# python - How do I plot in real-time in a while loop using matplotlib?

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### Top 5 Answer for python - How do I plot in real-time in a while loop using matplotlib?

90

Here's the working version of the code in question (requires at least version Matplotlib 1.1.0 from 2011-11-14):

``import numpy as np import matplotlib.pyplot as plt  plt.axis([0, 10, 0, 1])  for i in range(10):     y = np.random.random()     plt.scatter(i, y)     plt.pause(0.05)  plt.show() ``

Note the call to `plt.pause(0.05)`, which both draws the new data and runs the GUI's event loop (allowing for mouse interaction).

86

If you're interested in realtime plotting, I'd recommend looking into matplotlib's animation API. In particular, using `blit` to avoid redrawing the background on every frame can give you substantial speed gains (~10x):

``#!/usr/bin/env python  import numpy as np import time import matplotlib matplotlib.use('GTKAgg') from matplotlib import pyplot as plt   def randomwalk(dims=(256, 256), n=20, sigma=5, alpha=0.95, seed=1):     """ A simple random walk with memory """      r, c = dims     gen = np.random.RandomState(seed)     pos = gen.rand(2, n) * ((r,), (c,))     old_delta = gen.randn(2, n) * sigma      while True:         delta = (1. - alpha) * gen.randn(2, n) * sigma + alpha * old_delta         pos += delta         for ii in xrange(n):             if not (0. <= pos[0, ii] < r):                 pos[0, ii] = abs(pos[0, ii] % r)             if not (0. <= pos[1, ii] < c):                 pos[1, ii] = abs(pos[1, ii] % c)         old_delta = delta         yield pos   def run(niter=1000, doblit=True):     """     Display the simulation using matplotlib, optionally using blit for speed     """      fig, ax = plt.subplots(1, 1)     ax.set_aspect('equal')     ax.set_xlim(0, 255)     ax.set_ylim(0, 255)     ax.hold(True)     rw = randomwalk()     x, y = rw.next()      plt.show(False)     plt.draw()      if doblit:         # cache the background         background = fig.canvas.copy_from_bbox(ax.bbox)      points = ax.plot(x, y, 'o')[0]     tic = time.time()      for ii in xrange(niter):          # update the xy data         x, y = rw.next()         points.set_data(x, y)          if doblit:             # restore background             fig.canvas.restore_region(background)              # redraw just the points             ax.draw_artist(points)              # fill in the axes rectangle             fig.canvas.blit(ax.bbox)          else:             # redraw everything             fig.canvas.draw()      plt.close(fig)     print "Blit = %s, average FPS: %.2f" % (         str(doblit), niter / (time.time() - tic))  if __name__ == '__main__':     run(doblit=False)     run(doblit=True) ``

Output:

``Blit = False, average FPS: 54.37 Blit = True, average FPS: 438.27 ``

76

I know I'm a bit late to answer this question. Nevertheless, I've made some code a while ago to plot live graphs, that I would like to share:

Code for PyQt4:

