class SimpleDifferentiationFeature(unittest.TestCase):
def setUp(self):
self.channel_names = ['a', 'b', 'c', 'd', 'e', 'f']
self.x1 = TimeSeries(
[[1, 2, 3, 4, 5, 6], [6, 5, 3, 1, 7, 7]], self.channel_names, 120)
def test_sd_feature(self):
sd_node = SimpleDifferentiationFeatureNode()
features = sd_node.execute(self.x1)
for f in range(features.shape[1]):
channel = features.feature_names[f][4]
index = self.channel_names.index(channel)
self.assertEqual(
features.view(
numpy.ndarray)[0][f],
self.x1.view(
numpy.ndarray)[1][index] -
self.x1.view(
numpy.ndarray)[0][index])
class SimpleDifferentiationFeature(unittest.TestCase):
def setUp(self):
self.channel_names = ['a', 'b', 'c', 'd', 'e', 'f']
self.x1 = TimeSeries([[1, 2, 3, 4, 5, 6], [6, 5, 3, 1, 7, 7]],
self.channel_names, 120)
def test_sd_feature(self):
sd_node = SimpleDifferentiationFeatureNode()
features = sd_node.execute(self.x1)
for f in range(features.shape[1]):
channel = features.feature_names[f][4]
index = self.channel_names.index(channel)
self.assertEqual(
features.view(numpy.ndarray)[0][f],
self.x1.view(numpy.ndarray)[1][index] -
self.x1.view(numpy.ndarray)[0][index])
class WindowFuncTestCase(unittest.TestCase):
def setUp(self):
self.test_data = numpy.zeros((128, 3))
self.test_data[:, 1] = numpy.ones(128)
self.test_data[:, 2] = numpy.random.random(128)
self.test_time_series = TimeSeries(self.test_data, ["A", "B", "C"],
64,
start_time=0,
end_time=2000)
def test_zero_window(self):
""" Test that the window function [0 0 ... 0 0] raises an InvalidWindowException """
window_function_str = "lambda n: lambda x: 0"
node = window_func.WindowFuncNode(
window_function_str=window_function_str)
self.assertRaises(window_func.InvalidWindowException, node.execute,
self.test_time_series)
def test_one_window(self):
""" Test that the window function [1 1 ... 1 1] does not change the time series """
window_function_str = "lambda n: lambda x: 1"
node = window_func.WindowFuncNode(
window_function_str=window_function_str)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(
numpy.all(
windowed_time_series.view(numpy.ndarray) ==
self.test_time_series.view(numpy.ndarray)))
def test_convolving(self):
""" Test that convolving one with a window returns the window """
window_function_str = """lambda n: lambda x: (1 - __import__("numpy").cos((x + 1) * __import__("numpy").pi/n))/2"""
window_function = eval(window_function_str)
window = numpy.array([
window_function(self.test_time_series.shape[0])(i)
for i in range(self.test_time_series.shape[0])
])
node = window_func.WindowFuncNode(
window_function_str=window_function_str)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(
numpy.all(
windowed_time_series.view(numpy.ndarray)[:, 1] == window))
def test_chopping(self):
""" Test that the window function with trailing zeros chops the time series window """
# Chopping at the start
window_function_str = """lambda n: lambda x: 0 if x < 2 else 1"""
node = window_func.WindowFuncNode(
window_function_str=window_function_str, reduce_window=True)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(windowed_time_series.shape[0] +
2 == self.test_time_series.shape[0])
self.assert_(
numpy.all(
windowed_time_series.view(numpy.ndarray) ==
self.test_time_series.view(numpy.ndarray)[2:, :]))
# Chopping at the end
window_function_str = """lambda n: lambda x: 0 if x >= n - 2 else 1"""
node = window_func.WindowFuncNode(
window_function_str=window_function_str, reduce_window=True)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(windowed_time_series.shape[0] +
2 == self.test_time_series.shape[0])
self.assert_(
numpy.all(
windowed_time_series.view(numpy.ndarray) ==
self.test_time_series.view(numpy.ndarray)[:-2, :]))
class BaseDataTestCase(unittest.TestCase):
"""Test BaseData data type"""
def setUp(self):
"""Create some example data """
# Create some TimeSeries:
self.x1 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12,
marker_name='S4', name='Name_text ending with Standard',
