From 4d3abef750dfff582386cc8c062c58d39791cf0d Mon Sep 17 00:00:00 2001 From: relf Date: Wed, 29 Nov 2023 16:34:47 +0100 Subject: [PATCH] Update doc with pydoe samplings --- doc/_src_docs/sampling_methods.rst | 7 +- ...full_factorial_Test_run_full_factorial.png | Bin 0 -> 12610 bytes doc/_src_docs/sampling_methods/lhs.rstx | 4 +- .../sampling_methods/lhs_Test_run_lhs.png | Bin 0 -> 14094 bytes doc/_src_docs/sampling_methods/pydoe.rst | 267 ++++++++++++++++++ doc/_src_docs/sampling_methods/pydoe.rstx | 7 +- .../pydoe_Test_run_box_behnken.png | Bin 0 -> 82785 bytes .../pydoe_Test_run_factorial.png | Bin 0 -> 89369 bytes .../sampling_methods/pydoe_Test_run_gsd.png | Bin 0 -> 85860 bytes .../pydoe_Test_run_plackett_burman.png | Bin 0 -> 80954 bytes .../random_Test_run_random.png | Bin 0 -> 15281 bytes .../sampling_methods_Test_run_random.png | Bin 0 -> 15573 bytes .../sampling_methods_Test_test_random.png | Bin 15694 -> 15915 bytes doc/index.rst | 1 - .../tests/test_sampling_method_examples.py | 39 ++- 15 files changed, 300 insertions(+), 25 deletions(-) create mode 100644 doc/_src_docs/sampling_methods/full_factorial_Test_run_full_factorial.png create mode 100644 doc/_src_docs/sampling_methods/lhs_Test_run_lhs.png create mode 100644 doc/_src_docs/sampling_methods/pydoe.rst create mode 100644 doc/_src_docs/sampling_methods/pydoe_Test_run_box_behnken.png create mode 100644 doc/_src_docs/sampling_methods/pydoe_Test_run_factorial.png create mode 100644 doc/_src_docs/sampling_methods/pydoe_Test_run_gsd.png create mode 100644 doc/_src_docs/sampling_methods/pydoe_Test_run_plackett_burman.png create mode 100644 doc/_src_docs/sampling_methods/random_Test_run_random.png create mode 100644 doc/_src_docs/sampling_methods_Test_run_random.png diff --git a/doc/_src_docs/sampling_methods.rst b/doc/_src_docs/sampling_methods.rst index 0ba338c28..499dfcb7f 100644 --- a/doc/_src_docs/sampling_methods.rst +++ b/doc/_src_docs/sampling_methods.rst @@ -12,6 +12,7 @@ These are listed below. sampling_methods/random sampling_methods/lhs sampling_methods/full_factorial + sampling_methods/pydoe Usage ----- @@ -40,12 +41,12 @@ Usage (50, 2) -.. figure:: sampling_methods_Test_test_random.png +.. figure:: sampling_methods_Test_run_random.png :scale: 80 % :align: center -Problem class API ------------------ +Sampling method class API +------------------------- .. autoclass:: smt.sampling_methods.sampling_method.SamplingMethod diff --git a/doc/_src_docs/sampling_methods/full_factorial_Test_run_full_factorial.png b/doc/_src_docs/sampling_methods/full_factorial_Test_run_full_factorial.png new file mode 100644 index 0000000000000000000000000000000000000000..18b6d822ed3870f234d747f23165e31364625bcb GIT binary patch literal 12610 zcmeHtcUV(r-+wH%KGs1gLzHE)3W`7h1sNee6+{I=L`Hub+>5Z$Lw8vUI2<3{X+H znZ^(AH9?mFQGS~Q2Hqa1^cUs5;R(i zaHPP^H4os=B?