pysal · nightcoder26 · Apr 16, 2025 · Apr 16, 2025
diff --git a/.gitignore b/.gitignore
@@ -2,7 +2,7 @@
 *.pyc
 .rope*
 .idea/
-notebooks/.ipynb_checkpoints/
+docs/notebooks/.ipynb_checkpoints/
 .DS_Store
 .ipynb_checkpoints/
 *.bak
@@ -14,6 +14,7 @@ notebooks/.ipynb_checkpoints/
 *.egg-info
 dist
 build
+generated
 eggs
 parts
 bin

diff --git a/notebooks/azp.ipynb → docs/notebooks/azp.ipynb b/notebooks/azp.ipynb → docs/notebooks/azp.ipynb
diff --git a/notebooks/component_policy.ipynb → docs/notebooks/component_policy.ipynb b/notebooks/component_policy.ipynb → docs/notebooks/component_policy.ipynb
diff --git a/notebooks/facloc-disperse-real-world.ipynb → ...otebooks/facloc-disperse-real-world.ipynb b/notebooks/facloc-disperse-real-world.ipynb → ...otebooks/facloc-disperse-real-world.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "*Authors:* [Erin Olson](https://github.com/erinrolson), [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)\n",
     "\n",
-    "This tutorial extends the [Empirical examples](./facloc-real-world.ipynb) notebook, specifically for the $p$-dispersion problem. A deeper dive into the $p$-dispersion problem can be found [here](./p-dispersion.ipynb).\n",
+    "This tutorial extends the [Empirical examples](facloc-real-world.ipynb) notebook, specifically for the $p$-dispersion problem. A deeper dive into the $p$-dispersion problem can be found [here](p-dispersion.ipynb).\n",
     "Also, this tutorial demonstrates the use of different solvers that [PULP](https://github.com/coin-or/pulp) supports."
    ]
   },

diff --git a/notebooks/facloc-lscpb-real-world.ipynb → docs/notebooks/facloc-lscpb-real-world.ipynb b/notebooks/facloc-lscpb-real-world.ipynb → docs/notebooks/facloc-lscpb-real-world.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "*Authors:* [Erin Olson](https://github.com/erinrolson), [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)\n",
     "\n",
-    "This tutorial extends the [Empirical examples](./facloc-real-world.ipynb) notebook, specifically for the Backup Coverage Location Set Covering Problem (LSCP-B). A deeper dive into the LSCP-B can be found [here](./lscpb.ipynb).\n",
+    "This tutorial extends the [Empirical examples](facloc-real-world.ipynb) notebook, specifically for the Backup Coverage Location Set Covering Problem (LSCP-B). A deeper dive into the LSCP-B can be found [here](lscpb.ipynb).\n",
     "Also, this tutorial demonstrates the use of different solvers that [PULP](https://github.com/coin-or/pulp) supports."
    ]
   },

diff --git a/notebooks/facloc-real-world.ipynb → docs/notebooks/facloc-real-world.ipynb b/notebooks/facloc-real-world.ipynb → docs/notebooks/facloc-real-world.ipynb
@@ -8,7 +8,7 @@
     "\n",
     "*Authors:* [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)\n",
     "\n",
-    "This tutorial aims to show a facility location application. To achieve this goal the tuorial will solve mulitple real world facility location problems using a dataset describing an area of census tract 205, San Francisco. The general scenarios can be stated as: store sites should supply the demand in this census tract considering the distance between the two sets of sites: demand points and candidate supply sites. Four fundamental facility location models are utilized to highlight varying outcomes dependent on objectives: LSCP (Location Set Covering Problem), MCLP (Maximal Coverage Location Problem), P-Median and P-Center. For further information on these models, it's recommended to see the notebooks that explain more deeply about each one: [LSCP](./lscp.ipynb), [MCLP](./mclp.ipynb), [P-Median](./p-median.ipynb), [P-Center](./p-center.ipynb).\n",
+    "This tutorial aims to show a facility location application. To achieve this goal the tuorial will solve mulitple real world facility location problems using a dataset describing an area of census tract 205, San Francisco. The general scenarios can be stated as: store sites should supply the demand in this census tract considering the distance between the two sets of sites: demand points and candidate supply sites. Four fundamental facility location models are utilized to highlight varying outcomes dependent on objectives: LSCP (Location Set Covering Problem), MCLP (Maximal Coverage Location Problem), P-Median and P-Center. For further information on these models, it's recommended to see the notebooks that explain more deeply about each one: [LSCP](lscp.ipynb), [MCLP](mclp.ipynb), [P-Median](p-median.ipynb), [P-Center](p-center.ipynb).\n",
     "\n",
     "Also, this tutorial demonstrates the use of different solvers that [PULP](https://github.com/coin-or/pulp) supports."
    ]