start_time=1000.0, end_time=1004.0)
self.x1.specs={'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x1.generate_meta() #automatically generate key and tag
self.x2 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12,
marker_name='S4', start_time=2000.0, end_time=2004.0,
name='Name_text ending with Standard')
#manually generate key and tag
import uuid
self.x2_key=uuid.uuid4()
self.x2.key=self.x2_key
self.x2.tag='Tag of x2'
self.x2.specs={'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x3 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12,
marker_name='S4', start_time=3000.0, end_time=3004.0)
self.x3.specs={'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x3.generate_meta()
self.x4 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12,marker_name='S4')
self.x4.specs={'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x5 = TimeSeries([1,2], ['a','b'], 12)
self.x5.inherit_meta_from(self.x2)
self.x6 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12)
self.x6.specs={'Nice_Parameter': 11, 'Less_Nice_Param': '21'}
self.x6.generate_meta()
#safe information
self.x6_key=self.x6.key
self.x6.inherit_meta_from(self.x2)
self.some_nice_dict = {'guido': 4127, 'irv': 4127, 'jack': 4098}
self.x6.add_to_history(self.x5, self.some_nice_dict)
# Create some FeatureVectors:
self.f1 = FeatureVector([1,2,3,4,5,6],['a','b','c','d','e','f'])
self.f1.specs={'NiceParam':1,'LessNiceParam':2}
self.f2 = FeatureVector([1,2,3,4,5,6],['a','b','c','d','e','f'], tag = 'Tag of f2')
self.f2.specs={'NiceParam':1,'LessNiceParam':2}
self.f3 = FeatureVector([1,2], ['a','b'])
self.f3.inherit_meta_from(self.x2)
self.f3.add_to_history(self.x5)
def testTag(self):
"""Test tag behavior"""
# Generate from Meta Data
self.assertEqual(self.x1.tag,
'Epoch Start: 1000ms; End: 1004ms; Class: Standard')
# Tag passed, use that!
self.assertEqual(self.x2.tag, 'Tag of x2')
self.assertEqual(self.f2.tag, 'Tag of f2')
# No tag and only partial meta passed
self.assertEqual(self.x3.tag,
'Epoch Start: 3000ms; End: 3004ms; Class: na')
# No Tag and no meta passed, Tag remains None
self.assertEqual(self.x4.tag, None)
self.assertEqual(self.f1.tag, None)
def testKey(self):
"""Test key behavior"""
import uuid
self.assertEqual(type(self.x1.key),uuid.UUID)
# If Key passed, use that!
self.assertEqual(self.x2.key, self.x2_key)
def testInheritAndAddStuff(self):
"""test inheritance of meta data from other objects"""
# Inherit
self.assertEqual(self.x5.tag, self.x2.tag)
self.assertEqual(self.x5.key, self.x2.key)
self.assertEqual(self.f3.tag, self.x2.tag)
self.assertEqual(self.f3.key, self.x2.key)
#Inherit
#suppress warning of BaseData type and cast data back to numpy
hist_x6=self.x6.history[0].view(numpy.ndarray)
data_x5=self.x5.view(numpy.ndarray)
# history
self.assertEqual((hist_x6==data_x5).all(),True)
self.assertEqual(self.x6.history[0].key,self.x5.key)
self.assertEqual(self.x6.history[0].tag,self.x5.tag)
self.assertEqual(self.x6.history[0].specs['node_specs'],self.some_nice_dict)
hist_f3=self.f3.history[0].view(numpy.ndarray)
self.assertEqual((hist_f3==data_x5).all(),True)
self.assertEqual(self.f3.history[0].key,self.x5.key)
self.assertEqual(self.f3.history[0].tag,self.x5.tag)
#if key (and tag) were already set, these original values
#have to be kept
#
self.assertEqual(self.x6.key, self.x6_key)
self.assertEqual(self.x6.tag, self.x2.tag)
self.x6.inherit_meta_from(self.f3) #should not change tag and key
self.assertEqual(self.x6.key, self.x6_key)
self.assertEqual(self.x6.tag, self.x2.tag)
#testing multiple histories
x7 = TimeSeries([1,2,3,4,5,6], ['a','b','c','d','e','f'], 12,marker_name='S4')
x7.add_to_history(self.x1)
x7.add_to_history(self.x2)
x7.add_to_history(self.x3)
x7.add_to_history(self.x4)
x7.add_to_history(self.x5)
x7.add_to_history(self.x6)
x7.add_to_history(self.x1)
self.assertEqual(len(x7.history),7)
self.assertEqual(x7.history[0].key,x7.history[6].key)
self.assertEqual(x7.history[5].history,[])
def testSpecs(self):
"""Test specs behavior"""
