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I am trying to update the plot after a new file is selected, but the new plot that is generated it has the points that are of previous plot on both X and Y axis, I don't want to those previous points, please anyone explain why this happens so and how to get rid of this. Images are shown here, previous plot is
after this I choose to select second file with different data to plot it, next plot is this image
The code I am trying to build is
import matplotlib.pyplot as plt
from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as FigureCanvas
from PyQt5.QtWidgets import (QApplication, QWidget, QFileDialog, QPushButton, QLabel, QGridLayout, QVBoxLayout, QLineEdit)
from Bio import SeqIO
from collections import Counter
from Bio.SeqUtils import molecular_weight
from Bio.SeqUtils import GC
class MainWindow(QWidget):
def __init__(self):
super().__init__()
self.setWindowTitle("DNA Sequence Analysis - Prashik Lokhande")
self.setLayout(QVBoxLayout())
my_label = QLabel("DNA Sequence Analysis from the FASTA Database, (FASTA databse can be found on NCBI website). Build by Prashik Lokhande")
self.layout().addWidget(my_label)
self.visualize()
self.show()
def visualize(self):
container = QWidget()
container.setLayout(QGridLayout())
label_1 = QLabel("PLease Select FASTA file")
button_1 = QPushButton("Select file", clicked = lambda: self.get_plot())
gc_count_label = QLabel("GC Count = ")
self.gc_count_field = QLabel("0")
self.canvas = FigureCanvas(plt.Figure(figsize=(10, 4)))
container.layout().addWidget(label_1, 0,0)
container.layout().addWidget(button_1, 1,0)
container.layout().addWidget(gc_count_label, 2, 1)
container.layout().addWidget(self.gc_count_field, 3, 1)
container.layout().addWidget(self.canvas, 2, 0, 3, 1)
self.layout().addWidget(container)
def get_plot(self):
filepath, _ = QFileDialog.getOpenFileName(self, 'select FASTA file')
record = SeqIO.read(filepath,"fasta")
dna = record.seq
mrna = dna.transcribe()
protein = mrna.translate()
self.mol_weight = molecular_weight(dna)
gc = GC(dna)
self.gc_count_field.setText(str(gc))
pr_freq = Counter(protein)
self.ax = self.canvas.figure.subplots()
self.ax.bar(pr_freq.keys(), pr_freq.values())
self.ax.set_title("Amino Acid Contents in the sequence (X-axis Amino acids, Y-axis frequency)")
app = QApplication([])
mw = MainWindow()
app.exec_()
Every time you press the button, self.ax = self.canvas.figure.subplots() will create a new set of axes and add it at the (0,0) position in the grid of previously created subplots. Since all subplots are placed at the same position in the grid they all overlap. To get around this, you could just create one set of axes in MainWindow.__init__, and reuse this one in MainWidon.get_plot, i.e.
class MainWindow(QWidget):
def __init__(self):
....
self.ax = self.canvas.figure.subplots()
def get_plot(self):
....
# clear previous plot
self.ax.clear()
self.ax.bar(pr_freq.keys(), pr_freq.values())
....
I'm creating a GUI to allow users to see a "live view" of a spectrometer where data is taken from the spectrometer and plotted in Matplotlib to be displayed in the GUI window. The GUI also has a few other buttons which allow the user to go through other functions (irrelevant but just background).
I've gotten the live view to work in matplotlib using a while loop and clearing the data to re-plot:
while True:
data = ccs.take_data(num_avg=3) # spectrometer function
norm = (data[0]-dark[0])/(light[0]-dark[0]) # some calcs.
