Getting Started

This guide will walk you through the basic steps to use PyRth for thermal transient analysis.

Installation

First, ensure you have PyRth installed. If not, follow the installation instructions.

pip install PyRth

Basic Analysis Workflow

A standard thermal transient analysis workflow includes these steps:

Prepare your data: Load thermal transient data from your measurement system.
Create an Evaluation instance: Instantiate the main PyRth analysis object.
Process with standard module: Run the thermal impedance calculation and deconvolution.
Save and visualize results: Export data as CSV files and generate plots.

Example

Here’s a minimal example to process thermal transient data:

import numpy as np
from PyRth import Evaluation

# Load your measurement data (time and voltage columns)
data = np.loadtxt("your_measurement.csv", delimiter=",")

# Load your calibration data (temperature and voltage)
calibration = np.array([
    [25.0, 0.55],
    [50.0, 0.50],
    [75.0, 0.45],
    [100.0, 0.40],
])

# Set up parameters
params = {
    "data": data,
    "output_dir": "results",
    "label": "my_first_analysis",
    "input_mode": "volt",
    "calib": calibration,
    "power_step": 1.0,  # power applied during measurement in Watts
    "deconv_mode": "bayesian",
    "lower_fit_limit": 1e-4,  # seconds
    "upper_fit_limit": 1e-3,  # seconds
}

# Run the analysis
evaluator = Evaluation()
result = evaluator.standard_module(params)

# Save results
evaluator.save_all()

# Access computed data
print(f"Total thermal resistance: {result.int_cau_res[-1]:.2f} K/W")