I am struggling to find time complexity of get_size method which i created in Binary Search Tree because of the fact that there is multiple recursion with multiple conditions.Here is code
`class Node:
def __init__(self, data, left=None, right=None):
self.data = data
self.right = right
self.left = left
def __str__(self):
return str(self.data)
i created node class to stock data and then i created BST functions and it does work but problem is every functions time complexity should be log n in functions but i used if elif else and double recursion at the same time does it affect the run time if it does why if it doesn't why
class BST:
def __init__(self):
self.root = None
def add(self, value, x=None):
new_node = Node(value)
if self.root is None:
self.root = new_node
return True
if x is None:
main_node = self.root
else:
main_node = x
if value > main_node.data:
if main_node.left is None:
main_node.left = new_node
return True
else:
return self.add(value, main_node.left)
elif value == main_node.data:
return False
elif value < main_node.data:
if main_node.right is None:
main_node.right = new_node
return True
else:
return self.add(value, main_node.right)
def get_size(self, x=None):
if self.root is None:
return 0
if x is None:
main_node = self.root
else:
main_node = x
if main_node.left is not None and main_node.right is not None:
return 1 + self.get_size(main_node.left) + self.get_size(main_node.right)
elif main_node.left is None and main_node.right is None:
return 1
else:
if main_node.left is not None:
return 1 + self.get_size(main_node.left)
else:
return 1 + self.get_size(main_node.right)`
To determine the complexity, it helps to break your function apart and analyze the different parts separately.
Starting with the base cases, your complexity is O(1).
if self.root is None:
return 0
elif main_node.left is None and main_node.right is None:
return 1
However, as your start recursing, those base cases will add up. Let's look at one of the recursive calls:
if main_node.left is not None and main_node.right is not None:
return 1 + self.get_size(main_node.left) + self.get_size(main_node.right)
In the simplest tree where main_node's left and right children are both leaves, then these 2 calls to get_size() will not recurse any farther, resulting in two O(1) operations. However, if either of the nodes have children, then we will make additional calls to get_size(), making get_size() something greater than O(1). If the left child had children, but those children are leaves, then we will again call get_size() two more times, each being an O(1) call.
If we repeat this analysis for every possible if/else statement in the function, we will see that for each child that exists, we will call get_size() for it once and only once. Therefore, our overall complexity is O(n).
I got the emit signal working when it is in the Worker class - def run(self) method. Everything runs fine, the while loop is able to cycle and emit a signal every 1 second. Then the label will be updated after receiving the signal.
I decided to try out by placing the while loop in another class named loop, methodA. This is to try see if the emitted signal will be picked up by the MainWindow. Unfortunately, the signal is not picked up and the program hung up thereafter.
Did I miss any step that prevented the while loop's emitting signals from being picked up? Kindly point me in the right direction by making changes to my script.
Thanks.
import sys
import time
from PyQt5 import QtWidgets
from PyQt5.QtCore import QThread, pyqtSignal
from mydialog import Ui_mydialog
class Mainwindow(QtWidgets.QMainWindow, Ui_mydialog):
def __init__(self, *args, obj=None, **kwargs):
super(Mainwindow, self).__init__(*args, **kwargs)
self.setupUi(self)
self.thread = Worker()
self.loop = loop()
self.thread.sig.connect(self.updatelabel)
self.mypushbutton.clicked.connect(self.mypushbuttonclicked)
def mypushbuttonclicked(self):
self.thread.start()
def updatelabel(self, text):
self.mylabel.setText(text)
class Worker(QThread):
sig = pyqtSignal(str)
def __init__(self, parent=None):
super(Worker, self).__init__(parent)
# self.count = 0
self.loop = loop()
def run(self):
self.loop.methodA()
## Original code without being in class loop and method loopA
# while True:
# time.sleep(1)
# self.count += 1
# if (self.count % 1 == 0):
# self.sig.emit(f"Timer: {self.count} s")
# Newly added class with method "methodA"
class loop(object):
sig = pyqtSignal(str)
def __init__(self):
self.count = 0
def methodA(self):
while True:
time.sleep(1)
self.count += 1
if (self.count % 1 == 0):
self.sig.emit(f"Timer: {self.count} s")
app = QtWidgets.QApplication(sys.argv)
window = Mainwindow()
app.setStyle("Fusion")
window.show()
app.exec()
I had a similar problem.
