def next(self, debug=False):
"""Return next labeled window when used in iterator context."""
while len(self.cur_extract_windows) == 0:
# fetch the next block from data_client
if debug:
print "reading next block"
self._readnextblock()
self._extract_windows_cur_block()
if debug:
print " buffermarkers", self.buffermarkers
print " current block", self.samplebuf.get()[self.prebuflen][1, :]
# print " current extracted windows ", self.cur_extract_windows
(windef_name, current_window, class_, start_time, end_time, markers_cur_win) = self.cur_extract_windows.pop(0)
# TODO: Replace this by a decorator or something similar
current_window = numpy.atleast_2d(current_window.transpose())
current_window = TimeSeries(
input_array=current_window,
channel_names=self.data_client.channelNames,
sampling_frequency=self.data_client.dSamplingInterval,
start_time=start_time,
end_time=end_time,
name="Window extracted @ %d ms, length %d ms, class %s" % (start_time, end_time - start_time, class_),
marker_name=markers_cur_win,
)
current_window.generate_meta()
current_window.specs["sampling_frequency"] = self.data_client.dSamplingInterval
current_window.specs["wdef_name"] = windef_name
self.nwindow += 1
# return (ndsamplewin, ndmarkerwin)
return (current_window, class_)
def next(self, debug=False):
"""Return next labeled window when used in iterator context."""
while len(self.cur_extract_windows) == 0:
# fetch the next block from data_client
if debug:
print "reading next block"
self._readnextblock()
self._extract_windows_cur_block()
if debug:
print " buffermarkers", self.buffermarkers
print " current block", self.samplebuf.get()[self.prebuflen][
1, :]
# print " current extracted windows ", self.cur_extract_windows
(windef_name, current_window, class_, start_time, end_time, markers_cur_win) = \
self.cur_extract_windows.pop(0)
# TODO: Replace this by a decorator or something similar
current_window = numpy.atleast_2d(current_window.transpose())
current_window = TimeSeries(
input_array=current_window,
channel_names=self.data_client.channelNames,
sampling_frequency=self.data_client.dSamplingInterval,
start_time = start_time,
end_time = end_time,
name = "Window extracted @ %d ms, length %d ms, class %s" % \
(start_time, end_time - start_time, class_),
marker_name = markers_cur_win
)
current_window.generate_meta()
current_window.specs[
'sampling_frequency'] = self.data_client.dSamplingInterval
current_window.specs['wdef_name'] = windef_name
self.nwindow += 1
# return (ndsamplewin, ndmarkerwin)
return (current_window, class_)
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)
