I am currently working on using Vispy to add visualization capabilities to a Python simulation library. I have managed to get some basic visualizations running with the data from the simulations, and am now looking at wrapping it in functions/classes so users of the libraries easily visualize the simulation (by passing the data in a specific format or something) without having to code it themselves.
However, I am having trouble figuring out the right way/best practice to get the timers working properly to update the objects as they change in time.
For example, when running the visualization as script, an example of how I have implemented the timer is using global variables and iterators similar to how it is done in the Vispy Scene "Changing Line Colors" demo on the Vispy website :
def on_timer(event):
global colormaps, line, text, pos
color = next(colormaps)
line.set_data(pos=pos, color=color)
text.text = color
timer = app.Timer(.5, connect=on_timer, start=True)
But when I wrap the entire visualization script in a function/class, I am having trouble getting the timer to work correctly given the difference in scopes of the variables now. If anyone could give some idea of the best way to achieve this that would be great.
EDIT:
I have made an extremely simplified visualization that might be similar to some of the expected use cases. The code when run as a stand alone python script is:
import numpy as np
from vispy import app, scene
# Reproducible data (oscillating wave)
time = np.linspace(0, 5, 300)
rod_positions = []
for t in time:
wave_position = []
for i in range(100):
wave_position.append([0, i, 20 * (np.cos(t + i / 10))])
rod_positions.append(wave_position)
rod_positions = np.array(rod_positions)
# Prepare canvas
canvas = scene.SceneCanvas(keys="interactive", size=(800, 600), bgcolor="black")
canvas.measure_fps()
# Set up a view box to display the image with interactive pan/zoom
view = canvas.central_widget.add_view()
view.camera = scene.TurntableCamera()
rod = scene.visuals.Tube(
points=rod_positions[0], radius=5, closed=False, tube_points=16, color="green",
)
view.add(rod)
view.camera.set_range()
text = scene.Text(
f"Time: {time[0]:.4f}",
bold=True,
font_size=14,
color="w",
pos=(80, 30),
parent=canvas.central_widget,
)
update_counter = 0
max_updates = len(time) - 1
def on_timer_update(event):
global update_counter
update_counter += 1
if update_counter >= max_updates:
timer.stop()
canvas.close()
# Update new rod position and radius
rod_new_meshdata = scene.visuals.Tube(
points=rod_positions[update_counter],
radius=5,
closed=False,
tube_points=16,
color="green",
)._meshdata
rod.set_data(meshdata=rod_new_meshdata)
text.text = f"Time: {time[update_counter]:.4f}"
# Connect timer to app
timer = app.Timer("auto", connect=on_timer_update, start=True)
if __name__ == "__main__":
canvas.show()
app.run()
My attempt at wrapping this in a class is the following:
import numpy as np
from vispy import app, scene
class Visualizer:
def __init__(self, rod_position, time) -> None:
self.rod_positions = rod_position
self.time = time
self.app = app.application.Application()
# Prepare canvas
self.canvas = scene.SceneCanvas(keys="interactive", size=(800, 600), bgcolor="black")
self.canvas.measure_fps()
# Set up a view box to display the image with interactive pan/zoom
self.view = self.canvas.central_widget.add_view()
self.view.camera = scene.TurntableCamera()
self.update_counter = 0
self.max_updates = len(time) - 1
def _initialize_objects(self):
self.rod = scene.visuals.Tube(
points=self.rod_positions[0], radius=5, closed=False, tube_points=16, color="green",
)
self.view.add(self.rod)
self.view.camera.set_range()
self.text = scene.Text(
f"Time: {self.time[0]:.4f}",
bold=True,
font_size=14,
color="w",
pos=(80, 30),
parent=self.canvas.central_widget,
)
def update_timer(self, event):
self.update_counter += 1
if self.update_counter >= self.max_updates:
self.timer.stop()
self.canvas.close()
# Update new rod position and radius
rod_new_meshdata = scene.visuals.Tube(
points=self.rod_positions[self.update_counter],
radius=5,
closed=False,
tube_points=16,
color="green",
)._meshdata
self.rod.set_data(meshdata=rod_new_meshdata)
self.text.text = f"Time: {self.time[self.update_counter]:.4f}"
def run(self):
self._initialize_objects()
# Connect timer to app
self.timer = app.Timer("auto", connect=self.update_timer, start=True, app=self.app)
self.canvas.show()
self.app.run()
if __name__ == "__main__":
# Reproducible data (oscillating wave)
time = np.linspace(0, 5, 150)
rod_positions = []
for t in time:
wave_position = []
for i in range(100):
wave_position.append([0, i, 20 * (np.cos(2 * t + i / 10))])
rod_positions.append(wave_position)
rod_positions = np.array(rod_positions)
Visualizer = Visualizer(rod_positions, time)
Visualizer.run()
It seems to be working now which is good. However this is a minimal reproduction of my problem, so I would just like to make sure that this is the optimal/intended way. As a side note, I also feel as if my way of updating the rod by generating the meshdata and updating the rod in the view with this meshdata is not optimal and slowing the visualization down (it runs at around 10fps). Is the update loop itself optimal?
