commit 7ee950b2c5842be131ea018a9b5f68ab8db20d29
Author: Brandon4466 <spongebob.brandon@gmail.com>
Date:   Sun Jan 14 23:41:53 2024 -0800

    main application with tuning, playing, and GUI

diff --git a/.vscode/settings.json b/.vscode/settings.json
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+++ b/.vscode/settings.json
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+{
+    "python.languageServer": "Pylance",
+    "python.linting.pylintEnabled": false,
+    "python.analysis.diagnosticSeverityOverrides": {
+        "reportMissingModuleSource": "none"
+    },
+    "python.analysis.extraPaths": [
+        "",
+        "c:\\Users\\spong\\.vscode\\extensions\\joedevivo.vscode-circuitpython-0.1.20-win32-x64\\stubs",
+        "c:\\Users\\spong\\AppData\\Roaming\\Code\\User\\globalStorage\\joedevivo.vscode-circuitpython\\bundle\\20240113\\adafruit-circuitpython-bundle-py-20240113\\lib"
+    ],
+    "circuitpython.board.version": null
+}
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diff --git a/_detectsong.py b/_detectsong.py
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+++ b/_detectsong.py
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+import sounddevice as sd
+import numpy as np
+import time
+import asyncio
+from shazamio import Shazam
+
+def rec():
+    recording = sd.rec((44100 * 5), samplerate=44100, channels=1, detype=np.int16)
+    sd.wait()
+    return recording
+
+async def detect():
+    recording = rec()
+    shazam = Shazam()
+    out = await shazam.recognize_song(recording)
+    print(out)
+
+loop = asyncio.get_event_loop()
+loop.run_until_complete(detect())
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diff --git a/filtered_audio.wav b/filtered_audio.wav
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diff --git a/fm_capture.bin b/fm_capture.bin
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diff --git a/fm_capture5.bin b/fm_capture5.bin
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diff --git a/fm_capture6.bin b/fm_capture6.bin
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diff --git a/fm_data.raw b/fm_data.raw
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diff --git a/fm_data_test.wav b/fm_data_test.wav
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diff --git a/fm_data_test1.raw b/fm_data_test1.raw
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diff --git a/fm_rewind.wav b/fm_rewind.wav
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diff --git a/fmdemod.py b/fmdemod.py
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+++ b/fmdemod.py
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+from pydub import AudioSegment
+from pydub.effects import low_pass_filter
+from pydub.playback import play
+import sounddevice as sd
+import numpy as np
+
+# Input file path
+input_file = "fm_data.raw"
+
+# Load the audio file
+audio = AudioSegment.from_file(input_file, format="raw", sample_width=2, channels=1, frame_rate=170000)
+
+# Apply low pass filter (if needed)
+audio = low_pass_filter(audio, 75000)
+
+play(audio)
+
+# Convert to numpy array
+# samples = np.array(audio.get_array_of_samples())
+
+# # Play the audio using sounddevice
+# sd.play(samples, samplerate=audio.frame_rate)
+# sd.wait()
+
+# audio.export("fm_data.wav", format="wav")
+
+# rx_fm -f 94.7M -M fm -s 170k -A fast -l 0 -E deemp -d driver=hackrf fm_data.raw
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diff --git a/fmdemod2.py b/fmdemod2.py
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+++ b/fmdemod2.py
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+import numpy as np
+import matplotlib.pylab as plt
+import time
+
+# inspired by https://github.com/osmocom/rtl-sdr/blob/master/src/rtl_fm.c
+
+
+# loading in the .wav
+signal = np.memmap("HackRF_20240111_025820Z_94700kHz_IQ.wav", offset=44)
