I am writing a simple digital image processing program. To do this I have embedded a mpl widget in my qt application. The user can perform some simple analysis on the image such as box car filter, FFT etc. Every thing is working fine until I would like to switch from displaying an image to displaying a plot.
If I display a plot first, the axis are fine (see bottom plot in image). But if I display an image first, followed by a plot (top plot in image), the scale compresses.
https://picasaweb.google.com/105163945296073520628/Temp <-- sorry I can't post images yet
The code is hosted here https://code.launchpad.net/~marrabld/pymi/trunk
I am using imshow() to display the image. and plot(x,y) for the plots.
This is the main update method
def updateImage(self):
self.ui.mplWidget.canvas.PlotTitle = self.plotTitle
self.ui.mplWidget.canvas.xtitle = self.xTitle
self.ui.mplWidget.canvas.ytitle = self.yTitle
#self.ui.mplWidget.canvas.ax.visible(False)
self.ui.mplWidget.canvas.format_labels()
if self.projectProperty == globals.IMAGE:
if self.lastProjectProperty == globals.PLOT:
self.myImage = imageFuncs.basic(self.imageFileName)
self.imPlot = self.ui.mplWidget.canvas.ax.imshow(self.myImage.image,cmap=matplotlib.cm.gray,origin='upper')
elif self.projectProperty == globals.PLOT:
if self.lastProjectProperty == globals.IMAGE: # we need to reload the GUI
self.ui.mplWidget.canvas.ax.hold(False)
self.ui.mplWidget.canvas.ax.plot(self.xData,self.yData)
self.ui.mplWidget.canvas.draw()
And the mpl widget I am using
#!/usr/bin/env python
from PyQt4.QtCore import *
from PyQt4.QtGui import *
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
#from matplotlib.backends.backend_qt4 import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backend_bases import NavigationToolbar2
from matplotlib.figure import Figure
from matplotlib import rc
import numpy as N
class MyMplCanvas(FigureCanvas):
def __init__(self, parent=None, width = 10, height = 12, dpi = 125, sharex = None, sharey = None):
rc('text', usetex=True)
rc('font', family='sans-serif')
rc('legend',fontsize='small' )
rc('legend',shadow='true')
self.fig = Figure(figsize = (width, height), dpi=dpi, facecolor = '#FFFFFF')
self.ax = self.fig.add_subplot(111, sharex = sharex, sharey = sharey)
self.fig.subplots_adjust(left=0.15, bottom=0.15, right=0.9, top=0.9)
self.fig.add_axes(yscale='symlog')
self.xtitle=r"x-Axis"
self.ytitle=r"y-Axis"
self.PlotTitle = r"Title"
self.grid_status = True
self.xaxis_style = 'linear'
self.yaxis_style = 'linear'
#self.fig.yscale = 'log'
self.format_labels()
self.ax.hold(True)
FigureCanvas.__init__(self, self.fig)
#self.fc = FigureCanvas(self.fig)
#FigureCanvas.setSizePolicy(self,
# QSizePolicy.Expanding,
# QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
def format_labels(self):
self.ax.set_title(self.PlotTitle)
self.ax.title.set_fontsize(5)
self.ax.set_xlabel(self.xtitle, fontsize = 4)
self.ax.set_ylabel(self.ytitle, fontsize = 4)
labels_x = self.ax.get_xticklabels()