Thanks
Thanks for updating your question with your example. It makes it much easier to answer and continue our conversation. I started a pull request for VisPy about this topic where I add some examples that use Qt timers and Qt background threads. I hope to finish the PR in the next month or two so if you have any feedback please comment on it:
https://github.com/vispy/vispy/pull/2339
Timers
In general timers are a good way to update a visualization in a GUI event loop friendly way. However, in most GUI frameworks the timer is executed in the current GUI thread. This has the benefit that you can call GUI/drawing functions directly (they are in the same thread), but has the downside that any time you spend in your timer callback is time you're taking away from the GUI framework in order to respond to user interaction and redraw the application. You can see this in my timer example in the above PR if you uncomment the extra sleep line. The GUI basically stops responding while it is running the timer function.
I have a little message on GUI threads and event loops in the vispy FAQ here.
Threads
Threads are a good way around the limitations of timers, but come with a lot of complexities. Threads are also usually best done in a GUI-framework specific manner. I can't tell from your post if you are doing Qt or some other backend, but you will probably get the most bang for your buck by using the GUI framework specific thread functionality rather than generic python threads. If an application that works across GUI frameworks is what you're looking for then this likely isn't an option.
The benefit of using something like a QThread versus a generic python thread is that you can use things like Qt's signals and slots for sending data/information between the threads.
Note that as I described in the FAQ linked above that if you use threads you won't be able to call the set_data methods directly in your background thread(s). You'll need to send the data to the main GUI thread and then have it call the set_data method.
Suggestions
You are correct that your creation of a new Tube visual that you only use for extracting mesh data is a big slow down. The creation of a Visual is doing a lot of low-level GL stuff to get ready to draw the Visual, but then you don't use it so that work is essentially wasted time. If you can find a way to create the MeshData object yourself without the Visual you should see a speed up, but if you have a lot of data switching to threads is likely still needed.
I'm not sure how much this example's design resembles what you're really doing, but I would consider keeping the Application, Timer, and Visualizer classes separate. I'm not sure I can give you a good reason why, but something about creating these things in a singe class worries me. In general I think the programming concept of dependency injection applies here: don't create your dependencies inside your code, create them outside and pass them as arguments to your code. Or in the case of the Application and Timer, connect them to the proper methods on your class. If you have a much larger application then it may make sense to have a class that wraps all of the Vispy canvas and data updating logic, another one just for the outer GUI window, and then another for a data generation class. Then in the bottom if main block of code create your application, your timer, your canvas wrapper, your main window (passing the canvas wrapper if needed), and connect them all together.
Other thoughts
This is a problem I want to make easier for vispy users and scientific python programmers in general so let me know what I'm missing here and we'll see what kind of ideas we can come up with. Feel free to comment and provide feedback on my pull request. Do you have other ideas for what the examples should be doing? I have plans for additional fancier examples in that PR, but if you have thoughts about what you'd like to see let me know.
Related
this is a bit longer, the first part is just a description of the problem, the second one the question if my "fix" is correct.
I started with python programming. I created a program that communicates with an Arduino that reads the temperature of a furnace of our melting lab. The temperature is then used in a PID algorithm and an output is set to the Arduino. The communication is done via pyserial. So far, everthing works, including live plotting of the temperature signals, PID-variables and so on. The script includes a the main loop and 3 threads (serial communication, a datashifter that reads from serialport, the set temperature from the QWidget and the output of the PID algorithm. This values are used to create an array for displaying within pyqtgraph. Finally, the third thread shifts the data from the datashifter to the QWidget.
