Last active
August 30, 2023 23:59
-
-
Save knaaptime/60bcf942508a47f6028ab1bfd1f3fa26 to your computer and use it in GitHub Desktop.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
{ | |
"cells": [ | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "f8c3f7fb-efec-4f26-9616-216a00204395", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"id": "8a03938c-b48e-4cd4-89aa-88b98ad91fe4", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:02:49.123881Z", | |
"iopub.status.busy": "2023-08-30T23:02:49.122862Z", | |
"iopub.status.idle": "2023-08-30T23:03:16.174675Z", | |
"shell.execute_reply": "2023-08-30T23:03:16.173972Z", | |
"shell.execute_reply.started": "2023-08-30T23:02:49.123778Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/cg/alpha_shapes.py:41: NumbaDeprecationWarning: \u001b[1mThe keyword argument 'nopython=False' was supplied. From Numba 0.59.0 the default is being changed to True and use of 'nopython=False' will raise a warning as the argument will have no effect. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n", | |
" @jit(nopython=False)\n", | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/cg/alpha_shapes.py:167: NumbaDeprecationWarning: \u001b[1mThe keyword argument 'nopython=False' was supplied. From Numba 0.59.0 the default is being changed to True and use of 'nopython=False' will raise a warning as the argument will have no effect. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n", | |
" @jit(nopython=False)\n", | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/cg/alpha_shapes.py:201: NumbaDeprecationWarning: \u001b[1mThe keyword argument 'nopython=False' was supplied. From Numba 0.59.0 the default is being changed to True and use of 'nopython=False' will raise a warning as the argument will have no effect. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n", | |
" @jit(nopython=False)\n", | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/cg/alpha_shapes.py:263: NumbaDeprecationWarning: \u001b[1mThe keyword argument 'nopython=False' was supplied. From Numba 0.59.0 the default is being changed to True and use of 'nopython=False' will raise a warning as the argument will have no effect. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n", | |
" @jit(nopython=False)\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/numba/core/decorators.py:262: NumbaDeprecationWarning: \u001b[1mnumba.generated_jit is deprecated. Please see the documentation at: https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-generated-jit for more information and advice on a suitable replacement.\u001b[0m\n", | |
" warnings.warn(msg, NumbaDeprecationWarning)\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/quantecon/lss.py:20: NumbaDeprecationWarning: \u001b[1mThe 'nopython' keyword argument was not supplied to the 'numba.jit' decorator. The implicit default value for this argument is currently False, but it will be changed to True in Numba 0.59.0. See https://numba.readthedocs.io/en/stable/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit for details.\u001b[0m\n", | |
" def simulate_linear_model(A, x0, v, ts_length):\n", | |
"/Users/knaaptime/Dropbox/projects/geosnap/geosnap/_data.py:66: UserWarning: The geosnap data storage class is provided for convenience only. The geosnap developers make no promises regarding data quality, consistency, or availability, nor are they responsible for any use/misuse of the data. The end-user is responsible for any and all analyses or applications created with the package.\n", | |
" warn(\n" | |
] | |
} | |
], | |
"source": [ | |
"from geosnap.io import get_acs\n", | |
"from geosnap import DataStore" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"id": "a6d87e13-c86e-4539-be3a-d0b23b975ca8", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:16.176541Z", | |
"iopub.status.busy": "2023-08-30T23:03:16.176303Z", | |
"iopub.status.idle": "2023-08-30T23:03:16.303856Z", | |
"shell.execute_reply": "2023-08-30T23:03:16.302829Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:16.176519Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"import pandana as pdna\n", | |
"import geopandas as gpd\n", | |
"import pandas as pd" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"id": "df62dc39-44fd-4741-b3d8-f1c3e9dd3b75", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:16.308309Z", | |
"iopub.status.busy": "2023-08-30T23:03:16.307578Z", | |
"iopub.status.idle": "2023-08-30T23:03:16.313080Z", | |
"shell.execute_reply": "2023-08-30T23:03:16.312393Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:16.308267Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/knaaptime/Dropbox/projects/geosnap/geosnap/_data.py:66: UserWarning: The geosnap data storage class is provided for convenience only. The geosnap developers make no promises regarding data quality, consistency, or availability, nor are they responsible for any use/misuse of the data. The end-user is responsible for any and all analyses or applications created with the package.\n", | |
" warn(\n" | |
] | |
} | |
], | |
"source": [ | |
"datasets = DataStore()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "d895ed1f-f126-487d-b779-be90534ec12e", | |
"metadata": {}, | |
"source": [ | |
"To generate a routable network, use [pandana]() or [urbanaccess](). Alternatively, you can download one of the metropolitan-scale pedestrian networks for the U.S. from geosnap's [quilt bucket](https://open.quiltdata.com/b/spatial-ucr/tree/osm/metro_networks_8k/). The files are named for each CBSA fips code and extend 8km beyond the metro region's borders to help mitigate edge effects. Here, we'll use the quilt version from the San Diego region." | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "8f46c7a0-43e1-443a-83db-2be9a23c4c59", | |
"metadata": {}, | |
"source": [ | |
"to get the network file without downloading from OSM uncomment the cell below and update the path in the following cell" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"id": "1c4ba2ba-57f4-4ccc-ba87-c1094376e9ca", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:16.316249Z", | |
"iopub.status.busy": "2023-08-30T23:03:16.316112Z", | |
"iopub.status.idle": "2023-08-30T23:03:16.318481Z", | |
"shell.execute_reply": "2023-08-30T23:03:16.317617Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:16.316239Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"\n", | |
"#import quilt3 as q3\n", | |
"#b = q3.Bucket(\"s3://spatial-ucr\")\n", | |
"#b.fetch(\"osm/metro_networks_8k/41740.h5\", \"./41740.h5\")" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"id": "45f1c59d-c25f-460a-a8b5-b4b1484de274", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:16.320011Z", | |
"iopub.status.busy": "2023-08-30T23:03:16.319821Z", | |
"iopub.status.idle": "2023-08-30T23:03:20.971207Z", | |
"shell.execute_reply": "2023-08-30T23:03:20.970741Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:16.319998Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"sd_network = pdna.Network.from_hdf5(\"/Users/knaaptime/Dropbox/projects/geosnap_data/metro_networks_8k/41740.h5\")" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"id": "e81185c8-2666-4e9f-b9a3-136d65753592", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:20.972054Z", | |
"iopub.status.busy": "2023-08-30T23:03:20.971943Z", | |
"iopub.status.idle": "2023-08-30T23:03:24.243233Z", | |
"shell.execute_reply": "2023-08-30T23:03:24.242871Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:20.972044Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"# blockgroup data for san diego county\n", | |
"\n", | |
"sd = get_acs(datasets, msa_fips='41740', level='bg', years=[2019])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"id": "8adcb707-2754-4439-ad35-44bafc56875c", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:24.243852Z", | |
"iopub.status.busy": "2023-08-30T23:03:24.243761Z", | |
"iopub.status.idle": "2023-08-30T23:03:24.248863Z", | |
"shell.execute_reply": "2023-08-30T23:03:24.247957Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:24.243843Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"(1795, 58)" | |
] | |
}, | |
"execution_count": 8, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"sd.shape" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"id": "747cc698-f0f1-41db-9888-6b21b690ed87", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:24.251061Z", | |
"iopub.status.busy": "2023-08-30T23:03:24.250913Z", | |
"iopub.status.idle": "2023-08-30T23:03:35.809250Z", | |
"shell.execute_reply": "2023-08-30T23:03:35.808944Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:24.251048Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"<ipython-input-9-c6a526087904>:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" nodes = sd_network.get_node_ids(sd.to_crs(4326).geometry.centroid.x, sd.to_crs(4326).geometry.centroid.y)\n", | |
"<ipython-input-9-c6a526087904>:3: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" nodes = sd_network.get_node_ids(sd.to_crs(4326).geometry.centroid.x, sd.to_crs(4326).geometry.centroid.y)\n" | |
] | |
} | |
], | |
"source": [ | |
"# get network nodes for each observation\n", | |
"\n", | |
"nodes = sd_network.get_node_ids(sd.to_crs(4326).geometry.centroid.x, sd.to_crs(4326).geometry.centroid.y)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "23c37532-8d5e-4aad-bf50-d1c70a7944cc", | |
"metadata": {}, | |
"source": [ | |
"The new `nodes_in_range` returns an adjlist wicked fast" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 64, | |
"id": "9e6b98b3-a3ca-4107-87f5-3ea10c8b6097", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:58:21.463233Z", | |
"iopub.status.busy": "2023-08-30T23:58:21.462356Z", | |
"iopub.status.idle": "2023-08-30T23:58:52.448682Z", | |
"shell.execute_reply": "2023-08-30T23:58:52.448390Z", | |
"shell.execute_reply.started": "2023-08-30T23:58:21.463180Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"3.85 s ± 73.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"\n", | |
"# adjacency table for nodes accessible within 5km along the ped network\n", | |
"\n", | |
"adj = sd_network.nodes_in_range(nodes, 5000).rename(\n", | |
" columns={\"source\": \"focal\", \"destination\": \"neighbor\", \"distance\": \"weight\"}\n", | |
")" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "dc2bd80b-c9c8-462b-b1b0-af6c4306bce1", | |
"metadata": {}, | |
"source": [ | |
"thats pretty remarkable... 3-4 seconds to do a shortest path query between >3million pairs of nodes and build a formatted adjtable" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 35, | |
"id": "d0272b7e-dfdd-4a6f-a2d5-506be7caa7d0", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:36:09.689222Z", | |
"iopub.status.busy": "2023-08-29T20:36:09.689135Z", | |
"iopub.status.idle": "2023-08-29T20:36:09.695134Z", | |
"shell.execute_reply": "2023-08-29T20:36:09.694850Z", | |
"shell.execute_reply.started": "2023-08-29T20:36:09.689213Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>focal</th>\n", | |
" <th>neighbor</th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>0</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>3701750399</td>\n", | |
" <td>0.000000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>1</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>49260582</td>\n", | |
" <td>47.236000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>3701750398</td>\n", | |
" <td>88.501999</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>4635563929</td>\n", | |