plt.plot(data[1],norm)
plt.axis([400,740,0,1.1])
plt.grid(color='w', linestyle='--')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Normalized Intesity')
plt.pause(0.1)
plt.cla()
Next step was to show this figure in PySimpleGUI. Harder than expexted... I was able to use a few demo codes from PySimpleGUI to get a single figure to appear and update if user presses 'update' button:
from instrumental.drivers.spectrometers import thorlabs_ccs
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import PySimpleGUI as sg
import matplotlib, time, threading
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
def fig_maker(ccs, dark, sub):
plt.clf()
plt.close()
data = ccs.take_data(num_avg=3)
norm = (data[0]-dark[0])/(sub[0]-dark[0])
plt.plot(data[1],norm,c='r')
plt.axis([400,750,0,1.1])
plt.grid(color='w', linestyle='--')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Normalized Intesity')
return plt.gcf()
def draw_figure(canvas, figure, loc=(0, 0)):
figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
figure_canvas_agg.draw()
figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1)
return figure_canvas_agg
def delete_fig_agg(fig_agg):
fig_agg.get_tk_widget().forget()
plt.close('all')
if __name__ == '__main__':
... some code ...
# define the window layout
layout = [[sg.Button('update')],
[sg.Text('Plot test', font='Any 18')],
[sg.Canvas(size=(500,500), key='canvas')] ]
# create the form and show it without the plot
window = sg.Window('Demo Application - Embedding Matplotlib In PySimpleGUI',
layout, finalize=True)
fig_agg = None
while True:
event, values = window.read()
if event is None: # if user closes window
break
if event == "update":
if fig_agg is not None:
delete_fig_agg(fig_agg)
fig = fig_maker(ccs,dark,sub)
fig_agg = draw_figure(window['canvas'].TKCanvas, fig)
window.close()
Now for the fun part (I can't seem to get it to work). I would like the plot to always be updating similar to how I did it using just matplotlib so that the user doesn't have to press 'update'. Using PySimpleGUI long_task threaded example is where my program starts to fail. I don't actually get any errors thrown except for a print to the Debug I/O stating *** Faking Timeout *** before Python closes the script.
I even just tried to do a for loop of 10 iterations instead of continuous while loop:
from instrumental.drivers.spectrometers import thorlabs_ccs
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import PySimpleGUI as sg
import matplotlib, time, threading
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
def long_function_thread(window, ccs, dark, sub):
for i in range(10):
fig = fig_maker(ccs, dark, sub)
fig_agg = draw_figure(window['canvas'].TKCanvas, fig)
window.write_event_value('-THREAD PROGRESS-', i)
time.sleep(1)
delete_fig_agg(fig_agg)
time.sleep(0.1)
window.write_event_value('-THREAD DONE-', '')
def long_function(window, ccs, dark, sub):
print('In long_function')
threading.Thread(target=long_function_thread, args=(window, ccs, dark, sub), daemon=True).start()
def fig_maker(ccs, dark, sub):
plt.clf()
plt.close()
data = ccs.take_data(num_avg=3)
norm = (data[0]-dark[0])/(sub[0]-dark[0])
plt.plot(data[1],norm,c='r')
plt.axis([400,750,0,1.1])
plt.grid(color='w', linestyle='--')
plt.xlabel('Wavelength [nm]')
plt.ylabel('Normalized Intesity')
return plt.gcf()
def draw_figure(canvas, figure, loc=(0, 0)):
figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
figure_canvas_agg.draw()
figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1)
return figure_canvas_agg
def delete_fig_agg(fig_agg):
fig_agg.get_tk_widget().forget()
plt.close('all')
if __name__ == '__main__':
... some code ...
# define the window layout
layout = [[sg.Button('Go')],
[sg.Text('Plot test', font='Any 18')],
[sg.Canvas(size=(500,500), key='canvas')] ]
# create the form and show it without the plot
window = sg.Window('Demo Application - Embedding Matplotlib In PySimpleGUI',
layout, finalize=True)
fig_agg = None
while True:
event, values = window.read()
if event is None or event == 'Exit':
break
if event == 'Go':
print('Calling plotter')
long_function(window, ccs, dark, sub)
print('Long function has returned from starting')
elif event == '-THREAD DONE-':
print('Your long operation completed')
window.close()
Appologies on the long description and code dump but I thought this is the easiest way to explain. Any help or links on this issue would be greatly appreciated.
