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# Fast Fourier Transform API

## FFT API quick reference

Table 78 FFT functions - quick reference
Brief | Forward Function | Inverse Function
--- | --- | ---
BFP FFT on single real signal | `bfp_fft_forward_mono()` | `bfp_fft_inverse_mono()`
BFP FFT on single complex signal | `bfp_fft_forward_complex()` | `bfp_fft_inverse_complex()`
BFP FFT on pair of real signals | `bfp_fft_forward_stereo()` | `bfp_fft_inverse_stereo()`
BFP spectrum packing | `bfp_fft_unpack_mono()` | `bfp_fft_pack_mono()`
Low-level decimation-in-time FFT | `fft_dit_forward()` | `fft_dit_inverse()`
Low-level decimation-in-frequency FFT | `fft_dif_forward()` | `fft_dif_inverse()`
FFT on real signal of `float` | `fft_f32_forward()` | `fft_f32_inverse()`

group fft_api

  Functions

  bfp_complex_s32_t *bfp_fft_forward_mono(bfp_s32_t *x)

    Performs a forward real Discrete Fourier Transform on a real 32-bit sequence.

    Performs an \(N\)-point forward real DFT on the real 32-bit BFP vector `x`, where \(N\) is `x->length`. The operation is performed in-place, resulting in an \(N/2\)-element complex 32-bit BFP vector.

    Operation Performed

      \[\begin{split}\begin{aligned} & X[f] = \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ & \text{ for } 0 \le f \le N/2 \end{aligned}\end{split}\]

    where \(x[n]\) is the BFP vector initially represented by `x`, and \(X[f]\) is the DFT of \(x[n]\) represented by the returned pointer.

    The exponent, headroom, length and data contents of `x` are all updated by this function, though `x->data` will continue to point to the same address.

    `x->length` must be a power of 2, and must be no larger than `(1<<MAX_DIT_FFT_LOG2)`.

    This function returns a `bfp_complex_s32_t` pointer. This points to the same address as . This is intended as a convenience for user code.

    Upon completion, the spectrum data is encoded in `x->data` as specified for real DFTs in spectrum_packing. That is, `x->data[f]` for `1 <= f < (x->length)` represent \(X[f]\) for \(1 \le f < (N/2)\) and `x->data[0]` represents \(X[0] + j X[N/2]\).

    Example

          // Initialize time domain data with samples.
          int32_t buffer[N] = { ... };
          bfp_s32_t samples;
          bfp_s32_init(&samples, buffer, 0, N, 1);
          // Perform the forward DFT
          {
              bfp_complex_s32_t* spectrum = bfp_fft_forward_mono(&samples);
              // `samples` should no longer be used.
              // Operate on frequency domain data using `spectrum`
              ...
              // Perform the inverse DFT to go back to time domain
              bfp_fft_inverse_mono(spectrum); // returns (bfp_s32_t*) which is the address of `samples`
          }
          // Use `samples` again to use new time domain data.
          ...

    Parameters:

      - x – [inout] The BFP vector \(x[n]\) to be DFTed.

    Returns:

      Address of input BFP vector `x`, cast as `bfp_complex_s32_t*`.

  bfp_s32_t *bfp_fft_inverse_mono(bfp_complex_s32_t *x)

    Performs an inverse real Discrete Fourier Transform on a complex 32-bit sequence.

    Performs an \(N\)-point inverse real DFT on the real 32-bit BFP vector `x`, where \(N\) is `2*x->length`. The operation is performed in-place, resulting in an \(N\)-element real 32-bit BFP vector.

    Operation Performed

      \[\begin{split}\begin{aligned} & x[n] = \frac{1}{N}\sum_{f=0}^{N/2} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ & \text{ for } 0 \le n < N \end{aligned}\end{split}\]

    where \(X[f]\) is the BFP vector initially represented by `x`, and \(x[n]\) is the IDFT of \(X[f]\) represented by the returned pointer.

    The exponent, headroom, length and data contents of `x` are all updated by this function, though `x->data` will continue to point to the same address.

    `x->length` must be a power of 2, and must be no larger than `(1<<(MAX_DIT_FFT_LOG2-1))`.

    This function returns a `bfp_s32_t` pointer. This points to the same address as . This is intended as a convenience for user code.

