Update Sphinx documentation, commit 247a959 [skip ci].

notebooks/Batch mode overview.html

@@ -1384,7 +1384,7 @@ <h2>Ensemble propagations<a class="headerlink" href="#ensemble-propagations" tit
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-<img alt="../_images/6e6a62c14e57f13d28a9e74d541b1e0c3e10a00f7b9dae1733d5bd99cf523cc6.png" src="../_images/6e6a62c14e57f13d28a9e74d541b1e0c3e10a00f7b9dae1733d5bd99cf523cc6.png" />
+<img alt="../_images/4eaaa9cdba19e7de39bfcd4e8246dfb478888a831740b1fa62f7e0b8e838fdaa.png" src="../_images/4eaaa9cdba19e7de39bfcd4e8246dfb478888a831740b1fa62f7e0b8e838fdaa.png" />
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notebooks/Customising the adaptive integrator.html

@@ -636,8 +636,8 @@ <h2>Compact mode<a class="headerlink" href="#compact-mode" title="Link to this h
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 6.04 s, sys: 57.4 ms, total: 6.09 s
-Wall time: 6.09 s
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 6.48 s, sys: 72.2 ms, total: 6.55 s
+Wall time: 6.55 s
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@@ -652,8 +652,10 @@ <h2>Compact mode<a class="headerlink" href="#compact-mode" title="Link to this h
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 221 ms, sys: 0 ns, total: 221 ms
-Wall time: 221 ms
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>CPU times: user 193 ms, sys: 113 µs, total: 193 ms
+</pre></div>
+</div>
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>Wall time: 195 ms
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notebooks/NeuralHamiltonianODEs.html

@@ -636,10 +636,10 @@ <h1>Neural Hamiltonian ODEs<a class="headerlink" href="#neural-hamiltonian-odes"
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7efaaa3d7850&gt;]
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f7d6a16b940&gt;]
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-<img alt="../_images/655477f6238b86bc5f8c91aa52d833ba3cba86b1872ba756513535c276b2a626.png" src="../_images/655477f6238b86bc5f8c91aa52d833ba3cba86b1872ba756513535c276b2a626.png" />
+<img alt="../_images/1b619ab6cecb1b6f2f1ea264597dce7bca5196c8cce6e8dcff7f745c673db78c.png" src="../_images/1b619ab6cecb1b6f2f1ea264597dce7bca5196c8cce6e8dcff7f745c673db78c.png" />
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 <p>Clearly, the power and interest of this technique, applied to Hamiltonian systems, lies in the possibility to define some good training for the FFNN weights and biases so that the final system converges to something useful</p>

notebooks/NeuralODEs.html

@@ -694,7 +694,7 @@ <h3>Taylor Integrator<a class="headerlink" href="#taylor-integrator" title="Link
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.4891817569732666 seconds --- to build (jit) the Taylor integrator
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.4475550651550293 seconds --- to build (jit) the Taylor integrator
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@@ -735,7 +735,7 @@ <h3>Taylor Integrator<a class="headerlink" href="#taylor-integrator" title="Link
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.00013065338134765625 seconds --- to propagate using the Taylor scheme
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.00033354759216308594 seconds --- to propagate using the Taylor scheme
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@@ -754,7 +754,7 @@ <h3>Taylor Integrator<a class="headerlink" href="#taylor-integrator" title="Link
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-<img alt="../_images/af8c014c60921219e966aafe4c3237fe656fcbbbf9710b30d1bf9924684295da.png" src="../_images/af8c014c60921219e966aafe4c3237fe656fcbbbf9710b30d1bf9924684295da.png" />
+<img alt="../_images/63421472169e01a34ab0239b7676023dad4ea4a005be404d8cc03623a6a8256b.png" src="../_images/63421472169e01a34ab0239b7676023dad4ea4a005be404d8cc03623a6a8256b.png" />
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@@ -793,7 +793,7 @@ <h3>Scipy Counterpart<a class="headerlink" href="#scipy-counterpart" title="Link
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.002370119094848633 seconds --- to propagate
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.0014979839324951172 seconds --- to propagate
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@@ -808,7 +808,7 @@ <h3>Scipy Counterpart<a class="headerlink" href="#scipy-counterpart" title="Link
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-<img alt="../_images/073f0dd9a2a41a29e84bc93e2b4ebea5a440e89a7de8cd4fd50600ca16555893.png" src="../_images/073f0dd9a2a41a29e84bc93e2b4ebea5a440e89a7de8cd4fd50600ca16555893.png" />
+<img alt="../_images/205907a5f815b7c22b63371c3de5dce169af268cdc17829bc72d2ab46263c801.png" src="../_images/205907a5f815b7c22b63371c3de5dce169af268cdc17829bc72d2ab46263c801.png" />
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 <p>We see a net advantage in timings using the Taylor integration scheme. Note we are here not using batch propagation, which would add an additional 2-4 factor speedup in performances.</p>