I solved it by following this: http://zetcode.com/gui/pyqt5/eventssignals/
The idea is to create a class that hold all the signals, and pass the same communication class to all the classes as a parameter.
So your code might become:
import sys
import time
from PyQt5 import QtWidgets
from PyQt5.QtCore import QThread, pyqtSignal, QObject
from mydialog import Ui_mydialog
class Communicate(QObject):
sig = pyqtSignal(str)
class Mainwindow(QtWidgets.QMainWindow, Ui_mydialog):
def __init__(self, *args, obj=None, **kwargs):
super(Mainwindow, self).__init__(*args, **kwargs)
self.setupUi(self)
self.communicate = Communicate()
self.communicate.sig[str].connect(self.updatelabel)
self.thread = Worker(communicate = self.communicate)
#self.loop = loop() # this seems useless to me here
self.mypushbutton.clicked.connect(self.mypushbuttonclicked)
def mypushbuttonclicked(self):
self.thread.start()
def updatelabel(self, text):
self.mylabel.setText(text)
class Worker(QThread):
def __init__(self, parent=None, communicate=Communicate()):
super(Worker, self).__init__(parent)
self.communicate = communicate
# self.count = 0
self.loop = loop(communicate= self.communicate)
def run(self):
self.loop.methodA()
## Original code without being in class loop and method loopA
# while True:
# time.sleep(1)
# self.count += 1
# if (self.count % 1 == 0):
# self.sig.emit(f"Timer: {self.count} s")
# Newly added class with method "methodA"
class loop(object):
def __init__(self, communicate=Communicate()):
self.count = 0
self.communicate = communicate
def methodA(self):
while True:
time.sleep(1)
self.count += 1
if (self.count % 1 == 0):
self.communicate.sig.emit(f"Timer: {self.count} s")
app = QtWidgets.QApplication(sys.argv)
window = Mainwindow()
app.setStyle("Fusion")
window.show()
app.exec()
I haven't tested this code, but I hope that you've got the idea.
I am new to PyqtGraph ( Infact this is my first time)
I have a Qt designer file which I import in my python code. I 6 windows in which I plot a 42x22 (different sizes) as an inmage, these have been promoted the graphicview.
I have a data set which is 6x42x22 and so I use a for loop to plot the 6 images
for n in range(imageStackSize):
self.glayout = pg.GraphicsLayout()
self.vb = self.glayout.addViewBox()
self.vb.setAspectLocked(lock=True, ratio=self.aspect_ratio)
img_temp = image[n, :, :]
and...
``
img = pg.ImageItem(img_temp, lut=self.jet_lut)
if n == 0:
self.ui.Channel1_img.setCentralItem(self.glayout)
self.vb.addItem(img)
elif n == 1:
self.ui.Channel2_img.setCentralItem(self.glayout)
self.vb.addItem(img)
elif n == 2:
self.ui.Channel3_img.setCentralItem(self.glayout)
self.vb.addItem(img)
elif n == 3:
self.ui.Channel4_img.setCentralItem(self.glayout)
self.vb.addItem(img)
elif n == 4:
self.ui.Channel5_img.setCentralItem(self.glayout)
self.vb.addItem(img)
elif n == 5:
self.ui.Channel6_img.setCentralItem(self.glayout)
self.vb.addItem(img)
After this I am trying to click on one of the image (ideally I would like to make it such that I can click any of the six images) to get the (6,x,y) coordinated the first dimension does not matter. In order to achieve this I did
self.ui.Channel1_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.Channel2_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.Channel3_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.Channel4_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.Channel5_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.Channel6_img.scene().sigMouseClicked.connect(self.onClick)
#self.ui.PMTVoltage_plt.scene().sigMouseClicked.connect(self.onClick)
def onClick(self, event):
print("clicked")
and then I tried
items = self.ui.Channel1_img.imageItem.mapFromViewToItem(event.pos())
and
items = self.ui.Channel1_img.imageItem.mapFromSceneToView(event.pos())
but the prog just crashes. I read somewhere that the coordinates are in the viewbox, but I cant seem to find the viewbox or vb in the self.ui.Channel1_img
I went through the entire ui variable in debug to look for vb or image Item and could not find it.
