Skip to main content

bdi-viz library

Project description

bdi-viz

Tests Lint Documentation Status

Contents

:sparkle: 1. Introduction

BDIViz is a powerful, interactive tool designed as an extension to BDIKit to assist biomedical researchers and domain experts in performing schema matching tasks. Built to address the challenges of matching complex biomedical datasets, BDIViz leverages a visual approach to streamline the process and enhance both speed and accuracy.

Key features of BDIViz include:

  • Interactive Heatmap for exploring and comparing matching candidates.
  • Value Comparisons Panel for analyzing similarities between attributes.
  • Detailed Analysis Panel offering in-depth insights into attribute value distributions.
  • Filtering & Refinement Tools to customize and adjust matching candidates based on datatype and similarity scores.
  • Expert-in-the-Loop Workflow allowing users to iteratively accept, reject, or refine matches, keeping the expert in control of decision-making.

BDIViz is designed to be integrated with Python notebooks, providing a flexible and easy-to-use tool for domain-specific schema matching in biomedical research and beyond.

:package: 2. Installation

To use BDI-Viz, install it using pip:

pip install bdi-viz

:rocket: 3. Quick Start

BDI-Viz 1.0 is built leveraging Panel. The application is designed to provide a user-friendly interface on jupyter notebooks. Where users can explore the schema matching recommandations, interact with the result, and pass them to the next step of the data integration process.

import pandas as pd
from bdiviz import BDISchemaMatchingHeatMap

# Load the data
source_df = pd.read_csv('data/source.csv')
target_df = pd.read_csv('data/target.csv')

# Render the BDI-Viz Heatmap
heatmap_manager = BDISchemaMatchingHeatMap(
    source=source_df,
    target=target_df,
    top_k=20,
)
heatmap_manager.plot_heatmap()

The following interface will be displayed in the jupyter notebook: BDIViz Demo

:page_facing_up: 4. Documentation

4.1 Read the Docs

For more information, please refer to the documentation.

4.2 Demo Video

BDIViz Demo

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bdi-viz-0.1.4.tar.gz (69.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bdi_viz-0.1.4-py3-none-any.whl (69.3 kB view details)

Uploaded Python 3

File details

Details for the file bdi-viz-0.1.4.tar.gz.

File metadata

  • Download URL: bdi-viz-0.1.4.tar.gz
  • Upload date:
  • Size: 69.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.9.13

File hashes

Hashes for bdi-viz-0.1.4.tar.gz
Algorithm Hash digest
SHA256 8aef8c3eb0f4382559a06636a4fc4fb0066b01f90556f6b66cebbef67a711004
MD5 e6ced4b0eec2ad93cbb4a031eaf734e9
BLAKE2b-256 4e28efb338a56ada131120e920a7819e2e3c81694da0c4d4aaa9d7a58d7846ed

See more details on using hashes here.

File details

Details for the file bdi_viz-0.1.4-py3-none-any.whl.

File metadata

  • Download URL: bdi_viz-0.1.4-py3-none-any.whl
  • Upload date:
  • Size: 69.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.0.1 CPython/3.9.13

File hashes

Hashes for bdi_viz-0.1.4-py3-none-any.whl
Algorithm Hash digest
SHA256 207bbf564b71d90bed2a6de10a66797e248a87c2d5baf9bf994d24e7b7b78253
MD5 31f9f8842f241a62a8e7638cf5ccf721
BLAKE2b-256 942e98dada33deece14c4d64c09bf819158f9570dcabc294a2f6c01b25a215ed

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page