From 3e79436fc9bec13353cf58d23e5277491a2cffa6 Mon Sep 17 00:00:00 2001 From: Jean-Philippe ARGAUD Date: Tue, 15 Oct 2024 16:10:18 +0200 Subject: [PATCH] Documentation and code update and corrections --- doc/en/examples.rst | 2 + doc/en/images/sampling_01_SampleAsnUplet.png | Bin 14632 -> 14632 bytes .../sampling_02_SampleAsExplicitHyperCube.png | Bin 14632 -> 14632 bytes ...ampling_03_SampleAsMinMaxStepHyperCube.png | Bin 14632 -> 14632 bytes ...mpling_04_SampleAsMinMaxLatinHyperCube.png | Bin 15799 -> 15799 bytes ...ampling_05_SampleAsMinMaxSobolSequence.png | Bin 16216 -> 16216 bytes ...pleAsIndependantRandomVariables_normal.png | Bin 16708 -> 16708 bytes ...leAsIndependantRandomVariables_uniform.png | Bin 14004 -> 14004 bytes ...leAsIndependantRandomVariables_weibull.png | Bin 13608 -> 13608 bytes doc/en/index.rst | 24 +- ...ef_algorithm_ParticleSwarmOptimization.rst | 2 + doc/en/ref_observations_requirements.rst | 2 +- doc/en/ref_output_variables.rst | 2 +- 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doc/fr/scripts/simple_KalmanFilter2_state.png | Bin 30177 -> 30177 bytes .../scripts/simple_KalmanFilter2_variance.png | Bin 25376 -> 25376 bytes ...le_MeasurementsOptimalPositioningTask3.png | Bin 237609 -> 237609 bytes .../scripts/simple_NonLinearLeastSquares.png | Bin 40395 -> 40395 bytes .../simple_ParticleSwarmOptimization1.png | Bin 40622 -> 40622 bytes .../scripts/simple_ReducedModelingTest1.png | Bin 93132 -> 93132 bytes doc/fr/scripts/tui_example_07.res | 2 +- doc/fr/scripts/tui_example_11.py | 2 +- doc/fr/scripts/tui_example_12.png | Bin 0 -> 97602 bytes doc/fr/scripts/tui_example_12.py | 101 + doc/fr/scripts/tui_example_12.res | 26 + doc/fr/snippets/Header2Algo04.rst | 11 +- doc/fr/snippets/MaximumNumberOfLocations.rst | 2 +- doc/fr/snippets/ModuleCompatibility.rst | 14 +- doc/fr/snippets/ModuleValidation.rst | 1 + doc/fr/snippets/NoUnconditionalOutput.rst | 2 +- .../SampleAsIndependantRandomVariables.rst | 2 +- .../snippets/SampleAsMinMaxLatinHyperCube.rst | 2 +- .../snippets/SampleAsMinMaxSobolSequence.rst | 2 +- doc/fr/snippets/StoreInitialState.rst | 11 + doc/fr/tui.rst | 194 +- src/daComposant/daAlgorithms/Atoms/ecwapso.py | 10 + src/daComposant/daAlgorithms/Atoms/ecwnpso.py | 10 + src/daComposant/daAlgorithms/Atoms/ecwopso.py | 10 + .../daAlgorithms/Atoms/ecwpspso.py | 9 + src/daComposant/daAlgorithms/Atoms/ecwspso.py | 9 + .../daAlgorithms/Atoms/incr3dvar.py | 4 +- .../daAlgorithms/Atoms/std3dvar.py | 4 +- .../daAlgorithms/Atoms/van3dvar.py | 4 +- .../InterpolationByReducedModelTask.py | 2 +- .../daAlgorithms/ParticleSwarmOptimization.py | 6 + src/daComposant/daCore/Aidsm.py | 1019 +++--- src/daComposant/daCore/AssimilationStudy.py | 5 +- src/daComposant/daCore/BasicObjects.py | 3127 ++++++++++++----- src/daComposant/daCore/ExtendedLogging.py | 83 +- src/daComposant/daCore/Interfaces.py | 1175 ++++--- src/daComposant/daCore/NumericObjects.py | 1360 ++++--- src/daComposant/daCore/Persistence.py | 545 +-- src/daComposant/daCore/PlatformInfo.py | 459 ++- src/daComposant/daCore/Reporting.py | 58 +- src/daComposant/daCore/Templates.py | 361 +- .../daNumerics/Models/Lorenz1963.py | 106 + .../TwoDimensionalInverseDistanceCS2010.py | 28 +- .../TwoDimensionalRosenbrockFunctionR1960.py | 44 +- src/daEficas/prefs_ADAO.py.in | 2 +- 107 files changed, 6314 insertions(+), 2929 deletions(-) create mode 100644 doc/en/scripts/tui_example_12.png create mode 100644 doc/en/scripts/tui_example_12.py create mode 100644 doc/en/scripts/tui_example_12.res create mode 100644 doc/en/snippets/StoreInitialState.rst create mode 100644 doc/fr/scripts/tui_example_12.png create mode 100644 doc/fr/scripts/tui_example_12.py create mode 100644 doc/fr/scripts/tui_example_12.res create mode 100644 doc/fr/snippets/StoreInitialState.rst create mode 100644 src/daComposant/daNumerics/Models/Lorenz1963.py diff --git a/doc/en/examples.rst b/doc/en/examples.rst index 6cd8b44..a42dc85 100644 --- a/doc/en/examples.rst +++ b/doc/en/examples.rst @@ -71,6 +71,8 @@ Dedicated tasks or study oriented cases uses Advanced uses ------------- +#. :ref:`subsection_tui_advanced_ex11` +#. :ref:`subsection_tui_advanced_ex12` #. :ref:`section_advanced_convert_JDC` #. :ref:`section_advanced_YACS_tui` #. :ref:`section_advanced_R` diff --git a/doc/en/images/sampling_01_SampleAsnUplet.png b/doc/en/images/sampling_01_SampleAsnUplet.png index a10feeb3933637e9db62ddafaea52c8915b61396..97907e5ae94efb066c6639cb826f2c47da93dd02 100644 GIT binary patch delta 43 ycmZ2cw4!K&n}VgDk&Z$}Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5l{d=SC_ delta 43 ycmcanccX5Cn}UU&iH<@>Nl8JmmA-y%Vo52PG*u`eo?x2PG*u`eo?xJO{{ delta 43 ycmdmzyCrvmn}UU&iH<@>Nl8JmmA-y%Vo5JR_` delta 43 ycmZ3HwIXYRn}UU&iH<@>Nl8JmmA-y%Vo51y3K=CO1;tkS`nicE1v&X8Ihjd%`9L&62LOHi B5Xk@l delta 45 zcmdn7pJ~T_rU`Be7J4Q+3K=CO1;tkS`nicE1v&X8Ihjd%`91y3K=CO1;tkS`nicE1v&X8Ihjd%`9Q~^0|0nC B5Rw1@ delta 45 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zWTGO9zz)uh&oIK?l#e}xO(Xfe-#cyLvEujcR~v5k;b6a{c?XBJ`Evi?R)xp4lLdj4 ziDHaD8B}D5QS|Wbk73W(9yX49+u zN&e)v(@Q=3wFi4&Swb8-Os7er=kw8$Bh($z7^T(;HS&0dC>koT^2uNkHln3No;--!_&DbeZhY&W z$2;lT9zfl+BS#2Guef{L7QQI$-o@jBMtfS|(JY_v?wGCy>$mXUedK42b}*~?Z@tU@ ppBz)RW0XWc|1?4S-+$2fgq2SYd~;eCxqyKmy)_0pSF~-9{0}6iihlqA literal 0 HcmV?d00001 diff --git a/doc/en/scripts/tui_example_12.py b/doc/en/scripts/tui_example_12.py new file mode 100644 index 0000000..260dc6d --- /dev/null +++ b/doc/en/scripts/tui_example_12.py @@ -0,0 +1,101 @@ +# -*- coding: utf-8 -*- +# +from matplotlib import pyplot as plt +from numpy import array, set_printoptions +from adao import adaoBuilder +set_printoptions(precision=4, floatmode='fixed') +# +#------------------------------------------------------------------------------- +# +case = adaoBuilder.New() +case.set( 'AlgorithmParameters', + Algorithm='3DVAR', + Parameters = { + "StoreSupplementaryCalculations":[ + "CostFunctionJ", + "CurrentState", + "InnovationAtCurrentState", + ], + } +) +case.set( 'Background', Vector=[0, 1, 2] ) +case.set( 'BackgroundError', ScalarSparseMatrix=1.0 ) +case.set( 'Observation', Vector=array([0.5, 1.5, 2.5]) ) +case.set( 'ObservationError', DiagonalSparseMatrix='1 1 1' ) +case.set( 'ObservationOperator', Matrix='1 0 0;0 2 0;0 0 3' ) +case.set( 'Observer', + Variable="CurrentState", + Template="ValuePrinter", + Info=" Current state:", +) +# +print("Displays current state values, at each step:") +case.execute() +print("") +# +#------------------------------------------------------------------------------- +# +print("Calculation-measurement deviation (or error) indicators") +print(" (display only first 3 steps)") +print("") +CalculMeasureErrors = case.get("InnovationAtCurrentState") +# +print("===> Maximum error between calculations and measurements, at each step:") +print(" ",array( + CalculMeasureErrors.maxs() + [0:3] )) +print("===> Minimum error between calculations and measurements, at each step:") +print(" ",array( + CalculMeasureErrors.mins() + [0:3] )) +print("===> Norm of the error between calculation and measurement, at each step:") +print(" ",array( + CalculMeasureErrors.norms() + [0:3] )) +print("===> Mean absolute error (MAE) between calculations and measurements, at each step:") +print(" ",array( + CalculMeasureErrors.maes() + [0:3] )) +print("===> Mean square error (MSE) between calculations and measurements, at each step:") +print(" ",array( + CalculMeasureErrors.mses() + [0:3] )) +print("===> Root mean square error (RMSE) between calculations and measurements, at each step:") +print(" ",array( + CalculMeasureErrors.rmses() + [0:3] )) +# +#------------------------------------------------------------------------------- +# +import matplotlib.pyplot as plt +plt.rcParams['figure.figsize'] = (8, 12) +# +plt.figure() +plt.suptitle('Indicators built on the current value of the calculation-measurement deviation (or error)\n', fontweight='bold') +plt.subplot(611) +plt.plot(CalculMeasureErrors.maxs(), 'bx--', label='Indicator at current step') +plt.ylabel('Maximum (a.u.)') +plt.legend() +plt.subplot(612) +plt.plot(CalculMeasureErrors.mins(), 'bx--', label='Indicator at current step') +plt.ylabel('Minimum (a.u.)') +plt.legend() +plt.subplot(613) +plt.plot(CalculMeasureErrors.norms(), 'bx-', label='Indicator at current step') +plt.ylabel('Norm (a.u.)') +plt.legend() +plt.subplot(614) +plt.plot(CalculMeasureErrors.maes(), 'kx-', label='Indicator at current step') +plt.ylabel('MAE (a.u.)') +plt.legend() +plt.subplot(615) +plt.plot(CalculMeasureErrors.mses(), 'gx-', label='Indicator at current step') +plt.ylabel('MSE (a.u.)') +plt.legend() +plt.subplot(616) +plt.plot(CalculMeasureErrors.rmses(), 'rx-', label='Indicator at current step') +plt.ylabel('RMSE (a.u.)') +plt.legend() +plt.xlabel('Step size calculation (step number or rank)') +plt.tight_layout() +plt.savefig("tui_example_12.png") diff --git a/doc/en/scripts/tui_example_12.res b/doc/en/scripts/tui_example_12.res new file mode 100644 index 0000000..469fbd6 --- /dev/null +++ b/doc/en/scripts/tui_example_12.res @@ -0,0 +1,26 @@ +Displays current state values, at each step: + Current state: [0.0000 1.0000 2.0000] + Current state: [0.0474 0.9053 1.0056] + Current state: [0.0905 0.8492 0.9461] + Current state: [0.1529 0.7984 0.9367] + Current state: [0.2245 0.7899 0.9436] + Current state: [0.2508 0.8005 0.9486] + Current state: [0.2500 0.7998 0.9502] + Current state: [0.2500 0.8000 0.9500] + Current state: [0.2500 0.8000 0.9500] + +Calculation-measurement deviation (or error) indicators + (display only first 3 steps) + +===> Maximum error between calculations and