def make_uc_pipe(dic, data, dim=-1):
if dim == -1:
dim = data.ndim - 1 # last dimention
fn = "FDF" + str(int(dic["FDDIMORDER"][data.ndim - 1 - dim]))
size = float(data.shape[dim])
# check for quadrature in indirect dimentions
if (dic[fn + "QUADFLAG"] != 1) and (dim != data.ndim - 1):
size = size / 2.
cplx = True
else:
cplx = False
sw = dic[fn + "SW"]
if sw == 0.0:
sw = 1.0
obs = dic[fn + "OBS"]
if obs == 0.0:
obs = 1.0
car = dic[fn + "CAR"] * obs
# NMRPipe keeps the carrier constant during extractions storing the
# location of this point as CENTER. This may not be the actual "center" of
# the spectrum and may not even be a valid index in that dimension. We need
# to re-center the carrier value so that actually represents the
# frequency of the central point in the dimension.
if dic[fn + "X1"] != 0. or dic[fn + "XN"] != 0.:
car = car + sw / size * (dic[fn + "CENTER"] - 1. - size / 2.)
return unit_conversion(size, cplx, sw, obs, car)
def __new__(cls, input_array, udic, parent=None, uc=None):
if input_array.ndim == 1:
cls = NMRSpectrum1D
elif input_array.ndim == 2:
cls = NMRSpectrum2D
obj = np.asarray(input_array).view(cls)
if parent is None:
history = Workflow()
original = DataUdic(input_array, udic)
flags = {}
annotation = []
else:
history = parent.history
original = parent.original
flags = parent.spec_flags
annotation = parent.annotation
if uc is None: uc = parent.uc
# add the new attribute to the created instance
if uc is None:
uc = [unit_conversion(udic[i]['size'],
udic[i]['complex'],
udic[i]['sw'],
udic[i]['obs'],
udic[i]['car'])
for i in range(0, udic['ndim'])]
if hasattr(input_array, 'annotation'):
obj.annotation = input_array.annotation
obj.udic = udic
obj.uc = uc
obj.history = history
obj.original = original
obj.spec_flags = flags
obj.annotation = annotation
return obj
