From 801fe2dc11245b383f903a05e9dd7f83cac43e79 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Tue, 6 Feb 2024 22:53:14 +0000 Subject: [PATCH] Update documentation --- _sources/user/quickstart.rst.txt | 3 +-- api.html | 8 ++++---- full_ref.html | 18 +++++++++--------- searchindex.js | 2 +- user/quickstart.html | 11 ++++------- 5 files changed, 19 insertions(+), 23 deletions(-) diff --git a/_sources/user/quickstart.rst.txt b/_sources/user/quickstart.rst.txt index 21451e7f..b5cdf8ce 100644 --- a/_sources/user/quickstart.rst.txt +++ b/_sources/user/quickstart.rst.txt @@ -13,8 +13,7 @@ What you'll need Before we can start running Markov chains, you'll need to: * Install ``gerrychain`` from PyPI. See the :doc:`installation guide <./install>` for instructions. -* Download `this example json of Pennsylvania's VTDs -`_. +* Download `this example json of Pennsylvania's VTDs `_. * Open your preferred Python environment (e.g. JupyterLab, IPython, or a ``.py`` file in your favorite editor) in the directory containing the ``PA_VTDs.json`` file that you downloaded. diff --git a/api.html b/api.html index b1a27e8b..f07d259b 100644 --- a/api.html +++ b/api.html @@ -155,7 +155,7 @@

Adjacency graphs
-add_data(df: <Mock name='mock.DataFrame' id='140185783486256'>, columns: Optional[Iterable[str]] = None) → None[source]
+add_data(df: <Mock name='mock.DataFrame' id='139849168410512'>, columns: Optional[Iterable[str]] = None) → None[source]

Add columns of a DataFrame to a graph as node attributes by matching the DataFrame’s index to node ids.

@@ -211,7 +211,7 @@

Adjacency graphs
-classmethod from_geodataframe(dataframe: <Mock name='mock.DataFrame' id='140185783486256'>, adjacency: str = 'rook', cols_to_add: Optional[List[str]] = None, reproject: bool = False, ignore_errors: bool = False) → gerrychain.graph.graph.Graph[source]
+classmethod from_geodataframe(dataframe: <Mock name='mock.DataFrame' id='139849168410512'>, adjacency: str = 'rook', cols_to_add: Optional[List[str]] = None, reproject: bool = False, ignore_errors: bool = False) → gerrychain.graph.graph.Graph[source]

Creates the adjacency Graph of geometries described by dataframe. The areas of the polygons are included as node attributes (with key area). The shared perimeter of neighboring polygons are included as edge attributes @@ -311,7 +311,7 @@

Adjacency graphs
-join(dataframe: <Mock name='mock.DataFrame' id='140185783486256'>, columns: Optional[List[str]] = None, left_index: Optional[str] = None, right_index: Optional[str] = None) → None[source]
+join(dataframe: <Mock name='mock.DataFrame' id='139849168410512'>, columns: Optional[List[str]] = None, left_index: Optional[str] = None, right_index: Optional[str] = None) → None[source]

Add data from a dataframe to the graph, matching nodes to rows when the node’s left_index attribute equals the row’s right_index value.

@@ -1328,7 +1328,7 @@

Markov chains
-class gerrychain.updaters.DataTally(data: Union[Dict, <Mock name='mock.Series' id='140185783486352'>, str], alias: str)[source]
+class gerrychain.updaters.DataTally(data: Union[Dict, <Mock name='mock.Series' id='139849168410608'>, str], alias: str)[source]

An updater for tallying numerical data that is not necessarily stored as node attributes

diff --git a/full_ref.html b/full_ref.html index b3feeb14..630ec86b 100644 --- a/full_ref.html +++ b/full_ref.html @@ -1585,7 +1585,7 @@

Graph
-gerrychain.graph.adjacency.neighbors(df: <Mock name='mock.GeoDataFrame' id='140185783431376'>, adjacency: str) → Dict[source]
+gerrychain.graph.adjacency.neighbors(df: <Mock name='mock.GeoDataFrame' id='139849168871776'>, adjacency: str) → Dict[source]
@@ -1691,7 +1691,7 @@

Graph
-gerrychain.graph.geo.identify_utm_zone(df: <Mock name='mock.GeoDataFrame' id='140185783431376'>) → int[source]
+gerrychain.graph.geo.identify_utm_zone(df: <Mock name='mock.GeoDataFrame' id='139849168871776'>) → int[source]

Given a GeoDataFrame, identify the Universal Transverse Mercator zone number for the centroid of the geometries in the dataframe.

