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|
(IFFT-ALG
(NAME "ifft")
(ARGUMENTS ("time_type" "t0") ("rate_type" "sr")
("LVAL" "src") ("long" "stepsize")
("LVAL" "window"))
(SUPPORT-FUNCTIONS "
/* index: index into outbuf whree we get output samples
* length: size of the frame, window, and outbuf; half size of samples
* array: spectral frame goes here (why not a local var?)
* window_len: size of window, should equal length
* outbuf: real part of samples are multiplied by window and added to
* outbuf (after shifting)
* src: send :NEXT to this object to get next frame
* stepsize: shift by this many and add each frame
* samples: result of ifft goes here, real and imag
* window: multiply samples by window if any
*
* IMPLEMENTATION NOTE:
* The src argument is an XLisp object that returns either an
* array of samples or NIL. The output of ifft is simply the
* concatenation of the samples taken from the array. Later,
* an ifft will be plugged in and this will return overlapped
* adds of the ifft's.
*
* OVERLAP: stepsize must be less than or equal to the length
* of real part of the transformed spectrum. A transform step
* works like this:
* (1) shift the output buffer by stepsize samples, filling
* the end of the buffer with zeros
* (2) get and transform an array of spectral coefficients
* (3) multiply the result by a window
* (4) add the result to the output buffer
* (5) output the first stepsize samples of the buffer
*
* DATA FORMAT: the DC component goes in array elem 0
* Cosine part is in elements 2*i-1
* Sine part is in elements 2*i
* Nyquist frequency is in element length-1
*/
#include \"samples.h\"
#include \"fftext.h\"
#include \"fft.h\"
#define MUST_BE_FLONUM(e) \\
if (!(e) || ntype(e) != FLONUM) { xlerror(\"in IFFT: flonum expected\", (e)); }
table_type get_window_samples(LVAL window, sample_type **samples, long *len)
{
table_type result = NULL;
if (soundp(window)) {
sound_type window_sound = getsound(window);
xlprot1(window); /* maybe not necessary */
result = sound_to_table(window_sound);
xlpop();
*samples = result->samples;
*len = (long) (result->length + 0.5);
}
return result;
}
")
(SAMPLE-RATE "sr")
(STATE
("long" "index" "stepsize") ; samples index
("long" "length" "0") ; samples length
("LVAL" "array" "NULL")
("long" "window_len" "0")
("sample_type *" "outbuf" "NULL")
("LVAL" "src" "src")
("long" "stepsize" "stepsize")
("sample_type *" "window" "NULL") ; window samples
("sample_type *" "samples" "NULL")
("table_type" "table"
"get_window_samples(window, &susp->window, &susp->window_len)"))
(OUTER-LOOP "
if (susp->src == NULL) {
out: togo = 0; /* indicate termination */
break; /* we're done */
}
if (susp->index >= susp->stepsize) {
long i;
long m, n;
LVAL elem;
susp->index = 0;
susp->array =
xleval(cons(s_send, cons(susp->src, consa(s_next))));
if (susp->array == NULL) {
susp->src = NULL;
goto out;
} else if (!vectorp(susp->array)) {
xlerror(\"in IFFT: array expected\", susp->array);
} else if (susp->samples == NULL) {
/* assume arrays are all the same size as first one;
now that we know the size, we just have to do this
first allocation.
*/
susp->length = getsize(susp->array);
if (susp->length < 1)
xlerror(\"in IFFT: array has no elements\", susp->array);
if (susp->window && (susp->window_len != susp->length))
xlerror(\"in IFFT: window size and spectrum size differ\",
susp->array);
/* tricky non-power of 2 detector: only if this is a
* power of 2 will the highest 1 bit be cleared when
* we subtract 1 ...
*/
if (susp->length & (susp->length - 1))
xlfail(\"spectrum size must be a power of 2\");
if (susp->stepsize < 1)
xlfail(\"in IFFT: step size must be greater than zero\");
if (susp->length < susp->stepsize)
xlerror(\"in IFFT: step size must be smaller than spectrum size\",
susp->array);
susp->samples = (sample_type *) calloc(susp->length,
sizeof(sample_type));
susp->outbuf = (sample_type *) calloc(susp->length,
sizeof(sample_type));
} else if (getsize(susp->array) != susp->length) {
xlerror(\"in IFFT: arrays must all be the same length\", susp->array);
}
/* at this point, we have a new array to put samples */
/* the incoming array format is [DC, R1, I1, R2, I2, ... RN]
* where RN is the real coef at the Nyquist frequency
* but susp->samples should be organized as [DC, RN, R1, I1, ...]
*/
n = susp->length;
/* get the DC (real) coef */
elem = getelement(susp->array, 0);
MUST_BE_FLONUM(elem)
susp->samples[0] = (sample_type) getflonum(elem);
/* get the Nyquist (real) coef */
elem = getelement(susp->array, n - 1);
MUST_BE_FLONUM(elem);
susp->samples[1] = (sample_type) getflonum(elem);
/* get the remaining coef */
for (i = 1; i < n - 1; i++) {
elem = getelement(susp->array, i);
MUST_BE_FLONUM(elem)
susp->samples[i + 1] = (sample_type) getflonum(elem);
}
susp->array = NULL; /* free the array */
/* here is where the IFFT and windowing should take place */
//fftnf(1, &n, susp->samples, susp->samples + n, -1, 1.0);
m = ROUND32(log2(n));
if (!fftInit(m)) riffts(susp->samples, m, 1);
else xlfail(\"FFT initialization error\");
fft_shift(susp->samples, n);
if (susp->window) {
n = susp->length;
for (i = 0; i < n; i++) {
susp->samples[i] *= susp->window[i];
}
}
/* shift the outbuf */
n = susp->length - susp->stepsize;
for (i = 0; i < n; i++) {
susp->outbuf[i] = susp->outbuf[i + susp->stepsize];
}
/* clear end of outbuf */
for (i = n; i < susp->length; i++) {
susp->outbuf[i] = 0;
}
/* add in the ifft result */
n = susp->length;
for (i = 0; i < n; i++) {
susp->outbuf[i] += susp->samples[i];
}
}
togo = min(togo, susp->stepsize - susp->index);\n")
(INNER-LOOP "output = outbuf[index++]")
(CONSTANT "length" "samples" "array" "src" "window")
(TERMINATE COMPUTED)
(FINALIZATION " if (susp->samples) free(susp->samples);
if (susp->table) table_unref(susp->table);
if (susp->outbuf) free(susp->outbuf);\n")
)
|
