update patch generation 3d

examples/plot_data.py

@@ -23,6 +23,37 @@ except:
     print("PyQtGraph is not installed. Please install it using 'pip install pyqt5 pyqtgraph'.")
     exit()
 
+def lp_filter(series, alpha=0.5):
+    series = np.asarray(series)
+    if series.ndim == 0:
+        return float(series)
+    if series.shape[0] < 2:
+        return float(series[-1])
+    return float(series[-1] * alpha + series[-2] * (1 - alpha))
+
+def median_filter(series, window_size=5):
+    series = np.asarray(series)
+    if series.ndim == 0:
+        return float(series)
+    if series.shape[0] == 0:
+        return 0.0
+    try:
+        window_n = max(1, int(window_size))
+    except (TypeError, ValueError):
+        window_n = 1
+    return float(np.median(series[-window_n:]))
+def moving_average(series, window_size=5):
+    series = np.asarray(series)
+    if series.ndim == 0:
+        return float(series)
+    if series.shape[0] == 0:
+        return 0.0
+    try:
+        window_n = max(1, int(window_size))
+    except (TypeError, ValueError):
+        window_n = 1
+    return float(np.mean(series[-window_n:]))
+
 def create_plot():
     p1 = win.addPlot(title="法向力")
     p1.setLabel('bottom', '时间', units='s')
@@ -100,7 +131,7 @@ p1, p2, p3, plot_af, plot_tfx, plot_tfy = create_plot()
 data = np.zeros([npoints,2,3])
 start_time = None  # Will be set when sensor starts
 for i in range(3):
-    data[:,0,i] = np.linspace(-npoints,0,npoints)
+    data[:,0,i] = np.linspace(-npoints,0,npoints)/30
 
 
 
@@ -164,6 +195,7 @@ def main():
 
         # 更新实时曲线
         current_time = time.time() - start_time
+        data_filtered = data.copy()
         for i in range(3):
             data[:-1, 0, i] = data[1:, 0, i]  # 时间轴左移
             data[:-1, 1, i] = data[1:, 1, i]  # 力数据左移
@@ -171,7 +203,11 @@ def main():
         data[-1, 1, 0] = fn
         data[-1, 1, 1] = fx
         data[-1, 1, 2] = fy
-        update(plot_af, plot_tfx, plot_tfy, data, p1, p2, p3) # 更新曲线
+        # 对最新采样点做一阶低通，滤波对象是历史曲线而不是单个标量。
+        data_filtered[-1, 1, 0] = moving_average(data[:, 1, 0])
+        data_filtered[-1, 1, 1] = moving_average(data[:, 1, 1])
+        data_filtered[-1, 1, 2] = moving_average(data[:, 1, 2])
+        update(plot_af, plot_tfx, plot_tfy, data_filtered, p1, p2, p3) # 更新曲线
 
         key = cv2.waitKey(1)
         if key & 0xFF == ord("q"):