" <td>102.205002</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>4</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>49132747</td>\n", | |
" <td>119.944000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>9460548</th>\n", | |
" <td>2758616195</td>\n", | |
" <td>1734644544</td>\n", | |
" <td>4996.248047</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>9460549</th>\n", | |
" <td>2758616195</td>\n", | |
" <td>5543614905</td>\n", | |
" <td>4996.621094</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>9460550</th>\n", | |
" <td>2758616195</td>\n", | |
" <td>1977176619</td>\n", | |
" <td>4997.878906</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>9460551</th>\n", | |
" <td>2758616195</td>\n", | |
" <td>49176999</td>\n", | |
" <td>4999.333984</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>9460552</th>\n", | |
" <td>2758616195</td>\n", | |
" <td>806273547</td>\n", | |
" <td>4999.841797</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>9460553 rows × 3 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" focal neighbor weight\n", | |
"0 3701750399 3701750399 0.000000\n", | |
"1 3701750399 49260582 47.236000\n", | |
"2 3701750399 3701750398 88.501999\n", | |
"3 3701750399 4635563929 102.205002\n", | |
"4 3701750399 49132747 119.944000\n", | |
"... ... ... ...\n", | |
"9460548 2758616195 1734644544 4996.248047\n", | |
"9460549 2758616195 5543614905 4996.621094\n", | |
"9460550 2758616195 1977176619 4997.878906\n", | |
"9460551 2758616195 49176999 4999.333984\n", | |
"9460552 2758616195 806273547 4999.841797\n", | |
"\n", | |
"[9460553 rows x 3 columns]" | |
] | |
}, | |
"execution_count": 35, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"adj" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"id": "1fe86c90-80b7-413c-9403-f5e31f5242dc", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:03:39.843895Z", | |
"iopub.status.busy": "2023-08-30T23:03:39.843816Z", | |
"iopub.status.idle": "2023-08-30T23:03:39.857555Z", | |
"shell.execute_reply": "2023-08-30T23:03:39.857106Z", | |
"shell.execute_reply.started": "2023-08-30T23:03:39.843886Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"from libpysal.graph import Graph" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"id": "4198af5d-d93d-466a-8094-d2cd9e63a230", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:25:14.800245Z", | |
"iopub.status.busy": "2023-08-29T20:25:14.799976Z", | |
"iopub.status.idle": "2023-08-29T20:25:14.901547Z", | |
"shell.execute_reply": "2023-08-29T20:25:14.900886Z", | |
"shell.execute_reply.started": "2023-08-29T20:25:14.800222Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "ValueError", | |
"evalue": "The shape of the adjacency table needs to be (x, 2). (9460553, 3) was given instead.", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[11], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mGraph\u001b[49m\u001b[43m(\u001b[49m\u001b[43madj\u001b[49m\u001b[43m)\u001b[49m\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/base.py:52\u001b[0m, in \u001b[0;36mGraph.__init__\u001b[0;34m(self, adjacency, transformation)\u001b[0m\n\u001b[1;32m 50\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe adjacency table needs to be a pandas.DataFrame.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m 51\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m adjacency\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m] \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[0;32m---> 52\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 53\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe shape of the adjacency table needs to be (x, 2). \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 54\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00madjacency\u001b[38;5;241m.\u001b[39mshape\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m was given instead.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 55\u001b[0m )\n\u001b[1;32m 56\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m adjacency\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mname \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mfocal\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m 57\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\n\u001b[1;32m 58\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe index of the adjacency table needs to be named \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 59\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfocal\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m. \u001b[39m\u001b[38;5;132;01m{\u001b[39;00madjacency\u001b[38;5;241m.\u001b[39mindex\u001b[38;5;241m.\u001b[39mname\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m was given instead.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 60\u001b[0m )\n", | |
"\u001b[0;31mValueError\u001b[0m: The shape of the adjacency table needs to be (x, 2). (9460553, 3) was given instead." | |
] | |
} | |
], | |
"source": [ | |
"Graph(adj)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"id": "905796ec-0f7e-409a-ad1d-08c53f46fb3f", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:25:56.557165Z", | |
"iopub.status.busy": "2023-08-29T20:25:56.556137Z", | |
"iopub.status.idle": "2023-08-29T20:25:56.603176Z", | |
"shell.execute_reply": "2023-08-29T20:25:56.602631Z", | |
"shell.execute_reply.started": "2023-08-29T20:25:56.557104Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"g = Graph(adj.set_index('focal')) # not supposed to do it this way" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 13, | |
"id": "5a0324f6-e3f5-4224-b9b0-31e31aba5f30", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:25:56.900543Z", | |
"iopub.status.busy": "2023-08-29T20:25:56.900180Z", | |
"iopub.status.idle": "2023-08-29T20:25:56.949661Z", | |
"shell.execute_reply": "2023-08-29T20:25:56.941248Z", | |
"shell.execute_reply.started": "2023-08-29T20:25:56.900517Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>neighbor</th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>0.000000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49260582</td>\n", | |
" <td>47.236000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>3701750398</td>\n", | |
" <td>88.501999</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>4635563929</td>\n", | |
" <td>102.205002</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49132747</td>\n", | |
" <td>119.944000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>1734644544</td>\n", | |
" <td>4996.248047</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>5543614905</td>\n", | |
" <td>4996.621094</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>1977176619</td>\n", | |
" <td>4997.878906</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49176999</td>\n", | |
" <td>4999.333984</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>806273547</td>\n", | |
" <td>4999.841797</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>9460553 rows × 2 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" neighbor weight\n", | |
"focal \n", | |
"3701750399 3701750399 0.000000\n", | |
"3701750399 49260582 47.236000\n", | |
"3701750399 3701750398 88.501999\n", | |
"3701750399 4635563929 102.205002\n", | |
"3701750399 49132747 119.944000\n", | |
"... ... ...\n", | |
"2758616195 1734644544 4996.248047\n", | |
"2758616195 5543614905 4996.621094\n", | |
"2758616195 1977176619 4997.878906\n", | |
"2758616195 49176999 4999.333984\n", | |
"2758616195 806273547 4999.841797\n", | |
"\n", | |
"[9460553 rows x 2 columns]" | |
] | |
}, | |
"execution_count": 13, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"g.adjacency" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "919bc4c4-9cdc-4c03-a44c-63153cce991f", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"id": "a342af59-7625-48fb-8b10-5febd8072f00", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:25:58.537996Z", | |
"iopub.status.busy": "2023-08-29T20:25:58.536940Z", | |
"iopub.status.idle": "2023-08-29T20:25:58.572066Z", | |
"shell.execute_reply": "2023-08-29T20:25:58.571566Z", | |
"shell.execute_reply.started": "2023-08-29T20:25:58.537943Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"g_from_arrays = Graph.from_arrays(adj['focal'].values, adj['neighbor'].values, adj['weight'].values) # this is cumbersome" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"id": "1079d55a-5985-49e5-b0ad-977679fbd42c", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:25:58.862577Z", | |
"iopub.status.busy": "2023-08-29T20:25:58.859468Z", | |
"iopub.status.idle": "2023-08-29T20:26:01.987191Z", | |
"shell.execute_reply": "2023-08-29T20:26:01.986854Z", | |
"shell.execute_reply.started": "2023-08-29T20:25:58.862500Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"True" | |
] | |
}, | |
"execution_count": 15, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"g_from_arrays == g" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "992bd7cc-ad8f-49f3-8874-183d5cc56e96", | |
"metadata": {}, | |
"source": [ | |
"this works fine" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "5672ecbd-150b-4b78-8d5f-de69465ff2b0", | |
"metadata": {}, | |
"source": [ | |
"## Kernel or Distance" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "5551ad42-bfe0-4274-9ac9-86c92fc5d21e", | |
"metadata": {}, | |
"source": [ | |
"but what if i want to apply a kernel function to these distances, or truncate the neighbor set (after ive made the expensive call to pandana)?" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"id": "e3b7b132-b048-4f6d-8bbd-684ce39f0ff0", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:19:10.038136Z", | |
"iopub.status.busy": "2023-08-29T20:19:10.038021Z", | |
"iopub.status.idle": "2023-08-29T20:19:10.091013Z", | |
"shell.execute_reply": "2023-08-29T20:19:10.090283Z", | |
"shell.execute_reply.started": "2023-08-29T20:19:10.038127Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "AssertionError", | |
