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[pre-commit.ci] pre-commit autoupdate #767

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Oct 9, 2024
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[pre-commit.ci] pre-commit autoupdate #767

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fad5ed2
[pre-commit.ci] pre-commit autoupdate
pre-commit-ci[bot] Oct 7, 2024
708d0cf
reup linting & formating
jGaboardi Oct 8, 2024
fe3d7a8
Update pyproject.toml
martinfleis Oct 8, 2024
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4 changes: 2 additions & 2 deletions .pre-commit-config.yaml
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@@ -1,7 +1,7 @@
files: "libpysal\/"
files: "libpysal\/|docs\/"
repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: "v0.5.0"
rev: "v0.6.9"
hooks:
- id: ruff
- id: ruff-format
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4 changes: 1 addition & 3 deletions docs/conf.py
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@@ -1,5 +1,3 @@
# -*- coding: utf-8 -*-
#
# libpysal documentation build configuration file, created by
# sphinx-quickstart on Wed Jun 6 15:54:22 2018.
#
Expand All @@ -17,8 +15,8 @@
# documentation root, use os.path.abspath to make it absolute, like shown here.
#
import sphinx_bootstrap_theme
import libpysal

import libpysal

# -- General configuration ------------------------------------------------

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31 changes: 17 additions & 14 deletions docs/user-guide/data/examples.ipynb
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Expand Up @@ -35,7 +35,7 @@
"metadata": {},
"outputs": [],
"source": [
"from libpysal.examples import get_path \n"
"from libpysal.examples import get_path"
]
},
{
Expand Down Expand Up @@ -72,6 +72,7 @@
"outputs": [],
"source": [
"import libpysal\n",
"\n",
"dbf = libpysal.io.open(get_path(\"mexicojoin.dbf\"))"
]
},
Expand Down Expand Up @@ -357,7 +358,7 @@
}
],
"source": [
"libpysal.examples.load_example('dataset42')"
"libpysal.examples.load_example(\"dataset42\")"
]
},
{
Expand Down Expand Up @@ -387,7 +388,7 @@
}
],
"source": [
"balt_url = libpysal.examples.get_url('Baltimore')\n",
"balt_url = libpysal.examples.get_url(\"Baltimore\")\n",
"balt_url"
]
},
Expand Down Expand Up @@ -421,7 +422,7 @@
}
],
"source": [
"libpysal.examples.explain('taz')"
"libpysal.examples.explain(\"taz\")"
]
},
{
Expand All @@ -430,7 +431,7 @@
"metadata": {},
"outputs": [],
"source": [
"taz = libpysal.examples.load_example('taz')"
"taz = libpysal.examples.load_example(\"taz\")"
]
},
{
Expand Down Expand Up @@ -485,7 +486,7 @@
}
],
"source": [
"libpysal.examples.explain('Baltimore')"
"libpysal.examples.explain(\"Baltimore\")"
]
},
{
Expand All @@ -502,7 +503,7 @@
}
],
"source": [
"balt = libpysal.examples.load_example('Baltimore')"
"balt = libpysal.examples.load_example(\"Baltimore\")"
]
},
{
Expand Down Expand Up @@ -673,7 +674,8 @@
],
"source": [
"from libpysal.examples import explain\n",
"explain('Tampa1')"
"\n",
"explain(\"Tampa1\")"
]
},
{
Expand All @@ -691,7 +693,8 @@
],
"source": [
"from libpysal.examples import load_example\n",
"tampa1 = load_example('Tampa1')"
"\n",
"tampa1 = load_example(\"Tampa1\")"
]
},
{
Expand Down Expand Up @@ -820,7 +823,7 @@
"metadata": {},
"outputs": [],
"source": [
"tampa_counties_shp = tampa1.load('tampa_counties.shp')"
"tampa_counties_shp = tampa1.load(\"tampa_counties.shp\")"
]
},
{
Expand Down Expand Up @@ -858,7 +861,7 @@
"metadata": {},
"outputs": [],
"source": [
"tampa_df = geopandas.read_file(tampa1.get_path('tampa_counties.shp'))"
"tampa_df = geopandas.read_file(tampa1.get_path(\"tampa_counties.shp\"))"
]
},
{
Expand Down Expand Up @@ -936,7 +939,7 @@
}
],
"source": [
"libpysal.examples.explain('Rio Grande do Sul')"
"libpysal.examples.explain(\"Rio Grande do Sul\")"
]
},
{
Expand All @@ -960,7 +963,7 @@
}
],
"source": [
"rio = libpysal.examples.load_example('Rio Grande do Sul')"
"rio = libpysal.examples.load_example(\"Rio Grande do Sul\")"
]
},
{
Expand Down Expand Up @@ -1051,7 +1054,7 @@
}
],
"source": [
"libpysal.examples.remote_datasets.datasets # a listing of all remotes"
"libpysal.examples.remote_datasets.datasets # a listing of all remotes"
]
},
{
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51 changes: 28 additions & 23 deletions docs/user-guide/graph/matching-graph.ipynb
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Expand Up @@ -22,13 +22,13 @@
"metadata": {},
"outputs": [],
"source": [
"import sys\n",
"import os\n",
"sys.path.append(os.path.abspath('..'))\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import sys\n",
