def test_opening_existing_filename_overwrite(self, filename):
"""
Tests that we can overwrite an existing filename if we use the overwrite parameter.
"""
# create a blank file
f = open(filename, mode='w')
f.close()
sample_rate = 1.e6
baseline = 0.2
n = 5000
data_should_be = np.zeros(n) + baseline
create_specified_data(filename=filename,
n=n,
sample_rate=sample_rate,
baseline=baseline,
noise_scale=0.0,
events=[],
overwrite=True)
_test_params_equality(self,
filename=filename,
data_should_be=data_should_be,
sample_rate=sample_rate)
def test_noise_no_events(self, filename):
"""
Tests that noise is added correctly.
"""
sample_rate = 1.e5
baseline = 1.0
n = 100000
noise_scale = 1.
create_specified_data(filename=filename, n=n, sample_rate=sample_rate, baseline=baseline,
noise_scale=noise_scale, events=[])
reader = get_reader_from_filename(filename)
data_all = reader.get_all_data()
data = data_all[0]
reader.close()
self.assertEqual(n, data.size, "Unexpected array size. Wanted {0}, got {1}.".format(n, data.size))
decimal = 1
mean = np.mean(data)
self.assertAlmostEqual(baseline, mean, decimal,
"Unexpected baseline. Wanted {0}, got {1}. Tested to {2} decimals.".format(baseline,
mean,
decimal))
decimal = 1
std_dev = np.std(data)
self.assertAlmostEqual(noise_scale, std_dev, decimal,
msg="Unexpected stddev. Wanted{0}, got {1}. Tested to {2} decimals.".format(noise_scale,
std_dev,
decimal))
def test_no_noise_specified_events(self, filename):
"""
Tests that with no noise and specified events we get the right matrix
"""
sample_rate = 1.e6
baseline = 1.0
n = 5000
events = [[100, 200., -.5], [1000, 500, -1.0], [3000, 1000, .2]]
data_should_be = np.zeros(n) + baseline
# add in the events to the data_should_be
for event in events:
data_should_be[event[0]:event[0] + event[1]] += event[2]
create_specified_data(filename=filename,
n=n,
sample_rate=sample_rate,
baseline=baseline,
noise_scale=0.0,
events=events)
_test_params_equality(self,
filename=filename,
data_should_be=data_should_be,
sample_rate=sample_rate)
def test_simple_baseline(self, filename):
"""
Tests that a no noise, no event returns just a baseline.
"""
sample_rate = 1.e6
baseline = 0.2
n = 5000
data_should_be = np.zeros(n) + baseline
create_specified_data(filename=filename, n=n, sample_rate=sample_rate, baseline=baseline, noise_scale=0.0,
events=[])
_test_params_equality(self, filename=filename, data_should_be=data_should_be, sample_rate=sample_rate)
def test_opening_existing_filename_overwrite(self, filename):
"""
Tests that we can overwrite an existing filename if we use the overwrite parameter.
"""
# create a blank file
f = open(filename, mode='w')
f.close()
sample_rate = 1.e6
baseline = 0.2
n = 5000
data_should_be = np.zeros(n) + baseline
create_specified_data(filename=filename, n=n, sample_rate=sample_rate, baseline=baseline, noise_scale=0.0,
events=[], overwrite=True)
_test_params_equality(self, filename=filename, data_should_be=data_should_be, sample_rate=sample_rate)
def test_no_noise_specified_events(self, filename):
"""
Tests that with no noise and specified events we get the right matrix
"""
sample_rate = 1.e6
baseline = 1.0
n = 5000
events = [[100, 200., -.5], [1000, 500, -1.0], [3000, 1000, .2]]
data_should_be = np.zeros(n) + baseline
# add in the events to the data_should_be
for event in events:
data_should_be[event[0]:event[0] + event[1]] += event[2]
create_specified_data(filename=filename, n=n, sample_rate=sample_rate, baseline=baseline, noise_scale=0.0,
events=events)
_test_params_equality(self, filename=filename, data_should_be=data_should_be, sample_rate=sample_rate)
def test_simple_baseline(self, filename):
"""
Tests that a no noise, no event returns just a baseline.
"""
sample_rate = 1.e6
baseline = 0.2
n = 5000
data_should_be = np.zeros(n) + baseline
create_specified_data(filename=filename,
n=n,
sample_rate=sample_rate,
baseline=baseline,
noise_scale=0.0,
events=[])
_test_params_equality(self,
filename=filename,
data_should_be=data_should_be,
sample_rate=sample_rate)
def test_noise_no_events(self, filename):
"""
Tests that noise is added correctly.
"""
sample_rate = 1.e5
baseline = 1.0
n = 100000
noise_scale = 1.
create_specified_data(filename=filename,
n=n,
sample_rate=sample_rate,
baseline=baseline,
noise_scale=noise_scale,
events=[])
reader = get_reader_from_filename(filename)
data_all = reader.get_all_data()
data = data_all[0]
reader.close()
self.assertEqual(
n, data.size,
"Unexpected array size. Wanted {0}, got {1}.".format(n, data.size))
decimal = 1
mean = np.mean(data)
self.assertAlmostEqual(
baseline, mean, decimal,
"Unexpected baseline. Wanted {0}, got {1}. Tested to {2} decimals."
.format(baseline, mean, decimal))
decimal = 1
std_dev = np.std(data)
self.assertAlmostEqual(
noise_scale,
std_dev,
decimal,
msg="Unexpected stddev. Wanted{0}, got {1}. Tested to {2} decimals."
.format(noise_scale, std_dev, decimal))
def test_output_filename_correct(self, filename):
create_specified_data(filename, n=100, sample_rate=10)
self.assertTrue(os.path.exists(filename))
def test_output_filename_correct(self, filename):
create_specified_data(filename, n=100, sample_rate=10)
self.assertTrue(os.path.exists(filename))