodt_gen.generate_ubodt(\"stockholm/ubodt.bin\", 0.03, binary=True, use_omp=True)\n", - "print status" + "print(status)" ] }, { @@ -76,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -88,7 +88,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ @@ -107,7 +107,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 6, "metadata": {}, "outputs": [ { @@ -124,9 +124,9 @@ "wkt = \"LINESTRING(18.05522129697668 59.335820514008,18.050801016520136 59.33614881818502,18.04796860380041 59.33905964310512,18.046037413309687 59.341029232754444,18.049084402750605 59.34262670491522,18.052775122355097 59.34328317853977,18.056809164713496 59.34273611806721,18.059298254679316 59.34006633652867)\"\n", "result = fmm_model.match_wkt(wkt,fmm_config)\n", "### Print map matching result\n", - "print \"Opath \",list(result.opath)\n", - "print \"Cpath \",list(result.cpath)\n", - "print \"WKT \",result.mgeom.export_wkt()" + "print(\"Opath \",list(result.opath))\n", + "print(\"Cpath \",list(result.cpath))\n", + "print(\"WKT \",result.mgeom.export_wkt())" ] }, { @@ -138,7 +138,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -147,7 +147,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -156,7 +156,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -170,7 +170,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 10, "metadata": {}, "outputs": [ { @@ -185,11 +185,11 @@ ], "source": [ "wkt = \"LINESTRING(18.05522129697668 59.335820514008,18.050801016520136 59.33614881818502,18.04796860380041 59.33905964310512,18.046037413309687 59.341029232754444,18.049084402750605 59.34262670491522,18.052775122355097 59.34328317853977,18.056809164713496 59.34273611806721,18.059298254679316 59.34006633652867)\"\n", - "result = model.match_wkt(wkt,fmm_config)\n", + "result = stmatch_model.match_wkt(wkt, stmatch_config)\n", "### Print map matching result\n", - "print \"Opath \",list(result.opath)\n", - "print \"Cpath \",list(result.cpath)\n", - "print \"WKT \",result.mgeom.export_wkt()" + "print(\"Opath \",list(result.opath))\n", + "print(\"Cpath \",list(result.cpath))\n", + "print(\"WKT \",result.mgeom.export_wkt())" ] }, { @@ -201,7 +201,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -210,7 +210,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 12, "metadata": {}, "outputs": [ { @@ -233,12 +233,12 @@ "input_config = GPSConfig()\n", "input_config.file = \"stockholm/trips.csv\"\n", "input_config.id = \"id\"\n", - "print input_config.to_string()" + "print(input_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 13, "metadata": {}, "outputs": [ { @@ -255,12 +255,12 @@ "result_config = ResultConfig()\n", "result_config.file = \"stockholm/mr.txt\"\n", "result_config.output_config.write_opath = True\n", - "print result_config.to_string()" + "print(result_config.to_string())" ] }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 14, "metadata": {}, "outputs": [ { @@ -268,23 +268,23 @@ "output_type": "stream", "text": [ "Status: success\n", - "Time takes 0.001 seconds\n", + "Time takes 0.006 seconds\n", "Total points 14 matched 14\n", "Total trajectories 2 matched 2\n", "Map match percentage 1\n", - "Map match speed 14000 points/s \n", + "Map match speed 2333.33 points/s \n", "\n" ] } ], "source": [ "status = fmm_model.match_gps_file(input_config, result_config, fmm_config, use_omp = True)\n", - "print status" + "print(status)" ] }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 15, "metadata": {}, "outputs": [ { @@ -292,16 +292,16 @@ "output_type": "stream", "text": [ "Status: success\n", - "Time takes 0.009 seconds\n", + "Time takes 0.005 seconds\n", "Total points 14 matched 14\n", - "Map match speed 1555.56 points/s \n", + "Map match speed 2800 points/s \n", "\n" ] } ], "source": [ "status = stmatch_model.match_gps_file(input_config, result_config, stmatch_config, use_omp = True)\n", - "print status" + "print(status)" ] }, { @@ -314,23 +314,23 @@ ], "metadata": { "kernelspec": { - "display_name": "Python 2", + "display_name": "Python 3", "language": "python", - "name": "python2" + "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", - "version": 2 + "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.15" + "pygments_lexer": "ipython3", + "version": "3.8.5" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/example/python/fmm_test.py