def _calc_external(self, method):
"""Calculate NSB or BUB corrected entropy
"""
if method == 'nsb-ext':
from utils import nsb_entropy as entropy_fun
elif method == 'nsb':
# don't catch exceptions - just fail if can't import
from statk.wrap import nsb_entropy as entropy_fun
elif method == 'bub':
from statk.wrap import bub_entropy as entropy_fun
else:
raise ValueError, "Unknown external entropy method %s in _calc_external" % method
calc = self.calc
Hres = {}
if 'HX' in calc:
H = entropy_fun(self.PX, self.N, self.X_dim)
Hres['HX'] = H
if 'HY' in calc:
H = entropy_fun(self.PY, self.N, self.Y_dim)
Hres['HY'] = H
if 'HXY' in calc:
H = 0.0
for y in xrange(self.Y_dim):
H += self.PY[y] * entropy_fun(self.PXY[:, y], self.Ny[y],
self.X_dim)
Hres['HXY'] = H
if 'SiHXi' in calc:
H = 0.0
for i in xrange(self.X_n):
H += entropy_fun(self.PXi[:, i], self.N, self.X_m)
Hres['SiHXi'] = H
if 'HiXY' in calc:
H = 0.0
for i in xrange(self.X_n):
for y in xrange(self.Y_dim):
H += self.PY[y] * entropy_fun(self.PXiY[:, i, y],
self.Ny[y], self.X_m)
Hres['HiXY'] = H
if 'HiX' in calc:
H = entropy_fun(self.PiX, self.N, self.X_dim)
Hres['HiX'] = H
if 'ChiX' in calc:
print "Warning: No NSB or BUB correction applied for ChiX"
H = -(self.PX * malog2(
np.ma.array(self.PiX,
copy=False,
mask=(self.PiX <= np.finfo(np.float).eps)))).sum(
axis=0)
Hres['ChiX'] = H
# save result
self.__dict__['H_%s' % method] = Hres
def _calc_nsb(self, ext=False):
"""Calculate NSB corrected entropy
:Parameters:
ext : {False, True}, optional
Use external 'nsb-entropy' program vs STAT version
"""
if ext:
from utils import nsb_entropy
else:
# don't catch exceptions - just fail if can't import
from statk.wrap import nsb_entropy as _nsb_entropy
# for debugging
#nsb_entropy = lambda x,y,z: _nsb_entropy(x,y,z,verbose=True)
nsb_entropy = _nsb_entropy
calc = self.calc
H_nsb = {}
if 'HX' in calc:
H = nsb_entropy(self.PX, self.N, self.X_dim)
H_nsb['HX'] = H
if 'HY' in calc:
H = nsb_entropy(self.PY, self.N, self.Y_dim)
H_nsb['HY'] = H
if 'HXY' in calc:
H = 0.0
for y in xrange(self.Y_dim):
H += self.PY[y] * nsb_entropy(self.PXY[:,y], self.Ny[y], self.X_dim)
H_nsb['HXY'] = H
if 'SiHXi' in calc:
H = 0.0
for i in xrange(self.X_n):
H += nsb_entropy(self.PXi[:,i], self.N, self.X_m)
H_nsb['SiHXi'] = H
if 'HiXY' in calc:
H = 0.0
for i in xrange(self.X_n):
for y in xrange(self.Y_dim):
H += self.PY[y] * nsb_entropy(self.PXiY[:,i,y], self.Ny[y], self.X_m)
H_nsb['HiXY'] = H
if 'HiX' in calc:
H = nsb_entropy(self.PiX, self.N, self.X_dim)
H_nsb['HiX'] = H
if 'ChiX' in calc:
print "Warning: No NSB correction applied for ChiX"
H = -(self.PX*malog2(np.ma.array(self.PiX,copy=False,
mask=(self.PiX<=np.finfo(np.float).eps)))).sum(axis=0)
H_nsb['ChiX'] = H
if ext:
