mirror of
https://github.com/radio95-rnt/rds95.git
synced 2026-02-26 20:33:53 +01:00
will this work?
This commit is contained in:
53
gen_wave.py
53
gen_wave.py
@@ -7,7 +7,7 @@ if PLOT: import matplotlib.pyplot as plt
|
||||
if FFT: import numpy as np
|
||||
|
||||
DATA_RATE = 1187.5
|
||||
SIZE_RATIO = 2
|
||||
SIZE_RATIO = 1
|
||||
|
||||
ratio = 16
|
||||
sample_rate = DATA_RATE*ratio
|
||||
@@ -23,17 +23,12 @@ def rrcosfilter(NumSamples):
|
||||
|
||||
for x in sample_num:
|
||||
t = (x-NumSamples/2)*T_delta
|
||||
if t == 0.0:
|
||||
h_rrc[x] = 1.0 - 1 + (4/math.pi)
|
||||
elif t == SymbolPeriod/4:
|
||||
h_rrc[x] = (1/math.sqrt(2))*(((1+2/math.pi)* \
|
||||
(math.sin(math.pi/4))) + ((1-2/math.pi)*(math.cos(math.pi/4))))
|
||||
elif t == -SymbolPeriod/4:
|
||||
h_rrc[x] = (1/math.sqrt(2))*(((1+2/math.pi)* \
|
||||
(math.sin(math.pi/4))) + ((1-2/math.pi)*(math.cos(math.pi/4))))
|
||||
else:
|
||||
h_rrc[x] = (4*(t/SymbolPeriod)*math.cos(math.pi*t*2/SymbolPeriod))/ \
|
||||
(math.pi*t*(1-(4*t/SymbolPeriod)*(4*t/SymbolPeriod))/SymbolPeriod)
|
||||
if t == 0.0: h_rrc[x] = 1.0 - 1 + (4/math.pi)
|
||||
elif t == SymbolPeriod/4: h_rrc[x] = (1/math.sqrt(2))*(((1+2/math.pi) * (math.sin(math.pi/4))) + ((1-2/math.pi)*(math.cos(math.pi/4))))
|
||||
elif t == -SymbolPeriod/4: h_rrc[x] = (1/math.sqrt(2))*(((1+2/math.pi) * (math.sin(math.pi/4))) + ((1-2/math.pi)*(math.cos(math.pi/4))))
|
||||
else: h_rrc[x] = (4*(t/SymbolPeriod)*math.cos(math.pi*t*2/SymbolPeriod)) / (math.pi*t*(1-(4*t/SymbolPeriod)*(4*t/SymbolPeriod))/SymbolPeriod)
|
||||
blackman = [0.42 + 0.5*math.cos(math.pi*i/(NumSamples-1)) + 0.08*math.cos(2.0*math.pi*i/(NumSamples-1)) for i in range(NumSamples)]
|
||||
h_rrc = [h_rrc[i] * blackman[i] for i in range(NumSamples)]
|
||||
|
||||
return h_rrc
|
||||
|
||||
@@ -63,36 +58,14 @@ outc.write(header)
|
||||
outh.write(header)
|
||||
|
||||
def generate():
|
||||
l = ratio // 2
|
||||
|
||||
sample = [0.0] * (16*l)
|
||||
sample[l] = 1
|
||||
sample[2*l] = -1
|
||||
|
||||
sf = rrcosfilter(l*16)
|
||||
shapedSamples = convolve(sample, sf)
|
||||
|
||||
lowest = 0
|
||||
lowest_idx = 0
|
||||
highest = 0
|
||||
highest_idx = 0
|
||||
for i,j in enumerate(shapedSamples):
|
||||
if j < lowest:
|
||||
lowest = j
|
||||
lowest_idx = i
|
||||
if j > highest:
|
||||
highest = j
|
||||
highest_idx = i
|
||||
middle = int((lowest_idx+highest_idx)/2)
|
||||
|
||||
out = shapedSamples[middle-int(ratio*SIZE_RATIO):middle+int(ratio*SIZE_RATIO)]
|
||||
out = [2 * (i - min(out)) / (max(out) - min(out)) - 1 for i in out]
|
||||
if max(out) > 1 or min(out) < -1: raise Exception("Clipped")
|
||||
print(f"{len(out)=} {len(out)/sample_rate=} {(len(out)/sample_rate)/(1/DATA_RATE)=} {1/DATA_RATE=}")
|
||||
t = [i / sample_rate for i in range(ratio)]
|
||||
out = [math.sin(2 * math.pi * DATA_RATE * time) for time in t]
|
||||
print(f"{len(out)=} {len(out)/sample_rate=} {1/DATA_RATE=}")
|
||||
|
||||
if PLOT:
|
||||
plt.plot(out, label="out")
|
||||
plt.plot(out*4, label="out")
|
||||
plt.legend()
|
||||
plt.axvline(x=len(out)*2, color='r', linestyle='--', label='center')
|
||||
plt.grid(True)
|
||||
plt.show()
|
||||
|
||||
@@ -103,7 +76,7 @@ def generate():
|
||||
|
||||
plt.figure(figsize=(10, 6))
|
||||
plt.plot(fft_freqs[:N//2], np.abs(fft_out)[:N//2])
|
||||
plt.xlim(0,DATA_RATE*3)
|
||||
plt.xlim(0,DATA_RATE*2.5)
|
||||
plt.title("FFT of the waveform")
|
||||
plt.xlabel("Frequency (Hz)")
|
||||
plt.ylabel("Magnitude")
|
||||
|
||||
Reference in New Issue
Block a user