Module: sarpyx.processor.core.spectrum

Perform memory-efficient 2D inverse FFT on radar data.

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

Signature

ifft2d(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after 2D inverse FFT.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import ifft2d

result = ifft2d(radar_data=<radar_data>)

Edge Cases

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

Perform memory-efficient inverse FFT along azimuth dimension.

File location: sarpyx/processor/core/spectrum.py:65

Signature

ifft_azimuth(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after inverse FFT along azimuth dimension.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import ifft_azimuth

result = ifft_azimuth(radar_data=<radar_data>)

Edge Cases

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

Perform memory-efficient inverse FFT along range dimension.

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

Signature

ifft_range(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after inverse FFT along range dimension.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import ifft_range

result = ifft_range(radar_data=<radar_data>)

Edge Cases

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

Perform memory-efficient FFT along range dimension.

File location: sarpyx/processor/core/spectrum.py:148

Signature

fft_range(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after FFT along range dimension.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import fft_range

result = fft_range(radar_data=<radar_data>)

Edge Cases

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

Perform memory-efficient FFT along azimuth dimension.

File location: sarpyx/processor/core/spectrum.py:189

Signature

fft_azimuth(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after FFT along azimuth dimension.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import fft_azimuth

result = fft_azimuth(radar_data=<radar_data>)

Edge Cases

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

Perform memory-efficient 2D FFT on radar data in range and azimuth dimensions.

File location: sarpyx/processor/core/spectrum.py:230

Signature

fft2d(radar_data: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False, n: Optional[int]=None) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
radar_data	Union[np.ndarray, torch.Tensor]	yes	-	Input radar data array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.
n	Optional[int]	no	None	Number of points for the transform. If None, uses input size.

Return Type

Union[np.ndarray, torch.Tensor]

Processed radar data after 2D FFT.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import fft2d

result = fft2d(radar_data=<radar_data>)

Edge Cases

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

Perform 2D linear convolution of two signals using FFT with proper padding.

File location: sarpyx/processor/core/spectrum.py:394

Signature

linear_convolution_2d(signal1: Union[np.ndarray, torch.Tensor], signal2: Union[np.ndarray, torch.Tensor], backend: str='numpy', verbose: bool=False) -> Union[np.ndarray, torch.Tensor]

Parameters

Parameter	Type	Required	Default	Description
signal1	Union[np.ndarray, torch.Tensor]	yes	-	First input signal array.
signal2	Union[np.ndarray, torch.Tensor]	yes	-	Second input signal (kernel) array.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.

Return Type

Union[np.ndarray, torch.Tensor]

Result of linear convolution with size (M+N-1, P+Q-1) where signal1 is MxP and signal2 is NxQ.

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import linear_convolution_2d

result = linear_convolution_2d(signal1=<signal1>, signal2=<signal2>)

Edge Cases

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

Perform cross-correlation between radar data and nominal chip.

File location: sarpyx/processor/core/spectrum.py:631

Signature

correlation(x1: np.ndarray, nomchip: np.ndarray, backend: str='numpy', verbose: bool=False) -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
x1	np.ndarray	yes	-	Input radar data array of shape (azimuth, range).
nomchip	np.ndarray	yes	-	Nominal chip array for correlation.
backend	str	no	'numpy'	Backend to use ('numpy', 'torch', or 'scipy').
verbose	bool	no	False	Whether to print verbose output.

Return Type

np.ndarray

Cross-correlation result with shape (range, azimuth).

Exceptions

• ValueError

Side Effects

• io

Example Usage

from sarpyx.processor.core.spectrum import correlation

result = correlation(x1=<x1>, nomchip=<nomchip>)

Edge Cases

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

Perform linear convolution of two signals using scipy with enhanced control.

File location: sarpyx/processor/core/spectrum.py:837

Signature

linear_convolution(x: Union[np.ndarray, list], h: Union[np.ndarray, list], mode: str='same', axis: Optional[int]=None, zero_pad_length: Optional[int]=None, method: str='fft') -> np.ndarray

Parameters

Parameter	Type	Required	Default	Description
x	Union[np.ndarray, list]	yes	-	Input signal or 2D array.
h	Union[np.ndarray, list]	yes	-	Filter/impulse response (1D signal).
mode	str	no	'same'	Convolution mode ('full', 'valid', 'same').
axis	Optional[int]	no	None	Axis along which to perform convolution for 2D arrays.
zero_pad_length	Optional[int]	no	None	Additional zero-padding length to prevent circular convolution artifacts.
method	str	no	'fft'	Convolution method ('fft' for FFT-based, 'direct' for direct convolution).

Return Type

np.ndarray

Convolved signal with proper phase preservation.

Exceptions

None explicitly documented; inferred from implementation.

Side Effects

• inferred from implementation

Example Usage

from sarpyx.processor.core.spectrum import linear_convolution

result = linear_convolution(x=<x>, h=<h>)

Edge Cases

Includes optional parameters with implementation-defined fallback behavior.