22 lines
1.2 KiB
Plaintext
22 lines
1.2 KiB
Plaintext
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component Transforms {
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goal {
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Provide NumPy radio-data transforms used by the ML backends: data augmentations and channel/hardware impairment models over IQ.
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Own the functions that manipulate a signal while preserving its container type.
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}
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interface {
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Augmentations (iq_augmentations): generate_awgn, time_reversal, spectral_inversion, channel_swap, amplitude_reversal, drop_samples, quantize_tape, quantize_parts, magnitude_rescale, cut_out, patch_shuffle.
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Impairments (iq_impairments): add_awgn_to_signal, time_shift, frequency_shift, phase_shift, iq_imbalance, resample.
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Every function accepts an array or a Recording and returns the same type, preserving metadata for a Recording.
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This layer is a standalone library surface; the RIA Hub controller does not import it directly.
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}
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}
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expand Transforms {
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constraints {
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Input must be a 2-D complex channels-by-samples array or a ValueError is raised; most transforms implement only the single-channel path and raise NotImplementedError for more channels.
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frequency_shift is relative to the sample rate and must be within -0.5 to 0.5; phase_shift must be within -pi to pi.
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AWGN is generated to match a target SNR in dB.
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}
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}
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