def __init__(self, data_header, cube_header, ng=1, **kwargs):
self.data_header = data_header
self.map_header = cube_header
xout = dataarray_from_header(data_header)
xout[:] = 0
xin = fa.fitsarray_from_header(cube_header)
xin.header = dict(xin.header)
xin[:] = 0
self.xin = xin
self.xout = xout
def matvec(x):
y = dataarray_from_header(data_header)
y[:] = 0
for i in xrange(ng):
yi = y[..., i::ng]
yi.header = y.header[i::ng]
projector4d(yi, x, **kwargs)
del yi
return y
def rmatvec(x):
y = fa.fitsarray_from_header(cube_header)
y[:] = 0
for i in xrange(ng):
xi = x[..., i::ng]
xi.header = xi.header[i::ng]
backprojector4d(xi, y, **kwargs)
del xi
return y
lo.NDSOperator.__init__(self, xin=xin, xout=xout, matvec=matvec, rmatvec=rmatvec, dtype=xout.dtype)
def __init__(self, data_header, cube_header, **kwargs):
self.data_header = data_header
self.map_header = dict(cube_header)
xin = fa.fitsarray_from_header(cube_header)
xin.header = dict(xin.header)
xin[:] = 0
xout = dataarray_from_header(data_header)
xout[:] = 0
self.xin = xin
self.xout = xout
shapein = xin.shape
shapeout = xout.shape
def matvec(x):
x = fa.InfoArray(data=x, header=dict(cube_header))
y = xout
y[:] = 0.
projector(y, x, **kwargs)
return y
def rmatvec(x):
x = fa.InfoArray(data=x, header=data_header)
y = xin
y[:] = 0.
backprojector(x, y, **kwargs)
return y
lo.NDSOperator.__init__(self, shapein, shapeout, xin=xin, xout=xout,
matvec=matvec, rmatvec=rmatvec, dtype=xout.dtype)
def matvec(x):
y = dataarray_from_header(data_header)
y[:] = 0
for i in xrange(ng):
yi = y[..., i::ng]
yi.header = y.header[i::ng]
projector4d(yi, x, **kwargs)
del yi
return y
def siddon_lo(data_header, cube_header, obstacle=None):
"""
A linear operator performing projection and backprojection using
Siddon.
"""
data = dataarray_from_header(data_header)
data[:] = 0
cube = fa.fitsarray_from_header(cube_header)
cube[:] = 0
def matvec(x):
y = dataarray_from_header(data_header)
y[:] = 0
projector(y, x, obstacle=obstacle)
return y
def rmatvec(x):
y = fa.fitsarray_from_header(cube_header)
y[:] = 0
backprojector(x, y, obstacle=obstacle)
return y
return lo.ndsubclass(cube, data, matvec=matvec, rmatvec=rmatvec, dtype=data.dtype)
def matvec(x):
y = dataarray_from_header(data_header)
y[:] = 0
projector4d(y, x, obstacle=obstacle)
return y