# so far, there's not much going on with specs...
# same problem as in testkey
# timeseries doesn't set spec
self.assertEqual(self.x1.specs,
{'Nice_Parameter': 1, 'Less_Nice_Param': '2'})
# Inherit
self.assertEqual(self.x5.specs,self.x2.specs)
class BaseDataTestCase(unittest.TestCase):
"""Test BaseData data type"""
def setUp(self):
"""Create some example data """
# Create some TimeSeries:
self.x1 = TimeSeries([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'],
12,
marker_name='S4',
name='Name_text ending with Standard',
start_time=1000.0,
end_time=1004.0)
self.x1.specs = {'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x1.generate_meta() #automatically generate key and tag
self.x2 = TimeSeries([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'],
12,
marker_name='S4',
start_time=2000.0,
end_time=2004.0,
name='Name_text ending with Standard')
#manually generate key and tag
import uuid
self.x2_key = uuid.uuid4()
self.x2.key = self.x2_key
self.x2.tag = 'Tag of x2'
self.x2.specs = {'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x3 = TimeSeries([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'],
12,
marker_name='S4',
start_time=3000.0,
end_time=3004.0)
self.x3.specs = {'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x3.generate_meta()
self.x4 = TimeSeries([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'],
12,
marker_name='S4')
self.x4.specs = {'Nice_Parameter': 1, 'Less_Nice_Param': '2'}
self.x5 = TimeSeries([1, 2], ['a', 'b'], 12)
self.x5.inherit_meta_from(self.x2)
self.x6 = TimeSeries([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'], 12)
self.x6.specs = {'Nice_Parameter': 11, 'Less_Nice_Param': '21'}
self.x6.generate_meta()
#safe information
self.x6_key = self.x6.key
self.x6.inherit_meta_from(self.x2)
self.some_nice_dict = {'guido': 4127, 'irv': 4127, 'jack': 4098}
self.x6.add_to_history(self.x5, self.some_nice_dict)
# Create some FeatureVectors:
self.f1 = FeatureVector([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'])
self.f1.specs = {'NiceParam': 1, 'LessNiceParam': 2}
self.f2 = FeatureVector([1, 2, 3, 4, 5, 6],
['a', 'b', 'c', 'd', 'e', 'f'],
tag='Tag of f2')
self.f2.specs = {'NiceParam': 1, 'LessNiceParam': 2}
self.f3 = FeatureVector([1, 2], ['a', 'b'])
self.f3.inherit_meta_from(self.x2)
self.f3.add_to_history(self.x5)
def testTag(self):
"""Test tag behavior"""
# Generate from Meta Data
self.assertEqual(self.x1.tag,
'Epoch Start: 1000ms; End: 1004ms; Class: Standard')
# Tag passed, use that!
self.assertEqual(self.x2.tag, 'Tag of x2')
self.assertEqual(self.f2.tag, 'Tag of f2')
# No tag and only partial meta passed
self.assertEqual(self.x3.tag,
'Epoch Start: 3000ms; End: 3004ms; Class: na')
# No Tag and no meta passed, Tag remains None
self.assertEqual(self.x4.tag, None)
self.assertEqual(self.f1.tag, None)
def testKey(self):
"""Test key behavior"""
import uuid
self.assertEqual(type(self.x1.key), uuid.UUID)