If someone wants to try and run my script this should just produce a random plot instead
def random_fig_maker():
plt.scatter(np.random.rand(1,10),np.random.rand(1,10))
return plt.gcf()
You need to use two additional PySimpleGUI features: window.Refresh() and window.write_event_value(). When you deleted figg_agg and the new plot is ready, call window.Refresh(). This will redraw the window, but also introduces a problem: the main event (while) loop will keep running forever. To address this, you also need to add window.write_event_value('-THREAD-', 'some message.') to one of the functions that is called from within the event loop. This will act as an external trigger for the event loop to keep running, but this will also keep the window responsive, so you can change some other window element (here I used a radio switch) to stop the loop.
For bonus points, you can also run the "trigger function" as a separate thread. Then, time.sleep() in that function will not affect GUI responsiveness. Because of this, I would use some data gathering function that only returns some lists or tuples as the trigger for restarting the loop. In this case, matplotlib was unhappy about being called from an external thread, so I just added a delay in the event loop to keep the plot visible.
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import PySimpleGUI as sg
import matplotlib, time, threading
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt
import numpy as np
def fig_maker(window): # this should be called as a thread, then time.sleep() here would not freeze the GUI
plt.scatter(np.random.rand(1,10),np.random.rand(1,10))
window.write_event_value('-THREAD-', 'done.')
time.sleep(1)
return plt.gcf()
def draw_figure(canvas, figure, loc=(0, 0)):
figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
figure_canvas_agg.draw()
figure_canvas_agg.get_tk_widget().pack(side='top', fill='both', expand=1)
return figure_canvas_agg
def delete_fig_agg(fig_agg):
fig_agg.get_tk_widget().forget()
plt.close('all')
if __name__ == '__main__':
# define the window layout
layout = [[sg.Button('update'), sg.Button('Stop', key="-STOP-"), sg.Button('Exit', key="-EXIT-")],
[sg.Radio('Keep looping', "RADIO1", default=True, size=(12,3),key="-LOOP-"),sg.Radio('Stop looping', "RADIO1", size=(12,3), key='-NOLOOP-')],
[sg.Text('Plot test', font='Any 18')],
[sg.Canvas(size=(500,500), key='canvas')]]
# create the form and show it without the plot
window = sg.Window('Demo Application - Embedding Matplotlib In PySimpleGUI',
layout, finalize=True)
fig_agg = None
while True:
event, values = window.read()
if event is None: # if user closes window
break
if event == "update":
if fig_agg is not None:
delete_fig_agg(fig_agg)
fig = fig_maker(window)
fig_agg = draw_figure(window['canvas'].TKCanvas, fig)
if event == "-THREAD-":
print('Acquisition: ', values[event])
time.sleep(1)
if values['-LOOP-'] == True:
if fig_agg is not None:
delete_fig_agg(fig_agg)
fig = fig_maker(window)
fig_agg = draw_figure(window['canvas'].TKCanvas, fig)
window.Refresh()
if event == "-STOP-":
window['-NOLOOP-'].update(True)
if event == "-EXIT-":
break
window.close()
It's not exactly connected but I had a similar problem. Does this help....
import PySimpleGUI as sg
import matplotlib.pyplot as plt
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import numpy as np
class updateable_matplotlib_plot():
def __init__(self, canvas) -> None:
self.fig_agg = None
self.figure = None
self.canvas = canvas
def plot(self, data):
self.data = data
self.figure_controller()
self.figure_drawer()
#put all of your normal matplotlib stuff in here
def figure_controller(self):
#first run....