When using my Linux-Notebook, everything works fine, and the GUI never stops updating. In contrast, when using any Windows-Host, i have the problem that some pyqtgraphs stop to refresh. The behavior is strange, because i set all data at more or less the same time, with the same numpy array (just different columns) - some plots refresh longer (hours), some stop earlier (minutes). After searching more or less the hole internet ;-) I think that I found the problem: Its the passing of data from from a thread to the GUI. Some dummy code to explain what's going on:
DataUpdaterToGUI(QThread):
#sets the QWidget from main loop
def setGUI(self, gui):
self.gui = gui
def run()
while True:
with lock(): # RLock() Instance
copyArray = self.dataArray[:] # copy the array from the shifter
self.gui.plot1.copyArray(dataArray[:, 0], copyArray[:, 1])
self.gui.plot2.copyArray(dataArray[:, 0], copyArray[:, 2])
# self.gui.update()
# QApplication.instance().processEvents()
Neither calling self.gui.update() nor processEvents() has any influence on the outcome: The plots stop redrawing after a while (on windows).
Now i have a very simple example, and just want to make sure if I'm using the threading-stuff correctly. It works fine, but I have some questions:
Does the signal-slot approach copy the passed data?
Why is it not necessary to call the update() method of the QWidget?
Do I have to use any kind of locks when using signals?
class Main(QWidget):
def __init__(self):
super().__init__()
self.layout = QGridLayout(self)
self.graph = pg.PlotWidget()
self.graph.setYRange(0,1000)
self.plot = self.graph.plot()
self.layout.addWidget(self.graph,0,0)
self.show()
def make_connection(self, data_object):
data_object.signal.connect(self.grab_data)
#pyqtSlot(object)
def grab_data(self, data):
print(data)
self.plot.setData(data)
class Worker(QThread):
signal = pyqtSignal(object)
def __init__(self):
super().__init__()
def run(self):
self.data = [0, 1]
i = 2
while True:
self.data[1] = i
self.signal.emit(self.data)
time.sleep(0.01)
i += 1
if __name__ == "__main__":
app = QApplication(sys.argv)
widget = Main()
worker = Worker()
widget.make_connection(worker)
worker.start()
sys.exit(app.exec_())
Does the signal-slot approach copy the passed data? The signals are thread-safe and when transferring data they make a copy so the thread that precedes the data and the thread that consumes it (GUI Thread) will not have conflicts
Why is it not necessary to call the update() method of the QWidget? Actually pyqtgraph calls the update method, plot is a PlotDataItem, so if we check the source code of setData() method, it calls the updateItems() method, in that method the setData() method of the curve or scatter attribute is called (according to the type of graphics), in the case of curve its setData() method calls updateData(), and the updateData() method calls update, and in the case of the scatter its setData() method calls addpoint(), and addPoints() calls invalidate(), and this invalidate() method calls update().
Do I have to use any kind of locks when using signals? No, as the signals are thread-safe so Qt already has the guards set to avoid the collision.
I have a PyQt5 application that looks like this This. Now, with the "bailar" button I want the character on the grid to look left and right a couple of times. I do this in the following method:
def dance(self):
"""
Make the P1 dance
"""
p1 = self._objects['P1']
x = p1.x
y = p1.y
cell = self.worldGrid[y][x]
for i in xrange(3):
print("Moving my head...")
cell.objectLeaves('P1')
p1.pixmap = p1.pixmap.transformed(QTransform().scale(-1, 1))
cell.objectArrives('P1', p1)
time.sleep(0.2)
However, the label containing the pixmap updates only at the last iteration. I know this must be a problem of the update function being asynchronous and the time.sleep() blocking the main thread, but I don't know how else could I show the animation. I tried using a QThread with the moveToThread method, but it failed as the gird widget is a child of the main window. Any ideas?
You see only the last frame of your animation because the UI isn't updated by Qt until the dance function terminates. If you add QtGui.qApp.processEvents() just before the time.sleep(0.2) statement, the UI will be updated for every frame of the animation.