infact the only thing I found was,
items = {dict} {<pyqtgraph.graphicsItems.ViewBox.ViewBox.ViewBox
object at 0x000001CF73888CA8>: [(0, 0)]}
<pyqtgraph.graphicsItems.ViewBox.ViewBox.ViewBox object at
0x000001CF73888CA8> (1990508186792) = {list} <class 'list'>: [(0, 0)]
0 = {tuple} <class 'tuple'>: (0, 0)
0 = {int} 0
1 = {int} 0
__len__ = {int} 2
__len__ = {int} 1
__len__ = {int} 1
what am I missing? Any help is appreciated
Ok I figured it out, here is my solution for some who may have same question
I plot the data using it as imageItem
vb = pg.ViewBox()
self.ui.PMTVoltage_plt.useOpenGL()
self.ui.PMTVoltage_plt.setCentralItem(vb)
self.img = pg.ImageItem(pmtImage)
vb.addItem(self.img)
and then in other function I recover the vb using getViewBox() and then use mapFromViewtoItem()
vb = self.ui.PMTVoltage_plt.getViewBox()
items = vb.mapSceneToView(event.scenePos())
pixels = vb.mapFromViewToItem(self.img, items)
print(items)
Hope this helps
I am just playing around with the Paraboloid tutorial in OpenMDAO. I tried something simple, basically changing the input values to the Paraboloid component. See the following code. When I run it though, it will print the same result as if nothing happened. So what is going on? if I have a group, how would I modify the inputs?
from __future__ import print_function
from openmdao.api import IndepVarComp, Component, Problem, Group
class Paraboloid(Component):
""" Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 """
def __init__(self):
super(Paraboloid, self).__init__()
self.add_param('x', val=0.0)
self.add_param('y', val=0.0)
self.add_output('f_xy', val=0.0)
def solve_nonlinear(self, params, unknowns, resids):
"""f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3
"""
x = params['x']
y = params['y']
unknowns['f_xy'] = (x-3.0)**2 + x*y + (y+4.0)**2 - 3.0
def linearize(self, params, unknowns, resids):
""" Jacobian for our paraboloid."""
x = params['x']
y = params['y']
J = {}
J['f_xy', 'x'] = 2.0*x - 6.0 + y
J['f_xy', 'y'] = 2.0*y + 8.0 + x
return J
if __name__ == "__main__":
top = Problem()
root = top.root = Group()
root.add('p1', IndepVarComp('x', 3.0))
root.add('p2', IndepVarComp('y', -4.0))
root.add('p', Paraboloid())
root.connect('p1.x', 'p.x')
root.connect('p2.y', 'p.y')
root.p1.x=3.0;
root.p2.y=-4.0;
top.setup()
top.run()
print(root.p.unknowns['f_xy'])
root.p1.x=5.0;
root.p2.y=5.0;
top.setup()
top.run()
print(root.p.unknowns['f_xy'])
You have to call setup() before you can set any values.
After that you set them via a dictionary like access from the problem instance. For your sample code it should look like:
top.setup()
top['p1.x'] = 3.
top['p2.y'] = 4.
top.run()
print(top['p.f_xy'])
top['p1.x'] = 10.
top['p2.y'] = 10.
top.run()
print(top['p.f_xy'])
When I run this model with the adjusted script I get:
##############################################
Setup: Checking for potential issues...
No recorders have been specified, so no data will be saved.
Setup: Check complete.
##############################################
73.0
342.0
I have devices connected to my serial port and I need to poll them and then display that data in a plot. I currently have this working (slowly) using matplotlib. I could have up to 64 devices connected and each device could have 20 pieces of data to update. I've set it up so that a new window can be created and a piece of data can be added to be plotted. With each additional plotting window that is opened my update rate slows considerably.
I've tried using blit animation in matplotlib, but it's not real smooth and I can see anomolies in the update. I've tried PyQtGraph, but can't find any documentation on how to use this package, and now I'm trying PyQwt, but can't get it installed (mostly because my company won't let us install a package that will handle a .gz file).
