CSV Oscilloscope Output File Reading and Processing

Read CSV waveform files from a specified path and perform the following operations:

1. Integration: Compute the integral of the waveform to obtain its total area. This can be implemented using numerical integration methods like the trapezoidal rule (numpy.trapz() in Python) or cumulative summation for discrete data points.

2. Smoothing: Apply smoothing algorithms to eliminate noise and outliers from the waveform. Common implementations include moving average filters (using convolution operations), Savitzky-Golay filters (scipy.signal.savgol_filter), or low-pass digital filters to preserve signal trends while reducing high-frequency noise.

3. De-biasing: Shift the waveform baseline to zero value to remove DC offset. This is typically achieved by calculating the mean value of a baseline period and subtracting it from the entire waveform dataset using vectorized operations for efficiency.

These operations generate new waveform files saved in the original directory. After processing, you can better analyze waveform data and obtain more accurate results through proper signal conditioning techniques.