what I am trying to do is having a script compute something, prepare a plot and show the already obtained results as a pylab.figure - in python 2 (specifically python 2.7) with a stable matplotlib (which is 1.1.1).
In python 3 (python 3.2.3 with a matplotlib git build ... version 1.2.x), this works fine. As a simple example (simulating a lengthy computation by time.sleep()) consider
import pylab
import time
import random
dat=[0,1]
pylab.plot(dat)
pylab.ion()
pylab.draw()
for i in range (18):
dat.append(random.uniform(0,1))
pylab.plot(dat)
pylab.draw()
time.sleep(1)
In python 2 (version 2.7.3 vith matplotlib 1.1.1), the code runs cleanly without errors but does not show the figure. A little trial and error with the python2 interpreter seemed to suggest to replace pylab.draw() with pylab.show(); doing this once is apparently sufficient (not, as with draw calling it after every change/addition to the plot). Hence:
import pylab
import time
import random
dat=[0,1]
pylab.plot(dat)
pylab.ion()
pylab.show()
for i in range (18):
dat.append(random.uniform(0,1))
pylab.plot(dat)
#pylab.draw()
time.sleep(1)
However, this doesn't work either. Again, it runs cleanly but does not show the figure. It seems to do so only when waiting for user input. It is not clear to me why this is, but the plot is finally shown when a raw_input() is added to the loop
import pylab
import time
import random
dat=[0,1]
pylab.plot(dat)
pylab.ion()
pylab.show()
for i in range (18):
dat.append(random.uniform(0,1))
pylab.plot(dat)
#pylab.draw()
time.sleep(1)
raw_input()
With this, the script will of course wait for user input while showing the plot and will not continue computing the data before the user hits enter. This was, of course, not the intention.
This may be caused by different versions of matplotlib (1.1.1 and 1.2.x) or by different python versions (2.7.3 and 3.2.3).
Is there any way to accomplish with python 2 with a stable (1.1.1) matplotlib what the above script (the first one) does in python 3, matplotlib 1.2.x:
- computing data (which takes a while, in the above example simulated by time.sleep()) in a loop or iterated function and
- (while still computing) showing what has already been computed in previous iterations
- and not bothering the user to continually hit enter for the computation to continue
Thanks; I'd appreciate any help...
You want the pause function to give the gui framework a chance to re-draw the screen:
import pylab
import time
import random
import matplotlib.pyplot as plt
dat=[0,1]
fig = plt.figure()
ax = fig.add_subplot(111)
Ln, = ax.plot(dat)
ax.set_xlim([0,20])
plt.ion()
plt.show()
for i in range (18):
dat.append(random.uniform(0,1))
Ln.set_ydata(dat)
Ln.set_xdata(range(len(dat)))
plt.pause(1)
print 'done with loop'
You don't need to create a new Line2D object every pass through, you can just update the data in the existing one.
Documentation:
pause(interval)
Pause for *interval* seconds.
If there is an active figure it will be updated and displayed,
and the gui event loop will run during the pause.
If there is no active figure, or if a non-interactive backend
is in use, this executes time.sleep(interval).
This can be used for crude animation. For more complex
animation, see :mod:`matplotlib.animation`.
This function is experimental; its behavior may be changed
or extended in a future release.
A really over-kill method to is to use the matplotlib.animate module. On the flip side, it gives you a nice way to save the data if you want (ripped from my answer to Python- 1 second plots continous presentation).
example, api, tutorial
Some backends (in my experience "Qt4Agg") require the pause function, as #tcaswell suggested.
Other backends (in my experience "TkAgg") seem to just update on draw() without requiring a pause. So another solution is to switch your backend, for example with matplotlib.use('TkAgg').
Related
This is my code and after calculating some stuff I want it to draw them at each step
import time
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
FilePatch='E:\\# Civil Engineering Undergraduate\\Projects\\Python\\Frame'
NodesFile=FilePatch+'\\nodes.xlsx'
MemsFile=FilePatch+'\\members.xlsx'
MatsFile=FilePatch+'\\sections.xlsx'
nodes=pd.read_excel(NodesFile)
mems=pd.read_excel(MemsFile)
mats=pd.read_excel(MatsFile)
nodes=np.array(nodes)
mems=np.array(mems)
mats=np.array(mats)
np.nan_to_num(nodes)
np.nan_to_num(mems)
np.nan_to_num(mats)
Segments=100
Scale=1
n=np.size(nodes[:,0])
m=np.size(mems[:,0])
UsedEIA=np.zeros((m,3))
.
