scverse / scverse/spatialdata-plot

Vega-like viewconfigurations

Open
#388 1 comment 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

Dominant language
Python
Stars
86
Forks
21
Avg merge
14h 50m
Merged PRs (30d)
3

Description

During the hackathon in Basel we have brainstormed on the specification that would allow for viewing data across the spatialdata visualization ecosystem with one viewconfig. This issue describes the current ideas of this viewconfiguration.

Data

The first field in the view configuration is related to the data and specifies the zarr store and the particular elements that we want to visualize. It also includes a filtering step. For example:

"schema": "https://spatialdata-plot.github.io/schema/viewconfig/v1.json"
"height": 15 # This is in inches
"width": 14
"data": [
        {
            "name": "{UUID1}",
            "url": "blobs.zarr"
            "format": "spatialdata",
            "version": "0.2.0"
        },
        {
          "name": "{UUID2}",
          "format": "spatialdata_image",
          "version": "0.1.0",
          "source": "UUID1",
          "transform": [
            {
              "type": "filter",
              "expr": "datum['images/blobs_image']"
            }
          ]
        },
  ]      

Here the first block contains the location of the zarr store. We specify the particular format of the zarr store and the version. The name is serving as a UUID in the document so that other blocks in the configuration can refer to a particular block. Typically, on the data a transform is applied. In most cases for SpatialData this would be a filter transform initially to get the particular element that we require. The height and width is the overall size in inches of the plot.

Scales

Scales provide a mapping of a series of values to a different series of values, whether that is axes limits and ticks
or a mapping of values to color.

"scales": [
        { <!-- Example of scale for continuous variable-->
          "name": "color_0", <!-- can chain render_... calls that would use different normalize objects-->
          "type": "linear",
          "zero": true, <!-- Whether to include 0 value in the color mapping, useful for labels-->
          "domain": [0, 1],  <!-- this is the vmin vmax-->
          "clamp": true,  <!-- This is the clip of the normalize object in matplotlib-->
          "range": {"scheme": "gray"}
        },
        { <!-- Example of scale for categorical variable-->
      "name": "color",
      "type": "ordinal",
      "domain": {"data": "UUID of spatial element", "field": "category"}, <!-- category here is column-->
      "range": {"scheme": "category20"} <!--This is only required if there are no hex strings specified before, in some cases a user can already have the hexstrings representing color. In this case the color encoding in marks must be used.-->
        },
        {
              "name": "X_SCALE",
              "type": "linear",
              "zero": true,
              "domain": [-180, 180], <!-- This is the extent of the axes after having applied the transform to coordinate system-->
              "range": "width" <!-- refers to plot width-->
            },
            {
              "name": "Y_SCALE",
              "type": "linear",
              "zero": true,
              "domain": [-81, 87],
              "range": "height" <!-- refers to plot height-->
            }
    ],

Marks

Marks define the actual plots of the particular elements.

"marks": [
        {
          "type": "raster", <!-- type of element -->
          "from": {"data": "UUID3"},
          "zindex": 0,
          "encode": {
              <!-- "channel": {"value": 0}, // with "data": "UUID2" -->
              "opacity": {"value": 1}, <!-- sdata-plot "alpha". Also, it was fillOpacity -->
              "color": {"scale": "normalize", "field": "channel_zero_name"}
              <!--"zindex": {"field": "point_importance"}-->
          }
        },
        {
          "type": "shape", <!-- type of element -->
          "from": {"data": "UUID5"},
          "zindex": 1,
          "encode": {
              <!-- "channel": {"value": 0},
              "opacity": {"value": 1}, <!-- sdata-plot "alpha". Also, it was fillOpacity -->
              "color": {hexstrings} <!-- in case of predetermined hexstrings --> 
              <!--"zindex": {"field": "point_importance"}-->
          }
        }
      ],

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reviewing the proposed view configuration sections for data, scales, and marks, including their SpatialData references and transforms. Done means the view configuration specification has been resolved and agreed across the spatialdata visualization ecosystem; the issue does not name implementation files or tests.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
data-visualization
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
20/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.