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# tf.signal.dct

Computes the 1D Discrete Cosine Transform (DCT) of `input`.

Currently only Types I, II and III are supported. Type I is implemented using a length `2N` padded `tf.signal.rfft`. Type II is implemented using a length `2N` padded `tf.signal.rfft`, as described here: Type 2 DCT using 2N FFT padded (Makhoul). Type III is a fairly straightforward inverse of Type II (i.e. using a length `2N` padded `tf.signal.irfft`).

`input` A `[..., samples]` `float32` `Tensor` containing the signals to take the DCT of.
`type` The DCT type to perform. Must be 1, 2 or 3.
`n` The length of the transform. If length is less than sequence length, only the first n elements of the sequence are considered for the DCT. If n is greater than the sequence length, zeros are padded and then the DCT is computed as usual.
`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.

A `[..., samples]` `float32` `Tensor` containing the DCT of `input`.

`ValueError` If `type` is not `1`, `2` or `3`, `axis` is not `-1`, `n` is not `None` or greater than 0, or `norm` is not `None` or `'ortho'`.
`ValueError` If `type` is `1` and `norm` is `ortho`.

#### Scipy Compatibility

Equivalent to scipy.fftpack.dct for Type-I, Type-II and Type-III DCT.

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