.
.
But the problem is that when it calls the plt.plot(...) for the first time it stops execution and won't go on unless I close the figure!
Is there any solution for this issue??
.
.
.
for i in range(1,1+n):
dx=Scale*D[3*i-3,0]
dy=Scale*D[3*i-2,0]
xn=nodes[nodes[:,0]==i,1]+dx
yn=nodes[nodes[:,0]==i,2]+dy
plt.text(xn,yn,str(i))
s=np.sum(nodes[nodes[:,0]==i,3:5])
if nodes[nodes[:,0]==i,5]==1:
plt.scatter(xn,yn,c='r',marker='s')
elif nodes[nodes[:,0]==i,3]==1 or nodes[nodes[:,0]==i,4]==1:
plt.scatter(xn,yn,c='g',marker='^')
plt.axis('equal')
plt.show()
time.sleep(0.1)
Also I wanna add some text in to my plot but it gives me an error which I can't understand it!
Here it is:
p=mems[i,4]
px=mems[i,3]
dl=mems[i,5]*L
w=mems[i,6]
xtxt=(FrameShape[0,0]+FrameShape[0:])/2
ytxt=(FrameShape[1,0]+FrameShape[1:])/2
xtxtp=FrameShape[0,0]
xtxtpx=FrameShape[0,0]+abs(px)/(1+abs(p))
xtxtw=FrameShape[0,0]+abs(p)/(1+abs(p))+abs(px)/(1+abs(px))
if p!=0 or px!=0:
btxt=' Py='+str(p)+' , Px=',str(px)+' #'+str(dl)
plt.text(xtxtp,ytxt-0.5,btxt)
XY=np.array([X,Shape])
FrameShape=np.transpose(T[0:2,0:2])#XY
FrameShape[0,:]=FrameShape[0,:]+xi
FrameShape[1,:]=FrameShape[1,:]+yi
if w!=0:
atxt='UL='+str(w)
plt.text(xtxtw,ytxt+0.5,atxt)
This is the error it gives me in the console:
TypeError: only size-1 arrays can be converted to Python scalars
plt.show() blocks the execution of your code. To avoid that, you could replace that line by plt.show(block=False). Your application will then run, but, as described in this post, your plots will likely not show up during execution.
So instead, try replacing plt.show() by
plt.show(block=False)
plt.pause(0.001)
in order to see the plots during runtime.
Finally, add a plt.show() at the very end of your program to keep the plots open, elsewise every figure will be closed upon program termination.
I am using PyCharm 2016.1 and Python 2.7 on Windows 10 and imported the matplotlib module.
As the matplotlib module ist very extensive and I am relatively new to Python, I hoped the Auto Complete function in PyCharm could help me to get an overview of the existent properties/ functions of an object. It would be more convenient as digging through the api documentation every time, not knowing what to look for an where to find it.
For example:
from matplotlib import pyplot as plt
fig, ax = plt.subplots()
When I type ax. there ist no auto completion for the properties, functions etc. of the axis, I only get the suggestions list.
I already tried this and imported the axis module directly with:
import matplotlib.axis as axis
or
from matplotlib.axis import Axis as axis
Smart Auto Completion and 'Collect run-time types information' is already enabled.
Is there a way to enable the auto completion like described or is there another IDE that supports that?
I believe your problem is highlighted here:
https://intellij-support.jetbrains.com/hc/en-us/community/posts/205816499-Improving-collecting-run-time-type-information-for-code-insight?sort_by=votes
Tldr return types can vary, so it cant be figured out at compile time.
Most accepted way is to use a type hint, since it can only figure out what type it as run time :
import matplotlib.axes._axes as axes
fig = plt.figure(figsize=(5,10))
ax1 = fig.add_subplot(3,1,1) # type:axes.Axes
ax1.set_xlabel('Test') <- now autocompletes
You can also try an assert isinstance:
import matplotlib.axes._axes as axes
fig = plt.figure(figsize=(5,10))
ax1 = fig.add_subplot(3,1,1)
assert isinstance(ax1, axes.Axes)
ax1.set_xlabel('Test')
It wont find the autocomplete if you do it after the method you are looking for:
ax1.set_xlabel('Test')
assert isinstance(ax1, axes.Axes)
With this, you shouldnt let isinstance dictate the control flow of your code, if you are trying to run a method that doesnt exist on an object, it should crash, however, if your different object has a method of the same name (!) then you have inadvertently reached that goal without annotations being there. So I like it better, since you want it to crash early and in the correct place. YMMV
From the doc:
Assertions should not be used to test for failure cases that can
occur because of bad user input or operating system/environment
failures, such as a file not being found. Instead, you should raise an
exception, or print an error message, or whatever is appropriate. One
important reason why assertions should only be used for self-tests of
the program is that assertions can be disabled at compile time.
