merge validation to main

os-climate · Jul 17, 2024 · faf9ab7 · faf9ab7
2 parents 01e7715 + c9da378
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diff --git a/.gitignore b/.gitignore
@@ -0,0 +1,14 @@
+*.pyc
+__pycache__
+.project
+.pydevproject
+.settings/
+coverage.xml
+nosetests.xml
+.coverage
+xdsm.html
+build/
+dist/
+/.pytest_cache/
+/sostrades_optimization_plugins/tests/__pycache__/
+/sostrades_optimization_plugins/tests/.pytest_cache/
diff --git a/README.md b/README.md
@@ -0,0 +1 @@
+# sostrades-optimization-plugin
diff --git a/headers_ignore_config.json b/headers_ignore_config.json
@@ -0,0 +1,59 @@
+{
+    "extension_to_ignore": [
+        "pkl",
+        "png",
+        "jpg",
+        "csv",
+        "md",
+        "markdown",
+        "avif",
+        "json",
+        "in",
+        "gitignore",
+        "cfg",
+        "puml",
+        "pdf",
+        "txt",
+        "ipynb",
+        "zip",
+        "rst",
+        "ini",
+        "coveragerc",
+        "yaml",
+        "bat",
+        "tex",
+        "toml"
+    ],
+    "files_to_ignore": [
+        "LICENSE",
+        ".readthedocs",
+        "docs/Makefile",
+        ".flake8",
+        ".prettierignore",
+        "sostrades_optimization_plugins/models/design_var/design_var.py",
+        "sostrades_optimization_plugins/models/design_var/design_var_disc.py",
+        "sostrades_optimization_plugins/models/func_manager/func_manager.py",
+        "sostrades_optimization_plugins/models/func_manager/func_manager_disc.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_design_var/__init__.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_design_var/process.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_design_var/usecase.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager/__init__.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager/process.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager/usecase.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager_faulty/__init__.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager_faulty/process.py",
+        "sostrades_optimization_plugins/sos_processes/test/test_sellar_opt_w_func_manager_faulty/usecase.py",
+        "sostrades_optimization_plugins/tests/l0_test_14_optim_scenario_with_func_manager.py",
+        "sostrades_optimization_plugins/tests/l0_test_44_func_manager.py",
+        "sostrades_optimization_plugins/tests/l0_test_62_design_var_in_sellar.py",
+        "sostrades_optimization_plugins/tests/l1s_test_all_usecases.py",
+        "sostrades_optimization_plugins/tools/cst_manager/common_config.py",
+        "sostrades_optimization_plugins/tools/cst_manager/constraint_manager.py",
+        "sostrades_optimization_plugins/tools/cst_manager/constraint_object.py",
+        "sostrades_optimization_plugins/tools/cst_manager/database.py",
+        "sostrades_optimization_plugins/tools/cst_manager/fileutils.py",
+        "sostrades_optimization_plugins/tools/cst_manager/func_manager_common.py",
+        "sostrades_optimization_plugins/tools/cst_manager/__init__.py"
+    ],
+    "airbus_rev_commit": "d833fdf740389587b876e30f084631430687fa5a"
+}
diff --git a/platform_version_required.txt b/platform_version_required.txt
@@ -0,0 +1 @@
+v4.1.0
diff --git a/pytest.ini b/pytest.ini
@@ -0,0 +1,5 @@
+[pytest]
+python_files = l*_test*.py
+testpaths =
+  sostrades_optimization_plugins/tests
+addopts = --numprocesses=auto
diff --git a/requirements.in b/requirements.in
@@ -0,0 +1,3 @@
+numpy==1.24.4
+pandas==2.2.2
+plotly==5.3.0
diff --git a/ruff.toml b/ruff.toml
@@ -0,0 +1,13 @@
+[lint]
+select = ["I", "TCH", "PLC", "PLE", "F", "E", "W", "PERF"]
+# extend-select = ["ALL"]
+
+ignore  = ["E722", "F841", "E501", "D400", "D415", "D212", "D300", "PERF203", "ANN101"]
+# E722 Do not use bare `except`
+# F841 Local variable `xxx` is assigned to but never used
+# E501 Line too long
+# D400 First line should end with a period
+# D415 First line should end with a period, question mark, or exclamation point
+# D212 [*] Multi-line docstring summary should start at the first line
+# D300 [*] Use triple double quotes `"""`
+# ANN101 Missing type annotation for `self` in method
diff --git a/sostrades_optimization_plugins/__init__.py b/sostrades_optimization_plugins/__init__.py
@@ -0,0 +1,15 @@
+'''
+Copyright 2024 Capgemini
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+'''
diff --git a/sostrades_optimization_plugins/models/__init__.py b/sostrades_optimization_plugins/models/__init__.py
@@ -0,0 +1,15 @@
+'''
+Copyright 2024 Capgemini
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+'''
diff --git a/sostrades_optimization_plugins/models/design_var/__init__.py b/sostrades_optimization_plugins/models/design_var/__init__.py
@@ -0,0 +1,15 @@