if self.figure is None:
self.figure = plt.figure()
self.axes = self.figure.add_subplot(111)
self.line, = self.axes.plot(self.data)
self.axes.set_title("Example of a Matplotlib plot updating in PySimpleGUI")
#all other runs
else:
self.line.set_ydata(self.data)#update data
self.axes.relim() #scale the y scale
self.axes.autoscale_view() #scale the y scale
#finally draw the figure on a canvas
def figure_drawer(self):
if self.fig_agg is not None: self.fig_agg.get_tk_widget().forget()
self.fig_agg = FigureCanvasTkAgg(self.figure, self.canvas.TKCanvas)
self.fig_agg.get_tk_widget().pack(side='top', fill='both', expand=1)
self.fig_agg.draw()
def getGUI():
# All the stuff inside your window.
layout = [ [sg.Canvas(size=(500,500), key='canvas')],
[sg.Button('Update', key='update'), sg.Button('Close')] ]
# Create the Window
window = sg.Window('Updating a plot example....', layout)
return window
if __name__ == '__main__':
window = getGUI()
spectraPlot = updateable_matplotlib_plot(window['canvas']) #what canvas are you plotting it on
window.finalize() #show the window
spectraPlot.plot(np.zeros(1024)) # plot an empty plot
while True:
event, values = window.read()
if event == "update":
some_spectrum = np.random.random(1024) # data to be plotted
spectraPlot.plot(some_spectrum) #plot the data
if event == sg.WIN_CLOSED or event == 'Close': break # if user closes window or clicks cancel
window.close()
I have an application set up with an interactive plot window embedded. I would like to put a couple of subplots on top of eachother, with a shared x-axis and an independent y-axis. The whole thing is meant for data analysis.
I got the subplots set up, but for some reason the y-axis of the first subplot is somehow connected to the other subplots, but not the other way around.
Additionally, the ticks and labels overlap instead of staying at their respective subplots.
I tried using the pyplot.subplots function, which takes care of the problem of the independent axes and ticks/labels, but this opens up another window when I call it instead of embedding it.
working example code that showcases the problem (Python 3.7):
# -*- coding: utf-8 -*-
import tkinter as tk
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2Tk
from matplotlib.figure import Figure
from tkinter import ttk
import numpy as np
import pandas as pd
class window(tk.Tk):
def __init__(self,*args,**kwargs):
tk.Tk.__init__(self,*args,**kwargs)
self.generate_data()
self.plotPane = self.plot_pane(self)
def generate_data(self):
self.data = pd.DataFrame()
x = [1,2,3,4,5]
y = np.zeros((len(x)))
for i,yy in enumerate(y):
y[i] = yy + 10.*float(np.random.random())
self.data['x'] = x
self.data['y'] = y
class plot_pane():
def __init__(self,parent):
self.parent = parent
self.labelframe = ttk.Labelframe(self.parent,text="Plot")
replotButton = ttk.Button(self.parent,text="replot",command=self.update_plot)
self.labelframe.grid(row=0, column=0)
replotButton.grid(row=1,column=0)
self.figure = Figure(figsize=(6,3),dpi=100)
self.figure.subplots_adjust(left=0.11,bottom=0.09,right=0.77,top=0.92)# BaMa:. subplot margins, so labels are visible
self.sub = self.figure.add_subplot(111)
# toolbar and canvas for live plot
canvas = FigureCanvasTkAgg(self.figure,self.labelframe)
canvas.get_tk_widget().grid(row=1,column=1,rowspan=2,sticky="NSEW",pady=20)
canvas._tkcanvas.grid(row=1,column=1,rowspan=2, sticky="NSEW")
toolbar_frame = tk.Frame(self.labelframe)
toolbar_frame.grid(row=0,column=1,sticky="SEW")
toolbar = NavigationToolbar2Tk(canvas,toolbar_frame)
toolbar.update()
self.update_plot()
def update_plot(self,*args):
# clear figure
self.figure.clf()
stackAx = []
for i in range(0,2):
# generate new random data
self.parent.generate_data()
testX = self.parent.data['x']
testY = self.parent.data['y']
# add subplots
if i == 0:
stackAx.append(self.figure.add_subplot(i+1,1,1))# y-axis of this subplot is somehow connected to the other
else:
stackAx.append(self.figure.add_subplot(i+1,1,1,sharex=stackAx[0]))
# plot, add labels, ticks and grid
stackAx[i].plot(testX,testY)
stackAx[i].set_ylabel("ax-"+str(i))
stackAx[i].tick_params('y')
stackAx[i].grid()
self.figure.canvas.draw()
window = window()
window.mainloop()
So, when you move the subplot at the top, the bottom y-axis moves as well and the "ax-0" label + tickmarks breach the upper subplot. When you move the lower plot, the y-axis of the upper plot does not move (as it should be)
I figured it out. Apparently add_subplot and pyplot.subplots function somewhat differently and I didn't understand it correctly.