+>_qobn%iSTo&(ed%{_58csG0yby-P?IyFrqDtO-y9qq4UH<*CwgU zoAaPhPYn;EP*)uUzCxk4i>&<|g?e##&6tm)Bem;7M8mgIDSt+HZYBmiCTgmJy zd3~R{>If0+!t99QnKN6XEq(1YW?vnOwZS=+5`=Q+BfR>Cx@n>H&gJ|TI$_I+%|GpU zzHeGr>ir?beAC#}`i)w23X$lH=XAStUX0e(sw4)?rm)9tF(TcCj$veW82NympRTU% zYrmO#7nmbTsGv+=$xvdL`c%2nVWPNL(Q8-T$&sY?mYl+>=Kb|e?JhsztQ?PD+#9Q; 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F The four first criteria are the same than in pyDOE (for more details, see [1]_). The last criterion, ESE, is implemented by the authors of SMT (more details about such method could be found in [2]_). -.. [1] https://pythonhosted.org/pyDOE/index.html +.. [1] https://pydoe3.readthedocs.io/en/stable .. [2] Jin, R. and Chen, W. and Sudjianto, A. (2005), "An efficient algorithm for constructing optimal design of computer experiments." Journal of Statistical Planning and Inference, 134:268-287. 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+85,7 @@ def run_box_behnken(): print(x.shape) ax = plt.axes(projection="3d") - ax.plot3D(x[:, 0], x[:, 1], x[:, 2], ".") + ax.plot3D(x[:, 0], x[:, 1], x[:, 2], "o") ax.set_xlabel("x0") ax.set_ylabel("x1") @@ -99,16 +99,19 @@ def run_plackett_burman(): from smt.sampling_methods import PlackettBurman - xlimits = np.array([[0.0, 4.0], [0.0, 3.0]]) + xlimits = np.array([[0.0, 4.0], [0.0, 3.0], [-6.0, 1.0]]) sampling = PlackettBurman(xlimits=xlimits) x = sampling() print(x.shape) - plt.plot(x[:, 0], x[:, 1], "o") - plt.xlabel("x") - plt.ylabel("y") + ax = plt.axes(projection="3d") + ax.plot3D(x[:, 0], x[:, 1], x[:, 2], "o") + + ax.set_xlabel("x0") + ax.set_ylabel("x1") + ax.set_zlabel("x2") plt.show() @staticmethod @@ -118,16 +121,19 @@ def run_factorial(): from smt.sampling_methods import Factorial - xlimits = np.array([[0.0, 4.0], [0.0, 3.0]]) - sampling = Factorial(xlimits=xlimits, levels=[3, 6]) + xlimits = np.array([[0.0, 4.0], [0.0, 3.0], [-6.0, 1.0]]) + sampling = Factorial(xlimits=xlimits, levels=[3, 6, 4]) x = sampling() print(x.shape) - plt.plot(x[:, 0], x[:, 1], "o") - plt.xlabel("x") - plt.ylabel("y") + ax = plt.axes(projection="3d") + ax.plot3D(x[:, 0], x[:, 1], x[:, 2], "o") + + ax.set_xlabel("x0") + ax.set_ylabel("x1") + ax.set_zlabel("x2") plt.show() @staticmethod @@ -137,16 +143,19 @@ def run_gsd(): from smt.sampling_methods import Gsd - xlimits = np.array([[0.0, 4.0], [0.0, 3.0]]) - sampling = Gsd(xlimits=xlimits, levels=[3, 6]) + xlimits = np.array([[0.0, 4.0], [0.0, 3.0], [-6.0, 1.0]]) + sampling = Gsd(xlimits=xlimits, levels=[3, 6, 4]) x = sampling() print(x.shape) - plt.plot(x[:, 0], x[:, 1], "o") - plt.xlabel("x") - plt.ylabel("y") + ax = plt.axes(projection="3d") + ax.plot3D(x[:, 0], x[:, 1], x[:, 2], "o") + + ax.set_xlabel("x0") + ax.set_ylabel("x1") + ax.set_zlabel("x2") plt.show() @unittest.skipIf(NO_MATPLOTLIB, "Matplotlib not installed")