+
+result = np.zeros(len(signal)//2, dtype=np.cfloat)
+
+downsample = 128
+
+
+def low_pass(signal):
+    # simple square window FIR
+
+    lowpassed = signal[:]
+
+    # needs to be go outside this function
+    now_r = 0
+    now_j = 0
+
+    i=0
+    i2=0
+
+    prev_index = 0
+
+    while (i < len(lowpassed)):
+        now_r += lowpassed[i]
+        now_j += lowpassed[i + 1]
+        i += 2
+
+        prev_index += 2
+
+        if (prev_index < downsample):
+            continue
+
+        lowpassed[i2]     = now_r
+        lowpassed[i2 + 1] = now_j
+        prev_index = 0
+        now_r = 0
+        now_j = 0
+        i2 += 2
+
+    lp_len = i2
+
+    return lowpassed
+
+def multiply(ar, aj, br, bj):
+    cr = ar * br - aj * bj
+    cj = aj * br + ar * bj
+    return cr, cj
+
+def polar_discriminant(ar, aj, br, bj):
+    cr , cj = multiply(ar, aj, br, -bj)
+    #print(cr, cj)
+    angle = np.arctan2(cj, cr)
+    #print("angle", angle)
+    # return (angle / np.pi * (1<<14))
+    return (angle * 180.0 / np.pi)
+
+def fm_demod(signal, result):
+    pre_r = 0
+    pre_j = 0
+
+    i = 0
+    pcm = 0
+
+    lp_len = len(signal)
+
+    # low-passing
+    lp = low_pass(signal)
+    #print(lp[0], lp[1], pre_r, pre_j)
+
+    pcm = polar_discriminant(lp[0], lp[1], pre_r, pre_j)
+    result[0] = pcm
+
+    for i in range(2, lp_len-1, 2):
+        # being lazy, only case 0 for now...
+
+        # case 0
+        pcm = polar_discriminant(lp[i], lp[i + 1], lp[i - 2], lp[i - 1])
+
+        result[i // 2] = pcm
+
+    pre_r = lp[lp_len - 2]
+    pre_j = lp[lp_len - 1]
+    result_len = lp_len // 2
+
+    #return(result)
+
+
+time1 = time.time()
+signal = -127.5 + signal
+
+fm_demod(signal, result)
+
+print(time.time() - time1)
+
+plt.plot(result[::10])
+plt.show()
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diff --git a/fmdemod3.py b/fmdemod3.py
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+++ b/fmdemod3.py
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+import numpy as np
+import sounddevice as sd
+from scipy.io import wavfile
+from scipy.signal import decimate, butter, filtfilt
+
+# Load the raw IQ samples from the file
+filename = "fm_capture6.bin"
+iq_samples = np.fromfile(filename, dtype=np.int8)
+
+# Define the FM demodulation parameters
+sample_rate = int(2e6)  # Sample rate of the IQ samples
+audio_sample_rate = int(48e3)  # Desired audio sample rate
+fm_deviation = int(75e3)  # FM deviation of the radio signal
+channel_width = int(200e3)  # Channel width of the low-pass filter
+
+# Design the low-pass filter
+nyquist_freq = sample_rate / 2
+cutoff_freq = channel_width / nyquist_freq
+b, a = butter(10, int(75e3), btype='low', fs=int(2e6))
+
+# Apply the low-pass filter
+filtered_audio = filtfilt(b, a, iq_samples)
+
+# Demodulate the FM signal
+demodulated_audio = np.diff(filtered_audio.astype(np.float32)) * np.conj(filtered_audio[:-1]).astype(np.float32)
+demodulated_audio = decimate(demodulated_audio, int(100))
+
+# Normalize the audio to the range [-1, 1]
+normalized_audio = demodulated_audio / np.max(np.abs(demodulated_audio))
+
+# Play the audio
+sd.play(normalized_audio, audio_sample_rate)
+sd.wait()
+
+# output_filename = "demodulated_audio.wav"
+# wavfile.write(output_filename, audio_sample_rate, normalized_audio)
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diff --git a/fmdemod_old.py b/fmdemod_old.py
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+++ b/fmdemod_old.py
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+import numpy as np
+import scipy.signal
+import wave
+
+def read_raw_iq_samples(file_path):
+    with open(file_path, 'rb') as file:
+        raw_data = file.read()
+    iq_samples = np.frombuffer(raw_data, dtype=np.int8)
+    return iq_samples
+