Note that the user still cannot interact with your application until the animation has finished. This might not be a problem for short animations like this, but for longer animations you might better use a QTimer or the Qt animation framework that Brendan Abel suggested.
I've been working on a prototype application in Python for stereoscopic imaging of a 3D model using VTK, but I'm running into some issues on the interface end of things. The goal of the code below at the moment is to zoom in on both renderWindows when the middlemouse is pressed. However, upon calling the vtkRenderWindowInteractor.Start() function, my vtkRenderWindowInteractors are effectively stalling out the entire program as if they were being run in the same thread. Even more curious is that keyboard interrupts are not being thrown when I use CTRL-C (I'm working in UNIX shell) until I close the render windows manually using the 'x' button. If I just close the window manually without hitting CTRL-C, the program picks up directly after the Start() call (e.g. in the code below, the infinite while loop). I've provided a sequence of screen captures at the end of this post to visualize exactly what is happening in the case that my explanation is confusing.
I've tried multiple workarounds to remedy this but none so far have worked. Threading the renders into isolated threads made no difference even when I tried using ncurses for input, while forking them to a new process resulted in some OS issues that I'd rather not deal with. The most current interactor styles method (shown below) where I just use built-in VTK listeners works to a degree, allowing me to detect inputs when the windows are in focus and the interactors are active, but because of the lack of association between the camera and the MyInteractorStyle class, I can't really access the cameras without the inclusion a loop after the Start() call, which leads me right back to where I started.
Any thoughts? Am I just misunderstanding how VTK's render tools are supposed to be used?
from vtk import*
import os.path
#import thread
#import time
#import threading
#import curses
class MyInteractorStyle(vtk.vtkInteractorStyleTrackballCamera):
pos1 = [0, 0, 200]
foc1 = [0, 0, 0]
pos2 = [40, 0, 200]
foc2 = [0, 0, 0]
def __init__(self,parent=None):
self.AddObserver("MiddleButtonPressEvent", self.middleButtonPressEvent)
self.AddObserver("MiddleButtonReleaseEvent", self.middleButtonReleaseEvent)
def middleButtonPressEvent(self,obj,event):
print "Middle button pressed"
self.pos1[2] += 10
self.pos2[2] += 30
self.OnMiddleButtonDown()
return
def middleButtonReleaseEvent(self,obj,event):
print "Middle button released"
self.OnMiddleButtonUp()
return
def main():
# create two cameras
camera1 = vtkCamera()
camera1.SetPosition(0,0,200)
camera1.SetFocalPoint(0,0,0)
camera2 = vtkCamera()
camera2.SetPosition(40,0,200)
camera2.SetFocalPoint(0,0,0)
# create a rendering window and renderer
ren1 = vtkRenderer()
ren1.SetActiveCamera(camera1)
ren2 = vtkRenderer()
ren2.SetActiveCamera(camera2)
# create source
reader = vtkPolyDataReader()
path = "/home/compilezone/Documents/3DSlicer/SlicerScenes/LegoModel-6_25/Model_5_blood.vtk"
reader.SetFileName(path)
print(path)
reader.Update()
# create render window
renWin1 = vtkRenderWindow()
renWin1.AddRenderer(ren1)
renWin2 = vtkRenderWindow()
renWin2.AddRenderer(ren2)
# create a render window interactor
inputHandler = MyInteractorStyle()
iren1 = vtkRenderWindowInteractor()
iren1.SetRenderWindow(renWin1)
iren1.SetInteractorStyle(inputHandler)
iren2 = vtkRenderWindowInteractor()
iren2.SetRenderWindow(renWin2)
iren2.SetInteractorStyle(inputHandler)
# mapper
mapper = vtkPolyDataMapper()
mapper.SetInput(reader.GetOutput())
# actor
actor = vtkActor()
actor.SetMapper(mapper)
# assign actor to the renderer
ren1.AddActor(actor)
ren2.AddActor(actor)
# enable user interface interactor
iren1.Initialize()
iren2.Initialize()
renWin1.Render()
renWin2.Render()
iren1.Start()
iren2.Start()
print "Test"
while 1:
pos1 = iren1.GetInteractorStyle().pos1
foc1 = iren1.GetInteractorStyle().foc1
pos2 = iren2.GetInteractorStyle().pos2
foc2 = iren2.GetInteractorStyle().foc2
print
if __name__ == '__main__':
main()
Program running
KeyboardInterrupt (CTRL-C hit and echoed in terminal but nothing happens)
Render windows manually closed, KeyboardInterrupt thrown
Calling Start() on a RenderWindowInteractor starts the event loop necessary to execute render events, much as the event loop in a GUI. So what you're trying to do, starting two event loops, doesn't really make sense.
