def __init__(self):
super(QTCBCHMM, self).__init__()
self.num_possible_states = 92 # Setting number of possible states: QTCBC + start and end
self.qtcb = QTCBHMM()
self.qtcc = QTCCHMM()
class QTCBCHMM(QTCHMMAbstractclass):
def __init__(self):
super(QTCBCHMM, self).__init__()
self.num_possible_states = 92 # Setting number of possible states: QTCBC + start and end
self.qtcb = QTCBHMM()
self.qtcc = QTCCHMM()
def _create_transition_matrix(self, size, **kwargs):
"""Creates a Conditional Neighbourhood Diagram for QTCBC as a basis for the HMM.
:param kwargs:
* qtc: list of lists containing all possible qtc states. Different for all 3 qtc versions.
:return: The transition matrix only allowing transitions according to the CND
"""
qtc = []
# creating list of possible states
for i in xrange(1, 4):
for j in xrange(1, 4):
qtc.append([i-2, j-2, np.NaN, np.NaN])
for i in xrange(1, 4):
for j in xrange(1, 4):
for k in xrange(1, 4):
for l in xrange(1, 4):
qtc.append([i-2, j-2, k-2, l-2])
# Calling parent to generate actual matrix
return super(QTCBCHMM, self)._create_transition_matrix(size=size, qtc=qtc)
def _symbol_to_qsr(self, symbols):
"""Transforming alphabet symbols to QTCBC states.
:param symbols: A list of symbols
:return: The list of corresponding qtc symbols
"""
ret = []
for s in symbols:
qtc = []
for c in s[1:-1]:
if c <= 9: # QTCB
qtc.append(self.qtcb.symbol_to_qsr(c))
else:
qtc.append(self.qtcc.symbol_to_qsr(c-9))
ret.append(self._qtc_num_to_str(qtc))
return ret
def _qsr_to_symbol(self, qsr_data):
"""Transforms a qtc state chain to a list of numbers
:param qsr_data: The list of lists of qtc strings or numpy array states
E.g.: [['++++','+++0','+++-,]] or [[[1,1,1,1],[1,1,1,0],[1,1,1,-1]]]
:return: A lists of lists of alphabet symbols corresponding to the given state chains
"""
qsr_data = np.array(qsr_data)
state_rep = []
for idx, element in enumerate(qsr_data):
if all(isinstance(x, str) or isinstance(x, unicode) for x in element):
element = self._qtc_str_to_num(element) # check if content is string instead of numbers and convert
element = np.array(element)
try:
d = element.shape[1]
except IndexError: # Not a list of lists of lists
return self._qsr_to_symbol([qsr_data])
state_num = np.array([0]) # Start symbol
#Not ellegant at all but necessary due to the nan values and the different multipliers for qtcb and qtcc
for x in element:
x = x[~np.isnan(x)]
d = x.shape[0]
mult = 3**np.arange(d-1, -1, -1)
num = ((x + 1)*mult).sum() + 1
state_num = np.append(
state_num,
num if d == 2 else num + 9 # Adding a 9 when the state is qtcc
)
state_num = np.append(state_num, self.num_possible_states-1) # End symbol
state_char = ''
for n in state_num:
state_char += chr(int(n)+32)
state_rep.append(state_num.tolist())
return state_rep
class QTCBCHMM(QTCHMMAbstractclass):
def __init__(self):
super(QTCBCHMM, self).__init__()
self.num_possible_states = 92 # Setting number of possible states: QTCBC + start and end
self.qtcb = QTCBHMM()
self.qtcc = QTCCHMM()
def _create_transition_matrix(self, size, **kwargs):
"""Creates a Conditional Neighbourhood Diagram for QTCBC as a basis for the HMM.
:param kwargs:
* qtc: list of lists containing all possible qtc states. Different for all 3 qtc versions.
:return: The transition matrix only allowing transitions according to the CND
"""
qtc = []
# creating list of possible states
for i in xrange(1, 4):
for j in xrange(1, 4):
qtc.append([i - 2, j - 2, np.NaN, np.NaN])
for i in xrange(1, 4):
for j in xrange(1, 4):
for k in xrange(1, 4):
for l in xrange(1, 4):
qtc.append([i - 2, j - 2, k - 2, l - 2])
# Calling parent to generate actual matrix
return super(QTCBCHMM, self)._create_transition_matrix(size=size,
qtc=qtc)
def _symbol_to_qsr(self, symbols):
"""Transforming alphabet symbols to QTCBC states.
:param symbols: A list of symbols
:return: The list of corresponding qtc symbols
"""
ret = []
for s in symbols:
qtc = []
for c in s[1:-1]:
if c <= 9: # QTCB
qtc.append(self.qtcb.symbol_to_qsr(c))
else:
qtc.append(self.qtcc.symbol_to_qsr(c - 9))
ret.append(self._qtc_num_to_str(qtc))
return ret
def _qsr_to_symbol(self, qsr_data):
"""Transforms a qtc state chain to a list of numbers
:param qsr_data: The list of lists of qtc strings or numpy array states
E.g.: [['++++','+++0','+++-,]] or [[[1,1,1,1],[1,1,1,0],[1,1,1,-1]]]
:return: A lists of lists of alphabet symbols corresponding to the given state chains
"""
qsr_data = np.array(qsr_data)
state_rep = []
for idx, element in enumerate(qsr_data):
if all(
isinstance(x, str) or isinstance(x, unicode)
for x in element):
element = self._qtc_str_to_num(
element
) # check if content is string instead of numbers and convert
element = np.array(element)
try:
d = element.shape[1]
except IndexError: # Not a list of lists of lists
return self._qsr_to_symbol([qsr_data])
state_num = np.array([0]) # Start symbol
#Not ellegant at all but necessary due to the nan values and the different multipliers for qtcb and qtcc
for x in element:
x = x[~np.isnan(x)]
d = x.shape[0]
mult = 3**np.arange(d - 1, -1, -1)
num = ((x + 1) * mult).sum() + 1
state_num = np.append(
state_num,
num if d == 2 else num +
9 # Adding a 9 when the state is qtcc
)
state_num = np.append(state_num,
self.num_possible_states - 1) # End symbol
state_char = ''
for n in state_num:
state_char += chr(int(n) + 32)
state_rep.append(state_num.tolist())
return state_rep
def __init__(self):
super(QTCBCHMM, self).__init__()
self.num_possible_states = 92 # Setting number of possible states: QTCBC + start and end
self.qtcb = QTCBHMM()
self.qtcc = QTCCHMM()