measurements, at each step: + [0.5000 0.4526 0.4095] +===> Minimum error between calculations and measurements, at each step: + [-3.5000 -0.5169 -0.3384] +===> Norm of the error between calculation and measurement, at each step: + [3.5707 0.7540 0.5670] +===> Mean absolute error (MAE) between calculations and measurements, at each step: + [1.5000 0.4267 0.3154] +===> Mean square error (MSE) between calculations and measurements, at each step: + [4.2500 0.1895 0.1072] +===> Root mean square error (RMSE) between calculations and measurements, at each step: + [2.0616 0.4353 0.3274] diff --git a/doc/en/snippets/EntryTypeDataFile.rst b/doc/en/snippets/EntryTypeDataFile.rst index 855e69b..003c367 100644 --- a/doc/en/snippets/EntryTypeDataFile.rst +++ b/doc/en/snippets/EntryTypeDataFile.rst @@ -43,11 +43,10 @@ Example of TXT file for "*Observation*" variable in "*DataFile*" :: - # Fichier TXT à séparateur espace # TXT file with space delimiter # ============================= - # Ligne de commentaires quelconques débutant par # - # Ligne suivante réservée au nommage des variables + # Comment line beginning with # + # The next line is dedicated to variable naming Alpha1 Observation Alpha2 0.1234 5.6789 9.0123 1.2345 2.3456 3. diff --git a/doc/en/snippets/Header2Algo04.rst b/doc/en/snippets/Header2Algo04.rst index d778b79..92e3781 100644 --- a/doc/en/snippets/Header2Algo04.rst +++ b/doc/en/snippets/Header2Algo04.rst @@ -7,7 +7,7 @@ variables originating from the calculation. The description of named ``get``, of the variable "*ADD*" of the post-processing in graphical interface, or of the case in textual interface. The input variables, available to the user at the output in order to facilitate the writing of post-processing -procedures, are described in the :ref:`subsection_r_o_v_Inventaire`. +procedures, are described in an :ref:`subsection_r_o_v_Inventaire`. **Permanent outputs (non conditional)** diff --git a/doc/en/snippets/ModuleCompatibility.rst b/doc/en/snippets/ModuleCompatibility.rst index dc99912..44ddb74 100644 --- a/doc/en/snippets/ModuleCompatibility.rst +++ b/doc/en/snippets/ModuleCompatibility.rst @@ -10,13 +10,15 @@ remains without guarantee. If an unusual error is encountered for previously running calculations, it is strongly recommended to revert to supporting tool versions within the range described below. -.. csv-table:: Support tool verification intervals for ADAO +.. csv-table:: Support tool verification version intervals for ADAO :header: "Tool", "Minimal version", "Reached version" :widths: 20, 10, 10 + :align: center - Python, 3.6.5, 3.12.3 - Numpy, 1.14.3, 1.26.4 - Scipy, 0.19.1, 1.14.0 - MatplotLib, 2.2.2, 3.8.4 + Python, 3.6.5, 3.12.6 + Numpy, 1.14.3, 2.1.2 + Scipy, 0.19.1, 1.14.1 + MatplotLib, 2.2.2, 3.9.2 GnuplotPy, 1.8, 1.8 - NLopt, 2.4.2, 2.7.1 + NLopt, 2.4.2, 2.8.0 + FMPy, 0.3.20, 0.3.20 diff --git a/doc/en/snippets/ModuleValidation.rst b/doc/en/snippets/ModuleValidation.rst index 4ef9258..494a93b 100644 --- a/doc/en/snippets/ModuleValidation.rst +++ b/doc/en/snippets/ModuleValidation.rst @@ -5,9 +5,10 @@ current document. The validation versions are indicated here for information purposes only, knowing that, in case of doubt, the SALOME version sheet [Salome]_ is the official validation version. -.. csv-table:: Validation versions of support tools for ADAO +.. csv-table:: Validation versions of the support tools for ADAO :header: "Tool", "Version" :widths: 20, 10 + :align: center ADAO, |release| EFICAS, |release| diff --git a/doc/en/snippets/NoConditionalOutput.rst b/doc/en/snippets/NoConditionalOutput.rst index 6bd824c..d99c316 100644 --- a/doc/en/snippets/NoConditionalOutput.rst +++ b/doc/en/snippets/NoConditionalOutput.rst @@ -1 +1 @@ - *None* + *None* (messages or statistics are nevertheless displayed) diff --git a/doc/en/snippets/StoreInitialState.rst b/doc/en/snippets/StoreInitialState.rst new file mode 100644 index 0000000..df9e7e5 --- /dev/null +++ b/doc/en/snippets/StoreInitialState.rst @@ -0,0 +1,11 @@ +.. index:: single: StoreInitialState + +StoreInitialState + *Boolean value*. This variable defines whether the algorithm's initial state + is stored (with True) or not (with False, by default) as the first state in + the iterative sequence of found states. This makes algorithmic iterative + storage identical to temporal iterative storage (similar, for example, to + Kalman filters). + + Example : + ``{"StoreInitialState":False}`` diff --git a/doc/en/tui.rst b/doc/en/tui.rst index 0cda027..54ca033 100644 --- a/doc/en/tui.rst +++ b/doc/en/tui.rst @@ -71,6 +71,7 @@ command, in the SALOME Python command window of the interface, or by the script execution entry of the menu) is the following: .. literalinclude:: scripts/tui_example_01.res + :language: none Detailed setup of an ADAO TUI calculation case +++++++++++++++++++++++++++++++++++++++++++++++ @@ -625,7 +626,7 @@ Get the calculation results separately visualization. Its argument the name of a variable "*Concept*" and returns back the quantity as a list (even if there is only one specimen) of this base variable. For a list of variables and use them, the user has to refer - to the :ref:`subsection_r_o_v_Inventaire` and more generally to the + to an :ref:`subsection_r_o_v_Inventaire` and more generally to the :ref:`section_ref_output_variables` and to the individual documentations of the algorithms. @@ -634,8 +635,8 @@ Saving, loading or converting calculation case commands The saving or loading of a calculation case deals with quantities and actions that are linked by the previous commands, excepted case external operations -(such as, for example, post-processing that can be developped after the -calculation cas). The registered or loaded commands remain fully compatible +(such as, for example, post-processing that can be developed after the +calculation case). The registered or loaded commands remain fully compatible with these Python external case operations. .. index:: single: load @@ -672,47 +673,54 @@ with these Python external case operations. one the commands establishing the current calculation case. Some formats are only available as input or as output. -Obtain information on the case, the computation or the system -+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ +Getting information about the case, the calculation or the system ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ -It's easy to obtain **aggregate information on the study case** as defined by -the user, by using Python's "*print*" command directly on the case, at any -stage during its completion. For example: +There are various ways to obtain global information relating to the calculation +case, the run or the system on which a case is run. -.. literalinclude:: scripts/tui_example_07.py - :language: python +*print* (*case*) + It's easy to obtain **aggregate information on the study case** as defined + by the user, by using Python's "*print*" command directly on the case, at + any stage during its construction. For example: -which result is here: + .. literalinclude:: scripts/tui_example_07.py + :language: python -.. literalinclude:: scripts/tui_example_07.res + which result is here: -.. index:: single: callinfo + .. literalinclude:: scripts/tui_example_07.res + :language: none -**Synthetic information on the number of calls to operator computations** can -be dynamically obtained with the "**callinfo()**" command. These operator -computations are those defined by the user in an ADAO case, for the observation -and evolution operators. It is used after the calculation has been performed in -the ADAO case, bearing in mind that the result of this command is simply empty -when no calculation has been performed: -:: +.. index:: single: callinfo - from adao import adaoBuilder - case = adaoBuilder.New() - ... - case.execute() - print(case.callinfo()) +**callinfo** () + A **synthesized information on the number of calls to operator + calculations** can be dynamically obtained with the "**callinfo()**" + command. These operator calculations are those defined by the user in an + ADAO case, for the observation and evolution operators. It is used after + the case calculation has been executed, bearing in mind that the result of + this command is simply empty when no calculation has been performed: + :: + + from adao import adaoBuilder + case = adaoBuilder.New() + ... + case.execute() + print(case.callinfo()) .. index:: single: sysinfo -Synthetic **system information** can be obtained with the "**sysinfo()**" -command, present in every calculation case. It dynamically returns system -information and details of Python modules useful for ADAO. It is used as -follows: -:: +**sysinfo** () + **Synthetic system information** can be obtained with the "**sysinfo()**" + command, present in every ADAO calculation case. It dynamically returns system + information and details of Python modules useful for ADAO. It is used as + follows: + :: - from adao import adaoBuilder - case = adaoBuilder.New() - print(case.sysinfo()) + from adao import adaoBuilder + case = adaoBuilder.New() + print(case.sysinfo()) .. _subsection_tui_advanced: @@ -722,6 +730,8 @@ More advanced examples of ADAO TUI calculation case We propose here more comprehensive examples of ADAO TUI calculation, by giving the purpose of the example and a set of commands that can achieve this goal. +.. _subsection_tui_advanced_ex11: + Independent holding of the results of a calculation case ++++++++++++++++++++++++++++++++++++++++++++++++++++++++ @@ -750,11 +760,127 @@ Finally, the whole problem is set and solved by