If Python is started with the -O option, then assertions will be
stripped out and not evaluated. So if code uses assertions heavily,
but is performance-critical, then there is a system for turning them
off in release builds. (But don't do this unless it's really
necessary.
https://wiki.python.org/moin/UsingAssertionsEffectively
Alternatively, if you dont want to add to your code in this fashion, and have Ipython/jupyter installed through anoconda, you can get the code completion from the console by right clicking the code to be ran and choosing "execute selection in console"
In addition to Paul's answer. If you are using fig, ax = plt.subplots() , you could use figure type hint. See below example:
from matplotlib import pyplot as plt
import matplotlib.axes._axes as axes
import matplotlib.figure as figure
fig, ax = plt.subplots() # type:figure.Figure, axes.Axes
ax.
fig.
Introduction
As I am coming from matlab, I am used to an interactive interface where a script can update figures while it is running. During the processing each figure can be re-sized or even closed. This probably means that each figure is running in its own thread which is obviously not the case with matplotlib.
IPython can imitate the Matlab behavior using the magic command %pylab or %matplotlib which does something that I don't understand yet and which is the very point of my question.
My goal is then to allow standalone Python scripts to work as Matlab does (or as IPython with %matplotlib does). In other words, I would like this script to be executed from the command line. I am expecting a new figure that pop-up every 3 seconds. During the execution I would be able to zoom, resize or even close the figure.
#!/usr/bin/python
import matplotlib.pyplot as plt
import time
def do_some_work():
time.sleep(3)
for i in range(10):
plt.plot([1,2,3,4])
plt.show() # this is way too boilerplate, I'd like to avoid it too.
do_some_work()
What alternative to %matplotlib I can use to manipulate figures while a script is running in Python (not IPython)?
What solutions I've already investigated?
I currently found 3 way to get a plot show.
1. %pylab / %matplotlib
As tom said, the use of %pylab should be avoided to prevent the namespace to be polluted.
>>> %pylab
>>> plot([1,2,3,4])
This solution is sweet, the plot is non-blocking, there is no need for an additionnal show(), I can still add a grid with grid() afterwards and I can close, resize or zoom on my figure with no additional issues.
Unfortunately the %matplotlib command is only available on IPython.
2. from pylab import * or from matplotlib.pyplot import plt
>>> from pylab import *
>>> plot([1,2,3,4])
Things are quite different here. I need to add the command show() to display my figure which is blocking. I cannot do anything but closing the figure to execute the next command such as grid() which will have no effect since the figure is now closed...
** 3. from pylab import * or from matplotlib.pyplot import plt + ion()**
Some suggestions recommend to use the ion() command as follow:
>>> from pylab import *
>>> ion()
>>> plot([1,2,3,4])
>>> draw()
>>> pause(0.0001)
Unfortunately, even if the plot shows, I cannot close the figure manually. I will need to execute close() on the terminal which is not very convenient. Moreover the need for two additional commands such as draw(); pause(0.0001) is not what I am expecting.
Summary
With %pylab, everything is wonderful, but I cannot use it outside of IPython
With from pylab import * followed by a plot, I get a blocking behavior and all the power of IPython is wasted.
from pylab import * followed by ion offers a nice alternative to the previous one, but I have to use the weird pause(0.0001) command that leads to a window that I cannot close manually (I know that the pause is not needed with some backends. I am using WxAgg which is the only one that works well on Cygwin x64.
This question advices to use matplotlib.interactive(True). Unfortunately it does not work and gives the same behavior as ion() does.
Change your do_some_work function to the following and it should work.
def do_some_work():
plt.pause(3)
For interactive backends plt.pause(3) starts the event loop for 3 seconds so that it can process your resize events. Note that the documentation says that it is an experimental function and that for complex animations you should use the animation module.
The, %pylab and %matplotlib magic commands also start an event loop, which is why user interaction with the plots is possible. Alternatively, you can start the event loop with %gui wx, and turn it off with %gui. You can use the IPython.lib.guisupport.is_event_loop_running_wx() function to test if it is running.
