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-NaN,0.024543295,
-NaN,0.045466714,
-NaN,0.009439746,
-NaN,0.024050266,
-NaN,0.011524844,
-NaN,0.14163013,
-NaN,0.06711505,
-NaN,0.0050045946,
-NaN,0.08104964,
-NaN,0.010765678,
-NaN,0.01674367,
-NaN,0.0056363684,
-NaN,0.032970633,
-NaN,0.09780268,
-NaN,0.027655005,
-NaN,0.029862387,
-NaN,0.014085283,
-NaN,0.009250038,
-NaN,0.03341877,
-NaN,0.017688503,
-NaN,0.018098054,
-0.0000000000196622,0.027327256,
-0.000000012344408,0.021972267,
-0.000007930159,0.016842222,
-0.0049278964,0.07343243,
-2.1558397,0.0104899965,
-2143.0427,0.033005983,
-1242950.1,0.0018248067,
-1920520000,0.040035386,
-2444148000000,0.01662886,
-2459195000000000,0.034301497,
-2419745300000000000,0.0022967993,
-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
deleted file mode 100644
index 3d9b888..0000000
Binary files a/out.txt and /dev/null differ
diff --git a/sine.wav b/sine.wav
deleted file mode 100644
index b2ca554..0000000
Binary files a/sine.wav and /dev/null differ
diff --git a/src/bfsk.rs b/src/bfsk.rs
index 31a2022..f71b4b3 100644
--- a/src/bfsk.rs
+++ b/src/bfsk.rs
@@ -3,7 +3,7 @@
 use std::f32::consts::PI;
 
 use crate::complex::{Complex, Complex32};
-use crate::fft::{self, windows, FFTDirection, FFT};
+use crate::fft::{self, FFT, FFTDirection, windows};
 use crate::map;
 use crate::nco::Nco;
 
@@ -36,11 +36,7 @@ where
             self.sample_index = 0;
             let bit = self.bit_stream.next()?;
 
-            let frequency = if bit {
-                self.deviation
-            } else {
-                -self.deviation
-            };
+            let frequency = if bit { self.deviation } else { -self.deviation };
             self.oscillator.set_frequency(frequency);
         }
 
@@ -65,15 +61,15 @@ pub struct BFSKDem {
 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;
+        let bin_index = map(deviation, 0., 2. * PI, 0., samples_per_bit as f32).round() as u32;
 
         println!("bin_index: {bin_index}");
-        
+
         BFSKDem {
             samples_per_bit,
             deviation,
             sample_index: 0,
-            fft: FFT::new(samples_per_bit as usize, windows::rectangular),
+            fft: FFT::new(samples_per_bit as usize, windows::bartlett),
             bin_pos: bin_index as usize,
             bin_neg: (samples_per_bit - bin_index - 1) as usize, // -deviation = negative frequency = upper half
         }
@@ -86,6 +82,6 @@ impl BFSKDem {
         let positive_energy = self.fft.get_output()[self.bin_pos];
         let negative_energy = self.fft.get_output()[self.bin_neg];
 
-        positive_energy.mag() < negative_energy.mag()
+        positive_energy.mag() > negative_energy.mag()
     }
 }
diff --git a/src/fft.rs b/src/fft.rs
index 05a61a6..91b068b 100644
--- a/src/fft.rs
+++ b/src/fft.rs
@@ -5,11 +5,12 @@ pub mod rader2;
 pub mod radix2;
 pub mod windows;
 
-use std::{iter::Map, process::Output};
-
 use crate::{
     complex::Complex32,
-    fft::{dft::NaiveDFT, mixed_radix::MixedRadixFFT, rader::RaderFFT, radix2::Radix2FFT},
+    fft::{
+        dft::NaiveDFT, mixed_radix::MixedRadixFFT, rader::RaderFFT, rader2::Rader2FFT,
+        radix2::Radix2FFT,
+    },
 };
 
 pub type FFTWindow = fn(f32) -> f32;
@@ -41,39 +42,35 @@ pub trait 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}");
-        return Box::new(RaderFFT::create(size, direction));
+        //println!("Prime rader {size}");
+        return Box::new(Rader2FFT::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
-{
+pub struct FFT {
     fft: Box<dyn DFTAlgorithm>,
     size: usize,
     window: FFTWindow,
-    input_buffer: Box<[Complex32]>
+    input_buffer: Box<[Complex32]>,
 }
 
