Use nb_execution_raise_on_error Sphinx myst-nb option (#396)

* Use nb_execution_raise_on_error Sphinx myst-nb option

The option nb_execution_fail_on_error does not exist.

* Pin recent versions

* Fix logo

* Downgrade panel

* Do allow new packages

Author: basnijholt

docs/environment.yml

@@ -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

docs/logo.py

@@ -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
 
@@ -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)

docs/source/conf.py

@@ -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):