``################################################################### #                                                                 # #                    PLOT A LIVE GRAPH (PyQt4)                    # #                  -----------------------------                  # #            EMBED A MATPLOTLIB ANIMATION INSIDE YOUR             # #            OWN GUI!                                             # #                                                                 # ###################################################################   import sys import os from PyQt4 import QtGui from PyQt4 import QtCore import functools import numpy as np import random as rd import matplotlib matplotlib.use("Qt4Agg") from matplotlib.figure import Figure from matplotlib.animation import TimedAnimation from matplotlib.lines import Line2D from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas import time import threading   def setCustomSize(x, width, height):     sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.Fixed)     sizePolicy.setHorizontalStretch(0)     sizePolicy.setVerticalStretch(0)     sizePolicy.setHeightForWidth(x.sizePolicy().hasHeightForWidth())     x.setSizePolicy(sizePolicy)     x.setMinimumSize(QtCore.QSize(width, height))     x.setMaximumSize(QtCore.QSize(width, height))  ''''''  class CustomMainWindow(QtGui.QMainWindow):      def __init__(self):          super(CustomMainWindow, self).__init__()          # Define the geometry of the main window         self.setGeometry(300, 300, 800, 400)         self.setWindowTitle("my first window")          # Create FRAME_A         self.FRAME_A = QtGui.QFrame(self)         self.FRAME_A.setStyleSheet("QWidget { background-color: %s }" % QtGui.QColor(210,210,235,255).name())         self.LAYOUT_A = QtGui.QGridLayout()         self.FRAME_A.setLayout(self.LAYOUT_A)         self.setCentralWidget(self.FRAME_A)          # Place the zoom button         self.zoomBtn = QtGui.QPushButton(text = 'zoom')         setCustomSize(self.zoomBtn, 100, 50)         self.zoomBtn.clicked.connect(self.zoomBtnAction)         self.LAYOUT_A.addWidget(self.zoomBtn, *(0,0))          # Place the matplotlib figure         self.myFig = CustomFigCanvas()         self.LAYOUT_A.addWidget(self.myFig, *(0,1))          # Add the callbackfunc to ..         myDataLoop = threading.Thread(name = 'myDataLoop', target = dataSendLoop, daemon = True, args = (self.addData_callbackFunc,))         myDataLoop.start()          self.show()      ''''''       def zoomBtnAction(self):         print("zoom in")         self.myFig.zoomIn(5)      ''''''      def addData_callbackFunc(self, value):         # print("Add data: " + str(value))         self.myFig.addData(value)    ''' End Class '''   class CustomFigCanvas(FigureCanvas, TimedAnimation):      def __init__(self):          self.addedData = []         print(matplotlib.__version__)          # The data         self.xlim = 200         self.n = np.linspace(0, self.xlim - 1, self.xlim)         a = []         b = []         a.append(2.0)         a.append(4.0)         a.append(2.0)         b.append(4.0)         b.append(3.0)         b.append(4.0)         self.y = (self.n * 0.0) + 50          # The window         self.fig = Figure(figsize=(5,5), dpi=100)         self.ax1 = self.fig.add_subplot(111)           # self.ax1 settings         self.ax1.set_xlabel('time')         self.ax1.set_ylabel('raw data')         self.line1 = Line2D([], [], color='blue')         self.line1_tail = Line2D([], [], color='red', linewidth=2)         self.line1_head = Line2D([], [], color='red', marker='o', markeredgecolor='r')         self.ax1.add_line(self.line1)         self.ax1.add_line(self.line1_tail)         self.ax1.add_line(self.line1_head)         self.ax1.set_xlim(0, self.xlim - 1)         self.ax1.set_ylim(0, 100)           FigureCanvas.__init__(self, self.fig)         TimedAnimation.__init__(self, self.fig, interval = 50, blit = True)      def new_frame_seq(self):         return iter(range(self.n.size))      def _init_draw(self):         lines = [self.line1, self.line1_tail, self.line1_head]         for l in lines:             l.set_data([], [])      def addData(self, value):         self.addedData.append(value)      def zoomIn(self, value):         bottom = self.ax1.get_ylim()[0]         top = self.ax1.get_ylim()[1]         bottom += value         top -= value         self.ax1.set_ylim(bottom,top)         self.draw()       def _step(self, *args):         # Extends the _step() method for the TimedAnimation class.         try:             TimedAnimation._step(self, *args)         except Exception as e:             self.abc += 1             print(str(self.abc))             TimedAnimation._stop(self)             pass      def _draw_frame(self, framedata):         margin = 2         while(len(self.addedData) > 0):             self.y = np.roll(self.y, -1)             self.y[-1] = self.addedData[0]             del(self.addedData[0])           self.line1.set_data(self.n[ 0 : self.n.size - margin ], self.y[ 0 : self.n.size - margin ])         self.line1_tail.set_data(np.append(self.n[-10:-1 - margin], self.n[-1 - margin]), np.append(self.y[-10:-1 - margin], self.y[-1 - margin]))         self.line1_head.set_data(self.n[-1 - margin], self.y[-1 - margin])         self._drawn_artists = [self.line1, self.line1_tail, self.line1_head]  ''' End Class '''  # You need to setup a signal slot mechanism, to  # send data to your GUI in a thread-safe way. # Believe me, if you don't do this right, things # go very very wrong.. class Communicate(QtCore.QObject):     data_signal = QtCore.pyqtSignal(float)  ''' End Class '''   def dataSendLoop(addData_callbackFunc):     # Setup the signal-slot mechanism.     mySrc = Communicate()     mySrc.data_signal.connect(addData_callbackFunc)      # Simulate some data     n = np.linspace(0, 499, 500)     y = 50 + 25*(np.sin(n / 8.3)) + 10*(np.sin(n / 7.5)) - 5*(np.sin(n / 1.5))     i = 0      while(True):         if(i > 499):             i = 0         time.sleep(0.1)         mySrc.data_signal.emit(y[i]) # <- Here you emit a signal!         i += 1     ### ###   if __name__== '__main__':     app = QtGui.QApplication(sys.argv)     QtGui.QApplication.setStyle(QtGui.QStyleFactory.create('Plastique'))     myGUI = CustomMainWindow()     sys.exit(app.exec_())  '''''' ``

