Pushing the docs to 0.7/ for branch: 0.7.X, commit c50ef70f614c7c47f03371bde4d2f3ff965fb4c8

Author: skoptci

0.7/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: 16b82a1d7c55e2684c87b351530d164b
+config: a21ba50c9b054ae7749d45e1fc092164
 tags: 645f666f9bcd5a90fca523b33c5a78b7

0.7/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -152,7 +152,7 @@ <h1>All modules for which code is available</h1>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_downloads/d34667f097c619f8afda4bc936e7af21/auto_examples_jupyter.zip

@@ -814,7 +814,7 @@ <h1>Source code for sklearn.base</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_downloads/scikit-optimize-docs.pdf

@@ -2383,7 +2383,7 @@ <h1>Source code for sklearn.ensemble._forest</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/index.html

@@ -635,7 +635,7 @@ <h1>Source code for sklearn.gaussian_process._gpr</h1><div class="highlight"><pr
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/sklearn/base.html

@@ -1614,7 +1614,7 @@ <h1>Source code for sklearn.model_selection._search</h1><div class="highlight"><
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/sklearn/ensemble/_forest.html

@@ -451,7 +451,7 @@ <h1>Source code for skopt.acquisition</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/sklearn/gaussian_process/_gpr.html

@@ -230,7 +230,7 @@ <h1>Source code for skopt.benchmarks</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/sklearn/model_selection/_search.html

@@ -417,7 +417,7 @@ <h1>Source code for skopt.callbacks</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/acquisition.html

@@ -555,7 +555,7 @@ <h1>Source code for skopt.learning.forest</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/benchmarks.html

@@ -485,7 +485,7 @@ <h1>Source code for skopt.learning.gaussian_process.gpr</h1><div class="highligh
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/callbacks.html

@@ -253,7 +253,7 @@ <h1>Source code for skopt.learning.gbrt</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/learning/forest.html

@@ -408,7 +408,7 @@ <h1>Source code for skopt.optimizer.base</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/learning/gaussian_process/gpr.html

@@ -240,7 +240,7 @@ <h1>Source code for skopt.optimizer.dummy</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/learning/gbrt.html

@@ -306,7 +306,7 @@ <h1>Source code for skopt.optimizer.forest</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/base.html

@@ -295,7 +295,7 @@ <h1>Source code for skopt.optimizer.gbrt</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/dummy.html

@@ -401,7 +401,7 @@ <h1>Source code for skopt.optimizer.gp</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/forest.html

@@ -759,7 +759,7 @@ <h1>Source code for skopt.optimizer.optimizer</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/gbrt.html

@@ -891,7 +891,7 @@ <h1>Source code for skopt.plots</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/gp.html

@@ -821,7 +821,7 @@ <h1>Source code for skopt.searchcv</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/optimizer/optimizer.html

@@ -1055,7 +1055,7 @@ <h1>Source code for skopt.space.space</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/plots.html

@@ -370,7 +370,7 @@ <h1>Source code for skopt.space.transformers</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/searchcv.html

@@ -900,7 +900,7 @@ <h1>Source code for skopt.utils</h1><div class="highlight"><pre>
       </div>
     <div class="container">
       <footer class="sk-content-footer">
-            &copy; 2017 - 2020, The scikit-optimize contributors..
+            &copy; 2017 - 2020, scikit-optimize contributors (BSD License).
       </footer>
     </div>
   </div>

0.7/_modules/skopt/space/space.html

@@ -175,7 +175,7 @@ and report the value back to the optimizer:
               fun: -0.032758350111535384
         func_vals: array([-0.03275835])
            models: []
-     random_state: RandomState(MT19937) at 0x7FF328867D40
+     random_state: RandomState(MT19937) at 0x7F1316247D40
             space: Space([Real(low=-2.0, high=2.0, prior='uniform', transform='identity')])
             specs: None
                 x: [-1.7121321838148869]
@@ -312,7 +312,7 @@ meantime:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  4.256 seconds)
+   **Total running time of the script:** ( 0 minutes  4.366 seconds)
 