"evalue": "coordinates should represent a distance matrix if metric='precomputed'", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[17], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m g_pdna \u001b[38;5;241m=\u001b[39m \u001b[43mGraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43madj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mprecomputed\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/base.py:384\u001b[0m, in \u001b[0;36mGraph.build_kernel\u001b[0;34m(cls, data, kernel, k, bandwidth, metric, p)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Generate Graph from geometry data based on a kernel function\u001b[39;00m\n\u001b[1;32m 340\u001b[0m \n\u001b[1;32m 341\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[38;5;124;03m libpysal.graph.Graph encoding kernel weights\u001b[39;00m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 382\u001b[0m ids \u001b[38;5;241m=\u001b[39m _evaluate_index(data)\n\u001b[0;32m--> 384\u001b[0m head, tail, weight \u001b[38;5;241m=\u001b[39m \u001b[43m_kernel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 385\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 386\u001b[0m \u001b[43m \u001b[49m\u001b[43mbandwidth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbandwidth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 387\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 388\u001b[0m \u001b[43m \u001b[49m\u001b[43mkernel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkernel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 389\u001b[0m \u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 390\u001b[0m \u001b[43m \u001b[49m\u001b[43mp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 391\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 392\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 393\u001b[0m \u001b[38;5;66;03m# TODO: ensure sorting\u001b[39;00m\n\u001b[1;32m 395\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mfrom_arrays(head, tail, weight)\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/_kernel.py:121\u001b[0m, in \u001b[0;36m_kernel\u001b[0;34m(coordinates, bandwidth, metric, kernel, k, ids, p, taper)\u001b[0m\n\u001b[1;32m 117\u001b[0m coordinates, ids, _ \u001b[38;5;241m=\u001b[39m _validate_geometry_input(\n\u001b[1;32m 118\u001b[0m coordinates, ids\u001b[38;5;241m=\u001b[39mids, valid_geometry_types\u001b[38;5;241m=\u001b[39m_VALID_GEOMETRY_TYPES\n\u001b[1;32m 119\u001b[0m )\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 121\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m (\n\u001b[1;32m 122\u001b[0m coordinates\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m==\u001b[39m coordinates\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m 123\u001b[0m ), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcoordinates should represent a distance matrix if metric=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mprecomputed\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 125\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m k \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m metric \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mprecomputed\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n", | |
"\u001b[0;31mAssertionError\u001b[0m: coordinates should represent a distance matrix if metric='precomputed'" | |
] | |
} | |
], | |
"source": [ | |
"g_pdna = Graph.build_kernel(adj.values, metric='precomputed')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "f3c0891c-b477-445a-b9cd-637dbad2aaaa", | |
"metadata": {}, | |
"source": [ | |
"this fails because it was passed the adjacency table, not the matrix, so the dimensions are wrong" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 20, | |
"id": "4b216d25-cc8f-44e2-a49e-5e749549d3a4", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T18:21:51.812146Z", | |
"iopub.status.busy": "2023-08-29T18:21:51.811153Z", | |
"iopub.status.idle": "2023-08-29T18:21:51.826069Z", | |
"shell.execute_reply": "2023-08-29T18:21:51.824056Z", | |
"shell.execute_reply.started": "2023-08-29T18:21:51.812114Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"\u001b[0;31mSignature:\u001b[0m\n", | |
"\u001b[0mGraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuild_kernel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mkernel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'gaussian'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mbandwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mmetric\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'euclidean'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;31mDocstring:\u001b[0m\n", | |
"Generate Graph from geometry data based on a kernel function\n", | |
"\n", | |
"Parameters\n", | |
"----------\n", | |
"data : numpy.ndarray, geopandas.GeoSeries, geopandas.GeoDataFrame\n", | |
" geometries over which to compute a kernel. If a geopandas object with Point\n", | |
" geoemtry is provided, the .geometry attribute is used. If a numpy.ndarray\n", | |
" with shapely geoemtry is used, then the coordinates are extracted and used.\n", | |
" If a numpy.ndarray of a shape (2,n) is used, it is assumed to contain x, y\n", | |
" coordinates. If metric=\"precomputed\", data is assumed to contain a\n", | |
" precomputed distance metric.\n", | |
"kernel : string or callable (default: 'gaussian')\n", | |
" kernel function to apply over the distance matrix computed by `metric`.\n", | |
" The following kernels are supported:\n", | |
" - triangular:\n", | |
" - parabolic:\n", | |
" - gaussian:\n", | |
" - bisquare:\n", | |
" - cosine:\n", | |
" - boxcar/discrete: all distances less than `bandwidth` are 1, and all\n", | |
" other distances are 0\n", | |
" - identity/None : do nothing, weight similarity based on raw distance\n", | |
" - callable : a user-defined function that takes the distance vector and\n", | |
" the bandwidth and returns the kernel: kernel(distances, bandwidth)\n", | |
"k : int (default: None)\n", | |
" number of nearest neighbors used to truncate the kernel. This is assumed\n", | |
" to be constant across samples. If None, no truncation is conduted.\n", | |
"bandwidth : float (default: None)\n", | |
" distance to use in the kernel computation. Should be on the same scale as\n", | |
" the input coordinates.\n", | |
"metric : string or callable (default: 'euclidean')\n", | |
" distance function to apply over the input coordinates. Supported options\n", | |
" depend on whether or not scikit-learn is installed. If so, then any\n", | |
" distance function supported by scikit-learn is supported here. Otherwise,\n", | |
" only euclidean, minkowski, and manhattan/cityblock distances are admitted.\n", | |
"p : int (default: 2)\n", | |
" parameter for minkowski metric, ignored if metric != \"minkowski\".\n", | |
"\n", | |
"Returns\n", | |
"-------\n", | |
"Graph\n", | |
" libpysal.graph.Graph encoding kernel weights\n", | |
"\u001b[0;31mFile:\u001b[0m ~/Dropbox/projects/libpysal/libpysal/graph/base.py\n", | |
"\u001b[0;31mType:\u001b[0m method" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"Graph.build_kernel?" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "9aee73cb-3086-424f-b806-eebb4d3da91b", | |
"metadata": {}, | |
"source": [ | |
"kernel needs a n*n matrix, not an adjlist" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 32, | |
"id": "1f0b609c-e19c-4de6-b85a-01684ae2d0a6", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:11:07.096131Z", | |
"iopub.status.busy": "2023-08-30T23:11:07.095978Z", | |
"iopub.status.idle": "2023-08-30T23:11:07.339333Z", | |
"shell.execute_reply": "2023-08-30T23:11:07.339027Z", | |
"shell.execute_reply.started": "2023-08-30T23:11:07.096121Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th>neighbor</th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th rowspan=\"5\" valign=\"top\">3701750399</th>\n", | |
" <th>3701750399</th>\n", | |
" <td>0.000000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49260582</th>\n", | |
" <td>47.236000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750398</th>\n", | |
" <td>88.501999</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>4635563929</th>\n", | |
" <td>102.205002</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49132747</th>\n", | |
" <td>119.944000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th rowspan=\"5\" valign=\"top\">2758616195</th>\n", | |
" <th>1734644544</th>\n", | |
" <td>4996.248047</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>5543614905</th>\n", | |
" <td>4996.621094</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>1977176619</th>\n", | |
" <td>4997.878906</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49176999</th>\n", | |
" <td>4999.333984</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>806273547</th>\n", | |
" <td>4999.841797</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>9460553 rows × 1 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" weight\n", | |
"focal neighbor \n", | |
"3701750399 3701750399 0.000000\n", | |
" 49260582 47.236000\n", | |
" 3701750398 88.501999\n", | |
" 4635563929 102.205002\n", | |
" 49132747 119.944000\n", | |
"... ...\n", | |
"2758616195 1734644544 4996.248047\n", | |
" 5543614905 4996.621094\n", | |
" 1977176619 4997.878906\n", | |
" 49176999 4999.333984\n", | |
" 806273547 4999.841797\n", | |
"\n", | |
"[9460553 rows x 1 columns]" | |
] | |
}, | |
"execution_count": 32, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"adj.set_index(['focal','neighbor'])" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "08ef1105-f86b-4167-a504-17132daa89b0", | |
"metadata": { | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 41, | |
"id": "184f2f25-8ce1-4d20-bf64-b634319300ee", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:14:51.262759Z", | |
"iopub.status.busy": "2023-08-30T23:14:51.262141Z", | |
"iopub.status.idle": "2023-08-30T23:15:25.842600Z", | |
"shell.execute_reply": "2023-08-30T23:15:25.842289Z", | |
"shell.execute_reply.started": "2023-08-30T23:14:51.262708Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"3.94 s ± 134 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"matrix = adj.pivot(index='focal', columns= 'neighbor', values='weight').dropna(axis=1, how='all')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 31, | |
"id": "d3b8c57e-69da-4aa0-a064-946eebe93688", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:10:14.984077Z", | |
"iopub.status.busy": "2023-08-30T23:10:14.983973Z", | |
"iopub.status.idle": "2023-08-30T23:10:14.999471Z", | |
"shell.execute_reply": "2023-08-30T23:10:14.999043Z", | |
"shell.execute_reply.started": "2023-08-30T23:10:14.984068Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th>neighbor</th>\n", | |
" <th>28828453</th>\n", | |
" <th>48857408</th>\n", | |
" <th>48857412</th>\n", | |
" <th>48857413</th>\n", | |
" <th>48857415</th>\n", | |
" <th>48857420</th>\n", | |
" <th>48857429</th>\n", | |
" <th>48857434</th>\n", | |
" <th>48857437</th>\n", | |
" <th>48857443</th>\n", | |
" <th>...</th>\n", | |
" <th>6567117396</th>\n", | |
" <th>6567117397</th>\n", | |
" <th>6567117398</th>\n", | |
" <th>6567117399</th>\n", | |
" <th>6567117442</th>\n", | |
" <th>6567117478</th>\n", | |
" <th>6567117483</th>\n", | |
" <th>6567117486</th>\n", | |
" <th>6568333804</th>\n", | |
" <th>6568829948</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>48857478</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>48857833</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>48857940</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>48858835</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>48859855</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6481154589</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6487399706</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6493586285</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6512128187</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6520281457</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>2112.883057</td>\n", | |
" <td>2188.251953</td>\n", | |
" <td>2298.594971</td>\n", | |
" <td>2218.664062</td>\n", | |
" <td>2050.487061</td>\n", | |
" <td>1967.918945</td>\n", | |
" <td>1824.083008</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>1795 rows × 234977 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
"neighbor 28828453 48857408 48857412 48857413 48857415 \\\n", | |
"focal \n", | |
"48857478 NaN NaN NaN NaN NaN \n", | |
"48857833 NaN NaN NaN NaN NaN \n", | |
"48857940 NaN NaN NaN NaN NaN \n", | |
"48858835 NaN NaN NaN NaN NaN \n", | |
"48859855 NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... \n", | |
"6481154589 NaN NaN NaN NaN NaN \n", | |
"6487399706 NaN NaN NaN NaN NaN \n", | |
"6493586285 NaN NaN NaN NaN NaN \n", | |
"6512128187 NaN NaN NaN NaN NaN \n", | |
"6520281457 NaN NaN NaN 2112.883057 2188.251953 \n", | |
"\n", | |
"neighbor 48857420 48857429 48857434 48857437 48857443 \\\n", | |
