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MDMP Quickstart

MDMP is the IINTS protocol for validating data quality before modeling or evaluation.

Use a Virtual Environment

Run all commands from an active .venv: python3 -m venv .venv && source .venv/bin/activate

What MDMP Produces

  • Contract validation results (pass/fail per rule)
  • Compliance score
  • Deterministic dataset + contract fingerprints
  • MDMP grade: draft, research_grade, or clinical_grade

1) Generate a Contract Template

iints mdmp template --output-path mdmp_contract.yaml

Edit the contract to match your dataset schema and bounds.

2) Validate a Dataset

iints mdmp validate mdmp_contract.yaml data/my_cgm.csv --output-json results/mdmp_report.json

Strict mode for pipelines:

iints data contract-run mdmp_contract.yaml data/my_cgm.csv \
  --min-mdmp-grade research_grade \
  --fail-on-noncompliant \
  --output-json results/contract_data_report.json

3) Generate an Audit Dashboard

iints mdmp visualizer results/mdmp_report.json --output-html results/mdmp_dashboard.html

This creates a single-file HTML report that can be shared offline.

4) Create Synthetic Mirror Data

iints mdmp synthetic-mirror data/my_cgm.csv mdmp_contract.yaml \
  --output-csv data/synthetic_mirror.csv \
  --output-json results/synthetic_mirror_report.json

Use this for safe development/testing when real data access is restricted.

Grade Interpretation

  • draft: schema partially valid, not ready for rigorous research workflows.
  • research_grade: acceptable quality for research experiments.
  • clinical_grade: strongest validation profile available in the SDK.

Python Gate (Optional)

import pandas as pd
from iints import mdmp_gate

@mdmp_gate("contracts/clinical_mdmp_contract.yaml", min_grade="research_grade")
def process(df: pd.DataFrame) -> int:
    return len(df)

This blocks or warns if input data does not meet required quality.

Important Scope

MDMP improves data quality and traceability. It does not provide clinical approval.