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"],