the following script: The command set execution gives the following results: .. literalinclude:: scripts/tui_example_11.res + :language: none As it should be in twin experiments, when we trust mainly in observations, it is found that we get correctly the parameters that were used to artificially build the observations. +.. _subsection_tui_advanced_ex12: + +Some common numerical indicators : norm, RMS, MSE et RMSE... +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ + +The numerical quantities obtained from an ADAO calculation are often vectors +(such as the analysis :math:`\mathbf{x}^a`) or matrices (such as the analysis +covariance :math:`\mathbf{A}`). They are requested by the user through the +standard "*StoreSupplementaryCalculations*" variable of the ADAO case +algorithm. These quantities are available at each step of an iterative +algorithm, and therefore take the form of a series of vectors, or a series of +matrices. + +These objects support special methods for computing commonly used indicators. +The methods are named by the name of the indicator followed by "*s*" to note +that they apply to a series of elementary objects, and that they themselves +return a series of values. + +Note: some indicators are intended to qualify, for example, a "*value +increment*", a "*value deviation*" or a "*value difference*", rather than a +"*value*" itself. However, there is no computational impossibility to compute +indicators for any given quantity, so it's up to the user to check that the +indicator he is requesting is being used as intended. + +.. index:: single: means + +**means** () + Average of the quantity values, available at each step. + +.. index:: single: stds + +**stds** () + Standard deviation of the quantity values, available at each step. + +.. index:: single: sums + +**sums** () + Sum of the quantity values, available at each step. + +.. index:: single: mins + +**mins** () + Minimum of the quantity values, available at each step. + +.. index:: single: maxs + +**maxs** () + Maximum of the quantity values, available at each step. + +.. index:: single: norms + +**norms** (*_ord=None*) + Norm of the quantity, available at each step (*_ord*: see + *numpy.linalg.norm*). + +.. index:: single: traces + +**traces** (*offset=0*) + Trace of the quantity, available at each step (*offset*: see + *numpy.trace*). + +.. index:: single: maes +.. index:: single: Mean Absolute Error (MAE) + +**maes** (*predictor=None*) + Mean absolute error (**MAE**). This indicator is computed as the average of + the absolute deviations of the quantity from the predictor, and is + available at each step. If the predictor is not specified, this indicator + theoretically applies only to an increment or a difference. + +.. index:: single: mses +.. index:: single: msds +.. index:: single: Mean-Square Error (MSE) +.. index:: single: Mean-Square Deviation (MSD) + +**mses** (*predictor=None*) ou **msds** (*predictor=None*) + Mean square error (**MSE**) or mean-square deviation* (**MSD**). This + indicator is computed as the root-mean-square deviation of the quantity + from the predictor, and is available at each step. If the predictor is not + specified, this indicator theoretically applies only to an increment or + difference. + +.. index:: single: rmses +.. index:: single: rmsds +.. index:: single: Root-Mean-Square Error (RMSE) +.. index:: single: Root-Mean-Square Deviation (RMSD) +.. index:: single: Root-Mean-Square (RMS) + +**rmses** (*predictor=None*) or **rmsds** (*predictor=None*) + Root-mean-square error (**RMSE**) or root-mean-square deviation (**RMSD**). + This indicator is calculated as the root mean square of the deviations of + the quantity from the predictor, and is available at each step. If the + predictor is not specified, this indicator theoretically applies only to an + increment or a difference. In the latter case, it is a **RMS** of the + quantity. + +As a simple example, we can use the calculation example presented above: + +.. literalinclude:: scripts/tui_example_12.py + :language: python + +Execution of the command set gives the following results, which illustrate the +series structure of the indicators, associated with the series of values of the +incremental quantity "*InnovationAtCurrentState*" required: + +.. literalinclude:: scripts/tui_example_12.res + :language: none + +In graphical form, the indicators are displayed over all the steps: + +.. _tui_example_12: +.. image:: scripts/tui_example_12.png + :align: center + :width: 90% + .. [HOMARD] For more information on HOMARD, see the *HOMARD module* and its integrated help available from the main menu *Help* of the SALOME platform. .. [PARAVIS] For more information on PARAVIS, see the *PARAVIS module* and its integrated help available from the main menu *Help* of the SALOME platform. diff --git a/doc/fr/examples.rst b/doc/fr/examples.rst index 076f5f3..d029f51 100644 --- a/doc/fr/examples.rst +++ b/doc/fr/examples.rst @@ -71,6 +71,8 @@ Utilisations d'algorithmes orientés tâches ou études dédiées Utilisations avancées --------------------- +#. :ref:`subsection_tui_advanced_ex11` +#. :ref:`subsection_tui_advanced_ex12` #. :ref:`section_advanced_convert_JDC` #. :ref:`section_advanced_YACS_tui` #. :ref:`section_advanced_R` diff --git a/doc/fr/images/sampling_01_SampleAsnUplet.png b/doc/fr/images/sampling_01_SampleAsnUplet.png index e903025b78fab364cf80735e59cce699ee553a83..f53731c034d4601eea26d88149bd06532cf50acb 100644 GIT binary patch delta 43 ycmbPGGofaJn}VgDk&Z$}Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5Nl8JmmA-y%Vo5Nl8JmmA-y%Vo52PG*u`eo?x2PG*u`eo?x2PG*u`eo?x2PG*u`eo?x2PG*u`eo?x2PG*u`eo?x9) A7ytkO diff --git 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zW^&rS1~`o#V1*q~@(>3MwRIu<6ROB*uvbEuz&sdMMk(rk;4<8C>eML|iWYVPQlx{A zN?{&|Z=q;Y1Gtg~Owje^2U!8JbTn3248{nI#KEUog=rKa6cJY!5Y(AZbUCHBN;;+s zQ1W0e!}=98ICB?tPNUbHuZNr}(s*KDL2=g~B80e5SuFUAmo5P<)^e{C6``C;LAkW# zW&-*GpF)ab0Iu+hik?LXgSy^ngb>KNG+;L{dw?uLJAoCdGXBts1mp1q;tk-s)8Ona z0XnXQXha5lBQf(RX>)&p2H$iD!l42qYfmgHD}2g{47V&@(oA6-V+?bC)*9-=eIE_@!&9V|3taW0~`II%xi zanfjXV$f6wgljr@>D29Rw~aSId@c;RaUYwNwG|;h|=nQscUR70E zRSTLF4~9hC_E#o#oZ_49KXLw@G-(1WtZfm9AB27cv4cQ)i@+r;a^b=_iCC|AFPhOE z>nRd}db!Q*YnU&h$(oPRC^7`12rS+I$+{s21ZR?{Ml469aDtD5_oY%4>mW>Y)42NO zOFl3P3eZ32@tH>5K?sfGl;c8&jWAz00ofVZ#|CF$f~Je)U^`~|IDndfT^H_9<{d^8jtOWVFKK6_Ve%j^hMW zmgF{_&7p@0)fs9p;xiHa7Tn#V(WBXl{d+GSdin{|jIa1NY3ZBV!z_$Qvs3lH!&5O{ zvA(+P&gLaAV^&I_Jr#(w5YkN8W4Euw)XN{nUcqW()@aJL0;FjP$OtGJjj%g50*(f2 z%b)ruK=WhOsneMAvv>Wj<}V#jpFF{K1w*W*EuOtCSa9g~ie`NudQ-#zF zAnbzb>KUYyh2@%rKiUS;`bL<@kl1ifsa#AREIgrGo`*OZap@zD zB int(yyyymmddhhmm) """ __date = __date.strip() - if __date.count('/') == 2 and __date.count(':') == 0 and __date.count(' ') == 0: + if __date.count("/") == 2 and __date.count(":") == 0 and __date.count(" ") == 0: d, m, y = __date.split("/") __number = (10**4) * int(y) + (10**2) * int(m) + int(d) - elif __date.count('/') == 2 and __date.count(':') == 1 and __date.count(' ') > 0: + elif __date.count("/") == 2 and __date.count(":") == 1 and __date.count(" ") > 0: part1, part2 = __date.split() d, m, y = part1.strip().split("/") h, n = part2.strip().split(":") - __number = (10**8) * int(y) + (10**6) * int(m) + (10**4) * int(d) + (10**2) * int(h) + int(n) + __number = ( + (10**8) * int(y) + + (10**6) * int(m) + + (10**4) * int(d) + + (10**2) * int(h) + + int(n) + ) else: - raise ValueError("Cannot convert \"%s\" as a D/M/Y H:M date"%__date) + raise ValueError('Cannot convert "%s" as a D/M/Y H:M date' % __date) return __number + def vfloat(__value: numpy.ndarray): """ Conversion en flottant d'un vecteur de taille 1 et de dimensions quelconques @@ -516,9 +666,12 @@ def vfloat(__value: numpy.ndarray): elif isinstance(__value, (float, int)): return float(__value) else: - raise ValueError("Error in converting multiple float values from array when waiting for only one") + raise ValueError( + "Error in converting multiple float values from array when waiting for only one" + ) + -def strvect2liststr( __strvect ): +def strvect2liststr(__strvect): """ Fonction de secours, conversion d'une chaîne de caractères de représentation de vecteur en une liste de chaînes de caractères de @@ -530,7 +683,8 @@ def strvect2liststr( __strvect ): __strvect = __strvect.replace(st, " ") # Blanc return __strvect.split() -def strmatrix2liststr( __strvect ): + +def strmatrix2liststr(__strvect): """ Fonction de secours, conversion d'une chaîne de caractères de représentation de matrice en une liste de chaînes de caractères de @@ -541,19 +695,21 @@ def strmatrix2liststr( __strvect ): __strvect = __strvect.replace(",", " ") # Blanc for st in ("]", ")"): __strvect = __strvect.replace(st, ";") # "]" et ")" par ";" - __strvect = re.sub(r';\s*;', r';', __strvect) + __strvect = re.sub(r";\s*;", r";", __strvect) __strvect = __strvect.rstrip(";") # Après ^ et avant v __strmat = [__l.split() for __l in __strvect.split(";")] return __strmat -def checkFileNameConformity( __filename, __warnInsteadOfPrint=True ): + +def checkFileNameConformity(__filename, __warnInsteadOfPrint=True): if sys.platform.startswith("win") and len(__filename) > 256: __conform = False __msg = ( - " For some shared or older file systems on Windows, a file " + \ - "name longer than 256 characters can lead to access problems." + \ - "\n The name of the file in question is the following:" + \ - "\n %s")%(__filename,) + " For some shared or older file systems on Windows, a file " + + "name longer than 256 characters can lead to access problems." + + "\n The name of the file in question is the following:" + + "\n %s" + ) % (__filename,) if __warnInsteadOfPrint: logging.warning(__msg) else: @@ -563,19 +719,21 @@ def checkFileNameConformity( __filename, __warnInsteadOfPrint=True ): # return __conform -def checkFileNameImportability( __filename, __warnInsteadOfPrint=True ): + +def checkFileNameImportability(__filename, __warnInsteadOfPrint=True): if str(__filename).count(".") > 1: __conform = False __msg = ( - " The file name contains %i point(s) before the extension " + \ - "separator, which can potentially lead to problems when " + \ - "importing this file into Python, as it can then be recognized " + \ - "as a sub-module (generating a \"ModuleNotFoundError\"). If it " + \ - "is intentional, make sure that there is no module with the " + \ - "same name as the part before the first point, and that there is " + \ - "no \"__init__.py\" file in the same directory." + \ - "\n The name of the file in question is the following:" + \ - "\n %s")%(int(str(__filename).count(".") - 1), __filename) + " The file name contains %i point(s) before the extension " + + "separator, which can potentially lead to problems when " + + "importing this file into Python, as it can then be recognized " + + 'as a sub-module (generating a "ModuleNotFoundError"). If it ' + + "is intentional, make sure that there is no module with the " + + "same name as the part before the first point, and that there is " + + 'no "__init__.py" file in the same directory.' + + "\n The name of the file in question is the following:" + + "\n %s" + ) % (int(str(__filename).count(".") - 1), __filename) if __warnInsteadOfPrint is None: pass elif __warnInsteadOfPrint: @@ -587,30 +745,32 @@ def checkFileNameImportability( __filename, __warnInsteadOfPrint=True ): # return __conform + # ============================================================================== class SystemUsage(object): """ Permet de récupérer les différentes tailles mémoires du process courant """ + __slots__ = () # # Le module resource renvoie 0 pour les tailles mémoire. On utilise donc # plutôt : http://code.activestate.com/recipes/286222/ et Wikipedia # - _proc_status = '/proc/%d/status' % os.getpid() - _memo_status = '/proc/meminfo' + _proc_status = "/proc/%d/status" % os.getpid() + _memo_status = "/proc/meminfo" _scale = { - 'o' : 1.0, # Multiples SI de l'octet # noqa: E203 - 'ko' : 1.e3, # noqa: E203 - 'Mo' : 1.e6, # noqa: E203 - 'Go' : 1.e9, # noqa: E203 - 'kio': 1024.0, # Multiples binaires de l'octet # noqa: E203 - 'Mio': 1024.0 * 1024.0, # noqa: E203 - 'Gio': 1024.0 * 1024.0 * 1024.0, # noqa: E203 - 'B' : 1.0, # Multiples binaires du byte=octet # noqa: E203 - 'kB' : 1024.0, # noqa: E203 - 'MB' : 1024.0 * 1024.0, # noqa: E203 - 'GB' : 1024.0 * 1024.0 * 1024.0, # noqa: E203 + "o": 1.0, # Multiples SI de l'octet + "ko": 1.0e3, + "Mo": 1.0e6, + "Go": 1.0e9, + "kio": 1024.0, # Multiples binaires de l'octet + "Mio": 1024.0 * 1024.0, + "Gio": 1024.0 * 1024.0 * 1024.0, + "B": 1.0, # Multiples binaires du byte=octet + "kB": 1024.0, + "MB": 1024.0 * 1024.0, + "GB": 1024.0 * 1024.0 * 1024.0, } def __init__(self): @@ -624,33 +784,37 @@ class SystemUsage(object): v = t.read() t.close() except IOError: - return 0.0 # non-Linux? - i = v.index(VmKey) # get VmKey line e.g. 'VmRSS: 9999 kB\n ...' + return 0.0 # non-Linux? + i = v.index(VmKey) # get VmKey line e.g. 'VmRSS: 9999 kB\n ...' v = v[i:].split(None, 3) # whitespace if len(v) < 3: - return 0.0 # invalid format? + return 0.0 # invalid format? # convert Vm value to bytes mem = float(v[1]) * self._scale[v[2]] return mem / self._scale[unit] def getAvailablePhysicalMemory(self, unit="o"): "Renvoie la mémoire physique utilisable en octets" - return self._VmA('MemTotal:', unit) + return self._VmA("MemTotal:", unit) def getAvailableSwapMemory(self, unit="o"): "Renvoie la mémoire swap utilisable en octets" - return self._VmA('SwapTotal:', unit) + return self._VmA("SwapTotal:", unit) def getAvailableMemory(self, unit="o"): "Renvoie la mémoire totale (physique+swap) utilisable en octets" - return self._VmA('MemTotal:', unit) + self._VmA('SwapTotal:', unit) + return self._VmA("MemTotal:", unit) + self._VmA("SwapTotal:", unit) def getUsableMemory(self, unit="o"): """Renvoie la mémoire utilisable en octets Rq : il n'est pas sûr que ce décompte soit juste... """ - return self._VmA('MemFree:', unit) + self._VmA('SwapFree:', unit) + \ - self._VmA('Cached:', unit) + self._VmA('SwapCached:', unit) + return ( + self._VmA("MemFree:", unit) + + self._VmA("SwapFree:", unit) + + self._VmA("Cached:", unit) + + self._VmA("SwapCached:", unit) + ) def _VmB(self, VmKey, unit): "Lecture des paramètres mémoire du processus" @@ -659,34 +823,35 @@ class SystemUsage(object): v = t.read() t.close() except IOError: - return 0.0 # non-Linux? - i = v.index(VmKey) # get VmKey line e.g. 'VmRSS: 9999 kB\n ...' + return 0.0 # non-Linux? + i = v.index(VmKey) # get VmKey line e.g. 'VmRSS: 9999 kB\n ...' v = v[i:].split(None, 3) # whitespace if len(v) < 3: - return 0.0 # invalid format? + return 0.0 # invalid format? # convert Vm value to bytes mem = float(v[1]) * self._scale[v[2]] return mem / self._scale[unit] def getUsedMemory(self, unit="o"): "Renvoie la mémoire résidente utilisée en octets" - return self._VmB('VmRSS:', unit) + return self._VmB("VmRSS:", unit) def getVirtualMemory(self, unit="o"): "Renvoie la mémoire totale utilisée en octets" - return self._VmB('VmSize:', unit) + return self._VmB("VmSize:", unit) def getUsedStacksize(self, unit="o"): "Renvoie la taille du stack utilisé en octets" - return self._VmB('VmStk:', unit) + return self._VmB("VmStk:", unit) def getMaxUsedMemory(self, unit="o"): "Renvoie la mémoire résidente maximale mesurée" - return self._VmB('VmHWM:', unit) + return self._VmB("VmHWM:", unit) def getMaxVirtualMemory(self, unit="o"): "Renvoie la mémoire totale maximale mesurée" - return self._VmB('VmPeak:', unit) + return self._VmB("VmPeak:", unit) + # ============================================================================== if __name__ == "__main__": diff --git a/src/daComposant/daCore/Reporting.py b/src/daComposant/daCore/Reporting.py index 5d2af38..b5a934d 100644 --- a/src/daComposant/daCore/Reporting.py +++ b/src/daComposant/daCore/Reporting.py @@ -31,15 +31,17 @@ import os.path # ============================================================================== # Classes de services non utilisateur + class _ReportPartM__(object): """ Store and retrieve the data for C: internal class """ + __slots__ = ("__part", "__styles", "__content") def __init__(self, part="default"): - self.__part = str(part) - self.__styles = [] + self.__part = str(part) + self.__styles = [] self.__content = [] def append(self, content, style="p", position=-1): @@ -57,17 +59,19 @@ class _ReportPartM__(object): def get_content(self): return self.__content + class _ReportM__(object): """ Store and retrieve the data for C: internal class """ - __slots__ = ("__document") - def __init__(self, part='default'): + __slots__ = ("__document",) + + def __init__(self, part="default"): self.__document = {} self.__document[part] = _ReportPartM__(part) - def append(self, content, style="p", position=-1, part='default'): + def append(self, content, style="p", position=-1, part="default"): if part not in self.__document: self.__document[part] = _ReportPartM__(part) self.__document[part].append(content, style, position) @@ -86,10 +90,12 @@ class _ReportM__(object): def clear(self): self.__init__() + class __ReportC__(object): """ Get user commands, update M and V: user intertace to create the report """ + __slots__ = () # m = _ReportM__() @@ -105,11 +111,13 @@ class __ReportC__(object): def clear(self): self.m.clear() + class __ReportV__(object): """ Interact with user and C: template for reports """ - __slots__ = ("c") + + __slots__ = ("c",) # default_filename = "report.txt" @@ -122,7 +130,7 @@ class __ReportV__(object): _filename = os.path.abspath(filename) # _inside = self.get() - fid = open(_filename, 'w') + fid = open(_filename, "w") fid.write(_inside) fid.close() return filename, _filename @@ -137,14 +145,17 @@ class __ReportV__(object): del self.c return 0 + # ============================================================================== # Classes d'interface utilisateur : ReportViewIn*, ReportStorage # Tags de structure : (title, h1, h2, h3, p, uli, oli, , ) + class ReportViewInHtml(__ReportV__): """ Report in HTML """ + __slots__ = () # default_filename = "report.html" @@ -164,7 +175,11 @@ class ReportViewInHtml(__ReportV__): try: ii = ps.index("title") title = pc[ii] - pg += "%s\n%s\n%s"%('

', title, '

') + pg += "%s\n%s\n%s" % ( + '

', + title, + "