labels_y = self.ax.get_yticklabels()
for xlabel in labels_x:
xlabel.set_fontsize(4)
for ylabel in labels_y:
ylabel.set_fontsize(4)
ylabel.set_color('b')
def sizeHint(self):
w, h = self.get_width_height()
return QSize(w, h)
def minimumSizeHint(self):
return QSize(10, 10)
def sizeHint(self):
w, h = self.get_width_height()
return QSize(w, h)
def minimumSizeHint(self):
return QSize(10, 10)
#mouseClick = pyqtProperty("QPoint",mouseClick,click)
class mplWidget(QWidget):
def __init__(self, parent = None):
QWidget.__init__(self, parent)
self.canvas = MyMplCanvas()
#self.toolbar = MyNavigationToolbar(self.canvas, self.canvas, direction = 'v')
self.hbox = QHBoxLayout()
#self.hbox.addWidget(self.toolbar)
self.hbox.addWidget(self.canvas)
self.setLayout(self.hbox)
def savePlot(self,filePath):
self.canvas.fig.savefig(filePath)
def setLegend(self,handle, label):
self.canvas.fig.legend(handle,label,'upper right')
def clearPlot(self):
self.canvas.fig.clear()
width = 10
height = 12
dpi = 125
sharex = None
sharey = None
self.canvas.fig = Figure(figsize = (width, height), dpi=dpi, facecolor = '#FFFFFF')
self.canvas.ax = self.canvas.fig.add_subplot(111, sharex = sharex, sharey = sharey)
self.canvas.fig.subplots_adjust(left=0.15, bottom=0.15, right=0.9, top=0.9)
self.canvas.fig.add_axes(yscale='symlog')
self.canvas.xtitle=r"x-Axis"
self.canvas.ytitle=r"y-Axis"
self.canvas.PlotTitle = r"Title"
self.canvas.grid_status = True
self.canvas.xaxis_style = 'linear'
self.canvas.yaxis_style = 'linear'
#self.fig.yscale = 'log'
self.canvas.format_labels()
self.canvas.ax.hold(True)
FigureCanvas.__init__(self.canvas, self.canvas.fig)
#self.fc = FigureCanvas(self.fig)
FigureCanvas.setSizePolicy(self,
QSizePolicy.Expanding,
QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
Any Help would be greatly appreciated.
you can use aspect parameter of imshow() to adjust the ratio between the height & weight:
from pylab import *
a = np.zeros((100,10)) # height=100, weight=10
subplot(211)
imshow(a) # ratio = 10
subplot(212)
imshow(a, aspect=0.1) # ratio = 1
show()
but it will stretch the image.
or you can use xlim(), ylim() the set the range of x-y axis.
imshow(a)
xlim(-50,50)
EDIT:
imshow() will set the aspect property of axe to "equal". you need reset it before calling plot():
self.ui.mplWidget.canvas.ax.set_aspect("auto")
self.ui.mplWidget.canvas.ax.plot(self.xData,self.yData)
Related
I am trying to remove an image from a figure and release the memory. when colorbar is not added for the image, memory can be released successfully, however, if colorbar is added, it fails. In the demo-code bellow:
click push button Add ColorBar will add a color bar for one image in the figure.
click push button remove will remove one image(and the related colorbar) from the figure.
each time i remove the image, the colorbar related is also removed, so i don't know why the memory recycle fails, I guess there must be some extra reference to the image when add a colorbar to it, which fails the memory recycle.
