def compute_design(self, name="", verbose=1):
"""Sample the formula on the grid
Parameters
----------
name="", string, that characterized the model name
verbose=1, int, verbosity mode
Note: self.conditions and self.drift must be defined beforhand
"""
if self.protocol == None:
print "The selected session does not exists"
return None
self.formula = self.conditions + self.drift
temp = build_dmtx(self.formula, self.frametimes).T
## Force the design matrix to be full rank at working precision
self._design, self._design_cond = full_rank(temp)
# complete the names with the drift terms
for k in range(len(self.drift.terms)-1):
self._names.append('drift_%d'%(k+1))
self._names.append('constant')
if verbose:
self.show()
self.names = self._names
misc = ConfigObj(self.misc_file)
misc[self.model]["regressors_%s" % name] = self._names
misc[self.model]["design matrix cond"] = self._design_cond
misc.write()
return self._design
def compute_fir_design(self, drift=None, o=1, l=1, name=""):
"""
deprecated
"""
if self.protocol == None:
print "The selected session does not exists"
return None
misc = ConfigObj(self.misc_file)
temp = np.zeros((len(self.frametimes), (o * len(self.protocol.events))))
diff = l / o
self.names = []
i = 0
for event in misc["tasks"]:
if self.protocol.events.has_key(event):
for j in range(o):
if j == 0:
self.names.append("%s" % (event))
else:
self.names.append("%s_d%i" % (event, j))
for t in self.protocol.events[event].times:
base = np.argmax(self.frametimes > t)
for k in range(diff):
temp[base + (k + j * diff), j + i * o] = 1
i += 1
self._design, self._design_cond = full_rank(temp)
if drift == 0:
drm = np.ones((self._design.shape[0],1))
elif drift == cosine_drift:
drm = cosine_matrix(self.frametimes).T
elif drift == canonical_drift:
drm = _drift(self.frametimes).T
else:
drm = drift
drml = drm.shape[1]
for i in range(drml):
self.names.append('(drift:%i)' % i)
self._design = np.column_stack((self._design, drm))
misc[self.model]["regressors_%s" % name] = self.names
misc.write()
