Is there any way to get ginput() to work to plot inline interactive plots in jupter lab/notebook?
For example; something like:
pts = plt.ginput(2, show_clicks=True)
for p in pts:
plot_trajectory(ax, p[1], p[0], 0.1, 25000)
plt.show()
Would be used to let the user click two points on the plot that are then used as starting points for the trajectories plotted by another function. I've managed to get it working using the qt matplotlib magic but this cannot be integrated with inline plots and wigets. Is there any way to do this?
Related
I am making some small tests in Jupyter. The user should see two plots, one on the left and one on the right. Than after clicking somewhere on the left plot something on the right plot should happen. For example here a click on the left plot will produce a red dot on the right plot in the same place:
%matplotlib notebook
def onclick(event):
ax.clear()
ax2.clear()
ax.set_xlim(0,10)
ax.set_ylim(0,10)
ax2.set_xlim(0,10)
ax2.set_ylim(0,10)
ax2.plot([event.xdata],[event.ydata],'o',color='red')
ax.figure.canvas.draw_idle()
ax2.figure.canvas.draw_idle()
fig = plt.figure(figsize=(20,10))
ax = fig.add_subplot(121)
ax2 = fig.add_subplot(122)
ax.set_xlim(0,10)
ax.set_ylim(0,10)
ax2.set_xlim(0,10)
ax2.set_ylim(0,10)
cid = fig.canvas.mpl_connect('button_press_event',onclick)
This works, but the visualization in Jupyter is not the best. Is there a way to have this kind of interactive plots working outside of a Jupyter notebook ? Maybe in a window with varying dimensions ? As an example, how would one proceed with the example above ?
You can use plotly and export your plots to html file:
https://plotly.com/python/interactive-html-export/
I think I found a possible simple answer to my needs. Simply put the code in the question in a python script, remove the 'magic' command and insert at the end:
plt.show(block=True)
This way matplotlib will just use a different backend than notebook or inline in Jupiter and plot the figure in a separate window. This window is compatible with the interactive commands from matplotlib. I am not sure about widget compatibility though I will try and update the answer.
Update: I do not think ipywidgets can be used with plt.show() since these are not plotted in an axes, but there are some widgets within matplotlib (matplotlib.widgets) that can be used. Though, the resulting speed in my case is not satisfactory so I would avoid combining matplotlib widgets with matplotlib event catching.
I am facing the following problem: I need two interactive plots to work at the same time on Jupyter, however they are interfering. When I rotate the cell of the first, the second plot stops being interactive and becomes "inline". Other times one of the plots looks like this:
The expected result was something like this
I imagine the problem is in the implementation I made. As you can see below, I use plt.something to put things in the figure (both for plot 1 and plot 2).
I'm using the %matplotlib notebook environment and tried to implement using fig1, ax1 = plt.subplots(). I would like to know if it is possible to do this type of implementation, where there is no conflict between plots? Maybe I am using matplotlib badly, so I would like some suggestions.
I am trying to create a plot with matplotlib that has tooltip appearing when hovering hover certain elements of the charts. I want to do that in the Jupyter Notebook, with python 3.
I have tried the snippets provided here:
http://matplotlib.org/examples/event_handling/pick_event_demo.html
Possible to make labels appear when hovering over a point in matplotlib?
Is there a matplotlib equivalent of MATLAB's datacursormode?
Matplotlib basemap: Popup box
But none of them work. The plot shows but is not interactive.
I tried with and without the magic %matplotlib inline with no effect.
I of course also modified the print statement when it was without parenthesis.
Is there a specific command or backend to use in order to have the interaction working in Jupyter?
EDIT:
the example working with mpld3 "works" but i would rather stick to the basic matplotlib.
I think you want %matplotlib notebook. This will integrate interactive plots in the notebook.
When using Matplotlib to generate figures with hatching (e.g. pie, bar, bubble charts), I'm having some trouble getting decent resolution out of the PDF version of the figure. Saving as EPS is fine, but as soon as I use epstopdf or MPL's savefig(*.pdf), the hatching becomes pixellated and distored... the vector nature of the image appears to have been lost.
See minimal code below.
from matplotlib import pyplot as plt
# Define hatching styles
hatching = ["/", "o"]
fig, ax = plt.subplots()
wedges, texts = ax.pie([0.4, 0.6], colors=("SteelBlue", "Tomato"))
# Apply the hatching
for j, patch in enumerate(wedges): patch.set_hatch(hatching[j])
fig.savefig("hatchtest.pdf")
I've used Gimp to zoom in on a part of the plot to illustrate the difference...
Zoomed in on the EPS figure
Zoomed in on the PDF figure
As for system specific details, I'm using Ubuntu 13.04, Python 2.7.4 with MPL 1.2.1. I've tried different backends but nothing seems to resolve this. I'd ideally like to have nice vector images in EPS and PDF so that it's all journal-friendly. Any pointers would be much appreciated.
Just a problem with Evince PDF viewer. Viewing in Adobe Reader or printing the plot gives the desired result.
I have to translate an image plotting script from matlab to matplotlib/pylab, and I'm trying to achieve the same effect as the matlab image below:
As you can see, the z order of the plots seem to be higher than the z order of the grid, so the markers are not hidden by the axes. However, I can't figure out a way to do the same with my matplotlib image:
I'm wondering if it is possible to get the same display without having to increase the limits of the y axis.
To get the marker to show beyond the axes you can turn the clipping off. This can be done using the keyword argument in the plot command clip_on=False.
For example:
import matplotlib.pyplot as plt
plt.plot(range(5), range(5), 'ro', markersize=20, clip_on=False, zorder=100)
plt.show()
This is a complete example of how to use the zorder kwarg: http://matplotlib.sourceforge.net/examples/pylab_examples/zorder_demo.html
Note that a higher z-order equates to a graph-element being more in the foreground.
For your second question, have a look at the figsize kwarg to instances of the Figure class: http://matplotlib.sourceforge.net/api/figure_api.html?highlight=figsize#matplotlib.figure.Figure
If you run into issues, please post some of your code and we'll be able to give more-detailed recommendations. Best of luck.
If you're plotting the lines one after the other, just change the order of the plotting calls and that would fix the z order.