", + ) except Exception: pass for ip, sp in enumerate(ps): @@ -186,14 +201,16 @@ class ReportViewInHtml(__ReportV__): for tp in self.tags: if sp == tp: sp = self.tags[tp] - pg += "\n<%s>%s"%(sp, cp, sp) + pg += "\n<%s>%s" % (sp, cp, sp) pg += "\n\n" return pg + class ReportViewInRst(__ReportV__): """ Report in RST """ + __slots__ = () # default_filename = "report.rst" @@ -223,7 +240,7 @@ class ReportViewInRst(__ReportV__): try: ii = ps.index("title") title = pc[ii] - pg += "%s\n%s\n%s"%("=" * 80, title, "=" * 80) + pg += "%s\n%s\n%s" % ("=" * 80, title, "=" * 80) except Exception: pass for ip, sp in enumerate(ps): @@ -243,16 +260,22 @@ class ReportViewInRst(__ReportV__): for tp in self.translation: cp = cp.replace(tp, self.translation[tp]) if sp in self.titles.keys(): - pg += "\n%s\n%s\n%s"%(self.titles[sp][0] * len(cp), cp, self.titles[sp][1] * len(cp)) + pg += "\n%s\n%s\n%s" % ( + self.titles[sp][0] * len(cp), + cp, + self.titles[sp][1] * len(cp), + ) elif sp in self.tags.keys(): - pg += "%s%s%s"%(self.tags[sp][0], cp, self.tags[sp][1]) + pg += "%s%s%s" % (self.tags[sp][0], cp, self.tags[sp][1]) pg += "\n" return pg + class ReportViewInPlainTxt(__ReportV__): """ Report in plain TXT """ + # __slots__ = () # @@ -283,7 +306,7 @@ class ReportViewInPlainTxt(__ReportV__): try: ii = ps.index("title") title = pc[ii] - pg += "%s\n%s\n%s"%("=" * 80, title, "=" * 80) + pg += "%s\n%s\n%s" % ("=" * 80, title, "=" * 80) except Exception: pass for ip, sp in enumerate(ps): @@ -299,12 +322,17 @@ class ReportViewInPlainTxt(__ReportV__): for tp in self.translation: cp = cp.replace(tp, self.translation[tp]) if sp in self.titles.keys(): - pg += "\n%s\n%s\n%s"%(self.titles[sp][0] * len(cp), cp, -self.titles[sp][1] * len(cp)) + pg += "\n%s\n%s\n%s" % ( + self.titles[sp][0] * len(cp), + cp, + -self.titles[sp][1] * len(cp), + ) elif sp in self.tags.keys(): - pg += "\n%s%s%s"%(self.tags[sp][0], cp, self.tags[sp][1]) + pg += "\n%s%s%s" % (self.tags[sp][0], cp, self.tags[sp][1]) pg += "\n" return pg + # Interface utilisateur de stockage des informations ReportStorage = __ReportC__ diff --git a/src/daComposant/daCore/Templates.py b/src/daComposant/daCore/Templates.py index b14072b..54b4253 100644 --- a/src/daComposant/daCore/Templates.py +++ b/src/daComposant/daCore/Templates.py @@ -29,32 +29,36 @@ __all__ = ["ObserverTemplates"] import numpy + # ============================================================================== class TemplateStorage(object): """ Classe générale de stockage de type dictionnaire étendu (Template) """ + __slots__ = ("__preferedLanguage", "__values", "__order") - def __init__( self, language = "fr_FR" ): + def __init__(self, language="fr_FR"): self.__preferedLanguage = language - self.__values = {} - self.__order = -1 + self.__values = {} + self.__order = -1 - def store( self, name = None, content = None, fr_FR = "", en_EN = "", order = "next" ): + def store(self, name=None, content=None, fr_FR="", en_EN="", order="next"): "D.store(k, c, fr_FR, en_EN, o) -> Store template k and its main characteristics" if name is None or content is None: - raise ValueError("To be consistent, the storage of a template must provide a name and a content.") + raise ValueError( + "To be consistent, the storage of a template must provide a name and a content." + ) if order == "next": self.__order += 1 else: self.__order = int(order) self.__values[str(name)] = { - 'content': str(content), - 'fr_FR' : str(fr_FR), # noqa: E203 - 'en_EN' : str(en_EN), # noqa: E203 - 'order' : int(self.__order), # noqa: E203 + "content": str(content), + "fr_FR": str(fr_FR), + "en_EN": str(en_EN), + "order": int(self.__order), } def keys(self): @@ -70,11 +74,11 @@ class TemplateStorage(object): "x.__len__() <==> len(x)" return len(self.__values) - def __getitem__(self, name=None ): + def __getitem__(self, name=None): "x.__getitem__(y) <==> x[y]" - return self.__values[name]['content'] + return self.__values[name]["content"] - def getdoc(self, name = None, lang = "fr_FR"): + def getdoc(self, name=None, lang="fr_FR"): "D.getdoc(k, l) -> Return documentation of key k in language l" if lang not in self.__values[name]: lang = self.__preferedLanguage @@ -84,247 +88,248 @@ class TemplateStorage(object): "D.keys_in_presentation_order() -> list of D's keys in presentation order" __orders = [] for ik in self.keys(): - __orders.append( self.__values[ik]['order'] ) + __orders.append(self.__values[ik]["order"]) __reorder = numpy.array(__orders).argsort() return (numpy.array(self.keys())[__reorder]).tolist() + # ============================================================================== ObserverTemplates = TemplateStorage() ObserverTemplates.store( - name = "ValuePrinter", - content = """print(str(info)+" "+str(var[-1]))""", - fr_FR = "Imprime sur la sortie standard la valeur courante de la variable", - en_EN = "Print on standard output the current value of the variable", - order = "next", + name="ValuePrinter", + content="""print(str(info)+" "+str(var[-1]))""", + fr_FR="Imprime sur la sortie standard la valeur courante de la variable", + en_EN="Print on standard output the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueAndIndexPrinter", - content = """print(str(info)+(" index %i:"%(len(var)-1))+" "+str(var[-1]))""", - fr_FR = "Imprime sur la sortie standard la valeur courante de la variable, en ajoutant son index", - en_EN = "Print on standard output the current value of the variable, adding its index", - order = "next", + name="ValueAndIndexPrinter", + content="""print(str(info)+(" index %i:"%(len(var)-1))+" "+str(var[-1]))""", + fr_FR="Imprime sur la sortie standard la valeur courante de la variable, en ajoutant son index", + en_EN="Print on standard output the current value of the variable, adding its index", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinter", - content = """print(str(info)+" "+str(var[:]))""", - fr_FR = "Imprime sur la sortie standard la série des valeurs de la variable", - en_EN = "Print on standard output the value series of the variable", - order = "next", + name="ValueSeriePrinter", + content="""print(str(info)+" "+str(var[:]))""", + fr_FR="Imprime sur la sortie standard la série des valeurs de la variable", + en_EN="Print on standard output the value series of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueSaver", - content = """import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", - fr_FR = "Enregistre la valeur courante de la variable dans un fichier du répertoire '/tmp' nommé 'value...txt' selon le nom de la variable et l'étape d'enregistrement", - en_EN = "Save the current value of the variable in a file of the '/tmp' directory named 'value...txt' from the variable name and the saving step", - order = "next", + name="ValueSaver", + content="""import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", + fr_FR="Enregistre la valeur courante de la variable dans un fichier du répertoire '/tmp' nommé 'value...txt' selon le nom de la variable et l'étape d'enregistrement", + en_EN="Save the current value of the variable in a file of the '/tmp' directory named 'value...txt' from the variable name and the saving step", + order="next", ) ObserverTemplates.store( - name = "ValueSerieSaver", - content = """import numpy, re\nv=numpy.array(var[:], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", - fr_FR = "Enregistre la série des valeurs de la variable dans un fichier du répertoire '/tmp' nommé 'value...txt' selon le nom de la variable et l'étape", - en_EN = "Save the value series of the variable in a file of the '/tmp' directory named 'value...txt' from the variable name and the saving step", - order = "next", + name="ValueSerieSaver", + content="""import numpy, re\nv=numpy.array(var[:], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", + fr_FR="Enregistre la série des valeurs de la variable dans un fichier du répertoire '/tmp' nommé 'value...txt' selon le nom de la variable et l'étape", + en_EN="Save the value series of the variable in a file of the '/tmp' directory named 'value...txt' from the variable name and the saving step", + order="next", ) ObserverTemplates.store( - name = "ValuePrinterAndSaver", - content = """import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nprint(str(info)+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", - fr_FR = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur courante de la variable", - en_EN = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the current value of the variable", - order = "next", + name="ValuePrinterAndSaver", + content="""import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nprint(str(info)+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", + fr_FR="Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur courante de la variable", + en_EN="Print on standard output and, in the same time save in a file of the '/tmp' directory, the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueIndexPrinterAndSaver", - content = """import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nprint(str(info)+(" index %i:"%(len(var)-1))+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", - fr_FR = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur courante de la variable, en ajoutant son index", - en_EN = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the current value of the variable, adding its index", - order = "next", + name="ValueIndexPrinterAndSaver", + content="""import numpy, re\nv=numpy.array(var[-1], ndmin=1)\nprint(str(info)+(" index %i:"%(len(var)-1))+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", + fr_FR="Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur courante de la variable, en ajoutant son index", + en_EN="Print on standard output and, in the same time save in a file of the '/tmp' directory, the current value of the variable, adding its index", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinterAndSaver", - content = """import numpy, re\nv=numpy.array(var[:], ndmin=1)\nprint(str(info)+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", - fr_FR = "Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp', la série des valeurs de la variable", - en_EN = "Print on standard output and, in the same time, save in a file of the '/tmp' directory, the value series of the variable", - order = "next", + name="ValueSeriePrinterAndSaver", + content="""import numpy, re\nv=numpy.array(var[:], ndmin=1)\nprint(str(info)+" "+str(v))\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)""", + fr_FR="Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp', la