+'''
+Copyright 2024 Capgemini
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+'''
diff --git a/sostrades_optimization_plugins/models/design_var/design_var.py b/sostrades_optimization_plugins/models/design_var/design_var.py
@@ -0,0 +1,199 @@
+'''
+Copyright 2022 Airbus SAS
+Modifications on 2023/07/25-2024/05/16 Copyright 2023 Capgemini
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+'''
+import numpy as np
+from pandas import DataFrame, concat
+from sostrades_core.execution_engine.sos_wrapp import SoSWrapp
+from sostrades_core.tools.bspline.bspline import BSpline
+
+
+class DesignVar(object):
+    """
+    Class Design variable
+    """
+    ACTIVATED_ELEM_LIST = "activated_elem"
+    VARIABLES = "variable"
+    VALUE = "value"
+    DATAFRAME_FILL = SoSWrapp.DATAFRAME_FILL
+    COLUMNS_NAMES = SoSWrapp.COLUMNS_NAMES
+    ONE_COLUMN_PER_KEY = "one column per key"  # FIXME: on 4.0.3 --> SoSWrapp.ONE_COLUMN_PER_KEY
+    ONE_COLUMN_FOR_KEY = SoSWrapp.ONE_COLUMN_FOR_KEY
+    DATAFRAME_FILL_POSSIBLE_VALUES = [ONE_COLUMN_PER_KEY, ONE_COLUMN_FOR_KEY]
+    DESIGN_SPACE = 'design_space'
+    DESIGN_VAR_DESCRIPTOR = 'design_var_descriptor'
+    INDEX = 'index'
+    INDEX_NAME = 'index_name'
+    OUT_TYPE = 'out_type'
+    OUT_NAME = 'out_name'
+    FILL_ACTIVATED_ELEMENTS = 'fill_activated_elements'
+    LAST_ELEMENT_ACTIVATED = 'last element activated'
+    INITIAL_VALUE = 'initial_value'
+    FILL_ACTIVATED_ELEMENTS_POSSIBLE_VALUES = [LAST_ELEMENT_ACTIVATED, INITIAL_VALUE]
+
+    def __init__(self, inputs_dict, logger):
+        '''
+        Constructor
+        '''
+        self.design_var_descriptor = inputs_dict[self.DESIGN_VAR_DESCRIPTOR]
+        self.output_dict = {}
+        self.bspline_dict = {}
+        self.dspace = inputs_dict[self.DESIGN_SPACE]
+        self.logger = logger
+
+    def configure(self, inputs_dict):
+        '''
+        Configure with inputs_dict from the discipline
+        '''
+
+        self.output_dict = {}
+        list_ctrl = self.design_var_descriptor.keys()
+
+        for elem in list_ctrl:
+            l_activated = self.dspace.loc[self.dspace[self.VARIABLES]
+                                          == elem, self.ACTIVATED_ELEM_LIST].to_list()[0]
+            # check output length and compute BSpline only if necessary
+            # remark: float do not require any BSpline usage
+            output_length = len(self.design_var_descriptor[elem][self.INDEX])
+            deactivated_elem_flag = not all(l_activated)
+            if deactivated_elem_flag:
+                final_value, gradient = self.rebuild_input_array_with_activated_elements(inputs_dict, elem)
+            else:
+                final_value = inputs_dict[elem]
+                gradient = np.identity(output_length)
+
+            if len(final_value) == output_length:
+                self.bspline_dict[elem] = {
+                    'bspline': None, 'eval_t': final_value, 'b_array': gradient}
+            else:
+                self.create_array_with_bspline(elem, final_value, output_length,
+                                               deactivated_elem_flag)
+
+            # loop over design_var_descriptor to build output
+            self.build_output_with_design_var_descriptor(elem, final_value)
+
+    def create_array_with_bspline(self, elem, final_value, output_length, deactivated_elem_flag):
+
+        list_t = np.linspace(0.0, 1.0, output_length)
+        bspline = BSpline(n_poles=len(final_value))
+        bspline.set_ctrl_pts(final_value)
+        eval_t, b_array = bspline.eval_list_t(list_t)
+        b_array = bspline.update_b_array(b_array)
+        if deactivated_elem_flag:
+            b_array = self.update_gradient_with_deactivated_elements_first_value(b_array)
+        self.bspline_dict[elem] = {
+            'bspline': bspline, 'eval_t': eval_t, 'b_array': b_array}
+
+    def rebuild_input_array_with_activated_elements(self, inputs_dict, elem):
+        '''
+
+        If some elements are desactivated wit the option activated_elem in design space, the function rebuild the correct array depending on the method
+
+        '''
+        # checks that dspace and activated elements are coherent with input element size
+        l_activated = self.dspace.loc[self.dspace[self.VARIABLES]
+                                      == elem, self.ACTIVATED_ELEM_LIST].to_list()[0]
+
+        elem_input_value = list(inputs_dict[elem])
+        input_length = len(elem_input_value)
+        if sum(l_activated) != input_length:
+            self.logger.error(
+                f'The size of the input element {elem} is not coherent with the design space and its activated elements : {sum(l_activated)} activated elements and elem of length {len(elem_input_value)}')
+