-impl FFT
-{
-    pub fn new(size: usize, window: FFTWindow) -> FFT
-    {
-        FFT
-        {
+impl FFT {
+    pub fn new(size: usize, window: FFTWindow) -> FFT {
+        FFT {
             fft: create_fft(size, FFTDirection::Forward),
             window,
             size,
@@ -81,10 +78,8 @@ impl FFT
         }
     }
 
-    pub fn new_inv(size: usize) -> FFT
-    {
-        FFT
-        {
+    pub fn new_inv(size: usize) -> FFT {
+        FFT {
             fft: create_fft(size, FFTDirection::Inverse),
             window: windows::rectangular,
             size,
@@ -92,20 +87,17 @@ impl FFT
         }
     }
 
-    pub fn execute(&mut self, input: &[Complex32])
-    {
-        self.input_buffer.iter_mut().zip(input.iter()) 
+    pub fn execute(&mut self, input: &[Complex32]) {
+        self.input_buffer
+            .iter_mut()
+            .zip(input.iter())
             .enumerate()
-            .for_each(|(i, (x, y))|
-                {
-                *x = *y * (self.window)(i as f32 / self.size as f32)
-                });
-        
+            .for_each(|(i, (x, y))| *x = *y * (self.window)(i as f32 / self.size as f32));
+
         self.fft.execute(&self.input_buffer);
     }
 
-    pub fn get_output(&self) -> &[Complex32]
-    {
+    pub fn get_output(&self) -> &[Complex32] {
         self.fft.get_output()
     }
 }
diff --git a/src/fft/mixed_radix.rs b/src/fft/mixed_radix.rs
index 0a32953..60822c4 100644
--- a/src/fft/mixed_radix.rs
+++ b/src/fft/mixed_radix.rs
@@ -9,7 +9,6 @@ use crate::{
 
 pub struct MixedRadixFFT {
     //size: usize, size is implicitely stored in p and q
-
     p: usize,
     q: usize,
     twiddle_factors: Box<[Complex32]>,
@@ -19,7 +18,8 @@ pub struct MixedRadixFFT {
 
     staging_buffer: Box<[Complex32]>,
     pfft_input: Box<[Complex32]>,
-    output: Box<[Complex32]>
+    qfft_input: Box<[Complex32]>,
+    output: Box<[Complex32]>,
 }
 
 impl DFTAlgorithm for MixedRadixFFT {
@@ -39,6 +39,7 @@ impl DFTAlgorithm for MixedRadixFFT {
 
             staging_buffer: vec![Complex32::zero(); size].into_boxed_slice(),
             pfft_input: vec![Complex32::zero(); p].into_boxed_slice(),
+            qfft_input: vec![Complex32::zero(); q].into_boxed_slice(),
             output: vec![Complex32::zero(); size].into_boxed_slice(),
             p,
             q,
@@ -52,10 +53,10 @@ impl DFTAlgorithm for MixedRadixFFT {
             for k1 in 0..self.q {
                 let k = k1 * self.p + k0;
                 // Use output as staging buffer
-                self.output[k1] = input[k];
+                self.qfft_input[k1] = input[k];
             }
 
