Correct generated doc

openkim · Apr 28, 2022 · 17c4661 · 17c4661
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Showing 17 changed files with 357 additions and 27 deletions.
diff --git a/devtool/README.md b/devtool/README.md
@@ -17,6 +17,14 @@
   - remove `.git/hooks/pre-commit` so that it will not correct the generated
     doc files, otherwise ReadTheDoc will try to regenerate it and then fail
   - after commit it, then `$ pre-commit install` to get pre-commit back
+  - Note, check the generated tutorial notebooks -- sometimes sphinx-galley will
+    not correctly capture the stdout and embed it in the file. In this case,
+    delete hte .md5 file and return `make html`. (Also, do it one be one.)
+    For example,
+    ```shell
+    $ rm source/auto_examples/example_kim_SW_Si.py.md5
+    $ make html
+    ```
 
 - Commit and merge it to the `docs` branch. [ReadTheDocs](https://readthedocs.org)
   is set up to watch this branch and will automatically generate the docs.)

diff --git a/docs/source/auto_examples/auto_examples_jupyter.zip b/docs/source/auto_examples/auto_examples_jupyter.zip
diff --git a/docs/source/auto_examples/auto_examples_python.zip b/docs/source/auto_examples/auto_examples_python.zip
diff --git a/docs/source/auto_examples/example_kim_SW_Si.rst b/docs/source/auto_examples/example_kim_SW_Si.rst
@@ -99,6 +99,49 @@ parameters that can be optimized (we call this ``model parameters``).
 
  .. code-block:: none
 
+    #================================================================================
+    # Available parameters to optimize.
+    # Parameters in `original` space.
+    # Model: SW_StillingerWeber_1985_Si__MO_405512056662_006
+    #================================================================================
+
+    name: A
+    value: [15.28484792]
+    size: 1
+
+    name: B
+    value: [0.60222456]
+    size: 1
+
+    name: p
+    value: [4.]
+    size: 1
+
+    name: q
+    value: [0.]
+    size: 1
+
+    name: sigma
+    value: [2.0951]
+    size: 1
+
+    name: gamma
+    value: [2.51412]
+    size: 1
+
+    name: cutoff
+    value: [3.77118]
+    size: 1
+
+    name: lambda
+    value: [45.5322]
+    size: 1
+
+    name: costheta0
+    value: [-0.33333333]
+    size: 1
+
+
 
     '#================================================================================\n# Available parameters to optimize.\n# Parameters in `original` space.\n# Model: SW_StillingerWeber_1985_Si__MO_405512056662_006\n#================================================================================\n\nname: A\nvalue: [15.28484792]\nsize: 1\n\nname: B\nvalue: [0.60222456]\nsize: 1\n\nname: p\nvalue: [4.]\nsize: 1\n\nname: q\nvalue: [0.]\nsize: 1\n\nname: sigma\nvalue: [2.0951]\nsize: 1\n\nname: gamma\nvalue: [2.51412]\nsize: 1\n\nname: cutoff\nvalue: [3.77118]\nsize: 1\n\nname: lambda\nvalue: [45.5322]\nsize: 1\n\nname: costheta0\nvalue: [-0.33333333]\nsize: 1\n\n'
 
@@ -142,6 +185,25 @@ subset of them to reproduce the training set.
 
  .. code-block:: none
 
+    #================================================================================
+    # Model parameters that are optimized.
+    # Note that the parameters are in the transformed space if 
+    # `params_transform` is provided when instantiating the model.
+    #================================================================================
+
+    A 1
+      5.0000000000000000e+00   1.0000000000000000e+00   2.0000000000000000e+01 
+
+    B 1
+      6.0222455840000000e-01 
+
+    sigma 1
+      2.0951000000000000e+00 fix 
+
+    gamma 1
+      1.5000000000000000e+00 
+
+
 
     '#================================================================================\n# Model parameters that are optimized.\n# Note that the parameters are in the transformed space if \n# `params_transform` is provided when instantiating the model.\n#================================================================================\n\nA 1\n  5.0000000000000000e+00   1.0000000000000000e+00   2.0000000000000000e+01 \n\nB 1\n  6.0222455840000000e-01 \n\nsigma 1\n  2.0951000000000000e+00 fix \n\ngamma 1\n  1.5000000000000000e+00 \n\n'
 
@@ -201,6 +263,14 @@ For the silicon training set, we can read and process the files by:
 
 
 
+.. rst-class:: sphx-glr-script-out
+
+ Out:
+
+ .. code-block:: none
+
+    2022-04-28 11:03:34.898 | INFO     | kliff.dataset.dataset:_read:397 - 1000 configurations read from /Users/mjwen/Applications/kliff/examples/Si_training_set
+
 
 
 
@@ -236,6 +306,14 @@ by:
 
 
 
