diff --git a/out.csv b/out.csv
index 606a005..f8a772b 100644
--- a/out.csv
+++ b/out.csv
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+inf,0.052643593,
+inf,0.01738466,
+inf,0.08976218,
+inf,0.036189523,
+inf,0.012412146,
+inf,0.087044664,
+NaN,0.006123106,
+NaN,0.0075100553,
+NaN,0.045062404,
+NaN,0.101523735,
+NaN,0.024446653,
+NaN,0.00552307,
+NaN,0.01167301,
+NaN,0.062529445,
+NaN,0.017789006,
+NaN,0.008471162,
+NaN,0.014686415,
+NaN,0.011263741,
+NaN,0.037892517,
+NaN,0.039340757,
+NaN,0.01051959,
+NaN,0.037056174,
+NaN,0.11604104,
+NaN,0.009205304,
+NaN,0.055387173,
+NaN,0.00819793,
+NaN,0.04131652,
+NaN,0.03827691,
+NaN,0.045181405,
+NaN,0.0076938844,
+NaN,0.07616247,
+NaN,0.08462321,
+NaN,0.015132117,
+NaN,0.018358923,
+NaN,0.013284806,
+NaN,0.024557305,
+NaN,0.045315,
+NaN,0.029241713,
+NaN,0.061268665,
+NaN,0.080607414,
+NaN,0.012350233,
+NaN,0.028450007,
+NaN,0.038868524,
+NaN,0.0055723847,
+NaN,0.13128309,
+NaN,0.011653948,
+NaN,0.040431693,
+NaN,0.03452446,
+NaN,0.02401372,
+NaN,0.01845637,
+NaN,0.0068017836,
+NaN,0.012515326,
+NaN,0.010772835,
+0.00000000028218064,0.049956832,
+0.00000006593633,0.023087975,
+0.000056579367,0.008251006,
+0.030075686,0.04416382,
+26.841476,0.014911537,
+20505.045,0.017835585,
+20569212,0.009352485,
+15566198000,0.032767292,
+21241540000000,0.028296202,
+26385578000000000,0.24819264,
+inf,0.036346078,
+inf,0.013867968,
+inf,0.022261523,
+inf,0.028047912,
+inf,0.0091926595,
+inf,0.026851974,
+inf,0.009193021,
+NaN,0.02253213,
+NaN,0.035268825,
+NaN,0.07122683,
+NaN,0.026722498,
+NaN,0.008823038,
+NaN,0.02923289,
+NaN,0.007086563,
+NaN,0.008415913,
+NaN,0.016887747,
+NaN,0.048716486,
+NaN,0.017504524,
+NaN,0.018290833,
+NaN,0.02468298,
+NaN,0.035464033,
+NaN,0.030566515,
+NaN,0.023218652,
+NaN,0.019373624,
+NaN,0.028258689,
+NaN,0.031155856,
+NaN,0.062986866,
+NaN,0.014286407,
+NaN,0.0059457566,
+NaN,0.012821926,
+NaN,0.010947912,
+NaN,0.06474611,
+NaN,0.03190613,
+NaN,0.006050038,
+NaN,0.13149868,
+NaN,0.02861246,
+NaN,0.029239638,
+NaN,0.016975148,
+NaN,0.018089091,
+NaN,0.035088677,
+NaN,0.022062525,
+NaN,0.029293181,
+NaN,0.017082134,
+NaN,0.022892777,
+NaN,0.024192818,
+NaN,0.04867065,
+NaN,0.020805098,
+NaN,0.022518612,
+NaN,0.013112249,
+NaN,0.026231911,
+NaN,0.009777577,
+NaN,0.008326415,
+NaN,0.021842523,
+NaN,0.07415163,
+0.0000000025115818,0.027869225,
+0.00000094438843,0.15753588,
+0.00033033272,0.009109859,
+0.28461784,0.013369024,
+140.32462,0.016180178,
+200708.58,0.046301108,
+226506670,0.008726379,
+221991530000,0.011143562,
+199203280000000,0.017337833,
+248445990000000000,0.01764002,
+inf,0.02109857,
+inf,0.047790222,
+inf,0.031519253,
+inf,0.08990689,
+inf,0.008861429,
+inf,0.017515713,
+inf,0.023615085,
+NaN,0.0061068838,
+NaN,0.012699315,
+NaN,0.026163515,
+NaN,0.035831906,
+NaN,0.075557455,
+NaN,0.021918131,
+NaN,0.009009454,
+NaN,0.035757188,
+NaN,0.03705193,
+NaN,0.14959224,
+NaN,0.09174755,
+NaN,0.021495862,
+NaN,0.05250644,
+NaN,0.0041095875,
+NaN,0.10462898,
+NaN,0.0145207625,
+NaN,0.06782774,
+NaN,0.010878138,
+NaN,0.032607436,
+NaN,0.01293636,
+NaN,0.02569694,
+NaN,0.18222694,
+NaN,0.011385256,
+NaN,0.060232334,
+NaN,0.011990149,
+NaN,0.006120022,
+NaN,0.034112506,
+NaN,0.029830657,
+NaN,0.04017119,
+NaN,0.04222591,
+NaN,0.05671345,
+NaN,0.013873175,
+NaN,0.006999775,
+NaN,0.15964825,
+NaN,0.041701384,
+NaN,0.108236134,
+NaN,0.0064416775,
+NaN,0.014378196,
+NaN,0.102653265,
+NaN,0.032323822,
+NaN,0.04087752,
+NaN,0.005271934,
+NaN,0.17874242,
+NaN,0.00985278,
+NaN,0.16435303,
+NaN,0.006492914,
+NaN,0.8440847,
diff --git a/out.txt b/out.txt
index 0e0a395..3d9b888 100644
Binary files a/out.txt and b/out.txt differ
diff --git a/sine.wav b/sine.wav
index 1319c3e..b2ca554 100644
Binary files a/sine.wav and b/sine.wav differ
diff --git a/src/bfsk.rs b/src/bfsk.rs
index 18c11e6..31a2022 100644
--- a/src/bfsk.rs
+++ b/src/bfsk.rs
@@ -3,13 +3,13 @@
 use std::f32::consts::PI;
 
