[image: image.png]Hi Guys, how are you?
I am so sorry, this is the new version of my code, I am trying to plot just
one graph with the data which come from the serial port (PORT8),
This is the code:
from pyqtgraph.Qt import QtGui, QtCore
from pyqtgraph.ptime import time
import numpy as np
import pyqtgraph as pg
import serial
app = QtGui.QApplication([])
p = pg.plot()
p.setWindowTitle('live plot from serial')
curve = p.plot()
data = [0]
raw=serial.Serial("COM8",115200)
def leer():
while True:
line = raw.readline()
line=str(line)
line=line.split(' ')
if len(line)>4:
line=line[2]
line=int(line)
return(line)
else:
continue
def update():
global curve, data
data.append(int(leer()))
curve.setData(data)
app.processEvents()
timer = QtCore.QTimer()
timer.timeout.connect(update)
timer.start(50)
if __name__ == '__main__':
import sys
if (sys.flags.interactive != 1) or not hasattr(QtCore, 'PYQT_VERSION'):
QtGui.QApplication.instance().exec_()
raw.close()
And I always get the same answer from the program:
[image: image.png]
El sáb., 6 jul. 2019 a las 16:29, <[email protected]> escribió:
> Hi again,
>
> I have no your serial device, but your app should looks like:
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> *import pyqtgraph as pgimport randomapp = pg.Qt.QtGui.QApplication([]) p =
> pg.plot()p.setWindowTitle('live plot from random')curve = p.plot()data =
> [0]while p.isVisible(): line = random.randint(0, 255)
> data.append(int(line)) xdata = np.array(data, dtype='int32')
> curve.setData(xdata) app.processEvents()*
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>
> So you could start with this code:
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> *import numpy as npimport pyqtgraph as pgimport serialapp =
> pg.Qt.QtGui.QApplication([]) p = pg.plot()p.setWindowTitle('live plot from
> serial')curve = p.plot()data = [0]raw=serial.Serial("COM8",115200)while
> p.isVisible(): line = raw.readline() line=str(line)
> line=line.split(' ') if len(line)>4: line=line[2]
> line=int(line) else: continue data.append(int(line))
> xdata = np.array(data, dtype='int32') curve.setData(xdata)
> app.processEvents()*
>
>
> Next thing is probably to implement Marc's idea of initialization of a
> larger array.
>
> Cheers,
> Vasilije
>
>
>
> On Sat, Jul 6, 2019 at 10:16 AM Marc Le Roy <[email protected]> wrote:
>
>> I would add that this line of code is highly inefficient since a new
>> array of increasing size is created at each update:
>> xdata = np.array(data, dtype='float64')
>>
>> I would allocate a large array at initialization, and if required
>> increase its size using numpy.ndarray.resize with a strategy avoiding to do
>> it too frequently.
>>
>> Marc
>>
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--
*Wilmer Contreras Sepulveda*
*Grupo de Investigación en Desarrollo de Microelectronica Aplicada*
*Universidad Francisco de Paula Santander *
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