Beginners • Raspberry Pico, MAX7819, Micropython based Spectrum Visualizer

Code:

from machine import ADC, Pin, SPIimport timeimport mathimport arrayimport max7219# SPI setup for the LED matrix displayspi = SPI(0, baudrate=115200, polarity=0, phase=0, sck=Pin(18), mosi=Pin(19))cs = Pin(15, Pin.OUT)  # Chip Select for SPI# Initialize the displaynum_matrices = 4matrix = max7219.Matrix8x8(spi, cs, num_matrices)# Clear the displaymatrix.fill(0)matrix.show()# Configure the analog pin (let's use ADC0 which is GP26 on the Pico)# Input audio signal from 20 to 20.000 hz, 2.50v# Coupled with a 10uF capacitoradc = ADC(Pin(26))# Desired sampling rate (samples per second)sampling_rate = 48000  # 48 kHz# Calculate the delay between samples (in microseconds)sample_interval_us = int(1e6 / sampling_rate)  # Convert to microseconds# Function to sample the audio signaldef sample_audio(samples=128):    audio_samples = array.array('H')  # Use array for memory efficiency    for _ in range(samples):        audio_samples.append(adc.read_u16())  # Read the analog value (0-65535)        time.sleep_us(sample_interval_us)  # Delay between samples    return audio_samples# Apply Hamming window to the samplesdef apply_window(samples):    windowed_samples = []    for i in range(len(samples)):        windowed_samples.append(samples[i] * (0.54 - 0.46 * math.cos(2 * math.pi * i / (len(samples) - 1))))    return windowed_samples# Perform FFTdef fft(samples):    N = len(samples)    levels = int(math.log2(N))    # Bit-reversal permutation    def bit_reverse(n, bits):        reversed = 0        for _ in range(bits):            reversed = (reversed << 1) | (n & 1)            n >>= 1        return reversed    indices = [bit_reverse(i, levels) for i in range(N)]    sorted_samples = [samples[i] for i in indices]    # Cooley-Tukey FFT    m = 2    while m <= N:        omega_m = math.e ** (-2j * math.pi / m)        for k in range(0, N, m):            omega = 1            for j in range(m // 2):                t = omega * sorted_samples[k + j + m // 2]                u = sorted_samples[k + j]                sorted_samples[k + j] = u + t                sorted_samples[k + j + m // 2] = u - t                omega *= omega_m        m *= 2    return sorted_samples# Function to get the intensity at specific frequenciesdef get_intensity_at_frequencies(fft_result, frequencies, sample_rate, num_samples):    columnIndex = 1    intensity_list = []    for freq in frequencies:        index = int(freq * num_samples / sample_rate)        if index < len(fft_result):            magnitude = abs(fft_result[index])            print(f"freq: {freq} mag: {magnitude}")            intensity_list.append((columnIndex, freq, magnitude))        else:            intensity_list.append((columnIndex, freq, -1))        columnIndex += 1    return intensity_list# Normalize intensity to range 0 to 8def normalize_intensity(intensity_list, max_intensity=2318515, max_value=8):    if max_intensity == 0:        return [(freq, 0) for _, freq, _ in intensity_list]  # Avoid division by zero    normalized_intensity = []    for columnIndex, freq, magnitude in intensity_list:        normalized_magnitude = int((magnitude / max_intensity) * max_value)        normalized_intensity.append((columnIndex, freq, normalized_magnitude))    return normalized_intensity# Frequencies to inspectfrequencies = [30, 60, 125, 250, 375, 500, 750, 1000, 1500, 2000, 3000, 4000, 6000, 8000, 12000, 16000, 20000]# Function to display intensities on the LED matricesdef display_intensities(intensity_list):    matrix.fill(0)  # Clear the display    for columnIndex, freq, value in intensity_list:        print(f"Column: {columnIndex}, Frequency: {freq}, Intensity: {value}")        for row in range(value):            matrix.pixel(columnIndex, 7 - row, 1)  # Turn on the LED    matrix.show()# Main loopwhile True:    audio_samples = sample_audio()    windowed_samples = apply_window(audio_samples)    fft_result = fft(windowed_samples)    intensity = get_intensity_at_frequencies(fft_result, frequencies, sampling_rate, len(windowed_samples))    normalized_intensity = normalize_intensity(intensity)    display_intensities(normalized_intensity)    #time.sleep(0.1)