+def fm_demodulation(iq_samples, sample_rate, fm_deviation=75e3):
+    # Hilbert transform for FM demodulation
+    analytic_signal = scipy.signal.hilbert(iq_samples)
+    instantaneous_phase = np.unwrap(np.angle(analytic_signal))
+    demodulated_signal = np.unwrap(np.angle(iq_samples[1:] * np.conj(iq_samples[:-1]))) / (2.0 * np.pi * 1.0/sample_rate * fm_deviation)
+    return demodulated_signal
+
+def decimate_audio(signal, decimation_factor):
+    return scipy.signal.resample(signal, len(signal)//decimation_factor)
+
+def low_pass_filter(signal, cutoff_frequency, sample_rate):
+    nyquist = 0.5 * sample_rate
+    normal_cutoff = cutoff_frequency / nyquist
+    b, a = scipy.signal.butter(6, normal_cutoff, btype='low', analog=False)
+    filtered_signal = scipy.signal.filtfilt(b, a, signal)
+    return filtered_signal
+
+def save_wav_file(signal, sample_rate, output_file):
+    scaled_signal = np.int16(signal / np.max(np.abs(signal)) * 32767)
+    with wave.open(output_file, 'wb') as wav_file:
+        wav_file.setnchannels(1)
+        wav_file.setsampwidth(2)
+        wav_file.setframerate(sample_rate)
+        wav_file.writeframes(scaled_signal.tobytes())
+
+def main(input_file, output_file, sample_rate, channel_width, decimation_factor=10, cutoff_frequency=75e3):
+    iq_samples = read_raw_iq_samples(input_file)
+    demodulated_signal = fm_demodulation(iq_samples, sample_rate)
+    decimated_signal = decimate_audio(demodulated_signal, decimation_factor)
+    filtered_signal = low_pass_filter(decimated_signal, cutoff_frequency, sample_rate/decimation_factor)
+    new_sample_rate = sample_rate / decimation_factor
+    save_wav_file(filtered_signal, new_sample_rate, output_file)
+
+if __name__ == "__main__":
+    input_file_path = "fm_capture.bin"
+    output_wav_path = "output.wav"
+    sample_rate = 2e6  # Replace with the actual sample rate of your FM stream
+    channel_width = 200e3  # Replace with the channel width of your FM signal
+
+    main(input_file_path, output_wav_path, sample_rate, channel_width)
diff --git a/fmplay.py b/fmplay.py
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+++ b/fmplay.py
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+import subprocess
+from time import sleep
+import tkinter as ttk
+import _detectsong as ds
+
+root = ttk.Tk()
+root.title("Radio Controller")
+# root.geometry("1280x400")
+root.geometry("800x400")
+root.attributes("-topmost", True)
+# sv_ttk.use_dark_theme()
+
+st1_button = ttk.Button(root, text="94.7M", borderwidth=0, command=lambda: tune(94.7))
+st2_button = ttk.Button(root, text="96.9M", borderwidth=0, command=lambda: tune(96.9))
+st3_button = ttk.Button(root, text="98.5M", borderwidth=0, command=lambda: tune(98.5))
+st4_button = ttk.Button(root, text="100.5M", borderwidth=0, command=lambda: tune(100.5))
+st5_button = ttk.Button(root, text="101.1M", borderwidth=0, command=lambda: tune(101.1))
+st6_button = ttk.Button(root, text="102.5M", borderwidth=0, command=lambda: tune(102.5))
+st7_button = ttk.Button(root, text="103.5M", borderwidth=0, command=lambda: tune(103.5))
+st8_button = ttk.Button(root, text="106.5M", borderwidth=0, command=lambda: tune(106.5))
+st9_button = ttk.Button(root, text="107.9M", borderwidth=0, command=lambda: tune(107.9))
+
+exit_button = ttk.Button(root, text="Exit", command=lambda: on_close(True))
+volume_slider = ttk.Scale(root, from_=0, to=100, orient=ttk.HORIZONTAL)
+stop_button = ttk.Button(root, text="Stop", command=lambda: on_close())
+
+# root.protocol("WM_DELETE_WINDOW", lambda e: on_close())
+
+st1_button.grid(row=0, column=0)
+st2_button.grid(row=0, column=1)
+st3_button.grid(row=0, column=2)
+st4_button.grid(row=0, column=3)
+st5_button.grid(row=0, column=4)
+st6_button.grid(row=0, column=5)
+st7_button.grid(row=0, column=6)
+st8_button.grid(row=0, column=7)