notebooks/Optimal Control of the Lotka-Volterra equations.html

@@ -1098,9 +1098,9 @@ <h2>Implementing a single shooting method<a class="headerlink" href="#implementi
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-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_10690/2413872175.py:11: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_10695/2413872175.py:11: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
   ta.pars[6] = np.heaviside(switching_function(x_0,y_0,lx_0,ly_0, ps), 1.)
-/tmp/ipykernel_10690/2413872175.py:14: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
+/tmp/ipykernel_10695/2413872175.py:14: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
   ta.state[0] = x_0; ta.state[1] = y_0; ta.state[2] = lx_0; ta.state[3] = ly_0
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@@ -1142,7 +1142,7 @@ <h2>Implementing a single shooting method<a class="headerlink" href="#implementi
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-<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_10690/3578120629.py:12: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
+<div class="output stderr highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>/tmp/ipykernel_10695/3578120629.py:12: DeprecationWarning: Conversion of an array with ndim &gt; 0 to a scalar is deprecated, and will error in future. Ensure you extract a single element from your array before performing this operation. (Deprecated NumPy 1.25.)
   ta.pars[6] = np.heaviside(switching_function(x_0,y_0,lx_0,ly_0, ps), 1.)
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notebooks/Periodic orbits in the CR3BP.html

@@ -735,7 +735,7 @@ <h2>Putting all together and integrating some initial conditions<a class="header
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 14.274664640426636 seconds --- to build the Taylor integrator
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 13.061972618103027 seconds --- to build the Taylor integrator
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@@ -766,7 +766,7 @@ <h2>Putting all together and integrating some initial conditions<a class="header
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-<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.05044221878051758 seconds --- to propagate
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>--- 0.04901456832885742 seconds --- to propagate
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@@ -824,7 +824,7 @@ <h2>Putting all together and integrating some initial conditions<a class="header
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7fec80311c60&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f22d0f21f00&gt;
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 <img alt="../_images/de0d9b784e67d433c81e1c6d68b5b937452559993089914853f0e1f45dbc1669.png" src="../_images/de0d9b784e67d433c81e1c6d68b5b937452559993089914853f0e1f45dbc1669.png" />

notebooks/ensemble_mode.html

@@ -636,10 +636,10 @@ <h2>A simple example<a class="headerlink" href="#a-simple-example" title="Link t
  Taylor order            : 20
  Dimension               : 2
  Time                    : 20
- State                   : [0.04274221076606843, 0.05350602824322641],
+ State                   : [0.0432962437217672, 0.05844010861356886],
  &lt;taylor_outcome.time_limit: -4294967299&gt;,
- 0.20598213553603154,
- 0.2189188676003376,
+ 0.2049923359388591,
+ 0.2182946107061812,
  95,
  None,
  None)
@@ -692,7 +692,7 @@ <h2>A simple example<a class="headerlink" href="#a-simple-example" title="Link t
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-<img alt="../_images/48f6614d5fee834ba9898b1ff4ea18802d7848cf0d1c813cc6c165ddc7b36be0.png" src="../_images/48f6614d5fee834ba9898b1ff4ea18802d7848cf0d1c813cc6c165ddc7b36be0.png" />
+<img alt="../_images/6a534a8d2de0c198184aad060abd9c44cffb96f63378865bc2a1ce67b1924476.png" src="../_images/6a534a8d2de0c198184aad060abd9c44cffb96f63378865bc2a1ce67b1924476.png" />
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