I want the display graph by jupyter notebook embed to my pyqt app
It seems it's using the function by Ipython display
and may need HTML support
so, is there any way that I can embed these displays to qt, or even a pop out window that can control by qt?
I tried the jupyter console, but I think that's not what I want
Related
I'm using python3 with Tkinter but I can't get over that i need a mainloop() statemment to get the screen to pop up and draw, then only by closing the graphics screen will the program then go on to the text to speak section. How can I have my graphics displayed without the program halting?
I want to create a application in python using wxpython library with multiple windows which will be inter-related to each other using buttons, i.e. we can go from one window to other and again come back to the previous window using buttons just like an app.
There should be one window on the screen at any time if possible. Is this possible using wxpython library. If so then can you suggest me how.
It is really simple. Normally you create one window (usually a frame or a dialog). If you want more windows, you will just create more frames or dialogs.
Running my animated plot in a jupyter notebook is OK. Now trying the same code in Jupyter Lab does not work. I've read a lot of similar situations, tried every solution given, but my plot stays static. No animation running.
This is my extension list, installed and enabled ('jupyter lab build'):
$ jupyter labextension list
JupyterLab v0.35.4
Known labextensions:
app dir: /home/teleuff/anaconda3/share/jupyter/lab
#jupyter-widgets/jupyterlab-manager v0.38.1 enabled OK
#jupyterlab/plotly-extension v1.0.0 enabled OK
jupyter-matplotlib v0.3.0 enabled OK
plotlywidget v1.1.0 enabled OK
%matplotlib inline does not raise JavaScript error, but my plot is not animated.
%matplotlib widget and %pylab inline also have the same effect, only difference is the output line:
Populating the interactive namespace from numpy and matplotlib
Any ideas?
Thanks in advance!
Find and click the little shield on the table frame at the bottom of the screen. Is this shield icon displaying a check mark inside the shield? Hover the mouse above the shield, does the shield then display a message:
{ Active Cell Trusted: x of y shields trusted }
It's likely there is no check mark inside the shield. The reason is the Jupyter extension is designed to be locked down.
Review the Jupyter-notebook security page: Jupyter-notebook
Overview from the security page:
Untrusted HTML is always sanitized
Untrusted JavaScript is never executed
Html and JavaScript in Markdown cells are never trusted
Outputs generated by the user are trusted
Any other HTML or JavaScript (in Markdown cells, output generated by owners) is never trusted
The bottom line and central question of trust is: Did the current user do this? I've found Jupyter Lab security settings make bullet-number 3 the overriding rule.
I assume it should be possible to change the figure setting after plotting (not in the code).
By default, the Interactive Navigation has these buttons as explained in below link: https://matplotlib.org/users/navigation_toolbar.html?highlight=interactive%20navigation
However, it is not possible to change graph settings through any of these buttons (e.g. change axis limitations, or change label name, or change title). These options are available in MATLAB so it definitely should be there in Python3. How can I add these features to Interactive Navigation window?
P.S. My matplotlib version is 3.1.0
"These options are available in MATLAB so it definitely should be there in Python3" There is no indication for that causality being true.
Setting some of the parameters is nonetheless possible when using the Qt backend.
import matplotlib
matplotlib.use("Qt5Agg")
Then a respective button is available
Matplotlib when you invoke the show function, it will open a small python window and show the chart. How can I make Bokeh do the same? I don't want to save a file or open a browser windows. I want to to output like matplotlib. Why? Because I want to show its graphs inside Microsoft Power BI. So it has to produce some sort of image I guess.
Bokeh's normal operation is to generate web content, i.e. HTML+JS that can drive interactive visualizations in the browser. Doing that is explicitly the main reason it was created. However, it is possible to export Bokeh plots as PNG files:
from bokeh.io import export_png
export_png(plot, filename="plot.png")
Note that this will save a file to disk, not open any sort of application window. There is nothing built into Bokeh to auto-open except Bokeh HTML output to browsers.