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