"focal \n", | |
"48857478 NaN NaN NaN NaN NaN \n", | |
"48857833 NaN NaN NaN NaN NaN \n", | |
"48857940 NaN NaN NaN NaN NaN \n", | |
"48858835 NaN NaN NaN NaN NaN \n", | |
"48859855 NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... \n", | |
"6481154589 NaN NaN NaN NaN NaN \n", | |
"6487399706 NaN NaN NaN NaN NaN \n", | |
"6493586285 NaN NaN NaN NaN NaN \n", | |
"6512128187 NaN NaN NaN NaN NaN \n", | |
"6520281457 2298.594971 2218.664062 2050.487061 1967.918945 1824.083008 \n", | |
"\n", | |
"neighbor ... 6567117396 6567117397 6567117398 6567117399 6567117442 \\\n", | |
"focal ... \n", | |
"48857478 ... NaN NaN NaN NaN NaN \n", | |
"48857833 ... NaN NaN NaN NaN NaN \n", | |
"48857940 ... NaN NaN NaN NaN NaN \n", | |
"48858835 ... NaN NaN NaN NaN NaN \n", | |
"48859855 ... NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... ... \n", | |
"6481154589 ... NaN NaN NaN NaN NaN \n", | |
"6487399706 ... NaN NaN NaN NaN NaN \n", | |
"6493586285 ... NaN NaN NaN NaN NaN \n", | |
"6512128187 ... NaN NaN NaN NaN NaN \n", | |
"6520281457 ... NaN NaN NaN NaN NaN \n", | |
"\n", | |
"neighbor 6567117478 6567117483 6567117486 6568333804 6568829948 \n", | |
"focal \n", | |
"48857478 NaN NaN NaN NaN NaN \n", | |
"48857833 NaN NaN NaN NaN NaN \n", | |
"48857940 NaN NaN NaN NaN NaN \n", | |
"48858835 NaN NaN NaN NaN NaN \n", | |
"48859855 NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... \n", | |
"6481154589 NaN NaN NaN NaN NaN \n", | |
"6487399706 NaN NaN NaN NaN NaN \n", | |
"6493586285 NaN NaN NaN NaN NaN \n", | |
"6512128187 NaN NaN NaN NaN NaN \n", | |
"6520281457 NaN NaN NaN NaN NaN \n", | |
"\n", | |
"[1795 rows x 234977 columns]" | |
] | |
}, | |
"execution_count": 31, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"matrix" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "fb915db2-3046-4381-a4a3-fdc4bf5aa8b6", | |
"metadata": {}, | |
"source": [ | |
"but now these aren't aligned. Rows and cols arent in the same position. (and look at that shape... lots of all-nan columns)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "0634b1ce-6931-4ebb-8a9a-c7e3095aad89", | |
"metadata": {}, | |
"source": [ | |
"it also takes almost 4 seconds to compute" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 20, | |
"id": "38586469-2a86-40d9-8460-cf72232ba241", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:27:19.326830Z", | |
"iopub.status.busy": "2023-08-29T20:27:19.325662Z", | |
"iopub.status.idle": "2023-08-29T20:27:20.421202Z", | |
"shell.execute_reply": "2023-08-29T20:27:20.420681Z", | |
"shell.execute_reply.started": "2023-08-29T20:27:19.326777Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "AssertionError", | |
"evalue": "coordinates should represent a distance matrix if metric='precomputed'", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[20], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m g_pdna \u001b[38;5;241m=\u001b[39m \u001b[43mGraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mmatrix\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfillna\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mprecomputed\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m \n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/base.py:384\u001b[0m, in \u001b[0;36mGraph.build_kernel\u001b[0;34m(cls, data, kernel, k, bandwidth, metric, p)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Generate Graph from geometry data based on a kernel function\u001b[39;00m\n\u001b[1;32m 340\u001b[0m \n\u001b[1;32m 341\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[38;5;124;03m libpysal.graph.Graph encoding kernel weights\u001b[39;00m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 382\u001b[0m ids \u001b[38;5;241m=\u001b[39m _evaluate_index(data)\n\u001b[0;32m--> 384\u001b[0m head, tail, weight \u001b[38;5;241m=\u001b[39m \u001b[43m_kernel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 385\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 386\u001b[0m \u001b[43m \u001b[49m\u001b[43mbandwidth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbandwidth\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 387\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 388\u001b[0m \u001b[43m \u001b[49m\u001b[43mkernel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mkernel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 389\u001b[0m \u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 390\u001b[0m \u001b[43m \u001b[49m\u001b[43mp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 391\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 392\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 393\u001b[0m \u001b[38;5;66;03m# TODO: ensure sorting\u001b[39;00m\n\u001b[1;32m 395\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mfrom_arrays(head, tail, weight)\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/_kernel.py:121\u001b[0m, in \u001b[0;36m_kernel\u001b[0;34m(coordinates, bandwidth, metric, kernel, k, ids, p, taper)\u001b[0m\n\u001b[1;32m 117\u001b[0m coordinates, ids, _ \u001b[38;5;241m=\u001b[39m _validate_geometry_input(\n\u001b[1;32m 118\u001b[0m coordinates, ids\u001b[38;5;241m=\u001b[39mids, valid_geometry_types\u001b[38;5;241m=\u001b[39m_VALID_GEOMETRY_TYPES\n\u001b[1;32m 119\u001b[0m )\n\u001b[1;32m 120\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 121\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m (\n\u001b[1;32m 122\u001b[0m coordinates\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m==\u001b[39m coordinates\u001b[38;5;241m.\u001b[39mshape[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m 123\u001b[0m ), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcoordinates should represent a distance matrix if metric=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mprecomputed\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 125\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m k \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m 126\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m metric \u001b[38;5;241m!=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mprecomputed\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n", | |
"\u001b[0;31mAssertionError\u001b[0m: coordinates should represent a distance matrix if metric='precomputed'" | |
] | |
} | |
], | |
"source": [ | |
"g_pdna = Graph.build_kernel(matrix.fillna(0), metric='precomputed', ) " | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "d526f00a-5e0a-4ef2-831f-41bba380aec6", | |
"metadata": {}, | |
"source": [ | |
"luckily this will fail because `matrix` isnt square because of those all-nan cols" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "6974b2c7-1891-4fa4-93f4-8a8d822566d7", | |
"metadata": {}, | |
"source": [ | |
"need to reorder the rows/columns (i'm using nodes here, but we need the ID from when g was instantiated). This will also drop the all-nan cols giving us back a square" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 59, | |
"id": "82c751aa-8238-482a-a34c-67dd42df1428", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:53:29.228599Z", | |
"iopub.status.busy": "2023-08-30T23:53:29.228450Z", | |
"iopub.status.idle": "2023-08-30T23:53:32.100950Z", | |
"shell.execute_reply": "2023-08-30T23:53:32.099868Z", | |
"shell.execute_reply.started": "2023-08-30T23:53:29.228590Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"sorted_distmat = matrix.reindex(nodes.values, axis=0).reindex(nodes.values, axis=1)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 60, | |
"id": "7173e63e-b2b3-4c6e-ba46-03df0aaf8e41", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:53:32.102505Z", | |
"iopub.status.busy": "2023-08-30T23:53:32.102396Z", | |
"iopub.status.idle": "2023-08-30T23:53:32.117274Z", | |
"shell.execute_reply": "2023-08-30T23:53:32.116875Z", | |
"shell.execute_reply.started": "2023-08-30T23:53:32.102496Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th>neighbor</th>\n", | |
" <th>3701750399</th>\n", | |
" <th>49303299</th>\n", | |
" <th>49051393</th>\n", | |
" <th>48860702</th>\n", | |
" <th>6209203075</th>\n", | |
" <th>49086761</th>\n", | |
" <th>49193363</th>\n", | |
" <th>49069367</th>\n", | |
" <th>2774570835</th>\n", | |
" <th>49080906</th>\n", | |
" <th>...</th>\n", | |
" <th>49237173</th>\n", | |
" <th>49274404</th>\n", | |
" <th>5555269418</th>\n", | |
" <th>4702706154</th>\n", | |
" <th>5727232827</th>\n", | |
" <th>5560044731</th>\n", | |
" <th>5150937779</th>\n", | |
" <th>49195094</th>\n", | |
" <th>49116448</th>\n", | |
" <th>2758616195</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>0.000000</td>\n", | |
" <td>987.565979</td>\n", | |
" <td>1221.943970</td>\n", | |
" <td>2208.548096</td>\n", | |
" <td>1465.890991</td>\n", | |
" <td>1958.635010</td>\n", | |
" <td>2416.758057</td>\n", | |
" <td>2562.739014</td>\n", | |
" <td>3043.968018</td>\n", | |
" <td>2868.349121</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49303299</th>\n", | |
" <td>987.565979</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>1813.665039</td>\n", | |
" <td>2145.105957</td>\n", | |
" <td>1750.343018</td>\n", | |
" <td>2243.086914</td>\n", | |
" <td>2701.209961</td>\n", | |
" <td>2847.190918</td>\n", | |
" <td>3328.419922</td>\n", | |
" <td>3152.801025</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49051393</th>\n", | |
" <td>1221.943970</td>\n", | |
" <td>1813.665039</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>2238.597900</td>\n", | |
" <td>1407.656982</td>\n", | |
" <td>1387.229004</td>\n", | |
" <td>1845.352051</td>\n", | |
" <td>1991.333008</td>\n", | |
" <td>2472.562012</td>\n", | |
" <td>2296.943115</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>48860702</th>\n", | |
" <td>2208.548096</td>\n", | |
" <td>2145.105957</td>\n", | |
" <td>2238.597900</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>1224.015015</td>\n", | |
" <td>2005.060059</td>\n", | |
" <td>2518.873047</td>\n", | |
" <td>2664.854004</td>\n", | |
" <td>3146.083008</td>\n", | |
" <td>2970.464111</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>6209203075</th>\n", | |
" <td>1465.890991</td>\n", | |
" <td>1750.343018</td>\n", | |
" <td>1407.656982</td>\n", | |
" <td>1224.015015</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>1571.208984</td>\n", | |
" <td>2031.511963</td>\n", | |
" <td>2177.492920</td>\n", | |
" <td>2658.721924</td>\n", | |
" <td>2483.103027</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>5560044731</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>4908.983887</td>\n", | |
" <td>2834.831055</td>\n", | |
" <td>1224.026001</td>\n", | |
" <td>0.0</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>5150937779</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>0.00000</td>\n", | |
" <td>4982.752930</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49195094</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>4982.75293</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>3559.499023</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49116448</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>3559.499023</td>\n", | |
" <td>0.000000</td>\n", | |
" <td>NaN</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>...</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>NaN</td>\n", | |
" <td>0.0</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>1795 rows × 1795 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
"neighbor 3701750399 49303299 49051393 48860702 6209203075 \\\n", | |