 use crate::complex::{Complex, Complex32};
-use crate::fft::{self, windows};
+use crate::fft::{self, windows, FFTDirection, FFT};
 use crate::map;
 use crate::nco::Nco;
 
 pub struct BFSKMod<'a, T: Iterator<Item = bool>> {
     samples_per_bit: u32,
-    bandwidth: f32,
+    deviation: f32,
     bit_stream: &'a mut T,
 
     // State
@@ -21,10 +21,10 @@ impl<'a, T> BFSKMod<'a, T>
 where
     T: Iterator<Item = bool>,
 {
-    pub fn new(samples_per_bit: u32, bandwidth: f32, bit_stream: &'a mut T) -> Self {
+    pub fn new(samples_per_bit: u32, deviation: f32, bit_stream: &'a mut T) -> Self {
         BFSKMod {
             samples_per_bit,
-            bandwidth,
+            deviation,
             oscillator: Nco::new(0.0),
             bit_stream,
             sample_index: samples_per_bit,
@@ -37,9 +37,9 @@ where
             let bit = self.bit_stream.next()?;
 
             let frequency = if bit {
-                self.bandwidth / 2.0
+                self.deviation
             } else {
-                -self.bandwidth / 2.0
+                -self.deviation
             };
             self.oscillator.set_frequency(frequency);
         }
@@ -56,62 +56,36 @@ pub struct BFSKDem {
     deviation: f32,
     // State
     sample_index: u32,
+    fft: FFT,
 
-    //fft: Box<dyn DFT>,
+    bin_pos: usize,
+    bin_neg: usize,
 }
 
 impl BFSKDem {
     pub fn new(samples_per_bit: u32, deviation: f32) -> Self {
+        // Calculate bin locations :
+        let bin_index = map(deviation, 0., 2. * PI, 0., samples_per_bit as f32).floor() as u32;
+
+        println!("bin_index: {bin_index}");
+        
         BFSKDem {
             samples_per_bit,
             deviation,
             sample_index: 0,
-            //fft: fft::create_fft(samples_per_bit as usize, fft::FFTDirection::Forward),
+            fft: FFT::new(samples_per_bit as usize, windows::rectangular),
+            bin_pos: bin_index as usize,
+            bin_neg: (samples_per_bit - bin_index - 1) as usize, // -deviation = negative frequency = upper half
         }
     }
 
     pub fn demod(&mut self, baseband: &[Complex32]) -> bool {
         assert!(baseband.len() >= self.samples_per_bit as usize);
+        self.fft.execute(baseband);
 
