visdesignlab / upset2

UpSet - Visualizing Intersecting Sets

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UpSet 2.0 – Visualizing Intersecting Sets

UpSet 2 is deployed at https://upset.multinet.app/.

Deployment Status: Netlify Status

About

UpSet is an interactive, web based visualization technique designed to analyze set-based data. UpSet visualizes both, set intersections and their properties, and the items (elements) in the dataset.

Please see the https://upset.app for more info about UpSet.

This version is a re-implementation using modern web technologies of the original UpSet.

UpSet 2 is described in this short poster:

Kiran Gadhave, Hendrik Strobelt, Nils Gehlenborg, Alexander Lex
UpSet 2: From Prototype to Tool
Proceedings of the IEEE Information Visualization Conference – Posters (InfoVis ’19), 2019.

UpSet 2 is based on the original UpSet, which was first described in this paper:

Alexander Lex, Nils Gehlenborg, Hendrik Strobelt, Romain Vuillemot, Hanspeter Pfister
UpSet: Visualization of Intersecting Sets
IEEE Transactions on Visualization and Computer Graphics (InfoVis), 20(12): 1983--1992, doi:10.1109/TVCG.2014.2346248, 2014.

UpSet 2.0 as a React Component

UpSet 2.0 can be imported as a React component using:

npm install @visdesignlab/upset2-react

Note that UpSet 2.0 requires a react version of 16.0 or higher.

Import the component using import { Upset } from @visdesignlab/upset2-react in your react component.

UpSet 2.0 Data

Data structure

The raw data structure for UpSet should be a list of set membership objects.

Raw Data

The data object should be an array of objects. Each object should contain all the set membership boolean values as well as any attributes.

This data example shows only two characters from the Simpsons.

const rawData = [
   {
    "Name": "Homer",
    "School": false,
    "Blue Hair": false,
    "Duff Fan": true,
    "Evil": false,
    "Male": true,
    "Power Plant": true,
    "Age": 40
  },
  {
    "Name": "Marge",
    "School": false,
    "Blue Hair": true,
    "Duff Fan": false,
    "Evil": false,
    "Male": false,
    "Power Plant": false,
    "Age": 36
  },
]

The data and/or attributes objects can be JSON strings or traditional JS objects.

Loading Data into the UpSet 2.0 component

Loading Raw Data

Data uploaded to UpSet must follow the UpSet 2.0 Data Structure. Simply pass the data object to the Upset component in the data field.

The example below is a simple usecase for loading raw data into UpSet 2.0.

const main = () => {
  const rawData = [
    {
      "Name": "Homer",
      "School": false,
      "Blue Hair": false,
      "Duff Fan": true,
      "Evil": false,
      "Male": true,
      "Power Plant": true,
      "Age": 40
    },
    {
      "Name": "Marge",
      "School": false,
      "Blue Hair": true,
      "Duff Fan": false,
      "Evil": false,
      "Male": false,
      "Power Plant": false,
      "Age": 36
    },
  ];

  return <Upset data={rawData} />;
}
Pre-Processing Data

If you want to pre-process your data to gain access to the data objects generated and use by UpSet, or are having issues with the raw data loading, you must use the process function from UpSet 2.0 Core. First, import process from @visdesignlab/upset2-react. Then, before loading rendering the UpSet 2.0 component, call the process function, which takes the data and annotations objects as arguments.

The data object should be the same as raw data defined in Data Structure.

The annotations object should be an object with a nested object field columns. This field is a mapping of the column name to the column's data type. The columns field should contain an entry for each possible column in the data, as well as the type for each column.

The entry corresponding to the column which is the name of the item should be of type label. This will be used to generate ids and name the subsets. Note: There should only be one label column. Any entry for a set membership column should be a boolean type. Finally, any entry for an attribute column should be a number type.

In the example below, the item name is Name, noted by the label type. The sets are School, Blue Hair, Duff Fan, Evil, Male, and Power Plant. The only attribute in this dataset is Age, which is a number. This is clear in the annotations object, which denotes this.

const annotations = {
  "columns": {
    "Name": "label",
    "School": "boolean",
    "Blue Hair": "boolean",
    "Duff Fan": "boolean",
    "Evil": "boolean",
    "Male": "boolean",
    "Power Plant": "boolean",
    "Age": "number"
  }
}

The example below details a simple usecase of the process function.