"focal \n", | |
"3701750399 0.000000 987.565979 1221.943970 2208.548096 1465.890991 \n", | |
"49303299 987.565979 0.000000 1813.665039 2145.105957 1750.343018 \n", | |
"49051393 1221.943970 1813.665039 0.000000 2238.597900 1407.656982 \n", | |
"48860702 2208.548096 2145.105957 2238.597900 0.000000 1224.015015 \n", | |
"6209203075 1465.890991 1750.343018 1407.656982 1224.015015 0.000000 \n", | |
"... ... ... ... ... ... \n", | |
"5560044731 NaN NaN NaN NaN NaN \n", | |
"5150937779 NaN NaN NaN NaN NaN \n", | |
"49195094 NaN NaN NaN NaN NaN \n", | |
"49116448 NaN NaN NaN NaN NaN \n", | |
"2758616195 NaN NaN NaN NaN NaN \n", | |
"\n", | |
"neighbor 49086761 49193363 49069367 2774570835 49080906 \\\n", | |
"focal \n", | |
"3701750399 1958.635010 2416.758057 2562.739014 3043.968018 2868.349121 \n", | |
"49303299 2243.086914 2701.209961 2847.190918 3328.419922 3152.801025 \n", | |
"49051393 1387.229004 1845.352051 1991.333008 2472.562012 2296.943115 \n", | |
"48860702 2005.060059 2518.873047 2664.854004 3146.083008 2970.464111 \n", | |
"6209203075 1571.208984 2031.511963 2177.492920 2658.721924 2483.103027 \n", | |
"... ... ... ... ... ... \n", | |
"5560044731 NaN NaN NaN NaN NaN \n", | |
"5150937779 NaN NaN NaN NaN NaN \n", | |
"49195094 NaN NaN NaN NaN NaN \n", | |
"49116448 NaN NaN NaN NaN NaN \n", | |
"2758616195 NaN NaN NaN NaN NaN \n", | |
"\n", | |
"neighbor ... 49237173 49274404 5555269418 4702706154 \\\n", | |
"focal ... \n", | |
"3701750399 ... NaN NaN NaN NaN \n", | |
"49303299 ... NaN NaN NaN NaN \n", | |
"49051393 ... NaN NaN NaN NaN \n", | |
"48860702 ... NaN NaN NaN NaN \n", | |
"6209203075 ... NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... \n", | |
"5560044731 ... NaN NaN 4908.983887 2834.831055 \n", | |
"5150937779 ... NaN NaN NaN NaN \n", | |
"49195094 ... NaN NaN NaN NaN \n", | |
"49116448 ... NaN NaN NaN NaN \n", | |
"2758616195 ... NaN NaN NaN NaN \n", | |
"\n", | |
"neighbor 5727232827 5560044731 5150937779 49195094 49116448 \\\n", | |
"focal \n", | |
"3701750399 NaN NaN NaN NaN NaN \n", | |
"49303299 NaN NaN NaN NaN NaN \n", | |
"49051393 NaN NaN NaN NaN NaN \n", | |
"48860702 NaN NaN NaN NaN NaN \n", | |
"6209203075 NaN NaN NaN NaN NaN \n", | |
"... ... ... ... ... ... \n", | |
"5560044731 1224.026001 0.0 NaN NaN NaN \n", | |
"5150937779 NaN NaN 0.00000 4982.752930 NaN \n", | |
"49195094 NaN NaN 4982.75293 0.000000 3559.499023 \n", | |
"49116448 NaN NaN NaN 3559.499023 0.000000 \n", | |
"2758616195 NaN NaN NaN NaN NaN \n", | |
"\n", | |
"neighbor 2758616195 \n", | |
"focal \n", | |
"3701750399 NaN \n", | |
"49303299 NaN \n", | |
"49051393 NaN \n", | |
"48860702 NaN \n", | |
"6209203075 NaN \n", | |
"... ... \n", | |
"5560044731 NaN \n", | |
"5150937779 NaN \n", | |
"49195094 NaN \n", | |
"49116448 NaN \n", | |
"2758616195 0.0 \n", | |
"\n", | |
"[1795 rows x 1795 columns]" | |
] | |
}, | |
"execution_count": 60, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"sorted_distmat" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "c48087de-f21e-45c8-9f75-31f1cb66b54d", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 42, | |
"id": "f20f5fff-d23d-453a-997f-59a5bf23433a", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:16:22.029629Z", | |
"iopub.status.busy": "2023-08-30T23:16:22.028501Z", | |
"iopub.status.idle": "2023-08-30T23:16:44.111697Z", | |
"shell.execute_reply": "2023-08-30T23:16:44.111365Z", | |
"shell.execute_reply.started": "2023-08-30T23:16:22.029565Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"2.75 s ± 27.8 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"\n", | |
"adj.set_index(['focal','neighbor'])[\"weight\"].astype(\"Sparse[float]\").reindex(nodes, level=0).reindex(nodes, level=1).sparse.to_coo(\n", | |
" row_levels=[\"focal\"], column_levels=[\"neighbor\"], sort_labels=True\n", | |
" )[0].tocsr()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "4d32c220-465b-4d9a-8d08-5efb40d4a6e9", | |
"metadata": {}, | |
"source": [ | |
"if we pivot directly from the properly ordered adjtable and go directly to sparse, it takes only 2.75 seconds. But we lose the labels" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 43, | |
"id": "dc98cbbb-cee6-4564-9439-b2edf4b5384c", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:16:45.832499Z", | |
"iopub.status.busy": "2023-08-30T23:16:45.831733Z", | |
"iopub.status.idle": "2023-08-30T23:16:48.622538Z", | |
"shell.execute_reply": "2023-08-30T23:16:48.622040Z", | |
"shell.execute_reply.started": "2023-08-30T23:16:45.832471Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"distmat_sparse = adj.set_index(['focal','neighbor'])[\"weight\"].astype(\"Sparse[float]\").reindex(nodes, level=0).reindex(nodes, level=1).sparse.to_coo(\n", | |
" row_levels=[\"focal\"], column_levels=[\"neighbor\"], sort_labels=True\n", | |
" )[0].tocsr()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 54, | |
"id": "5db6884f-8f33-44e9-a2ad-03e7495d1bb8", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:52:26.809959Z", | |
"iopub.status.busy": "2023-08-30T23:52:26.809044Z", | |
"iopub.status.idle": "2023-08-30T23:52:26.817947Z", | |
"shell.execute_reply": "2023-08-30T23:52:26.816952Z", | |
"shell.execute_reply.started": "2023-08-30T23:52:26.809905Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<1795x1795 sparse matrix of type '<class 'numpy.float64'>'\n", | |
"\twith 87207 stored elements in Compressed Sparse Row format>" | |
] | |
}, | |
"execution_count": 54, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"distmat_sparse" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 55, | |
"id": "3ad847d5-9fc3-4bed-a467-32b0f2f4a9c1", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:52:37.561774Z", | |
"iopub.status.busy": "2023-08-30T23:52:37.560935Z", | |
"iopub.status.idle": "2023-08-30T23:52:37.580318Z", | |
"shell.execute_reply": "2023-08-30T23:52:37.579021Z", | |
"shell.execute_reply.started": "2023-08-30T23:52:37.561733Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"array([ 0. , 987.565979 , 1221.94396973, ..., 4300.32421875,\n", | |
" 3895.05102539, 0. ])" | |
] | |
}, | |
"execution_count": 55, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"distmat_sparse.data" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 45, | |
"id": "e5bd71d0-e81a-4b1e-a64b-f99213d0eb13", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:17:37.831053Z", | |
"iopub.status.busy": "2023-08-30T23:17:37.830307Z", | |
"iopub.status.idle": "2023-08-30T23:17:37.856817Z", | |
"shell.execute_reply": "2023-08-30T23:17:37.856318Z", | |
"shell.execute_reply.started": "2023-08-30T23:17:37.831009Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"matrix([[ 0. , 987.565979 , 1221.94396973, ..., 0. ,\n", | |
" 0. , 0. ],\n", | |
" [ 987.565979 , 0. , 1813.66503906, ..., 0. ,\n", | |
" 0. , 0. ],\n", | |
" [1221.94396973, 1813.66503906, 0. , ..., 0. ,\n", | |
" 0. , 0. ],\n", | |
" ...,\n", | |
" [ 0. , 0. , 0. , ..., 0. ,\n", | |
" 3559.49902344, 0. ],\n", | |
" [ 0. , 0. , 0. , ..., 3559.49902344,\n", | |
" 0. , 0. ],\n", | |
" [ 0. , 0. , 0. , ..., 0. ,\n", | |
" 0. , 0. ]])" | |
] | |
}, | |
"execution_count": 45, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"distmat_sparse.todense()" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 50, | |
"id": "46465b5c-cf09-40ed-9cfb-9f6b34a57bbe", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:49:06.751124Z", | |
"iopub.status.busy": "2023-08-30T23:49:06.750056Z", | |
"iopub.status.idle": "2023-08-30T23:49:06.759573Z", | |
"shell.execute_reply": "2023-08-30T23:49:06.758590Z", | |
"shell.execute_reply.started": "2023-08-30T23:49:06.751059Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"from scipy.sparse import csr_matrix, csr_array" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 51, | |
"id": "d3bb6b8d-d6cc-4b25-a811-a2bdbd99dc87", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:49:08.083048Z", | |
"iopub.status.busy": "2023-08-30T23:49:08.082427Z", | |
"iopub.status.idle": "2023-08-30T23:49:08.093419Z", | |
"shell.execute_reply": "2023-08-30T23:49:08.092344Z", | |
"shell.execute_reply.started": "2023-08-30T23:49:08.083016Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<1795x1795 sparse array of type '<class 'numpy.float64'>'\n", | |
"\twith 87207 stored elements in Compressed Sparse Row format>" | |
] | |
}, | |
"execution_count": 51, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"csr_array(distmat_sparse)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "14367812-6728-4ba3-bcc9-1e4bfe78782d", | |
"metadata": {}, | |
"source": [ | |
"sorted distmat is a pandas dataframe, not a sparse matrix, so the IDs will be populated from the rows" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 61, | |
"id": "cca2f62b-c0b2-4a1d-837a-3910378d3cc7", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:53:45.240763Z", | |
"iopub.status.busy": "2023-08-30T23:53:45.239092Z", | |
"iopub.status.idle": "2023-08-30T23:53:45.305130Z", | |
"shell.execute_reply": "2023-08-30T23:53:45.304632Z", | |
"shell.execute_reply.started": "2023-08-30T23:53:45.240693Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"g_pdna = Graph.build_kernel(sorted_distmat.fillna(0), metric='precomputed', )" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 62, | |
"id": "a25e5717-5634-4dc8-bea6-c0b7941527b3", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:53:49.882569Z", | |
"iopub.status.busy": "2023-08-30T23:53:49.881798Z", | |
"iopub.status.idle": "2023-08-30T23:53:49.899203Z", | |
"shell.execute_reply": "2023-08-30T23:53:49.897192Z", | |
"shell.execute_reply.started": "2023-08-30T23:53:49.882513Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>neighbor</th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49303299</td>\n", | |
" <td>0.215501</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49051393</td>\n", | |
" <td>0.210582</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>48860702</td>\n", | |
" <td>0.181085</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>6209203075</td>\n", | |
" <td>0.204515</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49086761</td>\n", | |
" <td>0.189692</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49337036</td>\n", | |
" <td>0.076529</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>373097160</td>\n", | |
" <td>0.119451</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>5546190899</td>\n", | |
" <td>0.094350</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49051837</td>\n", | |
" <td>0.098682</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49118630</td>\n", | |
" <td>0.114434</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>85412 rows × 2 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" neighbor weight\n", | |
"focal \n", | |
"3701750399 49303299 0.215501\n", | |
"3701750399 49051393 0.210582\n", | |
"3701750399 48860702 0.181085\n", | |
"3701750399 6209203075 0.204515\n", | |
"3701750399 49086761 0.189692\n", | |
"... ... ...\n", | |
"2758616195 49337036 0.076529\n", | |
"2758616195 373097160 0.119451\n", | |
"2758616195 5546190899 0.094350\n", | |
"2758616195 49051837 0.098682\n", | |
"2758616195 49118630 0.114434\n", | |
"\n", | |
"[85412 rows x 2 columns]" | |
] | |
}, | |
"execution_count": 62, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"g_pdna.adjacency" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "4b2267a6-126b-401f-87f2-a76635ba16e9", | |
"metadata": {}, | |