+.. rst-class:: sphx-glr-script-out
+
+ Out:
+
+ .. code-block:: none
+
+    2022-04-28 11:03:38.460 | INFO     | kliff.calculators.calculator:create:107 - Create calculator for 1000 configurations.
+
 
 
 
@@ -277,6 +355,9 @@ the loss, and the minimization is allowed to run for a max number of 100 iterati
 
  .. code-block:: none
 
+    2022-04-28 11:03:38.462 | INFO     | kliff.loss:minimize:290 - Start minimization using method: L-BFGS-B.
+    2022-04-28 11:03:38.462 | INFO     | kliff.loss:_scipy_optimize:406 - Running in multiprocessing mode with 2 processes.
+    2022-04-28 11:05:36.267 | INFO     | kliff.loss:minimize:292 - Finish minimization using method: L-BFGS-B.
 
           fun: 0.6940780132834561
      hess_inv: <3x3 LbfgsInvHessProduct with dtype=float64>
@@ -313,6 +394,33 @@ that can be used with LAMMPS_, GULP_, ASE_, etc. via the kim-api_.
 
 
 
+.. rst-class:: sphx-glr-script-out
+
+ Out:
+
+ .. code-block:: none
+
+    #================================================================================
+    # Model parameters that are optimized.
+    # Note that the parameters are in the transformed space if 
+    # `params_transform` is provided when instantiating the model.
+    #================================================================================
+
+    A 1
+      1.4938636641779590e+01   1.0000000000000000e+00   2.0000000000000000e+01 
+
+    B 1
+      5.8740288227791959e-01 
+
+    sigma 1
+      2.0951000000000000e+00 fix 
+
+    gamma 1
+      2.2014624192566941e+00 
+
+
+    2022-04-28 11:05:36.291 | INFO     | kliff.models.kim:write_kim_model:695 - KLIFF trained model write to `/Users/mjwen/Applications/kliff/examples/SW_StillingerWeber_1985_Si__MO_405512056662_006_kliff_trained`
+
 
 
 
@@ -340,7 +448,7 @@ parameters quite reasonably. The second line saves the fitted model to a file na
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 2 minutes  5.502 seconds)
+   **Total running time of the script:** ( 2 minutes  4.046 seconds)
 
 
 .. _sphx_glr_download_auto_examples_example_kim_SW_Si.py:

diff --git a/docs/source/auto_examples/example_kim_SW_Si_codeobj.pickle b/docs/source/auto_examples/example_kim_SW_Si_codeobj.pickle
diff --git a/docs/source/auto_examples/example_lennard_jones.rst b/docs/source/auto_examples/example_lennard_jones.rst
@@ -36,8 +36,69 @@ Compare this with :ref:`tut_kim_sw`.
 
 
 
+.. rst-class:: sphx-glr-script-out
 
+ Out:
 
+ .. code-block:: none
+
+    2022-04-28 11:07:49.718 | INFO     | kliff.dataset.dataset:_read:397 - 4 configurations read from /Users/mjwen/Applications/kliff/examples/Si_training_set_4_configs
+    #================================================================================
+    # Available parameters to optimize.
+    # Parameters in `original` space.
+    # Model: LJ6-12
+    #================================================================================
+
+    name: epsilon
+    value: [1.]
+    size: 1
+
+    name: sigma
+    value: [2.]
+    size: 1
+
+    name: cutoff
+    value: [5.]
+    size: 1
+
+
+    #================================================================================
+    # Model parameters that are optimized.
+    # Note that the parameters are in the transformed space if 
+    # `params_transform` is provided when instantiating the model.
+    #================================================================================
+
+    sigma 1
+      2.0000000000000000e+00 
+
+    epsilon 1
+      1.0000000000000000e+00 
+
+
+    2022-04-28 11:07:49.726 | INFO     | kliff.calculators.calculator:create:107 - Create calculator for 4 configurations.
+    2022-04-28 11:07:49.726 | INFO     | kliff.loss:minimize:290 - Start minimization using method: L-BFGS-B.
+    2022-04-28 11:07:49.727 | INFO     | kliff.loss:_scipy_optimize:404 - Running in serial mode.
+    2022-04-28 11:07:53.172 | INFO     | kliff.loss:minimize:292 - Finish minimization using method: L-BFGS-B.
+    #================================================================================
+    # Model parameters that are optimized.
+    # Note that the parameters are in the transformed space if 
+    # `params_transform` is provided when instantiating the model.
+    #================================================================================
+
+    sigma 1
+      2.0629043239028659e+00 
+
+    epsilon 1
+      1.5614870430532530e+00 
+
+
+
+
+
+
+
+
+|
 
 .. code-block:: default
 
@@ -75,7 +136,7 @@ Compare this with :ref:`tut_kim_sw`.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  6.187 seconds)
+   **Total running time of the script:** ( 0 minutes  5.538 seconds)
 
 
 .. _sphx_glr_download_auto_examples_example_lennard_jones.py:

diff --git a/docs/source/auto_examples/example_lennard_jones_codeobj.pickle b/docs/source/auto_examples/example_lennard_jones_codeobj.pickle
diff --git a/docs/source/auto_examples/example_linear_regression.rst b/docs/source/auto_examples/example_linear_regression.rst
@@ -65,17 +65,17 @@ symmetry functions.
 
