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martinRenou merged 1 commit into from
Feb 2, 2023
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Docs: Fix some broken links #1571

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12 changes: 6 additions & 6 deletions docs/usage/figure.md
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Expand Up @@ -2,8 +2,8 @@

`Figure` API documentation can be accessed using the following links:

1. [Figure](/api/figure) class
2. [`figure`](/api/pyplot/#bqplot.pyplot.figure) method in `pyplot`
1. [Figure](bqplot/api/figure) class
2. [`figure`](bqplot/api/pyplot/#bqplot.pyplot.figure) method in `pyplot`

In this section, we'll be focusing on pyplot API to create and configure `figure` objects.

Expand All @@ -17,9 +17,9 @@ fig = plt.figure()

### Attributes

#### [Style Attributes](/api/figure/#bqplot.Figure--style-attributes)
#### [Style Attributes](bqplot/api/figure/#bqplot.Figure--style-attributes)
Style attributes can be used for styling the figure (title, backgrounds, legends) etc.
#### [Layout Attributes](/api/figure/#bqplot.Figure--layout-attributes)
#### [Layout Attributes](bqplot/api/figure/#bqplot.Figure--layout-attributes)
Layout attributes can be used for controlling the dimensions and margins

### Code Examples
Expand Down Expand Up @@ -48,7 +48,7 @@ fig.layout.height = "500px"
Since bqplot figures are SVG nodes any CSS styles applicable to SVG can be passed as a `dict` to the `background_style` attribute, like so:

```
background_style = {"stroke": "blue",
background_style = {"stroke": "blue",
"fill": "red",
"fill-opacity": .3}
fig = plt.figure(title="Figure", background_style=background_style)
Expand All @@ -73,4 +73,4 @@ As you can see in the image above the grey region is the figure margin.


#### Interactions
Refer to the [Interaction](interactions/index.md) document for more details
Refer to the [Interaction](interactions/index.md) document for more details
10 changes: 5 additions & 5 deletions docs/usage/object-model.md
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Expand Up @@ -4,7 +4,7 @@ Following are the core components in the `Object Model`:

1. [Scales](../api/scales.md)
2. [Marks](../api/marks.md)
3. [Axes](../api/axes.md)
3. [Axes](../api/axes.md)
4. [Figure](../api/figure.md)


Expand All @@ -13,7 +13,7 @@ The following are the steps to build a Figure in bqplot using the Object Model:
1. Build the scales for `x` and `y` quantities using the `Scale` classes (Scales map the data into pixels in the figure)
2. Build the marks using the `Mark` classes. Marks represent the core plotting objects (lines, scatter, bars, pies etc.). Marks take the scale objects created in step 1 as arguments
3. Build the axes for `x` and `y` scales
4. Finally create a figure using `Figure` class. Figure takes marks and axes as inputs.
4. Finally create a figure using `Figure` class. Figure takes marks and axes as inputs.
__Figure object is a instance of `DOMWidget` and can be rendered like any other jupyter widgets__

Let's look a few examples (`pyplot` usage available [here](pyplot.md)):
Expand Down Expand Up @@ -87,7 +87,7 @@ xax = bq.Axis(scale=xs, label="X")
yax = bq.Axis(scale=ys, orientation="vertical", label="Y")

# 3. Create a Lines and Scatter marks by passing in the scales
# additional attributes (stroke_width, colors etc.) can be passed as attributes
# additional attributes (stroke_width, colors etc.) can be passed as attributes
# to the mark objects as needed
line = bq.Lines(x=x, y=y, scales={"x": xs, "y": ys}, colors=["green"], stroke_width=3)
scatter = bq.Scatter(
Expand All @@ -102,7 +102,7 @@ bq.Figure(marks=[line, scatter], axes=[xax, yax], title="Scatter and Line")

#### Summary

__Object Model__ is a verbose but fully customizable object-oriented API for plotting. Lower level constructs like scales, axes etc. have to explicitly constructed.
__Object Model__ is a verbose but fully customizable object-oriented API for plotting. Lower level constructs like scales, axes etc. have to explicitly constructed.
For detailed usage refer to the [example notebooks](https://github.com/bqplot/bqplot/tree/master/examples/Marks/Object%20Model) using `Object Model`.

__Object Model__ can be used to build re-usable plotting widgets and widget libraries. More details can be found in [here]
__Object Model__ can be used to build re-usable plotting widgets and widget libraries. More details can be found in [here]