diff --git a/notebooks/lscp.ipynb → docs/notebooks/lscp.ipynb b/notebooks/lscp.ipynb → docs/notebooks/lscp.ipynb
diff --git a/notebooks/lscp_capacity.ipynb → docs/notebooks/lscp_capacity.ipynb b/notebooks/lscp_capacity.ipynb → docs/notebooks/lscp_capacity.ipynb
diff --git a/notebooks/lscp_gis.ipynb → docs/notebooks/lscp_gis.ipynb b/notebooks/lscp_gis.ipynb → docs/notebooks/lscp_gis.ipynb
diff --git a/notebooks/lscpb.ipynb → docs/notebooks/lscpb.ipynb b/notebooks/lscpb.ipynb → docs/notebooks/lscpb.ipynb
@@ -13,7 +13,7 @@
     "\n",
     "*Authors:* [Erin Olson](https://github.com/erinrolson), [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)\n",
     "\n",
-    "The Backup Coverage Problem is refered to as an extension of the LSCP (Location Set Covering Problem) as it seeks a solution to LSCP while selecting a set of facilities that optimizes for backup coverage (Church and Murray, 2018). If you are unfamiliar with LSCP the following [notebook](./lscp.ipynb) explains the problem formulation in detail.\n",
+    "The Backup Coverage Problem is refered to as an extension of the LSCP (Location Set Covering Problem) as it seeks a solution to LSCP while selecting a set of facilities that optimizes for backup coverage (Church and Murray, 2018). If you are unfamiliar with LSCP the following [notebook](lscp.ipynb) explains the problem formulation in detail.\n",
     "\n",
     "Daskin and Stern (1981) posed the following problem, which Church and Murray (2018) refers to as LSCP-B (Location Set Covering Problem with Backup): _Find the minimum number of facilities and their locations such that each demand is covered, while maximizing the number of backup coverage instances among demand areas._\n",
     "\n",

diff --git a/notebooks/maxp.ipynb → docs/notebooks/maxp.ipynb b/notebooks/maxp.ipynb → docs/notebooks/maxp.ipynb
diff --git a/notebooks/mclp.ipynb → docs/notebooks/mclp.ipynb b/notebooks/mclp.ipynb → docs/notebooks/mclp.ipynb
diff --git a/notebooks/mclp_gis.ipynb → docs/notebooks/mclp_gis.ipynb b/notebooks/mclp_gis.ipynb → docs/notebooks/mclp_gis.ipynb
diff --git a/notebooks/p-center.ipynb → docs/notebooks/p-center.ipynb b/notebooks/p-center.ipynb → docs/notebooks/p-center.ipynb
diff --git a/notebooks/p-dispersion.ipynb → docs/notebooks/p-dispersion.ipynb b/notebooks/p-dispersion.ipynb → docs/notebooks/p-dispersion.ipynb
diff --git a/notebooks/p-median.ipynb → docs/notebooks/p-median.ipynb b/notebooks/p-median.ipynb → docs/notebooks/p-median.ipynb
diff --git a/notebooks/p-median_variations.ipynb → docs/notebooks/p-median_variations.ipynb b/notebooks/p-median_variations.ipynb → docs/notebooks/p-median_variations.ipynb
diff --git a/notebooks/randomregion.ipynb → docs/notebooks/randomregion.ipynb b/notebooks/randomregion.ipynb → docs/notebooks/randomregion.ipynb
diff --git a/notebooks/reg-k-means.ipynb → docs/notebooks/reg-k-means.ipynb b/notebooks/reg-k-means.ipynb → docs/notebooks/reg-k-means.ipynb
diff --git a/notebooks/skater.ipynb → docs/notebooks/skater.ipynb b/notebooks/skater.ipynb → docs/notebooks/skater.ipynb
diff --git a/notebooks/ward.ipynb → docs/notebooks/ward.ipynb b/notebooks/ward.ipynb → docs/notebooks/ward.ipynb