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Use nb_execution_raise_on_error Sphinx myst-nb option #396

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Apr 7, 2023
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34 changes: 17 additions & 17 deletions docs/environment.yml
Original file line number Diff line number Diff line change
Expand Up @@ -4,23 +4,23 @@ channels:
- conda-forge

dependencies:
- python
- python=3.11.3
- sortedcollections=2.1.0
- scikit-optimize=0.9.0
- scikit-learn=0.24.2
- scipy=1.9.1
- holoviews=1.14.6
- bokeh=2.4.0
- panel=0.12.7
- pandas=1.4.4
- plotly=5.3.1
- ipywidgets=7.6.5
- myst-nb=0.16.0
- scikit-learn=1.2.2
- scipy=1.10.1
- holoviews=1.15.4
- bokeh=2.4.3
- panel=0.14.4
- pandas=2.0.0
- plotly=5.14.1
- ipywidgets=8.0.6
- myst-nb=0.17.1
- sphinx_fontawesome=0.0.6
- sphinx=4.2.0
- ffmpeg=5.1.1
- cloudpickle
- loky
- furo
- myst-parser
- dask
- sphinx=5.3.0
- ffmpeg=5.1.2
- cloudpickle=2.2.1
- loky=3.3.0
- furo=2023.3.27
- myst-parser=0.18.1
- dask=2023.3.2
4 changes: 3 additions & 1 deletion docs/logo.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@

import holoviews
import matplotlib.pyplot as plt
import numpy as np
import matplotlib.tri as mtri
from PIL import Image, ImageDraw

Expand Down Expand Up @@ -31,7 +32,8 @@ def plot_learner_and_save(learner, fname):
tri = learner.interpolator(scaled=True).tri
triang = mtri.Triangulation(*tri.points.T, triangles=tri.vertices)
ax.triplot(triang, c="k", lw=0.8)
ax.imshow(learner.plot().Image.I.data, extent=(-0.5, 0.5, -0.5, 0.5))
data = learner.interpolated_on_grid()
ax.imshow(np.vstack(data), extent=(-0.5, 0.5, -0.5, 0.5))
ax.set_xticks([])
ax.set_yticks([])
plt.savefig(fname, bbox_inches="tight", transparent=True, dpi=300, pad_inches=-0.1)
Expand Down
2 changes: 1 addition & 1 deletion docs/source/conf.py
Original file line number Diff line number Diff line change
Expand Up @@ -76,7 +76,7 @@
# myst-nb configuration
nb_execution_mode = "cache"
nb_execution_timeout = 180
nb_execution_fail_on_error = True
nb_execution_raise_on_error = True


def setup(app):
Expand Down