Merge pull request #17 from darribas/license

License

infrastructure/booksite/LICENSE

@@ -0,0 +1,8 @@
+Geographic Data Science with PySAL and the PyData Stack
+=======================================================
+
+This project is released under a Creative Commons BY-NC-ND license. 
+
+For more information, please visit:
+
+https://creativecommons.org/licenses/by-nc-nd/4.0/

infrastructure/booksite/build.sh

@@ -21,14 +21,15 @@ cp host/infrastructure/booksite/toc.yml host/tmp_book/_data/toc.yml
 # Fill in
 #---------------------------
 # LICENSE
+cp host/infrastructure/booksite/LICENSE host/tmp_book/LICENSE
 # Code requirements
 # Bibliography
 # Build book
 #---------------------------
 echo "Building book..."
 jupyter-book build host/tmp_book
 echo "Building site HTML..."
-cd host/tmp_book && make site
+cd host/tmp_book && make build
 # Move over to docs folder to be served online
 echo "Moving build over to docs folder..."
 cd /home/jovyan

infrastructure/booksite/intro.md

@@ -6,6 +6,6 @@
 
 Placeholder for the introduction to the book
 
-## LICENSE
+---
 
-**IMPORTANT**: this work is under a license!
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

infrastructure/docker/Dockerfile

@@ -2,25 +2,6 @@ FROM darribas/gds_py:2.0
 
 LABEL maintainer="Dani Arribas-Bel <d.arribas-bel@liverpool.ac.uk>"
 
-#--- Jekyll ---#
-
-USER root
-
-RUN apt-get update \
- && apt-get install -y ruby-full build-essential zlib1g-dev 
-
-# Install Ruby Gems to ~/gems
-ENV GEM_HOME="/home/$NB_USER/gems"
-ENV PATH="/home/$NB_USER/gems/bin:$PATH"
-
-USER $NB_UID
-
-RUN gem install jekyll bundler jekyll-scholar
-
-# Clean up
-RUN rm -rf $GEM_HOME/cache
-RUN rm -rf /usr/local/bundle/cache
-
 #--- Jupyter-book ---#
 RUN pip install -U --no-deps \
                     bs4 \
@@ -30,8 +11,21 @@ RUN pip install -U --no-deps \
                     pytest \
                     ruamel.yaml
 RUN jupyter-book create testbook --demo
+
+#--- Jekyll ---#
+# Taken inspiration from:
+# https://github.com/jupyter/jupyter-book/blob/master/jupyter_book/Dockerfile
+
+USER root
+RUN apt-get update \
+ && apt-get install -y ruby-full build-essential zlib1g-dev libc-dev
+USER $NB_UID
+# Install Ruby Gems to ~/gems
+ENV GEM_HOME="/home/$NB_USER/gems"
+ENV PATH="/home/$NB_USER/gems/bin:$PATH"
 RUN cd /home/$NB_USER/testbook \
- && gem install bundler -v 1.17.2 \
+#&& mv Gemfile.lock original_Gemfile.lock \
+ && gem install bundler -v '2.0.1' \
  && bundle install
 
 # JupyText
@@ -50,7 +44,7 @@ RUN echo "c.NotebookApp.contents_manager_class = "\
 RUN rm -rf $GEM_HOME/cache \
  && rm -rf /usr/local/bundle/cache \
  && rm -r /home/$NB_USER/testbook \
- && conda clean -tipsy
+ && conda clean --all
 
 EXPOSE 4000
 

notebooks/00_toc.ipynb

@@ -28,7 +28,9 @@
     "- [Spatial Inequality](09_spatial_inequality)\n",
     "- [Clustering and Regionalization](10_clustering_and_regionalization)\n",
     "- [Spatial Regression](11_regression)\n",
-    "- [Spatial Feature Engineering](12_feature_engineering)\n"
+    "- [Spatial Feature Engineering](12_feature_engineering)\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
    ]
   }
  ],

notebooks/00_toc.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -37,4 +37,5 @@ jupyter:
 - [Spatial Regression](11_regression)
 - [Spatial Feature Engineering](12_feature_engineering)
 
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.
 <!-- #endregion -->

notebooks/01_geospatial_computational_environment.ipynb

@@ -2610,25 +2610,11 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/01_geospatial_computational_environment.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -994,14 +994,5 @@ Write a properly documented function that:
   3. If the number is odd, it should be stored in the dictionary as a key, with a value of "odd."
 4. Returns the now-filled dictionary.
 
