Computes the inverse of `rfft2`. Parameters ---------- a : array_like The input array s : sequence of ints, optional Shape of the real output to the inverse FFT. axes : sequence of ints, optional The axes over which to compute the inverse fft.
(a, s=None, axes=(-2, -1), norm=None)
| 1369 | |
| 1370 | @array_function_dispatch(_fftn_dispatcher) |
| 1371 | def irfft2(a, s=None, axes=(-2, -1), norm=None): |
| 1372 | """ |
| 1373 | Computes the inverse of `rfft2`. |
| 1374 | |
| 1375 | Parameters |
| 1376 | ---------- |
| 1377 | a : array_like |
| 1378 | The input array |
| 1379 | s : sequence of ints, optional |
| 1380 | Shape of the real output to the inverse FFT. |
| 1381 | axes : sequence of ints, optional |
| 1382 | The axes over which to compute the inverse fft. |
| 1383 | Default is the last two axes. |
| 1384 | norm : {"backward", "ortho", "forward"}, optional |
| 1385 | .. versionadded:: 1.10.0 |
| 1386 | |
| 1387 | Normalization mode (see `numpy.fft`). Default is "backward". |
| 1388 | Indicates which direction of the forward/backward pair of transforms |
| 1389 | is scaled and with what normalization factor. |
| 1390 | |
| 1391 | .. versionadded:: 1.20.0 |
| 1392 | |
| 1393 | The "backward", "forward" values were added. |
| 1394 | |
| 1395 | Returns |
| 1396 | ------- |
| 1397 | out : ndarray |
| 1398 | The result of the inverse real 2-D FFT. |
| 1399 | |
| 1400 | See Also |
| 1401 | -------- |
| 1402 | rfft2 : The forward two-dimensional FFT of real input, |
| 1403 | of which `irfft2` is the inverse. |
| 1404 | rfft : The one-dimensional FFT for real input. |
| 1405 | irfft : The inverse of the one-dimensional FFT of real input. |
| 1406 | irfftn : Compute the inverse of the N-dimensional FFT of real input. |
| 1407 | |
| 1408 | Notes |
| 1409 | ----- |
| 1410 | This is really `irfftn` with different defaults. |
| 1411 | For more details see `irfftn`. |
| 1412 | |
| 1413 | Examples |
| 1414 | -------- |
| 1415 | >>> a = np.mgrid[:5, :5][0] |
| 1416 | >>> A = np.fft.rfft2(a) |
| 1417 | >>> np.fft.irfft2(A, s=a.shape) |
| 1418 | array([[0., 0., 0., 0., 0.], |
| 1419 | [1., 1., 1., 1., 1.], |
| 1420 | [2., 2., 2., 2., 2.], |
| 1421 | [3., 3., 3., 3., 3.], |
| 1422 | [4., 4., 4., 4., 4.]]) |
| 1423 | """ |
| 1424 | return irfftn(a, s, axes, norm) |