# If Key passed, use that!
self.assertEqual(self.x2.key, self.x2_key)
def testInheritAndAddStuff(self):
"""test inheritance of meta data from other objects"""
# Inherit
self.assertEqual(self.x5.tag, self.x2.tag)
self.assertEqual(self.x5.key, self.x2.key)
self.assertEqual(self.f3.tag, self.x2.tag)
self.assertEqual(self.f3.key, self.x2.key)
#Inherit
#suppress warning of BaseData type and cast data back to numpy
hist_x6 = self.x6.history[0].view(numpy.ndarray)
data_x5 = self.x5.view(numpy.ndarray)
# history
self.assertEqual((hist_x6 == data_x5).all(), True)
self.assertEqual(self.x6.history[0].key, self.x5.key)
self.assertEqual(self.x6.history[0].tag, self.x5.tag)
self.assertEqual(self.x6.history[0].specs['node_specs'],
self.some_nice_dict)
hist_f3 = self.f3.history[0].view(numpy.ndarray)
self.assertEqual((hist_f3 == data_x5).all(), True)
self.assertEqual(self.f3.history[0].key, self.x5.key)
self.assertEqual(self.f3.history[0].tag, self.x5.tag)
#if key (and tag) were already set, these original values
#have to be kept
#
self.assertEqual(self.x6.key, self.x6_key)
self.assertEqual(self.x6.tag, self.x2.tag)
self.x6.inherit_meta_from(self.f3) #should not change tag and key
self.assertEqual(self.x6.key, self.x6_key)
self.assertEqual(self.x6.tag, self.x2.tag)
#testing multiple histories
x7 = TimeSeries([1, 2, 3, 4, 5, 6], ['a', 'b', 'c', 'd', 'e', 'f'],
12,
marker_name='S4')
x7.add_to_history(self.x1)
x7.add_to_history(self.x2)
x7.add_to_history(self.x3)
x7.add_to_history(self.x4)
x7.add_to_history(self.x5)
x7.add_to_history(self.x6)
x7.add_to_history(self.x1)
self.assertEqual(len(x7.history), 7)
self.assertEqual(x7.history[0].key, x7.history[6].key)
self.assertEqual(x7.history[5].history, [])
def testSpecs(self):
"""Test specs behavior"""
# so far, there's not much going on with specs...
# same problem as in testkey
# timeseries doesn't set spec
self.assertEqual(self.x1.specs, {
'Nice_Parameter': 1,
'Less_Nice_Param': '2'
})
# Inherit
self.assertEqual(self.x5.specs, self.x2.specs)
class WindowFuncTestCase(unittest.TestCase):
def setUp(self):
self.test_data = numpy.zeros((128, 3))
self.test_data[:,1] = numpy.ones(128)
self.test_data[:,2] = numpy.random.random(128)
self.test_time_series = TimeSeries(self.test_data, ["A","B", "C"], 64,
start_time = 0, end_time = 2000)
def test_zero_window(self):
""" Test that the window function [0 0 ... 0 0] raises an InvalidWindowException """
window_function_str = "lambda n: lambda x: 0"
node = window_func.WindowFuncNode(window_function_str = window_function_str)
self.assertRaises(window_func.InvalidWindowException,
node.execute, self.test_time_series)
def test_one_window(self):
""" Test that the window function [1 1 ... 1 1] does not change the time series """
window_function_str = "lambda n: lambda x: 1"
node = window_func.WindowFuncNode(window_function_str = window_function_str)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(numpy.all(windowed_time_series.view(numpy.ndarray) == self.test_time_series.view(numpy.ndarray)))
def test_convolving(self):
""" Test that convolving one with a window returns the window """
window_function_str = """lambda n: lambda x: (1 - __import__("numpy").cos((x + 1) * __import__("numpy").pi/n))/2"""
window_function = eval(window_function_str)
window = numpy.array([window_function(self.test_time_series.shape[0])(i)
for i in range(self.test_time_series.shape[0])])
node = window_func.WindowFuncNode(window_function_str = window_function_str)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(numpy.all(windowed_time_series.view(numpy.ndarray)[:,1] == window))
def test_chopping(self):
""" Test that the window function with trailing zeros chops the time series window """
# Chopping at the start
window_function_str = """lambda n: lambda x: 0 if x < 2 else 1"""
node = window_func.WindowFuncNode(window_function_str = window_function_str,
reduce_window = True)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(windowed_time_series.shape[0] + 2 == self.test_time_series.shape[0])
self.assert_(numpy.all(windowed_time_series.view(numpy.ndarray) == self.test_time_series.view(numpy.ndarray)[2:,:]))
# Chopping at the end
window_function_str = """lambda n: lambda x: 0 if x >= n - 2 else 1"""
node = window_func.WindowFuncNode(window_function_str = window_function_str,
reduce_window = True)
windowed_time_series = node.execute(self.test_time_series)
self.assert_(windowed_time_series.shape[0] + 2 == self.test_time_series.shape[0])
self.assert_(numpy.all(windowed_time_series.view(numpy.ndarray) == self.test_time_series.view(numpy.ndarray)[:-2,:]))
