refactor: stage before 0.0.1

matlab/main.m

@@ -2,15 +2,15 @@
 clearvars
 clc
 
-t = readtable("../assets/csv/sna.csv");
+t = readtable("../assets/csv/voice2.csv");
 numRows = height(t);
 outputs = [];
 filterOutputs = [];
 
 for i = 1:numRows
   if t{i, "p_0_out"} == 1
     o = t{i, "axis_upstream_tdata_1_31_16_"};
-    fo = filter_simu_lpx(o);
+    fo = filter_simu(o);
     filterOutputs = [filterOutputs; fo]; %#ok<AGROW>
     outputs = [outputs; o]; %#ok<AGROW>
   end
@@ -22,14 +22,14 @@
 plot(filterOutputs, 'b', 'DisplayName', 'Filtered'); % Creates a line chart with circle markers at data points
 xlabel('Sample Number'); % Assuming each output corresponds to a sample
 ylabel('Filter Output');
-title('Line Chart of filter\_simu Outputs');
+title('滤波后');
 grid on; % Adds a grid to the plot for better readability
 legend show;
 
 subplot(2, 1, 2);
 plot(outputs, 'r', 'DisplayName', 'Original');
 xlabel('Sample Number'); % Assuming each output corresponds to a sample
 ylabel('Filter Output');
-title('Line Chart of original');
+title('滤波前');
 grid on; % Adds a grid to the plot for better readability
 legend show;

python/gcc_phat_debug.py

@@ -3,6 +3,7 @@
 from scipy.fftpack import fft, ifft
 import matplotlib.pyplot as plt
 
+plt.rcParams["font.family"] = "SimSun"
 
 def csv_to_list(csv_file_name: str) -> tuple[list, list]:
     csv_path: str = f"./assets/csv/{csv_file_name}.csv"

python/sin_gen.py

@@ -1,41 +1,38 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-Fs = 1024
+plt.rcParams["font.family"] = "SimSun"
+
+Fs = 4096
 t = np.arange(0, 1, 1 / Fs)
-y = np.sin(30 * t)
+y = np.sin(70 * t) + np.sin(700 * t) + np.sin(7000 * t)
 noise = np.random.randn(len(t))
-noise_intensity = 0.2
+noise_intensity = 0.05
 y_noisy = y + noise_intensity * noise
-y_16bit = np.floor(y_noisy * np.power(2, 14))
+y_16bit = np.floor(y_noisy * np.power(2, 10))
 
 plt.figure()
 
-plt.subplot(221)
+plt.subplot(311)
 plt.plot(y_16bit)
-plt.xlabel("Original signed sine wave")
+plt.title("输入信号", fontsize=12)
 
-y1 = np.fft.fft(y_16bit, 1024)
+y1 = np.fft.fft(y_16bit, 4096)
 
-plt.subplot(222)
+plt.subplot(312)
 plt.plot(y1.real)
-plt.xlabel("FFT of original signed number (Real part)")
+plt.title("FFT 结果 (实部)", fontsize=12)
 
 y_16bit_a = y_16bit.copy()
 
 y_16bit_a[y_16bit_a < 0] += 2**16
 
-plt.subplot(223)
-plt.plot(y_16bit_a)
-plt.xlabel("Sine wave after converting signed number to unsigned number")
-
 y2 = np.fft.fft(y_16bit_a, 1024)
 
-plt.subplot(224)
-plt.plot(y2.real)
-print(y2.real)
-plt.xlabel("FFT after converting to unsigned number (Real part)")
-
-np.savetxt("../assets/txt/sinwave_n2.txt", y_16bit_a, fmt="%d")
+plt.subplot(313)
+plt.plot(y1.imag)
+plt.title("FFT 结果 (虚部)", fontsize=12)
 
+np.savetxt("./assets/txt/sinwave_n2.txt", y_16bit_a, fmt="%d")
+plt.tight_layout()
 plt.show()