A conceptual workaround would be to not call Start on the RenderWindowInteractors but to write a small GUI with multiple toolkit-specific RenderWindowInteractors and use that GUI's event loop.
As an example, here's how this is done with GUI toolkit-specific code in tvtk's wxVtkRenderWindowInteractor class, which doesn't call start on the RenderWindowInteractor but instead uses the GUI's event loop to manage events:
def wxVTKRenderWindowInteractorConeExample():
"""Like it says, just a simple example
"""
# every wx app needs an app
app = wx.PySimpleApp()
# create the top-level frame, sizer and wxVTKRWI
frame = wx.Frame(None, -1, "wxVTKRenderWindowInteractor", size=(400,400))
widget = wxVTKRenderWindowInteractor(frame, -1)
sizer = wx.BoxSizer(wx.VERTICAL)
sizer.Add(widget, 1, wx.EXPAND)
frame.SetSizer(sizer)
frame.Layout()
# It would be more correct (API-wise) to call widget.Initialize() and
# widget.Start() here, but Initialize() calls RenderWindow.Render().
# That Render() call will get through before we can setup the
# RenderWindow() to render via the wxWidgets-created context; this
# causes flashing on some platforms and downright breaks things on
# other platforms. Instead, we call widget.Enable(). This means
# that the RWI::Initialized ivar is not set, but in THIS SPECIFIC CASE,
# that doesn't matter.
widget.Enable(1)
widget.AddObserver("ExitEvent", lambda o,e,f=frame: f.Close())
ren = vtk.vtkRenderer()
widget.GetRenderWindow().AddRenderer(ren)
cone = vtk.vtkConeSource()
cone.SetResolution(8)
coneMapper = vtk.vtkPolyDataMapper()
coneMapper.SetInput(cone.GetOutput())
coneActor = vtk.vtkActor()
coneActor.SetMapper(coneMapper)
ren.AddActor(coneActor)
# show the window
frame.Show()
app.MainLoop()
(Note that this code is not altered and has some clear differences with what you are trying to do.)
Also, the reason that ctrl+C doesn't work is because the VTK event loop doesn't do anything with this event. Some GUIs do respect this event, including wxpython. But if you aren't using a GUI that respects this event (for example, Qt) you can manually tell the python interpreter to intercept this event and crash instead of forwarding the event to the GUI event loop:
import signal
signal.signal(signal.SIGINT, signal.SIG_DFL)
For anyone who happens to stumble along this with the same problem of being unable to manipulate the camera from the vtkInteractorStyle classes, check out the Dolly(), Pan(), Spin(), Rotate(), Zoom(), and UniformScale(). All of these should let you access the camera from your whichever child class of vtkInteractorStyle you're using. Good luck!
EDIT: Even better, just attach your camera to your class that inherits from vtkInteractorStyle as a property, e.g.:
style = MyInteractorStyleClass()
style.camera = myCam
This way you can access it from anywhere within your custom class! Pretty basic, but it flew right past me.
For my class, I am creating a "Mandelbrot Explorer" program. There is one main issue: I lose control of the GUI (all written in Tkinter/Ttk, in Python 2.7) when actually drawing to the Canvas.
Here is my code:
# There is some code above and below, but only this is relevant
for real, imag in graph.PlaneIteration(self.graph.xMin, self.graph.xMax, resolution, self.graph.yMin, self.graph.yMax, resolution, master = self.graph, buffer_action = self.graph.flush):
# the above line iterates on the complex plane, updating the Canvas for every x value
c = complex(real, imag)
function, draw, z, current_iter = lambda z: z**2 + c, True, 0, 1
while current_iter <= iterations:
z = function(z)
if abs(z) > limit:
draw = False
break
current_iter += 1
self.progressbar.setValue(100 * (real + self.graph.xMax) / total)
color = self.scheme(c, current_iter, iterations, draw)
# returns a hex color value
self.graph.plot(c, color)
# self.graph is an instance of my custom class (ComplexGraph) which is a wrapper
# around the Canvas widget
# self.graph.plot just creates a line on the Canvas:
# self.create_line(xs,ys,xs+1,ys+1, fill=color)
My issue is that when run, the graphing takes a while - about 30 seconds. In this time, I cannot use the GUI. If I try to, the window freezes and only unfreezes once the drawing is done.
