Metadata-Version: 2.4
Name: matmech
Version: 1.0.6
Summary: A library for analyzing data from universal test machines.
Author-email: Mitchell Blaha <mitchell@blahafamily.com>
License-Expression: MIT
Project-URL: Repository, https://github.com/WhiteRabbit2006/matmech
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: matplotlib
Provides-Extra: animation
Requires-Dist: imageio; extra == "animation"
Requires-Dist: imageio-ffmpeg; extra == "animation"
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Dynamic: license-file

# matmech

## Overview

The `matmech` Python library processes, analyzes, and visualizes mechanical testing data (e.g., from Instron devices using WaveMatrix or BlueHill software).

It automates the workflow from:
*   Raw CSV import
*   Standardized data cleanup
*   Phase-based analysis
*   Graph generation (static and animated)

## Supported Features

*   Axial Stress–Strain calculations (rectangular cross-sections)
*   Torsional Shear Stress–Strain calculations (rectangular cross-sections)
*   Multi-phase test segmentation by time
*   Plotting with autoscaling, linear fits, and animations

## Library Structure

```
matmech/
│
├── __init__.py             # Package initialization
├── common_utils.py         # General utility functions like data loading and splitting
├── axial_analysis.py       # Functions for calculating axial material properties
├── torsional_analysis.py   # Functions for calculating torsional material properties
├── plotting_tools.py       # Functions for generating static and animated plots
├── config_defaults.py      # Default configurations and registries for software profiles, data columns, and plot settings
└── workflow.py             # Orchestrates the entire data analysis process
```

## Installation

To install the `matmech` package, navigate to the root of the `matmech` repository and install it in editable mode within your development environment:

```bash
pip install -e .
```

This command installs the package in "editable" mode, meaning that changes to the source code in your `matmech` repository will immediately affect the installed package without needing to reinstall.

### Requirements

The core `matmech` library requires the following Python packages, which will be installed automatically:
*   `pandas`
*   `numpy`
*   `matplotlib`

**Optional Dependencies:**

*   **Animation Output (`.mp4`):** For generating animated plots, `ffmpeg` is required. This is a system dependency, not a Python package.
    *   On Ubuntu/Debian, install it using: `sudo apt install ffmpeg`
    *   On Windows, download it from the [FFmpeg website](https://ffmpeg.org/download.html) and add it to your system's PATH.
*   **Development/Testing:** For running tests, `pytest` is required. Install it with:
    ```bash
    pip install -e ".[dev]"
    ```

## How It Works

1.  Loads raw CSV data from `./data/` (relative to the calling script).
2.  Standardizes column names and units (based on selected software profile).
3.  Splits data into segments by time (based on test recipe).
4.  Applies phase-specific analysis functions (axial or torsional).
5.  Generates static and/or animated plots saved to `./graphs/`.

## Example Directory Layout

```
matmech/
│
├── data/
│   └── my_test_run.csv
│
├── matmech/
│   └── (library modules...)
│
└── main.py
```

## Full Example: `main.py`

The following example shows ALL available configuration options.

```python
import os
from matmech.workflow import run_analysis_workflow

if __name__ == "__main__":
    # Path configuration
    SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))

    user_config = {
        # --- Software Profile (choose 'wavematrix' or 'bluehill') ---
        "software_type": "bluehill",

        # --- Input CSV file name (inside ./data) ---
        "data_file_name": "my_test_run.csv",

        # --- Geometry (in millimeters) ---
        "geometry": {
            "axial_width_mm": 10.0,
            "axial_thickness_mm": 2.0,
            "gauge_length_mm": 25.0,
            "torsional_side1_mm": 10.0,
            "torsional_side2_mm": 5.0
        },

        # --- Optional inversion and taring settings ---
        "inversion_flags": {
            "force": False,
            "torque": False
        },
        "tare_options": {
            "position": True,
            "force": True
        },

        # --- Test Phases (with end times in seconds) ---
        "test_recipe": [
            {"name": "Axial Calibration", "end_time": 5.0, "type": "AXIAL"},
            {"name": "Torsion Loading", "end_time": 10.0, "type": "TORSIONAL"}
        ],

        # --- Plot definitions ---
        "plots": [
            # Static plot with fit
            {
                "title": "Axial Stress vs. Axial Strain ({phase_name})",
                "output_filename": "axial_stress_strain_{phase_name}",
                "phases": ["Axial Calibration"],
                "x_col": "axial_strain",
                "y_col": "axial_stress",
                "fit_line": True,
                "fit_bounds": (0.0, 0.002),
                "x_units": "auto",
                "y_units": "auto",
                "type": "static"
            },

            # Animated plot
            {
                "title": "Shear Stress vs. Shear Strain ({phase_name})",
                "output_filename": "shear_stress_strain_{phase_name}",
                "phases": ["Torsion Loading"],
                "x_col": "shear_strain",
                "y_col": "shear_stress",
                "type": "animated",
                "animation_options": {
                    "target_duration_s": 8,
                    "target_fps": 24,
                    "snap_x_to_zero": True,
                    "snap_y_to_zero": True
                }
            }
        ]
    }

    # Run the full workflow
    run_analysis_workflow(SCRIPT_DIR, user_config)
```

## Configuration Reference

| Key               | Type    | Description                                                 |
| :---------------- | :------ | :---------------------------------------------------------- |
| `software_type`   | `str`   | "wavematrix" or "bluehill"                                  |
| `data_file_name`  | `str`   | Name of the CSV file inside `./data/`                       |
| `geometry`        | `dict`  | Required dimensions for calculations (in millimeters)       |
| `inversion_flags` | `dict`  | Optional channel sign reversals (`force`, `torque`)         |
| `tare_options`    | `dict`  | Taring channels to zero at start (`position`, `force`)      |
| `test_recipe`     | `list`  | Phases with `"name"`, `"end_time"` (seconds), `"type"`      |
| `plots`           | `list`  | One or more plot configs, may include animation             |
| `fit_bounds`      | `tuple` | `(x_min, x_max)` bounds for linear fitting                  |
| `animation_options`| `dict`  | Parameters for animations (`fps`, `duration`, `snap_to_zero`)|

## Output Files

All output graphs and videos are written to:
`./graphs/`

Files include:
*   `*.png` (static plots)
*   `*.mp4` (animated plots)

## Logging

Progress and analysis info will appear as console logs, including steps such as:
*   File loading
*   Data standardization
*   Axial/Torsional calculations
*   Linear modulus fitting results
*   Plot saving

### Example Log Output

```
INFO: Using software profile: 'bluehill'
INFO: Loading data from: my_test_run.csv
INFO: Axial stress calculated.
INFO: Linear Fit Analysis — Modulus: 1.98 GPa
INFO: Static plot saved to: axial_stress_strain_Axial Calibration.png
INFO: Animation saved: shear_stress_strain_Torsion Loading.mp4
```

## Extending the Library

To register a new analysis type:

1.  Create a new module function:
    ```python
    def my_new_analysis(df, geometry):
        # ... implement analysis logic ...
        return df
    ```
2.  Add it to the registry in `matmech/workflow.py`:
    ```python
    ANALYSIS_REGISTRY["NEW_TYPE"] = my_new_analysis
    ```
3.  Reference it in your `test_recipe`:
    ```python
    {"name": "My New Phase", "end_time": 12.0, "type": "NEW_TYPE"}
    ```

## Notes

*   The data column naming conventions differ between software types. The file `matmech/config_defaults.py` defines these profiles for both WaveMatrix and BlueHill.
*   Axis units and autoscaling are handled automatically but can be overridden per plot.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

Copyright (c) 2025 Mitchell Blaha
