def setUp(self):
# make a test dataset
# print os.getcwd()
data_dir_path = ds.get_data_dir_path()
# print os.getcwd()
os.chdir(r"%s" % data_dir_path)
try:
os.mkdir("TEST")
except OSError:
shutil.rmtree("TEST")
os.mkdir("TEST")
os.chdir("TEST")
# make some files in the test dataset
f = open("TEST.json", "w")
f.write("{\"PtEtaPhi\":{\"train_file\":\"train_all_ptEtaPhi"
".txt\",\"test_file\":\"test_all_ptEtaPhi.txt\"},\""
"Pt\":{\"train_file\":\"train_all_Pt.txt\",\"test_f"
"ile\":\"test_all_Pt.txt\"},\"3v\":{\"train_file\":"
"\"train_all_3v.txt\",\"test_file\":\"test_all_3v.t"
"xt\"}}")
f.close()
os.system("touch train_all_ptEtaPhi.txt")
os.system("touch test_all_ptEtaPhi.txt")
os.system("touch train_all_Pt.txt")
os.system("touch test_all_Pt.txt")
os.system("touch train_all_3v.txt")
os.system("touch test_all_3v.txt")
os.system("touch PtEtaPhi.npz")
os.chdir(data_dir_path)
def setUp(self):
# make a test dataset
# print os.getcwd()
data_dir_path = ds.get_data_dir_path()
# print os.getcwd()
os.chdir(r"%s" % data_dir_path)
try:
os.mkdir("TEST")
except OSError:
shutil.rmtree("TEST")
os.mkdir("TEST")
os.chdir("TEST")
# make some files in the test dataset
f = open("TEST.json", "w")
f.write("{\"PtEtaPhi\":{\"train_file\":\"train_all_ptEtaPhi"
".txt\",\"test_file\":\"test_all_ptEtaPhi.txt\"},\""
"Pt\":{\"train_file\":\"train_all_Pt.txt\",\"test_f"
"ile\":\"test_all_Pt.txt\"},\"3v\":{\"train_file\":"
"\"train_all_3v.txt\",\"test_file\":\"test_all_3v.t"
"xt\"}}")
f.close()
os.system("touch train_all_ptEtaPhi.txt")
os.system("touch test_all_ptEtaPhi.txt")
os.system("touch train_all_Pt.txt")
os.system("touch test_all_Pt.txt")
os.system("touch train_all_3v.txt")
os.system("touch test_all_3v.txt")
os.system("touch PtEtaPhi.npz")
os.chdir(data_dir_path)
def setUp(self):
# make a test dataset
data_dir_path = ds.get_data_dir_path()
os.chdir(data_dir_path)
os.mkdir("TEST")
os.chdir("TEST")
# make some files in the test dataset
os.system("touch test.experiment")
os.system("touch is_experiment.experiment")
os.system("touch is_not_experiment.test")
os.system("touch PtEtaPhi.npz")
os.chdir(data_dir_path)
def setUp(self):
# make a test dataset
data_dir_path = ds.get_data_dir_path()
os.chdir(data_dir_path)
os.mkdir("TEST")
os.chdir("TEST")
# make some files in the test dataset
os.system("touch test.experiment")
os.system("touch is_experiment.experiment")
os.system("touch is_not_experiment.test")
os.system("touch PtEtaPhi.npz")
os.chdir(data_dir_path)
def test_get_path_to_dataset(self):
""" Test the get_path_to_dataset function """
# nominal case : just dataset_name
data_dir_path = ds.get_data_dir_path()
test_dataset_path = os.path.join(data_dir_path, "TEST")
self.assertEqual(ds.get_path_to_dataset("TEST"), test_dataset_path)
# nominal case: dataset_name and format
test_format_path = os.path.join(test_dataset_path, "PtEtaPhi.npz")
self.assertEqual(ds.get_path_to_dataset("TEST", "PtEtaPhi"),
test_format_path)
# if the dataset doesn't exist
with self.assertRaises(IOError):
ds.get_path_to_dataset("some random folder")
# if the format doesn't exist in a valid dataset
with self.assertRaises(IOError):
ds.get_path_to_dataset("TEST", "Spherical")
def test_get_path_to_dataset(self):
""" Test the get_path_to_dataset function """
# nominal case : just dataset_name
data_dir_path = ds.get_data_dir_path()
test_dataset_path = os.path.join(data_dir_path, "TEST")
self.assertEqual(ds.get_path_to_dataset("TEST"), test_dataset_path)
# nominal case: dataset_name and format
test_format_path = os.path.join(test_dataset_path,
"PtEtaPhi.npz")
self.assertEqual(ds.get_path_to_dataset("TEST", "PtEtaPhi"),
test_format_path)
# if the dataset doesn't exist
with self.assertRaises(IOError):
ds.get_path_to_dataset("some random folder")
# if the format doesn't exist in a valid dataset
with self.assertRaises(IOError):
ds.get_path_to_dataset("TEST", "Spherical")
def set_configurations():
print("What would you like to name this experiment setup?")
