[OptApp] Small fix for QNBB #12262
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[OptApp] Small fix for QNBB #12262
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sunethwarna
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Apr 17, 2024
...ationApplication/python_scripts/algorithms/algorithm_momentum_relaxed_gradient_projection.py
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| def test_L2_max(self): | ||
| param = Kratos.Parameters("""{ | ||
| "type" : "l2_norm", | ||
| "max_iter" : 2, | ||
| "tolerance" : 1e-4 | ||
| }""") | ||
| algorithm_data = ComponentDataView("algorithm", self.optimization_problem) | ||
| convergence_criterium = CreateConvergenceCriteria(param, self.optimization_problem) | ||
| search_direction = KratosOA.CollectiveExpression([Kratos.Expression.ElementExpression(self.model_part)]) | ||
| KratosOA.CollectiveExpressionIO.Read(search_direction, KratosOA.CollectiveExpressionIO.PropertiesVariable(Kratos.DENSITY)) | ||
| algorithm_data.GetBufferedData()["search_direction"] = search_direction | ||
| self.assertFalse(convergence_criterium.IsConverged()) | ||
| self.optimization_problem.AdvanceStep() | ||
| algorithm_data.GetBufferedData()["search_direction"] = search_direction | ||
| self.assertFalse(convergence_criterium.IsConverged()) | ||
| self.optimization_problem.AdvanceStep() | ||
| algorithm_data.GetBufferedData()["search_direction"] = search_direction | ||
| self.assertTrue(convergence_criterium.IsConverged()) |
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I would add a test for max_iter as well
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It is a test for max iter, other one without max in the test name, it tests the expected behavior of conv. criteria
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| def test_TargetValue_max(self): | ||
| param = Kratos.Parameters("""{ | ||
| "type" : "target_value", | ||
| "max_iter" : 2, | ||
| "target_value" : 0.001 | ||
| }""") | ||
| algorithm_data = ComponentDataView("algorithm", self.optimization_problem) | ||
| convergence_criterium = CreateConvergenceCriteria(param, self.optimization_problem) | ||
| algorithm_data.GetBufferedData()["std_obj_value"] = 1 | ||
| self.assertFalse(convergence_criterium.IsConverged()) | ||
| self.optimization_problem.AdvanceStep() | ||
| algorithm_data.GetBufferedData()["std_obj_value"] = 0.1 | ||
| self.assertFalse(convergence_criterium.IsConverged()) | ||
| self.optimization_problem.AdvanceStep() | ||
| algorithm_data.GetBufferedData()["std_obj_value"] = 0.01 | ||
| self.assertTrue(convergence_criterium.IsConverged()) |
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I would add a test for max_iter
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It is a test for max iter
…/algorithm_momentum_relaxed_gradient_projection.py Co-authored-by: Suneth Warnakulasuriya <suneth.warna@gmail.com>
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@sunethwarna FSI application fails=( |
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📝 Description
Changes the QNBB max step comparison logic for QNBB to avoid small step size estimations.