I recently rewrote the code for PyQt5.
Code for PyQt5:

``################################################################### #                                                                 # #                    PLOT A LIVE GRAPH (PyQt5)                    # #                  -----------------------------                  # #            EMBED A MATPLOTLIB ANIMATION INSIDE YOUR             # #            OWN GUI!                                             # #                                                                 # ###################################################################  import sys import os from PyQt5.QtWidgets import * from PyQt5.QtCore import * from PyQt5.QtGui import * import functools import numpy as np import random as rd import matplotlib matplotlib.use("Qt5Agg") from matplotlib.figure import Figure from matplotlib.animation import TimedAnimation from matplotlib.lines import Line2D from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas import time import threading  class CustomMainWindow(QMainWindow):     def __init__(self):         super(CustomMainWindow, self).__init__()         # Define the geometry of the main window         self.setGeometry(300, 300, 800, 400)         self.setWindowTitle("my first window")         # Create FRAME_A         self.FRAME_A = QFrame(self)         self.FRAME_A.setStyleSheet("QWidget { background-color: %s }" % QColor(210,210,235,255).name())         self.LAYOUT_A = QGridLayout()         self.FRAME_A.setLayout(self.LAYOUT_A)         self.setCentralWidget(self.FRAME_A)         # Place the zoom button         self.zoomBtn = QPushButton(text = 'zoom')         self.zoomBtn.setFixedSize(100, 50)         self.zoomBtn.clicked.connect(self.zoomBtnAction)         self.LAYOUT_A.addWidget(self.zoomBtn, *(0,0))         # Place the matplotlib figure         self.myFig = CustomFigCanvas()         self.LAYOUT_A.addWidget(self.myFig, *(0,1))         # Add the callbackfunc to ..         myDataLoop = threading.Thread(name = 'myDataLoop', target = dataSendLoop, daemon = True, args = (self.addData_callbackFunc,))         myDataLoop.start()         self.show()         return      def zoomBtnAction(self):         print("zoom in")         self.myFig.zoomIn(5)         return      def addData_callbackFunc(self, value):         # print("Add data: " + str(value))         self.myFig.addData(value)         return  ''' End Class '''   class CustomFigCanvas(FigureCanvas, TimedAnimation):     def __init__(self):         self.addedData = []         print(matplotlib.__version__)         # The data         self.xlim = 200         self.n = np.linspace(0, self.xlim - 1, self.xlim)         a = []         b = []         a.append(2.0)         a.append(4.0)         a.append(2.0)         b.append(4.0)         b.append(3.0)         b.append(4.0)         self.y = (self.n * 0.0) + 50         # The window         self.fig = Figure(figsize=(5,5), dpi=100)         self.ax1 = self.fig.add_subplot(111)         # self.ax1 settings         self.ax1.set_xlabel('time')         self.ax1.set_ylabel('raw data')         self.line1 = Line2D([], [], color='blue')         self.line1_tail = Line2D([], [], color='red', linewidth=2)         self.line1_head = Line2D([], [], color='red', marker='o', markeredgecolor='r')         self.ax1.add_line(self.line1)         self.ax1.add_line(self.line1_tail)         self.ax1.add_line(self.line1_head)         self.ax1.set_xlim(0, self.xlim - 1)         self.ax1.set_ylim(0, 100)         FigureCanvas.__init__(self, self.fig)         TimedAnimation.