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remove _inline_js=False in adaptive.notebook_extension call

Bas Nijholt authored on 17/09/2020 22:19:56
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ 3a3a33a
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@@ -14,7 +14,7 @@ Tutorial `~adaptive.DataSaver`
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     :hide-code:
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     import adaptive
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-    adaptive.notebook_extension(_inline_js=False)
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+    adaptive.notebook_extension()
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 If the function that you want to learn returns a value along with some
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 metadata, you can wrap your learner in an `adaptive.DataSaver`.
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remove thebelab buttons

Bas Nijholt authored on 01/08/2019 16:10:21
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ 5990c15
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@@ -10,8 +10,6 @@ Tutorial `~adaptive.DataSaver`
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     The complete source code of this tutorial can be found in
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     :jupyter-download:notebook:`tutorial.DataSaver`
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-.. thebe-button:: Run the code live inside the documentation!
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-
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 .. jupyter-execute::
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     :hide-code:
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add thebelab activation buttons

Bas Nijholt authored on 10/07/2019 19:30:06
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ b2db3d8
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@@ -10,6 +10,8 @@ Tutorial `~adaptive.DataSaver`
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     The complete source code of this tutorial can be found in
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     :jupyter-download:notebook:`tutorial.DataSaver`
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+.. thebe-button:: Run the code live inside the documentation!
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+
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 .. jupyter-execute::
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     :hide-code:
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do not inline the HoloViews JS

Bas Nijholt authored on 26/03/2019 12:44:31
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ 6b17023
... ... 
@@ -14,7 +14,7 @@ Tutorial `~adaptive.DataSaver`
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     :hide-code:
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     import adaptive
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-    adaptive.notebook_extension()
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+    adaptive.notebook_extension(_inline_js=False)
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 If the function that you want to learn returns a value along with some
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 metadata, you can wrap your learner in an `adaptive.DataSaver`.
Browse code

change "execute" into "jupyter-execute"

Bas Nijholt authored on 18/10/2018 18:21:31
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ d9aaa49
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@@ -8,11 +8,10 @@ Tutorial `~adaptive.DataSaver`
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 .. seealso::
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     The complete source code of this tutorial can be found in
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-    :jupyter-download:notebook:`DataSaver`
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+    :jupyter-download:notebook:`tutorial.DataSaver`
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-.. execute::
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+.. jupyter-execute::
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     :hide-code:
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-    :new-notebook: DataSaver
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     import adaptive
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     adaptive.notebook_extension()
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@@ -23,7 +22,7 @@ metadata, you can wrap your learner in an `adaptive.DataSaver`.
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 In the following example the function to be learned returns its result
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 and the execution time in a dictionary:
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-.. execute::
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+.. jupyter-execute::
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     from operator import itemgetter
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... ... 
@@ -48,20 +47,20 @@ and the execution time in a dictionary:
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 ``learner.learner`` is the original learner, so
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 ``learner.learner.loss()`` will call the correct loss method.
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-.. execute::
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+.. jupyter-execute::
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     runner = adaptive.Runner(learner, goal=lambda l: l.learner.loss() < 0.1)
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-.. execute::
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+.. jupyter-execute::
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     :hide-code:
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     await runner.task  # This is not needed in a notebook environment!
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-.. execute::
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+.. jupyter-execute::
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     runner.live_info()
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-.. execute::
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+.. jupyter-execute::
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     runner.live_plot(plotter=lambda l: l.learner.plot(), update_interval=0.1)
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... ... 
@@ -69,6 +68,6 @@ Now the ``DataSavingLearner`` will have an dictionary attribute
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 ``extra_data`` that has ``x`` as key and the data that was returned by
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 ``learner.function`` as values.
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-.. execute::
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+.. jupyter-execute::
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     learner.extra_data
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add tutorials

Bas Nijholt authored on 17/10/2018 13:30:10
Showing 1 changed files
docs/source/tutorial/tutorial.DataSaver.rst
History View file @ 6fca822
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new file mode 100644
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@@ -0,0 +1,74 @@
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+Tutorial `~adaptive.DataSaver`
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+------------------------------
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+
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+.. note::
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+   Because this documentation consists of static html, the ``live_plot``
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+   and ``live_info`` widget is not live. Download the notebook
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+   in order to see the real behaviour.
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+
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+.. seealso::
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+    The complete source code of this tutorial can be found in
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+    :jupyter-download:notebook:`DataSaver`
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+
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+.. execute::
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+    :hide-code:
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+    :new-notebook: DataSaver
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+
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+    import adaptive
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+    adaptive.notebook_extension()
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+
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+If the function that you want to learn returns a value along with some
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+metadata, you can wrap your learner in an `adaptive.DataSaver`.
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+
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+In the following example the function to be learned returns its result
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+and the execution time in a dictionary:
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+
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+.. execute::
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+
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+    from operator import itemgetter
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+
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+    def f_dict(x):
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+        """The function evaluation takes roughly the time we `sleep`."""
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+        import random
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+        from time import sleep
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+
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+        waiting_time = random.random()
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+        sleep(waiting_time)
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+        a = 0.01
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+        y = x + a**2 / (a**2 + x**2)
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+        return {'y': y, 'waiting_time': waiting_time}
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+
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+    # Create the learner with the function that returns a 'dict'
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+    # This learner cannot be run directly, as Learner1D does not know what to do with the 'dict'
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+    _learner = adaptive.Learner1D(f_dict, bounds=(-1, 1))
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+
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+    # Wrapping the learner with 'adaptive.DataSaver' and tell it which key it needs to learn
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+    learner = adaptive.DataSaver(_learner, arg_picker=itemgetter('y'))
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+
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+``learner.learner`` is the original learner, so
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+``learner.learner.loss()`` will call the correct loss method.
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+
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+.. execute::
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+
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+    runner = adaptive.Runner(learner, goal=lambda l: l.learner.loss() < 0.1)
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+
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+.. execute::
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+    :hide-code:
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+
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+    await runner.task  # This is not needed in a notebook environment!
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+
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+.. execute::
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+
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+    runner.live_info()
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+
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+.. execute::
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+
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+    runner.live_plot(plotter=lambda l: l.learner.plot(), update_interval=0.1)
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+
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+Now the ``DataSavingLearner`` will have an dictionary attribute
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+``extra_data`` that has ``x`` as key and the data that was returned by
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+``learner.function`` as values.
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+
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+.. execute::
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+
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+    learner.extra_data