print("*Note: this is used for naming the result files")
name = raw_input(">> ")
print("Which dataset would you like to run on?")
## Collect the names of the directories here
# Selects dataset
data_dir = get_data_dir_path()
print(' '.join(filter(lambda x: path.isdir(path.join(data_dir, x)), os.listdir(data_dir))))
dataset = raw_input(">> ")
print()
data_dir = get_path_to_dataset(dataset)
with open(path.join(data_dir, dataset+".json")) as fp:
j = json.load(fp)
print("Which coordinates would you like to use?")
print(' '.join(j.keys()))
coords = raw_input(">> ")
print()
# Collect data files from that dataset and repeat question
batch_size = raw_input("What will be your batch size?\n>> ")
print()
learning_rate = raw_input("What will be your learning rate?\n>> ")
print()
layers = raw_input("How many layers do you want?\n>> ")
print()
nodes = raw_input("How many nodes per layer do you want?\n>> ")
print()
print("How often do you want to save the model?")
print("(Number of epochs)")
sf = raw_input(">> ")
print()
print("How would you like to determine the end of the program:")
print("1. After a certain number of epochs")
print("2. After a certain amount of time")
print("3. When the accuracy plateaus")
print("*Note: You may select multiple, just separate them by spaces.")
ending = filter(None, raw_input("[1/2/3] >> ").split())
print()
terms = {"epochs": None, "timeout": None, "plateau": {"m": None, "w": None}}
if '1' in ending:
terms['epochs'] = int(raw_input("How many epochs do you want to run?\n>> "))
print()
if '2' in ending:
print("After how long do you want the program to be killed?")
print("(Put units after the number, i.e. s/m/h/d/w/y)")
time = raw_input(">> ")
print()
unit = time[-1]
time = int(time[:-1])
if unit == 'm':
time *= 60
elif unit == 'h':
time *= 3600
elif unit == 'd':
time *= 3600*24
elif unit == 'w':
time *= 3600*24*7
elif unit == 'y':
time *= 3600*24*7*52
terms['timeout'] = time
if '3' in ending:
print("For determining plateau:")
x = raw_input("Over what interval would you like to measure the accuracy change?\n>> ")
print()
y = raw_input("What is the minimal increase in percentile you can accept over this interval?\n>> ")
print()
terms['plateau'] = dict(x=float(x), y=int(y))
d = dict(save_name=name,
dataset=dataset,
coords=coords,
batch_size=int(batch_size),
learning_rate=float(learning_rate),
layers=int(layers),
nodes=int(nodes),
save_freq=int(sf),
terms=terms)
return d
def tearDown(self):
data_dir_path = ds.get_data_dir_path()
shutil.rmtree("TEST")
def tearDown(self):
data_dir_path = ds.get_data_dir_path()
shutil.rmtree("TEST")