    When calling, the spectrum data must be encoded in `x->data` as specified for real DFTs in spectrum_packing. That is, `x->data[f]` for `1 <= f < (x->length)` represent \(X[f]\) for \(1 \le f < N/2\), and `x->data[0]` represents \(X[0] + j X[N/2]\).

    Example

          // Initialize time domain data with samples.
          int32_t buffer[N] = { ... };
          bfp_s32_t samples;
          bfp_s32_init(&samples, buffer, 0, N, 1);
          // Perform the forward DFT
          {
              bfp_complex_s32_t* spectrum = bfp_fft_forward_mono(&samples);
              // `samples` should no longer be used.
              // Operate on frequency domain data using `spectrum`
              ...
              // Perform the inverse DFT to go back to time domain
              bfp_fft_inverse_mono(spectrum); // returns (bfp_s32_t*) which is the address of `samples`
          }
          // Use `samples` again to use new time domain data.
          ...

    Parameters:

      - x – [inout] The BFP vector \(X[f]\) to be IDFTed.

    Returns:

      Address of input BFP vector `x`, cast as `bfp_s32_t*`.

  void bfp_fft_forward_complex(bfp_complex_s32_t *x)

    Performs a forward complex Discrete Fourier Transform on a complex 32-bit sequence.

    Performs an \(N\)-point forward complex DFT on the complex 32-bit BFP vector `x`, where \(N\) is `x->length`. The operation is performed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & X[f] = \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ & \text{ for } 0 \le f < N \end{aligned}\end{split}\]

    where \(x[n]\) is the BFP vector initially represented by `x`, and \(X[f]\) is the DFT of \(x[n]\), also represented by `x` upon completion.

    The exponent, headroom and data contents of `x` are updated by this function. `x->data` will continue to point to the same address.

    `x->length` ( \(N\)) must be a power of 2, and must be no larger than `(1<<MAX_DIT_FFT_LOG2)`.

    Upon completion, the spectrum data is encoded in `x` as specified in spectrum_packing. That is, `x->data[f]` for `0 <= f < (x->length)` represent \(X[f]\) for \(0 \le f < N\).

    Example

          // Initialize complex time domain data with samples.
          complex_s32_t buffer[N] = { ... };
          bfp_complex_s32_t vector;
          bfp_complex_s32_init(&vector, buffer, 0, N, 1);
          // Perform the forward DFT
          bfp_fft_forward_mono(&vector);
          // Operate on frequency domain data
          ...
          // Perform the inverse DFT to go back to time domain
          bfp_fft_inverse_mono(&vector);
          // `vector` contains (complex) time-domain data again
          ...

    Parameters:

      - x – [inout] The BFP vector \(x[n]\) to be DFTed.

  void bfp_fft_inverse_complex(bfp_complex_s32_t *x)

    Performs an inverse complex Discrete Fourier Transform on a complex 32-bit sequence.

    Performs an \(N\)-point inverse complex DFT on the complex 32-bit BFP vector `x`, where \(N\) is `x->length`. The operation is performed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & x[n] = \frac{1}{N}\sum_{f=0}^{N-1} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ & \text{ for } 0 \le f < N \end{aligned}\end{split}\]

    where \(X[f]\) is the BFP vector initially represented by `x`, and \(x[n]\) is the DFT of \(X[f]\), also represented by `x` upon completion.

    The exponent, headroom and data contents of `x` are updated by this function. `x->data` will continue to point to the same address.

    `x->length` must be a power of 2, and must be no larger than `(1<<MAX_DIT_FFT_LOG2)`.

    The data initially encoded in `x` are interpreted as specified in spectrum_packing. That is, `x->data[f]` for `0 <= f < (x->length)` represent \(X[f]\) for \(0 \le f < N\).

    Example

          // Initialize complex time domain data with samples.
          complex_s32_t buffer[N] = { ... };
          bfp_complex_s32_t vector;
          bfp_complex_s32_init(&vector, buffer, 0, N, 1);
          // Perform the forward DFT
          bfp_fft_forward_mono(&vector);
          // Operate on frequency domain data
          ...
          // Perform the inverse DFT to go back to time domain
          bfp_fft_inverse_mono(&vector);
          // `vector` contains (complex) time-domain data again
          ...