 **Estimated memory usage:**  8 MB
 

0.7/_modules/skopt/space/transformers.html

@@ -267,13 +267,13 @@ provide the following information:
                              n_restarts_optimizer=2, noise=0.010000000000000002,
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
                              random_state=822569775)]
-     random_state: RandomState(MT19937) at 0x7FF310B5AB40
+     random_state: RandomState(MT19937) at 0x7F12F8453840
             space: Space([Real(low=-2.0, high=2.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function f at 0x7ff3029e73a0>, 'dimensions': Space([Real(low=-2.0, high=2.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
+            specs: {'args': {'func': <function f at 0x7f12f1cc4310>, 'dimensions': Space([Real(low=-2.0, high=2.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
                              kernel=1**2 * Matern(length_scale=1, nu=2.5),
                              n_restarts_optimizer=2, noise=0.010000000000000002,
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
-                             random_state=822569775), 'n_calls': 15, 'n_random_starts': 5, 'acq_func': 'EI', 'acq_optimizer': 'auto', 'x0': None, 'y0': None, 'random_state': RandomState(MT19937) at 0x7FF310B5AB40, 'verbose': False, 'callback': None, 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
+                             random_state=822569775), 'n_calls': 15, 'n_random_starts': 5, 'acq_func': 'EI', 'acq_optimizer': 'auto', 'x0': None, 'y0': None, 'random_state': RandomState(MT19937) at 0x7F12F8453840, 'verbose': False, 'callback': None, 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
                 x: [-0.35076964188527904]
           x_iters: [[-0.009345334109402526], [1.2713537644662787], [0.4484475787090836], [1.0854396754496047], [1.4426790855107496], [0.9698921802985794], [-0.4464493263345517], [-0.6474638284799423], [-0.35076964188527904], [-0.28714767658880325], [-0.2968537755362253], [-2.0], [2.0], [-1.3149517825054502], [-0.32181607448732485]]
 
@@ -305,7 +305,7 @@ the last iteration:
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3003f7d90>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f12fa5c4460>
 
 
 
@@ -476,7 +476,7 @@ because the GP does not gain anything more by further exploration:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  3.545 seconds)
+   **Total running time of the script:** ( 0 minutes  3.392 seconds)
 
 **Estimated memory usage:**  8 MB
 

0.7/_modules/skopt/utils.html

@@ -562,7 +562,7 @@ recalculated.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  39.104 seconds)
+   **Total running time of the script:** ( 0 minutes  31.909 seconds)
 
 **Estimated memory usage:**  8 MB
 

0.7/_sources/auto_examples/ask-and-tell.rst.txt

@@ -207,16 +207,16 @@ Convergence plot
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7ff3029c85b0>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f12fa4449a0>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  32.779 seconds)
+   **Total running time of the script:** ( 0 minutes  29.788 seconds)
 
-**Estimated memory usage:**  35 MB
+**Estimated memory usage:**  36 MB
 
 
 .. _sphx_glr_download_auto_examples_hyperparameter-optimization.py:

0.7/_sources/auto_examples/bayesian-optimization.rst.txt

@@ -163,13 +163,13 @@ and pass it to the minimizer:
                              n_restarts_optimizer=2, noise='gaussian',
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
                              random_state=655685735)]
-     random_state: RandomState(MT19937) at 0x7FF310B5AB40
+     random_state: RandomState(MT19937) at 0x7F12F9B91B40
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7ff302a49d30>, 'dimensions': Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
+            specs: {'args': {'func': <function obj_fun at 0x7f12f8444d30>, 'dimensions': Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
                              kernel=1**2 * Matern(length_scale=1, nu=2.5),
                              n_restarts_optimizer=2, noise='gaussian',
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
-                             random_state=655685735), 'n_calls': 10, 'n_random_starts': 0, 'acq_func': 'LCB', 'acq_optimizer': 'auto', 'x0': [-20.0], 'y0': None, 'random_state': RandomState(MT19937) at 0x7FF310B5AB40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7ff3002b6970>], 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
+                             random_state=655685735), 'n_calls': 10, 'n_random_starts': 0, 'acq_func': 'LCB', 'acq_optimizer': 'auto', 'x0': [-20.0], 'y0': None, 'random_state': RandomState(MT19937) at 0x7F12F9B91B40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f12f1c627f0>], 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
                 x: [20.0]
           x_iters: [[-20.0], [20.0], [20.0], [-20.0], [-20.0], [20.0], [-20.0], [20.0], [20.0], [20.0]]
 