import numpy as np
from PyQt5 import QtWidgets
from memory_profiler import profile
import matplotlib
from matplotlib.figure import Figure
import matplotlib.cm as cm
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg
from matplotlib.axes._axes import Axes
matplotlib.use("Qt5Agg")
class MplCanvas(FigureCanvasQTAgg):
def __init__(self, parent=None, width=5, height=4, dpi=100):
self.fig = Figure(figsize=(width, height), dpi=dpi)
self.axe = self.fig.add_subplot(1, 1, 1, label='good')
super().__init__(self.fig)
class MainWindow(QtWidgets.QMainWindow):
def __init__(self):
super().__init__()
layout = QtWidgets.QVBoxLayout()
self.canvas = MplCanvas(self, width=5, height=4, dpi=100)
self.axe = self.canvas.axe
layout.addWidget(self.canvas)
self.pushButton_addColorBar = QtWidgets.QPushButton('Add ColorBar')
layout.addWidget(self.pushButton_addColorBar)
self.pushButton_remove = QtWidgets.QPushButton('remove')
layout.addWidget(self.pushButton_remove)
widget = QtWidgets.QWidget()
widget.setLayout(layout)
self.setCentralWidget(widget)
self.pushButton_remove.clicked.connect(self.removeImage)
self.pushButton_addColorBar.clicked.connect(self.createColorBar)
self.pcolormesh_test()
def pcolormesh_test(self):
"""add two images"""
delta = 0.01
x = y = np.arange(-3.0, 3.0, delta)
X, Y = np.meshgrid(x, y)
Z1 = np.exp(-X ** 2 - Y ** 2)
Z2 = np.exp(-(X - 1) ** 2 - (Y - 1) ** 2)
Z = (Z1 - Z2) * 2
im = self.axe.pcolormesh(X, Y, Z, cmap=cm.viridis, shading='auto')
im.set_clim(vmax=np.amax(Z), vmin=np.amin(Z))
Zx = (Z1 + Z2) * 2
imx = self.axe.pcolormesh(X, Y, Zx, cmap=cm.Blues, shading='auto')
imx.set_clim(vmax=np.amax(Zx), vmin=np.amin(Zx))
def createColorBar(self):
""" to create a color bar for an image. """
axe = self.axe
fig = axe.get_figure()
images = self.getImages(axe)
for image in images:
if not image.colorbar: # color bar doesn't exist
inset_axe = axe.inset_axes([1.0, 0, 0.05, 1], transform=axe.transAxes)
fig.colorbar(image, ax=axe, cax=inset_axe)
break # each trigger create one colorbar for one image
self.reDraw()
#profile
def removeImage(self, checked):
"""
Usage:
* each trigger remove one image
"""
images = self.getImages(self.axe)
# print(f'images={images}')
if images:
image = images[-1]
color_bar = image.colorbar
if color_bar:
color_bar.remove()
del color_bar
# remove image
image.remove()
del image
self.reDraw()
def getImages(self, axe: Axes):
"""to obtain the image list in the axe"""
images = []
images.extend(axe.images)
images.extend(axe.collections)
return images
def reDraw(self):
self.canvas.draw_idle()
self.canvas.flush_events()
if __name__ == '__main__':
import sys
app = QtWidgets.QApplication(sys.argv)
window = MainWindow()
window.show()
sys.exit(app.exec_())
I have found the solution, and post an answer to help.
we need to add gc.collect() at the end of removeImage() method. then the memory can be reclaimed when the image is removed.
So I'd like to integrate a matplotlib canvas in qt5 with manual blit.
I've found this thread:
Fast Live Plotting in Matplotlib / PyPlot
and the voted answer seems pretty nice however I need it in a qt5 window...
So I have tried to mash the code above together with the matplotlib qt5 tutorial into one script. https://matplotlib.org/gallery/user_interfaces/embedding_in_qt5_sgskip.html
It kinda works, however the animation only works when using the pan/zoom and the background is black :D and if blit is set to false it doesnt even draw...
If somebody could help me that would be amazing :) Its hilariously broken
from __future__ import unicode_literals
import random
import time
import matplotlib
from PyQt5.QtWidgets import QSizePolicy, QApplication, QWidget, QVBoxLayout
from matplotlib import pyplot as plt
import sys
import matplotlib
matplotlib.use('Qt5Agg')
from matplotlib.animation import FuncAnimation
from matplotlib.backends.backend_qt5agg import NavigationToolbar2QT as NavigationToolbar
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
import numpy as np
class MyMplCanvas(FigureCanvas):
