def run(self, conversion): # Uses assembler for speed
if self.popfunc is not None:
self.popfunc(self) # Populate the data (for fwd transfers, just the real data)
if conversion != REVERSE: # Forward transform: real data assumed
setarray(self.im, 0, self._length)# Fast zero imaginary data
if self.windata is not None: # Fast apply the window function
winapply(self.re, self.windata, self._length)
fft(self.ctrl, conversion)
if (conversion & POLAR) == POLAR: # Ignore complex conjugates, convert 1st half of arrays
topolar(self.re, self.im, self._length//2) # Fast
if conversion == DB: # Ignore conjugates: convert 1st half only
for idx, val in enumerate(self.re[0:self._length//2]):
self.re[idx] = -80.0 if val <= 0.0 else 20*math.log10(val) - self.dboffset
def run(self, conversion): # Uses assembler for speed
if self.popfunc is not None:
self.popfunc(self) # Populate the data (for fwd transfers, just the real data)
if conversion != REVERSE: # Forward transform: real data assumed
setarray(self.im, 0, self._length)# Fast zero imaginary data
if self.windata is not None: # Fast apply the window function
winapply(self.re, self.windata, self._length)
start = utime.ticks_us()
fft(self.ctrl, conversion)
delta = utime.ticks_diff(utime.ticks_us(), start)
if (conversion & POLAR) == POLAR: # Ignore complex conjugates, convert 1st half of arrays
topolar(self.re, self.im, self._length//2) # Fast
if conversion == DB: # Ignore conjugates: convert 1st half only
for idx, val in enumerate(self.re[0:self._length//2]):
self.re[idx] = -80.0 if val <= 0.0 else 20*math.log10(val) - self.dboffset
return delta
def INT_TEST():
print('INT TEST:\n\n')
#signal x
x = []
#making signal a sine wave
amount = 8
n = 0
inkrement = 1
i = 0
for i in range(amount):
x.append(n)
n = n + inkrement
N = len(x)
#Diskrete-Fourier-Transformation
X = around(dft(x), decimals=6)
print('Diskrete-Fourier-Transformation:')
print(f'X = {X}\n')
#amplitude and phase
A = [None] * N
p = [None] * N
i = 0
for i in range(len(X)):
temp1 = abs(X[i])
A[i] = temp1
temp2 = angle(X[i])
p[i] = temp2
#print(p[i])
print(f'Amplitude: A = {A}')
print(f'Phase: p = {p}\n\n')
#Fast-Fourier-Transformation
X2 = around(fft(x), decimals=6)
print('Fast-Fourier-Transformation:')
print(f'X2 = {X2}\n')
#amplitude and phase
A2 = [None] * N
p2 = [None] * N
i = 0
for i in range(len(X2)):
temp1 = abs(X2[i])
A2[i] = temp1
temp2 = angle(X[i])
p2[i] = temp2
print(f'Amplitude: A2 = {A2}')
print(f'Phase: p2 = {p2}\n\n\n')
plt.plot(x, X, max(x))
def AC_TEST():
print('AC TEST:\n\n')
#signal x
x = []
#making signal a sine wave
amount = 8
n = 0
inkrement = 2 * pi / amount
i = 0
for i in range(amount):
x.append(sin(n) * 5)
n = n + inkrement
N = len(x)
#original signal
print(f'signal: x = {x}\n\n')
#if my ouput is the same it highly possible that is correct
#try out yourself with the file ProofItWorks.m
print('Octave(Matlab)-Output:')
print(
'fft = 0.00000 + 0.00000i -0.00000 - 20.00000i 0.00000 - 0.00000i 0.00000 - 0.00000i 0.00000 + 0.00000i 0.00000 + 0.00000i 0.00000 + 0.00000i -0.00000 + 20.00000i\n'
)
print(
'fft(Amplitude) = 1.6823e-16 2.0000e+01 1.4662e-15 1.7764e-15 1.0564e-15 1.7764e-15 1.4662e-15 2.0000e+01'
)
print(
'fft(Phase) = 0.00000 -1.57080 -1.13998 -1.56195 0.00000 1.56195 1.13998 1.57080\nthe phase is actually false\n\n'
)
#you can also try numpy fft.fft()
NUMPYFFT = around(npfft.fft(x), decimals=6)
print(f'NumpyFFT = {NUMPYFFT}\n')
print(f'Amplitude = {around(abs(NUMPYFFT), decimals=6)}')
print(f'Phase = {around(npangle(NUMPYFFT), decimals=6)}\n\n')
#Diskrete-Fourier-Transformation
X = around(dft(x), decimals=6)
print('Diskrete-Fourier-Transformation:')
print(f'X = {X}\n')
#amplitude and phase
A = [None] * N
p = [None] * N
i = 0
for i in range(len(X)):
temp1 = abs(X[i])
A[i] = temp1
temp2 = angle(X[i])
p[i] = temp2
#print(p[i])
print(f'Amplitude: A = {A}')
print(f'Phase: p = {p}\n\n')
#Fast-Fourier-Transformation
X2 = around(fft(x), decimals=6)
print('Fast-Fourier-Transformation:')
print(f'X2 = {X2}\n')
#amplitude and phase
A2 = [None] * N
p2 = [None] * N
i = 0
for i in range(len(X2)):
temp1 = abs(X2[i])
A2[i] = temp1
temp2 = angle(X[i])
p2[i] = temp2
print(f'Amplitude: A2 = {A2}')
print(f'Phase: p2 = {p2}\n\n\n')
plt.plot(x, X, max(x))
def DC_TEST():
print('DC TEST:\n\n')
#signal x
x = []
#making a dc signal with 5V here
amount = 8
n = 0
inkrement = 2 * pi / amount
i = 0
for i in range(amount):
x.append(5)
n = n + inkrement
N = len(x)
#original signal
print(f'signal: x = {x}\n\n')
#if my ouput is the same it highly possible that is correct
NUMPYFFT = around(npfft.fft(x), decimals=6)
print(f'NumpyFFT = {NUMPYFFT}\n')
print(f'Amplitude = {around(abs(NUMPYFFT), decimals=6)}')
print(f'Phase = {around(npangle(NUMPYFFT), decimals=6)}\n\n')
#Diskrete-Fourier-Transformation
X = around(dft(x), decimals=6)
print('Diskrete-Fourier-Transformation:')
print(f'X = {X}\n')
#amplitude and phase
A = [None] * N
p = [None] * N
i = 0
for i in range(len(X)):
temp1 = abs(X[i])
A[i] = temp1
temp2 = angle(X[i])
p[i] = temp2
print(f'Amplitude: A = {A}')
print(f'Phase: p = {p}\n\n')
#Fast-Fourier-Transformation
X2 = around(fft(x), decimals=6)
print('Fast-Fourier-Transformation:')
print(f'X2 = {X2}\n')
#amplitude and phase
A2 = [None] * N
p2 = [None] * N
i = 0
for i in range(len(X2)):
temp1 = abs(X2[i])
A2[i] = temp1
temp2 = angle(X[i])
p2[i] = temp2
print(f'Amplitude: A2 = {A2}')
print(f'Phase: p2 = {p2}\n\n\n')
plt.plot(x, X, max(x))
def call_fft ( signal ) :
dft.fft ( signal )