-            self.qfft.execute(&self.output);
+            self.qfft.execute(&self.qfft_input);
 
             for j0 in 0..self.q {
                 // "Store j0'th of k0'th fft into staging buffer"
diff --git a/src/fft/rader.rs b/src/fft/rader.rs
index e906fe9..cd5bd24 100644
--- a/src/fft/rader.rs
+++ b/src/fft/rader.rs
@@ -4,7 +4,9 @@ use std::f32::consts::PI;
 
 use crate::{
     complex::Complex32,
-    fft::{create_fft, dft::NaiveDFT, is_prime, DFTAlgorithm, FFTDirection},
+    fft::{
+        DFTAlgorithm, FFTDirection, create_fft, dft::NaiveDFT, is_prime, mixed_radix::MixedRadixFFT,
+    },
 };
 
 pub struct RaderFFT {
@@ -31,21 +33,23 @@ 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 = 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))})
+        let twiddle_factors = (0..(size - 1))
+            .map(|i| {
+                Complex32::cexp(
+                    -2. * PI * direction.sign() * (permutations[i] as f32) / (size as f32),
+                )
+            })
             .collect::<Vec<Complex32>>();
-        convolution_fft.execute(&convolution_operand);
-        convolution_operand = Vec::from(convolution_fft.get_output());
 
+        let mut convolution_fft = create_fft(size - 1, FFTDirection::Forward);
+        convolution_fft.execute(&twiddle_factors);
         RaderFFT {
             permutations,
-            convolution_operand: convolution_operand.into(),
+            convolution_operand: convolution_fft.get_output().iter().copied().collect(),
 
-            //convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
-            convolution_ifft: Box::new(NaiveDFT::create(size - 1, FFTDirection::Inverse)),
+            //convolution_fft,
             convolution_fft,
+            convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
 
             output: vec![Complex32::zero(); size].into(),
             size,
@@ -70,13 +74,16 @@ impl DFTAlgorithm for RaderFFT {
 
         self.convolution_ifft.execute(&self.output);
 
-        self.output[0] = input[0];
+        self.output[0] = Complex32::zero();
+        for x in input {
+            self.output[0] = self.output[0] + *x;
+        }
 
         for i in 0..(self.size - 1) {
             // 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[k] =
+                (self.convolution_ifft.get_output()[i] / (self.size - 1) as f32) + input[0];
         }
     }
 
diff --git a/src/fft/rader2.rs b/src/fft/rader2.rs
index fbcd9d0..f5b90cf 100644
--- a/src/fft/rader2.rs
+++ b/src/fft/rader2.rs
@@ -1,26 +1,29 @@
 // Implementation of raders's fft for prime sized ffts
-/*
 
 use std::f32::consts::PI;
 
 use crate::{
     complex::Complex32,
-    fft::{create_fft, dft::NaiveDFT, is_prime, DFTAlgorithm, FFTDirection},
+    fft::{
+        DFTAlgorithm, FFTDirection, create_fft, dft::NaiveDFT, is_prime, mixed_radix::MixedRadixFFT,
+    },
 };
 
-pub struct RaderFFT {
+pub struct Rader2FFT {
     permutations: Box<[usize]>,
     convolution_operand: Box<[Complex32]>,
 
+    convolution_fft_input: Box<[Complex32]>,
     convolution_ifft: Box<dyn DFTAlgorithm>,
     convolution_fft: Box<dyn DFTAlgorithm>,
 
     output: Box<[Complex32]>,
 
+    sub_size: usize,
     size: usize,
 }
 
-impl DFTAlgorithm for RaderFFT {
+impl DFTAlgorithm for Rader2FFT {
     fn create(size: usize, direction: FFTDirection) -> Self
     where
         Self: Sized,
@@ -30,54 +33,69 @@ impl DFTAlgorithm for RaderFFT {
         // Primitive root and its powers
         let g = compute_prime_primitive_root(size);
         let permutations: Box<[usize]> = (0..(size - 1)).map(|i| exp_mod(g, i + 1, size)).collect();
+        let sub_size = next_pow2(2 * size - 3);
+        println!("{}", sub_size);
 
         // 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))})
+        let twiddle_factors = (0..sub_size)
+            .map(|i| {
+                Complex32::cexp(
+                    -2. * PI * direction.sign() * (permutations[i % (size - 1)] as f32)
+                        / (size as f32),
+                )
+            })
             .collect::<Vec<Complex32>>();
-        convolution_fft.execute(&convolution_operand);
-        convolution_operand = Vec::from(convolution_fft.get_output());
 