-        /*
-        self.fft
-            .get_input()
-            .iter_mut()
-            .enumerate()
-            .for_each(|(i, x)| *x = baseband[i]);
-        self.fft.execute(windows::rectanguar);
-        */
+        let positive_energy = self.fft.get_output()[self.bin_pos];
+        let negative_energy = self.fft.get_output()[self.bin_neg];
 
-        let bin_id = map(
-            self.deviation,
-            0.,
-            PI,
-            0.,
-            (self.samples_per_bit / 2) as f32,
-        )
-        .floor() as i32;
-
-        let bin_width = 5;
-
-        /*
-        let mut positive_energy = 0.0;
-        for i in (bin_id - bin_width)..(bin_id + bin_width) {
-            if i >= 0 && i < self.samples_per_bit as i32 {
-                positive_energy += self.fft.get_output()[i as usize].mag();
-            }
-        }
-
-        let mut negative_energy = 0.0;
-        for i in (self.samples_per_bit as i32 - bin_id - bin_width)
-            ..(self.samples_per_bit as i32 - bin_id + bin_width)
-        {
-            if i >= 0 && i < self.samples_per_bit as i32 {
-                negative_energy += self.fft.get_output()[i as usize].mag();
-            }
-        }
-
-        return positive_energy < negative_energy;
-        */
-        false
+        positive_energy.mag() < negative_energy.mag()
     }
 }
diff --git a/src/fft.rs b/src/fft.rs
index b9aa676..05a61a6 100644
--- a/src/fft.rs
+++ b/src/fft.rs
@@ -39,23 +39,25 @@ pub trait DFTAlgorithm {
     fn get_output(&self) -> &[Complex32];
 }
 
-fn create_fft(size: usize, direction: FFTDirection) -> Box<dyn DFTAlgorithm> {
+pub fn create_fft(size: usize, direction: FFTDirection) -> Box<dyn DFTAlgorithm> {
     if size <= 16 {
-        //println!("Naive {size}");
+        println!("Naive {size}");
         return Box::new(NaiveDFT::create(size, direction));
     }
     if size.count_ones() == 1 {
-        //println!("Radix 2 {size}");
+        println!("Radix 2 {size}");
         return Box::new(Radix2FFT::create(size, direction));
     }
 
     if is_prime(size) {
-        //println!("Prime rader {size}");
+        println!("Prime rader {size}");
         return Box::new(RaderFFT::create(size, direction));
+        //return Box::new(NaiveDFT::create(size, direction));
     }
 
-    //println!("Mixed radix {size}");
+    println!("Mixed radix {size}");
     Box::new(MixedRadixFFT::create(size, direction))
+    //Box::new(NaiveDFT::create(size, direction))
 }
 
 pub struct FFT
diff --git a/src/fft/mixed_radix.rs b/src/fft/mixed_radix.rs
index dc42f13..0a32953 100644
--- a/src/fft/mixed_radix.rs
+++ b/src/fft/mixed_radix.rs
@@ -29,6 +29,9 @@ impl DFTAlgorithm for MixedRadixFFT {
         let qfft = create_fft(q, direction);
         let pfft = create_fft(p, direction);
 
+        //let qfft = Box::new(NaiveDFT::create(q, direction));
+        //let pfft = Box::new(NaiveDFT::create(p, direction));
+
         MixedRadixFFT {
             twiddle_factors: compute_twiddle_factors(size, direction),
             qfft,
diff --git a/src/fft/rader.rs b/src/fft/rader.rs
index e6bce41..e906fe9 100644
--- a/src/fft/rader.rs
+++ b/src/fft/rader.rs
@@ -4,7 +4,7 @@ use std::f32::consts::PI;
 
 use crate::{
     complex::Complex32,
-    fft::{create_fft, is_prime , DFTAlgorithm, FFTDirection},
+    fft::{create_fft, dft::NaiveDFT, is_prime, DFTAlgorithm, FFTDirection},
 };
 
 pub struct RaderFFT {
@@ -31,7 +31,8 @@ impl DFTAlgorithm for RaderFFT {
         let permutations: Box<[usize]> = (0..(size - 1)).map(|i| exp_mod(g, i + 1, size)).collect();
 