série des valeurs de la variable", + en_EN="Print on standard output and, in the same time, save in a file of the '/tmp' directory, the value series of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueGnuPlotter", - content = """import numpy, Gnuplot\nv=numpy.array(var[-1], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Affiche graphiquement avec Gnuplot la valeur courante de la variable (affichage persistant)", - en_EN = "Graphically plot with Gnuplot the current value of the variable (persistent plot)", - order = "next", + name="ValueGnuPlotter", + content="""import numpy, Gnuplot\nv=numpy.array(var[-1], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Affiche graphiquement avec Gnuplot la valeur courante de la variable (affichage persistant)", + en_EN="Graphically plot with Gnuplot the current value of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueSerieGnuPlotter", - content = """import numpy, Gnuplot\nv=numpy.array(var[:], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Affiche graphiquement avec Gnuplot la série des valeurs de la variable (affichage persistant)", - en_EN = "Graphically plot with Gnuplot the value series of the variable (persistent plot)", - order = "next", + name="ValueSerieGnuPlotter", + content="""import numpy, Gnuplot\nv=numpy.array(var[:], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Affiche graphiquement avec Gnuplot la série des valeurs de la variable (affichage persistant)", + en_EN="Graphically plot with Gnuplot the value series of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValuePrinterAndGnuPlotter", - content = """print(str(info)+' '+str(var[-1]))\nimport numpy, Gnuplot\nv=numpy.array(var[-1], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Imprime sur la sortie standard et, en même temps, affiche graphiquement avec Gnuplot la valeur courante de la variable (affichage persistant)", - en_EN = "Print on standard output and, in the same time, graphically plot with Gnuplot the current value of the variable (persistent plot)", - order = "next", + name="ValuePrinterAndGnuPlotter", + content="""print(str(info)+' '+str(var[-1]))\nimport numpy, Gnuplot\nv=numpy.array(var[-1], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Imprime sur la sortie standard et, en même temps, affiche graphiquement avec Gnuplot la valeur courante de la variable (affichage persistant)", + en_EN="Print on standard output and, in the same time, graphically plot with Gnuplot the current value of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinterAndGnuPlotter", - content = """print(str(info)+' '+str(var[:]))\nimport numpy, Gnuplot\nv=numpy.array(var[:], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Imprime sur la sortie standard et, en même temps, affiche graphiquement avec Gnuplot la série des valeurs de la variable (affichage persistant)", - en_EN = "Print on standard output and, in the same time, graphically plot with Gnuplot the value series of the variable (persistent plot)", - order = "next", + name="ValueSeriePrinterAndGnuPlotter", + content="""print(str(info)+' '+str(var[:]))\nimport numpy, Gnuplot\nv=numpy.array(var[:], ndmin=1)\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Imprime sur la sortie standard et, en même temps, affiche graphiquement avec Gnuplot la série des valeurs de la variable (affichage persistant)", + en_EN="Print on standard output and, in the same time, graphically plot with Gnuplot the value series of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValuePrinterSaverAndGnuPlotter", - content = """print(str(info)+' '+str(var[-1]))\nimport numpy, re\nv=numpy.array(var[-1], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)\nimport Gnuplot\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp' et affiche graphiquement la valeur courante de la variable (affichage persistant)", - en_EN = "Print on standard output and, in the same, time save in a file of the '/tmp' directory and graphically plot the current value of the variable (persistent plot)", - order = "next", + name="ValuePrinterSaverAndGnuPlotter", + content="""print(str(info)+' '+str(var[-1]))\nimport numpy, re\nv=numpy.array(var[-1], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)\nimport Gnuplot\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp' et affiche graphiquement la valeur courante de la variable (affichage persistant)", + en_EN="Print on standard output and, in the same, time save in a file of the '/tmp' directory and graphically plot the current value of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinterSaverAndGnuPlotter", - content = """print(str(info)+' '+str(var[:]))\nimport numpy, re\nv=numpy.array(var[:], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)\nimport Gnuplot\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", - fr_FR = "Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp' et affiche graphiquement la série des valeurs de la variable (affichage persistant)", - en_EN = "Print on standard output and, in the same, time save in a file of the '/tmp' directory and graphically plot the value series of the variable (persistent plot)", - order = "next", + name="ValueSeriePrinterSaverAndGnuPlotter", + content="""print(str(info)+' '+str(var[:]))\nimport numpy, re\nv=numpy.array(var[:], ndmin=1)\nglobal istep\ntry:\n istep+=1\nexcept:\n istep=0\nf='/tmp/value_%s_%05i.txt'%(info,istep)\nf=re.sub(r'\\s','_',f)\nprint('Value saved in \"%s\"'%f)\nnumpy.savetxt(f,v)\nimport Gnuplot\nglobal igfig, gp\ntry:\n igfig+=1\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\nexcept:\n igfig=0\n gp=Gnuplot.Gnuplot(persist=1)\n gp('set title \"%s (Figure %i)\"'%(info,igfig))\n gp('set style data lines')\n gp('set xlabel \"Step\"')\n gp('set ylabel \"Variable\"')\ngp.plot( Gnuplot.Data( v, with_='lines lw 2' ) )""", + fr_FR="Imprime sur la sortie standard et, en même temps, enregistre dans un fichier du répertoire '/tmp' et affiche graphiquement la série des valeurs de la variable (affichage persistant)", + en_EN="Print on standard output and, in the same, time save in a file of the '/tmp' directory and graphically plot the value series of the variable (persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueMatPlotter", - content = """import numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la valeur courante de la variable (affichage non persistant)", - en_EN = "Graphically plot with Matplolib the current value of the variable (non persistent plot)", - order = "next", + name="ValueMatPlotter", + content="""import numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la valeur courante de la variable (affichage non persistant)", + en_EN="Graphically plot with Matplolib the current value of the variable (non persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueMatPlotterSaver", - content = """import numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la valeur courante de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", - en_EN = "Graphically plot with Matplolib the current value of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", - order = "next", + name="ValueMatPlotterSaver", + content="""import numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la valeur courante de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", + en_EN="Graphically plot with Matplolib the current value of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", + order="next", ) ObserverTemplates.store( - name = "ValueSerieMatPlotter", - content = """import numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la série des valeurs de la variable (affichage non persistant)", - en_EN = "Graphically plot with Matplolib the value series of the variable (non persistent plot)", - order = "next", + name="ValueSerieMatPlotter", + content="""import numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la série des valeurs de la variable (affichage non persistant)", + en_EN="Graphically plot with Matplolib the value series of the variable (non persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueSerieMatPlotterSaver", - content = """import numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la série des valeurs de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", - en_EN = "Graphically plot with Matplolib the value series of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", - order = "next", + name="ValueSerieMatPlotterSaver", + content="""import numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la série des valeurs de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", + en_EN="Graphically plot with Matplolib the value series of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", + order="next", ) ObserverTemplates.store( - name = "ValuePrinterAndMatPlotter", - content = """print(str(info)+' '+str(var[-1]))\nimport numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la valeur courante de la variable (affichage non persistant)", - en_EN = "Graphically plot with Matplolib the current value of the variable (non persistent plot)", - order = "next", + name="ValuePrinterAndMatPlotter", + content="""print(str(info)+' '+str(var[-1]))\nimport numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la valeur courante de la variable (affichage non persistant)", + en_EN="Graphically plot with Matplolib the current value of the variable (non persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValuePrinterAndMatPlotterSaver", - content = """print(str(info)+' '+str(var[-1]))\nimport numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la valeur courante