diff --git a/summit/multiview_platform/exec_classif.py b/summit/multiview_platform/exec_classif.py
index 73b87d7786e0d034896a9046e4c3803e675cff53..09f708aa7593fb13e9db91ba2c0e88e61c82eca4 100644
--- a/summit/multiview_platform/exec_classif.py
+++ b/summit/multiview_platform/exec_classif.py
@@ -955,7 +955,6 @@ class Summit(BaseExec):
metrics=self.metrics)
return plif
-
def gen_single_multiview_arg_dictionary(self, classifier_name, arguments, nb_class,
hps_kwargs, views_dictionary=None,):
if classifier_name in arguments:
@@ -975,10 +974,7 @@ class Summit(BaseExec):
database_name=self.name,
hps_type=self.hps_type,
nb_cores=self.nb_cores,
- metrics=self.metrics,
-
- )
-
+ metrics=self.metrics,)
def extract_dict(self, classifier_config):
"""Reverse function of get_path_dict"""
@@ -987,7 +983,6 @@ class Summit(BaseExec):
extracted_dict = self.set_element(extracted_dict, key, value)
return extracted_dict
-
def set_element(self, dictionary, path, value):
"""Set value in dictionary at the location indicated by path"""
existing_keys = path.split(".")[:-1]
@@ -1001,7 +996,6 @@ class Summit(BaseExec):
dict_state[path.split(".")[-1]] = value
return dictionary
-
def get_path_dict(self, multiview_classifier_args):
"""This function is used to generate a dictionary with each key being
the path to the value.
@@ -1018,7 +1012,6 @@ class Summit(BaseExec):
paths = self.is_dict_in(path_dict)
return path_dict
-
def is_dict_in(self, dictionary):
"""
Returns True if any of the dictionary value is a dictionary itself.
@@ -1037,7 +1030,6 @@ class Summit(BaseExec):
paths.append(key)
return paths
-
def init_kwargs(self, classifiers_names, framework="monoview"):
r"""Used to init kwargs thanks to a function in each monoview classifier package.
@@ -1068,8 +1060,8 @@ class Summit(BaseExec):
getattr(multiview_classifiers, classifiers_name)
except AttributeError:
raise AttributeError(
- classifiers_name + " is not implemented in monoview_classifiers, "
- "please specify the name of the file in monoview_classifiers")
+ classifiers_name + " is not implemented in {}_classifiers, "
+ "please specify the name of the file in {}_classifiers".format(framework, framework))
if classifiers_name in self.args:
kwargs[classifiers_name] = self.args[classifiers_name]
else:
diff --git a/summit/multiview_platform/result_analysis/error_analysis.py b/summit/multiview_platform/result_analysis/error_analysis.py
index 672404462e214d85b1ded0ea75b377cdbf6fffe8..96dbc9bba0cee7b831db65fc6c8ac684255d6424 100644
--- a/summit/multiview_platform/result_analysis/error_analysis.py
+++ b/summit/multiview_platform/result_analysis/error_analysis.py
@@ -55,9 +55,13 @@ def publish_sample_errors(sample_errors, directory, database_name,
nb_classifiers, nb_samples, classifiers_names, \
data_2d, error_on_samples = gen_error_data(sample_errors)
- np.savetxt(base_file_name + "2D_plot_data.csv", data_2d, delimiter=",")
- np.savetxt(base_file_name + "bar_plot_data.csv", error_on_samples,
- delimiter=",")
+ heat_map_data = pd.DataFrame(index=sample_ids, columns=classifiers_names, data=data_2d)
+ bar_plot_data = pd.DataFrame(index=sample_ids, data=error_on_samples)
+ heat_map_data.to_csv(base_file_name + "2D_plot_data.csv")
+ bar_plot_data.to_csv(base_file_name + "bar_plot_data.csv")
+ # np.savetxt(base_file_name + "2D_plot_data.csv", data_2d, delimiter=",")
+ # np.savetxt(base_file_name + "bar_plot_data.csv", error_on_samples,
+ # delimiter=",")
plot_2d(data_2d, classifiers_names, nb_classifiers, base_file_name, database_name,
sample_ids=sample_ids, labels=labels, label_names=label_names, test=test)
@@ -82,9 +86,14 @@ def publish_all_sample_errors(iter_results, directory,
add='t'
else:
add = ""
- np.savetxt(os.path.join(directory, "clf_errors{}.csv".format(add)), data, delimiter=",")
- np.savetxt(os.path.join(directory, "sample_errors{}.csv".format(add)), error_on_samples,
- delimiter=",")
+ heat_map_data = pd.DataFrame(index=sample_ids, columns=classifier_names,
+ data=data)
+ bar_plot_data = pd.DataFrame(index=sample_ids, data=error_on_samples)
+ heat_map_data.to_csv(os.path.join(directory, "clf_errors{}.csv".format(add)))
+ bar_plot_data.to_csv(os.path.join(directory, "sample_errors{}.csv".format(add)))
+ # np.savetxt(os.path.join(directory, "clf_errors{}.csv".format(add)), data, delimiter=",")
+ # np.savetxt(os.path.join(directory, "sample_errors{}.csv".format(add)), error_on_samples,
+ # delimiter=",")
df = pd.DataFrame(index = sample_ids, columns=["err"], data=1-error_on_samples)
df.to_csv(os.path.join(directory, "sample_err_df{}.csv".format(add)))
plot_2d(data, classifier_names, nb_classifiers,
diff --git a/summit/multiview_platform/result_analysis/feature_importances.py b/summit/multiview_platform/result_analysis/feature_importances.py
index ec233dc22b50e0e50ab5cfb18752852b7577705d..ad92c6cdf8e0314a4677b3d438370d9b3c809db6 100644
--- a/summit/multiview_platform/result_analysis/feature_importances.py
+++ b/summit/multiview_platform/result_analysis/feature_importances.py
@@ -25,6 +25,7 @@ def get_feature_importances(result, feature_ids=None, view_names=None,):
"""
feature_importances = {}
for classifier_result in result:
+ print((classifier_result.classifier_name))
if isinstance(classifier_result, MonoviewResult):
if classifier_result.view_name not in feature_importances:
feature_importances[classifier_result.view_name] = pd.DataFrame(