How fraunhoferportugal/pymdma works
pyMDMA is a Python library for auditing input and synthetic datasets across image, tabular, and time-series modalities. Users invoke evaluation through the CLI or API, or import modality metrics directly; the shared runtime selects metrics and modality-specific input handling, computes results, and formats outputs. The modality branches provide their own loaders, feature extraction, and input/synthesis metrics. The README establishes the product capabilities; several subsystem details are represented at directory level because their implementations were not sampled.
Main entry points: selection.py Metric Selector · run_api.py REST API · compute.py Computation Manager · cli.py CLI
Components 21
Evaluation Runtime
- Metric Selector
src/pymdma/common/selection.py - Computation Manager
src/pymdma/common/compute.py - Metric Contracts
src/pymdma/common/definitions.py - Result Formatting
src/pymdma/common/output.py - Shared Metrics
src/pymdma/general/measures
Image Auditing
- Image Input
src/pymdma/image/input_layer.py - Image Features
src/pymdma/image/models/features.py - Image Metrics
src/pymdma/image/measures - Image Processing
src/pymdma/image/utils/processing.py
Tabular Auditing
- Tabular Input
src/pymdma/tabular/input_layer.py - Tabular Loading
src/pymdma/tabular/data/load.py - Data Harmonization
src/pymdma/tabular/data/harmonize.py - Tabular Embeddings
src/pymdma/tabular/embeddings/embed.py - Tabular Metrics
src/pymdma/tabular/measures
Time-Series Auditing
- Time-Series Input
src/pymdma/time_series/input_layer.py - Time-Series Dataset
src/pymdma/time_series/data/simple_dataset.py - Time-Series Features
src/pymdma/time_series/models/features.py - Time-Series Metrics
src/pymdma/time_series/measures
Other components
- User
Connections 22
- User → CLI: runs evaluation
- User → REST API: requests evaluation
- CLI → Metric Selector: selects metrics
src/pymdma/cli.py - CLI → Computation Manager: runs computation
src/pymdma/cli.py - REST API → Metric Selector: selects metrics
src/pymdma/api/run_api.py - REST API → Computation Manager: runs computation
src/pymdma/api/run_api.py - REST API → Result Formatting: formats response
src/pymdma/api/run_api.py - Metric Selector → Image Input: creates input
src/pymdma/common/selection.py - Metric Selector → Tabular Input: creates input
src/pymdma/common/selection.py - Metric Selector → Time-Series Input: creates input
src/pymdma/common/selection.py - Metric Selector → Image Metrics: loads metrics
src/pymdma/common/selection.py - Computation Manager → Metric Contracts: uses metric interface
src/pymdma/common/compute.py - Computation Manager → Result Formatting: produces results
src/pymdma/common/compute.py - Image Input → Image Features: extracts features
src/pymdma/image/input_layer.py - Image Input → Image Processing: uses processing
src/pymdma/image/input_layer.py - Tabular Input → Tabular Loading: loads data
src/pymdma/tabular/input_layer.py - Tabular Loading → Data Harmonization: harmonizes data
src/pymdma/tabular/data/load.py - Tabular Loading → Tabular Embeddings: encodes data
src/pymdma/tabular/data/load.py - Time-Series Input → Time-Series Dataset: builds datasets
src/pymdma/time_series/input_layer.py - Time-Series Input → Time-Series Features: uses features
src/pymdma/time_series/input_layer.py - User → Image Metrics: imports metrics
- Image Features → Image Metrics: feeds features