-        RaderFFT {
+        let mut convolution_fft = create_fft(sub_size, FFTDirection::Forward);
+        convolution_fft.execute(&twiddle_factors);
+        Rader2FFT {
             permutations,
-            convolution_operand: convolution_operand.into(),
+            convolution_operand: convolution_fft.get_output().iter().copied().collect(),
 
-            convolution_ifft: create_fft(size - 1, FFTDirection::Inverse),
-            //convolution_ifft: Box::new(NaiveDFT::create(size - 1, FFTDirection::Inverse)),
             convolution_fft,
+            convolution_ifft: create_fft(sub_size, FFTDirection::Inverse),
+            convolution_fft_input: vec![Complex32::zero(); sub_size].into(),
 
             output: vec![Complex32::zero(); size].into(),
             size,
+            sub_size,
         }
     }
 
     fn execute(&mut self, input: &[Complex32]) {
         // Compute fft of input signal
-        for i in 0..(self.size - 1) {
+
+        self.convolution_fft_input[0] = input[self.permutations[self.size - 2]];
+        for i in 0..(self.sub_size - self.size + 1) {
+            self.convolution_fft_input[i + 1] = Complex32::zero();
+        }
+        for i in 1..(self.size - 1) {
+            // reverse sequence
             let k = self.permutations[self.size - 1 - i - 1];
-            // Using output as staging buffer
-            self.output[i] = input[k];
+            self.convolution_fft_input[i + self.sub_size - self.size + 1] = input[k];
         }
 
-        self.convolution_fft.execute(&self.output);
+        self.convolution_fft.execute(&self.convolution_fft_input);
 
         // Compute convolution by multiplying in freq domain
-        for i in 0..(self.size - 1) {
+        for i in 0..self.sub_size {
             // Using output as staging buffer
-            self.output[i] = self.convolution_fft.get_output()[i] * self.convolution_operand[i];
+            self.convolution_fft_input[i] =
+                self.convolution_fft.get_output()[i] * self.convolution_operand[i];
         }
 
-        self.convolution_ifft.execute(&self.output);
+        self.convolution_ifft.execute(&self.convolution_fft_input);
 
-        self.output[0] = input[0];
+        self.output[0] = Complex32::zero();
+        for x in input {
+            self.output[0] = self.output[0] + *x;
+        }
 
         for i in 0..(self.size - 1) {
             // 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[k] =
+                (self.convolution_ifft.get_output()[i] / (self.sub_size) as f32) + input[0];
         }
     }
 
@@ -131,4 +149,15 @@ pub fn exp_mod(mut n: usize, mut exp: usize, m: usize) -> usize {
     r
 }
 
-*/
+pub fn next_pow2(mut n: usize) -> usize {
+    if n.count_ones() == 1 {
+        n
+    } else {
+        let mut p = 0;
+        while n > 0 {
+            n >>= 1;
+            p += 1;
+        }
+        1 << p
+    }
+}
diff --git a/src/main.rs b/src/main.rs
index 617385f..7f33b3e 100644
--- a/src/main.rs
+++ b/src/main.rs
@@ -15,11 +15,34 @@ mod nco;
 use bfsk::BFSKMod;
 use complex::Complex;
 use complex::Complex32;
+use fft::DFTAlgorithm;
 use nco::Nco;
 use plotters::prelude::*;
-use fft::DFTAlgorithm;
 
-use crate::{bfsk::BFSKDem, fft::{create_fft, dft::NaiveDFT, mixed_radix::MixedRadixFFT, rader::RaderFFT, radix2::Radix2FFT, windows, FFTDirection, FFT}};
+use crate::{
+    bfsk::BFSKDem,
+    fft::{
+        FFT, FFTDirection, create_fft,
+        dft::NaiveDFT,
+        mixed_radix::MixedRadixFFT,
+        prime_factors,
+        rader::{RaderFFT, compute_prime_primitive_root, exp_mod},
+        rader2::{Rader2FFT, next_pow2},
+        radix2::Radix2FFT,
+        windows,
+    },
+};
+
+struct QuickLCG(i32);
+impl QuickLCG {
+    pub fn seed(val: i32) -> QuickLCG {
+        QuickLCG(val % 10)
+    }
+    pub fn next(&mut self) -> i32 {
+        self.0 = self.0.overflowing_mul(9321).0.overflowing_add(5672).0 % 10;
+        self.0
+    }
+}
 
