def plot_results(self): """ Plots the results """ print("Plotting Results...") prepare_sns(sns, self.params) self.plot_all_diseases() for disease_id in tqdm(self.params.disease_plots): self.plot_disease(self.diseases[disease_id])
def plot_results(self): """ Plots the results """ print("Plotting Results...") prepare_sns(sns, self.params) self.figures_dir = os.path.join(self.dir, 'figures') if not os.path.exists(self.figures_dir): os.makedirs(self.figures_dir) for plot_name, params in self.params.plots_to_params.items(): plot_fn = params["plot_fn"] del params["plot_fn"] getattr(self, plot_fn)(name=plot_name, **params)
def plot_results(self): """ Outputs the results as a plot """ assert (self.results != None) prepare_sns(sns, self.params) for name in self.plots: _, codisease_probs = self.results[name] if self.smooth: codisease_probs = np.maximum( 0, savgol_filter(codisease_probs, window_length=self.window_length - 1, polyorder=3)) bucket_size = self.top_k / self.n_buckets plt.plot(np.arange(1, len(codisease_probs) * bucket_size + 1, bucket_size), codisease_probs[::-1], label=name, linewidth=2.0 if name == self.params.primary else 1.0) #plt.xticks(np.arange(1, len(codisease_probs) * bucket_size, bucket_size)) plt.legend() plt.ylabel('Codisease Probability') plt.xlabel('Protein Pair Rank') figures_dir = os.path.join(self.dir, 'figures') if not os.path.exists(figures_dir): os.makedirs(figures_dir) time_string = datetime.datetime.now().strftime("%m-%d_%H%M") sns.despine() plt.tight_layout() plt.savefig( os.path.join(figures_dir, 'codisease_' + time_string + '.pdf'))
assert os.path.isfile( json_path), "No json configuration file found at {}".format(json_path) params = Params(json_path) params.update(json_path) # Set the logger set_logger(os.path.join(args.experiment_dir, 'experiment.log'), level=logging.INFO, console=True) # Log Title logging.info("DPP-Diff Generator") logging.info("Sabri Eyuboglu -- SNAP Group") logging.info("======================================") prepare_sns(sns, params) diseases_dict = load_diseases(params.diseases_path, params.disease_subset) method_to_scores = {} for method_name, method_exp_dir in params.method_exp_dirs.items(): method_to_scores[method_name] = {} with open(os.path.join(method_exp_dir, 'metrics.csv'), 'r') as metrics_file: metrics_reader = csv.DictReader(metrics_file) print(method_exp_dir) for i, row in enumerate(metrics_reader): if row[params.metric] == params.metric: continue if not is_disease_id(row["Disease ID"]): continue if (diseases_dict[row["Disease ID"]].split == "none"): continue