"source": [ | |
"but trying to build from sparse fails because it doesnt have len/shape" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 57, | |
"id": "e1a903b7-94ad-4b87-9288-17c5ea22ac19", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T23:53:00.767902Z", | |
"iopub.status.busy": "2023-08-30T23:53:00.766852Z", | |
"iopub.status.idle": "2023-08-30T23:53:00.811403Z", | |
"shell.execute_reply": "2023-08-30T23:53:00.810634Z", | |
"shell.execute_reply.started": "2023-08-30T23:53:00.767836Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "TypeError", | |
"evalue": "sparse array length is ambiguous; use getnnz() or shape[0]", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[57], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m g_pdna_sparse \u001b[38;5;241m=\u001b[39m \u001b[43mGraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_kernel\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdistmat_sparse\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mprecomputed\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/base.py:382\u001b[0m, in \u001b[0;36mGraph.build_kernel\u001b[0;34m(cls, data, kernel, k, bandwidth, metric, p)\u001b[0m\n\u001b[1;32m 329\u001b[0m \u001b[38;5;129m@classmethod\u001b[39m\n\u001b[1;32m 330\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mbuild_kernel\u001b[39m(\n\u001b[1;32m 331\u001b[0m \u001b[38;5;28mcls\u001b[39m,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 337\u001b[0m p\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m,\n\u001b[1;32m 338\u001b[0m ):\n\u001b[1;32m 339\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Generate Graph from geometry data based on a kernel function\u001b[39;00m\n\u001b[1;32m 340\u001b[0m \n\u001b[1;32m 341\u001b[0m \u001b[38;5;124;03m Parameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[38;5;124;03m libpysal.graph.Graph encoding kernel weights\u001b[39;00m\n\u001b[1;32m 381\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[0;32m--> 382\u001b[0m ids \u001b[38;5;241m=\u001b[39m \u001b[43m_evaluate_index\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 384\u001b[0m head, tail, weight \u001b[38;5;241m=\u001b[39m _kernel(\n\u001b[1;32m 385\u001b[0m data,\n\u001b[1;32m 386\u001b[0m bandwidth\u001b[38;5;241m=\u001b[39mbandwidth,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 391\u001b[0m ids\u001b[38;5;241m=\u001b[39mids,\n\u001b[1;32m 392\u001b[0m )\n\u001b[1;32m 393\u001b[0m \u001b[38;5;66;03m# TODO: ensure sorting\u001b[39;00m\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/_utils.py:274\u001b[0m, in \u001b[0;36m_evaluate_index\u001b[0;34m(data)\u001b[0m\n\u001b[1;32m 269\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_evaluate_index\u001b[39m(data):\n\u001b[1;32m 270\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Helper to get ids from any input.\"\"\"\u001b[39;00m\n\u001b[1;32m 271\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\n\u001b[1;32m 272\u001b[0m data\u001b[38;5;241m.\u001b[39mindex\n\u001b[1;32m 273\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(data, (pd\u001b[38;5;241m.\u001b[39mSeries, pd\u001b[38;5;241m.\u001b[39mDataFrame))\n\u001b[0;32m--> 274\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m pd\u001b[38;5;241m.\u001b[39mRangeIndex(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28;43mlen\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mdata\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m 275\u001b[0m )\n", | |
"File \u001b[0;32m~/mambaforge/envs/geosnap/lib/python3.9/site-packages/scipy/sparse/_base.py:340\u001b[0m, in \u001b[0;36m_spbase.__len__\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 339\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__len__\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[0;32m--> 340\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msparse array length is ambiguous; use getnnz()\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m 341\u001b[0m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m or shape[0]\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", | |
"\u001b[0;31mTypeError\u001b[0m: sparse array length is ambiguous; use getnnz() or shape[0]" | |
] | |
} | |
], | |
"source": [ | |
"g_pdna_sparse = Graph.build_kernel(distmat_sparse, metric='precomputed', )" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 24, | |
"id": "7e05aece-9115-4c97-b1cb-328ff9af23e9", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:27:34.957254Z", | |
"iopub.status.busy": "2023-08-29T20:27:34.956269Z", | |
"iopub.status.idle": "2023-08-29T20:27:54.430110Z", | |
"shell.execute_reply": "2023-08-29T20:27:54.429776Z", | |
"shell.execute_reply.started": "2023-08-29T20:27:34.957200Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"2.43 s ± 29.1 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"adj.pivot(index='focal', columns= 'neighbor', values='weight')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "911b3dcb-f8e0-4815-bec8-a2cb1b314c3c", | |
"metadata": {}, | |
"source": [ | |
"going form long to wide takes a little computation" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 25, | |
"id": "c597471f-31ee-4cfc-85fc-4b9c364590cc", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:27:54.431010Z", | |
"iopub.status.busy": "2023-08-29T20:27:54.430914Z", | |
"iopub.status.idle": "2023-08-29T20:27:57.681872Z", | |
"shell.execute_reply": "2023-08-29T20:27:57.681537Z", | |
"shell.execute_reply.started": "2023-08-29T20:27:54.431001Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"405 ms ± 12.6 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"%%timeit\n", | |
"matrix.reindex(nodes.values, axis=0).reindex(nodes.values, axis=1)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "c264109d-2db8-4351-923f-d89ccb2213d2", | |
"metadata": {}, | |
"source": [ | |
"but reindexing is pretty cheap" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 29, | |
"id": "b9b414ec-2534-4447-9d5f-ce2155b35b7a", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:23:20.970884Z", | |
"iopub.status.busy": "2023-08-29T20:23:20.970086Z", | |
"iopub.status.idle": "2023-08-29T20:23:44.449505Z", | |
"shell.execute_reply": "2023-08-29T20:23:44.449233Z", | |
"shell.execute_reply.started": "2023-08-29T20:23:20.970839Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"2.93 s ± 23.7 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)\n" | |
] | |
} | |
], | |
"source": [ | |
"\n", | |
"%%timeit\n", | |
"adj.pivot(index='focal', columns= 'neighbor', values='weight').reindex(nodes.values, axis=0).reindex(nodes.values, axis=1)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "9e399afe-2432-492d-9edd-f86cc52b31a6", | |
"metadata": {}, | |
"source": [ | |
"Alternatively, i could roundtrip through a Graph, because it will properly align the sparse" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 29, | |
"id": "0abfd3dc-cfd5-4fd7-a4d5-5f3efca917d3", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:31:36.634947Z", | |
"iopub.status.busy": "2023-08-29T20:31:36.634121Z", | |
"iopub.status.idle": "2023-08-29T20:31:36.840100Z", | |
"shell.execute_reply": "2023-08-29T20:31:36.839537Z", | |
"shell.execute_reply.started": "2023-08-29T20:31:36.634901Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"alternate_g = Graph.from_sparse(g.sparse, g.unique_ids)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 30, | |
"id": "0aa7fb4b-0691-42d6-8a31-cdae0c9d0753", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:31:37.382836Z", | |
"iopub.status.busy": "2023-08-29T20:31:37.381446Z", | |
"iopub.status.idle": "2023-08-29T20:31:37.426630Z", | |
"shell.execute_reply": "2023-08-29T20:31:37.426036Z", | |
"shell.execute_reply.started": "2023-08-29T20:31:37.382758Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>neighbor</th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>3701750399</td>\n", | |
" <td>0.000000</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>6191183097</td>\n", | |
" <td>4186.121094</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>1257497549</td>\n", | |
" <td>4185.868164</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>4890138485</td>\n", | |
" <td>4185.819824</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>1924777525</td>\n", | |
" <td>4185.645020</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>1835361235</td>\n", | |
" <td>2906.748047</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>4701742712</td>\n", | |
" <td>2908.202881</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>1327742768</td>\n", | |
" <td>2910.728027</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>4701742475</td>\n", | |
" <td>2889.834961</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>806273547</td>\n", | |
" <td>4999.841797</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>9460553 rows × 2 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" neighbor weight\n", | |
"focal \n", | |
"3701750399 3701750399 0.000000\n", | |
"3701750399 6191183097 4186.121094\n", | |
"3701750399 1257497549 4185.868164\n", | |
"3701750399 4890138485 4185.819824\n", | |
"3701750399 1924777525 4185.645020\n", | |
"... ... ...\n", | |
"2758616195 1835361235 2906.748047\n", | |
"2758616195 4701742712 2908.202881\n", | |
"2758616195 1327742768 2910.728027\n", | |
"2758616195 4701742475 2889.834961\n", | |
"2758616195 806273547 4999.841797\n", | |
"\n", | |
"[9460553 rows x 2 columns]" | |
] | |
}, | |
"execution_count": 30, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"alternate_g.adjacency" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "0295ef9b-dff5-4f13-8785-c2bc49adda4a", | |
"metadata": {}, | |
"source": [ | |
"but there's no way to kernelize this, because now we're back to sparse, which `build_kernel` doesnt accept" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 28, | |
"id": "bb043fb6-1078-4e66-84e4-111b378207cb", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:31:18.822105Z", | |
"iopub.status.busy": "2023-08-29T20:31:18.819868Z", | |
"iopub.status.idle": "2023-08-29T20:31:20.100897Z", | |
"shell.execute_reply": "2023-08-29T20:31:20.100367Z", | |
"shell.execute_reply.started": "2023-08-29T20:31:18.822032Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<234977x234977 sparse array of type '<class 'numpy.float64'>'\n", | |
"\twith 9460553 stored elements in COOrdinate format>" | |
] | |
}, | |
"execution_count": 28, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"alternate_g.sparse" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "d68807ad-a869-4b53-a67e-0866bc079c12", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 48, | |
"id": "f4e634f1-d115-4ed6-b780-14bc82773b2d", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:43:13.802336Z", | |
"iopub.status.busy": "2023-08-29T20:43:13.801401Z", | |
"iopub.status.idle": "2023-08-29T20:43:13.813021Z", | |
"shell.execute_reply": "2023-08-29T20:43:13.812066Z", | |
"shell.execute_reply.started": "2023-08-29T20:43:13.802286Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"sd['nodes']=nodes" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 49, | |
"id": "5e17a116-b3e3-41a4-a5d2-ca5a2a5850e0", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:43:14.067948Z", | |
"iopub.status.busy": "2023-08-29T20:43:14.067486Z", | |
"iopub.status.idle": "2023-08-29T20:43:14.073643Z", | |
"shell.execute_reply": "2023-08-29T20:43:14.072649Z", | |