# Ultimately, this is a QWidget (as well as a FigureCanvasAgg, etc.).
def __init__(self, parent=None, width=5, height=4, dpi=100):
self.fig = plt.figure()
FigureCanvas.__init__(self, self.fig)
self.setParent(parent)
FigureCanvas.setSizePolicy(self,
QSizePolicy.Expanding,
QSizePolicy.Expanding)
FigureCanvas.updateGeometry(self)
self.x = np.linspace(0, 50., num=100)
self.X, self.Y = np.meshgrid(self.x, self.x)
# self.fig = plt.figure()
self.ax1 = self.fig.add_subplot(2, 1, 1)
self.ax2 = self.fig.add_subplot(2, 1, 2)
self.img = self.ax1.imshow(self.X, vmin=-1, vmax=1, interpolation="None", cmap="RdBu")
self.line, = self.ax2.plot([], lw=3)
self.text = self.ax2.text(0.8, 0.5, "")
self.ax2.set_xlim(self.x.min(), self.x.max())
self.ax2.set_ylim([-1.1, 1.1])
self.t_start = time.time()
self.k = 0.
#self.fig.canvas.draw() # note that the first draw comes before setting data
#self.update(blit=False)
anim = FuncAnimation(self.fig, self.update, interval=20)
def update(self, blit=True):
if blit:
# cache the background
self.axbackground = self.fig.canvas.copy_from_bbox(self.ax1.bbox)
self.ax2background = self.fig.canvas.copy_from_bbox(self.ax2.bbox)
self.img.set_data(np.sin(self.X / 3. + self.k) * np.cos(self.Y / 3. + self.k))
self.line.set_data(self.x, np.sin(self.x / 3. + self.k))
self.k += 0.11
if blit:
# restore background
self.fig.canvas.restore_region(self.axbackground)
self.fig.canvas.restore_region(self.ax2background)
# redraw just the points
self.ax1.draw_artist(self.img)
self.ax2.draw_artist(self.line)
self.ax2.draw_artist(self.text)
# fill in the axes rectangle
self.fig.canvas.blit(self.ax1.bbox)
self.fig.canvas.blit(self.ax2.bbox)
# in this post http://bastibe.de/2013-05-30-speeding-up-matplotlib.html
# it is mentionned that blit causes strong memory leakage.
# however, I did not observe that.
else:
# redraw everything
self.fig.canvas.draw()
# self.fig.canvas.flush_events()
# alternatively you could use
# plt.pause(0.000000000001)
# however plt.pause calls canvas.draw(), as can be read here:
# http://bastibe.de/2013-05-30-speeding-up-matplotlib.html
class PlotDialog(QWidget):
def __init__(self):
QWidget.__init__(self)
self.plot_layout = QVBoxLayout(self)
self.plot_canvas = MyMplCanvas(self, width=5, height=4, dpi=100)
self.navi_toolbar = NavigationToolbar(self.plot_canvas, self)
self.plot_layout.addWidget(self.plot_canvas)
self.plot_layout.addWidget(self.navi_toolbar)
if __name__ == "__main__":
app = QApplication(sys.argv)
dialog0 = PlotDialog()
dialog0.show()
sys.exit(app.exec_())
Is it possible to replace Figure in FigureCanvas (see funcs plot & plot_data)?
I thought, it's possible to use fig.set_canvas(self) (see plot func), but it doesn't work.
PS: I know, it's possible to clear figure with self.axes.clear(), but it doesn't fit me. I'd like to save Figure in some map in the future (caching)
class Canvas(FigureCanvas):
def __init__(self, parent = None, width = 5, height = 5, dpi = 100):
self.fig_width = width
self.fig_height = height
self.fig_dpi = dpi
fig = Figure(figsize=(self.fig_width, self.fig_height), dpi=self.fig_dpi)
self.axes = fig.subplots(2,3)
FigureCanvas.__init__(self, fig)
self.setParent(parent)
def plot(self, datatest_data):
fig = self.plot_data(new_data)
fig.set_canvas(self)
def plot_data(self, new_data):
len_keys = len(new_data.index)
fig = Figure(figsize=(30, 5*len_keys), dpi=self.fig_dpi)
self.axes = fig.subplots(len_keys, 2)
.....
return fig
I want to display sensor data on a PyQT GUI with a matplotlib animation.
