def __init__(self,
data,
S,
w_augments,
h_augments=None,
num_bases=4,
mask_zeros=False,
**kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
if mask_zeros:
mask = (data != 0).astype(int)
else:
mask = np.ones(data.shape)
self.S = S * mask
self.S_sqrt = np.sqrt(S)
self.comp_S = (S - 1) * -1
self.w_augments = w_augments
self.h_augments = h_augments
S_shape = S.shape
# Make sure augments have the right dimensions
assert w_augments.shape[0] == S_shape[0]
assert w_augments.shape[1] <= num_bases
# set w_augments index
m_range_w = list(range(0, S_shape[0]))
n_range_w = list(range(num_bases - w_augments.shape[1], num_bases))
self.w_augments_idx = np.ix_(m_range_w, n_range_w)
def __init__(self, data, S, w_augments, h_augments=None, num_bases=4,
mask_zeros=False, **kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
if mask_zeros:
mask = (data != 0).astype(int)
else:
mask = np.ones(data.shape)
self.S = S * mask
self.S_sqrt = np.sqrt(S)
self.comp_S = (S - 1) * -1
self.w_augments = w_augments
self.h_augments = h_augments
S_shape = S.shape
# Make sure augments have the right dimensions
assert w_augments.shape[0] == S_shape[0]
assert w_augments.shape[1] <= num_bases
# set w_augments index
m_range_w = list(range(0, S_shape[0]))
n_range_w = list(range(num_bases - w_augments.shape[1],
num_bases))
self.w_augments_idx = np.ix_(m_range_w, n_range_w)
def factorize(self, show_progress=False, compute_w=True, compute_h=True,
compute_err=True, niter=1):
""" Factorize s.t. WH = data
Parameters
----------
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH|.
"""
PyMFBase.factorize(self, niter=1, show_progress=show_progress,
compute_w=compute_w, compute_h=compute_h,
compute_err=compute_err)
def __init__(self,
data,
num_bases=4,
augments=None,
smoothness=100,
**kwargs):
# Setup
self.num_bases = num_bases
self.smoothness = smoothness
data_shape = data.shape
self.w_outer = data_shape[0]
self.h_outer = data_shape[1]
self.augments = augments
if self.augments is not None:
# Make sure augments have the right dimensions
assert augments.shape[0] == data.shape[0]
assert augments.shape[1] <= num_bases
m_range = list(range(0, data.shape[0]))
n_range = list(range(num_bases - augments.shape[1], num_bases))
self.augments_idx = np.ix_(m_range, n_range)
PyMFBase.__init__(self, data, num_bases, **kwargs)
self._parse_args(**kwargs)
def factorize(self, show_progress=False, compute_w=True, compute_h=True,
compute_err=True, niter=1):
""" Factorize s.t. WH = data
Parameters
----------
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH|.
"""
PyMFBase.factorize(self, niter=1, show_progress=show_progress,
compute_w=compute_w, compute_h=compute_h,
compute_err=compute_err)
def __init__(self, data, num_bases=4, augments=None, smoothness=100, **kwargs):
# Setup
self.num_bases = num_bases
self.smoothness = smoothness
data_shape = data.shape
self.w_outer = data_shape[0]
self.h_outer = data_shape[1]
self.augments = augments
if self.augments is not None:
# Make sure augments have the right dimensions
assert augments.shape[0] == data.shape[0]
assert augments.shape[1] <= num_bases
m_range = list(range(0, data.shape[0]))
n_range = list(range(num_bases - augments.shape[1], num_bases))
self.augments_idx = np.ix_(m_range, n_range)
PyMFBase.__init__(self, data, num_bases, **kwargs)
self._parse_args(**kwargs)
def __init__(self, data, S, num_bases=4, mask_zeros=False, **kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
if mask_zeros:
mask = (data != 0).astype(int)
else:
mask = np.ones(data.shape)
self.S = S * mask
self.S_sqrt = np.sqrt(S)
self.comp_S = (S - 1) * -1
def __init__(self, data, S, num_bases=4, mask_zeros=False, **kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
if mask_zeros:
mask = (data != 0).astype(int)
else:
mask = np.ones(data.shape)
