moved python3 prototyping to the python folder

python/naive_DFT.py

@@ -0,0 +1,124 @@
+#!/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()