         // Compute fourrier transform of twiddle factors
-        let mut convolution_fft = create_fft(size - 1, FFTDirection::Forward);
+        //let mut convolution_fft = create_fft(size - 1, FFTDirection::Forward);
+        let mut convolution_fft = Box::new(NaiveDFT::create(size - 1, FFTDirection::Forward));
         let mut convolution_operand = (0..(size - 1))
             .map(|i| {Complex32::cexp(-2. * direction.sign() * PI * (permutations[i] as f32) / (size as f32))})
             .collect::<Vec<Complex32>>();
@@ -42,7 +43,8 @@ impl DFTAlgorithm for RaderFFT {
             permutations,
             convolution_operand: convolution_operand.into(),
 
-            convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
+            //convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
+            convolution_ifft: Box::new(NaiveDFT::create(size - 1, FFTDirection::Inverse)),
             convolution_fft,
 
             output: vec![Complex32::zero(); size].into(),
diff --git a/src/fft/rader2.rs b/src/fft/rader2.rs
index 6d14b6e..fbcd9d0 100644
--- a/src/fft/rader2.rs
+++ b/src/fft/rader2.rs
@@ -1,118 +1,91 @@
 // Implementation of raders's fft for prime sized ffts
-
 /*
-use std::{f32::consts::PI, ops::Deref};
 
-use super::mixed_radix;
+use std::f32::consts::PI;
+
 use crate::{
     complex::Complex32,
-    fft::{DFT, FFTDirection, create_fft, dft::NaiveDFT, is_prime, windows},
+    fft::{create_fft, dft::NaiveDFT, is_prime, DFTAlgorithm, FFTDirection},
 };
 
-pub struct Rader2FFT {
-    input_buffer: Box<[Complex32]>,
-    output_buffer: Box<[Complex32]>,
+pub struct RaderFFT {
+    permutations: Box<[usize]>,
+    convolution_operand: Box<[Complex32]>,
+
+    convolution_ifft: Box<dyn DFTAlgorithm>,
+    convolution_fft: Box<dyn DFTAlgorithm>,
+
+    output: Box<[Complex32]>,
 
     size: usize,
-    sub_size: usize,
-
-    // Fourrier transform of the exponential terms
-    convolution_operand: Box<[Complex32]>,
-    convolution_fft: Box<dyn DFT>, // TODO: Use fft
-    permutation: Box<[usize]>,
 }
 
-impl DFT for Rader2FFT {
+impl DFTAlgorithm for RaderFFT {
     fn create(size: usize, direction: FFTDirection) -> Self
     where
         Self: Sized,
     {
+        assert!(is_prime(size));
+
+        // Primitive root and its powers
         let g = compute_prime_primitive_root(size);
-        let permutation: Box<[usize]> = (0..(size - 1)).map(|i| exp_mod(g, i + 1, size)).collect();
-        let sub_size = next_pow2((2 * size - 4) - 1);
-        Rader2FFT {
-            input_buffer: vec![Complex32::zero(); size].into_boxed_slice(),
-            output_buffer: vec![Complex32::zero(); sub_size].into_boxed_slice(),
+        let permutations: Box<[usize]> = (0..(size - 1)).map(|i| exp_mod(g, i + 1, size)).collect();
 
+        // Compute fourrier transform of twiddle factors
+        let mut convolution_fft = create_fft(size - 1, FFTDirection::Forward);
+        //let mut convolution_fft = Box::new(NaiveDFT::create(size - 1, FFTDirection::Forward));
+        let mut convolution_operand = (0..(size - 1))
+            .map(|i| {Complex32::cexp(-2. * direction.sign() * PI * (permutations[i] as f32) / (size as f32))})
+            .collect::<Vec<Complex32>>();
+        convolution_fft.execute(&convolution_operand);
+        convolution_operand = Vec::from(convolution_fft.get_output());
+
+        RaderFFT {
+            permutations,
+            convolution_operand: convolution_operand.into(),
+
+            convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
+            //convolution_ifft: Box::new(NaiveDFT::create(size - 1, FFTDirection::Inverse)),
+            convolution_fft,
+
+            output: vec![Complex32::zero(); size].into(),
             size,
-            sub_size,
-
-            convolution_operand: compute_convolution_operand(size, sub_size, &permutation),
-            //convolution_fft: create_fft(next_pow2((2 * size - 4) - 1)),
-            convolution_fft: Box::new(NaiveDFT::create(sub_size)),
-            permutation,
         }
     }
 