The reason for using ion() or ioff() is very well explained in the 'What is interactive mode' page. In principle, user interaction is possible without IPython. However, I could not get the interactive-example from that page to work with the Qt4Agg backend, only with the MacOSX backend (on my Mac). I didn't try with the WX backend.
Edit
I did manage to get the interactive-example to work with the Qt4Agg backend by using PyQt4 instead of PySide (so by setting backend.qt4 : PyQt4 in my ~/.config/matplotlibrc file). I think the example doesn't work with all backends. I submitted an issue here.
Edit 2
I'm afraid I can't think of a way of manipulating the figure while a long calculation is running, without using threads. As you mentioned: Matplotlib doesn't start a thread, and neither does IPython. The %pylab and %matplotlib commands alternate between processing commands from the read-eval-print loop and letting the GUI processing events for a short time. They do this sequentially.
In fact, I'm unable to reproduce your behavior, even with the %matplotlib or %pylab magic. (Just to be clear: in ipython I first call %matplotlib and then %run yourscript.py). The %matplotlib magic puts Matplotlib in interactive-mode, which makes the plt.show() call non-blocking so that the do_some_work function is executed immediately. However, during the time.sleep(3) call, the figure is unresponsive (this becomes even more apparent if I increase the sleeping period). I don't understand how this can work at your end.
Unless I'm wrong you'll have to break up your calculation in smaller parts and use plt.pause (or even better, the animation module) to update the figures.
My advice would be to keep using IPython, since it manages the GUI event loop for you (that's what pylab/pylot does).
I tried interactive plotting in a normal interpreter and it worked the way it is expected, even without calling ion() (Debian unstable, Python 3.4.3+, Matplotlib 1.4.2-3.1). If I recall it right, it's a fairly new feature in Matplotlib.
Alternatively, you can also use Matplotlib's animation capabilities to update a plot periodically:
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import time
plt.ion()
tt = np.linspace(0, 1, 200)
freq = 1 # parameter for sine
t0 = time.time() # for measuring ellapsed time
fig, ax = plt.subplots()
def draw_func(i):
""" This function gets called repeated times """
global freq # needed because freq is changed in this function
xx = np.sin(2*np.pi*freq*tt)/freq
ax.set_title("Passed Time: %.1f s, " % (time.time()-t0) +
"Parameter i=%d" % i)
ax.plot(tt, xx, label="$f=%d$ Hz" % freq)
ax.legend()
freq += 1
# call draw_func every 3 seconds 1 + 4 times (first time is initialization):
ani = animation.FuncAnimation(fig, draw_func, np.arange(4), interval=3000,
repeat=False)
# plt.show()
Checkout matplotlib.animation.FuncAnimation for details. You'll find further examples in the examples section.
I was able to successfully install matplotlib; however, when I run my code, I don't get an error, but instead the Python icon bouncing over and over again.
I don't know if it has anything to do with
from rcParamsSettings import *
I don't have any idea what that is, but if I try to run it with that line uncommented out, I get
ImportError: No module named rcParamsSettings
Here's the code I'm trying to run:
import pylab
#from rcParamsSettings import *
import random
def flipPlot(minExp, maxExp):
"""Assumes minExp and maxExp positive integers; minExp < maxExp
Plots results of 2**minExp to 2**maxExp coin flips"""
ratios = []
diffs = []
xAxis = []
for exp in range(minExp, maxExp + 1):
xAxis.append(2**exp)
for numFlips in xAxis:
numHeads = 0
for n in range(numFlips):
if random.random() < 0.5:
numHeads += 1
numTails = numFlips - numHeads
ratios.append(numHeads/float(numTails))
diffs.append(abs(numHeads - numTails))
pylab.title('Difference Between Heads and Tails')
pylab.xlabel('Number of Flips')
pylab.ylabel('Abs(#Heads - #Tails)')
pylab.plot(xAxis, diffs)
pylab.figure()
pylab.title('Heads/Tails Ratios')
pylab.xlabel('Number of Flips')
pylab.ylabel('#Heads/#Tails')
pylab.plot(xAxis, ratios)
random.seed(0)
flipPlot(4, 20)
What do I need to do to get the code running?
Note: My experience with programming and Python is very limited; I'm just starting out.
You need to use pylab.show() otherwise nothing will come up.
See the example here: http://matplotlib.org/examples/pylab_examples/simple_plot.html
(although you should avoid using from pylab import *, the way you import is fine.)