+st9_button.grid(row=0, column=8)
+
+exit_button.grid(row=1, column=0)
+volume_slider.grid(row=1, column=1, columnspan=3)
+stop_button.grid(row=1, column=4)
+
+# Input file path
+input_file = "fm_data.raw"
+
+tuner = None
+player = None
+
+def tune(station):
+    global tuner
+    global player
+    # random_num = random.randint(0, 1000000)
+    # print(random_num)
+    if tuner is not None:
+        tuner.kill()
+        sleep(3)
+    if player is not None:
+        player.kill()
+    tuner = subprocess.Popen(["rx_fm", "-f", f"{station}M", "-M", "fm", "-s", "170k", "-A", "fast", "-l", "0", "-E", "deemp", "-E", "wav", "-d", "driver=hackrf", input_file])
+    sleep(2.5)
+    player = subprocess.Popen(["C:\\Program Files\\VideoLAN\\VLC\\vlc", "--play-and-exit", "C:\\Users\\spong\\Documents\\Python Programs\\PySDR\\FM Radio\\fm_data.raw"])
+
+def on_close(halt=False):
+    if tuner:
+        tuner.kill()
+    if player:
+        player.kill()
+    if halt == True:
+        exit()
+
+def adj_vol():
+    pass
+
+try:
+    root.mainloop()
+except KeyboardInterrupt:
+    on_close()
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diff --git a/main.py b/main.py
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+++ b/main.py
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+import numpy as np
+import matplotlib.pyplot as plt
+from pysdr import IQFileSource
+from pysdr import FMReceiver
+from hackrf import HackRfSource
+
+# Set the HackRF parameters
+sample_rate = 2e6  # 2 MHz sample rate
+center_freq = 100e6  # 100 MHz center frequency
+
+# Set the FM receiver parameters
+audio_sample_rate = 48e3  # 48 kHz audio sample rate
+fm_deviation = 75e3  # FM deviation (typical for broadcast FM)
+
+# Create HackRF source
+hackrf_source = HackRfSource(sample_rate, center_freq)
+
+# Create IQ file source
+iq_file_source = IQFileSource('fm_radio.iq', sample_rate)
+
+# Create FM receiver
+fm_receiver = FMReceiver(sample_rate, audio_sample_rate, fm_deviation)
+
+# Read samples from the source and process them
+try:
+    while True:
+        samples = hackrf_source.read_samples(1024)
+        if len(samples) == 0:
+            break
+
+        # Process the samples using the FM receiver
+        audio_samples = fm_receiver.process(samples)
+
+        # Do something with the audio samples (e.g., play them)
+        # For simplicity, let's just plot the spectrum
+        plt.specgram(audio_samples, Fs=audio_sample_rate, cmap='viridis')
+        plt.xlabel('Time (s)')
+        plt.ylabel('Frequency (Hz)')
+        plt.title('FM Radio Spectrum')
+        plt.show()
+
+except KeyboardInterrupt:
+    pass
+
+finally:
+    # Close the HackRF source
+    hackrf_source.close()
diff --git a/output55.wav b/output55.wav
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diff --git a/output55.zip b/output55.zip
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diff --git a/output66.wav b/output66.wav
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diff --git a/test_vlc.py b/test_vlc.py
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+++ b/test_vlc.py
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+import vlc
+import time
+
+instance = vlc.Instance('--no-xlib')
+
+player = instance.media_player_new()
+
+media = instance.media_new('C:\\Users\\spong\\Documents\\Python Programs\\PySDR\\FM Radio\\fm_data.raw')
+player.set_media(media)
+
+player.play()
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diff --git a/todo.txt b/todo.txt
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+++ b/todo.txt
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+implement volume slider to control the VLC volume.
+
+put stop button in
+
+get a 10 second slice of audio and use shazamio to get the song name etc
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