    Parameters:

      - x – [inout] The BFP vector \(x[n]\) to be IDFTed.

  void bfp_fft_forward_stereo(bfp_s32_t *a, bfp_s32_t *b, complex_s32_t scratch[])

    Performs a forward real Discrete Fourier Transform on a pair of real 32-bit sequences.

    Performs an \(N\)-point forward real DFT on the real 32-bit BFP vectors \(\bar a\) and \(\bar b\), where \(N\) is `a->length` (which must equal `b->length`). The resulting spectra, \(\bar A\) and \(\bar B\), are placed in `a` and `b`. Each spectrum is a \(N/2\)-element complex 32-bit BFP vectors. To access the spectrum, the pointers `a` and `b` should be cast to `bfp_complex_s32_t*` following a call to this function.

    Operation Performed

      \[\begin{split}\begin{aligned} & A[f] = \sum_{n=0}^{N-1} \left( a[n]\cdot e^{-j2\pi fn/N} \right) \text{ for } 0 \le f \le N/2 \\ & B[f] = \sum_{n=0}^{N-1} \left( b[n]\cdot e^{-j2\pi fn/N} \right) \text{ for } 0 \le f \le N/2 \end{aligned}\end{split}\]

    where \(a[n]\) and \(b[n]\) are the two time-domain sequences represented by input BFP vectors `a` and `b`, and \(A[f]\) and \(B[f]\) are the DFT of \(a[n]\) and \(b[n]\) respectively.

    `a->length` ( \(N\)) must be equal to `b->length, must be a power of 2, and must be no larger than`(1<<MAX_DIT_FFT_LOG2)`.

    The parameters and are used as both inputs and outputs. To access the result of the FFT, `a` and `b` should be cast to `bfp_complex_s32_t`*. The structs’ metadata (e.g. `exp`, `hr`, `length`) are updated by this function to reflect this change of interpretation. The `bfp_s32_t` references should be considered corrupted after this call (at least until bfp_fft_inverse_stereo() is called).

    The spectrum data is encoded in `a->data` and `b->data` as specified for real DFTs in spectrum_packing. That is, `a->data[f]` for `1 <= f < (a->length)` represent \(A[f]\) for \(1 \le f < (N/2)\) and `a->data[0]` represents \(A[0] + j A[N/2]\). Likewise for the encoding of `b->data`.

    This function requires a scratch buffer large enough to contain \(N\) `complex_s32_t` elements.

    Deprecated:
    Example

          // Initialize time domain data with samples.
          int32_t bufferA[N] = { ... };
          int32_t bufferB[N] = { ... };
          complex_s32_t scratch[N]; // scratch buffer -- contents don't matter
          bfp_s32_t channel_A, channel_B;
          bfp_s32_init(&channel_A, buffer, 0, N, 1);
          bfp_s32_init(&channel_B, buffer, 0, N, 1);

          // Perform the forward DFT
          bfp_fft_forward_stereo(&channel_A, &channel_B, scratch);

          // channel_A and channel_B should now be considered clobbered as the structs are now
          // effectively bfp_complex_s32_t
          bfp_complex_s32_t* chanA = (bfp_complex_s32_t*) &channel_A;
          bfp_complex_s32_t* chanB = (bfp_complex_s32_t*) &channel_B;

          // Operate on frequency domain data using `chanA` and `chanB`
          ...
          // Perform the inverse DFT to go back to time domain
          bfp_fft_inverse_stereo(&chanA, &chanB, scratch);

          // Use channel_A and channel_B again to use new time domain data.
          ...

    // Suppress this from generated documentation for the time being //

    Note

    Use of this function is not currently recommended. It functions correctly, but a recent change in this library’s API (namely, dropping support for channel-pair vectors) means this function is no more computationally efficient than calling `bfp_fft_forward_mono()` on each input vector separately. Additionally, this function currently requires a scratch buffer, whereas the mono FFT does not.

