Pushing the docs for revision for branch: master, commit d9062c27c8c6e58e39f6ccc31e10c7d0d0146de6

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 0x7FB6A30BB940
+     random_state: RandomState(MT19937) at 0x7F5B01BC0940
             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  2.800 seconds)
+   **Total running time of the script:** ( 0 minutes  2.973 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=843828734)]
-     random_state: RandomState(MT19937) at 0x7FB6FF8B9D40
+     random_state: RandomState(MT19937) at 0x7F5B5E3BED40
             space: Space([Real(low=-2.0, high=2.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function f at 0x7fb6f72b0ee0>, '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 0x7f5b53d95820>, '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=843828734), 'n_calls': 15, 'n_random_starts': 5, 'acq_func': 'EI', 'acq_optimizer': 'auto', 'x0': None, 'y0': None, 'random_state': RandomState(MT19937) at 0x7FB6FF8B9D40, '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=843828734), 'n_calls': 15, 'n_random_starts': 5, 'acq_func': 'EI', 'acq_optimizer': 'auto', 'x0': None, 'y0': None, 'random_state': RandomState(MT19937) at 0x7F5B5E3BED40, '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: [-0.2861162952526968]
           x_iters: [[0.8518212820929092], [-0.2861162952526968], [0.7635394201074472], [0.8766012406190926], [-0.03552426626961047], [-0.34247541478780397], [-0.26155519596964205], [-0.4646415758058908], [-0.31387649972906195], [1.38961533306915], [-1.9998214636995275], [-1.218993447030592], [2.0], [0.37684326379289823], [-1.6363051829417985]]
 
@@ -305,7 +305,7 @@ the last iteration:
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7fb66f132340>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f5aca717310>
 
 
 
@@ -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  2.638 seconds)
+   **Total running time of the script:** ( 0 minutes  2.730 seconds)
 
 
 .. _sphx_glr_download_auto_examples_bayesian-optimization.py:

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

@@ -207,14 +207,14 @@ Convergence plot
  .. code-block:: none
 
 
-    <matplotlib.axes._subplots.AxesSubplot object at 0x7fb6f709da60>
+    <matplotlib.axes._subplots.AxesSubplot object at 0x7f5b53d942b0>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  53.164 seconds)
+   **Total running time of the script:** ( 1 minutes  22.113 seconds)
 
 
 .. _sphx_glr_download_auto_examples_hyperparameter-optimization.py:

_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 0x7FB6F2A33740
+     random_state: RandomState(MT19937) at 0x7F5B53682740
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7fb6f72b0d30>, '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 0x7f5b53f64d30>, '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 0x7FB6F2A33740, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7fb66e5a5850>], '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 0x7F5B53682740, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f5acd07fc10>], '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 0x7FB6F2A33740
+     random_state: RandomState(MT19937) at 0x7F5B53682740
             space: Space([Real(low=-20.0, high=20.0, prior='uniform', transform='normalize')])
-            specs: {'args': {'func': <function obj_fun at 0x7fb6f72b0d30>, '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 0x7f5b53f64d30>, '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 0x7FB6F2A33740, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7fb66e5a5850>], '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 0x7F5B53682740, 'verbose': False, 'callback': [<skopt.callbacks.CheckpointSaver object at 0x7f5acd07fc10>], '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  3.923 seconds)
+   **Total running time of the script:** ( 0 minutes  3.936 seconds)
 
 
 .. _sphx_glr_download_auto_examples_interruptible-optimization.py:

_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  45.126 seconds)
+   **Total running time of the script:** ( 1 minutes  5.223 seconds)
 
 
 .. _sphx_glr_download_auto_examples_parallel-optimization.py:

_sources/auto_examples/interruptible-optimization.rst.txt

@@ -5,24 +5,24 @@
 
 Computation times
 =================
-**16:25.220** total execution time for **auto_examples** files:
+**18:55.071** total execution time for **auto_examples** files:
 
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_visualizing-results.py` (``visualizing-results.py``)                           | 07:34.032 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_visualizing-results.py` (``visualizing-results.py``)                           | 07:40.760 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_strategy-comparison.py` (``strategy-comparison.py``)                           | 05:50.887 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_strategy-comparison.py` (``strategy-comparison.py``)                           | 07:20.455 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` (``sklearn-gridsearchcv-replacement.py``) | 01:09.956 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_hyperparameter-optimization.py` (``hyperparameter-optimization.py``)           | 01:22.113 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_hyperparameter-optimization.py` (``hyperparameter-optimization.py``)           | 00:53.164 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_sklearn-gridsearchcv-replacement.py` (``sklearn-gridsearchcv-replacement.py``) | 01:14.203 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_parallel-optimization.py` (``parallel-optimization.py``)                       | 00:45.126 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_parallel-optimization.py` (``parallel-optimization.py``)                       | 01:05.223 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_interruptible-optimization.py` (``interruptible-optimization.py``)             | 00:03.923 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_interruptible-optimization.py` (``interruptible-optimization.py``)             | 00:03.936 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_ask-and-tell.py` (``ask-and-tell.py``)                                         | 00:02.800 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_ask-and-tell.py` (``ask-and-tell.py``)                                         | 00:02.973 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_store-and-load-results.py` (``store-and-load-results.py``)                     | 00:02.694 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_bayesian-optimization.py` (``bayesian-optimization.py``)                       | 00:02.730 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_auto_examples_bayesian-optimization.py` (``bayesian-optimization.py``)                       | 00:02.638 | 0.0 MB |
+| :ref:`sphx_glr_auto_examples_store-and-load-results.py` (``store-and-load-results.py``)                     | 00:02.677 | 0.0 MB |
 +-------------------------------------------------------------------------------------------------------------+-----------+--------+