  .. code-block:: none
 
-    2022-04-28 10:33:14.541 | INFO     | kliff.dataset.dataset:_read:397 - 400 configurations read from /Users/mjwen/Applications/kliff/examples/Si_training_set/varying_alat
-    2022-04-28 10:33:14.541 | INFO     | kliff.calculators.calculator_torch:_get_device:417 - Training on cpu
-    2022-04-28 10:33:14.542 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:104 - Start computing mean and stdev of fingerprints.
-    2022-04-28 10:33:37.085 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:121 - Finish computing mean and stdev of fingerprints.
-    2022-04-28 10:33:37.092 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:129 - Fingerprints mean and stdev saved to `fingerprints_mean_and_stdev.pkl`.
-    2022-04-28 10:33:37.092 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:164 - Pickling fingerprints to `fingerprints.pkl`
-    2022-04-28 10:33:37.095 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 0.
-    2022-04-28 10:33:37.424 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 100.
-    2022-04-28 10:33:38.046 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 200.
-    2022-04-28 10:33:38.510 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 300.
-    2022-04-28 10:33:38.884 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:219 - Pickle 400 configurations finished.
+    2022-04-28 10:49:35.846 | INFO     | kliff.dataset.dataset:_read:397 - 400 configurations read from /Users/mjwen/Applications/kliff/examples/Si_training_set/varying_alat
+    2022-04-28 10:49:35.848 | INFO     | kliff.calculators.calculator_torch:_get_device:417 - Training on cpu
+    2022-04-28 10:49:35.849 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:104 - Start computing mean and stdev of fingerprints.
+    2022-04-28 10:49:56.708 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:121 - Finish computing mean and stdev of fingerprints.
+    2022-04-28 10:49:56.712 | INFO     | kliff.descriptors.descriptor:generate_fingerprints:129 - Fingerprints mean and stdev saved to `fingerprints_mean_and_stdev.pkl`.
+    2022-04-28 10:49:56.712 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:164 - Pickling fingerprints to `fingerprints.pkl`
+    2022-04-28 10:49:56.734 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 0.
+    2022-04-28 10:49:57.294 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 100.
+    2022-04-28 10:49:57.906 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 200.
+    2022-04-28 10:49:58.640 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:176 - Processing configuration: 300.
+    2022-04-28 10:49:59.157 | INFO     | kliff.descriptors.descriptor:_dump_fingerprints:219 - Pickle 400 configurations finished.
 
 
 
@@ -109,7 +109,7 @@ function of its calculator.
 
  .. code-block:: none
 
-    2022-04-28 10:33:39.460 | INFO     | kliff.models.linear_regression:fit:39 - fit model "LinearRegression" finished.
+    2022-04-28 10:49:59.693 | INFO     | kliff.models.linear_regression:fit:39 - fit model "LinearRegression" finished.
     fit model "LinearRegression" finished.
 
 
@@ -118,7 +118,7 @@ function of its calculator.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  26.918 seconds)
+   **Total running time of the script:** ( 0 minutes  25.892 seconds)
 
 
 .. _sphx_glr_download_auto_examples_example_linear_regression.py:

diff --git a/docs/source/auto_examples/example_linear_regression_codeobj.pickle b/docs/source/auto_examples/example_linear_regression_codeobj.pickle
diff --git a/docs/source/auto_examples/example_nn_Si.rst b/docs/source/auto_examples/example_nn_Si.rst
@@ -270,7 +270,7 @@ codes such as LAMMPS via the KIM API.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  47.669 seconds)
+   **Total running time of the script:** ( 0 minutes  45.015 seconds)
 
 
 .. _sphx_glr_download_auto_examples_example_nn_Si.py:

diff --git a/docs/source/auto_examples/example_nn_SiC.rst b/docs/source/auto_examples/example_nn_SiC.rst
@@ -160,7 +160,7 @@ We can save the trained model to disk, and later can load it back if we want.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  2.116 seconds)
+   **Total running time of the script:** ( 0 minutes  1.955 seconds)
 
 
 .. _sphx_glr_download_auto_examples_example_nn_SiC.py:

diff --git a/docs/source/auto_examples/example_nn_SiC_codeobj.pickle b/docs/source/auto_examples/example_nn_SiC_codeobj.pickle
diff --git a/docs/source/auto_examples/example_nn_Si_codeobj.pickle b/docs/source/auto_examples/example_nn_Si_codeobj.pickle