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-#N canvas 22 7 886 436 12;
-#X text 85 158 frequency;
-#X floatatom 16 173 0 0 0 0 - - -;
-#X obj 16 120 * 44100;
-#X floatatom 16 94 0 0 0 0 - - -;
-#X text 88 92 frequency;
-#X text 91 111 in bins;
-#X text 85 175 in Hz.;
-#X obj 16 229 osc~;
-#X obj 36 16 fft~;
-#X obj 86 17 ifft~;
-#X text 146 15 - forward and inverse complex FFT;
-#X obj 36 42 rfft~;
-#X obj 86 43 rifft~;
-#X text 146 41 - forward and inverse real FFT;
-#X obj 16 254 rfft~;
-#X obj 16 148 / 64;
-#X obj 574 21 loadbang;
-#X msg 574 47 \; pd dsp 1;
-#X text 636 403 updated for Pd version 0.33;
-#X obj 16 322 rifft~;
-#X obj 102 310 print~ real;
-#X obj 115 285 print~ imaginary;
-#X obj 16 352 /~ 64;
-#X obj 16 407 print~ resynthesized;
-#X msg 30 380 bang;
-#X msg 101 248 bang;
-#X msg 100 199 0.25;
-#X msg 152 199 0;
-#X text 195 200 <-- bash phase;
-#X text 152 249 <-- print analysis;
-#X text 79 380 <-- print resynthesis;
-#X text 76 352 <-- renormalize;
-#X text 347 294 There is no normalization \, so that an FFT followed
-by an IFFT has a gain of N.;
-#X text 346 343 See the FFT examples to see how to use these in practice.
-;
-#X text 347 205 The real FFT outputs N/2+1 real parts and N/2-1 imaginary
-parts. The other outputs are zero. At DC and at the Nyquist there is
-no imaginary part \, but the second through Nth output is as a real
-and imaginary pair \, which can be thought of as the cosine and sin
-component strengths.;
-#X text 346 112 The FFT objects do Fourier analyses and resyntheses
-of incoming real or complex signals. Complex signals are handled as
-pairs of signals (real and imaginary part.) The analysis size is one
-block (you can use the block~ or switch~ objects to control block size).
-;
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-#X connect 3 0 2 0;
-#X connect 7 0 14 0;
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-#X connect 14 1 19 1;
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-#X connect 26 0 7 1;
-#X connect 27 0 7 1;