@@ -1851,7 +1851,7 @@

Graph
-add_data(df: <Mock name='mock.DataFrame' id='140185783486256'>, columns: Optional[Iterable[str]] = None) → None[source]
+add_data(df: <Mock name='mock.DataFrame' id='139849168410512'>, columns: Optional[Iterable[str]] = None) → None[source]

Add columns of a DataFrame to a graph as node attributes by matching the DataFrame’s index to node ids.

@@ -1912,7 +1912,7 @@

Graph
-classmethod from_geodataframe(dataframe: <Mock name='mock.DataFrame' id='140185783486256'>, adjacency: str = 'rook', cols_to_add: Optional[List[str]] = None, reproject: bool = False, ignore_errors: bool = False) → gerrychain.graph.graph.Graph[source]
+classmethod from_geodataframe(dataframe: <Mock name='mock.DataFrame' id='139849168410512'>, adjacency: str = 'rook', cols_to_add: Optional[List[str]] = None, reproject: bool = False, ignore_errors: bool = False) → gerrychain.graph.graph.Graph[source]

Creates the adjacency Graph of geometries described by dataframe. The areas of the polygons are included as node attributes (with key area). The shared perimeter of neighboring polygons are included as edge attributes @@ -2012,7 +2012,7 @@

Graph
-join(dataframe: <Mock name='mock.DataFrame' id='140185783486256'>, columns: Optional[List[str]] = None, left_index: Optional[str] = None, right_index: Optional[str] = None) → None[source]
+join(dataframe: <Mock name='mock.DataFrame' id='139849168410512'>, columns: Optional[List[str]] = None, left_index: Optional[str] = None, right_index: Optional[str] = None) → None[source]

Add data from a dataframe to the graph, matching nodes to rows when the node’s left_index attribute equals the row’s right_index value.

@@ -2100,7 +2100,7 @@

Graph
-gerrychain.graph.graph.add_boundary_perimeters(graph: gerrychain.graph.graph.Graph, geometries: <Mock name='mock.Series' id='140185783486352'>) → None[source]
+gerrychain.graph.graph.add_boundary_perimeters(graph: gerrychain.graph.graph.Graph, geometries: <Mock name='mock.Series' id='139849168410608'>) → None[source]

Add shared perimeter between nodes and the total geometry boundary.

Parameters
@@ -2120,7 +2120,7 @@

Graph
-gerrychain.graph.graph.check_dataframe(df: <Mock name='mock.DataFrame' id='140185783486256'>) → None[source]
+gerrychain.graph.graph.check_dataframe(df: <Mock name='mock.DataFrame' id='139849168410512'>) → None[source]
Returns

None

@@ -2516,7 +2516,7 @@

Partition
-to_series() → <Mock name='mock.Series' id='140185783486352'>[source]
+to_series() → <Mock name='mock.Series' id='139849168410608'>[source]
Returns

The assignment as a pandas.Series.

@@ -4483,7 +4483,7 @@

Updaters
-class gerrychain.updaters.tally.DataTally(data: Union[Dict, <Mock name='mock.Series' id='140185783486352'>, str], alias: str)[source]
+class gerrychain.updaters.tally.DataTally(data: Union[Dict, <Mock name='mock.Series' id='139849168410608'>, str], alias: str)[source]

Bases: object

An updater for tallying numerical data that is not necessarily stored as node attributes

diff --git a/searchindex.js b/searchindex.js index c882f9c6..4dd3a4f2 100644 --- a/searchindex.js +++ b/searchindex.js @@ -1 +1 @@ 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\ No newline at end of file diff --git a/user/quickstart.html b/user/quickstart.html index 6b1bfaee..94e9f01a 100644 --- a/user/quickstart.html +++ b/user/quickstart.html @@ -108,14 +108,11 @@

What you’ll need

  • Install gerrychain from PyPI. See the installation guide for instructions.

    • -

  • Download `this example json of Pennsylvania’s VTDs

    • +

  • Download this example json of Pennsylvania’s VTDs.

    • +

  • Open your preferred Python environment (e.g. JupyterLab, IPython, or a .py file +in your favorite editor) in the directory containing the PA_VTDs.json file +that you downloaded.

    • -

    <https://github.com/mggg/GerryChain/blob/main/docs/_static/PA_VTDs.json>`_. -* Open your preferred Python environment (e.g. JupyterLab, IPython, or a .py file

    -
    -

    in your favorite editor) in the directory containing the PA_VTDs.json file -that you downloaded.

    -

    Throughout this guide, we will assume that the user is working with a jupyter notebook or a python script file (a *.py file). We will also assume that the end user is working through this guide is familiar with, but still relatively new to Python.