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|
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#N canvas 297 254 646 523 fft-analysis 0;
#X obj 115 409 *~;
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#X obj 76 137 rfft~;
#X obj 75 466 *~;
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#X obj 75 432 rifft~;
#X obj 75 489 outlet~;
#X obj 137 177 *~;
#X obj 137 200 +~;
#X obj 461 85 block~ 1024 4;
#X obj 137 351 clip~;
#X obj 178 306 r squelch;
#X obj 110 114 tabreceive~ \$0-hann;
#X obj 177 329 expr 0.01*$f1*$f1;
#X obj 461 116 loadbang;
#X obj 137 381 *~ 0.00065;
#X obj 137 225 +~ 1e-20;
#X obj 136 262 q8_rsqrt~;
#X obj 109 466 tabreceive~ \$0-hann;
#X text 31 5 As in the previous patch \, this works by multiplying
each channel of the Fourier analysis by a real number computed from
the magnitude. If the magnutude is "m" \, the correction factor is
1/m \, but only to an upper limit controlled by the "squelch" parameter.
;
#X text 211 174 squared magnitude;
#X text 219 225 protect against divide-by-zero;
#X text 223 261 quick 8-bit-accurate reciprocal square root;
#X text 222 277 (done by table lookup - about 0.25% accurate);
#X text 193 351 limit the gain to squelch*squelch/100;
#X text 238 381 normalize for 1024-point \, overlap-4 Hann;
#X text 151 409 multiply gain by real and complex part;
#X text 152 429 of the amplitude;
#X text 130 137 outputs complex amplitudes;
#X msg 461 139 \; pd dsp 1 \; window-size 1024 \; squelch 10 \; squelch-set
set 10;
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#X msg 90 322 1;
#X obj 90 344 metro 1000;
#X obj 259 272 t b b f;
#X obj 117 270 t b f;
#X obj 90 469 tabread4~ \$0-sample;
#X text 21 28 test signal: looped sample playback;
#X obj 67 131 hip~ 5;
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#X obj 129 107 samplerate~;
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#X restore 43 303 pd test-signal;
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#X restore 259 24 graph;
#X obj 19 23 r read-sample;
#X obj 19 74 unpack s f;
#X obj 19 184 soundfiler;
#X text 356 250 read a sample;
#X obj 276 249 loadbang;
#X obj 19 100 t s b;
#X obj 75 99 symbol \$0-sample;
#X obj 19 135 pack s s;
#X msg 19 160 read -resize \$1 \$2;
#X obj 74 46 44100;
#X obj 19 47 t a b;
#X msg 276 273 \; read-sample ../sound/bell.aiff;
#X obj 29 208 s \$0-samplength;
#X obj 116 74 s \$0-insamprate;
#X obj 19 247 /;
#X obj 19 271 * 1000;
#X obj 19 294 s \$0-samp-msec;
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#X restore 223 313 pd insample;
#X text 362 406 updated for Pd version 0.39;
#X text 56 43 Here we divide each complex channel in the Fourier analysis
by its own magnitude to "flatten" the spectrum. The "squelch" control
limits the amplitude boost the algorithm will apply. If infinite \,
you'll get a white spectrum. If less \, the louder parts of the spectrum
will be flattened but the quieter ones will only be boosted by the
squelch value.;
#X text 73 6 DYNAMIC RANGE COMPRESSION BY FOURIER ANALYSIS CHANNEL
;
#X floatatom 223 366 5 0 0 0 - #0-samp-msec -;
#X obj 43 282 bng 15 250 50 0 empty empty empty 0 -6 0 8 -262144 -1
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#X text 62 281 <- record;
#X text 276 365 sample length \, msec;
#X msg 292 183 ../sound/bell.aiff;
#X msg 292 208 ../sound/voice.wav;
#X msg 292 233 ../sound/voice2.wav;
#X text 91 197 <- squelch;
#X text 295 161 change input sound;
#X obj 292 259 s read-sample;
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#X array \$0-hann 1024 float 0;
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#X restore 82 311 graph;
#X obj 378 165 osc~;
#X obj 378 190 *~ -0.5;
#X obj 378 214 +~ 0.5;
#X obj 331 247 tabwrite~ \$0-hann;
#X obj 37 88 r window-size;
#X obj 38 173 /;
#X obj 127 142 samplerate~;
#X obj 38 251 s window-sec;
#X obj 177 204 swap;
#X obj 177 228 /;
#X obj 177 252 s window-hz;
#X obj 49 201 * 1000;
#X obj 49 228 s window-msec;
#X obj 38 115 t f b f;
#X msg 173 92 resize \$1;
#X obj 173 116 s \$0-hann;
#X obj 330 105 r window-hz;
#X msg 382 130 0;
#X obj 330 131 t f b;
#X text 15 8 calculate Hann window table (variable window size) and
constants window-hz (fundamental frequency of analysis) \, window-sec
and window-msec (analysis window size in seconds and msec).;
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#X restore 223 335 pd hann-window;
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