tf.signal.idct
| View source on GitHub |
Computes the 1D Inverse Discrete Cosine Transform (DCT) of input.
tf.signal.idct(
input, type=2, n=None, axis=-1, norm=None, name=None
)
Currently only Types I, II and III are supported. Type III is the inverse of Type II, and vice versa.
Note that you must re-normalize by 1/(2n) to obtain an inverse if norm is not 'ortho'. That is: signal == idct(dct(signal)) * 0.5 / signal.shape[-1]. When norm='ortho', we have: signal == idct(dct(signal, norm='ortho'), norm='ortho').
| Args | |
|---|---|
input | A [..., samples] float32 Tensor containing the signals to take the DCT of. |
type | The IDCT type to perform. Must be 1, 2 or 3. |
n | For future expansion. The length of the transform. Must be None. |
axis | For future expansion. The axis to compute the DCT along. Must be -1. |
norm | The normalization to apply. None for no normalization or 'ortho' for orthonormal normalization. |
name | An optional name for the operation. |
| Returns | |
|---|---|
A [..., samples] float32 Tensor containing the IDCT of input. |
| Raises | |
|---|---|
ValueError | If type is not 1, 2 or 3, n is not None,axisis not-1, ornormis notNoneor'ortho'`. |
Scipy Compatibility
Equivalent to scipy.fftpack.idct for Type-I, Type-II and Type-III DCT.
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/signal/idct