Any ideas or suggestions would be greatly appreciated.
import sys
from PyQt4.QtCore import (Qt, QModelIndex, QObject, SIGNAL, SLOT, QTimer, QThread, QSize, QString, QVariant)
from PyQt4 import QtGui
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from plot_toolbar import NavigationToolbar2QT as NavigationToolbar
import matplotlib.dates as md
import psutil as p
import time
import datetime as dt
import string
import ui_plotting
import pickle
try:
_fromUtf8 = QString.fromUtf8
except AttributeError:
_fromUtf8 = lambda s: s
class Monitor(FigureCanvas):
"""Plot widget to display real time graphs"""
def __init__(self, timenum):
self.timenum=timenum
self.main_frame = QtGui.QWidget()
self.timeTemp1 = 0
self.timeTemp2 = 0
self.temp = 1
self.placeHolder = []
self.y_max = 0
self.y_min = 100
# initialization of the canvas
# self.dpi = 100
# self.fig = Figure((5.0, 4.0), dpi=self.dpi)
self.fig = Figure()
FigureCanvas.__init__(self, self.fig)
# self.canvas = FigureCanvas(self.fig)
# self.canvas.setParent(self.main_frame)
# first image setup
# self.fig = Figure()
# self.fig.subplots_adjust(bottom=0.5)
self.ax = self.fig.add_subplot(111)
self.mpl_toolbar = NavigationToolbar(self.fig.canvas, self.main_frame,False)
self.mpl_toolbar.setFixedHeight(24)
# set specific limits for X and Y axes
# now=dt.datetime.fromtimestamp(time.mktime(time.localtime()))
# self.timenum = now.strftime("%H:%M:%S.%f")
self.timeSec = 0
self.x_lim = 100
self.ax.set_xlim(0, self.x_lim)
self.ax.set_ylim(0, 100)
self.ax.get_xaxis().grid(True)
self.ax.get_yaxis().grid(True)
# and disable figure-wide autoscale
self.ax.set_autoscale_on(False)
self.ax.set_xlabel('Time in Seconds')
# generates first "empty" plots
self.timeb = []
self.user = []
self.l_user = []
self.l_user = [[] for x in xrange(50)]
for i in range(50):
self.l_user[i], = self.ax.plot(0,0)
# add legend to plot
# self.ax.legend()
def addTime(self,t1,t2):
timeStamp = t1+"000"
# print "timeStamp",timeStamp
timeStamp2 = t2+"000"
test = string.split(timeStamp,":")
test2 = string.split(test[2],".")
testa = string.split(timeStamp2,":")
testa2 = string.split(testa[2],".")
sub1 = int(testa[0])-int(test[0])
sub2 = int(testa[1])-int(test[1])
sub3 = int(testa2[0])-int(test2[0])
sub4 = int(testa2[1])-int(test2[1])
testing = dt.timedelta(hours=sub1,minutes=sub2,seconds=sub3,microseconds=sub4)
self.timeSec = testing.total_seconds()
def timerEvent(self, evt, timeStamp, val, lines):
temp_min = 0
temp_max = 0
# Add user arrays for each user_l array used, don't reuse user arrays
if self.y_max<max(map(float, val)):
self.y_max = max(map(float, val))
if self.y_min>min(map(float, val)):
self.y_min = min(map(float, val))
# print "val: ",val
if lines[len(lines)-1]+1 > len(self.user):
for k in range((lines[len(lines)-1]+1)-len(self.user)):
self.user.append([])
# append new data to the datasets
# print "timenum=",self.timenum
self.addTime(self.timenum, timeStamp)
self.timeb.append(self.timeSec)
for j in range((lines[len(lines)-1]+1)):
if j >49:
break
if j not in lines:
del self.user[j][:]
self.user[j].extend(self.placeHolder)
self.user[j].append(0)
else:
if len(self.timeb) > (len(self.user[j])+1):
self.user[j].extend(self.placeHolder)
self.user[j].append(str(val[lines.index(j)]))
for i in range(len(lines)):
if i>49:
break
self.l_user[lines[i]].set_data(self.timeb, self.user[lines[i]])
# force a redraw of the Figure
# if self.y_max < 2:
# self.y_max = 2
# if self.y_min < 2:
# self.y_min = 0
if self.y_min > -.1 and self.y_max < .1:
temp_min = -1
temp_max = 1
else:
temp_min = self.y_min-(self.y_min/10)
temp_max = self.y_max+(self.y_max/10)
self.ax.set_ylim(temp_min, temp_max)
if self.timeSec >= self.x_lim:
if str(self.x_lim)[0]=='2':
