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PyCharm - Auto Completion for matplotlib (and other imported modules)

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.

No module named objects [bokeh]

Note from maintainers: This question is no longer relevant. The bokeh.objects module has not existed for years
I'm trying to run this script:
#Code will be significantly simplified in the 0.4 release
import time
from bokeh.objects import GlyphRenderer
renderer = [r for r in curplot().renderers if isinstance(r, GlyphRenderer)][0]
ds = renderer.data_source
while True:
df = pd.io.json.read_json(url+json_call)
ds.data["x"] = x+N*i
ds.data["y"] = df.rssi
ds._dirty = True
session().store_obj(ds)
time.sleep(1.5)
i+=1
from:
https://www.continuum.io/content/painless-streaming-plots-bokeh
but at this line:
from bokeh.objects import GlyphRenderer
I got:
No module named objects
The version I'm using is
0.11.1
On linux mint 17.1

Note from maintainers: This answer is no longer relevant. The bokeh.objects module has not existed for years
did you try installing bokeh before trying the examples? If not, just run:
pip install bokeh
and try your script again.
if it does not work, it's likely that the bokeh sources changed, so you might want to change the
from bokeh.objects import GlyphRenderer
into
from bokeh.models.renderers import GlyphRenderer
cf the source code
At the first line of your example it states:
#Code will be significantly simplified in the 0.4 release
which means that the example's code was already about to be deprecated at the time of the writing of the tutorial.
So instead of copy/pasting that code, you should try to understand how it works, and recreate it using the documentation and sources:
http://docs.bokeh.org/en/latest/docs/user_guide/quickstart.html#userguide-quickstart
https://github.com/bokeh/bokeh
have fun!

The objects module was deleted in commit 5b5d28304c5ea209e243af5943917fe494d9ef9c (v0.7.1) after being deprecated in 8bb4a2f1f43b39b869c508ef7aee69f7aabb46b8 (v0.7.0). The deprecation message reads: "use bokeh.models instead". I leave finding GlyphRenderer in the current codebase as an exercise for you.

conda update bokeh solved this for me.

Regarding streaming (since that is is the example the OP was interested in), the current and stable streaming API is demonstrated here:
https://github.com/bokeh/bokeh/tree/master/examples/app/ohlc
This simple interface has been the way to efficiently stream to data soruces since 0.11.1, and will continue to be going forward.
The basic idea is to construct a dict with all the columns of a data source, and just the new data that is to be appended:
# construct a source with x and y columns
source = ColumnDataSource(data=dict(x=[....], y=[....]))
# sends the few new data points to the client, does not re-send all the data
source.stream(dict(x=[10, 11], y=[20, 21]))
Typically you'd probably call stream from some kind of periodic callback. The OHLC app linked above is a complete example.

How to manipulate figures while a script is running in Python?

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.

Hold is not working for pyplot

I have a problem using pyplot. I am new to Python so sorry if I am doing some obvious mistake.
After I have plotted something using pyplot it shows the graph, but when I then try and add e.g. ylabel it will not update the current graph. It results in a new graph with only the ylabel, not previously entered information. So to me it seems to be a problem with recognizing the current graph/axis, but the ishold delivers a True statement.
My setup is Python 2.7 in Python(x,y). The problem occurs both in the Spyder IDE and the IPython Qt Console. It does however not occur in the regular IPython console (which, by constrast, is not interactive, but everything is included when using show(). When I turn off interactive in Spyder/Qt console it does not show anything after using the show() command).
import matplotlib.pyplot as plt
plt.plot([1,2,3,4])
Out[2]: [<matplotlib.lines.Line2D at 0x78ca370>]

plt.ylabel('test')
Out[3]: <matplotlib.text.Text at 0x5bd5990>

plt.ishold()
Out[4]: True
matplotlib.get_backend()
Out[6]: 'module://IPython.kernel.zmq.pylab.backend_inline'
Hope any of you have some input. Thanks.

This is one of the things were InlineBackend have to behave differently from other backend or you would have sort of a memory leak. You have to keep explicit handle to matplotlib figure and/or set close_figure to False in config. Usually pyplot is a compatibility layer for matlab for convenience, try to learn to do using the Object Oriented way.
fig,ax = subplots()
ax.plot(range(4))
ax.set_ylabel('my label')
...

matplotlib.pyplot/pylab not updating figure while isinteractive(), using ipython -pylab [duplicate]

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.