-```python
 
-```
-
-```python
-
-```
-
-```python
-
-```
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/02_spatial_data.ipynb

@@ -6,6 +6,15 @@
    "source": [
     "# Spatial Data"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/02_spatial_data.md

@@ -6,11 +6,16 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
     name: python3
 ---
 
 # Spatial Data
+
+
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/03_spatial_data_processing.ipynb

@@ -4738,6 +4738,15 @@
     "\n",
     "message is, if you have the column in the table use it, but many cases you do not have the column and need to go the spatial join route"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/03_spatial_data_processing.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -138,3 +138,7 @@ df.columns
 
 message is, if you have the column in the table use it, but many cases you do not have the column and need to go the spatial join route
 <!-- #endregion -->
+
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/04_spatial_weights.ipynb

@@ -3342,6 +3342,15 @@
     "\n",
     "[4] Dean, N., Dong, G., and Price, G. \"Frontiers in Residential Segregation: Understanding Neighbourhood Boundaries and their Impacts.\" *Tijdschrift voor economische en sociale geografie*, in press"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/04_spatial_weights.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -1108,3 +1108,8 @@ These are the starkest contrasts in the map, and result in the most distinctive
 [3] Fitzpatrick, M C.,Preisser, E.L., Porter, A., Elkinton, J., Waller, L.A., Carlin, B. P., and Ellison, A.M. 2010. “Ecological Boundary Detection Using Bayesian Areal Wombling.” *Ecology* 91 (12): 3448–3455.
 
 [4] Dean, N., Dong, G., and Price, G. "Frontiers in Residential Segregation: Understanding Neighbourhood Boundaries and their Impacts." *Tijdschrift voor economische en sociale geografie*, in press
+
+
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/05_choropleth.ipynb

@@ -2413,6 +2413,15 @@
     "\"Interregional inequality dynamics in Mexico.\" *Spatial Economic Analysis*, 5:\n",
     "277-298."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/05_choropleth.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -651,3 +651,8 @@ structure and dynamics." *Cities*, 43: 69-77.
 Rey, S.J. and M.L. Guitierez. (2010)
 "Interregional inequality dynamics in Mexico." *Spatial Economic Analysis*, 5:
 277-298.
+
+
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/06_spatial_autocorrelation.ipynb

@@ -1432,11 +1432,13 @@
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
+   "cell_type": "markdown",
    "metadata": {},
-   "outputs": [],
-   "source": []
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/06_spatial_autocorrelation.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -459,6 +459,7 @@ Moran, P. A. (1950). Notes on continuous stochastic phenomena. Biometrika, 37(1/
 
 Tukey, J. W. (1977). Exploratory data analysis (Vol. 2).
 
-```python
 
-```
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/07_local_autocorrelation.ipynb

@@ -1103,6 +1103,15 @@
    "source": [
     "As you can see, the results are virtually the same for $G_i$ and $G_i^*$. Also, at first glance, these maps appear to be visually similar to the final LISA map from above, and this leads to the question of why use the $G$ statistics at all. The answer to this question is that the two sets of local statistics, Local $I$ and the local $G$, are complementary statistics. This is because the local $I$ by itself cannot distinguish between the two forms of positive spatial association while the G can. At the same time, the G statistic does not consider negative spatial association, while the local I statistic does."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {

notebooks/07_local_autocorrelation.md

@@ -6,7 +6,7 @@ jupyter:
       extension: .md
       format_name: markdown
       format_version: '1.1'
-      jupytext_version: 1.1.1
+      jupytext_version: 1.1.6
   kernelspec:
     display_name: Python 3
     language: python
@@ -423,3 +423,8 @@ plt.show()
 ```
 
 As you can see, the results are virtually the same for $G_i$ and $G_i^*$. Also, at first glance, these maps appear to be visually similar to the final LISA map from above, and this leads to the question of why use the $G$ statistics at all. The answer to this question is that the two sets of local statistics, Local $I$ and the local $G$, are complementary statistics. This is because the local $I$ by itself cannot distinguish between the two forms of positive spatial association while the G can. At the same time, the G statistic does not consider negative spatial association, while the local I statistic does.
+
+
+---
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-nd/4.0/">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>.

notebooks/08_point_pattern_analysis.ipynb

@@ -1817,6 +1817,15 @@
     "# Display the figure\n",
     "plt.show()"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "\n",
+    "<a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\"><img alt=\"Creative Commons License\" style=\"border-width:0\" src=\"https://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png\" /></a><br />This work is licensed under a <a rel=\"license\" href=\"http://creativecommons.org/licenses/by-nc-nd/4.0/\">Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License</a>."
+   ]
   }
  ],
  "metadata": {