self.x_lim = self.x_lim * 2.5
else:
self.x_lim = self.x_lim * 2
self.ax.set_xlim(0, self.x_lim)
# self.fig.canvas.restore_region(self.fig.canvas)
# self.ax.draw_artist(self.l_user[lines[0]])
# self.fig.canvas.blit(self.ax.bbox)
self.fig.canvas.draw()
# self.draw()
self.placeHolder.append(None)
class List(QtGui.QListWidget):
def __init__(self, parent):
super(List, self).__init__(parent)
font = QtGui.QFont()
font.setFamily(_fromUtf8("Century Gothic"))
font.setPointSize(7)
self.setFont(font)
self.setDragDropMode(4)
self.setAcceptDrops(True)
self.row = []
self.col = []
self.disName = []
self.lines = []
self.counter = 0
self.setStyleSheet("background-color:#DDDDDD")
self.colors = ["blue", "green", "red", "deeppink", "black", "slategray", "sienna", "goldenrod", "teal", "orange", "orchid", "lightskyblue", "navy", "darkgreen", "indigo", "firebrick", "deepskyblue", "lightskyblue", "darkseagreen", "gold"]
def dragEnterEvent(self, e):
if e.mimeData().hasFormat("application/x-qabstractitemmodeldatalist"):
# print "currentRow : ", self.currentRow()
# print "self.col: ", self.col
# print "self.row: ", self.row
# print "self.col[]: ", self.col.pop(self.currentRow())
# print "self.row[]: ", self.row.pop(self.currentRow())
self.col.pop(self.currentRow())
self.row.pop(self.currentRow())
self.disName.pop(self.currentRow())
self.lines.pop(self.currentRow())
self.takeItem(self.currentRow())
if e.mimeData().hasFormat("application/pubmedrecord"):
e.accept()
else:
e.ignore()
def dropEvent(self, e):
items = 0
data = e.mimeData()
bstream = data.retrieveData("application/pubmedrecord", QVariant.ByteArray)
selected = pickle.loads(bstream.toByteArray())
e.accept()
# print selected
# if self.count() != 0:
# j = (self.lines[self.count()-1]%len(self.colors))+1
# else:
# j=0
while items < len(selected):
j=self.counter
if j >= len(self.colors)-1:
j = self.counter%len(self.colors)
m = len(self.lines)
self.lines.append(self.counter)
# if m != 0:
# n = self.lines[m-1]
# self.lines.append(n+1)
# else:
# self.lines.append(0)
self.col.append(str(selected[items]))
items = items+1
self.row.append(str(selected[items]))
items = items+1
self.disName.append(str(selected[items]))
listItem = QtGui.QListWidgetItem()
listItem.setText(str(selected[items]))
listItem.setTextColor(QtGui.QColor(self.colors[j]))
self.addItem(listItem)
items = items+1
self.counter += 1
def dragLeaveEvent(self, event):
event.accept()
class PlotDlg(QtGui.QDialog):
NextID = 0
filename = 'Plot'
def __init__(self,time, callback, parent=None):
super(PlotDlg, self).__init__(parent)
self.id = PlotDlg.NextID
PlotDlg.NextID += 1
self.callback = callback
self.setWindowFlags(Qt.Window | Qt.WindowMinimizeButtonHint | Qt.WindowMaximizeButtonHint)
self.setAttribute(Qt.WA_DeleteOnClose,True)
self.value = []
print "time=",time
self.time = time
self.dc = Monitor(self.time)
# self.threadPool = []
self.listWidget = List(self)
sizePolicy = QtGui.QSizePolicy(QtGui.QSizePolicy.Fixed, QtGui.QSizePolicy.MinimumExpanding)
sizePolicy.setHorizontalStretch(0)
self.listWidget.setSizePolicy(sizePolicy)
self.listWidget.setMaximumSize(QSize(150, 16777215))
grid = QtGui.QGridLayout()
grid.setSpacing(0)
grid.setContentsMargins(0, 0, 0, 0)
grid.addWidget(self.dc.mpl_toolbar,0,0,1,12)
grid.addWidget(self.listWidget,1,1)
grid.addWidget(self.dc,1,0)
grid.setColumnMinimumWidth(1,110)
self.setLayout(grid)
def update(self, clear=0):
if clear == 1:
now=dt.datetime.fromtimestamp(time.mktime(time.localtime()))
self.dc.timenum = now.strftime("%H:%M:%S.%f")
self.dc.timeSec = 0
self.dc.x_lim = 100
self.dc.y_max = 0
self.dc.y_min = 100
del self.dc.timeb[:]
del self.dc.user[:]
del self.dc.placeHolder[:]
