test-Ordner eingefügt

simulation/test/helper.py

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+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import signal
+import pandas as pd
+
+def get_psd(data, fs, bin_width):
+    f, psd = signal.welch(data, 
+                          fs=fs, 
+                          nperseg=fs/bin_width,
+                          window='hann',
+                          axis=0
+                         )
+ 
+    return f[1:], psd[1:] #drop the first value because it makes the plots look bad and is effectively 0
+
+
+def setup_timeplot(figsize=(11, 6), plot_coeffs=False):
+    global plot1, line1, plot2, line2, plot3, line3, plot4
+    # time domain plot
+    cols = 1
+    rows = 4
+    plt.figure(0, figsize=figsize)
+    plt.clf()
+    
+    plot1 = plt.subplot2grid( (rows, cols), (0,0), 1)
+    line1 = plot1.plot([0], label="mic")
+    plt.legend()
+    plot2 = plt.subplot2grid((rows,cols),(1,0), sharex=plot1)
+    line2 = plot2.plot([0], label="acc")
+    plt.legend()
+    plot3 = plt.subplot2grid((rows, cols), (2,0), sharex=plot1)
+    line3 = plot3.plot([0], label="out")
+    plt.legend()
+    
+    if plot_coeffs:
+        plot4 = plt.subplot2grid( (rows, cols), (3,0), sharex=plot1, rowspan=3)
+        plt.legend(loc='upper right')
+    
+    plt.xlabel("sample")
+    plt.tight_layout()
+    plt.show()
+
+
+def setup_freqplot(figsize=(11, 6)):
+    global plot_freq, line_freq1, line_freq2, line_freq3
+    cols = 1
+    rows = 1
+    # frequency domain plot
+    plt.figure(1, figsize=figsize)
+    plt.clf()
+    plt.title("Power spectrum")
+    plot_freq = plt.subplot2grid( (rows, cols), (0,0), 1)
+    line_freq1 = plot_freq.loglog([0], label="mic")
+    line_freq2 = plot_freq.loglog([0], label="acc")
+    line_freq3 = plot_freq.loglog([0], label="out")
+    plt.xlabel("frequency / Hz")
+    plt.ylabel("dB²/Hz")
+    plt.legend()
+    plt.tight_layout()
+    plt.show()
+
+
+def plot_freqdomain(fs, ch1, ch2, output):
+
+    x_min = []
+    x_max = []
+    y_min = []
+    y_max = []
+
+    f, psd = get_psd(ch1, fs, 10)
+    x_min.append(min(f))
+    x_max.append(max(f))
+    y_min.append(min(psd))
+    y_max.append(max(psd))
+    line_freq1[0].set_data(f, psd)
+
+    f, psd = get_psd(ch2, fs, 10)
+    x_min.append(min(f))
+    x_max.append(max(f))
+    y_min.append(min(psd))
+    y_max.append(max(psd))
+    line_freq2[0].set_data(f, psd)
+
+    f, psd = get_psd(output, fs, 10)
+    x_min.append(min(f))
+    x_max.append(max(f))
+    y_min.append(min(psd))
+    y_max.append(max(psd))
+    line_freq3[0].set_data(f, psd)
+
+    plot_freq.set_xlim(min(x_min), max(x_max))
+    plot_freq.set_ylim(min(y_min), max(y_max))
+
+
+def plot_timedomain(ch1, ch2, output, coeffs: pd.DataFrame =None):
+    #Plot the result
+    data= output
+    line3[0].set_data(range(len(data)), data)
+    plot3.set_xlim(0, len(data))
+    plot3.set_ylim(np.min(data), np.max(data))
+
+    # plot the chirp with noise
+    data = ch1
+    line1[0].set_data(range(len(data)), data)
+    plot1.set_xlim(0, len(data))
+    plot1.set_ylim(min(data), max(data))
+
+    # Plot the noise
+    data = ch2
+    line2[0].set_data(range(len(data)), data)
+    plot2.set_xlim(0, len(data))
+    plot2.set_ylim(min(data), max(data))
+
+    # Plot the coeffs
+    if coeffs is not None:
+        data = coeffs
+        coeffs.plot(ax=plot4)
+        #plot4.legend(bbox_to_anchor=(1.2, 1.05))
+         
+        #line4 = plot4.plot([0], label="coeffs")
+        #line4[0].set_data(range(len(data)), data)
+        
+        #plot4.set_xlim(0, len(data))
+        #plot4.set_ylim(min(data), max(data))