`TimeExpAverage`#

class acoular.tprocess.TimeExpAverage

Bases: Filter

Compute an exponentially weighted moving average of the input signal.

This filter implements exponential averaging as defined in IEC 61672-1, which is commonly used for sound level measurements. The time weighting determines how quickly past values decay in significance.

See also

Filter: Base class for implementing IIR filters.

Notes

The Impulse ('I') weighting is not part of IEC 61672-1 but is included for additional flexibility.

weight

Time weighting constant, determining the exponential decay rate.

'F' (Fast) → 0.125
'S' (Slow) → 1.0
'I' (Impulse) → 0.035 (non-standard)

Default is 'F'.

sos: Filter coefficients in second-order section (SOS) format.

digest: A unique identifier for the filter, based on its properties. (read-only)

result(num)

Apply the IIR filter to the input signal and yields filtered data block-wise.

This method processes the signal provided by source, applying the defined filter coefficients (sos) using the scipy.signal.sosfilt() function. The filtering is performed in a streaming fashion, yielding blocks of filtered signal data.

Parameters:

numint: Number of samples per block.

Yields:

numpy.ndarray: An array containing the bandpass-filtered signal for the current block. Each block has the shape (num, num_channels), where num_channels is inherited from the source. The last block may contain fewer samples if the total number of samples is not a multiple of num.

source: The input data source. It must be an instance of a SamplesGenerator-derived class.

sample_freq: Sampling frequency of output signal, as given by source.

num_channels: Number of channels in output, as given by source.

num_samples: Number of samples in output, as given by source.

TimeExpAverage#

`TimeExpAverage`#