-    fn execute(&mut self, window: fn(f32) -> f32) {
-        self.convolution_fft.get_input()[0] = self.input_buffer[self.permutation[self.size - 2]];
-
-        for i in 0..(self.sub_size - self.size + 1) {
-            self.convolution_fft.get_input()[i + 1] = Complex32::zero();
-        }
-        for i in 1..(self.size - 1) {
-            let k = self.permutation[self.size - 1 - i - 1];
-            self.convolution_fft.get_input()[i + self.sub_size - self.size + 1] =
-                self.input_buffer[k] * window(k as f32 / self.size as f32)
+    fn execute(&mut self, input: &[Complex32]) {
+        // Compute fft of input signal
+        for i in 0..(self.size - 1) {
+            let k = self.permutations[self.size - 1 - i - 1];
+            // Using output as staging buffer
+            self.output[i] = input[k];
         }
 
-        self.convolution_fft.execute(windows::rectanguar);
+        self.convolution_fft.execute(&self.output);
 
-        // Use output buffer as staging buffer
-        for i in 0..(self.sub_size) {
-            self.output_buffer[i] =
-                self.convolution_fft.get_output()[i] * self.convolution_operand[i];
+        // Compute convolution by multiplying in freq domain
+        for i in 0..(self.size - 1) {
+            // Using output as staging buffer
+            self.output[i] = self.convolution_fft.get_output()[i] * self.convolution_operand[i];
         }
 
-        for i in 0..(self.sub_size) {
-            self.convolution_fft.get_input()[i] = self.output_buffer[i];
-        }
-        /*
-        self.convolution_fft.get_input()[0] =
-            self.convolution_fft.get_input()[0] + self.input_buffer[0] * window(0.);
-        */
+        self.convolution_ifft.execute(&self.output);
 
-        // Compute ifft to obtain convolution
-        self.convolution_fft.execute(window);
+        self.output[0] = input[0];
 
         for i in 0..(self.size - 1) {
-            self.output_buffer[self.permutation[i]] =
-                self.convolution_fft.get_output()[i] / self.sub_size as f32;
+            // Actually compute the output
+            let k = self.permutations[i];
+            self.output[k] = (self.convolution_ifft.get_output()[i] / (self.size - 1) as f32) + input[0];
+            self.output[0] = self.output[0] + input[i + 1];
         }
-
-        self.output_buffer[0] = self
-            .input_buffer
-            .iter()
-            .copied()
-            .enumerate()
-            .map(|(i, x)| x * window(i as f32 / self.size as f32))
-            .sum();
-    }
-
-    fn get_input(&mut self) -> &mut [Complex32] {
-        &mut self.input_buffer
     }
 
     fn get_output(&self) -> &[Complex32] {
-        &self.output_buffer
+        &self.output
     }
 }
 
-pub fn compute_convolution_operand(
-    n: usize,
-    sub_size: usize,
-    permutation: &[usize],
-) -> Box<[Complex32]> {
-    //let mut fft = create_fft(sub_size);
-    let mut fft = NaiveDFT::create(sub_size);
-
-    fft.get_input().iter_mut().enumerate().for_each(|(i, x)| {
-        *x = Complex32::cexp(-2. * PI * (permutation[i % (n - 1)] as f32) / (n as f32))
-    });
-    fft.execute(windows::rectanguar);
-    fft.get_output().iter().copied().collect()
-}
-
 pub fn compute_prime_primitive_root(n: usize) -> usize {
     assert!(is_prime(n));
 
@@ -123,7 +96,7 @@ pub fn compute_prime_primitive_root(n: usize) -> usize {
         // Find multiplicative order of i
         let mut val = i;
         let mut order = 1;
-        for j in 0..n {
+        for _ in 0..n {
             if val == 1 {
                 break;
             }
@@ -158,12 +131,4 @@ pub fn exp_mod(mut n: usize, mut exp: usize, m: usize) -> usize {
     r
 }
 