self.H_nsbext = H_nsb
else:
self.H_nsb = H_nsb
def _calc_external(self, method):
"""Calculate NSB or BUB corrected entropy
"""
if method == 'nsb-ext':
from utils import nsb_entropy as entropy_fun
elif method == 'nsb':
# don't catch exceptions - just fail if can't import
from statk.wrap import nsb_entropy as entropy_fun
elif method == 'bub':
from statk.wrap import bub_entropy as entropy_fun
else:
raise ValueError, "Unknown external entropy method %s in _calc_external"%method
calc = self.calc
Hres = {}
if 'HX' in calc:
H = entropy_fun(self.PX, self.N, self.X_dim)
Hres['HX'] = H
if 'HY' in calc:
H = entropy_fun(self.PY, self.N, self.Y_dim)
Hres['HY'] = H
if 'HXY' in calc:
H = 0.0
for y in xrange(self.Y_dim):
H += self.PY[y] * entropy_fun(self.PXY[:,y], self.Ny[y], self.X_dim)
Hres['HXY'] = H
if 'SiHXi' in calc:
H = 0.0
for i in xrange(self.X_n):
H += entropy_fun(self.PXi[:,i], self.N, self.X_m)
Hres['SiHXi'] = H
if 'HiXY' in calc:
H = 0.0
for i in xrange(self.X_n):
for y in xrange(self.Y_dim):
H += self.PY[y] * entropy_fun(self.PXiY[:,i,y], self.Ny[y], self.X_m)
Hres['HiXY'] = H
if 'HiX' in calc:
H = entropy_fun(self.PiX, self.N, self.X_dim)
Hres['HiX'] = H
if 'ChiX' in calc:
print "Warning: No NSB or BUB correction applied for ChiX"
H = -(self.PX*malog2(np.ma.array(self.PiX,copy=False,
mask=(self.PiX<=np.finfo(np.float).eps)))).sum(axis=0)
Hres['ChiX'] = H
# save result
self.__dict__['H_%s'%method] = Hres
def _calc_pt_plugin(self, pt):
"""Calculate direct entropies and apply PT correction if required """
calc = self.calc
pt_corr = lambda R: (R - 1) / (2 * self.N * np.log(2))
self.H_plugin = {}
if pt: self.H_pt = {}
# compute basic entropies
if 'HX' in calc:
H = ent(self.PX)
self.H_plugin['HX'] = H
if pt:
self.H_pt['HX'] = H + pt_corr(pt_bayescount(self.PX, self.N))
if 'HY' in calc:
H = ent(self.PY)
self.H_plugin['HY'] = H
if pt:
self.H_pt['HY'] = H + pt_corr(pt_bayescount(self.PY, self.N))
if 'HXY' in calc:
H = (self.PY * ent(self.PXY)).sum()
self.H_plugin['HXY'] = H
if pt:
for y in xrange(self.Y_dim):
H += pt_corr(pt_bayescount(self.PXY[:, y], self.Ny[y]))
self.H_pt['HXY'] = H
if 'SiHXi' in calc:
H = ent(self.PXi).sum()
self.H_plugin['SiHXi'] = H
if pt:
for x in xrange(self.X_n):
H += pt_corr(pt_bayescount(self.PXi[:, x], self.N))
self.H_pt['SiHXi'] = H
if 'HiXY' in calc:
H = (self.PY * ent(self.PXiY)).sum()
self.H_plugin['HiXY'] = H
if pt:
for x in xrange(self.X_n):
for y in xrange(self.Y_dim):
H += pt_corr(
pt_bayescount(self.PXiY[:, x, y], self.Ny[y]))
self.H_pt['HiXY'] = H
if 'HiX' in calc:
H = ent(self.PiX)
self.H_plugin['HiX'] = H
if pt:
# no PT correction for HiX
self.H_pt['HiX'] = H
if 'ChiX' in calc:
H = -(self.PX * malog2(
np.ma.array(self.PiX,
copy=False,
mask=(self.PiX <= np.finfo(np.float).eps)))).sum(
