matplotlib / matplotlib/ipympl

Partial or Glitchy Interactivity

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Jupyter Notebook
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Descripción

Partial or Glitchy Interactivity

In my dev. environment, interactive figures:

  • fail to show resize handle, figure header and footer are never displayed
  • do not respect (but do not error) settings for:
    • fig.canvas.header_visible
    • fig.canvas.footer_visible
    • fig.canvas.resizable
  • completely disappear on mouse click or drag (no toolbar option selected) and never return on selecting toolbar Reset option
  • toolbar panning/zooming work fine
  • playing with figure.set_frameon(False) seems to cure the disappearing figure issue

My production environment (with [as far as I can tell] same versions) works as expected:

  • shows and respects resize handle, figure header and footer are displayed
  • respects settings for:
    • fig.canvas.header_visible
    • fig.canvas.footer_visible
    • fig.canvas.resizable
  • does not disappear on mouse click or drag (no toolbar option selected)
  • toolbar panning/zooming work fine

Both environments are using the classic notebook experience (not Lab), the biggest/most obvious difference being that production is a TLJH installation (i.e. JupyterHub spawning single-user notebooks), but all the notebook package versions across environments appear to be in sync (see below), so unless spawning affects things silently, I'd be surprised if that's the issue.

I've borrowed and executed this code (from https://github.com/matplotlib/ipympl/issues/203) as a test to make sure there's nothing wonky in my code and because it incorporates the ioff/ion pattern I'm reliant on:

%matplotlib widget
from IPython.display import display # this is automatically imported in the notebook anyway
from ipywidgets.widgets import HBox
import matplotlib.pyplot as plt
from scipy.misc import face

plt.ioff() # turn off interactive mode so figure doesn't show
fig1, ax1 = plt.subplots()
fig2, ax2 = plt.subplots()
plt.ion() # figure still doesn't show

ax1.imshow(face())
ax2.imshow(face(True))

display(HBox([fig1.canvas, fig2.canvas]))

Executing this code exhibits all of the issues I've described, i.e. it does not work (as described above) in development, but does work in production.

Versions

Development environment:
 3.6.9 (default, Jan 15 2020, 16:16:15) 
[GCC 6.3.0 20170516]
ipympl version: 0.5.6
jupyter core     : 4.6.3
jupyter-notebook : 6.0.3
qtconsole        : not installed
ipython          : 7.14.0
ipykernel        : 5.3.0
jupyter client   : 6.1.3
jupyter lab      : not installed
nbconvert        : 5.6.1
ipywidgets       : 7.5.1
nbformat         : 5.0.6
traitlets        : 4.3.3
Known nbextensions:
  config dir: /home/dschofield/.jupyter/nbconfig
    notebook section
      jupyter-js-widgets/extension  enabled 
      - Validating: OK
  config dir: /home/dschofield/.local/share/virtualenvs/goldmine-hCKJOvFR/etc/jupyter/nbconfig
    notebook section
      jupyter-matplotlib/extension  enabled 
      - Validating: OK
      voila/extension  enabled 
      - Validating: OK
      jupyter-js-widgets/extension  enabled 
      - Validating: OK
      qgrid/extension  enabled 
      - Validating: OK
JupyterLab v1.0.0
Known labextensions:
   app dir: /home/dschofield/.local/share/jupyter/lab
        @jupyter-widgets/jupyterlab-manager v1.1.0  enabled  OK
        bqplot v0.5.1  enabled  OK
        ipyevents v1.7.0  enabled  OK
        ipysheet v0.4.3  enabled  OK
        ipytree v0.1.3  enabled  OK
        ipyvolume v0.5.2  enabled  OK
        jupyter-leaflet v0.11.4  enabled  OK
        jupyter-matplotlib v0.4.2  enabled  OK
        jupyter-threejs v2.1.1  enabled  OK
        jupyter-vue v1.0.0  enabled  OK
        jupyter-vuetify v1.1.1  enabled  OK
        jupyterlab-datawidgets v6.2.0  enabled  OK
        pywwt v0.7.0  enabled  OK
Production environment:
3.6.7 | packaged by conda-forge | (default, Feb 28 2019, 09:07:38) 
[GCC 7.3.0]
ipympl version: 0.5.6
jupyter core     : 4.6.3
jupyter-notebook : 6.0.3
qtconsole        : not installed
ipython          : 7.14.0
ipykernel        : 5.3.0
jupyter client   : 6.1.3
jupyter lab      : 1.2.5
nbconvert        : 5.6.1
ipywidgets       : 7.5.1
nbformat         : 5.0.6
traitlets        : 4.3.3
Known nbextensions:
  config dir: /opt/tljh/user/etc/jupyter/nbconfig
    notebook section
      jupyter-matplotlib/extension  enabled 
      - Validating: OK
      nbresuse/main  enabled 
      - Validating: OK
      voila/extension  enabled 
      - Validating: OK
      jupyter-js-widgets/extension  enabled 
      - Validating: OK
      qgrid/extension  enabled 
      - Validating: OK
    tree section
      jupyter_server_proxy/tree  enabled 
      - Validating: OK
JupyterLab v1.2.5
Known labextensions:
   app dir: /opt/tljh/user/share/jupyter/lab
        @jupyter-widgets/jupyterlab-manager v1.1.0  enabled  OK
        jupyter-matplotlib v0.7.2  enabled  OK

I'm assuming that the differences in Lab extensions are not of concern here because I'm not using Lab, but before I go about testing that assumption, expert insight is welcomed.
Thanks in advance.

Guía de contribución

Abrir la guía de contribución

Primeros pasos

  1. Lee el issue completo y luego la guía de contribución del proyecto.
  2. Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
  3. Haz un fork del repositorio y trabaja en una rama.
  4. Abre un pull request que haga referencia al número del issue.

Línea de trabajo

Empieza ejecutando la reproducción proporcionada de %matplotlib widget con las versiones de desarrollo y producción indicadas; después, compara las extensiones de Notebook y las extensiones de Lab que aparecen en el informe. Se considera terminado cuando las figuras interactivas conservan su header, footer, resize handle y configuración de visibilidad, y dejan de desaparecer después de una interacción con el ratón o de Reset.

Escrito por el modelo de indexación a partir del texto del issue.

Evaluación

Stack tecnológico
jupyter-notebook, python
Área
frontend
Tipo de issue
Error
Dificultad
4/5
Tiempo estimado
3-5 días
Estado de actividad
Estancado
Claridad
Bastante claro
Aptitud para principiantes
35/100

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