File corr2d_core.h¶

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2-D FFT-based cross-correlator with coherent integrate-and-dump. More...

• #include "clib_common.h"
• #include "dp_state.h"
• #include "fft2d/fft2d_core.h"

Classes¶

Public Functions¶

Macros¶

Detailed Description¶

Two-dimensional extension of corr_core: all buffers are ny×nx row-major flat arrays of length ny*nx. The correlation theorem extends naturally:

R_xh[i,j] = IFFT2( FFT2(x) · conj(FFT2(h)) ) / (ny*nx)

The reference spectrum is pre-computed at create time. The int-dump semantics are identical to the 1-D case: coherently sum dwell frames, then dump.

Lifecycle:

float complex ref[NY * NX] = { ... };    // row-major 2-D reference
corr2d_state_t *c = corr2d_create(ref, NY, NX, 4, 1);
float complex out[NY * NX];
for (int i = 0; i < 4; i++) {
    size_t n_out = corr2d_execute(c, frame[i], NY*NX, out);
    if (n_out) process_2d(out, NY, NX);   // fires once, on i == 3
}
corr2d_destroy(c);

Public Functions Documentation¶

function corr2d_create¶

Allocate a 2-D FFT correlator with coherent integrate-and-dump. Two-dimensional extension of corr_create() . The reference is a flat row-major ny×nx CF32 array; its conjugate spectrum is pre-computed once so each execute() call costs two 2-D FFTs plus ny*nx complex multiplies. The Python wrapper requiresref to be a 2-D ndarray with shape (ny, nx); it passes a flat view to C.

corr2d_state_t * corr2d_create (
    const float complex * ref,
    size_t ny,
    size_t nx,
    size_t dwell,
    int nthreads,
    size_t ny_out,
    size_t nx_out
) 

Parameters:

• ref Reference image, 2-D (ny, nx) CF32 ndarray in Python.
• ny Number of rows in the reference and input frames.
• nx Number of columns in the reference and input frames.
• dwell Integration depth; must be >= 1.
• nthreads Accepted for API compatibility; ignored.
• ny_out Inverse/output rows; 0 => native (ny). Must be >= ny. A larger output zero-pads the cross-spectrum before the inverse, returning the band-limited (Dirichlet) interpolation of the correlation on a finer (ny_out, nx_out) grid — same peak, sub-bin resolution. Native is bit-exact and allocates no extra buffers.
• nx_out Inverse/output columns; 0 => native (nx). Must be >= nx.

Returns:

Heap-allocated state, or NULL on failure.

>>> from doppler.spectral import Corr2D
>>> import numpy as np
>>> ref = np.zeros((4, 4), dtype=np.complex64); ref[0, 0] = 1.0
>>> c = Corr2D(ref=ref, dwell=1, nthreads=1)
>>> c.ny, c.nx, c.dwell, c.count
(4, 4, 1, 0)

function corr2d_destroy¶

Destroy and free a corr2d instance.

void corr2d_destroy (
    corr2d_state_t * state
) 

Parameters:

• state May be NULL.

function corr2d_execute¶

Correlate one 2-D frame and optionally dump the coherent accumulator. Runs the 2-D pipeline: FFT2 → pointwise multiply with ref_spec → accumulate the cross-spectrum; on dump, IFFT2 → normalise (÷ ny*nx). Accumulating in the frequency domain and inverting once is exactly the per-frame inverse summed, by linearity of the IFFT — valid because the dwell is coherent (a complex sum); a non-coherent (magnitude) integration could not defer the inverse. The Python wrapper accepts a (ny, nx) CF32 ndarray; a dump returns a flat length-ny*nx ndarray, a no-dump returns None.

size_t corr2d_execute (
    corr2d_state_t * state,
    const float complex * in,
    size_t n_in,
    float complex * out
) 

Parameters:

• state Allocated 2-D correlator (non-NULL).
• in Input frame, flat row-major CF32, length ny*nx.
• n_in Number of input samples; must equal ny*nx.
• out Output buffer for the correlation map (CF32, length ny*nx); written only on a dump call.

Returns:

ny*nx on a dump, 0 otherwise (None in Python).

>>> from doppler.spectral import Corr2D
>>> import numpy as np
>>> ref = np.zeros((2, 2), dtype=np.complex64); ref[0, 0] = 1.0
>>> c = Corr2D(ref=ref, dwell=2)
>>> x = np.ones((2, 2), dtype=np.complex64)
>>> c.execute(x) is None   # frame 1 — no dump
True
>>> c.execute(x).tolist()  # frame 2 — dump
[(2+0j), (2+0j), (2+0j), (2+0j)]

function corr2d_execute_max_out¶

Maximum output samples per execute call (always == ny*nx).

size_t corr2d_execute_max_out (
    corr2d_state_t * state
) 

function corr2d_get_state¶

void corr2d_get_state (
    const corr2d_state_t * state,
    void * blob
) 

function corr2d_reset¶

Zero the accumulator and reset the integration counter to 0. Equivalent to starting a fresh dwell cycle without rebuilding FFT plans or recomputing ref_spec.

void corr2d_reset (
    corr2d_state_t * state
) 

>>> from doppler.spectral import Corr2D
>>> import numpy as np
>>> ref = np.zeros((2, 2), dtype=np.complex64); ref[0, 0] = 1.0
>>> c = Corr2D(ref=ref, dwell=3)
>>> _ = c.execute(np.ones((2, 2), dtype=np.complex64))
>>> c.count
1
>>> c.reset()
>>> c.count
0

function corr2d_set_ref¶

Replace the reference and recompute conj(FFT2(ref)).

void corr2d_set_ref (
    corr2d_state_t * state,
    const float complex * ref
) 

Also resets accumulator and counter.

Parameters:

• state Must be non-NULL.
• ref New reference, flat row-major CF32, length ny*nx.

function corr2d_set_state¶

int corr2d_set_state (
    corr2d_state_t * state,
    const void * blob
) 

function corr2d_state_bytes¶

size_t corr2d_state_bytes (
    const corr2d_state_t * state
) 

Macro Definition Documentation¶

define CORR2D_STATE_MAGIC¶

#define CORR2D_STATE_MAGIC `DP_FOURCC ('C','R','2','D')`

define CORR2D_STATE_VERSION¶

#define CORR2D_STATE_VERSION `1u`

The documentation for this class was generated from the following file native/inc/corr2d/corr2d_core.h