Added done Work

2.py

@@ -0,0 +1,101 @@
+import plot_lib
+import read_file
+import editing_data
+import matplotlib
+import matplotlib.pyplot as plt
+import numpy as np
+import scipy.signal as signal
+import os
+
+matplotlib.use('Qt5Agg')
+
+def plot1():
+    volt_in, volt_out = read_file.read_xy_file("prak2/test.txt")
+
+    y = [volt_in, volt_out]
+    x = volt_in
+
+    labels = ["Ideale Kennlinie", "Reale Kennlinie"]
+
+    plot_lib.plot_shared_xy(
+        x=x,
+        y_list=y,
+        xlabel="Input Voltage (V)",
+        ylabel="Output Voltage (V)",
+        title="Kennlinie des Tiefpassfilters",
+        show_points=True,
+        save_path="prak2/kennlinie_tiefpass.svg",
+        labels=labels
+    )
+
+    diff = plot_lib.plot_difference(
+        x=x,
+        y1=y[0],
+        y2=y[1],
+        return_sum=True,
+        xlabel="Input Voltage (V)",
+        ylabel="Output Voltage (V)",
+        title="Differenz der idealen und realen Kennlinie des Tiefpassfilters",
+        show_points=True,
+        save_path="prak2/kennlinie_tiefpass_diff.svg"
+    )
+
+    print(diff)
+
+def plot2():
+    data_1k, indecies = read_file.read_data_with_indices("prak2/333_output1k.txt")
+    data_3k, _ = read_file.read_data_with_indices("prak2/333_output3k.txt")
+    data_5k, _ = read_file.read_data_with_indices("prak2/333_output5k.txt")
+    data = [data_1k, data_3k, data_5k]
+    labels = [r"$1\,\mathrm{k\Omega}$", r"$3\,\mathrm{k\Omega}$", r"$5\,\mathrm{k\Omega}$"]
+    colors = ["red", "green", "blue"]
+    indecies = indecies*1000
+    ys = []
+    xs = []
+
+    length = 169
+
+    figsize = (10, 6)
+    plt.figure(figsize=figsize)
+
+    for i in range(len(data)):
+        idxs = editing_data.detect_step_segments(data[i], diff_threshold=0.2, min_length=50)
+        # print(i, idxs)
+        y = data[i][idxs[0][0]:idxs[0][0]+length]
+        x = np.arange(0, len(y)) / 48000 *1000000  # Zeit in mycrosekunden
+        plt.plot(x, y, label=labels[i] + " (Messung)", color=colors[i], linestyle='--', marker='x', markersize=8)
+        ys.append(y)
+        xs.append(x)
+    
+    C = 100e-9  
+    R = [1e3, 3e3, 5e3]
+
+    t = np.linspace(0, 0.0035, 1000)
+    
+    for i in range(len(R)):
+        Rs = R[i]
+        label = labels[i]
+        num = [5]           
+        den = [Rs*C, 1]
+        system = signal.TransferFunction(num, den)
+        t_out, y = signal.step(system, T=t)
+        t_out = t_out * 1000 * 1000
+        plt.plot(t_out,  y, label=label + " (Ideal)", color=colors[i])
+
+    plt.xlim(0, 1.5*1000)
+    plt.ylim(0, 5.5)
+    plt.xlabel(r"Zeit ($\mu s$)")
+    # plt.xlabel(r"Zeit (ms)")
+    plt.ylabel("Voltage (V)")
+    plt.title("Sprungantwort des Tiefpassfilters")
+    plt.grid()
+    plt.legend()
+    plt.tight_layout()
+
+    save_path=f"prak2/tiefpass_mult_r.svg"
+    plt.savefig(save_path, format="svg")
+    plt.show()
+
+if __name__ == "__main__":
+    # plot1()
+    plot2()