J

datamanager.py

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+import os
+import sys
+import math
+import tarfile
+
+
+class DataManager:
+    def __init__(self, dataset_path):
+        self.dataset_path = dataset_path
+
+    def extract_dataset(self, compressed_dataset_file_name, dataset_directory):
+        try:
+            # extract files to dataset folder
+            tar = tarfile.open(compressed_dataset_file_name, "r:gz")
+            tar.extractall(dataset_directory)
+            tar.close()
+            print("Files extraction was successfull ...")
+
+        except:
+            print("Ecxception raised: No extraction was done ...")
+
+    def make_folder(self, folder_path):
+        try:
+            os.mkdir(folder_path)
+            print(folder_path, "was created ...")
+        except:
+            print("Ecxception raised: ", folder_path, "could not be created ...")
+
+    def move_files(self, src, dst, group):
+        for fname in group:
+            os.rename(src + '/' + fname, dst + '/' + fname)
+
+    def get_fnames_from_dict(self, dataset_dict, f_or_m):
+        training_data, testing_data = [], []
+
+        for i in range(1,5):
+            length_data       = len(dataset_dict[f_or_m +"000" + str(i)])
+            length_separator  = math.trunc(length_data*2/3)
+
+            training_data += dataset_dict[f_or_m + "000" + str(i)][:length_separator]
+            testing_data  += dataset_dict[f_or_m + "000" + str(i)][length_separator:]
+
+        return training_data, testing_data
+
+    def manage(self):
+
+        # read config file and get path to compressed dataset
+        compressed_dataset_file_name = self.dataset_path
+        dataset_directory = compressed_dataset_file_name.split(".")[0]
+
+        # create a folder for the data
+        try:
+            os.mkdir(dataset_directory)
+        except:
+            pass
+
+        # extract dataset
+        self.extract_dataset(compressed_dataset_file_name, dataset_directory)
+
+        # select females files and males files
+        file_names   = [fname for fname in os.listdir(dataset_directory) if ("f0" in fname or "m0" in fname)]
+        dataset_dict = {"f0001": [], "f0002": [], "f0003": [], "f0004": [], "f0005": [],
+                        "m0001": [], "m0002": [], "m0003": [], "m0004": [], "m0005": [], }
+
+        # fill in dictionary
+        for fname in file_names:
+            dataset_dict[fname.split('_')[0]].append(fname)
+
+        # divide and group file names
+        training_set, testing_set = {},{}
+        training_set["females"], testing_set["females"] = self.get_fnames_from_dict(dataset_dict, "f")
+        training_set["males"  ], testing_set["males"  ] = self.get_fnames_from_dict(dataset_dict, "m")
+
+        # make training and testing folders
+        self.make_folder("TrainingData")
+        self.make_folder("TestingData")
+        self.make_folder("TrainingData/females")
+        self.make_folder("TrainingData/males")
+        self.make_folder("TestingData/females")
+        self.make_folder("TestingData/males")
+
+        # move files
+        self.move_files(dataset_directory, "TrainingData/females", training_set["females"])
+        self.move_files(dataset_directory, "TrainingData/males",   training_set["males"])
+        self.move_files(dataset_directory, "TestingData/females",  testing_set["females"])
+        self.move_files(dataset_directory, "TestingData/males",    testing_set["males"])
+
+
+if __name__== "__main__":
+    data_manager = DataManager("SLR45.tgz")
+    data_manager.manage()