    Parameters:

      - a – [inout] [Input] Time-domain BFP vector \(\bar a\). [Output] Frequency domain BFP vector \(\bar A\)

      - b – [inout] [Input] Time-domain BFP vector \(\bar b\). [Output] Frequency domain BFP vector \(\bar B\)

      - scratch – Scratch buffer of at least `a->length` `complex_s32_t` elements

  void bfp_fft_inverse_stereo(bfp_complex_s32_t *A_fft, bfp_complex_s32_t *B_fft, complex_s32_t scratch[])

    Performs an inverse real Discrete Fourier Transform on a pair of complex 32-bit sequences.

    Performs an \(N\)-point inverse real DFT on the 32-bit complex BFP vectors \(\bar A\) and \(\bar B\) (`A_fft` and `B_fft` respectively), where \(N\) is `A_fft->length` . The resulting real signals, \(\bar a\) and \(\bar b\), are placed in `A_fft` and `B_fft`. Each time-domain result is a \(N/2\)-element real 32-bit BFP vectors. To access the spectrum, the pointers `A_fft` and `B_fft` should be cast to `bfp_s32_t*` following a call to this function.

    Operation Performed

      \[\begin{split}\begin{aligned} & a[n] = \frac{1}{N}\sum_{f=0}^{N/2-1} \left( A[f]\cdot e^{j2\pi fn/N} \right) \text{ for } 0 \le n < N \\ & b[n] = \frac{1}{N}\sum_{f=0}^{N/2-1} \left( B[f]\cdot e^{j2\pi fn/N} \right) \text{ for } 0 \le n < N \end{aligned}\end{split}\]

    where \(A[f]\) and \(B[f]\) are the frequency spectra represented by BFP vectors `A_fft` and `B_fft`, and \(a[n]\) and \(b[n]\) are the IDFT of \(A[f]\) and \(B[f]\).

    `A_fft->length` ( \(N\)) must be a power of 2, and must be no larger than `(1<<(MAX_DIT_FFT_LOG2-1))`.

    The parameters and are used as both inputs and outputs. To access the result of the IFFT, `A_fft` and `B_fft` should be cast to `bfp_s32_t`*. The structs’ metadata (e.g. `exp`, `hr`, `length`) are updated by this function to reflect this change of interpretation. The `bfp_complex_s32_t` references should be considered corrupted after this call.

    The spectrum data encoded in `A_fft->data` and `A_fft->data` are interpreted as specified for real DFTs in spectrum_packing. That is, `A_fft->data[f]` for `1 <= f < (a->length)` represent \(A[f]\) for \(1 \le f < (N/2)\) and `A_fft->data[0]` represents \(A[0] + j A[N/2]\). Likewise for the encoding of `B_fft->data`.

    This function requires a scratch buffer large enough to contain \(2N\) `complex_s32_t` elements.

    Deprecated:
    Example

          // Initialize time domain data with samples.
          int32_t bufferA[N] = { ... };
          int32_t bufferB[N] = { ... };
          complex_s32_t scratch[N]; // scratch buffer -- contents don't matter
          bfp_s32_t channel_A, channel_B;
          bfp_s32_init(&channel_A, buffer, 0, N, 1);
          bfp_s32_init(&channel_B, buffer, 0, N, 1);

          // Perform the forward DFT
          bfp_fft_forward_stereo(&channel_A, &channel_B, scratch);

          // channel_A and channel_B should now be considered clobbered as the structs are now
          // effectively bfp_complex_s32_t
          bfp_complex_s32_t* chanA = (bfp_complex_s32_t*) &channel_A;
          bfp_complex_s32_t* chanB = (bfp_complex_s32_t*) &channel_B;

          // Operate on frequency domain data using `chanA` and `chanB`
          ...
          // Perform the inverse DFT to go back to time domain
          bfp_fft_inverse_stereo(&chanA, &chanB, scratch);

          // Use channel_A and channel_B again to use new time domain data.
          ...

    // Suppress this from generated documentation for the time being //

    Note

    Use of this function is not currently recommended. It functions correctly, but a recent change in this library’s API (namely, dropping support for channel-pair vectors) means this function is no more computationally efficient than calling `bfp_fft_forward_mono()` on each input vector separately. Additionally, this function currently requires a scratch buffer, whereas the mono FFT does not.

