def readXYZ(self):
# Create coordinate space based on x,y,z dimensions, and multiply by affine matrix
# Examples shown if xdim = 3, ydim=4, zdim=5
# Create R row variable [1 2 3 1 2 3...] ydim * zdim times
Rrow = list(scinu.seq(1,self.xdim)) * (self.ydim*self.zdim)
# Create C row variable [1 1 1 2 2 2 3 3 3 4 4 4 1 1 1 2 2 2...] zdim X
Crow = []
for y in range(1,self.ydim+1):
for x in range(0,self.xdim):
Crow.append(y)
Crow = Crow * self.zdim
# Create P row variable [ each of 1:zdim xdim*ydim times ]
Prow = []
for z in range(1,self.zdim+1):
holder = ([z] * self.xdim*self.ydim)
for i in holder:
Prow.append(i)
# Create row of 1s of length zdim*xdim*ydim so we can multiply matrices
onedim = [1] * self.xdim * self.ydim * self.zdim
# Stack each row on top of one another
self.RCP = np.vstack((Rrow,Crow,Prow,onedim))
# Make it into a matrix
self.RCP = scinu.mat(self.RCP)
# Grab the first three rows of the affine transformation matrix (4th is for time)
affXYZ = self.aff[0:3]
# Multiply affine transformation matrix by coordinate data to go from coordinate --> MNI space
self.XYZ = affXYZ * self.RCP
def readXYZ(self):
# I couldn't get this method to work, but will keep to try again...
# R, C, P = scinu.ndgrid(scinu.seq(1,3),scinu.seq(1,4),scinu.seq(1,5))
# Create coordinate space based on x,y,z dimensions, and multiply by affine matrix
# Examples shown if xdim = 3, ydim=4, zdim=5
# Create R row variable [1 2 3 1 2 3...] ydim * zdim times
Rrow = list(scinu.seq(1, self.xdim)) * (self.ydim * self.zdim)
# Create C row variable [1 1 1 2 2 2 3 3 3 4 4 4 1 1 1 2 2 2...] zdim X
Crow = []
for y in range(1, self.ydim + 1):
for x in range(0, self.xdim):
Crow.append(y)
Crow = Crow * self.zdim
# Create P row variable [ each of 1:zdim xdim*ydim times ]
Prow = []
for z in range(1, self.zdim + 1):
holder = ([z] * self.xdim * self.ydim)
for i in holder:
Prow.append(i)
# Create row of 1s of length zdim*xdim*ydim so we can multiply matrices
onedim = [1] * self.xdim * self.ydim * self.zdim
# Stack each row on top of one another
self.RCP = np.vstack((Rrow, Crow, Prow, onedim))
# Make it into a matrix
self.RCP = scinu.mat(self.RCP)
# Grab the first three rows of the affine transformation matrix (4th is for time)
affXYZ = self.aff[0:3]
# Multiply affine transformation matrix by coordinate data to go from coordinate --> MNI space
self.XYZ = affXYZ * self.RCP
def readAff(self):
self.aff = scinu.mat(self.img.get_affine())
def readAff(self):
self.aff = scinu.mat(self.img.get_affine())
