Diagnostics, analysis, and visualization for ML model development
Project description
Model Tools
Diagnostics, analysis, and visualization for ML model development.
Purpose
This package provides utilities used across model sub-projects:
- analysis — Chain-length analysis, metrics computation
- viz — Training curves, market plots (OHLCV, peaks, volume)
- io — Thin wrappers around homebrewlibra I/O
What is NOT here:
- Data preparation (sliding window, standardize, split) →
data-prep - Model-specific tensor loading →
model-core
Installation
# From model-tools directory
pip install -e .
# With tests
pip install -e ".[tests]"
# From GitHub
pip install git+https://github.com/Alex-Glebov/model-tools.git
Package Structure
model_tools/
├── analysis/ # Chain analysis, metrics
│ └── analyze_chains.py
├── viz/ # Visualization
│ ├── plot_metrics.py
│ └── market_plots.py
└── io/ # I/O wrappers (homebrewlibra)
Usage
import model_tools
print(model_tools.__version__) # 0.1.1
# Analysis
from model_tools.analysis import analyze_all_chains
min_len, max_len, mean_len, all_lengths = analyze_all_chains(data_path)
# Visualization
from model_tools.viz import plot_training_history
plot_training_history(config_path)
Tests
pytest tests/ -v
Version
0.1.1 — defined in pyproject.toml.
Author
Alex & Claude python@iitsp.com.au
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