    Parameters:

      - A_fft – [inout] [Input] Freq-domain BFP vector \(\bar A\). [Output] Time domain BFP vector \(\bar b\)

      - B_fft – [inout] [Input] Freq-domain BFP vector \(\bar b\). [Output] Time domain BFP vector \(\bar b\)

      - scratch – Scratch buffer of at least `2*A_fft->length` `complex_s32_t` elements

  void bfp_fft_unpack_mono(bfp_complex_s32_t *x)

    Unpack the spectrum resulting from bfp_fft_forward_mono().

    The DFT of a real signal is periodic with period FFT_N (the FFT length) and has a complex conjugate symmetry about index 0. These two properties guarantee that the imaginary part of both the DC component (index 0) and the Nyquist component (index FFT_N/2) of the spectrum are zero. To compute the forward FFT in-place, bfp_fft_forward_mono() packs the real part of the Nyquist rate component of the output spectrum into the imaginary part of the DC component.

    This may be undesirable when operating on the signal’s complex spectrum. Use this function to unpack the Nyquist component. This function will also adjust the BFP vector’s length to reflect this unpacking.

    NOTE: If you intend to unpack the spectrum using this function, the buffer for the time-domain BFP vector must have length `FFT_N+2`, rather than `FFT_N` (`int32_t` elements), but these should NOT be reflected in the time-domain BFP vector’s `length` field.

    Operation Performed

      \[\begin{split}\begin{aligned} & Re{x_{N/2}} && \leftarrow Im{x_0} \\ & Im{x_0} && \leftarrow 0 \\ & Im{x_{N/2}} && \leftarrow 0 \\ & x.length && \leftarrow x.length + 1 \end{aligned}\end{split}\]

    NOTE: Before bfp_fft_inverse_mono() may be applied, bfp_fft_pack_mono() must be called, as the inverse FFT expects the data to be packed.

    See also

    bfp_fft_forward_mono, bfp_fft_pack_mono

    Parameters:

      - x – [inout] The spectrum to be unpacked

  void bfp_fft_pack_mono(bfp_complex_s32_t *x)

    Pack the spectrum resulting from bfp_fft_unpack_mono().

    This function applies the reverse process of bfp_fft_unpack_mono(), to prepare it for an inverse FFT using bfp_fft_inverse_mono().

    See also

    bfp_fft_inverse_mono, bfp_fft_unpack_mono

    Parameters:

      - x – [inout] The spectrum to be packed

  void fft_dit_forward(complex_s32_t x[], const unsigned N, headroom_t *hr, exponent_t *exp)

    Compute a forward DFT using the decimation-in-time FFT algorithm.

    This function computes the `N`-point forward DFT of a complex input signal using the decimation-in-time FFT algorithm. The result is computed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & X[f] = \frac{1}{2^{\alpha}} \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ & \text{ for } 0 \le f < N \end{aligned}\end{split}\]

    `x[]` is interpreted to be a block floating-point vector with shared exponent `*exp` and with `*hr` bits of headroom initially in `x[]`. During computation, this function monitors the headroom of the data and compensates to avoid overflows and underflows by bit-shifting the data up or down as appropriate. In the equation above, \(\alpha\) represents the (net) number of bits that the data was right-shifted by.

    Upon completion, `*hr` is updated with the final headroom in `x[]`, and the exponent `*exp` is incremented by \(\alpha\).

    Note

    In order to guarantee that saturation will not occur, `x[]` must have an initial headroom of at least 2 bits.

    Parameters:

      - x – [inout] The `N`-element complex input vector to be transformed.

      - N – [in] The size of the DFT to be performed.

      - hr – [inout] Pointer to the initial headroom in `x[]`.

      - exp – [inout] Pointer to the initial exponent associated with `x[]`.

    Throws ET_LOAD_STORE:

      Raised if `x` is not word-aligned (See Note: Vector Alignment)

  void fft_dit_inverse(complex_s32_t x[], const unsigned N, headroom_t *hr, exponent_t *exp)

    Compute an inverse DFT using the decimation-in-time IFFT algorithm.

