Troubleshooting

This guide addresses common issues you might encounter when using Pkynetics and provides solutions.

Installation Issues

ImportError: No module named pkynetics

  • Issue: After installation, Python cannot find the Pkynetics module.

  • Solution: Ensure Pkynetics is installed in the correct Python environment. Try reinstalling:

    pip install --upgrade --force-reinstall pkynetics

  • Tip: If using a virtual environment, make sure it’s activated before installing and using Pkynetics.

Data Import Problems

FileNotFoundError

  • Issue: The specified data file cannot be found.

  • Solution: Check the file path and ensure it’s correct. Use absolute paths if unsure about the working directory.

ValueError: Unsupported manufacturer

  • Issue: The manufacturer specified in tga_importer or dsc_importer is not recognized.

  • Solution: Use one of the supported manufacturers: ‘auto’, ‘TA’, ‘Mettler’, ‘Netzsch’, or ‘Setaram’.

  • Tip: Try using ‘auto’ for automatic detection if unsure about the manufacturer.

Analysis Errors

ValueError in Kinetic Analysis Methods

  • Issue: Errors like “invalid value encountered in log” during analysis.

  • Solution: Check your input data for zero or negative values. Preprocess your data to handle these cases:

    import numpy as np
data = np.clip(data, 1e-10, None)  # Replace zeros/negatives with a small positive value

RuntimeWarning: invalid value encountered in true_divide

  • Issue: Division by zero in calculations.

  • Solution: Ensure your temperature data is in Kelvin and conversion data is between 0 and 1. Preprocess your data:

    temperature_k = temperature_c + 273.15  # Convert to Kelvin if necessary
alpha = np.clip(alpha, 0.001, 0.999)  # Avoid exact 0 or 1 values

Visualization Problems

RuntimeError: PNG support not available

  • Issue: Unable to save plots as PNG files.

  • Solution: Ensure you have a backend that supports PNG. Install pillow:

    pip install pillow

Performance Issues

Slow Performance with Large Datasets

  • Issue: Analysis is taking too long with large datasets.

  • Solution: Consider downsampling your data or using more efficient data structures:

    # Downsample large datasets
from scipy import signal
downsampled_temp = signal.resample(temperature, len(temperature)//10)
downsampled_alpha = signal.resample(alpha, len(alpha)//10)

Reporting Issues

If you encounter a bug or issue not covered here:

  1. Check the Pkynetics GitHub Issues to see if it’s a known problem.

  2. If not, create a new issue with: - A minimal code example that reproduces the problem - The full error traceback - Your Pkynetics version (print(pkynetics.__version__)) - Your Python version (python --version)

For feature requests or general questions, consider starting a discussion in the GitHub Discussions section.