#!/usr/bin/python3
from math import sin, cos, pi, sqrt
import plotly.graph_objs as go
from plotly.subplots import make_subplots

from FFT import FFT_real
from FP_trigonometry import *


INP_L = 1024


F_nyquist = INP_L//2





def abs_f(re, im):
  return sqrt(re*re + im*im)
  
  


def DFT_naive(inp, out):
  for f in range(len(out)):
    val_re = 0
    val_im = 0
    for n in range(len(inp)):
      phi = 2*pi*f*n/INP_L
      val_re += inp[n] * sin(phi) /INP_L
      val_im += inp[n] * cos(phi) /INP_L
      
    val_abs = abs_f(val_re, val_im)
    #print("F, val_abs:",f, val_abs)
    out[f] = val_abs




def DFT_naive_FP(inp_float, out):
  inp = [val*FP_acc for val in inp_float]
  for f in range(len(out)):
    val_re = 0
    val_im = 0
    for n in range(len(inp)):
      phi = 2*pi_FP*f*n/INP_L
      phi_sin = sin_FP(phi)
      phi_cos = cos_FP(phi)
      #print(phi, phi_sin, phi_cos)
      val_re += inp[n] * phi_sin /INP_L
      val_im += inp[n] * phi_cos /INP_L
      
    val_abs = abs_FP(val_re, val_im)
    #print("F, val_abs:",f, val_abs)
    out[f] = val_abs
  



  
def FFT_naive(inp, out):
  fft_out = FFT_real(inp)
  for i in range(len(fft_out)):
    val = fft_out[i]/len(inp)
    if (i < len(out)):
      out[i] = val
    else:
      pass
      #out.append(val)

def FFT_tester():
  inp = [-1 + 0.01*i + sin(2*pi*i/10) + cos(2*pi*i/20) + sin(2*pi*i/250) + sin(2*pi*i/2.001) for i in range(INP_L)]
#  inp = [sin(2*pi*i/2.001)for i in range(INP_L)]
  out_DFT = [0 for i in range(F_nyquist + 1)]
  out_FFT = [0 for val in range(F_nyquist + 1)]
  DFT_naive(inp, out_DFT)
  FFT_naive(inp, out_FFT)
  Fourier_error = []
  for a,b in zip(out_FFT, out_DFT):
    Fourier_error.append(a - b)
  chart = make_subplots(rows=3, cols=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(inp))], y=inp, name="inp", mode="markers+lines"), row=1, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(out_DFT))], y=out_DFT, name="out_DFT", mode="markers+lines"), row=2, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(out_FFT))], y=out_FFT, name="out_FFT", mode="markers+lines"), row=2, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(Fourier_error))], y=Fourier_error, name="error", mode="markers+lines"), row=3, col=1)
  chart.update_xaxes(matches="x2", row=3, col=1)
  chart.show()





def DFT_tester():
  inp = [-1 + 0.01*i + sin(2*pi*i/10) + cos(2*pi*i/20) + sin(2*pi*i/250) + sin(2*pi*i/2.001) for i in range(INP_L)]
#  inp = [sin(2*pi*i/2.001)for i in range(INP_L)]
  out_float = [0 for i in range(F_nyquist + 1)]
  out_FP = [0 for val in out_float]
  DFT_naive(inp, out_float)
  DFT_naive_FP(inp, out_FP)
  FP_error = []
  for a,b in zip(out_float, out_FP):
    FP_error.append(a - b/FP_acc)
  chart = make_subplots(rows=3, cols=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(inp))], y=inp, name="inp", mode="markers+lines"), row=1, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(out_float))], y=out_float, name="out_float", mode="markers+lines"), row=2, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(out_FP))], y=[val/FP_acc for val in out_FP], name="out_FP", mode="markers+lines"), row=2, col=1)
  chart.add_trace(go.Scatter(x=[i for i in range(len(out_FP))], y=FP_error, name="FP_error", mode="markers+lines"), row=3, col=1)
  chart.update_xaxes(matches="x2", row=3, col=1)
  chart.show()
  




  
  


if __name__ == "__main__":
  #main()
#  DFT_tester()
  FFT_tester()
  #sin_tester()