I already have a working Plot which gets updates every time I receive new sensor value from an external source with this code:
def __init__(self):
self.fig = Figure(figsize=(width, height), dpi=dpi)
self.axes = self.fig.add_subplot(111)
self.axes.grid()
self.xdata = []
self.ydata = []
self.entry_limit = 50
self.line, = self.axes.plot([0], [0], 'r')
def update_figure_with_new_value(self, xval: float, yval: float):
self.xdata.append(xval)
self.ydata.append(yval)
if len(self.xdata) > self.entry_limit:
self.xdata.pop(0)
self.ydata.pop(0)
self.line.set_data(self.xdata, self.ydata)
self.axes.relim()
self.axes.autoscale_view()
self.fig.canvas.draw()
self.fig.canvas.flush_events()
I want now to extend the plot to show another data series with the same x-axis. I tried to achieve this with the following additions to the init-code above:
self.axes2 = self.axes.twinx()
self.y2data = []
self.line2, = self.axes2.plot([0], [0], 'b')
and in the update_figure_with_new_value() function (for test purpose I just tried to add 1 to yval, I will extend the params of the function later):
self.y2data.append(yval+1)
if len(self.y2data) > self.entry_limit:
self.y2data.pop(0)
self.line2.set_data(self.xdata, self.ydata)
self.axes2.relim()
self.axes2.autoscale_view()
But instead of getting two lines in the plot which should have the exact same movement but just shifted by one I get vertical lines for the second plot axis (blue). The first axis (red) remains unchanged and is ok.
How can I use matplotlib to update multiple axis so that they display the right values?
I'm using python 3.4.0 with matplotlib 2.0.0.
Since there is no minimal example available, it's hard to tell the reason for this undesired behaviour. In principle ax.relim() and ax.autoscale_view() should do what you need.
So here is a complete example which works fine and updates both scales when being run with python 2.7, matplotlib 2.0 and PyQt4:
import numpy as np
import matplotlib.pyplot as plt
from PyQt4 import QtGui, QtCore
from matplotlib.figure import Figure
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as FigureCanvas
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
class Window(QtGui.QMainWindow):
def __init__(self):
QtGui.QMainWindow.__init__(self)
self.widget = QtGui.QWidget()
self.setCentralWidget(self.widget)
self.widget.setLayout(QtGui.QVBoxLayout())
self.widget.layout().setContentsMargins(0,0,0,0)
self.widget.layout().setSpacing(0)
self.fig = Figure(figsize=(5,4), dpi=100)
self.axes = self.fig.add_subplot(111)
self.axes.grid()
self.xdata = [0]
self.ydata = [0]
self.entry_limit = 50
self.line, = self.axes.plot([], [], 'r', lw=3)
self.axes2 = self.axes.twinx()
self.y2data = [0]
self.line2, = self.axes2.plot([], [], 'b')
self.canvas = FigureCanvas(self.fig)
self.canvas.draw()
self.nav = NavigationToolbar(self.canvas, self.widget)
self.widget.layout().addWidget(self.nav)
self.widget.layout().addWidget(self.canvas)
self.show()
self.ctimer = QtCore.QTimer()
self.ctimer.timeout.connect(self.update)
self.ctimer.start(150)
def update(self):
y = np.random.rand(1)
self.update_figure_with_new_value(self.xdata[-1]+1,y)
def update_figure_with_new_value(self, xval,yval):
self.xdata.append(xval)
self.ydata.append(yval)
if len(self.xdata) > self.entry_limit:
self.xdata.pop(0)
self.ydata.pop(0)
self.y2data.pop(0)
self.line.set_data(self.xdata, self.ydata)
self.axes.relim()
self.axes.autoscale_view()
self.y2data.append(yval+np.random.rand(1)*0.17)
self.line2.set_data(self.xdata, self.y2data)
self.axes2.relim()
self.axes2.autoscale_view()
self.fig.canvas.draw()
self.fig.canvas.flush_events()
if __name__ == "__main__":
qapp = QtGui.QApplication([])
a = Window()
exit(qapp.exec_())
You may want to test this and report back if it is working or not.