+        final_value = []
+        # TODO compute the gradient for each case
+        gradient = []
+        initial_gradient = np.identity(input_length).tolist()
+        # We fill deactivated elements with the last element activated in the array
+        if self.FILL_ACTIVATED_ELEMENTS in self.design_var_descriptor[elem] and self.design_var_descriptor[elem][
+            self.FILL_ACTIVATED_ELEMENTS] == self.LAST_ELEMENT_ACTIVATED:
+
+            for activated_bool in l_activated:
+                if activated_bool:
+                    gradient.append(initial_gradient.pop(0))
+                    final_value.append(elem_input_value.pop(0))
+                else:
+                    final_value.append(final_value[-1])
+                    # TODO gradient is not null but depend on last value
+                    # need to fix it
+                    gradient.append([0.] * input_length)
+        # by default we use initial value to fill the deactivated elements
+        else:
+            initial_value = self.dspace.loc[self.dspace[self.VARIABLES]
+                                            == elem, self.VALUE].to_list()[0]
+
+            for i, activated_bool in enumerate(l_activated):
+                if activated_bool:
+                    final_value.append(elem_input_value.pop(0))
+                    gradient.append(initial_gradient.pop(0))
+                else:
+                    final_value.append(initial_value[i])
+                    gradient.append([0.] * input_length)
+        return np.array(final_value), np.array(gradient)
+
+    def update_gradient_with_deactivated_elements_first_value(self, initial_gradient):
+        ### TO DO generalize it with other deactivated elements
+
+        result = np.delete(initial_gradient, 0, axis=1)
+        return result
+
+    def build_output_with_design_var_descriptor(self, elem, final_value):
+
+        out_name = self.design_var_descriptor[elem][self.OUT_NAME]
+        out_type = self.design_var_descriptor[elem][self.OUT_TYPE]
+
+        if out_type == 'float':
+            if final_value.size != 1:
+                raise ValueError(" The input must be of size 1 for a float output")
+            self.output_dict[out_name] = final_value[0]
+        elif out_type == 'array':
+            self.output_dict[out_name] = self.bspline_dict[elem]['eval_t']
+        elif out_type == 'dataframe':
+            # dataframe fill is optional ,by default we fill the dataframe with one column per key
+            if self.DATAFRAME_FILL in self.design_var_descriptor[elem]:
+                dataframe_fill = self.design_var_descriptor[elem][self.DATAFRAME_FILL]
+            else:
+                dataframe_fill = self.ONE_COLUMN_PER_KEY
+            index = self.design_var_descriptor[elem][self.INDEX]
+            index_name = self.design_var_descriptor[elem][self.INDEX_NAME]
+            if dataframe_fill == self.ONE_COLUMN_PER_KEY:
+                # for the method one column per key we create a dataframe if it does not exists
+                if self.design_var_descriptor[elem][self.OUT_NAME] not in self.output_dict.keys():
+                    # init output dataframes with index
+
+                    self.output_dict[out_name] = DataFrame({index_name: index})
+                # we use the key 'key' in the design_var_descriptor for the name of the column and the column to the dataframe
+                col_name = self.design_var_descriptor[elem]['key']
+                self.output_dict[out_name][col_name] = self.bspline_dict[elem]['eval_t']
+            elif dataframe_fill == self.ONE_COLUMN_FOR_KEY:
+
+                column_names = self.design_var_descriptor[elem][self.COLUMNS_NAMES]
+                # # create a dataframe using column_names, in this method the dataframe will ALWAYS have 2 columns
+                # first column will store the key
+                # second column the value
+
+                df_to_merge = DataFrame(
+                    {index_name: index,
+                     column_names[0]: self.design_var_descriptor[elem]['key'],
+                     column_names[1]: self.bspline_dict[elem]['eval_t']})
+                # if the dataframe still not exists werite it
+                if self.design_var_descriptor[elem][self.OUT_NAME] not in self.output_dict.keys():
+                    self.output_dict[out_name] = df_to_merge
+                    # if it exists, concatenate it in order to have multiple lines in the dataframe for each key
+                else:
+                    self.output_dict[out_name] = concat([self.output_dict[out_name], df_to_merge],
+                                                        ignore_index=True)
+        else:
+            raise (ValueError('Output type not yet supported'))