Look at the scrolling plot example you have in the examples directory.
Original rows are:
curve1 = p1.plot(data1)
curve2 = p2.plot(data1)
This make exception:
curve1 = p1.plot(data1, stepMode = True)
This also make exception:
curve2 = p2.plot(data1, stepMode = True)
>From documentation:
http://www.pyqtgraph.org/documentation/graphicsItems/plotcurveitem.html
*stepMode If True, two orthogonal lines are drawn for each sample as steps.
This is commonly used when drawing histograms. Note that in this case,
len(x) == len(y) + 1*
*so, if you decide to use curve2 with stepMode enabled, initialize it
with:*curve2
= p2.plot(stepMode = True) # without data1 as parameter!!!
*and be sure that you calling setData for curve2 (for example)
as:*curve2.setData(y=data1,
x=range(len(data1)+1))
On Wed, Feb 8, 2017 at 2:38 PM, Marija Zupunski <[email protected]>
wrote:
> Vasilije, I tried that but I think that is not a problem.
>
> Here is what I have tried and some of my conclusions:
>
> 1. *setDownsampling(ds=True, auto=False, mode='peak')* method should be
> called only after creating PlotItem not after every plot()
> 2. attribute *auto *must be False, otherwise I have exception earlier
> mention
> 3. I tried calling method *setClipToView(True) *also only after creating
> PlotItem
> (not after every plot) but no luck - same exception ("len(X) must be
> len(Y)+1 since stepMode=True")
>
> So downsampling just once and not using clip to view solves exception in
> use case where I want to plot two PlotDataItem (one has stepMode=True,
> other=False) on same PlotItem.
>
> Also when I had exception there is also some ignored exceptions that
> weren't by biggest problem but I would point that out.
>
>
> On Wednesday, February 8, 2017 at 12:32:44 AM UTC+1, Vasilije Mehandzic
> wrote:
>>
>>
>> On Tue, Feb 7, 2017 at 5:38 PM, Marija Zupunski <[email protected]>
>> wrote:
>>
>>> setClipToView
>>
>>
>>
>> Maybe to try wih *setClipToView(True)* without 'clip='?
>>
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# -*- coding: utf-8 -*-
"""
Various methods of drawing scrolling plots.
"""
#~
www.pyqtgraph.org\downloads\0.10.0\pyqtgraph-0.10.0-deb\pyqtgraph-0.10.0\examples\scrollingPlots.py
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_()
# -*- coding: utf-8 -*-
"""
Various methods of drawing scrolling plots.
"""
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(stepMode = True)
curve2.setData(y=data1, x=range(len(data1)+1))
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(y=data1, x=range(len(data1)+1))
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_()
