def _get_indices(self,element,labels,return_indices,mode):
r'''
This is the actual method for getting indices, but should not be called
directly.
'''
if mode == 'union':
union = sp.zeros_like(self._get_info(element=element,label='all'),dtype=bool)
for item in labels: #iterate over labels list and collect all indices
union = union + self._get_info(element=element,label=item)
ind = union
elif mode == 'intersection':
intersect = sp.ones_like(self._get_info(element=element,label='all'),dtype=bool)
for item in labels: #iterate over labels list and collect all indices
intersect = intersect*self._get_info(element=element,label=item)
ind = intersect
elif mode == 'not_intersection':
not_intersect = sp.zeros_like(self._get_info(element=element,label='all'),dtype=int)
for item in labels: #iterate over labels list and collect all indices
info = self._get_info(element=element,label=item)
not_intersect = not_intersect + sp.int8(info)
ind = (not_intersect == 1)
elif mode == 'none':
none = sp.zeros_like(self._get_info(element=element,label='all'),dtype=int)
for item in labels: #iterate over labels list and collect all indices
info = self._get_info(element=element,label=item)
none = none - sp.int8(info)
ind = (none == 0)
if return_indices: ind = sp.where(ind==True)[0]
return ind
def get_incidence_matrix(self):
ets = sp.array(self.ecotypes)
unique_ets = []
i = 0
while i < len(ets):
et = ets[i]
unique_ets.append(et)
while i < len(ets) and ets[i] == et: #The ecotypes are assumed to be sorted
i += 1
Z = sp.int8(sp.mat(ets).T == sp.mat(unique_ets))
return Z
def get_incidence_matrix(self):
ets = sp.array(self.ecotypes)
unique_ets = []
i = 0
while i < len(ets):
et = ets[i]
unique_ets.append(et)
while i < len(ets) and ets[
i] == et: #The ecotypes are assumed to be sorted
i += 1
Z = sp.int8(sp.mat(ets).T == sp.mat(unique_ets))
return Z
def get_incidence_matrix(self, pid):
ets = sp.array(self.phen_dict[pid]['ecotypes'])
unique_ets = []
i = 0
while i < len(ets):
et = ets[i]
unique_ets.append(et)
while i < len(ets) and ets[i] == et: #The ecotypes are assumed to be sorted
i += 1
# unique_ets = sp.mat(sp.unique(ets))
Z = sp.int8(sp.mat(ets).T == sp.mat(unique_ets))
#print Z
return Z
def get_incidence_matrix(self, pid):
ets = sp.array(self.phen_dict[pid]['ecotypes'])
unique_ets = []
i = 0
while i < len(ets):
et = ets[i]
unique_ets.append(et)
while i < len(ets) and ets[i] == et: #The ecotypes are assumed to be sorted
i += 1
# unique_ets = sp.mat(sp.unique(ets))
Z = sp.int8(sp.mat(ets).T == sp.mat(unique_ets))
#print Z
return Z