 // Utilities
 fn map<T>(input: T, in_min: T, in_max: T, out_min: T, out_max: T) -> T
@@ -30,44 +53,14 @@ where
 }
 
 fn main() {
-    //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();
-    }
+    modulate();
+    //œtest();
 }
 
 fn modulate() {
     let sample_rate = 44100;
     let frequency = 2000.0; //HZ
-    let bandwidth = 1000.0; //HZ
+    let bandwidth = 500.0; //HZ
     println!("deviation: {}", PI * (bandwidth / sample_rate as f32));
 
     let path = "s.txt";
@@ -92,7 +85,7 @@ fn modulate() {
     println!("{} samples/bit", sample_rate / baud_rate);
     let mut bfsk = BFSKMod::new(
         sample_rate / baud_rate,
-        PI * 0.05, //PI * (bandwidth / sample_rate as f32),
+        PI * (bandwidth / sample_rate as f32),
         &mut bit_stream,
     );
 
@@ -111,35 +104,33 @@ fn modulate() {
     let mut output_samples = vec![];
     while let Some(sample) = bfsk.step_modulate() {
         let amplitude = i16::MAX as f32;
-        let c_sample = lo.cexp() * sample;
+        let c_sample = sample * lo.cexp();
+        //let c_sample = sample;
 
-        let filtered = prev + (c_sample - prev) * alpha;
-        output_samples.push(filtered);
+        //let filtered = prev + (c_sample - prev) * alpha;
+        output_samples.push(c_sample);
         writer
             .write_sample((amplitude * c_sample.re) as i16)
             .unwrap();
         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.jpg").unwrap();
+
+    let mut fft = FFT::new(110, windows::bartlett);
+    fft.execute(&output_samples[220..]);
+
+    let mut csv = File::create("out.csv").unwrap();
+    for x in fft.get_output() {
+        csv.write_all(format!("{},\n", x.mag()).as_bytes()).unwrap();
     }
 
-    let mut of = File::create("out.txt").unwrap();
-
     let mut bits = vec![];
     let mut lodem = Nco::new(-2. * PI * (frequency / sample_rate as f32));
     let mut demod = BFSKDem::new(
         sample_rate / baud_rate,
-        PI * 0.05, //PI * (bandwidth / sample_rate as f32),
+        PI * (bandwidth / sample_rate as f32),
     );
     for chunk in output_samples.chunks((sample_rate / baud_rate) as usize) {
         let base_chunk: Vec<Complex32> = chunk
@@ -155,14 +146,26 @@ fn modulate() {
     }
 
     for b in bits.chunks(8) {
-        of.write_all(&[(b[0] as u8)
-            | ((b[0] as u8) << 1)
-            | ((b[0] as u8) << 2)
-            | ((b[0] as u8) << 3)
-            | ((b[0] as u8) << 4)
-            | ((b[0] as u8) << 5)
-            | ((b[0] as u8) << 6)
+        /*
+        of.write_all(&[(b[7] as u8)
+            | ((b[6] as u8) << 1)
+            | ((b[5] as u8) << 2)
+            | ((b[4] as u8) << 3)
+            | ((b[3] as u8) << 4)
+            | ((b[2] as u8) << 5)
+            | ((b[1] as u8) << 6)
             | ((b[0] as u8) << 7)])
             .unwrap();
+        */
+
+        of.write_all(&[(b[0] as u8)
+            | ((b[1] as u8) << 1)
+            | ((b[2] as u8) << 2)
+            | ((b[3] as u8) << 3)
+            | ((b[4] as u8) << 4)
+            | ((b[5] as u8) << 5)
+            | ((b[6] as u8) << 6)
+            | ((b[7] as u8) << 7)])
+            .unwrap();
     }
 }