@inb/oeb-widgets
v1.1.0
Published
Collection of visualisers for benchmarking.
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OpenEBench Widgets
oeb-widgets is a collection of easy-to-use Vue components for benchmarking, initially designed for OpenEBench but also usable in other projects, making it a flexible tool. It includes two essential visualizers: a Bar Plot and a Scatter Plot, both capable of handling metrics and classifications. This package has been crafted with scalability in mind, allowing for seamless addition of more visualizers in future updates.
Features
- Bar Plot: Create bar charts to compare different categories.
- Scatter Plot: Generate scatter plots to visualize relationships between variables.
- Extensible Design: Built to support additional visualizers in future versions.
Installation
To install the package run:
npm i @inb/oeb_visualizations
How to Use
Import
import LoaderWidgets from '@inb/oeb-widgets/components/LoaderWidgets.vue';
Usage
<LoaderWidgets :data-chart="data"></LoaderWidgets>
Firstly, import the LoaderWidgets component, which receives and processes data and displays either a bar plot or a scatter plot based on the provided data.
Bar Plot
Bar plot shows the results of a benchmarking challenge that uses one single evaluation metric in the form of a Barplot. Challenge participants are shown in the X axis, while the value of their metric is shown in the Y axis.
Classification
The results of this plot format can be transformed into a tabular format by sorting the participants in descending/ascending order according to their metrics and applying a quartile classification over that linear set of values. This classification splits the participants into four different groups/clusters depending on their performance. Clusters are separated in the plot with vertical lines and shown in the right table together with a green color-scale, which is easier to interpret for both experts and non-expert users.
Example Data Structure in Bar Plot
{
"_id": "OEBD003000002S",
"dates": {
"creation": "2018-04-09T00:00:00Z",
"modification": "2020-04-05T14:00:00Z"
},
"dataset_contact_ids": ["Name.Lastname"],
"inline_data": {
"challenge_participants": [
{
"tool_id": "group01",
"metric_value": 0.932
},
{
"tool_id": "group02",
"metric_value": 0.9279
},
],
"visualization": {
"metric": "F-Measure",
"type": "bar-plot"
}
}
}
Scatter Plot
Scatter plot muestra los resultados de experimentos científicos de evaluación comparativa en formato de gráfico, y aplicar varios métodos de clasificación para transformarlos a formato tabular.
Classification methods
- Square quartiles - divide the plotting area in four squares by getting the 2nd quartile of the X and Y metrics.
- Diagonal quartiles - divide the plotting area with diagonal lines by assigning a score to each participant based in the distance to the 'optimal performance'.
- Clustering - group the participants using the K-means clustering algorithm and sort the clusters according to the performance.
Example Data Structure for Scatter Plot
{
"_id": "OEBD0080000U6A",
"dates": {
"creation": "2023-05-04T16:00:26Z",
"modification": "2023-11-05T13:09:13Z",
"public": null
},
"dataset_contact_ids": ["Name.Lastname", "Name.Lastname"],
"inline_data": {
"challenge_participants": [
{
"tool_id": "Domainoid+",
"metric_x": 220046,
"stderr_x": 0,
"metric_y": 0.91590127,
"stderr_y": 0.00081763741
},
{
"tool_id": "OMA_Groups",
"metric_x": 99657,
"stderr_x": 0,
"metric_y": 0.97144131,
"stderr_y": 0.00071919219
},
],
"visualization": {
"type": "2D-plot",
"x_axis": "NR_ORTHOLOGS",
"y_axis": "avg Schlicker",
"optimization": "top-right"
}
}
}
Box Plot
Box plot shiw the results of a benchmarking challenge that uses a graphical representation of the distribution of a dataset on a seven-number summary of datapoints. The challenge metrics is represented in Y axis by default.
Classification
The result of the plot can be ordened by maximum or minimum median value.
Example Data Structure in Box Plot
{
"_id": "OEBD003000002S",
"dates": {
"modification": "2024-04-05T14:00:00Z"
},
"dataset_contact_ids": ["Name.Lastname"],
"inline_data": {
"challenge_participants": [
{
"name": "rnaSPAdes 2",
"metric_id": "length of transcripts",
"q1": 4.028134794028789,
"mean": 4.6573958631434174,
"median": 4.574031267727719,
"q3": 4.92020145948564,
"lowerfence": 3.8400347958435121,
"upperfence": 5.408301457670917
},
],
"visualization": {
"type": "box-plot",
"y_axis": "length of transcripts",
"optimization": "minimum"
}
}
}