import { Upset, process } from '@visdesignlab/upset2-react';

const main = () => {
  const rawData = [
    {
      "Name": "Homer",
      "School": false,
      "Blue Hair": false,
      "Duff Fan": true,
      "Evil": false,
      "Male": true,
      "Power Plant": true,
      "Age": 40
    },
    {
      "Name": "Marge",
      "School": false,
      "Blue Hair": true,
      "Duff Fan": false,
      "Evil": false,
      "Male": false,
      "Power Plant": false,
      "Age": 36
    },
  ];

  const annotations = {
    columns: {
      "Name": "label",
      "School": "boolean",
      "Blue Hair": "boolean",
      "Duff Fan": "boolean",
      "Evil": "boolean",
      "Male": "boolean",
      "Power Plant": "boolean",
      "Age": "number"
    }
  };

  const processedData = process(rawData, annotations);

  return <Upset data={processedData} />;
}

UpSet 2.0 component options

All options

  • data: The data for the Upset component. See UpSet 2.0 Data for more information.
  • config (optional): The configuration options for the Upset component. This can be partial. See Configuration Options for more details.
  • visualizeAttributes (optional)(string[]): List of attribute names (strings) which should be visualized. Defaults to the first 3 if no value is provided. If an empty list is provided, displays no attributes.
  • visualizeUpsetAttributes (optional)(boolean): Whether or not to visualize UpSet generated attributes (degree and deviation). Defaults to false.
  • allowAttributeRemoval (optional)(boolean): Whether or not to allow the user to remove attribute columns. This should be enabled only if there is an option within the parent application which allows for attributes to be added after removal. Default attribute removal behavior in UpSet 2.0 is done via context menu on attribute headers. Defaults to false.
  • hideSettings (optional)(boolean): Hide the aggregations/filter settings sidebar.
  • parentHasHeight (optional)(boolean): Indicates if the parent component has a fixed height. If this is set to false, the plot will occupy the full viewport height. When set to true, the plot will fit entirely within the parent component. Defaults to false.
  • extProvenance (optional): External provenance actions and TrrackJS object for provenance history tracking and actions. This should only be used if your tool is using TrrackJS and the Trrack object you provide has all the actions used by UpSet 2.0. Provenance is still tracked if nothing is provided. See App.tsx to see how UpSet 2.0 and Multinet use an external Trrack object. Note that initializeProvenanceTracking and getActions are used to ensure that the provided provenance object is compatible. The provided provenance object must have a type compatible with the extProvenance UpSet 2.0 prop type.
  • provVis (optional): Sidebar options for the provenance visualization sidebar. See Trrack-Vis for more information about Trrack provenance visualization.
  • elementSidebar (optional): Sidebar options for the element visualization sidebar. This sidebar is used for element queries, element selection datatable, and supplimental plot generation.
  • altTextSidebar (optional): Sidebar options for the text description sidebar. This sidebar is used to display the generated text descriptions for an Upset 2.0 plot, given that the generateAltText function is provided.
  • generateAltText (optional)(() => Promise<AltText>): Async function which should return a generated AltText object. See Alt Text Generation for more information about Alt Text generation.
Configuration (Grammar) options

The configuration (grammar) is used both as internal tracking for UpSet 2.0, and to generate the alt-text via Multinet's API. Other implementations which are attempting to generate text descriptions using the same API must generate a grammar containing the values below. Reference upset-alt-txt-gen for more information about generating text descriptions.

If no configuration options are provided, the default will be:

  • No aggregation
  • Sort rows by Size - Descending
  • Sort visible sets by Alphabetical
  • Minimum degree filter: 0
  • Maximum degree filter: 6
  • Show the "no set" row
  • Hide empty rows

The configuration options are documented below:

  • plotInformation: An object which contains meta data abut the plot. The three keys are description, sets, and items. The values should be strings.
    • description: A short description about the dataset. Ex: Movie genres and ratings
    • sets: A very short description of what the sets are in the data. Ex: Movie Genres
    • items: A very short description of what the items in the data are. Ex: Movies
  • horizontal: Boolean value describing whether or not the plot is horizontal. Defaults to false. Note this value is not used by UpSet 2.0 but may be used to generate text descriptions.
  • firstAggregateBy (string): Describes the first aggregation state. Defaults to "None". Possible values:
    • "None": No first level of aggregation.
    • "Sets": Aggregate by which rows contain each set.
    • "Degree": Aggregate by the Degree (set membership count) of the rows.
    • "Deviations": Aggregate by positive and negative deviation.
    • "Overlaps": Aggregate by the minimum specified overlap degree.
  • firstOverlapDegree: Describes the first aggregation's degree of overlap required. This is only used if firstAggregateBy is set to Overlaps. Defaults to 2.
  • secondAggregateBy (string): Describes the second (nested) aggregation state. Must be "None" if firstAggregateBy is set to "None". If firstAggregateBy is not "None", this value cannot be the same as firstAggregateBy. Possible values:
    • "None": No first level of aggregation.
    • "Sets": Aggregate by which rows contain each set.
    • "Degree": Aggregate by the Degree (set membership count) of the rows.
    • "Deviations": Aggregate by positive and negative deviation.
    • "Overlaps": Aggregate by the minimum specified overlap degree.
  • secondOverlapDegree: Describes the second aggregation's degree of overlap required. This is only used if secondAggregateBy is set to Overlaps. Defaults to 2.
  • sortVisibleBy (string): Describes the sorting of the visible sets (above the intersection matrix). Defaults to "Alphabetical". Possible values:
    • "Alphabetical": Sort from A - Z. Note Only A - Z sorting is supported.
    • "Ascending": Sort based on size, low to high.
    • "Descending": Sort based on size, high to low.
  • sortBy (string): Describes the sorting of the subset rows. Defaults to S"ize". Possible values:
    • "Size": Sorts the plot by the subset size (cardinality) rows.
    • "Degree": Sorts the plot by the degree (set membership) of the rows.
    • "Deviation": Sorts the plot by the calculated deviation. See the original 2014 paper for more information about deviation and how it is calculated.
    • Set_{Set Name}: Sort the plot by Degree (Ascending), but always sort subsets containing the provided set first. For example, a dataset containing movie genres could be sorted by Set_Comedy.
    • Any attribute: Sort the plot by the calculated mean of an attribute value. For example, if the dataset contains an attribute named ReleaseDate, sorting by "ReleaseDate" would use the calculated average release date for the items in the rows.
  • sortByOrder (string): The order to sort the plot. This is simply an order indicator, the actual sort type is defined in sortBy. Possible values:
    • "Ascending": Sort from low to high
    • "Descending": Sort from high to low
    • "None": This should only be used if sortBy sorts by a set (ex: Set_Comedy). This is because there is only one possible direction for this sorting method.
  • filters: An object that defines which subsets (rows) are shown in the UpSet plot.
    • maxVisible (number): The maximum degree (set membership count) that a subset can have and still be shown. Defaults to 6.
    • minVisible (number): The minimum degree (set membership count) that a subset must have and still be shown. Defaults to 0.
    • hideEmpty (boolean): Whether or not to hide empty subset rows. Defaults to true.
    • hideNoSet (boolean): Whether or not to hide the subset which is a member of no sets. Defaults to false.
  • visibleSets (string[]): List of which sets are visible and loaded into the UpSet plot. (Ex: ["Set_Comedy", "Set_Drama", "Set_Action"]).
  • visibleAttributes (string[]): List of which attributes are visible and loaded into the UpSet plot. (Ex: ["ReleaseDate", "AvgRating"]).
  • bookmarkedIntersections: List of which subsets (ids) are bookmarked. Each list entry should be an object with the following key-value pairs:
    • id (string): Generated id for the subset. In UpSet 2.0, the id uses ~&~ as a set delimiter, and always prepends Subset_. Ex: Subset_Action~&~Adventure~&~Comedy
    • label (string): Human readable label for the subset. Ex: Action & Adventure & Comedy
    • size (number): The size of the subset.
  • collapsed (string[]): List of the aggregate rows which are currently collapsed. (Ex: `["Agg_Degree_1, Agg_Degree_4"]).
  • plots: Object for noting which plots are currently rendered in the element sidebar. Has two fields: scatterplots and histograms. Both are lists of the below object. Note This should not be included in your grammar unless it was generated with the UpSet 2.0 interface.
    • keys:
      • id (string): Generated id for the plot.
      • type (string): Type of plot. Will always be scatterplot or histogram.
      • x (string): Attribute for the x axis
      • y (string): Attribute for the y axis
      • xScaleLog (boolean): Whether or not to use a logoritihmic scale for the x axis.
      • yScaleLog (boolean): Whether or not to use a logoritihmic scale for the y axis.
  • allSets: List of set objects for every set in the dataset. Each object requires the following fields:
    • name (string): Set id. Prepend Set_ to the set name. Ex: Set_Action.
    • size (number): The size of the set.
  • selected: The currently selected row. This value should not be populated manually, as the data is specific to UpSet 2.0 and automatically generated.

To export the grammar of an UpSet 2.0 plot programmatically, use the exportState function. This function has the following parameters:

  • provenance: The Trrack object for the provenance being used by the UpSet plot.
  • data (optional): The raw data used to generated the plot.
  • rows (optional): The processed row data generated by the UpSet data pipeline.

