Module: `sarpyx.processor.core.signal`

File: sarpyx/processor/core/signal.py

Signal processing functions for Sentinel-1 Level-0 processing. This module provides signal processing functions including FFT operations, filtering, windowing, and other DSP utilities for SAR processing.

Exported Symbols (`all`)

No explicit __all__ list. Public symbols inferred from implementation.

Public Functions (23)

fft_1d function

Compute 1D FFT of input data.

File location: sarpyx/processor/core/signal.py:17

Signature

fft_1d(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`int`	no	`-1`	Axis along which to compute FFT

Return Type

np.ndarray

FFT of input data

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import fft_1d

result = fft_1d(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

ifft_1d function

Compute 1D inverse FFT of input data.

File location: sarpyx/processor/core/signal.py:31

Signature

ifft_1d(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`int`	no	`-1`	Axis along which to compute IFFT

Return Type

np.ndarray

IFFT of input data

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import ifft_1d

result = ifft_1d(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

fft_2d function

Compute 2D FFT of input data.

File location: sarpyx/processor/core/signal.py:45

Signature

fft_2d(data: np.ndarray) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input 2D data array

Return Type

np.ndarray

2D FFT of input data

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import fft_2d

result = fft_2d(data=<data>)

Edge Cases

No explicit edge-case section found; behavior is inferred from implementation.

ifft_2d function

Compute 2D inverse FFT of input data.

File location: sarpyx/processor/core/signal.py:58

Signature

ifft_2d(data: np.ndarray) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input 2D data array

Return Type

np.ndarray

2D IFFT of input data

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import ifft_2d

result = ifft_2d(data=<data>)

Edge Cases

No explicit edge-case section found; behavior is inferred from implementation.

zero_pad function

Zero-pad data to specified length.

File location: sarpyx/processor/core/signal.py:71

Signature

zero_pad(data: np.ndarray, new_length: int, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`new_length`	`int`	yes	`-`	Target length after padding
`axis`	`int`	no	`-1`	Axis along which to pad

Return Type

np.ndarray

Zero-padded data array

Exceptions

ValueError

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import zero_pad

result = zero_pad(data=<data>, new_length=<new_length>)

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

apply_window function

Apply window function to data.

File location: sarpyx/processor/core/signal.py:105

Signature

apply_window(data: np.ndarray, window_type: str='hamming', axis: int=-1, beta: float=8.6) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`window_type`	`str`	no	`'hamming'`	Type of window ('hamming', 'hanning', 'blackman', 'kaiser')
`axis`	`int`	no	`-1`	Axis along which to apply window
`beta`	`float`	no	`8.6`	Beta parameter for Kaiser window

Return Type

np.ndarray

Windowed data array

Exceptions

ValueError

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import apply_window

result = apply_window(data=<data>)

Edge Cases

May raise: ValueError. Includes optional parameters with implementation-defined fallback behavior.

bandpass_filter function

Apply bandpass filter to data.

File location: sarpyx/processor/core/signal.py:143

Signature

bandpass_filter(data: np.ndarray, low_freq: float, high_freq: float, sample_rate: float, order: int=5) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`low_freq`	`float`	yes	`-`	Low cutoff frequency (Hz)
`high_freq`	`float`	yes	`-`	High cutoff frequency (Hz)
`sample_rate`	`float`	yes	`-`	Sampling rate (Hz)
`order`	`int`	no	`5`	Filter order

Return Type

np.ndarray

Filtered data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import bandpass_filter

result = bandpass_filter(data=<data>, low_freq=<low_freq>, high_freq=<high_freq>, sample_rate=<sample_rate>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

lowpass_filter function

Apply lowpass filter to data.