I am a real beginner in python and try to connect a qslider to a matplotlibwidget.
That means if I change the value of the slider the graph should change. It seems that the value changes correctly, while the graph stays the same. Can anyone tell me how to connect the change of the slider with the graph? Here is my algorithm so far:
# -*- coding: utf-8 -*-
"""
Created on Tue Feb 04 16:48:12 2014
#author: Christoph
"""
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as Canvas
from matplotlib.figure import Figure
from matplotlib import rcParams
import numpy as np
import scipy.constants as const
import sys
rcParams['font.size'] = 9
class MatplotlibWidget(Canvas):
"""
MatplotlibWidget inherits PyQt4.QtGui.QWidget
and matplotlib.backend_bases.FigureCanvasBase
Options: option_name (default_value)
-------
parent (None): parent widget
title (''): figure title
xlabel (''): X-axis label
ylabel (''): Y-axis label
xlim (None): X-axis limits ([min, max])
ylim (None): Y-axis limits ([min, max])
xscale ('linear'): X-axis scale
yscale ('linear'): Y-axis scale
width (4): width in inches
height (3): height in inches
dpi (100): resolution in dpi
hold (False): if False, figure will be cleared each time plot is called
Widget attributes:
-----------------
figure: instance of matplotlib.figure.Figure
axes: figure axes
Example:
-------
self.widget = MatplotlibWidget(self, yscale='log', hold=True)
from numpy import linspace
x = linspace(-10, 10)
self.widget.axes.plot(x, x**2)
self.wdiget.axes.plot(x, x**3)
"""
def __init__(self, parent=None, title='', xlabel='', ylabel='',
xlim=None, ylim=None, xscale='linear', yscale='linear',
width=4, height=3, dpi=100, hold=False):
self.figure = Figure(figsize=(width, height), dpi=dpi)
self.axes = self.figure.add_subplot(111)
self.axes.set_title(title)
self.axes.set_xlabel(xlabel)
self.axes.set_ylabel(ylabel)
if xscale is not None:
self.axes.set_xscale(xscale)
if yscale is not None:
self.axes.set_yscale(yscale)
if xlim is not None:
self.axes.set_xlim(*xlim)
if ylim is not None:
self.axes.set_ylim(*ylim)
self.axes.hold(hold)
Canvas.__init__(self, self.figure)
self.setParent(parent)
Canvas.setSizePolicy(self, QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Expanding)
Canvas.updateGeometry(self)
def sizeHint(self):
w, h = self.get_width_height()
return QtGui.QSize(w, h)
def minimumSizeHint(self):
return QtGui.QSize(10, 10)
class ApplicationWindow(QtGui.QMainWindow):
def __init__(self):
QtGui.QMainWindow.__init__(self)
# Graphics Window
self.mpl = MatplotlibWidget(self, title='Graph',
xlabel='x',
ylabel='y',
hold=True)
self.mpl.setGeometry(0,0,1300,800)
self.setGeometry(0, 30, 1680, 800)
# Slider Resistance
title1=QtGui.QLabel(self)
title1.setText('R')
title1.move(1400,10)
self.value1=QtGui.QLabel(self)
self.value1.setText('1')
self.value1.move(1550,40)
cb=QtGui.QSlider(QtCore.Qt.Horizontal, self)
cb.setGeometry(1400,40,100,30)
cb.setMinimum(1)
cb.setMaximum(10000)
cb.valueChanged.connect(self.Rout)
self.plot(1, self.mpl.axes)
def Rout(self, position):
