/usr/lib/python2.7/dist-packages/pyqtgraph/examples/scrollingPlots.py is in python-pyqtgraph 0.9.10-5.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | # -*- coding: utf-8 -*-
"""
Various methods of drawing scrolling plots.
"""
import initExample ## Add path to library (just for examples; you do not need this)
import pyqtgraph as pg
from pyqtgraph.Qt import QtCore, QtGui
import numpy as np
win = pg.GraphicsWindow()
win.setWindowTitle('pyqtgraph example: Scrolling Plots')
# 1) Simplest approach -- update data in the array such that plot appears to scroll
# In these examples, the array size is fixed.
p1 = win.addPlot()
p2 = win.addPlot()
data1 = np.random.normal(size=300)
curve1 = p1.plot(data1)
curve2 = p2.plot(data1)
ptr1 = 0
def update1():
global data1, curve1, ptr1
data1[:-1] = data1[1:] # shift data in the array one sample left
# (see also: np.roll)
data1[-1] = np.random.normal()
curve1.setData(data1)
ptr1 += 1
curve2.setData(data1)
curve2.setPos(ptr1, 0)
# 2) Allow data to accumulate. In these examples, the array doubles in length
# whenever it is full.
win.nextRow()
p3 = win.addPlot()
p4 = win.addPlot()
# Use automatic downsampling and clipping to reduce the drawing load
p3.setDownsampling(mode='peak')
p4.setDownsampling(mode='peak')
p3.setClipToView(True)
p4.setClipToView(True)
p3.setRange(xRange=[-100, 0])
p3.setLimits(xMax=0)
curve3 = p3.plot()
curve4 = p4.plot()
data3 = np.empty(100)
ptr3 = 0
def update2():
global data3, ptr3
data3[ptr3] = np.random.normal()
ptr3 += 1
if ptr3 >= data3.shape[0]:
tmp = data3
data3 = np.empty(data3.shape[0] * 2)
data3[:tmp.shape[0]] = tmp
curve3.setData(data3[:ptr3])
curve3.setPos(-ptr3, 0)
curve4.setData(data3[:ptr3])
# 3) Plot in chunks, adding one new plot curve for every 100 samples
chunkSize = 100
# Remove chunks after we have 10
maxChunks = 10
startTime = pg.ptime.time()
win.nextRow()
p5 = win.addPlot(colspan=2)
p5.setLabel('bottom', 'Time', 's')
p5.setXRange(-10, 0)
curves = []
data5 = np.empty((chunkSize+1,2))
ptr5 = 0
def update3():
global p5, data5, ptr5, curves
now = pg.ptime.time()
for c in curves:
c.setPos(-(now-startTime), 0)
i = ptr5 % chunkSize
if i == 0:
curve = p5.plot()
curves.append(curve)
last = data5[-1]
data5 = np.empty((chunkSize+1,2))
data5[0] = last
while len(curves) > maxChunks:
c = curves.pop(0)
p5.removeItem(c)
else:
curve = curves[-1]
data5[i+1,0] = now - startTime
data5[i+1,1] = np.random.normal()
curve.setData(x=data5[:i+2, 0], y=data5[:i+2, 1])
ptr5 += 1
# update all plots
def update():
update1()
update2()
update3()
timer = pg.QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)
## Start Qt event loop unless running in interactive mode or using pyside.
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
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