def setOutFile(self):
if '\\' in self.__currentdataset__:
datasetName = self.__currentdataset__.split("\\")[-1].split('-')[0]
else:
datasetName = self.__currentdataset__.split("/")[-1].split('-')[0]
fpath = os.path.join(self.__root__, 'a_s' + Configs.version)
fpath = os.path.join(fpath, 'a_Column')
check_folder(fpath)
self.__currentoutfile__ = os.path.join(fpath, datasetName)
del_dir_tree(self.__currentoutfile__)
def save_prediction_valid(self, prediction):
filepath = os.path.join(self.root_path, "_cache_",
"_cache_prediction_valid", self.dataname,
self.classifier_name, self.getfilename())
if not os.path.exists(filepath):
dirtools.check_folder(
os.path.join(self.root_path, "_cache_",
"_cache_prediction_valid", self.dataname,
self.classifier_name))
with open(filepath, 'w') as f: # open file with write-mode
pickle.dump(prediction, f) # serialize and save object
def save_estimator_test(self, estimator):
filepath = os.path.join(self.root_path, "_cache_",
"_cache_classifier_test", self.dataname,
self.classifier_name, self.getfilename())
if not os.path.exists(filepath):
dirtools.check_folder(
os.path.join(self.root_path, "_cache_",
"_cache_classifier_test", self.dataname,
self.classifier_name))
with open(filepath, 'w') as f: # open file with write-mode
pickle.dump(estimator, f) # serialize and save object
def logMiddle(genid, fitness, filename):
filedir = gol.get_val("root_path")
filedir = os.path.join(filedir, 'Results/' + gol.get_val("version"))
filedir = os.path.join(filedir, gol.get_val("dataName")+"-v"+gol.get_val("version"))
filedir = os.path.join(filedir, gol.get_val("aimFolder"))
check_folder(filedir)
filedir = os.path.join(filedir, filename)
f = file(filedir, 'a')
i = genid+1
f.write(str(i))
f.write(":")
f.write('\n')
f.write("fitness:")
f.write(str(fitness))
f.write('\n')
f.write('\n')
f.close()
def logPopulations( genid, pop):
filedir = gol.get_val("root_path")
filedir = os.path.join(filedir, 'Results/' + gol.get_val("version"))
filedir = os.path.join(filedir, gol.get_val("dataName")+"-v"+gol.get_val("version"))
filedir = os.path.join(filedir, gol.get_val("aimFolder"))
check_folder(filedir)
filedir = os.path.join(filedir, "Gen."+str(genid)+".gpecoc")
f = file(filedir, 'w+')
i = 1
for ind in pop:
Matrix , feature_list = getMatrixDirectly_and_feature(ind)
feature_method_index = gol.get_val("feature_method_index")
feature_index_list = list( feature_method_index[method] for method in feature_list)
Matrix = np.ndarray.tolist(Matrix)
Matrix.insert(0,feature_index_list)
Matrix = np.array(Matrix)
f.write(str(i))
f.write(":")
f.write('\n')
f.write(str(Matrix))
f.write('\n')
f.write("f-score:")
f.write(str(ind.fscore))
f.write('\n')
f.write("accuracy:")
f.write(str(ind.accuracy))
f.write('\n')
f.write('--------------------------------------------------------------------------------------------\n')
for text in ind.infos_evaluation:
f.write(str(text))
f.write('\n')
f.write('\n\n\n\n\n')
i=i+1
f.close()
def _agp_main_runner(dataName, aimFolder):
std = sys.stdout
try:
Configs.dataName = dataName
Configs.aimFolder = aimFolder
_rootp = Configs.root_path
_rootp = os.path.join(_rootp, 'Results/' + Configs.version)
_rootp = os.path.join(_rootp,
Configs.dataName + "-v" + Configs.version)
_rootp = os.path.join(_rootp, Configs.aimFolder)
del_dir_tree(_rootp) # delete former results
check_folder(_rootp)
_res = "/Result"
out = open(_rootp + _res, 'w+')
sys.stdout = out
sys.stderr = out
AGpEcocStart.main_run()
except Exception as e:
_err = "/Error"
err = open(_rootp + _err, 'w+')
err.write(e.message)
err.flush()
finally:
sys.stdout = std