I tried using threading (I enclosed the entirety of the upper code in a function, thread_process):
thread.start_new_thread(thread_process, ())
However, the problem remains.
Is there a way to fix this? Thanks!
You can execute your loop "threaded" with Tkinter by implicitly returning to Tkinter's main loop execution after every point your draw. Do this by using widget.after to register the next function call:
plane = graph.PlaneIteration(...)
def plotNextPoint():
try:
real, imag = plane.next()
except StopIteration:
return
c = complex(real, imag)
...
self.graph.plot(c, color)
self.graph.after(0, plotNextPoint)
plotNextPoint()
This way, after each point you draw, the Tkinter mainloop will run again and update the display before calling your plotNextPoint function again. If this is too slow, try wrapping the body of plotNextPoint in a for _ in xrange(n) loop to draw n points between redraws.
You're right about the cause of the problem—the GUI event loop is not running while you're busy running this code.
And you're right about threading being a good solution. (The other major solution is to break the job up into smaller subtasks and have each one schedule the next. For a more detailed overview of the options and all of the wrinkles, see Why your GUI app freezes.)
But it's not quite as simple as putting the whole thing on a thread.
Unfortunately, Tkinter (like many GUI frameworks) is not free-threaded. You cannot call methods on any GUI objects from a background thread. If you do, different things happen on different platforms and versions, ranging from blocking the main thread to crashing the program to raising exceptions.
Also, remember that, even without Tkinter, you can't safely share mutable objects between threads without some kind of synchronization. And you're doing exactly that with the Tkinter objects, right?
The Tkinter wiki explains one way to get around both of these problems at once in Tkinter and Threads: Create a Queue, have the background thread put messages on it, and have the main thread check it every so often (e.g., by using after to schedule a nonblocking get every 100ms until the background thread is done).
If you don't want to come up with a "protocol" for passing data from the background thread to the main thread, remember that in Python, a bound method, or a tuple of a bound method and some arguments, it perfectly good, passable data. So, instead of calling self.graph.plot(c, color), you can just self.q.put((self.graph.plot, c, color)).
The library mtTkinter wraps this all up for you, making it look like Tkinter is free-threaded by using a Queue in the background. It isn't highly tested or frequently maintained, but even if it doesn't work in the future it still makes great sample code.
I've created a simple application to display a scatterplot of data using Tkinter's Canvas widget (see the simple example below). After plotting 10,000 data points, the application becomes very laggy, which can be seen by trying to change the size of the window.
I realize that each item added to the Canvas is an object, so there may be some performance issues at some point, however, I expected that level to be much higher than 10,000 simple oval objects. Further, I could accept some delays when drawing the points or interacting with them, but after they are drawn, why would just resizing the window be so slow?
After reading effbot's performance issues with the Canvas widget it seems there may be some unneeded continuous idle tasks during resizing that need to be ignored:
The Canvas widget implements a straight-forward damage/repair display
model. Changes to the canvas, and external events such as Expose, are
all treated as “damage” to the screen. The widget maintains a dirty
rectangle to keep track of the damaged area.
When the first damage event arrives, the canvas registers an idle task
(using after_idle) which is used to “repair” the canvas when the
program gets back to the Tkinter main loop. You can force updates by
calling the update_idletasks method.
So, the question is whether there is any way to use update_idletasks to make the application more responsive once the data has been plotted? If so, how?
Below is the simplest working example. Try resizing the window after it loads to see how laggy the application becomes.
Update
I originally observed this problem in Mac OS X (Mavericks), where I get a substantial spike in CPU usage when just resizing the window. Prompted by Ramchandra's comments I've tested this in Ubuntu and this doesn't seem to occur. Perhaps this is a Mac Python/Tk problem? Wouldn't be the first I've run into, see my other question:
PNG display in PIL broken on OS X Mavericks?