File location: sarpyx/processor/core/signal.py:171

Signature

lowpass_filter(data: np.ndarray, cutoff_freq: float, sample_rate: float, order: int=5) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`cutoff_freq`	`float`	yes	`-`	Cutoff frequency (Hz)
`sample_rate`	`float`	yes	`-`	Sampling rate (Hz)
`order`	`int`	no	`5`	Filter order

Return Type

np.ndarray

Filtered data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import lowpass_filter

result = lowpass_filter(data=<data>, cutoff_freq=<cutoff_freq>, sample_rate=<sample_rate>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

highpass_filter function

Apply highpass filter to data.

File location: sarpyx/processor/core/signal.py:196

Signature

highpass_filter(data: np.ndarray, cutoff_freq: float, sample_rate: float, order: int=5) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`cutoff_freq`	`float`	yes	`-`	Cutoff frequency (Hz)
`sample_rate`	`float`	yes	`-`	Sampling rate (Hz)
`order`	`int`	no	`5`	Filter order

Return Type

np.ndarray

Filtered data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import highpass_filter

result = highpass_filter(data=<data>, cutoff_freq=<cutoff_freq>, sample_rate=<sample_rate>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

cross_correlate function

Compute cross-correlation between two signals.

File location: sarpyx/processor/core/signal.py:221

Signature

cross_correlate(signal1: np.ndarray, signal2: np.ndarray, mode: str='full') -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`signal1`	`np.ndarray`	yes	`-`	First input signal
`signal2`	`np.ndarray`	yes	`-`	Second input signal
`mode`	`str`	no	`'full'`	Correlation mode ('full', 'valid', 'same')

Return Type

np.ndarray

Cross-correlation result

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import cross_correlate

result = cross_correlate(signal1=<signal1>, signal2=<signal2>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

autocorrelate function

Compute autocorrelation of a signal.

File location: sarpyx/processor/core/signal.py:237

Signature

autocorrelate(signal_data: np.ndarray, max_lag: Optional[int]=None) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`signal_data`	`np.ndarray`	yes	`-`	Input signal
`max_lag`	`Optional[int]`	no	`None`	Maximum lag to compute (None for full)

Return Type

np.ndarray

Autocorrelation result

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import autocorrelate

result = autocorrelate(signal_data=<signal_data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

hilbert_transform function

Compute Hilbert transform of data.

File location: sarpyx/processor/core/signal.py:259

Signature

hilbert_transform(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`int`	no	`-1`	Axis along which to compute transform

Return Type

np.ndarray

Hilbert transform result

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import hilbert_transform

result = hilbert_transform(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

envelope_detection function

Detect envelope of signal using Hilbert transform.

File location: sarpyx/processor/core/signal.py:273

Signature

envelope_detection(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input signal data
`axis`	`int`	no	`-1`	Axis along which to compute envelope

Return Type

np.ndarray

Signal envelope

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import envelope_detection

result = envelope_detection(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

phase_unwrap function

Unwrap phase discontinuities.

File location: sarpyx/processor/core/signal.py:288

Signature

phase_unwrap(phase: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`phase`	`np.ndarray`	yes	`-`	Input phase array (radians)
`axis`	`int`	no	`-1`	Axis along which to unwrap

Return Type

np.ndarray

Unwrapped phase array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import phase_unwrap

result = phase_unwrap(phase=<phase>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

detrend_linear function

Remove linear trend from data.

File location: sarpyx/processor/core/signal.py:302

Signature

detrend_linear(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`int`	no	`-1`	Axis along which to detrend

Return Type

np.ndarray

Detrended data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import detrend_linear

result = detrend_linear(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

detrend_constant function

Remove constant (DC) component from data.

File location: sarpyx/processor/core/signal.py:316

Signature

detrend_constant(data: np.ndarray, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`int`	no	`-1`	Axis along which to detrend

Return Type

np.ndarray

Detrended data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import detrend_constant

result = detrend_constant(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

upsample function

Upsample data by integer factor using zero-padding in frequency domain.

