I have a long Jupyter notebook code and there is many cells, which are redrawing the actual graph plot. When I am running cells after changing their contents I need to check the plot, but I always need to scroll up and down. I would prefer to watch the plot changes in separated window (I am using two monitors), so I will change the cell content, run the cell, and then just turn my head and see the plot - without any scrolling. Is there a way how to do that? I know it can be done by Spyder, but I want to do it in Jupyter notebook, since I use a lot of notebook advantages, such as Latex notes and headings between cells. Thanks a lot for any advice!
It would be great if you could tell us how you print your graph (what library ?). Ipython provide magic command. For example, if you use matplotlib to plot some figures, just add %matplotlib qt on top of your cell to make the plots appear in a separate window.
See the list of magic command available here.
Related
I'm using matplotlib to show a plot with %matplotlib widget in jupyter lab. Almost every time I show the plot, next thing I have to do is zoom in and examine one of the sections of the plot. I would like to be able to show the plot zoomed into that section, and if I want to examine the rest of the plot, as I sometimes do, I would press back button and see all of it.
This is similar to showing subplot with relevant data or using plt.xlim, except I would like to do it in a single plot so the data I'm looking at can occupy more screen space, and plt.xlim just shows relevant stretch of data without possibility to zoom out again.
How do I do this is jupyter lab?
I'm learning Matplotlib and using a Jupyter notebook to track each thing that I learn. However, I ran into a problem because I have multiple cells with matplotlib code. In one of my first cells, I run plt.show(), which outputs a plot beneath the cell. Further down the page, I have some other code which plots new points, resizes an axis, etc., then runs plt.show()....which works, but applies the changes to the original plot that was created after the first cell.
Is there any way to get a new plot window to display beneath whichever cell I am running?
(The reason I want to do this: The first cell might be an example showing how to plot a basic set of points. I want this to display its own simple plot. Further down the page, I resize axes and change the style of graph. However, when this plots, I want to see a separate plot, or maybe the same plot redone (as in, it can keep the original points I plotted -- no need to clear the whole thing) but with the new changes, beneath this more complex cell.)
UPDATE: Images.
In Image 1, I have run the first cell of code. The graph displays beneath the cell. Just as I want.
In this second image, I've now run the lower block of code (marked [3]). The changes, however, are applied to the plot sitting above it, because that's where it was originally created. But I'd like a new plot, or maybe not a clean new plot, but at least some way to make that plot display beneath cell [3] that I just ran.
In the comments, you mentioned that you're using the %matplotlib notebook magic, because it allows interactivity.
One option is to stop using interactivity.
As you found, you can turn off interactivity with plt.ioff(). You could also stop using %matplotlib notebook altogether and instead use %matplotlib inline (called at the top of the notebook). With %matplotlib inline, you don't need to call plt.show().
But you want to use interactivity.
So what you should do is define a new figure after you've plotted your first figure. To do this, call plt.figure() after the first plot, before the code for the second.
While there are a few things that are still being worked out, I am a big fan of the LightTable editor. The IPython Notebook is a remarkable delivery system, but managing a larger product is a bit easier in a more conventional development environment.
One thing that I have not yet figured out, however, is complicated plotting in LightTable. With no cell equivalent, I am not sure how to modify plot components because each command seems to be considered independently. In particular, I am not clear on how to work with subplots. I am unable to connect the actual plot to the subplot array. For example, consider the following:
fig,ax=plt.subplots(2)
ax[0].hist(np.random.uniform(size=100))
ax[1].hist(np.random.normal(size=100))
When I create the subplots, they show up empty inline. The remaining code, however, does not cause them to update inline. In the Notebook, all the code is considered jointly in batch. LightTable interactivity is a bit closer to dealing with an interpreter in interactive mode (even though the script is obviously preserved). I have experiemented with turning interactivity on and off via plt.ioff(), but to no avail. Any assistance would be greatly appreciated...
I often find myself using matplotlib to quickly display data, then later going back and tweaking my plotting code to make pretty figures. In this process, I often use the interactive plot window to adjust things like spacing, zooming, cropping, etc. While I can easily save the resulting figure to an image file, what I really want is to save the sequence of function calls/parameters that produced it.
Note that I don't particularly care to open the same figure again (as in Saving interactive Matplotlib figures). Even something as simple as being able to print the various properties of the figure and axes would be useful.
While I don't have the answer to your specific question, I'd generally suggest using the Ipython Notebook for these things (and much more!)
Make sure you have %pylab inline in one cell.
When you plot, it will display it in the notebook itself. Then within your cell, just keep experimenting until you have it right (use Ctrl-Enter in the cell). Now the cell will have all the statements you need (and no more!)
The difference between the command line interpreter and the notebook is that the former all statements you typed which leads to a lot of clutter. With the notebook you can edit the line in place.
A similar question here
has an answer I just posted here.
The gist: use MatPlotLib's picklable figure object to save the figure object to a file. See the aforementioned answer for a full example.
Here's a shortened example:
fig, ax = matplotlib.pyplot.subplots()
# plot some stuff
import pickle
pickle.dump( fig, open('SaveToFile.pickle', 'wb') )
This does indeed save all plotting tweaks, even those made by the GUI subplot-adjuster. Unpickling via pickle.load() still allows you to interact via CLI or GUI.
I'm writing a program in Python. The first thing that happens is a window is displayed (I'm using wxPython) that has some buttons and text. When the user performs some actions, a plot is displayed in its own window. This plot is made with R, using rpy2. The problem is that the plot usually pops up on top of the main window, so the user has to move the plot to see the main window again. This is a big problem for the user, because he's lazy and good-for-nothing. He wants the plot to simply appear somewhere else, so he can see the main window and the plot at the same time, without having to lift a finger.
Two potential solutions to my problem are:
(1) display the plot within a wxPython frame (which I think I could control the location of), or
(2) be able to specify where on the screen the plot window appears.
I can't figure out how to do either.
Plot to a graphics file using jpeg(), png() or another device, then display that file on your wxWidget.
There are few lines about this in the documentation:
http://rpy.sourceforge.net/rpy2/doc-2.2/html/graphics.html
By default R plots to the "interactive" plotting device (X11). Specifying a non-interactive file-based device (jpeg, png, pdf - pdf being probably easier if rescaling or zooming is wished).
There is a very experimental feature in rpy2-2.2.0dev that would let one implement relatively easily new devices (e.g., plot into matplotlib canvases, or wxWindows panels), but unfortunately this is not complete, not documented, and probably not fully working.