if file.endswith(".txt"): predictions_fname = os.path.join("predictions/", file) last_modified = os.path.getmtime(predictions_fname) if latest_time <= last_modified: self.predictions_fname = predictions_fname latest_time = last_modified fname = self.predictions_fname with open(fname, 'r') as f: self.predictions_strings = f.readlines() self.days_out_prediction = len(self.predictions_strings) def write_predictions_file(self, fname=None): if fname is None: fname = self.predictions_fname with open(fname, 'w') as f: for string, pred in zip(self.predictions_strings, self.predictions): string = string.strip('\n') f.write(string + str(pred) + '\n') if __name__ == '__main__': mlpr = MLPRegressor() mlpr.load() mlpr.read_predictions_file() for i in range(mlpr.days_out_prediction): mlpr.load_feature_vector(fname='sd_feature_vec_' + str(i)) output = mlpr.predict(np.reshape(mlpr.feature_vector, (1, -1))) print(output[0]) mlpr.write_predictions_file()