__init__(self, self.fig, interval = 50, blit = True)         return      def new_frame_seq(self):         return iter(range(self.n.size))      def _init_draw(self):         lines = [self.line1, self.line1_tail, self.line1_head]         for l in lines:             l.set_data([], [])         return      def addData(self, value):         self.addedData.append(value)         return      def zoomIn(self, value):         bottom = self.ax1.get_ylim()[0]         top = self.ax1.get_ylim()[1]         bottom += value         top -= value         self.ax1.set_ylim(bottom,top)         self.draw()         return      def _step(self, *args):         # Extends the _step() method for the TimedAnimation class.         try:             TimedAnimation._step(self, *args)         except Exception as e:             self.abc += 1             print(str(self.abc))             TimedAnimation._stop(self)             pass         return      def _draw_frame(self, framedata):         margin = 2         while(len(self.addedData) > 0):             self.y = np.roll(self.y, -1)             self.y[-1] = self.addedData[0]             del(self.addedData[0])          self.line1.set_data(self.n[ 0 : self.n.size - margin ], self.y[ 0 : self.n.size - margin ])         self.line1_tail.set_data(np.append(self.n[-10:-1 - margin], self.n[-1 - margin]), np.append(self.y[-10:-1 - margin], self.y[-1 - margin]))         self.line1_head.set_data(self.n[-1 - margin], self.y[-1 - margin])         self._drawn_artists = [self.line1, self.line1_tail, self.line1_head]         return  ''' End Class '''   # You need to setup a signal slot mechanism, to # send data to your GUI in a thread-safe way. # Believe me, if you don't do this right, things # go very very wrong.. class Communicate(QObject):     data_signal = pyqtSignal(float)  ''' End Class '''    def dataSendLoop(addData_callbackFunc):     # Setup the signal-slot mechanism.     mySrc = Communicate()     mySrc.data_signal.connect(addData_callbackFunc)      # Simulate some data     n = np.linspace(0, 499, 500)     y = 50 + 25*(np.sin(n / 8.3)) + 10*(np.sin(n / 7.5)) - 5*(np.sin(n / 1.5))     i = 0      while(True):         if(i > 499):             i = 0         time.sleep(0.1)         mySrc.data_signal.emit(y[i]) # <- Here you emit a signal!         i += 1     ### ###  if __name__== '__main__':     app = QApplication(sys.argv)     QApplication.setStyle(QStyleFactory.create('Plastique'))     myGUI = CustomMainWindow()     sys.exit(app.exec_()) ``

Just try it out. Copy-paste this code in a new python-file, and run it. You should get a beautiful, smoothly moving graph:

68

None of the methods worked for me. But I have found this Real time matplotlib plot is not working while still in a loop

All you need is to add

``plt.pause(0.0001) ``

and then you could see the new plots.

So your code should look like this, and it will work

``import matplotlib.pyplot as plt import numpy as np plt.ion() ## Note this correction fig=plt.figure() plt.axis([0,1000,0,1])  i=0 x=list() y=list()  while i <1000:     temp_y=np.random.random();     x.append(i);     y.append(temp_y);     plt.scatter(i,temp_y);     i+=1;     plt.show()     plt.pause(0.0001) #Note this correction ``

54

`show` is probably not the best choice for this. What I would do is use `pyplot.draw()` instead. You also might want to include a small time delay (e.g., `time.sleep(0.05)`) in the loop so that you can see the plots happening. If I make these changes to your example it works for me and I see each point appearing one at a time.