Example of full configuration (grammar) JSON produced for default Simpsons dataset:

{
  "plotInformation": {
    "description": "",
    "sets": "",
    "items": ""
  },
  "horizontal": false,
  "firstAggregateBy": "None",
  "firstOverlapDegree": 2,
  "secondAggregateBy": "None",
  "secondOverlapDegree": 2,
  "sortVisibleBy": "Alphabetical",
  "sortBy": "Size",
  "sortByOrder": "Descending",
  "filters": {
    "maxVisible": 6,
    "minVisible": 0,
    "hideEmpty": true,
    "hideNoSet": false
  },
  "visibleSets": [
    "Set_School",
    "Set_Blue Hair",
    "Set_Duff Fan",
    "Set_Evil",
    "Set_Male",
    "Set_Power Plant"
  ],
  "visibleAttributes": [
    "Age"
  ],
  "bookmarkedIntersections": [],
  "collapsed": [],
  "plots": {
    "scatterplots": [],
    "histograms": []
  },
  "allSets": [
    {
      "name": "Set_School",
      "size": 6
    },
    {
      "name": "Set_Blue Hair",
      "size": 3
    },
    {
      "name": "Set_Duff Fan",
      "size": 6
    },
    {
      "name": "Set_Evil",
      "size": 6
    },
    {
      "name": "Set_Male",
      "size": 18
    },
    {
      "name": "Set_Power Plant",
      "size": 5
    }
  ],
  "selected": null
}
Sidebar options

SidebarProps type:

interface SidebarProps {
  /**
   * Indicates whether the sidebar is open or closed.
   */
  open: boolean;

  /**
   * Callback function to close the sidebar.
   */
  close: () => void;
}
Alt Text Generation

Alt Text generation requires the use of a custom or imported Alt-Text generation function. In upset.multinet.app, we are using the Multinet API, which exposes an api call to the upset-alttxt python package.

Default Configuration

The default configuration for UpSet 2.0 shows the Aggregation/Filtering settings sidebar, sort the plot by Size (Descending), and shows up to the first 3 attributes in the data.

Example using Simpsons dataset:

<Upset data={simpsonsCharacterData} />

Default UpSet 2.0 plot configuration

Developer Docs

Developer documentation can be found at https://vdl.sci.utah.edu/upset2/.

For more information on documentation see the Developer Documentation Guidelines.

Local Installation

To deploy UpSet 2.0 locally it is necessary to install the Multinet infrastructure.

Multinet Installation

  1. Clone Multinet API, Multinet Client, and Multinet JS into individual folders.
  2. Follow the installation instructions for Multinet API and Multinet Client.

Upset Installation

  1. Clone the repository using git clone or download and extract the zip file.
  2. Open terminal in the cloned folder and run yarn install
  3. Run yarn build in the terminal to compile.
  4. Navigate to the upset2 folder.
  5. In packages/app copy .env.default and rename the copied file to .env
  6. In the OAUTH application created during the OAUTH API setup of Multinet API, add http://localhost:3000/ to the redirect uris field.
  7. Copy the Client id field in the application but do not modify the value
  8. Navigate to the .env file created in step 5.
  9. Paste the Client id to the field VITE_OAUTH_CLIENT_ID

Running the application

To run UpSet 2.0 locally, first, complete the Local Installation steps. Then, use yarn dev to run UpSet 2.0 on port 3000. A browser window for localhost:3000 will open during the launch process.

End To End (e2e) Testing

To run the playwright end to end tests, use the command: yarn test

To open the test in a UI view to track steps, append --ui.

This will launch a local server if there is not one already running on port 3000.

To add a test, add a .spec.ts file to e2e-tests. For information on how to use playwright, please see the playwright documentation.

Storybook development

Storybook can be used to test development of UpSet 2.0 as a react component. To run storybook, run cd packages/upset from the project root directory. Then, run yarn storybook. This will run Upset.stories.tsx, which opens a browser tab for the storybook. This will render the react component of UpSet with the simpsons dataset and stripped of any attribute or settings rendering.

A new story can be added by adding a {name}.stories.tsx file to packages/upset/stories/. New data can be added to the data subfolder in the same directory.

Developer Documentation Guidelines

When adding a new feature, ensure that your additions are well documented following JSDoc style annotations. Also, please add testing via Playwright, outlined in #end-to-end-e2e-testing.

To build the documentation locally, use the command: yarn doc. The default file output is at /docs.

About

UpSet - Visualizing Intersecting Sets

https://upset.multinet.app/

License:BSD 3-Clause "New" or "Revised" License


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