-pub fn next_pow2(mut n: usize) -> usize {
-    let mut pow = 0;
-    while n > 0 {
-        n >>= 1;
-        pow += 1;
-    }
-    1 << pow
-}
 */
diff --git a/src/main.rs b/src/main.rs
index 4d8e985..617385f 100644
--- a/src/main.rs
+++ b/src/main.rs
@@ -19,7 +19,7 @@ use nco::Nco;
 use plotters::prelude::*;
 use fft::DFTAlgorithm;
 
-use crate::{bfsk::BFSKDem, fft::{dft::NaiveDFT, mixed_radix::MixedRadixFFT, rader::RaderFFT, radix2::Radix2FFT, windows, FFT}};
+use crate::{bfsk::BFSKDem, fft::{create_fft, dft::NaiveDFT, mixed_radix::MixedRadixFFT, rader::RaderFFT, radix2::Radix2FFT, windows, FFTDirection, FFT}};
 
 // Utilities
 fn map<T>(input: T, in_min: T, in_max: T, out_min: T, out_max: T) -> T
@@ -29,15 +29,46 @@ where
     ((input - in_min.clone()) / (in_max - in_min)) * (out_max - out_min.clone()) + out_min
 }
 
-
 fn main() {
-    modulate();
+    //modulate();
+    test();
+}
+
+fn test()
+{
+    let mut o1 = Nco::new(PI / 2.0);
+    let mut o2 = Nco::new(PI / 4.0);
+    let sample_count = 4800;
+    //let mut fft = FFT::new(sample_count, windows::rectangular);
+    let mut dft = NaiveDFT::create(sample_count, FFTDirection::Forward);
+    let mut fft = FFT::new(sample_count, windows::rectangular);
+    //let mut fft = RaderFFT::create(sample_count, FFTDirection::Forward);
+    let mut fft_input = vec![Complex32::zero(); sample_count];
+
+    for x in fft_input.iter_mut()
+    {
+        *x = o1.cexp() + o2.cexp();
+        o1.step();
+        o2.step();
+    }
+
+    fft.execute(&fft_input);
+    dft.execute(&fft_input);
+
+    let mut out_file = File::create("out.csv").unwrap();
+    for (x, y) in fft.get_output().iter().zip(dft.get_output())
+    {
+        out_file.write_all(
+            format!("{},{},\n", x.mag(), y.mag()).as_bytes()
+            ).unwrap();
+    }
 }
 
 fn modulate() {
     let sample_rate = 44100;
-    let mut frequency = 2000.0; //HZ
-    let mut bandwidth = 500.0; //HZ
+    let frequency = 2000.0; //HZ
+    let bandwidth = 1000.0; //HZ
+    println!("deviation: {}", PI * (bandwidth / sample_rate as f32));
 
     let path = "s.txt";
     let file = File::open(path).unwrap();
@@ -61,7 +92,7 @@ fn modulate() {
     println!("{} samples/bit", sample_rate / baud_rate);
     let mut bfsk = BFSKMod::new(
         sample_rate / baud_rate,
-        2. * PI * (bandwidth / sample_rate as f32),
+        PI * 0.05, //PI * (bandwidth / sample_rate as f32),
         &mut bit_stream,
     );
 
@@ -90,6 +121,17 @@ fn modulate() {
         lo.step();
     }
     writer.finalize().unwrap();
+    let mut tfft = FFT::new(44100, windows::rectangular);
+    tfft.execute(&output_samples);
+
+    // Write csv
+    let mut out_csv = File::create("out.csv").unwrap();
+    for x in output_samples.iter().take(4400)
+    {
+        out_csv.write_all(
+            format!("{},\n", x.mag()).as_bytes()
+        ).unwrap();
+    }
 
     let mut of = File::create("out.txt").unwrap();
 
@@ -97,7 +139,7 @@ fn modulate() {
     let mut lodem = Nco::new(-2. * PI * (frequency / sample_rate as f32));
     let mut demod = BFSKDem::new(
         sample_rate / baud_rate,
-        PI * (bandwidth / sample_rate as f32),
+        PI * 0.05, //PI * (bandwidth / sample_rate as f32),
     );
     for chunk in output_samples.chunks((sample_rate / baud_rate) as usize) {
         let base_chunk: Vec<Complex32> = chunk
@@ -109,7 +151,7 @@ fn modulate() {
             .collect();
         let bit = demod.demod(base_chunk.as_slice());
         bits.push(bit);
-        println!("{:?}", bit)
+        //println!("{:?}", bit)
     }
 
     for b in bits.chunks(8) {