def run(self):
path_split = self.path.split(os.get_path_seperator())
backup_name = path_split[len(path_split) - 1]
backup_name = backup_name.split('.')[0]
backup = os.copy_file(self.path,
f"{backup_name}{self.backup_name_index}.bak")
with open(self.path, 'w') as data_file:
with open(backup) as backup_file:
data_file.write(backup_file.readline())
data_reading = backup_file.readline()
index = 0
while index < self.readings and data_reading != "":
data_file.write(data_reading)
data_reading = backup_file.readline()
index += 1
os.remove_file(backup)
def _save_training_samples(self, rec_loc, indexes):
copied_file = os.copy_file(rec_loc, "temp.bak")
index = 0
with open(copied_file) as training_copy:
with open(rec_loc, 'w') as training:
training.write(training_copy.readline())
for elem in indexes:
for _ in range(index, elem):
index += 1
training.write(training_copy.readline())
training_copy.readline()
index += 1
os.remove_file(copied_file)
def run(self):
file_to_backup = os.path_join(self.path, self.resource)
backup_name = f"{self.resource.split('.')[0]}.bak"
backup_path = os.copy_file(file_to_backup, backup_name)
with open(os.path_join(self.path, self.resource), 'w') as datafile:
with open(backup_path) as data:
datafile.write(data.readline())
temp = data.readline()
while temp != "":
normalized_reading = self.data_reading_normalizer(temp)
datafile.write(normalized_reading)
temp = data.readline()
os.remove_file(backup_path)
def run(self):
backup_path = os.copy_file(self.res_path, self.backup_name)
with open(self.res_path, 'w') as data_file:
with open(backup_path) as backup:
data = backup.read()
splitted_data = data.split("\n")
data_file.write("readings\n")
index = 0
for elem in splitted_data:
try:
reading = self.get_reading_value(elem)
if reading != None:
data_file.write(f"{reading}\n")
index += 1
except:
pass
os.remove_file(backup_path)
def _bakup_saved(self, training_loc):
if not os.is_path_file(training_loc):
return
return os.copy_file(training_loc, "temp.bak")
def exec(self, task_input, task_output):
sampling_frequency = task_input["sampled_frequency"]
target_frequency = task_input["target_frequency"]
doubling_rate = math.ceil(sampling_frequency / (((target_frequency / sampling_frequency) - 1) * sampling_frequency))
res_elems = os.dir_res_list(task_output["res_loc"])
for res_elem in res_elems:
origin_path = os.path_join(task_output["res_loc"], res_elem)
if os.is_path_file(origin_path):
backup_path = os.copy_file(origin_path, f"{task_input['name']}_bakup.bak")
with open(origin_path, 'w') as file:
with open(backup_path) as backup_file:
temp_reading = backup_file.readline()
sampling_nr = 1
while temp_reading != "":
temp_reading = backup_file.readline()
if temp_reading != "":
splitted = temp_reading.split(',')
file.write(f"{sampling_nr},{splitted[1]},{splitted[2]}")
if "f2" in res_elem:
file.write("\n")
sampling_nr += 1
for _ in range(1, doubling_rate):
temp_reading = backup_file.readline()
if temp_reading != "":
splitted = temp_reading.split(',')
file.write(f"{sampling_nr},{splitted[1]},{splitted[2]}")
if "f2" in res_elem:
file.write("\n")
sampling_nr += 1
if temp_reading != "":
splitted = temp_reading.split(',')
file.write(f"{sampling_nr},{splitted[1]},{splitted[2]}")
if "f2" in res_elem:
file.write("\n")
sampling_nr += 1
splitted = temp_reading.split(',')
file.write(f"{sampling_nr},{splitted[1]},{splitted[2]}")
if "f2" in res_elem:
file.write("\n")
sampling_nr += 1
temp_reading = backup_file.readline()
os.remove_file(backup_path)