"\n",
"sys.path.append(os.path.abspath(\"..\"))\n",
"import geopandas\n",
"import pandas"
"import matplotlib.pyplot as plt\n",
"import numpy as np"
]
},
{
Expand All @@ -46,7 +46,7 @@
"metadata": {},
"outputs": [],
"source": [
"points = np.row_stack([(10.2, 5.1), (4.7, 2.2), (5.3, 5.7), (2.7, 5.3), (7,4)])\n",
"points = np.row_stack([(10.2, 5.1), (4.7, 2.2), (5.3, 5.7), (2.7, 5.3), (7, 4)])\n",
"gdf = geopandas.GeoDataFrame(geometry=geopandas.points_from_xy(*points.T))"
]
},
Expand Down Expand Up @@ -108,8 +108,8 @@
}
],
"source": [
"f, ax =plt.subplots(1,3)\n",
"for i,g in enumerate((g1, g2, g3)):\n",
"f, ax = plt.subplots(1, 3)\n",
"for i, g in enumerate((g1, g2, g3)):\n",
" g.plot(gdf, ax=ax[i])\n",
" ax[i].set_title(f\"k = {i+1}\")"
]
Expand All @@ -128,6 +128,7 @@
"outputs": [],
"source": [
"import geodatasets\n",
"\n",
"stores = geopandas.read_file(geodatasets.get_path(\"geoda liquor_stores\")).explode(\n",
" index_parts=False\n",
")"
Expand Down Expand Up @@ -261,8 +262,8 @@
}
],
"source": [
"f, ax =plt.subplots(1,3)\n",
"for i,g in enumerate((g1, g5, g10)):\n",
"f, ax = plt.subplots(1, 3)\n",
"for i, g in enumerate((g1, g5, g10)):\n",
" g.plot(stores, ax=ax[i], nodes=False)\n",
" ax[i].set_title(f\"k = {(1, 5, 10)[i]}\")"
]
Expand Down Expand Up @@ -293,8 +294,8 @@
"source": [
"sources = stores.sample(100)\n",
"sinks = stores[~stores.index.isin(sources.index)].sample(100)\n",
"ax = sources.plot(color='red')\n",
"sinks.plot(color='blue', ax=ax)\n",
"ax = sources.plot(color=\"red\")\n",
"sinks.plot(color=\"blue\", ax=ax)\n",
"plt.show()"
]
},
Expand All @@ -304,8 +305,9 @@
"metadata": {},
"outputs": [],
"source": [
"from libpysal.graph._matching import _spatial_matching\n",
"import shapely"
"import shapely\n",
"\n",
"from libpysal.graph._matching import _spatial_matching"
]
},
{
Expand Down Expand Up @@ -334,7 +336,9 @@
"metadata": {},
"outputs": [],
"source": [
"crosspattern_heads, crosspattern_tails, weights, mip = _spatial_matching(x=sink_coordinates, y = source_coordinates, n_matches=1, return_mip=True)"
"crosspattern_heads, crosspattern_tails, weights, mip = _spatial_matching(\n",
" x=sink_coordinates, y=source_coordinates, n_matches=1, return_mip=True\n",
")"
]
},
{
Expand Down Expand Up @@ -364,12 +368,13 @@
"outputs": [],
"source": [
"lines = shapely.linestrings(\n",
" list( \n",
" zip(\n",
" map(list, source_coordinates[crosspattern_heads]),\n",
" map(list, sink_coordinates[crosspattern_tails])\n",
" list(\n",
" zip(\n",
" map(list, source_coordinates[crosspattern_heads]),\n",
" map(list, sink_coordinates[crosspattern_tails]),\n",
" strict=False,\n",
" )\n",
" )\n",
")\n",
")"
]
},
Expand All @@ -390,9 +395,9 @@
}
],
"source": [
"ax = sources.plot(color='red')\n",
"sinks.plot(color='blue', ax=ax)\n",
"geopandas.GeoSeries(lines).plot(linewidth=1, color='k', ax=ax)\n",
"ax = sources.plot(color=\"red\")\n",
"sinks.plot(color=\"blue\", ax=ax)\n",
"geopandas.GeoSeries(lines).plot(linewidth=1, color=\"k\", ax=ax)\n",
"plt.show()"
]
}
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22 changes: 10 additions & 12 deletions docs/user-guide/graph/w_g_migration.ipynb
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Expand Up @@ -47,8 +47,7 @@
"metadata": {},
"outputs": [],
"source": [
"from libpysal import weights\n",
"from libpysal import graph"
"from libpysal import graph, weights"
]
},
{
Expand Down Expand Up @@ -85,11 +84,10 @@
"source": [
"%matplotlib inline\n",
"\n",
"import seaborn as sns\n",
"import pandas as pd\n",
"import geopandas as gpd\n",
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"import seaborn as sns\n",
"\n",
"from libpysal import examples\n",
"\n",
"%load_ext watermark\n",
Expand Down Expand Up @@ -2710,7 +2708,7 @@
"metadata": {},
"outputs": [],
"source": [
"w_queen.transform = 'r'\n",
"w_queen.transform = \"r\"\n",
"wlag = lag_spatial(w_queen, y)"
]
},
Expand Down Expand Up @@ -3111,7 +3109,7 @@
"metadata": {},
"outputs": [],
"source": [
"ngdf = gdf.set_index('NAME')"
"ngdf = gdf.set_index(\"NAME\")"
]
},
{
Expand Down Expand Up @@ -3162,7 +3160,7 @@
}
],
"source": [
"g['Ashe']"
"g[\"Ashe\"]"
]
},
{
Expand Down Expand Up @@ -3742,9 +3740,9 @@
}
],
"source": [
"m = ngdf.loc[g['Ashe'].index].explore(color=\"#25b497\")\n",
"ngdf.loc[['Ashe']].explore(m=m, color=\"#fa94a5\")\n",
"g.explore(ngdf, m=m, focal='Ashe')"
"m = ngdf.loc[g[\"Ashe\"].index].explore(color=\"#25b497\")\n",
"ngdf.loc[[\"Ashe\"]].explore(m=m, color=\"#fa94a5\")\n",
"g.explore(ngdf, m=m, focal=\"Ashe\")"
]
},
{
Expand Down
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