ddca7f56ce7a154c2284d6464cf872a1f4992f3d,skopt/optimizer/optimizer.py,Optimizer,__init__,#Optimizer#,154

Before Change

        self._initial_point_generator = cook_initial_point_generator(
            initial_point_generator)

        if self._initial_point_generator is not None:
            transformer = self.space.get_transformer()
            self._initial_samples = self._initial_point_generator.generate(
                self.space.dimensions, n_initial_points,
                random_state=self.rng.randint(0, np.iinfo(np.int32).max))
            self.space.set_transformer(transformer)

        // record categorical and non-categorical indices
        self._cat_inds = []
        self._non_cat_inds = []
        for ind, dim in enumerate(self.space.dimensions):
            if isinstance(dim, Categorical):

After Change

        self.init_point_gen_kwargs = init_point_gen_kwargs
        if initial_point_generator != "random" and \
                isinstance(initial_point_generator, str):
            if initial_point_generator == "sobol":
                self._initial_point_generator = Sobol(
                    **self.init_point_gen_kwargs)
            elif initial_point_generator == "halton":
                self._initial_point_generator = Halton(
                    **self.init_point_gen_kwargs)
            elif initial_point_generator == "hammersly":
                self._initial_point_generator = Hammersly(
                    **self.init_point_gen_kwargs)
            elif initial_point_generator == "lhs":
                self._initial_point_generator = Lhs(
                    **self.init_point_gen_kwargs)
            else:
                raise ValueError(
                    "Unkown initial_point_generator: " +
                    str(initial_point_generator)
                )
            transformer = self.space.get_transformer()
            self._initial_samples = self._initial_point_generator.generate(
                self.space.dimensions, n_initial_points,
                random_state=self.rng.randint(0, np.iinfo(np.int32).max))

Instances