Could someone also try in Windows (I don't have access to a Windows box)?
I may try running on the Mac with my own compiled version of Python and see if the problem persists.
Minimal working example:
import Tkinter
import random
LABEL_FONT = ('Arial', 16)
class Application(Tkinter.Frame):
def __init__(self, master, width, height):
Tkinter.Frame.__init__(self, master)
self.master.minsize(width=width, height=height)
self.master.config()
self.pack(
anchor=Tkinter.NW,
fill=Tkinter.NONE,
expand=Tkinter.FALSE
)
self.main_frame = Tkinter.Frame(self.master)
self.main_frame.pack(
anchor=Tkinter.NW,
fill=Tkinter.NONE,
expand=Tkinter.FALSE
)
self.plot = Tkinter.Canvas(
self.main_frame,
relief=Tkinter.RAISED,
width=512,
height=512,
borderwidth=1
)
self.plot.pack(
anchor=Tkinter.NW,
fill=Tkinter.NONE,
expand=Tkinter.FALSE
)
self.radius = 2
self._draw_plot()
def _draw_plot(self):
# Axes lines
self.plot.create_line(75, 425, 425, 425, width=2)
self.plot.create_line(75, 425, 75, 75, width=2)
# Axes labels
for i in range(11):
x = 75 + i*35
y = x
self.plot.create_line(x, 425, x, 430, width=2)
self.plot.create_line(75, y, 70, y, width=2)
self.plot.create_text(
x, 430,
text='{}'.format((10*i)),
anchor=Tkinter.N,
font=LABEL_FONT
)
self.plot.create_text(
65, y,
text='{}'.format((10*(10-i))),
anchor=Tkinter.E,
font=LABEL_FONT
)
# Plot lots of points
for i in range(0, 10000):
x = round(random.random()*100.0, 1)
y = round(random.random()*100.0, 1)
# use floats to prevent flooring
px = 75 + (x * (350.0/100.0))
py = 425 - (y * (350.0/100.0))
self.plot.create_oval(
px - self.radius,
py - self.radius,
px + self.radius,
py + self.radius,
width=1,
outline='DarkSlateBlue',
fill='SteelBlue'
)
root = Tkinter.Tk()
root.title('Simple Plot')
w = 512 + 12
h = 512 + 12
app = Application(root, width=w, height=h)
app.mainloop()
There is actually a problem with some distributions of TKinter and OS Mavericks. Apparently you need to install ActiveTcl 8.5.15.1. There is a bug with TKinter and OS Mavericks. If it still isn't fast eneough, there are some more tricks below.
You could still save the multiple dots into one image. If you don't change it very often, it should still be faster. If you are changing them more often, here are some other ways to speed up a python program. This other stack overflow thread talks about using cython to make a faster class. Because most of the slowing down is probably due to the graphics this probably won't make it a lot faster but it could help.
Suggestions on how to speed up a distance calculation
you could also speed up the for loop by defining an iterator ( ex: iterator = (s.upper() for s in list_to_iterate_through) ) beforehand, but this is called to draw the window, not constantly as the window is maintained, so this shouldn't matter very much. Also, a another way to speed things up, taken from python docs, is to lower the frequency of python's background checks:
"The Python interpreter performs some periodic checks. In particular, it decides whether or not to let another thread run and whether or not to run a pending call (typically a call established by a signal handler). Most of the time there's nothing to do, so performing these checks each pass around the interpreter loop can slow things down. There is a function in the sys module, setcheckinterval, which you can call to tell the interpreter how often to perform these periodic checks. Prior to the release of Python 2.3 it defaulted to 10. In 2.3 this was raised to 100. If you aren't running with threads and you don't expect to be catching many signals, setting this to a larger value can improve the interpreter's performance, sometimes substantially."
Another thing I found online is that for some reason setting the time by changing os.environ['TZ'] will speed up the program a small amount.
If this still doesn't work, than it is likely that TKinter is not the best program to do this in. Pygame could be faster, or a program that uses the graphics card like open GL (I don't think that is available for python, however)
Tk must be getting bogged down looping over all of those ovals. I'm not
sure that the canvas was ever intended to hold so many items at once.
One solution is to draw your plot into an image object, then place the image
into your canvas.