implemented FFT wrapper in naive_DFT.py. It imports FFT func from FFT.py and calculates data throw it

FFT.py

@@ -0,0 +1,12 @@
+import numpy as np
+
+
+
+
+def FFT(inp):
+  inp = np.array(inp)
+  out = np.fft.fft(inp)
+  out = [val for val in np.abs(out)]
+  print(out)
+  return out
+

naive_DFT.py

@@ -3,6 +3,8 @@ from math import sin, cos, pi, sqrt
 import plotly.graph_objs as go
 from plotly.subplots import make_subplots
 
+from FFT import FFT
+
 FP_acc = 1e3
 
 INP_L = 1024
@@ -149,20 +151,19 @@ def DFT_naive_FP(inp_float, out):
     print("F, val_abs:",f, val_abs)
     out[f] = val_abs
   
+
+
+
   
 def FFT_naive(inp, out):
-  for f in range(len(out)):
+  fft_out = FFT(inp)
-    val_re = 0
+  for i in range(len(fft_out)):
-    val_im = 0
+    val = fft_out[i]/len(inp)
-    for n in range(len(inp)):
+    if (i < len(out)):
-      phi = 2*pi*f*n/INP_L
+      out[i] = val
-      val_re += inp[n] * sin(phi) /INP_L
+    else:
-      val_im += inp[n] * cos(phi) /INP_L
+      pass
-      
+      #out.append(val)
-    val_abs = abs_f(val_re, val_im)
-    print("F, val_abs:",f, val_abs)
-    out[f] = val_abs
-
 
 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)]