def shave_matrix(rawMatrix, mask, tools=TM_tools):
if tools:
return TM_tools.shaveMatrix(rawMatrix, mask)
else:
mask = np.ones(rawMatrix.shape[0], dtype=bool)
for irow,row in enumerate(rawMatrix):
if rawMatrix[irow,:].sum() == 0.0 and rawMatrix[:,irow].sum() == 0.0:
mask[irow] = False
return rawMatrix[...,mask][mask,...], mask
def normalize_matrix(shavedMatrix, tools=TM_tools):
if tools:
return TM_tools.normalizeMatrix(shavedMatrix)
else:
for irow, row in enumerate(shavedMatrix):
total = row.sum()
if total != 0.0:
shavedMatrix[irow] = row/total
return shavedMatrix
def build_raw_matrix(first_iter, last_iter, westH5, assignments, init_matrix, tools=TM_tools):
'''Build the raw matrix, iteration window is left exclusive'''
dim = init_matrix.shape[0]
for iiter in range(first_iter, last_iter):
print "Calculating iteration %i"%(iiter)
iter_obj = westH5.openFile['iterations']['iter_%08d'%(iiter)]
weights = iter_obj['seg_index']['weight'][...]
if tools:
curr_assignments = np.array(assignments[iiter-1], dtype=np.uint16)
init_matrix = TM_tools.addIterToMatrix(curr_assignments, weights, init_matrix, dim)
else:
for iwalk, walkerObj in enumerate(assignments[iiter-1]):
print walkerObj.dtype, walkerObj.shape
for ipoint, point in enumerate(walkerObj):
if ipoint == 0:
prev_point = point
if ipoint > 0 and point < dim:
# Here it's now a transition between prev_point -> point
#print prev_point, point, iwalk
init_matrix[prev_point][point] += weights[iwalk]
if point == dim:
break
return init_matrix