b/example/python/fmm_test.py index d783f1a..a5b000e 100644 --- a/example/python/fmm_test.py +++ b/example/python/fmm_test.py @@ -1,7 +1,7 @@ from fmm import Network,NetworkGraph,STMATCH,STMATCHConfig network = Network("../data/edges.shp") graph = NetworkGraph(network) -print graph.get_num_vertices() +print(graph.get_num_vertices()) model = STMATCH(network,graph) wkt = "LINESTRING(0.200812146892656 2.14088983050848,1.44262005649717 2.14879943502825,3.06408898305084 2.16066384180791,3.06408898305084 2.7103813559322,3.70872175141242 2.97930790960452,4.11606638418078 2.62337570621469)" config = STMATCHConfig() @@ -11,7 +11,7 @@ config.vmax = 30; config.factor =1.5 result = model.match_wkt(wkt,config) -print type(result) -print "Opath ",list(result.opath) -print "Cpath ",list(result.cpath) -print "WKT ",result.mgeom.export_wkt() +print(type(result)) +print("Opath ",list(result.opath)) +print("Cpath ",list(result.cpath)) +print("WKT ",result.mgeom.export_wkt()) diff --git a/example/web_demo/mapmatcher.py b/example/web_demo/mapmatcher.py index e2aeb72..353be48 100644 --- a/example/web_demo/mapmatcher.py +++ b/example/web_demo/mapmatcher.py @@ -11,56 +11,60 @@ def __init__(self, config_json_file): "File for {} is missing.".format(config_json_file)) with open(config_json_file) as f: data = json.load(f) - if (not data.has_key("model")): + if ("model" not in data): raise Exception("Model is missing.") - if (not data.has_key("input")): + if ("input" not in data): raise Exception("Input is missing.") - if (not data["input"].has_key("network")): + if ("network" not in data["input"]): raise Exception("Network is missing.") - if (not data["input"]["network"].has_key("file")): + if ("file" not in data["input"]["network"]): raise Exception("Network file is missing.") self.network_file = str(data["input"]["network"]["file"]) - if data["input"]["network"].has_key("id"): + if "id" in data["input"]["network"]: self.network_id = str(data["input"]["network"]["id"]) else: self.network_id = "id" - if data["input"]["network"].has_key("source"): + if "source" in data["input"]["network"]: self.network_source = str(data["input"]["network"]["source"]) else: self.network_source = "source" - if data["input"]["network"].has_key("target"): + if "target" in data["input"]["network"]: self.network_target = str(data["input"]["network"]["target"]) else: self.network_target = "target" if str(data["model"])=="stmatch": self.model_tag = "stmatch" self.mm_config = STMATCHConfig() - if data.has_key("parameters"): - if data["parameters"].has_key("k"): + if "parameters" in data: + if "k" in data["parameters"]: self.mm_config.k = data["parameters"]["k"] - if data["parameters"].has_key("r"): + if "r" in data["parameters"]: self.mm_config.radius = data["parameters"]["r"] - if data["parameters"].has_key("e"): + if "e" in data["parameters"]: self.mm_config.gps_error = data["parameters"]["e"] - if data["parameters"].has_key("f"): + if "f" in data["parameters"]: self.mm_config.factor = data["parameters"]["f"] - if data["parameters"].has_key("vmax"): + if "vmax" in data["parameters"]: self.mm_config.vmax = data["parameters"]["vmax"] + if "reverse_tolerance" in data["parameters"]: + self.mm_config.reverse_tolerance = data["parameters"]["reverse_tolerance"] elif (str(data["model"])=="fmm"): self.model_tag = "fmm" - if (not data["input"].has_key("ubodt")): + if ("ubodt" not in data["input"]): raise Exception("Ubodt is missing.") - if (not data["input"]["ubodt"].has_key("file")): + if ("file" not in data["input"]["ubodt"]): raise Exception("Ubodt file is missing.") self.ubodt_file = str(data["input"]["ubodt"]["file"]) self.mm_config = FastMapMatchConfig() - if data.has_key("parameters"): - if data["parameters"].has_key("k"): + if "parameters" in data: + if "k" in data["parameters"]: self.mm_config.k = data["parameters"]["k"] - if data["parameters"].has_key("r"): + if "r" in data["parameters"]: self.mm_config.radius = data["parameters"]["r"] - if data["parameters"].has_key("e"): + if "e" in data["parameters"]: self.mm_config.gps_error = data["parameters"]["e"] + if "reverse_tolerance" in data["parameters"]: + self.mm_config.reverse_tolerance = data["parameters"]["reverse_tolerance"] else: raise Exception( "Model not found for {} ".format(