axis=0)
self.H_plugin['ChiX'] = H
if pt:
# no PT correction for ChiX
self.H_pt['ChiX'] = H
# for adelman style I(k;spike) (bits/spike)
if 'HXY1' in calc:
if self.Y_m != 2:
raise ValueError, \
"HXY1 calculation only makes sense for spike data, ie Y_m = 2"
H = ent(self.PXY[:, 1])
self.H_plugin['HXY1'] = H
if pt:
self.H_pt['HXY1'] = H + pt_corr(
pt_bayescount(self.PXY[:, 1], self.Ny[1]))
if 'ChiXY1' in calc:
if self.Y_m != 2:
raise ValueError, \
"ChiXY1 calculation only makes sense for spike data, ie Y_m = 2"
H = -np.ma.array(self.PXY[:, 1] * np.log2(self.PX),
copy=False,
mask=(self.PX <= np.finfo(np.float).eps)).sum()
self.H_plugin['ChiXY1'] = H
if pt:
# no PT for ChiXY1
self.H_pt['ChiXY1'] = H
def _calc_pt_plugin(self, pt):
"""Calculate direct entropies and apply PT correction if required """
calc = self.calc
pt_corr = lambda R: (R-1)/(2*self.N*np.log(2))
self.H_plugin = {}
if pt: self.H_pt = {}
# compute basic entropies
if 'HX' in calc:
H = ent(self.PX)
self.H_plugin['HX'] = H
if pt:
self.H_pt['HX'] = H + pt_corr(pt_bayescount(self.PX, self.N))
if 'HY' in calc:
H = ent(self.PY)
self.H_plugin['HY'] = H
if pt:
self.H_pt['HY'] = H + pt_corr(pt_bayescount(self.PY, self.N))
if 'HXY' in calc:
H = (self.PY * ent(self.PXY)).sum()
self.H_plugin['HXY'] = H
if pt:
for y in xrange(self.Y_dim):
H += pt_corr(pt_bayescount(self.PXY[:,y], self.Ny[y]))
self.H_pt['HXY'] = H
if 'SiHXi' in calc:
H = ent(self.PXi).sum()
self.H_plugin['SiHXi'] = H
if pt:
for x in xrange(self.X_n):
H += pt_corr(pt_bayescount(self.PXi[:,x],self.N))
self.H_pt['SiHXi'] = H
if 'HiXY' in calc:
H = (self.PY * ent(self.PXiY)).sum()
self.H_plugin['HiXY'] = H
if pt:
for x in xrange(self.X_n):
for y in xrange(self.Y_dim):
H += pt_corr(pt_bayescount(self.PXiY[:,x,y],self.Ny[y]))
self.H_pt['HiXY'] = H
if 'HiX' in calc:
H = ent(self.PiX)
self.H_plugin['HiX'] = H
if pt:
# no PT correction for HiX
self.H_pt['HiX'] = H
if 'ChiX' in calc:
H = -(self.PX*malog2(np.ma.array(self.PiX,copy=False,
mask=(self.PiX<=np.finfo(np.float).eps)))).sum(axis=0)
self.H_plugin['ChiX'] = H
if pt:
# no PT correction for ChiX
self.H_pt['ChiX'] = H
# for adelman style I(k;spike) (bits/spike)
if 'HXY1' in calc:
if self.Y_m != 2:
raise ValueError, \
"HXY1 calculation only makes sense for spike data, ie Y_m = 2"
H = ent(self.PXY[:,1])
self.H_plugin['HXY1'] = H
if pt:
self.H_pt['HXY1'] = H + pt_corr(pt_bayescount(self.PXY[:,1],self.Ny[1]))
if 'ChiXY1' in calc:
if self.Y_m != 2:
raise ValueError, \
"ChiXY1 calculation only makes sense for spike data, ie Y_m = 2"
H = -np.ma.array(self.PXY[:,1]*np.log2(self.PX),copy=False,
mask=(self.PX<=np.finfo(np.float).eps)).sum()
self.H_plugin['ChiXY1'] = H
if pt:
# no PT for ChiXY1
self.H_pt['ChiXY1'] = H