"shell.execute_reply.started": "2023-08-29T20:43:14.067916Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"import matplotlib.pyplot as plt" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 50, | |
"id": "804f43fd-2639-42a8-b470-3aaaf9807aaf", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:43:14.459454Z", | |
"iopub.status.busy": "2023-08-29T20:43:14.458825Z", | |
"iopub.status.idle": "2023-08-29T20:43:14.466751Z", | |
"shell.execute_reply": "2023-08-29T20:43:14.465680Z", | |
"shell.execute_reply.started": "2023-08-29T20:43:14.459403Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"from splot.libpysal import plot_spatial_weights" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "ceaa7046-4beb-4b26-b2fe-3da66b501acc", | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"f, ax = plt.subplots(1,2, figsize=(16,8))" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 38, | |
"id": "0e1d38d6-bbc6-4b13-b9d0-1361f636754c", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T19:45:21.622672Z", | |
"iopub.status.busy": "2023-08-29T19:45:21.621527Z", | |
"iopub.status.idle": "2023-08-29T19:45:21.639982Z", | |
"shell.execute_reply": "2023-08-29T19:45:21.638935Z", | |
"shell.execute_reply.started": "2023-08-29T19:45:21.622618Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"from libpysal.weights import DistanceBand" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 40, | |
"id": "3cd4baa7-c21b-401e-a75a-4fc690a29be4", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T19:46:10.534113Z", | |
"iopub.status.busy": "2023-08-29T19:46:10.533226Z", | |
"iopub.status.idle": "2023-08-29T19:46:10.912734Z", | |
"shell.execute_reply": "2023-08-29T19:46:10.912446Z", | |
"shell.execute_reply.started": "2023-08-29T19:46:10.534073Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/weights/weights.py:224: UserWarning: The weights matrix is not fully connected: \n", | |
" There are 30 disconnected components.\n", | |
" There are 27 islands with ids: 1173, 1451, 1476, 1480, 1482, 1494, 1722, 1735, 1745, 1746, 1747, 1748, 1749, 1750, 1753, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1770, 1771, 1794.\n", | |
" warnings.warn(message)\n" | |
] | |
} | |
], | |
"source": [ | |
"db = DistanceBand.from_dataframe(sd.to_crs(sd.estimate_utm_crs()), threshold=5000)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 46, | |
"id": "b643cecd-2c8e-45b1-9817-392c96a35146", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T19:48:58.491530Z", | |
"iopub.status.busy": "2023-08-29T19:48:58.489879Z", | |
"iopub.status.idle": "2023-08-29T19:49:05.116685Z", | |
"shell.execute_reply": "2023-08-29T19:49:05.116374Z", | |
"shell.execute_reply.started": "2023-08-29T19:48:58.491476Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/weights/weights.py:224: UserWarning: The weights matrix is not fully connected: \n", | |
" There are 14 disconnected components.\n", | |
" warnings.warn(message)\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:115: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" centroids_shp = gdf.centroid.values\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:154: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" gdf.centroid.plot(ax=ax, **node_kws)\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:115: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" centroids_shp = gdf.centroid.values\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:154: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" gdf.centroid.plot(ax=ax, **node_kws)\n" | |
] | |
}, | |
{ | |
"data": { | |
"text/plain": [ | |
"Text(0.5, 1.0, 'Euclidean Graph')" | |
] | |
}, | |
"execution_count": 46, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": "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", | |
"text/plain": [ | |
"<Figure size 1152x576 with 2 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 288, | |
"width": 907 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"f, ax = plt.subplots(1,2, figsize=(16,8))\n", | |
"plot_spatial_weights(g_pdna.to_W(), sd, indexed_on='nodes', ax=ax[0])\n", | |
"ax[0].set_title('Network Graph')\n", | |
"plot_spatial_weights(db, sd, ax=ax[1])\n", | |
"ax[1].set_title('Euclidean Graph')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 34, | |
"id": "4c1463e0-42bd-4bbc-a9a9-9d6c19b4eb48", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T19:44:42.256459Z", | |
"iopub.status.busy": "2023-08-29T19:44:42.255224Z", | |
"iopub.status.idle": "2023-08-29T19:44:42.302208Z", | |
"shell.execute_reply": "2023-08-29T19:44:42.301645Z", | |
"shell.execute_reply.started": "2023-08-29T19:44:42.256406Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "TypeError", | |
"evalue": "build_distance_band() got an unexpected keyword argument 'metric'", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[34], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m g_dist \u001b[38;5;241m=\u001b[39m \u001b[43mGraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_distance_band\u001b[49m\u001b[43m(\u001b[49m\u001b[43msorted_distmat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfillna\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mprecomputed\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mthreshold\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m500\u001b[39;49m\u001b[43m)\u001b[49m\n", | |
"\u001b[0;31mTypeError\u001b[0m: build_distance_band() got an unexpected keyword argument 'metric'" | |
] | |
} | |
], | |
"source": [ | |
"g_dist = Graph.build_distance_band(sorted_distmat.fillna(0), metric='precomputed', threshold=500)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 35, | |
"id": "b7ea4e18-efa1-4242-b7ad-491a70a04a79", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T19:44:43.639771Z", | |
"iopub.status.busy": "2023-08-29T19:44:43.637338Z", | |
"iopub.status.idle": "2023-08-29T19:44:43.661627Z", | |
"shell.execute_reply": "2023-08-29T19:44:43.660301Z", | |
"shell.execute_reply.started": "2023-08-29T19:44:43.639697Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"\u001b[0;31mSignature:\u001b[0m\n", | |
"\u001b[0mGraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuild_distance_band\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mthreshold\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mbinary\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0malpha\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1.0\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mkernel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m \u001b[0mbandwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n", | |
"\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;31mDocstring:\u001b[0m\n", | |
"Generate Graph from geometry based on a distance band\n", | |
"\n", | |
"Parameters\n", | |
"----------\n", | |
"data : numpy.ndarray, geopandas.GeoSeries, geopandas.GeoDataFrame\n", | |
" geometries containing locations to compute the\n", | |
" delaunay triangulation. If a geopandas object with Point\n", | |
" geometry is provided, the .geometry attribute is used. If a numpy.ndarray\n", | |
" with shapely geometry is used, then the coordinates are extracted and used.\n", | |
" If a numpy.ndarray of a shape (2,n) is used, it is assumed to contain x, y\n", | |
" coordinates.\n", | |
"threshold : float\n", | |
" distance band\n", | |
"binary : bool, optional\n", | |
" If True w_{ij}=1 if d_{i,j}<=threshold, otherwise w_{i,j}=0\n", | |
" If False wij=dij^{alpha}, by default True.\n", | |
"alpha : float, optional\n", | |
" distance decay parameter for weight (default -1.0)\n", | |
" if alpha is positive the weights will not decline with\n", | |
" distance. Ignored if ``binary=True`` or ``kernel`` is not None.\n", | |
"kernel : str, optional\n", | |
" kernel function to use in order to weight the output graph. See\n", | |
" :meth:`Graph.build_kernel` for details. Ignored if ``binary=True``.\n", | |
"bandwidth : float (default: None)\n", | |
" distance to use in the kernel computation. Should be on the same scale as\n", | |
" the input coordinates. Ignored if ``binary=True`` or ``kernel=None``.\n", | |
"\n", | |
"Returns\n", | |
"-------\n", | |
"Graph\n", | |
" libpysal.graph.Graph encoding distance band weights\n", | |
"\u001b[0;31mFile:\u001b[0m ~/Dropbox/projects/libpysal/libpysal/graph/base.py\n", | |
"\u001b[0;31mType:\u001b[0m method" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"Graph.build_distance_band?" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "cab1c88c-938c-4a43-9e54-51206b2dbb18", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "3a13aa6b-ec10-493d-8210-35c276b17606", | |
"metadata": {}, | |
"source": [ | |
"the boxcar kernel can be used to truncate into a distance-band since `build_distance_band` doesnt accept `metric='precomputed'`" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 41, | |
"id": "bae7ab05-3658-49ec-8628-1276f3e186f5", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:42:04.446211Z", | |
"iopub.status.busy": "2023-08-29T20:42:04.445213Z", | |
"iopub.status.idle": "2023-08-29T20:42:04.495771Z", | |
"shell.execute_reply": "2023-08-29T20:42:04.495204Z", | |
"shell.execute_reply.started": "2023-08-29T20:42:04.446153Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [], | |
"source": [ | |
"g_pdna_truncated = Graph.build_kernel(sorted_distmat.fillna(0), metric='precomputed', bandwidth=2000, kernel='boxcar')" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 43, | |
"id": "a0f89afd-842b-451f-a288-aa2db4b0e996", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:42:11.259432Z", | |
"iopub.status.busy": "2023-08-29T20:42:11.259004Z", | |
"iopub.status.idle": "2023-08-29T20:42:11.274707Z", | |
"shell.execute_reply": "2023-08-29T20:42:11.273700Z", | |
"shell.execute_reply.started": "2023-08-29T20:42:11.259405Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/html": [ | |
"<div>\n", | |
"<style scoped>\n", | |
" .dataframe tbody tr th:only-of-type {\n", | |
" vertical-align: middle;\n", | |
" }\n", | |
"\n", | |
" .dataframe tbody tr th {\n", | |
" vertical-align: top;\n", | |
" }\n", | |
"\n", | |
" .dataframe thead th {\n", | |
" text-align: right;\n", | |
" }\n", | |
"</style>\n", | |
"<table border=\"1\" class=\"dataframe\">\n", | |
" <thead>\n", | |
" <tr style=\"text-align: right;\">\n", | |
" <th></th>\n", | |
" <th>neighbor</th>\n", | |
" <th>weight</th>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>focal</th>\n", | |
" <th></th>\n", | |
" <th></th>\n", | |
" </tr>\n", | |
" </thead>\n", | |
" <tbody>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49303299</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49051393</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>6209203075</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49086761</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>3701750399</th>\n", | |
" <td>49127692</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>...</th>\n", | |
" <td>...</td>\n", | |
" <td>...</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>49116448</th>\n", | |
" <td>49098013</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>3701898253</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49200337</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>4342986770</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" <tr>\n", | |
" <th>2758616195</th>\n", | |
" <td>49445655</td>\n", | |
" <td>1</td>\n", | |
" </tr>\n", | |
" </tbody>\n", | |
"</table>\n", | |
"<p>15346 rows × 2 columns</p>\n", | |
"</div>" | |
], | |