    This function computes the `N`-point inverse DFT of a complex spectrum using the decimation-in-time IFFT algorithm. The result is computed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & x[n] = \frac{1}{2^{\alpha}} \sum_{f=0}^{N-1} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ & \text{ for } 0 \le n < N \end{aligned}\end{split}\]

    `x[]` is interpreted to be a block floating-point vector with shared exponent `*exp` and with `*hr` bits of headroom initially in `x[]`. During computation, this function monitors the headroom of the data and compensates to avoid overflows and underflows by bit-shifting the data up or down as appropriate. In the equation above, \(\alpha\) represents the (net) number of bits that the data was right-shifted by.

    Upon completion, `*hr` is updated with the final headroom in `x[]`, and the exponent `*exp` is incremented by \(\alpha - log_2(N)\).

    Note

    In order to guarantee that saturation will not occur, `x[]` must have an initial headroom of at least 2 bits.

    Parameters:

      - x – [inout] The `N`-element complex input vector to be transformed.

      - N – [in] The size of the inverse DFT to be performed.

      - hr – [inout] Pointer to the initial headroom in `x[]`.

      - exp – [inout] Pointer to the initial exponent associated with `x[]`.

    Throws ET_LOAD_STORE:

      Raised if `x` is not word-aligned (See Note: Vector Alignment)

  void fft_dif_forward(complex_s32_t x[], const unsigned N, headroom_t *hr, exponent_t *exp)

    Compute a forward DFT using the decimation-in-frequency FFT algorithm.

    This function computes the `N`-point forward DFT of a complex input signal using the decimation-in-frequency FFT algorithm. The result is computed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & X[f] = \frac{1}{2^{\alpha}} \sum_{n=0}^{N-1} \left( x[n]\cdot e^{-j2\pi fn/N} \right) \\ & \text{ for } 0 \le f < N \end{aligned}\end{split}\]

    `x[]` is interpreted to be a block floating-point vector with shared exponent `*exp` and with `*hr` bits of headroom initially in `x[]`. During computation, this function monitors the headroom of the data and compensates to avoid overflows and underflows by bit-shifting the data up or down as appropriate. In the equation above, \(\alpha\) represents the (net) number of bits that the data was right-shifted by.

    Upon completion, `*hr` is updated with the final headroom in `x[]`, and the exponent `*exp` is incremented by \(\alpha\).

    Note

    In order to guarantee that saturation will not occur, `x[]` must have an initial headroom of at least 2 bits.

    Parameters:

      - x – [inout] The `N`-element complex input vector to be transformed.

      - N – [in] The size of the DFT to be performed.

      - hr – [inout] Pointer to the initial headroom in `x[]`.

      - exp – [inout] Pointer to the initial exponent associated with `x[]`.

    Throws ET_LOAD_STORE:

      Raised if `x` is not word-aligned (See Note: Vector Alignment)

  void fft_dif_inverse(complex_s32_t x[], const unsigned N, headroom_t *hr, exponent_t *exp)

    Compute an inverse DFT using the decimation-in-frequency IFFT algorithm.

    This function computes the `N`-point inverse DFT of a complex spectrum using the decimation-in-frequency IFFT algorithm. The result is computed in-place.

    Operation Performed

      \[\begin{split}\begin{aligned} & x[n] = \frac{1}{2^{\alpha}} \sum_{f=0}^{N-1} \left( X[f]\cdot e^{j2\pi fn/N} \right) \\ & \text{ for } 0 \le n < N \end{aligned}\end{split}\]

    `x[]` is interpreted to be a block floating-point vector with shared exponent `*exp` and with `*hr` bits of headroom initially in `x[]`. During computation, this function monitors the headroom of the data and compensates to avoid overflows and underflows by bit-shifting the data up or down as appropriate. In the equation above, \(\alpha\) represents the (net) number of bits that the data was right-shifted by.

    Upon completion, `*hr` is updated with the final headroom in `x[]`, and the exponent `*exp` is incremented by \(\alpha - log_2(N)\).

    Note

    In order to guarantee that saturation will not occur, `x[]` must have an initial headroom of at least 2 bits.

    Parameters:

      - x – [inout] The `N`-element complex input vector to be transformed.

      - N – [in] The size of the inverse DFT to be performed.

      - hr – [inout] Pointer to the initial headroom in `x[]`.

      - exp – [inout] Pointer to the initial exponent associated with `x[]`.

    Throws ET_LOAD_STORE:

      Raised if `x` is not word-aligned (See Note: Vector Alignment)