Pushing the docs for revision for branch: master, commit cff7d30044e487c6e8ba9c220955db87474aebec

Author: skoptci

_downloads/56061d60b433157ebf7d13e5f8a92c2a/auto_examples_python.zip

@@ -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 0x7F0518481A40
+     random_state: RandomState(MT19937) at 0x7F56FAD76A40
             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  2.757 seconds)
+   **Total running time of the script:** ( 0 minutes  3.277 seconds)
 
 
 .. _sphx_glr_download_auto_examples_ask-and-tell.py:

_downloads/80167a555a9152802d82aab42c671ad2/auto_examples_jupyter.zip

@@ -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 0x7F0565DCFA40
+     random_state: RandomState(MT19937) at 0x7F57486C4A40
             space: Space([Real(low=-2.0, high=2.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function f at 0x7f05683ecca0>, '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 0x7f574b16ee50>, '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 0x7F0565DCFA40, '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 0x7F57486C4A40, '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: [-0.35076964213550554]
           x_iters: [[-0.009345334109402526], [1.2713537644662787], [0.4484475787090836], [1.0854396754496047], [1.4426790855107496], [0.9698921802985794], [-0.4464493263345515], [-0.6474638307563569], [-0.35076964213550554], [-0.28714768066245777], [-0.2968537677230516], [-2.0], [2.0], [-1.3149517821938494], [-0.3218160845454081]]
 
@@ -305,7 +305,7 @@ the last iteration:
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7f05684473a0>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f574b11c670>
 
 
 
@@ -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  2.991 seconds)
+   **Total running time of the script:** ( 0 minutes  3.117 seconds)
 
 
 .. _sphx_glr_download_auto_examples_bayesian-optimization.py:

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

@@ -562,7 +562,7 @@ recalculated.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  52.811 seconds)
+   **Total running time of the script:** ( 1 minutes  2.911 seconds)
 
 
 .. _sphx_glr_download_auto_examples_exploration-vs-exploitation.py:

_sources/auto_examples/bayesian-optimization.rst.txt

@@ -207,14 +207,14 @@ Convergence plot
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7f05686a7f10>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f574b1448e0>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  26.638 seconds)
+   **Total running time of the script:** ( 1 minutes  43.528 seconds)
 
 
 .. _sphx_glr_download_auto_examples_hyperparameter-optimization.py:

_sources/auto_examples/exploration-vs-exploitation.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 0x7F0565DCFA40
+     random_state: RandomState(MT19937) at 0x7F57486C4A40
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7f05683e6d30>, '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 0x7f574ae8cd30>, '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 0x7F0565DCFA40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f04e39bceb0>], '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 0x7F57486C4A40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f56c61d4d00>], '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 0x7F0565DCFA40
+     random_state: RandomState(MT19937) at 0x7F57486C4A40
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7f05683e6d30>, '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 0x7f574ae8cd30>, '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 0x7F0565DCFA40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f04e39bceb0>], '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 0x7F57486C4A40, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f56c61d4d00>], '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  3.989 seconds)
+   **Total running time of the script:** ( 0 minutes  4.301 seconds)
 
 
 .. _sphx_glr_download_auto_examples_interruptible-optimization.py:

_sources/auto_examples/hyperparameter-optimization.rst.txt

@@ -292,7 +292,7 @@ Test different kernels
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  11.542 seconds)
+   **Total running time of the script:** ( 0 minutes  12.725 seconds)
 
 
 .. _sphx_glr_download_auto_examples_optimizer-with-different-base-estimator.py:

_sources/auto_examples/interruptible-optimization.rst.txt

@@ -119,7 +119,7 @@ scikit-optimize.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  23.928 seconds)
+   **Total running time of the script:** ( 1 minutes  21.826 seconds)
 
 
 .. _sphx_glr_download_auto_examples_parallel-optimization.py:

_sources/auto_examples/optimizer-with-different-base-estimator.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  25.249 seconds)
+   **Total running time of the script:** ( 0 minutes  26.657 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plots_partial-dependence-plot-with-categorical.py:

_sources/auto_examples/parallel-optimization.rst.txt

@@ -259,7 +259,7 @@ as the minimum argument:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 3 minutes  42.608 seconds)
+   **Total running time of the script:** ( 4 minutes  0.029 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plots_partial-dependence-plot.py:

_sources/auto_examples/plots/partial-dependence-plot-with-categorical.rst.txt

@@ -5,12 +5,12 @@
 
 Computation times
 =================
-**11:51.881** total execution time for **auto_examples_plots** files:
+**13:09.927** total execution time for **auto_examples_plots** files:
 
 +-----------------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_plots_visualizing-results.py` (``visualizing-results.py``)                                           | 07:44.023 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_plots_visualizing-results.py` (``visualizing-results.py``)                                           | 08:43.241 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_plots_partial-dependence-plot.py` (``partial-dependence-plot.py``)                                   | 03:42.608 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_plots_partial-dependence-plot.py` (``partial-dependence-plot.py``)                                   | 04:00.029 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_plots_partial-dependence-plot-with-categorical.py` (``partial-dependence-plot-with-categorical.py``) | 00:25.249 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_plots_partial-dependence-plot-with-categorical.py` (``partial-dependence-plot-with-categorical.py``) | 00:26.657 | 0.0 MB |
 +-----------------------------------------------------------------------------------------------------------------------------------+-----------+--------+

_sources/auto_examples/plots/partial-dependence-plot.rst.txt

@@ -359,7 +359,7 @@ in both the placement of samples and the partial dependence plots.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 7 minutes  44.023 seconds)
+   **Total running time of the script:** ( 8 minutes  43.241 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plots_visualizing-results.py:

_sources/auto_examples/plots/sg_execution_times.rst.txt

@@ -5,26 +5,26 @@
 
 Computation times
 =================
-**13:22.349** total execution time for **auto_examples** files:
+**15:13.166** total execution time for **auto_examples** files:
 
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_strategy-comparison.py` (``strategy-comparison.py``)                                         | 08:03.169 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_strategy-comparison.py` (``strategy-comparison.py``)                                         | 09:14.689 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_hyperparameter-optimization.py` (``hyperparameter-optimization.py``)                         | 01:26.638 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_hyperparameter-optimization.py` (``hyperparameter-optimization.py``)                         | 01:43.528 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_parallel-optimization.py` (``parallel-optimization.py``)                                     | 01:23.928 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` (``sklearn-gridsearchcv-replacement.py``)               | 01:23.359 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` (``sklearn-gridsearchcv-replacement.py``)               | 01:11.624 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_parallel-optimization.py` (``parallel-optimization.py``)                                     | 01:21.826 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_exploration-vs-exploitation.py` (``exploration-vs-exploitation.py``)                         | 00:52.811 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_exploration-vs-exploitation.py` (``exploration-vs-exploitation.py``)                         | 01:02.911 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_optimizer-with-different-base-estimator.py` (``optimizer-with-different-base-estimator.py``) | 00:11.542 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_optimizer-with-different-base-estimator.py` (``optimizer-with-different-base-estimator.py``) | 00:12.725 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_interruptible-optimization.py` (``interruptible-optimization.py``)                           | 00:03.989 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_interruptible-optimization.py` (``interruptible-optimization.py``)                           | 00:04.301 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_bayesian-optimization.py` (``bayesian-optimization.py``)                                     | 00:02.991 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_store-and-load-results.py` (``store-and-load-results.py``)                                   | 00:03.433 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_store-and-load-results.py` (``store-and-load-results.py``)                                   | 00:02.899 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_ask-and-tell.py` (``ask-and-tell.py``)                                                       | 00:03.277 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_ask-and-tell.py` (``ask-and-tell.py``)                                                       | 00:02.757 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_bayesian-optimization.py` (``bayesian-optimization.py``)                                     | 00:03.117 | 0.0 MB |
 +---------------------------------------------------------------------------------------------------------------------------+-----------+--------+

_sources/auto_examples/plots/visualizing-results.rst.txt

@@ -364,7 +364,7 @@ calculated with `total_iterations` property, as in the code below.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 1 minutes  11.624 seconds)
+   **Total running time of the script:** ( 1 minutes  23.359 seconds)
 
 
 .. _sphx_glr_download_auto_examples_sklearn-gridsearchcv-replacement.py:

_sources/auto_examples/sg_execution_times.rst.txt

@@ -95,6 +95,14 @@ We will use the same optimization problem as in the
 
     /root/project/skopt/optimizer/optimizer.py:409: UserWarning: The objective has been evaluated at this point before.
       warnings.warn("The objective has been evaluated "
+    /root/project/skopt/optimizer/optimizer.py:409: UserWarning: The objective has been evaluated at this point before.
+      warnings.warn("The objective has been evaluated "
+    /root/project/skopt/optimizer/optimizer.py:409: UserWarning: The objective has been evaluated at this point before.
+      warnings.warn("The objective has been evaluated "
+    /root/project/skopt/optimizer/optimizer.py:409: UserWarning: The objective has been evaluated at this point before.
+      warnings.warn("The objective has been evaluated "
+    /root/project/skopt/optimizer/optimizer.py:409: UserWarning: The objective has been evaluated at this point before.
+      warnings.warn("The objective has been evaluated "
 
 
 
@@ -152,7 +160,7 @@ And load from file using :class:`skopt.load`:
  .. code-block:: none
 
 
-    -0.44942475469808835
+    -0.3086229194859892
 
 
 
@@ -186,7 +194,7 @@ level (highest in this case):
  .. code-block:: none
 
     Without compression: 80120 bytes
-    Compressed with gz:  25128 bytes
+    Compressed with gz:  21396 bytes
 
 
 
@@ -274,7 +282,7 @@ copy is created:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  2.899 seconds)
+   **Total running time of the script:** ( 0 minutes  3.433 seconds)
 
 
 .. _sphx_glr_download_auto_examples_store-and-load-results.py:

_sources/auto_examples/sklearn-gridsearchcv-replacement.rst.txt

@@ -206,7 +206,7 @@ Note that this can take a few minutes.
  .. code-block:: none
 
 
-    <matplotlib.legend.Legend object at 0x7f04e397d9d0>
+    <matplotlib.legend.Legend object at 0x7f56c6240820>
 
 
 
@@ -227,7 +227,7 @@ values that are below the true value simply because they are fluctuations.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 8 minutes  3.169 seconds)
+   **Total running time of the script:** ( 9 minutes  14.689 seconds)
 
 
 .. _sphx_glr_download_auto_examples_strategy-comparison.py:

_sources/auto_examples/store-and-load-results.rst.txt

@@ -7,7 +7,8 @@ Release notes for all scikit-optimize releases are linked in this this page.
 
 .. toctree::
     :maxdepth: 1
-
+    Version 0.8 <whats_new/v0.8.rst>
+    Version 0.7.2 <whats_new/v0.7.2.rst>
     Version 0.7.1 <whats_new/v0.7.1.rst>
     Version 0.7 <whats_new/v0.7.rst>
     Version 0.6 <whats_new/v0.6.rst>