"text/plain": [ | |
" neighbor weight\n", | |
"focal \n", | |
"3701750399 49303299 1\n", | |
"3701750399 49051393 1\n", | |
"3701750399 6209203075 1\n", | |
"3701750399 49086761 1\n", | |
"3701750399 49127692 1\n", | |
"... ... ...\n", | |
"49116448 49098013 1\n", | |
"2758616195 3701898253 1\n", | |
"2758616195 49200337 1\n", | |
"2758616195 4342986770 1\n", | |
"2758616195 49445655 1\n", | |
"\n", | |
"[15346 rows x 2 columns]" | |
] | |
}, | |
"execution_count": 43, | |
"metadata": {}, | |
"output_type": "execute_result" | |
} | |
], | |
"source": [ | |
"g_pdna_truncated.adjacency" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 56, | |
"id": "f579cc74-2d3c-4fa9-a8a2-13cf8c4b9139", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-29T20:44:30.437868Z", | |
"iopub.status.busy": "2023-08-29T20:44:30.436671Z", | |
"iopub.status.idle": "2023-08-29T20:44:32.156273Z", | |
"shell.execute_reply": "2023-08-29T20:44:32.155959Z", | |
"shell.execute_reply.started": "2023-08-29T20:44:30.437796Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"name": "stderr", | |
"output_type": "stream", | |
"text": [ | |
"/Users/knaaptime/Dropbox/projects/libpysal/libpysal/weights/weights.py:224: UserWarning: The weights matrix is not fully connected: \n", | |
" There are 40 disconnected components.\n", | |
" warnings.warn(message)\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:115: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" centroids_shp = gdf.centroid.values\n", | |
"/Users/knaaptime/mambaforge/envs/geosnap/lib/python3.9/site-packages/splot/_viz_libpysal_mpl.py:154: UserWarning: Geometry is in a geographic CRS. Results from 'centroid' are likely incorrect. Use 'GeoSeries.to_crs()' to re-project geometries to a projected CRS before this operation.\n", | |
"\n", | |
" gdf.centroid.plot(ax=ax, **node_kws)\n" | |
] | |
}, | |
{ | |
"data": { | |
"text/plain": [ | |
"(<Figure size 720x720 with 1 Axes>, <AxesSubplot:>)" | |
] | |
}, | |
"execution_count": 56, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": "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", | |
"text/plain": [ | |
"<Figure size 720x720 with 1 Axes>" | |
] | |
}, | |
"metadata": { | |
"image/png": { | |
"height": 370, | |
"width": 572 | |
}, | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plot_spatial_weights(g_pdna_truncated.to_W(), sd, indexed_on='nodes')" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "8102c89d-5bd0-4409-8f68-11f4c18cb2a4", | |
"metadata": {}, | |
"source": [ | |
"(that centroid for the water polygon gets attached to its nearest intersection before computing the neighbor-set, which is why it always ends up in the figure)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "dc6ac4e1-003c-40b3-b01b-80943947e8b0", | |
"metadata": {}, | |
"source": [ | |
"this also gives rise to some useful combinations, like taking the k-nearest neighbors, subject to a network distance constraint" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"id": "21193a9c-78e3-4729-b661-f42792f12ca7", | |
"metadata": {}, | |
"source": [ | |
"`sorted_distmat` is a network distance-band of 5k" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 60, | |
"id": "1416a304-34b7-4577-a0fe-325e987bbe8d", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T04:43:11.108488Z", | |
"iopub.status.busy": "2023-08-30T04:43:11.108043Z", | |
"iopub.status.idle": "2023-08-30T04:43:11.222010Z", | |
"shell.execute_reply": "2023-08-30T04:43:11.221247Z", | |
"shell.execute_reply.started": "2023-08-30T04:43:11.108461Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"ename": "TypeError", | |
"evalue": "'<' not supported between instances of 'memoryview' and 'float'", | |
"output_type": "error", | |
"traceback": [ | |
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", | |
"\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", | |
"Cell \u001b[0;32mIn[60], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m g_pdna_knn \u001b[38;5;241m=\u001b[39m \u001b[43mGraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbuild_knn\u001b[49m\u001b[43m(\u001b[49m\u001b[43msorted_distmat\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfillna\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mvalues\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mprecomputed\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m5\u001b[39;49m\u001b[43m)\u001b[49m\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/base.py:427\u001b[0m, in \u001b[0;36mGraph.build_knn\u001b[0;34m(cls, data, k, metric, p)\u001b[0m\n\u001b[1;32m 400\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Generate Graph from geometry data based on k-nearest neighbors search\u001b[39;00m\n\u001b[1;32m 401\u001b[0m \n\u001b[1;32m 402\u001b[0m \u001b[38;5;124;03mParameters\u001b[39;00m\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 423\u001b[0m \u001b[38;5;124;03m libpysal.graph.Graph encoding KNN weights\u001b[39;00m\n\u001b[1;32m 424\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m 425\u001b[0m ids \u001b[38;5;241m=\u001b[39m _evaluate_index(data)\n\u001b[0;32m--> 427\u001b[0m head, tail, weight \u001b[38;5;241m=\u001b[39m \u001b[43m_kernel\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 428\u001b[0m \u001b[43m \u001b[49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 429\u001b[0m \u001b[43m \u001b[49m\u001b[43mbandwidth\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minf\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 430\u001b[0m \u001b[43m \u001b[49m\u001b[43mmetric\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmetric\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 431\u001b[0m \u001b[43m \u001b[49m\u001b[43mkernel\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mboxcar\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 432\u001b[0m \u001b[43m \u001b[49m\u001b[43mk\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mk\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 433\u001b[0m \u001b[43m \u001b[49m\u001b[43mp\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mp\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 434\u001b[0m \u001b[43m \u001b[49m\u001b[43mids\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 435\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 437\u001b[0m \u001b[38;5;66;03m# TODO: ensure sorting\u001b[39;00m\n\u001b[1;32m 439\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mcls\u001b[39m\u001b[38;5;241m.\u001b[39mfrom_arrays(head, tail, weight)\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/_kernel.py:146\u001b[0m, in \u001b[0;36m_kernel\u001b[0;34m(coordinates, bandwidth, metric, kernel, k, ids, p, taper)\u001b[0m\n\u001b[1;32m 144\u001b[0m smooth \u001b[38;5;241m=\u001b[39m kernel(D\u001b[38;5;241m.\u001b[39mdata, bandwidth)\n\u001b[1;32m 145\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 146\u001b[0m smooth \u001b[38;5;241m=\u001b[39m \u001b[43m_kernel_functions\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkernel\u001b[49m\u001b[43m]\u001b[49m\u001b[43m(\u001b[49m\u001b[43mD\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdata\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mbandwidth\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 148\u001b[0m sp \u001b[38;5;241m=\u001b[39m sparse\u001b[38;5;241m.\u001b[39mcsc_array((smooth, D\u001b[38;5;241m.\u001b[39mindices, D\u001b[38;5;241m.\u001b[39mindptr), dtype\u001b[38;5;241m=\u001b[39msmooth\u001b[38;5;241m.\u001b[39mdtype)\n\u001b[1;32m 150\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m taper:\n", | |
"File \u001b[0;32m~/Dropbox/projects/libpysal/libpysal/graph/_kernel.py:42\u001b[0m, in \u001b[0;36m_boxcar\u001b[0;34m(distances, bandwidth)\u001b[0m\n\u001b[1;32m 41\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_boxcar\u001b[39m(distances, bandwidth):\n\u001b[0;32m---> 42\u001b[0m r \u001b[38;5;241m=\u001b[39m (\u001b[43mdistances\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m<\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mbandwidth\u001b[49m)\u001b[38;5;241m.\u001b[39mastype(\u001b[38;5;28mint\u001b[39m)\n\u001b[1;32m 43\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m r\n", | |
"\u001b[0;31mTypeError\u001b[0m: '<' not supported between instances of 'memoryview' and 'float'" | |
] | |
} | |
], | |
"source": [ | |
"g_pdna_knn = Graph.build_knn(sorted_distmat.fillna(0).values, metric='precomputed', k=5)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 57, | |
"id": "bcb6c411-6616-4940-8b8f-80024ab59c21", | |
"metadata": { | |
"execution": { | |
"iopub.execute_input": "2023-08-30T04:40:38.273669Z", | |
"iopub.status.busy": "2023-08-30T04:40:38.269283Z", | |
"iopub.status.idle": "2023-08-30T04:40:38.287208Z", | |
"shell.execute_reply": "2023-08-30T04:40:38.286176Z", | |
"shell.execute_reply.started": "2023-08-30T04:40:38.273609Z" | |
}, | |
"tags": [] | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"\u001b[0;31mSignature:\u001b[0m \u001b[0mGraph\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbuild_knn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mk\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmetric\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'euclidean'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mp\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", | |
"\u001b[0;31mDocstring:\u001b[0m\n", | |
"Generate Graph from geometry data based on k-nearest neighbors search\n", | |
"\n", | |
"Parameters\n", | |
"----------\n", | |
"data : numpy.ndarray, geopandas.GeoSeries, geopandas.GeoDataFrame\n", | |
" geometries over which to compute a kernel. If a geopandas object with Point\n", | |
" geoemtry is provided, the .geometry attribute is used. If a numpy.ndarray\n", | |
" with shapely geoemtry is used, then the coordinates are extracted and used.\n", | |
" If a numpy.ndarray of a shape (2,n) is used, it is assumed to contain x, y\n", | |
" coordinates.\n", | |
"k : int\n", | |
" number of nearest neighbors.\n", | |
"metric : string or callable (default: 'euclidean')\n", | |
" distance function to apply over the input coordinates. Supported options\n", | |
" depend on whether or not scikit-learn is installed. If so, then any\n", | |
" distance function supported by scikit-learn is supported here. Otherwise,\n", | |
" only euclidean, minkowski, and manhattan/cityblock distances are admitted.\n", | |
"p : int (default: 2)\n", | |
" parameter for minkowski metric, ignored if metric != \"minkowski\".\n", | |
"\n", | |
"Returns\n", | |
"-------\n", | |
"Graph\n", | |
" libpysal.graph.Graph encoding KNN weights\n", | |
"\u001b[0;31mFile:\u001b[0m ~/Dropbox/projects/libpysal/libpysal/graph/base.py\n", | |
"\u001b[0;31mType:\u001b[0m method" | |
] | |
}, | |
"metadata": {}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"Graph.build_knn?" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": null, | |
"id": "6d2a564c-318e-4db8-822c-a64430ee3c0a", | |
"metadata": {}, | |
"outputs": [], | |
"source": [] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python [conda env:geosnap]", | |
"language": "python", | |
"name": "conda-env-geosnap-py" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.9.16" | |
}, | |
"widgets": { | |
"application/vnd.jupyter.widget-state+json": { | |
"state": {}, | |
"version_major": 2, | |
"version_minor": 0 | |
} | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 5 | |
} |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment