def __init__(self, fn):
arr = Mrc.bindFile(fn)
self.pxlsiz = arr.Mrc.hdr.d
self.waves = arr.Mrc.hdr.wave[:arr.Mrc.hdr.NumWaves].copy()
self.refwave = self.waves[arr.Mrc.hdr.n1]
self.XYsize = arr.Mrc.hdr.Num[:2]
self.nt = arr.Mrc.hdr.NumTimes
self.nw = len(self.waves)
self.t = 0
self.dtype = arr.dtype.type
if 'SIR' in fn:
self.mid = 512
else:
self.mid = 256
if arr.Mrc.hdr.n2 == 1:
parm = arr
nentry = aligner.NUM_ENTRY
self.map_str = 'None'
else:
parm = arr.Mrc.extFloats[:arr.Mrc.hdr.NumTimes *
arr.Mrc.hdr.NumWaves, :arr.Mrc.hdr.
NumFloats]
nentry = arr.Mrc.hdr.NumFloats
self.nz = arr.Mrc.hdr.Num[-1] / (arr.Mrc.hdr.NumTimes *
arr.Mrc.hdr.NumWaves * 2)
if self.nz == 1:
self.map_str = 'Projection'
else:
self.map_str = 'Section-wise'
parm = parm.reshape(
(arr.Mrc.hdr.NumTimes, arr.Mrc.hdr.NumWaves, nentry))
self.alignParms = parm.copy() # writable
del arr, parm
def makeFiles(fns, std=10, div_step=50, div_max=800): #1000):
"""
makes a series of images added Gaussain and Poisson noise
std: standard deviation for Gaussian, and mean=std*10 for Poisson
div_step: the step that the original image is divided while noise is added
div_max: the maximum value that the original image is divided
return output filenames
"""
outs = []
for fn in fns:
a = Mrc.bindFile(fn)
for ns in NOISE_STATS:
hdr = mrcIO.makeHdr_like(a.Mrc.hdr)
if ns == NOISE_STATS[0]:
noise = F.noiseArr(a.shape, stddev=std, mean=0)
else:
noise = F.poissonArr(a.shape, mean=std * 10)
steps = range(div_step, div_max + div_step, div_step)
ag = [a / c + noise for c in steps]
for i, arr in enumerate(ag):
val = steps[i]
if hasattr(arr, "Mrc"):
del arr.Mrc
if arr.dtype == N.float64:
arr = arr.astype(N.float32)
hdr.PixelType = 2
out = a.Mrc.path + ns + '%04d' % val
Mrc.save(arr, out, ifExists='overwrite', hdr=hdr)
outs.append(out)
return outs