The following update function works:
def update_plot(self,*args):
# clear figure
self.figure.clf()
stackAx = []
numberOfPlots = 2
for i in range(0,numberOfPlots):
# generate new random data
self.parent.generate_data()
testX = self.parent.data['x']
testY = self.parent.data['y']
# add subplots
if i == 0:
stackAx.append(self.figure.add_subplot(numberOfPlots,1,i+1))
else:
stackAx.append(self.figure.add_subplot(numberOfPlots,1,i+1,sharex=stackAx[0]))
# plot, add labels, ticks and grid
stackAx[i].plot(testX,testY)
stackAx[i].set_ylabel("ax-"+str(i))
stackAx[i].tick_params('y')
stackAx[i].grid()
self.figure.canvas.draw()
I got it from here: https://pythonprogramming.net/subplot2grid-add_subplot-matplotlib-tutorial/
I am working on a GUI (developed with wxPython) where you can plot graphs on different panels. At the moment I have this:
from matplotlib.backends.backend_wxagg import FigureCanvasWxAgg as FigureCanvas
from matplotlib.backends.backend_wx import NavigationToolbar2Wx
from matplotlib import pyplot as plt
import numpy as np
import wx
class Frame(wx.Frame):
def __init__(self):
wx.Frame.__init__(self,None,-1,'Plot',size=(1000,800))
# Main Panel (It will contain other elements besides the plotting panel)
self.mainPanel = wx.Panel(self,-1,size=(1000,800))
self.mainPanel.SetBackgroundColour('gray')
# Plotting panel
self.plottingPanel = wx.Panel(self,-1,pos=(50,20),size=(500,400))
self.plottingPanel.SetBackgroundColour('white')
# Plot example
figure = plt.figure()
axes = figure.add_subplot(111)
t = np.arange(0.0, 3.0, 0.01); s = np.cos(2 * np.pi * t);axes.plot(t,s)
plt.title('Cosine')
plt.xlabel('x');plt.ylabel('y')
# Canvas
canvas = FigureCanvas(self.plottingPanel,-1,figure)
# Navegation toolbar
navToolbar = NavigationToolbar2Wx(canvas)
navToolbar.DeleteToolByPos(6);navToolbar.DeleteToolByPos(2);navToolbar.DeleteToolByPos(1)
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add(canvas)
sizer.Add(navToolbar)
class App(wx.App):
def OnInit(self):
self.Frame = Frame()
self.Frame.Show()
self.SetTopWindow(self.Frame)
return True
def main():
app = App()
app.MainLoop()
if __name__ == '__main__':
main()
When I run the script get this:
I have colored the plotting panel white to highlight it. How can the plot size be adapted to the panel size?
I want to get something like this (this is a montage):
On the other hand, I managed to eliminate from the bar some buttons that are unnecessary for what I need but the bar does not work, that is, when pressing the buttons nothing happens :(
Thanks for your help
It is possible to set parameters when the container for the plot elements (matplotlib.figure.Figure) is created.
e.g. figsize sets the figure dimension in inches and tight_layout adjust the sub plots in tight layout.
figure = plt.figure(figsize = (4, 3), tight_layout=True)
Alternatively you can set the position of the matplotlib.axes.Axes object by .set_position:
figure = plt.figure()
axes = figure.add_subplot(111)
axes.set_position(pos = [0.15,0.3,0.55,0.55], which='both')
I dont seem to be able to fully control the figure size on my embedded figure on a Tkinter canvas.
