Merge pull request #291 from python-adaptive/fix-docs

fix docs

Author: basnijholt

adaptive/runner.py

@@ -62,7 +62,8 @@ class BaseRunner(metaclass=abc.ABCMeta):
         the learner as its sole argument, and return True when we should
         stop requesting more points.
     executor : `concurrent.futures.Executor`, `distributed.Client`,\
-               `mpi4py.futures.MPIPoolExecutor`, or `ipyparallel.Client`, optional
+               `mpi4py.futures.MPIPoolExecutor`, `ipyparallel.Client` or\
+               `loky.get_reusable_executor`, optional
         The executor in which to evaluate the function to be learned.
         If not provided, a new `~concurrent.futures.ProcessPoolExecutor`.
     ntasks : int, optional

docs/environment.yml

@@ -5,18 +5,18 @@ channels:
 
 dependencies:
   - python
-  - sortedcollections
-  - scikit-optimize
-  - scikit-learn <=0.23.1  # because of https://github.com/scikit-optimize/scikit-optimize/issues/931, remove dep when fixed
-  - scipy
-  - holoviews
-  - bokeh
-  - plotly
-  - ipywidgets
-  - jupyter_sphinx ==0.2.3 # because of https://github.com/jupyter/jupyter-sphinx/issues/126
-  - atomicwrites
-  - sphinx_fontawesome
-  - sphinx
-  - m2r2
+  - sortedcollections=1.2.1
+  - scikit-optimize=0.8.1
+  - scikit-learn=0.23.2
+  - scipy=1.5.2
+  - holoviews=1.13.3
+  - bokeh=2.2.1
+  - plotly=4.10.0
+  - ipywidgets=7.5.1
+  - jupyter_sphinx=0.3.1
+  - atomicwrites=1.4.0
+  - sphinx_fontawesome=0.0.6
+  - sphinx=3.2.1
+  - m2r2=0.2.5
   - pip:
     - sphinx_rtd_theme

docs/source/conf.py

@@ -51,7 +51,7 @@
     "sphinx.ext.mathjax",
     "sphinx.ext.viewcode",
     "sphinx.ext.napoleon",
-    "jupyter_sphinx.execute",
+    "jupyter_sphinx",
     "sphinx_fontawesome",
     "m2r2",
 ]
@@ -142,7 +142,10 @@
     "loky": ("https://loky.readthedocs.io/en/stable/", None),
 }
 
-
+html_js_files = [
+    "https://cdn.bokeh.org/bokeh/release/bokeh-2.2.1.min.js",
+    "https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.2.1.min.js",
+]
 html_logo = "logo_docs.png"
 
 

docs/source/docs.rst

@@ -48,7 +48,7 @@ on the *Play* :fa:`play` button or move the sliders.
     from adaptive.learner.learner1D import uniform_loss, default_loss
     import holoviews as hv
     import numpy as np
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
     %output holomap='scrubber'
 
 `adaptive.Learner1D`

docs/source/tutorial/tutorial.AverageLearner.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.AverageLearner`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
 The next type of learner averages a function until the uncertainty in
 the average meets some condition.

docs/source/tutorial/tutorial.BalancingLearner.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.BalancingLearner`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
     import holoviews as hv
     import numpy as np

docs/source/tutorial/tutorial.DataSaver.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.DataSaver`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
 If the function that you want to learn returns a value along with some
 metadata, you can wrap your learner in an `adaptive.DataSaver`.

docs/source/tutorial/tutorial.IntegratorLearner.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.IntegratorLearner`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
     import holoviews as hv
     import numpy as np

docs/source/tutorial/tutorial.Learner1D.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.Learner1D`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
     import numpy as np
     from functools import partial

docs/source/tutorial/tutorial.Learner2D.rst

@@ -14,7 +14,7 @@ Tutorial `~adaptive.Learner2D`
     :hide-code:
 
     import adaptive
-    adaptive.notebook_extension(_inline_js=False)
+    adaptive.notebook_extension()
 
     import numpy as np
     from functools import partial