self.value1.setText('%i' %position)
self.plot(position, self.mpl.axes)
def plot(self, R, axes):
x=np.linspace(0,5,1001)
B=0.035
n1=0.115
H=2.06227451e-15
n2=1.37040209e-01
gamma=0.001*const.e
C=0.13
x=np.array(x)
diodetheo = H*(np.exp((const.e*x*n2)/(const.k*300))-1)
zaehler = 1+np.exp((B-C+n1*x)*const.e/(const.k*300))
nenner = 1+np.exp((B-C-n1*x)*const.e/(const.k*300))
A=8.7476434*10**(29)*gamma
D=gamma/2
klammer2 = (const.pi/2)+np.arctan((C-n1*x)/D)
y1 = A*np.log(zaehler/nenner)*klammer2
# plt.figure()
# plt.plot(x, diodetheo, 'g')
# plt.show()
indup=[]
inddown=[]
iup=[]
idown=[]
theo = (y1+diodetheo)*(10**(-12))*(100)/4
for i, Volt in enumerate(x):
xup=np.linspace(0,Volt,i+1)
last=Volt/R-xup/R
diff=np.array(last)-np.array(theo[0:i+1])
inter=np.where(np.diff(np.sign(diff)))[0]
if inter.size==0:
inter=np.array([0])
indup.append(inter[0])
inddown.append(inter[-1])
iup.append(theo[inter[0]])
idown.append(theo[inter[-1]])
up = np.array(iup)
down = np.array(idown)
down=np.flipud(down)
ytotal=np.concatenate((up, down))
xneg=np.flipud(x)
xtotal=np.concatenate((x,xneg))
#plt.figure()
#plt.plot(xtotal, ytotal, 'g')
#plt.show()
axes.plot(xtotal, ytotal, 'r')
if __name__ == '__main__':
app = QtGui.QApplication(sys.argv)
win = ApplicationWindow()
win.show()
sys.exit(app.exec_())
Greetings
Christoph
OK I've made some changes to your code in order to make it works:
Change the function definition def plot(self, R, axes): for def plot(self, R):
Change the call self.plot(position, self.mpl.axes) on Rout accordingly to self.plot(position)
Change the final line axes.plot(xtotal, ytotal, 'r') on the previous plot function by:
self.mpl.axes.clear() #clear the previous plot
self.mpl.axes.plot(xtotal, ytotal, 'r') #replot
self.mpl.figure.canvas.draw() #redraw the canvas
Explanations:
First, you don't need to pass the axes to the plot function if it's already an attribute of self.mpl and is easy accessible. Second, when you make another plot you need to clear the previous one and also refresh the canvas.
Next all the code with modifications for easy use of copy-paste:
from PyQt4 import QtGui, QtCore
from matplotlib.backends.backend_qt4agg import FigureCanvasQTAgg as Canvas
from matplotlib.figure import Figure
from matplotlib import rcParams
import numpy as np
import scipy.constants as const
import sys
rcParams['font.size'] = 9
class MatplotlibWidget(Canvas):
"""
MatplotlibWidget inherits PyQt4.QtGui.QWidget
and matplotlib.backend_bases.FigureCanvasBase
Options: option_name (default_value)
-------
parent (None): parent widget
title (''): figure title
xlabel (''): X-axis label
ylabel (''): Y-axis label
xlim (None): X-axis limits ([min, max])
ylim (None): Y-axis limits ([min, max])
xscale ('linear'): X-axis scale
yscale ('linear'): Y-axis scale
width (4): width in inches
height (3): height in inches
dpi (100): resolution in dpi
hold (False): if False, figure will be cleared each time plot is called
Widget attributes:
-----------------
figure: instance of matplotlib.figure.Figure
axes: figure axes
Example:
-------
self.widget = MatplotlibWidget(self, yscale='log', hold=True)
from numpy import linspace
x = linspace(-10, 10)
self.widget.axes.plot(x, x**2)
self.wdiget.axes.plot(x, x**3)
"""
def __init__(self, parent=None, title='', xlabel='', ylabel='',
xlim=None, ylim=None, xscale='linear', yscale='linear',
width=4, height=3, dpi=100, hold=False):
self.figure = Figure(figsize=(width, height), dpi=dpi)
self.axes = self.figure.add_subplot(111)
self.axes.set_title(title)
self.axes.set_xlabel(xlabel)
self.axes.set_ylabel(ylabel)
if xscale is not None:
self.axes.set_xscale(xscale)
if yscale is not None:
self.axes.set_yscale(yscale)
if xlim is not None:
self.axes.set_xlim(*xlim)
if ylim is not None:
self.axes.set_ylim(*ylim)
self.axes.hold(hold)
Canvas.__init__(self, self.figure)
self.setParent(parent)
Canvas.setSizePolicy(self, QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Expanding)
Canvas.updateGeometry(self)
def sizeHint(self):
w, h = self.get_width_height()
return QtGui.QSize(w, h)
def minimumSizeHint(self):
return QtGui.QSize(10, 10)
class ApplicationWindow(QtGui.QMainWindow):
def __init__(self):
QtGui.QMainWindow.__init__(self)
# Graphics Window
self.mpl = MatplotlibWidget(self, title='Graph',
xlabel='x',
ylabel='y',
hold=True)
self.mpl.setGeometry(0,0,1300,800)
self.setGeometry(0, 30, 1680, 800)
# Slider Resistance
title1=QtGui.QLabel(self)
title1.setText('R')
title1.move(1400,10)
self.value1=QtGui.QLabel(self)
self.value1.setText('1')
self.value1.move(1550,40)
cb=QtGui.QSlider(QtCore.Qt.Horizontal, self)
cb.setGeometry(1400,40,100,30)
cb.setMinimum(1)
cb.setMaximum(10000)
cb.valueChanged.connect(self.Rout)
self.plot(1)
def Rout(self, position):
self.value1.setText('%i' %position)
self.plot(position)
def plot(self, R):
x=np.linspace(0,5,1001)
B=0.035
n1=0.115
H=2.06227451e-15
n2=1.37040209e-01
gamma=0.001*const.e
C=0.13
x=np.array(x)
diodetheo = H*(np.exp((const.e*x*n2)/(const.k*300))-1)
zaehler = 1+np.exp((B-C+n1*x)*const.e/(const.k*300))
nenner = 1+np.exp((B-C-n1*x)*const.e/(const.k*300))
A=8.7476434*10**(29)*gamma
D=gamma/2
klammer2 = (const.pi/2)+np.arctan((C-n1*x)/D)
y1 = A*np.log(zaehler/nenner)*klammer2
# plt.figure()
# plt.plot(x, diodetheo, 'g')
# plt.show()
indup=[]
inddown=[]
iup=[]
idown=[]
theo = (y1+diodetheo)*(10**(-12))*(100)/4
for i, Volt in enumerate(x):
xup=np.linspace(0,Volt,i+1)
last=Volt/R-xup/R
diff=np.array(last)-np.array(theo[0:i+1])
inter=np.where(np.diff(np.sign(diff)))[0]
if inter.size==0:
inter=np.array([0])
indup.append(inter[0])
inddown.append(inter[-1])
iup.append(theo[inter[0]])
idown.append(theo[inter[-1]])
up = np.array(iup)
down = np.array(idown)
down=np.flipud(down)
ytotal=np.concatenate((up, down))
xneg=np.flipud(x)
xtotal=np.concatenate((x,xneg))
#plt.figure()
#plt.plot(xtotal, ytotal, 'g')
#plt.show()
self.mpl.axes.clear()
self.mpl.axes.plot(xtotal, ytotal, 'r')
self.mpl.figure.canvas.draw()
if __name__ == '__main__':
app = QtGui.QApplication(sys.argv)
win = ApplicationWindow()
win.show()
sys.exit(app.exec_())