PyThermostat: Add main function to plot.py

pythermostat/pythermostat/plot.py

@@ -5,127 +5,133 @@ import matplotlib.animation as animation
 from threading import Thread, Lock
 from pythermostat.client import Client
 
-TIME_WINDOW = 300.0
 
-tec = Client()
+def main():
-target_temperature = tec.get_pid()[0]['target']
+    TIME_WINDOW = 300.0
-print("Channel 0 target temperature: {:.3f}".format(target_temperature))
 
-class Series:
+    tec = Client()
-    def __init__(self, conv=lambda x: x):
+    target_temperature = tec.get_pid()[0]['target']
-        self.conv = conv
+    print("Channel 0 target temperature: {:.3f}".format(target_temperature))
-        self.x_data = []
-        self.y_data = []
 
-    def append(self, x, y):
+    class Series:
-        self.x_data.append(x)
+        def __init__(self, conv=lambda x: x):
-        self.y_data.append(self.conv(y))
+            self.conv = conv
+            self.x_data = []
+            self.y_data = []
 
-    def clip(self, min_x):
+        def append(self, x, y):
-        drop = 0
+            self.x_data.append(x)
-        while drop < len(self.x_data) and self.x_data[drop] < min_x:
+            self.y_data.append(self.conv(y))
-            drop += 1
-        self.x_data = self.x_data[drop:]
-        self.y_data = self.y_data[drop:]
 
-series = {
+        def clip(self, min_x):
-    # 'adc': Series(),
+            drop = 0
-    # 'sens': Series(lambda x: x * 0.0001),
+            while drop < len(self.x_data) and self.x_data[drop] < min_x:
-    'temperature': Series(),
+                drop += 1
-    # 'i_set': Series(),
+            self.x_data = self.x_data[drop:]
-    'pid_output': Series(),
+            self.y_data = self.y_data[drop:]
-    # 'vref': Series(),
-    # 'dac_value': Series(),
-    # 'dac_feedback': Series(),
-    # 'i_tec': Series(),
-    'tec_i': Series(),
-    'tec_u_meas': Series(),
-    # 'interval': Series(),
-}
-series_lock = Lock()
 
-quit = False
+    series = {
+        # 'adc': Series(),
+        # 'sens': Series(lambda x: x * 0.0001),
+        'temperature': Series(),
+        # 'i_set': Series(),
+        'pid_output': Series(),
+        # 'vref': Series(),
+        # 'dac_value': Series(),
+        # 'dac_feedback': Series(),
+        # 'i_tec': Series(),
+        'tec_i': Series(),
+        'tec_u_meas': Series(),
+        # 'interval': Series(),
+    }
+    series_lock = Lock()
+
+    quit = False
+
+    def recv_data(tec):
+        global last_packet_time
+        while True:
+            data = tec.get_report()
+            ch0 = data[0]
+            series_lock.acquire()
+            try:
+                for k, s in series.items():
+                    if k in ch0:
+                        v = ch0[k]
+                        if type(v) is float:
+                            s.append(ch0['time'], v)
+            finally:
+                series_lock.release()
+
+            if quit:
+                break
+            time.sleep(0.05)
+
+    thread = Thread(target=recv_data, args=(tec,))
+    thread.start()
+
+    fig, ax = plt.subplots()
+
+    for k, s in series.items():
+        s.plot, = ax.plot([], [], label=k)
+    legend = ax.legend()
+
+    def animate(i):
+        min_x, max_x, min_y, max_y = None, None, None, None
         
-def recv_data(tec):
-    global last_packet_time
-    while True:
-        data = tec.get_report()
-        ch0 = data[0]
         series_lock.acquire()
         try:
             for k, s in series.items():
-                if k in ch0:
+                s.plot.set_data(s.x_data, s.y_data)
-                    v = ch0[k]
+                if len(s.y_data) > 0:
-                    if type(v) is float:
+                    s.plot.set_label("{}: {:.3f}".format(k, s.y_data[-1]))
-                        s.append(ch0['time'], v)
+
+                if len(s.x_data) > 0:
+                    min_x_ = min(s.x_data)
+                    if min_x is None:
+                        min_x = min_x_
+                    else:
+                        min_x = min(min_x, min_x_)
+                    max_x_ = max(s.x_data)
+                    if max_x is None:
+                        max_x = max_x_
+                    else:
+                        max_x = max(max_x, max_x_)
+                if len(s.y_data) > 0:
+                    min_y_ = min(s.y_data)
+                    if min_y is None:
+                        min_y = min_y_
+                    else:
+                        min_y = min(min_y, min_y_)
+                    max_y_ = max(s.y_data)
+                    if max_y is None:
+                        max_y = max_y_
+                    else:
+                        max_y = max(max_y, max_y_)
+
+            if min_x and max_x - TIME_WINDOW > min_x:
+                for s in series.values():
+                    s.clip(max_x - TIME_WINDOW)
         finally:
             series_lock.release()
 
-        if quit:
+        if min_x != max_x:
-            break
+            ax.set_xlim(min_x, max_x)
-        time.sleep(0.05)
+        if min_y != max_y:
+            margin_y = 0.01 * (max_y - min_y)
+            ax.set_ylim(min_y - margin_y, max_y + margin_y)
 
-thread = Thread(target=recv_data, args=(tec,))
+        nonlocal legend
-thread.start()
+        legend.remove()
+        legend = ax.legend()
 
-fig, ax = plt.subplots()
+    ani = animation.FuncAnimation(
+        fig, animate, interval=1, blit=False, save_count=50)
 
-for k, s in series.items():
+    plt.show()
-    s.plot, = ax.plot([], [], label=k)
+    quit = True
-legend = ax.legend()
+    thread.join()
 
-def animate(i):
-    min_x, max_x, min_y, max_y = None, None, None, None
 
-    series_lock.acquire()
+if __name__ == "__main__":
-    try:
+    main()
-        for k, s in series.items():
-            s.plot.set_data(s.x_data, s.y_data)
-            if len(s.y_data) > 0:
-                s.plot.set_label("{}: {:.3f}".format(k, s.y_data[-1]))
-
-            if len(s.x_data) > 0:
-                min_x_ = min(s.x_data)
-                if min_x is None:
-                    min_x = min_x_
-                else:
-                    min_x = min(min_x, min_x_)
-                max_x_ = max(s.x_data)
-                if max_x is None:
-                    max_x = max_x_
-                else:
-                    max_x = max(max_x, max_x_)
-            if len(s.y_data) > 0:
-                min_y_ = min(s.y_data)
-                if min_y is None:
-                    min_y = min_y_
-                else:
-                    min_y = min(min_y, min_y_)
-                max_y_ = max(s.y_data)
-                if max_y is None:
-                    max_y = max_y_
-                else:
-                    max_y = max(max_y, max_y_)
-
-        if min_x and max_x - TIME_WINDOW > min_x:
-            for s in series.values():
-                s.clip(max_x - TIME_WINDOW)
-    finally:
-        series_lock.release()
-
-    if min_x != max_x:
-        ax.set_xlim(min_x, max_x)
-    if min_y != max_y:
-        margin_y = 0.01 * (max_y - min_y)
-        ax.set_ylim(min_y - margin_y, max_y + margin_y)
-
-    global legend
-    legend.remove()
-    legend = ax.legend()
-
-ani = animation.FuncAnimation(
-    fig, animate, interval=1, blit=False, save_count=50)
-
-plt.show()
-quit = True
-thread.join()