def build_gan(self): # neighbours self.df, self.neighbour_list = get_neighbours_featurize(self.df, self.coord_vars, self.cont_vars, self.neighbours) # data structures self.target = self.df[self.output_vars].values self.cond_input = self.df[self.cond_vars + self.neighbour_list].values self.coord_input = self.df[self.coord_vars].values self.prob_config["output_labels"] = self.output_vars # move to fit, before calling spaceGAN.train self.prob_config["input_labels"] = self.cond_vars + self.neighbour_list # move to fit, before calling spaceGAN.train # pre-instantiation self.disc_method = Discriminator(self.prob_config["output_dim"], self.prob_config["cond_dim"]) self.disc_method.to(self.prob_config["device"]) self.gen_method = Generator(self.prob_config["cond_dim"], self.prob_config["noise_dim"], self.prob_config["output_dim"]) self.gen_method.to(self.prob_config["device"])
}, }, "agg_funcs": { "avg": np.mean, "std": np.std }, "sample_metrics": False, "agg_metrics": True } model_save_prefix = 'saved_models/' # train the model # neighbours df, neighbour_list = get_neighbours_featurize(df, coord_vars, cont_vars, neighbours) # data structures target = df[output_vars].values cond_input = df[cond_vars + neighbour_list].values coord_input = df[coord_vars].values prob_config["output_labels"] = output_vars prob_config["input_labels"] = cond_vars + neighbour_list # pre-instantiation disc_method = Discriminator(prob_config["output_dim"], prob_config["cond_dim"]) disc_method.to(prob_config["device"]) gen_method = Generator(prob_config["cond_dim"], prob_config["noise_dim"], prob_config["output_dim"]) gen_method.to(prob_config["device"])
import os import pandas as pd import spacegan_method import spacegan_config import spacegan_utils import spacegan_selection if __name__ == "__main__": cur_dir = os.getcwd() os.chdir(spacegan_config.results_path) # neighbours df, neighbour_list = spacegan_utils.get_neighbours_featurize( spacegan_config.df, spacegan_config.coord_vars, spacegan_config.output_vars, spacegan_config.neighbours) # data structures target = df[spacegan_config.output_vars].values cond_input = df[spacegan_config.cond_vars + neighbour_list].values coord_input = df[spacegan_config.coord_vars].values spacegan_config.prob_config["output_labels"] = spacegan_config.output_vars spacegan_config.prob_config[ "input_labels"] = spacegan_config.cond_vars + neighbour_list # pre-instantiation disc_method = spacegan_config.Discriminator( spacegan_config.prob_config["output_dim"], spacegan_config.prob_config["cond_dim"]) disc_method.to(spacegan_config.prob_config["device"]) gen_method = spacegan_config.Generator( spacegan_config.prob_config["cond_dim"],