_sources/auto_examples/parallel-optimization.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  9.956 seconds)
+   **Total running time of the script:** ( 1 minutes  14.203 seconds)
 
 
 .. _sphx_glr_download_auto_examples_sklearn-gridsearchcv-replacement.py:

_sources/auto_examples/sg_execution_times.rst.txt

@@ -111,10 +111,6 @@ We will use the same optimization problem as in the
       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 "
 
 
 
@@ -172,7 +168,7 @@ And load from file using :class:`skopt.load`:
  .. code-block:: none
 
 
-    -0.20989221173875044
+    -0.19571605508900328
 
 
 
@@ -206,7 +202,7 @@ level (highest in this case):
  .. code-block:: none
 
     Without compression: 80120 bytes
-    Compressed with gz:  19386 bytes
+    Compressed with gz:  21139 bytes
 
 
 
@@ -294,7 +290,7 @@ copy is created:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  2.694 seconds)
+   **Total running time of the script:** ( 0 minutes  2.677 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 0x7fb66e601550>
+    <matplotlib.legend.Legend object at 0x7f5acd12c730>
 
 
 
@@ -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:** ( 5 minutes  50.887 seconds)
+   **Total running time of the script:** ( 7 minutes  20.455 seconds)
 
 
 .. _sphx_glr_download_auto_examples_strategy-comparison.py:

_sources/auto_examples/store-and-load-results.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  34.032 seconds)
+   **Total running time of the script:** ( 7 minutes  40.760 seconds)
 
 
 .. _sphx_glr_download_auto_examples_visualizing-results.py:

_sources/auto_examples/strategy-comparison.rst.txt

@@ -8,6 +8,7 @@ Release notes for all scikit-optimize releases are linked in this this page.
 .. toctree::
     :maxdepth: 1
 
+    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>
     Version 0.5 <whats_new/v0.5.rst>

_sources/auto_examples/visualizing-results.rst.txt

@@ -0,0 +1,22 @@
+Version 0.7.1
+=============
+
+New features
+------------
+
+* Sphinx documentation
+* notebooks are replaced by sphinx-gallery
+* New StringEncoder, can be used in Categoricals
+* Remove string conversion in Identity
+* dtype can be set in Integer and Real
+
+Bug fixes
+---------
+
+* Fix categorical space (issue #821)
+* int can be set as dtype to fix issue #790
+
+Maintenance
+-----------
+
+* Old pdoc scripts are removed and replaced by sphinx

_sources/whats_new.rst.txt

@@ -217,7 +217,7 @@ <h2>The Setup<a class="headerlink" href="#the-setup" title="Permalink to this he
 <div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>         fun: -0.032758350111535384
    func_vals: array([-0.03275835])
       models: []
-random_state: RandomState(MT19937) at 0x7FB6A30BB940
+random_state: RandomState(MT19937) at 0x7F5B01BC0940
        space: Space([Real(low=-2.0, high=2.0, prior=&#39;uniform&#39;, transform=&#39;identity&#39;)])
        specs: None
            x: [-1.7121321838148869]
@@ -300,7 +300,7 @@ <h2>The Setup<a class="headerlink" href="#the-setup" title="Permalink to this he
     <span class="n">opt_restored</span> <span class="o">=</span> <a href="https://docs.python.org/3/library/pickle.html#pickle.load" title="View documentation for pickle.load"><span class="n">pickle</span><span class="o">.</span><span class="n">load</span></a><span class="p">(</span><span class="n">f</span><span class="p">)</span>
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  2.800 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> ( 0 minutes  2.973 seconds)</p>
 <div class="sphx-glr-footer class sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-ask-and-tell-py">
 <div class="binder-badge docutils container">
 <a class="reference external image-reference" href="https://mybinder.org/v2/gh/scikit-optimize/scikit-optimize/master?urlpath=lab/tree/notebooks/auto_examples/ask-and-tell.ipynb"><img alt="https://mybinder.org/badge_logo.svg" src="https://mybinder.org/badge_logo.svg" width="150px" /></a>