Heres what i want to do. Maybe you have another suggestion, than using the embedded figure.
Im trying to make a simple script to make some visual content. Right now its just a pixel mapping of falling squares in random colors.
My problem is that i need it to be fullscreen, and i can for my life not figure out how.
It is mainly about this piece of code, i think:
fig = plt.figure(figsize=(40,40))
im = plt.imshow(top.img) # later use a.set_data(new_data)
plt.tick_params(
axis='both', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
left='off',
right='off',
labelleft='off',
labelbottom='off') # labels along the bottom edge are off
# a tk.DrawingArea
canvas = FigureCanvasTkAgg(fig, master=top)
canvas.show()
canvas.get_tk_widget().pack(side=gui.TOP , fill=gui.BOTH, expand=1)
It seems that figsize has a limit to how big it goes.
Heres all the code:
import matplotlib
import numpy as np
matplotlib.use('TkAgg')
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
from matplotlib import figure
import matplotlib.pyplot as plt
import tkinter as gui
from math import floor
import time
class FullScreenApp(object):
def __init__(self, master, **kwargs):
self.master=master
pad=3
self._geom='200x200+0+0'
master.geometry("{0}x{1}+0+0".format(
master.winfo_screenwidth()-pad, master.winfo_screenheight()-pad))
master.bind('<Escape>',self.toggle_geom)
def toggle_geom(self,event):
geom=self.master.winfo_geometry()
print(geom,self._geom)
self.master.geometry(self._geom)
self._geom=geom
def flashBox(color,oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = color
im.set_data(top.img)
canvas.draw();
time.sleep(t)
top.img[0+oy:j2+oy,0+ox:j1+ox] = [0,0,0]
im.set_data(top.img)
canvas.draw();
return top.img
def drawBox(color,oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = color
im.set_data(top.img)
canvas.draw();
time.sleep(t)
return top.img
def resetBox(oy,ox):
global j1, j2
top.img[0+oy:j2+oy,0+ox:j1+ox] = [0,0,0]
im.set_data(top.img)
canvas.draw();
return top.img
def drawColumn(color,u):
global gridsize, j1, j2
for l in range(gridsize):
im.set_data(flashBox(color,j2*l,j1*u))
time.sleep(t2)
top = gui.Tk()
t = 0.1
t2 = 0.00001
x = 40
y = 40
gridsize = 10
j1 = floor(x // gridsize)
j2 = floor(y // gridsize)
top.img = np.zeros([y,x,3],dtype=np.uint8)
top.img.fill(0) # or img[:] = 255
fig = plt.figure(figsize=(40,40))
im = plt.imshow(top.img) # later use a.set_data(new_data)
plt.tick_params(
axis='both', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
left='off',
right='off',
labelleft='off',
labelbottom='off') # labels along the bottom edge are off
# a tk.DrawingArea
canvas = FigureCanvasTkAgg(fig, master=top)
canvas.show()
canvas.get_tk_widget().pack(side=gui.TOP , fill=gui.BOTH, expand=1)
#app=FullScreenApp(top)
while True:
for n in range(gridsize):
top.update()
p = np.random.randint(0,99)
#drawColumn([np.random.random_integers(0,255),np.random.random_integers(0,255),np.random.random_integers(0,255)],np.random.random_integers(0,gridsize-1))
if p > 10:
flashBox([np.random.random_integers(0,255),np.random.random_integers(0,255),np.random.random_integers(0,255)],j1*np.random.random_integers(0,gridsize-1),j2*np.random.random_integers(0,gridsize-1))
else:
flashBox([0,0,0],0,0)