self.S = S * mask
self.S_sqrt = np.sqrt(S)
self.comp_S = (S - 1) * -1
def __init__(self, data, num_bases=0, center_mean=True, **kwargs):
PyMFBase.__init__(self, data, num_bases=num_bases)
# center the data around the mean first
self._center_mean = center_mean
if self._center_mean:
# copy the data before centering it
self._data_orig = data
self._meanv = self._data_orig[:,:].mean(axis=1).reshape(-1,1)
self.data = self._data_orig - self._meanv
else:
self.data = data
def __init__(self, data, num_bases=0, center_mean=True, **kwargs):
PyMFBase.__init__(self, data, num_bases=num_bases)
# center the data around the mean first
self._center_mean = center_mean
if self._center_mean:
# copy the data before centering it
self._data_orig = data
self._meanv = self._data_orig[:,:].mean(axis=1).reshape(-1,1)
self.data = self._data_orig - self._meanv
else:
self.data = data
def __init__(self, data, w_augments, h_augments=None, num_bases=4, **kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
self.w_augments = w_augments
self.h_augments = h_augments
S_shape = data.shape
# Make sure augments have the right dimensions
assert w_augments.shape[0] == S_shape[0]
assert w_augments.shape[1] <= num_bases
#assert h_augments.shape[0] == S_shape[1]
# set w_augments index
m_range_w = list(range(0, S_shape[0]))
n_range_w = list(range(num_bases - w_augments.shape[1],
num_bases))
self.w_augments_idx = np.ix_(m_range_w, n_range_w)
def factorize(self,
niter=10,
compute_w=True,
compute_h=True,
show_progress=False,
compute_err=True):
""" Factorize s.t. WH = data
Parameters
----------
niter : int
number of iterations.
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH| for each iteration.
"""
# init some learning parameters
self._lamb_W = 1.0 / niter
self._lamb_H = 1.0 / niter
PyMFBase.factorize(self,
niter=niter,
compute_w=compute_w,
compute_h=compute_h,
show_progress=show_progress,
compute_err=compute_err)
def __init__(self,
data,
w_augments,
h_augments=None,
num_bases=4,
**kwargs):
PyMFBase.__init__(self, data, num_bases, **kwargs)
self.w_augments = w_augments
self.h_augments = h_augments
S_shape = data.shape
# Make sure augments have the right dimensions
assert w_augments.shape[0] == S_shape[0]
assert w_augments.shape[1] <= num_bases
#assert h_augments.shape[0] == S_shape[1]
# set w_augments index
m_range_w = list(range(0, S_shape[0]))
n_range_w = list(range(num_bases - w_augments.shape[1], num_bases))
self.w_augments_idx = np.ix_(m_range_w, n_range_w)
def factorize(self,
niter=10,
compute_w=True,
compute_h=True,
show_progress=False,
compute_err=True):
""" Factorize s.t. WH = data
Parameters
----------
niter : int
number of iterations.
show_progress : bool
print some extra information to stdout.
compute_h : bool
iteratively update values for H.
compute_w : bool
iteratively update values for W.
compute_err : bool
compute Frobenius norm |data-WH| after each update and store
it to .ferr[k].
Updated Values
--------------
.W : updated values for W.
.H : updated values for H.
.ferr : Frobenius norm |data-WH| for each iteration.
"""
# init some learning parameters
self._lamb_W = 1.0/niter
self._lamb_H = 1.0/niter
PyMFBase.factorize(self, niter=niter, compute_w=compute_w,
compute_h=compute_h, show_progress=show_progress,
compute_err=compute_err)
def __init__(self, data, num_bases=4, lamb=2.0):
# call inherited method
PyMFBase.__init__(self, data, num_bases=num_bases)
self._lamb = lamb
def __init__(self, data, k=-1, num_bases=4):
# call inherited method
PyMFBase.__init__(self, data, num_bases=num_bases)
self._k = k
if self._k == -1:
self._k = num_bases
def __init__(self, data, k=-1, num_bases=4):
# call inherited method
PyMFBase.__init__(self, data, num_bases=num_bases)
self._k = k
if self._k == -1:
self._k = num_bases