File location: sarpyx/processor/core/signal.py:330

Signature

upsample(data: np.ndarray, factor: int, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`factor`	`int`	yes	`-`	Upsampling factor
`axis`	`int`	no	`-1`	Axis along which to upsample

Return Type

np.ndarray

Upsampled data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import upsample

result = upsample(data=<data>, factor=<factor>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

downsample function

Downsample data by integer factor.

File location: sarpyx/processor/core/signal.py:356

Signature

downsample(data: np.ndarray, factor: int, axis: int=-1, anti_alias: bool=True) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`factor`	`int`	yes	`-`	Downsampling factor
`axis`	`int`	no	`-1`	Axis along which to downsample
`anti_alias`	`bool`	no	`True`	Whether to apply anti-aliasing filter

Return Type

np.ndarray

Downsampled data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import downsample

result = downsample(data=<data>, factor=<factor>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

complex_to_magnitude_phase function

Convert complex data to magnitude and phase.

File location: sarpyx/processor/core/signal.py:388

Signature

complex_to_magnitude_phase(data: np.ndarray) -> Tuple[np.ndarray, np.ndarray]

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Complex input data

Return Type

Tuple[np.ndarray, np.ndarray]

Tuple of (magnitude, phase) arrays

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import complex_to_magnitude_phase

result = complex_to_magnitude_phase(data=<data>)

Edge Cases

No explicit edge-case section found; behavior is inferred from implementation.

magnitude_phase_to_complex function

Convert magnitude and phase to complex data.

File location: sarpyx/processor/core/signal.py:403

Signature

magnitude_phase_to_complex(magnitude: np.ndarray, phase: np.ndarray) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`magnitude`	`np.ndarray`	yes	`-`	Magnitude array
`phase`	`np.ndarray`	yes	`-`	Phase array (radians)

Return Type

np.ndarray

Complex data array

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import magnitude_phase_to_complex

result = magnitude_phase_to_complex(magnitude=<magnitude>, phase=<phase>)

Edge Cases

No explicit edge-case section found; behavior is inferred from implementation.

rms function

Compute root mean square of data.

File location: sarpyx/processor/core/signal.py:418

Signature

rms(data: np.ndarray, axis: Optional[int]=None) -> Union[float, np.ndarray]

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`axis`	`Optional[int]`	no	`None`	Axis along which to compute RMS (None for all)

Return Type

Union[float, np.ndarray]

RMS value(s)

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import rms

result = rms(data=<data>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior. Documented return may be None for some execution paths.

snr_estimate function

Estimate signal-to-noise ratio.

File location: sarpyx/processor/core/signal.py:432

Signature

snr_estimate(signal_data: np.ndarray, noise_data: np.ndarray) -> float

Parameters

Parameter	Type	Required	Default	Description
`signal_data`	`np.ndarray`	yes	`-`	Signal data array
`noise_data`	`np.ndarray`	yes	`-`	Noise data array

Return Type

float

SNR in dB

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import snr_estimate

result = snr_estimate(signal_data=<signal_data>, noise_data=<noise_data>)

Edge Cases

No explicit edge-case section found; behavior is inferred from implementation.

frequency_shift function

Apply frequency shift to data.

File location: sarpyx/processor/core/signal.py:453

Signature

frequency_shift(data: np.ndarray, shift_freq: float, sample_rate: float, axis: int=-1) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
`data`	`np.ndarray`	yes	`-`	Input data array
`shift_freq`	`float`	yes	`-`	Frequency shift in Hz
`sample_rate`	`float`	yes	`-`	Sampling rate in Hz
`axis`	`int`	no	`-1`	Axis along which to apply shift

Return Type

np.ndarray

Frequency-shifted data

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

inferred from implementation

Example Usage

from sarpyx.processor.core.signal import frequency_shift

result = frequency_shift(data=<data>, shift_freq=<shift_freq>, sample_rate=<sample_rate>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.

Public Classes (0)

No public classes detected.

Module: sarpyx.processor.core.signal

Exported Symbols (__all__)

Public Functions (23)

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Module: `sarpyx.processor.core.signal`

Exported Symbols (`all`)