de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", - en_EN = "Graphically plot with Matplolib the current value of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", - order = "next", + name="ValuePrinterAndMatPlotterSaver", + content="""print(str(info)+' '+str(var[-1]))\nimport numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[-1], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la valeur courante de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", + en_EN="Graphically plot with Matplolib the current value of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinterAndMatPlotter", - content = """print(str(info)+' '+str(var[:]))\nimport numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la série des valeurs de la variable (affichage non persistant)", - en_EN = "Graphically plot with Matplolib the value series of the variable (non persistent plot)", - order = "next", + name="ValueSeriePrinterAndMatPlotter", + content="""print(str(info)+' '+str(var[:]))\nimport numpy\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la série des valeurs de la variable (affichage non persistant)", + en_EN="Graphically plot with Matplolib the value series of the variable (non persistent plot)", + order="next", ) ObserverTemplates.store( - name = "ValueSeriePrinterAndMatPlotterSaver", - content = """print(str(info)+' '+str(var[:]))\nimport numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", - fr_FR = "Affiche graphiquement avec Matplolib la série des valeurs de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", - en_EN = "Graphically plot with Matplolib the value series of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", - order = "next", + name="ValueSeriePrinterAndMatPlotterSaver", + content="""print(str(info)+' '+str(var[:]))\nimport numpy, re\nimport matplotlib.pyplot as plt\nv=numpy.array(var[:], ndmin=1)\nglobal imfig, mp, ax\nplt.ion()\ntry:\n imfig+=1\n mp.suptitle('%s (Figure %i)'%(info,imfig))\nexcept:\n imfig=0\n mp = plt.figure()\n ax = mp.add_subplot(1, 1, 1)\n mp.suptitle('%s (Figure %i)'%(info,imfig))\n ax.set_xlabel('Step')\n ax.set_ylabel('Variable')\nax.plot(v)\nf='/tmp/figure_%s_%05i.pdf'%(info,imfig)\nf=re.sub(r'\\s','_',f)\nplt.savefig(f)\nplt.show()""", + fr_FR="Affiche graphiquement avec Matplolib la série des valeurs de la variable, et enregistre la figure dans un fichier du répertoire '/tmp' (figure persistante)", + en_EN="Graphically plot with Matplolib the value series of the variable, and save the figure in a file of the '/tmp' directory (persistant figure)", + order="next", ) ObserverTemplates.store( - name = "ValueMean", - content = """import numpy\nprint(str(info)+' '+str(numpy.nanmean(var[-1])))""", - fr_FR = "Imprime sur la sortie standard la moyenne de la valeur courante de la variable", - en_EN = "Print on standard output the mean of the current value of the variable", - order = "next", + name="ValueMean", + content="""import numpy\nprint(str(info)+' '+str(numpy.nanmean(var[-1])))""", + fr_FR="Imprime sur la sortie standard la moyenne de la valeur courante de la variable", + en_EN="Print on standard output the mean of the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueStandardError", - content = """import numpy\nprint(str(info)+' '+str(numpy.nanstd(var[-1])))""", - fr_FR = "Imprime sur la sortie standard l'écart-type de la valeur courante de la variable", - en_EN = "Print on standard output the standard error of the current value of the variable", - order = "next", + name="ValueStandardError", + content="""import numpy\nprint(str(info)+' '+str(numpy.nanstd(var[-1])))""", + fr_FR="Imprime sur la sortie standard l'écart-type de la valeur courante de la variable", + en_EN="Print on standard output the standard error of the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueVariance", - content = """import numpy\nprint(str(info)+' '+str(numpy.nanvar(var[-1])))""", - fr_FR = "Imprime sur la sortie standard la variance de la valeur courante de la variable", - en_EN = "Print on standard output the variance of the current value of the variable", - order = "next", + name="ValueVariance", + content="""import numpy\nprint(str(info)+' '+str(numpy.nanvar(var[-1])))""", + fr_FR="Imprime sur la sortie standard la variance de la valeur courante de la variable", + en_EN="Print on standard output the variance of the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueL2Norm", - content = """import numpy\nv = numpy.ravel( var[-1] )\nprint(str(info)+' '+str(float( numpy.linalg.norm(v) )))""", - fr_FR = "Imprime sur la sortie standard la norme L2 de la valeur courante de la variable", - en_EN = "Print on standard output the L2 norm of the current value of the variable", - order = "next", + name="ValueL2Norm", + content="""import numpy\nv = numpy.ravel( var[-1] )\nprint(str(info)+' '+str(float( numpy.linalg.norm(v) )))""", + fr_FR="Imprime sur la sortie standard la norme L2 de la valeur courante de la variable", + en_EN="Print on standard output the L2 norm of the current value of the variable", + order="next", ) ObserverTemplates.store( - name = "ValueRMS", - content = """import numpy\nv = numpy.ravel( var[-1] )\nprint(str(info)+' '+str(float( numpy.sqrt((1./v.size)*numpy.dot(v,v)) )))""", - fr_FR = "Imprime sur la sortie standard la racine de la moyenne des carrés (RMS), ou moyenne quadratique, de la valeur courante de la variable", - en_EN = "Print on standard output the root mean square (RMS), or quadratic mean, of the current value of the variable", - order = "next", + name="ValueRMS", + content="""import numpy\nv = numpy.ravel( var[-1] )\nprint(str(info)+' '+str(float( numpy.sqrt((1./v.size)*numpy.dot(v,v)) )))""", + fr_FR="Imprime sur la sortie standard la racine de la moyenne des carrés (RMS), ou moyenne quadratique, de la valeur courante de la variable", + en_EN="Print on standard output the root mean square (RMS), or quadratic mean, of the current value of the variable", + order="next", ) # ============================================================================== UserPostAnalysisTemplates = TemplateStorage() UserPostAnalysisTemplates.store( - name = "AnalysisPrinter", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)""", - fr_FR = "Imprime sur la sortie standard la valeur optimale", - en_EN = "Print on standard output the optimal value", - order = "next", + name="AnalysisPrinter", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)""", + fr_FR="Imprime sur la sortie standard la valeur optimale", + en_EN="Print on standard output the optimal value", + order="next", ) UserPostAnalysisTemplates.store( - name = "AnalysisSaver", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", - fr_FR = "Enregistre la valeur optimale dans un fichier du répertoire '/tmp' nommé 'analysis.txt'", - en_EN = "Save the optimal value in a file of the '/tmp' directory named 'analysis.txt'", - order = "next", + name="AnalysisSaver", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", + fr_FR="Enregistre la valeur optimale dans un fichier du répertoire '/tmp' nommé 'analysis.txt'", + en_EN="Save the optimal value in a file of the '/tmp' directory named 'analysis.txt'", + order="next", ) UserPostAnalysisTemplates.store( - name = "AnalysisPrinterAndSaver", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", - fr_FR = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur optimale", - en_EN = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value", - order = "next", + name="AnalysisPrinterAndSaver", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", + fr_FR="Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur optimale", + en_EN="Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value", + order="next", ) UserPostAnalysisTemplates.store( - name = "AnalysisSeriePrinter", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)""", - fr_FR = "Imprime sur la sortie standard la série des valeurs optimales", - en_EN = "Print on standard output the optimal value series", - order = "next", + name="AnalysisSeriePrinter", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)""", + fr_FR="Imprime sur la sortie standard la série des valeurs optimales", + en_EN="Print on standard output the optimal value series", + order="next", ) UserPostAnalysisTemplates.store( - name = "AnalysisSerieSaver", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", - fr_FR = "Enregistre la série des valeurs optimales dans un fichier du répertoire '/tmp' nommé 'analysis.txt'", - en_EN = "Save the optimal value series in a file of the '/tmp' directory named 'analysis.txt'", - order = "next", + name="AnalysisSerieSaver", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", + fr_FR="Enregistre la série des valeurs optimales dans un fichier du répertoire '/tmp' nommé 'analysis.txt'", + en_EN="Save the optimal value series in a file of the '/tmp' directory named 'analysis.txt'", + order="next", ) UserPostAnalysisTemplates.store( - name = "AnalysisSeriePrinterAndSaver", - content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", - fr_FR = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la série des valeurs optimales", - en_EN = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value series", - order = "next", + name="AnalysisSeriePrinterAndSaver", + content="""print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""", + fr_FR="Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la série des valeurs optimales", + en_EN="Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value series", + order="next", ) # ============================================================================== diff --git a/src/daComposant/daNumerics/Models/Lorenz1963.py b/src/daComposant/daNumerics/Models/Lorenz1963.py new file mode 100644 index 0000000..8c8a774 --- /dev/null +++ b/src/daComposant/daNumerics/Models/Lorenz1963.py @@ -0,0 +1,106 @@ +# -*- coding: utf-8 -*- +# +# Copyright (C) 2008-2024 EDF R&D +# +# This library is free software; you can redistribute it and/or +# modify it under the terms of the GNU Lesser General Public +# License as published by the Free Software Foundation; either +# version 2.1 of the License. +# +# This library is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +# Lesser General Public License for more details. +# +# You should have received a copy of the GNU Lesser General Public +# License along with this library; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA +# +# See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com +# +# Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D + +import sys +import unittest +import math +import numpy +from daCore.BasicObjects import DynamicalSimulator + + +# ============================================================================== +class Lorenz1963(DynamicalSimulator): + """ + Three-dimensional parametrized nonlinear ODE system depending on µ=(σ,ρ,β): + + ∂x/∂t = σ (y − x) + ∂y/∂t = ρ x − y − x z + ∂z/∂t = x y − β z + + with t ∈ [0, 40] the time interval, x(t), y(t), z(t) the dependent + variables, and with σ=10, ρ=28, and β=8/3 the commonly used parameter + values. The initial conditions for (x, y, z) at t=0 for the reference + case are (0, 1, 0). + + This is the well known parametrized coupled system of three nonlinear + ordinary differential equations: + Lorenz, E. N. (1963). Deterministic nonperiodic flow. Journal of the + Atmospheric Sciences, 20, 130–141. + doi:10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2 + """ + + def set_canonical_description(self): + self.set_mu((10.0, 28.0, 8.0 / 3.0)) # µ = (σ, ρ, β) + self.set_integrator("rk4") + self.set_dt(0.01) + self.set_t0(0.0) + self.set_tf(40) + self.set_y0((0.0, 1.0, 0.0)) + self.set_autonomous(True) + return True + + def ODEModel(self, t, Y): + "ODE dY/dt = F(Y,t)" + sigma, rho, beta = self.set_mu() + x, y, z = map(float, Y) + # + rx = sigma * (y - x) + ry = x * rho - y - x * z + rz = x * y - beta * z + # + return numpy.array([rx, ry, rz]) + + +# ============================================================================== +class LocalTest(unittest.TestCase): + @classmethod + def setUpClass(cls): + print("\nAUTODIAGNOSTIC\n==============\n") + print(" " + Lorenz1963().__doc__.strip()) + + def test001(self): + numpy.random.seed(123456789) + ODE = Lorenz1963() # Default parameters + trajectory = ODE.ForecastedPath() + # + print() + self.assertTrue(trajectory.shape[0] == 1 + int(ODE.set_tf() / ODE.set_dt())) + self.assertTrue( + abs( + max( + trajectory[-1] + - numpy.array([16.48799962, 14.01693428, 40.30448848]) + ) + ) + <= 1.0e-8, + msg=" Last value is not equal to the reference one", + ) + print(" Last value is equal to the reference one") + + def tearDown(cls): + print("\n Tests are finished\n") + + +# ============================================================================== +if __name__ == "__main__": + sys.stderr = sys.stdout + unittest.main(verbosity=0) diff --git a/src/daComposant/daNumerics/Models/TwoDimensionalInverseDistanceCS2010.py b/src/daComposant/daNumerics/Models/TwoDimensionalInverseDistanceCS2010.py index 052d3eb..08ef395 100644 --- a/src/daComposant/daNumerics/Models/TwoDimensionalInverseDistanceCS2010.py +++ b/src/daComposant/daNumerics/Models/TwoDimensionalInverseDistanceCS2010.py @@ -20,7 +20,10 @@ # # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D -import sys, unittest, numpy +import sys +import unittest +import numpy + # ============================================================================== class TwoDimensionalInverseDistanceCS2010: @@ -36,19 +39,20 @@ class TwoDimensionalInverseDistanceCS2010: Nonlinear Model Reduction via Discrete Empirical Interpolation, SIAM Journal on Scientific Computing, 32(5), pp. 2737-2764 (2010). """ + def __init__(self, nx: int = 20, ny: int = 20): "Définition du maillage spatial" - self.nx = max(1, nx) - self.ny = max(1, ny) - self.x = numpy.linspace(0.1, 0.9, self.nx, dtype=float) - self.y = numpy.linspace(0.1, 0.9, self.ny, dtype=float) + self.nx = max(1, nx) + self.ny = max(1, ny) + self.x = numpy.linspace(0.1, 0.9, self.nx, dtype=float) + self.y = numpy.linspace(0.1, 0.9, self.ny, dtype=float) - def FieldG(self, mu ): + def FieldG(self, mu): "Fonction simulation pour un paramètre donné" - mu1, mu2 = numpy.ravel( mu ) + mu1, mu2 = numpy.ravel(mu) # - x, y = numpy.meshgrid( self.x, self.y ) - sxymu = 1. / numpy.sqrt( (x - mu1)**2 + (y - mu2)**2 + 0.1**2 ) + x, y = numpy.meshgrid(self.x, self.y) + sxymu = 1.0 / numpy.sqrt((x - mu1) ** 2 + (y - mu2) ** 2 + 0.1**2) # return sxymu @@ -83,18 +87,19 @@ class TwoDimensionalInverseDistanceCS2010: OneRealisation = FieldG + # ============================================================================== class LocalTest(unittest.TestCase): @classmethod def setUpClass(cls): - print('\nAUTODIAGNOSTIC\n==============\n') + print("\nAUTODIAGNOSTIC\n==============\n") print(" " + TwoDimensionalInverseDistanceCS2010().__doc__.strip()) def test001(self): numpy.random.seed(123456789) Equation = TwoDimensionalInverseDistanceCS2010() for mu in Equation.get_sample_of_mu(5, 5): - solution = Equation.OneRealisation( mu ) + solution = Equation.OneRealisation(mu) # Nappe maximale au coin (0,0) self.assertTrue(numpy.max(solution.flat) <= solution[0, 0]) # Nappe minimale au coin [-1,-1] @@ -103,6 +108,7 @@ class LocalTest(unittest.TestCase): def tearDown(cls): print("\n Tests OK\n") + # ============================================================================== if __name__ == "__main__": sys.stderr = sys.stdout diff --git a/src/daComposant/daNumerics/Models/TwoDimensionalRosenbrockFunctionR1960.py b/src/daComposant/daNumerics/Models/TwoDimensionalRosenbrockFunctionR1960.py index 7f7b27a..655f757 100644 --- a/src/daComposant/daNumerics/Models/TwoDimensionalRosenbrockFunctionR1960.py +++ b/src/daComposant/daNumerics/Models/TwoDimensionalRosenbrockFunctionR1960.py @@ -20,7 +20,11 @@ # # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D -import sys, unittest, math, numpy +import sys +import unittest +import math +import numpy + # ============================================================================== class TwoDimensionalRosenbrockFunctionR1960: @@ -29,33 +33,35 @@ class TwoDimensionalRosenbrockFunctionR1960: f(x,y) = (a - x)² + b (y -x²)² - with (x,y) ∈ [-2,2]x[-1,3]² and usually a=1, b=100. There is a - global minimum at (x,y) = (a,a²) for which f(x,y) = 0. + with (x,y) ∈ [-2,2]x[-1,3]² and a=1, b=100 the commonly used parameter + values. There exists a global minimum at (x,y) = (a,a²) for which + f(x,y) = 0. This is the non-linear non-convex parametric function of the reference: Rosenbrock, H. H., An Automatic Method for Finding the Greatest or Least Value of a Function, The Computer Journal, 3(3), pp.175–184, (1960) """ + def __init__(self, nx: int = 40, ny: int = 40): "Définition du maillage spatial" - self.nx = max(1, nx) - self.ny = max(1, ny) - self.x = numpy.linspace(-2, 2, self.nx, dtype=float) - self.y = numpy.linspace(-1, 3, self.ny, dtype=float) + self.nx = max(1, nx) + self.ny = max(1, ny) + self.x = numpy.linspace(-2, 2, self.nx, dtype=float) + self.y = numpy.linspace(-1, 3, self.ny, dtype=float) - def FieldZ(self, mu ): + def FieldZ(self, mu): "Fonction simulation pour un paramètre donné" - a, b = numpy.ravel( mu ) + a, b = numpy.ravel(mu) # - x, y = numpy.meshgrid( self.x, self.y ) - sxymu = (a - x)**2 + b * (y - x**2)**2 + x, y = numpy.meshgrid(self.x, self.y) + sxymu = (a - x) ** 2 + b * (y - x**2) ** 2 # return sxymu - def FunctionH(self, xy, a = 1, b = 100): + def FunctionH(self, xy, a=1, b=100): "Construit la fonction de Rosenbrock en L2 (Scipy 1.8.1 p.1322)" - xy = numpy.ravel( xy ).reshape((-1, 2)) # Deux colonnes + xy = numpy.ravel(xy).reshape((-1, 2)) # Deux colonnes x = xy[:, 0] y = xy[:, 1] return numpy.array([(a - x), math.sqrt(b) * (y - x**2)]) @@ -91,26 +97,28 @@ class TwoDimensionalRosenbrockFunctionR1960: OneRealisation = FieldZ + # ============================================================================== class LocalTest(unittest.TestCase): @classmethod def setUpClass(cls): - print('\nAUTODIAGNOSTIC\n==============\n') + print("\nAUTODIAGNOSTIC\n==============\n") print(" " + TwoDimensionalRosenbrockFunctionR1960().__doc__.strip()) def test001(self): numpy.random.seed(123456789) Equation = TwoDimensionalRosenbrockFunctionR1960() - optimum = Equation.FunctionH( [1, 1] ) - self.assertTrue( max(optimum.flat) <= 0.) + optimum = Equation.FunctionH([1, 1]) + self.assertTrue(max(optimum.flat) <= 0.0) - optimum = Equation.FunctionH( [0.5, 0.25], a=0.5 ) - self.assertTrue( max(optimum.flat) <= 0.) + optimum = Equation.FunctionH([0.5, 0.25], a=0.5) + self.assertTrue(max(optimum.flat) <= 0.0) def tearDown(cls): print("\n Tests OK\n") + # ============================================================================== if __name__ == "__main__": sys.stderr = sys.stdout diff --git a/src/daEficas/prefs_ADAO.py.in b/src/daEficas/prefs_ADAO.py.in index 1bbcbc5..6b502f5 100644 --- a/src/daEficas/prefs_ADAO.py.in +++ b/src/daEficas/prefs_ADAO.py.in @@ -24,7 +24,7 @@ import os, sys -# print "import des prefs de Adao" +# print ("import des prefs de Adao") # # Configuration de Eficas # ======================= -- 2.39.2