@@ -321,14 +321,14 @@ The previous results can then be used to continue the optimization process:
                              n_restarts_optimizer=2, noise='gaussian',
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
                              random_state=655685735)]
-     random_state: RandomState(MT19937) at 0x7FF310B5AB40
+     random_state: RandomState(MT19937) at 0x7F12F9B91B40
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7ff302a49d30>, 'dimensions': Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
+            specs: {'args': {'func': <function obj_fun at 0x7f12f8444d30>, 'dimensions': Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')]), 'base_estimator': GaussianProcessRegressor(alpha=1e-10, copy_X_train=True,
                              kernel=1**2 * Matern(length_scale=1, nu=2.5),
                              n_restarts_optimizer=2, noise='gaussian',
                              normalize_y=True, optimizer='fmin_l_bfgs_b',
                              random_state=655685735), 'n_calls': 10, 'n_random_starts': 0, 'acq_func': 'LCB', 'acq_optimizer': 'auto', 'x0': [[-20.0], [20.0], [20.0], [-20.0], [-20.0], [20.0], [-20.0], [20.0], [20.0], [20.0]], 'y0': array([-0.04682088, -0.08228249, -0.00653801, -0.07133619,  0.09063509,
-            0.07662367,  0.08260541, -0.13236828, -0.17524445,  0.10024491]), 'random_state': RandomState(MT19937) at 0x7FF310B5AB40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7ff3002b6970>], 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
+            0.07662367,  0.08260541, -0.13236828, -0.17524445,  0.10024491]), 'random_state': RandomState(MT19937) at 0x7F12F9B91B40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f12f1c627f0>], 'n_points': 10000, 'n_restarts_optimizer': 5, 'xi': 0.01, 'kappa': 1.96, 'n_jobs': 1, 'model_queue_size': None}, 'function': 'base_minimize'}
                 x: [20.0]
           x_iters: [[-20.0], [20.0], [20.0], [-20.0], [-20.0], [20.0], [-20.0], [20.0], [20.0], [20.0], [20.0], [20.0], [-20.0], [-20.0], [-20.0], [-20.0], [-20.0], [-20.0], [-20.0], [-20.0]]
 
@@ -350,7 +350,7 @@ for more information on how the results get saved and possible caveats
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  2.945 seconds)
+   **Total running time of the script:** ( 0 minutes  3.040 seconds)
 
 **Estimated memory usage:**  8 MB
 

0.7/_sources/auto_examples/exploration-vs-exploitation.rst.txt

@@ -292,9 +292,9 @@ Test different kernels
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  9.005 seconds)
+   **Total running time of the script:** ( 0 minutes  8.427 seconds)
 
-**Estimated memory usage:**  14 MB
+**Estimated memory usage:**  13 MB
 
 
 .. _sphx_glr_download_auto_examples_optimizer-with-different-base-estimator.py:

0.7/_sources/auto_examples/hyperparameter-optimization.rst.txt

@@ -119,7 +119,7 @@ scikit-optimize.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  31.549 seconds)
+   **Total running time of the script:** ( 0 minutes  26.899 seconds)
 
 **Estimated memory usage:**  31 MB
 

0.7/_sources/auto_examples/interruptible-optimization.rst.txt

@@ -190,7 +190,7 @@ parsing a list as the pars argument:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  29.354 seconds)
+   **Total running time of the script:** ( 0 minutes  23.400 seconds)
 
 **Estimated memory usage:**  34 MB
 

0.7/_sources/auto_examples/optimizer-with-different-base-estimator.rst.txt

@@ -259,9 +259,9 @@ as the minimum argument:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 4 minutes  9.577 seconds)
+   **Total running time of the script:** ( 3 minutes  40.614 seconds)
 
-**Estimated memory usage:**  8 MB
+**Estimated memory usage:**  9 MB
 
 
 .. _sphx_glr_download_auto_examples_plots_partial-dependence-plot.py: