Returns the discrete, linear convolution of two one-dimensional sequences. Parameters ---------- a, v : array_like Input sequences. mode : {'valid', 'same', 'full'}, optional Refer to the `np.convolve` docstring. propagate_mask : bool If True, then i
(a, v, mode='full', propagate_mask=True)
| 8008 | |
| 8009 | |
| 8010 | def convolve(a, v, mode='full', propagate_mask=True): |
| 8011 | """ |
| 8012 | Returns the discrete, linear convolution of two one-dimensional sequences. |
| 8013 | |
| 8014 | Parameters |
| 8015 | ---------- |
| 8016 | a, v : array_like |
| 8017 | Input sequences. |
| 8018 | mode : {'valid', 'same', 'full'}, optional |
| 8019 | Refer to the `np.convolve` docstring. |
| 8020 | propagate_mask : bool |
| 8021 | If True, then if any masked element is included in the sum for a result |
| 8022 | element, then the result is masked. |
| 8023 | If False, then the result element is only masked if no non-masked cells |
| 8024 | contribute towards it |
| 8025 | |
| 8026 | Returns |
| 8027 | ------- |
| 8028 | out : MaskedArray |
| 8029 | Discrete, linear convolution of `a` and `v`. |
| 8030 | |
| 8031 | See Also |
| 8032 | -------- |
| 8033 | numpy.convolve : Equivalent function in the top-level NumPy module. |
| 8034 | """ |
| 8035 | return _convolve_or_correlate(np.convolve, a, v, mode, propagate_mask) |
| 8036 | |
| 8037 | |
| 8038 | def allequal(a, b, fill_value=True): |
nothing calls this directly
no test coverage detected