From dad67c814f7d6ab8c229e6bde5c2da9b9a2784d6 Mon Sep 17 00:00:00 2001 From: Julien Barnier Date: Fri, 24 May 2024 10:59:38 +0000 Subject: [PATCH] Built site for gh-pages --- .nojekyll | 2 +- changelog.html | 1 + development.html | 8 ++-- gallery_geo.html | 8 ++-- gallery_interaction.html | 14 +++---- gallery_marks.html | 8 ++-- gallery_themes.html | 14 +++---- gallery_transforms.html | 10 ++--- getting_started.html | 16 +++---- index.html | 10 ++--- search.json | 8 ++-- sitemap.xml | 20 ++++----- usage.html | 44 ++++++++++---------- usage_files/figure-html/cell-10-output-1.svg | 2 +- usage_files/figure-html/cell-5-output-1.svg | 2 +- 15 files changed, 84 insertions(+), 83 deletions(-) diff --git a/.nojekyll b/.nojekyll index 5cad7a7..7b2a51c 100644 --- a/.nojekyll +++ b/.nojekyll @@ -1 +1 @@ -380c5522 \ No newline at end of file +612c7d7b \ No newline at end of file diff --git a/changelog.html b/changelog.html index f6e1c8b..21b475b 100644 --- a/changelog.html +++ b/changelog.html @@ -194,6 +194,7 @@

pyobsplot 0.4.3 (dev)<
diff --git a/development.html b/development.html index 6c34bfc..3ba51a5 100644 --- a/development.html +++ b/development.html @@ -228,9 +228,9 @@

Install fom source

If you want to build pyobsplot from source, you’ll have to follow these steps:

  • Install node.js
  • -
  • Install hatch dependency management system
  • +
  • Install rye dependency management system
  • Clone the pyobsplot repository
  • -
  • Install Python dependencies with : hatch shell
  • +
  • Install Python dependencies with : rye sync
  • Install pyobsplot-js JavaScript dependencies with : npm install --workspaces
  • Install pyobsplot dependencies with : npm install
@@ -266,7 +266,7 @@

Tests

Debug mode

“Debug mode” outputs the computed JavaScript plot structure (the one passed to Plot.plot).

To activate it, add debug=True when creating your plot generator object:

-
+
op = Obsplot(render="widget", debug=True)

If using the widget renderer, debug output will be displayed in JavaScript console. With the jsdom renderer, it will be displayed directly in the notebook.

@@ -279,7 +279,7 @@

Releases

  • If necessary release the npm package with npm publish in packages/pyobsplot-js
  • Check that the min_npm_version value in .utils is correct
  • Change version in NEWS.md and src/pyobsplot/__about__.py
  • -
  • Release the Python package with hatch build and hatch publish in pyobsplot
  • +
  • Release the Python package with rye build and rye publish in pyobsplot
  • Tag the version in git
  • Create a release on Github
  • Bump to dev version in pyproject.toml and NEWS.md
  • diff --git a/gallery_geo.html b/gallery_geo.html index 7322f21..1299163 100644 --- a/gallery_geo.html +++ b/gallery_geo.html @@ -215,7 +215,7 @@

    Mapping and spatial data

    Geo mark

    The Geo mark allows to draw geographic features such as points, lines and polygons. These marks data are passed as GeoJSON.

    This allows to create choropleth maps such as the following:

    -
    +
    from pyobsplot import Obsplot, Plot
     import geopandas as gpd
     import pandas as pd
    @@ -268,7 +268,7 @@ 

    Geo mark

    Of course other marks can be used in conjunction with geo marks. This example represents the density of Walmarts supermarkets and is taken from the Mapping notebook.

    -
    +
    # Load US states from TopoJson with geopandas and convert to GeoJson
     states = gpd.read_file("data/us-counties-10m.json", layer="states").to_json()
     nation = gpd.read_file("data/us-counties-10m.json", layer="nation").to_json()
    @@ -306,7 +306,7 @@ 

    Geo mark

    Raster mark

    The Raster mark creates an image from spatial data.

    Plot allows to do different type of spatial interpolations, such as nearest, which draws voronoi cells around values:

    -
    +
    import polars as pl
     
     ca55 = pl.read_csv("data/ca55-south.csv")
    @@ -347,7 +347,7 @@ 

    Raster mark

    Or the more recent random walk interpolation:

    -
    +
    flare_map("random-walk")
    diff --git a/gallery_interaction.html b/gallery_interaction.html index 379af34..b39d03e 100644 --- a/gallery_interaction.html +++ b/gallery_interaction.html @@ -229,7 +229,7 @@

    Interaction

    Tooltips

    The tip mark, introduced in Observable 0.6.7, allows to easily add tooltips to a plot.

    -
    +
    import polars as pl
     from pyobsplot import Plot, d3, js
     
    @@ -248,7 +248,7 @@ 

    Tooltips

    )
    @@ -256,7 +256,7 @@

    Tooltips

    Crosshair mark

    The crosshair mark alows to display the coordinates of the nearest point.

    -
    +
    penguins = pl.read_csv("data/penguins.csv")
     
     Plot.plot(
    @@ -275,7 +275,7 @@ 

    Crosshair mark

    )
    @@ -283,7 +283,7 @@

    Crosshair mark

    Pointer interaction

    More generally, the pointer interaction allows to filter out the closest data point and apply some custom marks to it.

    -
    +
    aapl = stocks.filter(pl.col("Symbol") == "AAPL")
     
     Plot.plot(
    @@ -314,7 +314,7 @@ 

    Pointer interaction)

    @@ -324,7 +324,7 @@

    Pointer interaction

    @@ -246,7 +246,7 @@

    light theme

    dark theme

    The dark theme produces plots with a black background and a white foreground color.

    -
    +
    op = Obsplot(theme="dark")
     
     op(
    @@ -262,7 +262,7 @@ 

    dark theme

    )
    @@ -271,7 +271,7 @@

    dark theme

    current theme

    The “current” theme uses a transparent background and a currentColor foreground, so it should keep the current color theme:

    -
    +
    op = Obsplot(theme="current")
     
     op(
    @@ -287,7 +287,7 @@ 

    current theme)

    @@ -298,7 +298,7 @@

    current theme

    Or, for a bit more complex example:

    -
    +
    Plot.plot(
         {
             "marginLeft": 75,
    @@ -276,7 +276,7 @@ 

    Overview

    )
    @@ -324,7 +324,7 @@

    Credits