Source code for openmdao.test_suite.components.paraboloid_invalid_region


import openmdao.api as om


[docs]class Paraboloid(om.ExplicitComponent): """ Evaluates the equation f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 This version of Paraboloid optionally raises an analysis error when the design variables x and y are in an invalid region defined by the specified "invalid_x" and "invalid_y" ranges. The path of evaluated points to the optmized solution is recorded as well as the number of analysis errors raised. Parameters ---------- invalid_x : tuple of float or None The range of values for x which will trigger an AnalysisError invalid_y : tuple of float or None The range of values for y which will trigger an AnalysisError func : str, 'compute' or 'compute_partials' The function that will raise the AnalysisError (compute or compute_partials). Attributes ---------- invalid_x : tuple of float or None The range of values for x which will trigger an AnalysisError invalid_y : tuple of float or None The range of values for y which will trigger an AnalysisError func : str, 'compute' or 'compute_partials' The function that will raise the AnalysisError (compute or compute_partials). """
[docs] def __init__(self, invalid_x=None, invalid_y=None, func='compute'): super().__init__() self.invalid_x = invalid_x self.invalid_y = invalid_y self.func = func self.eval_count = -1 self.eval_history = [] self.raised_eval_errors = [] self.grad_count = -1 self.grad_history = [] self.raised_grad_errors = []
[docs] def setup(self): self.add_input('x', val=0.0) self.add_input('y', val=0.0) self.add_output('f_xy', val=0.0) self.declare_partials('*', '*')
[docs] def compute(self, inputs, outputs): """ f(x,y) = (x-3)^2 + xy + (y+4)^2 - 3 """ self.eval_count += 1 x = inputs['x'] y = inputs['y'] f_xy = outputs['f_xy'] = (x-3.0)**2 + x*y + (y+4.0)**2 - 3.0 self.eval_history.append((x.item(), y.item(), f_xy.item())) if self.invalid_x and self.func == 'compute': beg, end = self.invalid_x if x > beg and x < end: self.raised_eval_errors.append(self.eval_count) raise om.AnalysisError(f'Invalid x: {beg} < {float(x):8.4f} < {end}).') if self.invalid_y and self.func == 'compute': beg, end = self.invalid_y if y > beg and y < end: self.raised_eval_errors.append(self.eval_count) raise om.AnalysisError(f'Invalid y: {beg} < {float(y):8.4f} < {end}).')
[docs] def compute_partials(self, inputs, partials): """ Partial derivatives. """ self.grad_count += 1 x = inputs['x'] y = inputs['y'] partials['f_xy', 'x'] = 2.0*x - 6.0 + y partials['f_xy', 'y'] = 2.0*y + 8.0 + x self.grad_history.append((x.item(), y.item())) if self.invalid_x and self.func == 'compute_partials': beg, end = self.invalid_x if x > beg and x < end: self.raised_grad_errors.append(self.grad_count) raise om.AnalysisError(f'Invalid x: {beg} < {float(x):8.4f} < {end}).') if self.invalid_y and self.func == 'compute_partials': beg, end = self.invalid_y if y > beg and y < end: self.raised_grad_errors.append(self.grad_count) raise om.AnalysisError(f'Invalid y: {beg} < {float(y):8.4f} < {end}).')