# del self.dc.l_user[:]
# self.dc.l_user = [[] for x in xrange(50)]
# for i in range(50):
# self.dc.l_user[i], = self.dc.ax.plot(0,0)
for i in range(50):
self.dc.l_user[i].set_data(0, 0)
# print self.dc.l_user
# print self.dc.user
self.dc.ax.set_xlim(0, self.dc.x_lim)
self.dc.fig.canvas.draw()
# print self.value
# print str(self.time)
# print "time:",str(self.time)
# self.threadPool.append( GenericThread(self.dc.timerEvent,None, str(self.time), self.value, self.listWidget.lines) )
# self.threadPool[len(self.threadPool)-1].start()
self.dc.timerEvent(None, str(self.time), self.value, self.listWidget.lines)
def closeEvent(self, event):
# self.update(1)
self.callback(self.id)
PlotDlg.NextID -= 1
class GenericThread(QThread):
def __init__(self, function, *args, **kwargs):
QThread.__init__(self)
self.function = function
self.args = args
self.kwargs = kwargs
def __del__(self):
self.wait()
def run(self):
self.function(*self.args,**self.kwargs)
return
The pyqtgraph website has a comparison of plotting libraries including matplotlib, chaco, and pyqwt. The summary is:
Matplotlib is the de-facto standard plotting library, but is not built for speed.
Chaco is built for speed but is difficult to install / deploy
PyQwt is currently abandoned
PyQtGraph is built for speed and easy to install
I've used matplotlib and PyQtGraph both extensively and for any sort of fast or 'real time' plotting I'd STRONGLY recommend PyQtGraph, (in one application I plot a data stream from an inertial sensor over a serial connection of 12 32-bit floats each coming in at 1 kHz and plot without noticeable lag.)
As previous folks have mentioned, installation of PyQtGraph is trivial, in my experience it displays and performs on both windows and linux roughly equivalently (minus window manager differences), and there's an abundance of demo code in the included examples to guide completion of almost any data plotting task.
The web documentation for PyQtGraph is admittedly less than desirable, but the source code is well commented and easy to read, couple that with well documented and diverse set of demo code and in my experience it far surpasses matplotlib in both ease of use and performance (even with the much more extensive online documentation for matplotlib).
I would suggest Chaco "... a package for building interactive and custom 2-D plots and visualizations." It can be integrated in Qt apps, though you can probably get higher frame rates from PyQwt.
I've actually used it to write an "app" (that's too big a word: it's not very fancy and it all fits in ~200 LOC) that gets data from a serial port and draws it (20 lines at over 20 fps, 50 at 15 fps, at full screen in my laptop).
Chaco documentation or online help weren't as comprehensive as matplotlib's, but I guess it will have improved and at any rate it was enough for me.
As a general advice, avoid drawing everything at every frame, ie., use the .set_data methods in both matplotlib and chaco. Also, here in stackoverflow there are some questions about making matplotlib faster.
Here is a way to do it using the animation function:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
fig, ax = plt.subplots()
data = np.zeros((32,100))
X = np.arange(data.shape[-1])
# Generate line plots
lines = []
for i in range(len(data)):
# Each plot each shifter upward
line, = ax.plot(X,i+data[i], color=".75")
lines.append(line)
# Set limits
ax.set_ylim(0,len(data))
ax.set_xlim(0,data.shape[-1]-1)
# Update function
def update(*args):
# Shift data left
data[:,:-1] = data[:,1:]
# Append new values
data[:,-1] = np.arange(len(data))+np.random.uniform(0,1,len(data))
# Update data
for i in range(len(data)):
lines[i].set_ydata(data[i])
ani = animation.FuncAnimation(fig, update,interval=10)
plt.show()