There are cases in MatPlotLib where you do not want to show the graph. An example I have is designing a graph on a server using data collected by an automated process. The server has no screen and is only accessed by a terminal, and therefore trying to show a graph will result in an error as there is no DISPLAY variable set (there is no screen to display to).
In this case it would be normal to save the figure somewhere using pylab.savefig(), and then maybe email it or use an ftp to send it somewhere it can be viewed.
Because of this MatPlotLib will not implicitly show a graph and must be asked to show it.
Your code works for me if I add a pylab.show().
Alternatively, you could save the plot to a file:
pylab.savefig("file.png")
This makes sense if you are updating your plot frequently.
This question already has answers here:
pylab.ion() in python 2, matplotlib 1.1.1 and updating of the plot while the program runs
(2 answers)
Closed 8 years ago.
There are a lot of questions about matplotlib, pylab, pyplot, ipython, so I'm sorry if you're sick of seeing this asked. I'll try to be as specific as I can, because I've been looking through people's questions and looking at documentation for pyplot and pylab, and I still am not sure what I'm doing wrong. On with the code:
Goal: plot a figure every .5 seconds, and update the figure as soon as the plot command is called.
My attempt at coding this follows (running on ipython -pylab):
import time
ion()
x=linspace(-1,1,51)
plot(sin(x))
for i in range(10):
plot([sin(i+j) for j in x])
#see **
print i
time.sleep(1)
print 'Done'
It correctly plots each line, but not until it has exited the for loop. I have tried forcing a redraw by putting draw() where ** is, but that doesn't seem to work either. Ideally, I'd like to have it simply add each line, instead of doing a full redraw. If redrawing is required however, that's fine.
Additional attempts at solving:
just after ion(), tried adding hold(True) to no avail.
for kicks tried show() for **
The closest answer I've found to what I'm trying to do was at plotting lines without blocking execution, but show() isn't doing anything.
I apologize if this is a straightforward request, and I'm looking past something so obvious. For what it's worth, this came up while I was trying to convert matlab code from class to some python for my own use. The original matlab (initializations removed) which I have been trying to convert follows:
for i=1:time
plot(u)
hold on
pause(.01)
for j=2:n-1
v(j)=u(j)-2*u(j-1)
end
v(1)= pi
u=v
end
Any help, even if it's just "look up this_method" would be excellent, so I can at least narrow my efforts to figuring out how to use that method. If there's any more information that would be useful, let me know.
from pylab import *
import time
ion()
tstart = time.time() # for profiling
x = arange(0,2*pi,0.01) # x-array
line, = plot(x,sin(x))
for i in arange(1,200):
line.set_ydata(sin(x+i/10.0)) # update the data
draw() # redraw the canvas
pause(0.01)
print 'FPS:' , 200/(time.time()-tstart)
ioff()
show()
########################
The above worked for me nicely. I ran it in spyder editor in pythonxy2.7.3 under win7 OS.
Note the pause() statement following draw() followed by ioff() and show().
The second answer to the question you linked provides the answer: call draw() after every plot() to make it appear immediately; for example:
import time
ion()
x = linspace(-1,1,51)
plot(sin(x))
for i in range(10):
plot([sin(i+j) for j in x])
# make it appear immediately
draw()
time.sleep(1)
If that doesn't work... try what they do on this page: http://www.scipy.org/Cookbook/Matplotlib/Animations
import time
ion()
tstart = time.time() # for profiling
x = arange(0,2*pi,0.01) # x-array
line, = plot(x,sin(x))
for i in arange(1,200):
line.set_ydata(sin(x+i/10.0)) # update the data
draw() # redraw the canvas
print 'FPS:' , 200/(time.time()-tstart)
The page mentions that the line.set_ydata() function is the key part.
had the exact same problem with ipython running on my mac. (Enthought Distribution of python 2.7 32bit on Macbook pro running snow leopard).
Got a tip from a friend at work. Run ipython from the terminal with the following arguments:
ipython -wthread -pylab
This works for me. The above python code from "Daniel G" runs without incident, whereas previously it didn't update the plot.
According to the ipython documentation:
[-gthread, -qthread, -q4thread, -wthread, -pylab:...] They provide
threading support for the GTK, Qt (versions 3 and 4) and WXPython
toolkits, and for the matplotlib library.
I don't know why that is important, but it works.
hope that is helpful,
labjunky
Please see the answer I posted here to a similar question. I could generate your animation without problems using only the GTKAgg backend. To do this, you need to add this line to your script (I think before importing pylab):
matplotlib.use('GTkAgg')
and also install PyGTK.