def segment(fname, bg, datamem, datapath, block=128, nsigma=3.):
""" Does a segmentation of a single file/frame """
imo = fabio.open(os.path.join(datapath, fname)) # data
# print(fname)
oname = os.path.split(os.path.splitext(fname)[0])[-1]
# subtract dark and promote to float32 (without overflow on uint16 I hope)
cImageD11.uint16_to_float_darksub(datamem.ravel(), bg.ravel(),
imo.data.ravel())
# check offset and noise
avg, sig = cImageD11.array_mean_var_cut(datamem, cut=nsigma)
# remove the frelon lines
datamem.shape = imo.data.shape[0] * (imo.data.shape[1] // block), block
cImageD11.frelon_lines(datamem, avg + sig * nsigma)
datamem.shape = imo.data.shape
# overwrites datamem (should copy before if you want it
avg, sig = cImageD11.array_mean_var_cut(datamem, cut=nsigma)
threshold = avg + sig * nsigma
# select the pixels to keep:
rawmask = datamem > threshold
cleanmask = rawmask.astype(np.int8)
cImageD11.clean_mask(rawmask.astype(np.int8), cleanmask)
# save some metadata:
header = {"filename": fname}
for k in ("SRCUR", "time_of_day"):
if k in imo.header:
header[k] = imo.header[k]
spar = sparseframe.from_data_mask(cleanmask, datamem, header)
return spar
def binary_clean( mask ):
"""
Remove the one pixel stuff
"""
ret = np.zeros(mask.shape, np.int8)
cImageD11.clean_mask( mask.astype( np.int8 ), ret )
return ret
def segment(fname, bg):
""" Does a segmentation of a single file/frame """
imb = fabio.open(fname).data - bg
imc = fix_frelon_lines(imb, block=128)
s = sigma_cut(imc)
m = imc > s
cleanmask = m.astype(np.int8)
cImageD11.clean_mask(m.astype(np.int8), cleanmask)
spar = to_scipy_csr(imc, cleanmask)
return spar
def segment(fname, bg):
""" Does a segmentation of a single file/frame """
imo = fabio.open(fname)
imb = imo.data.astype(np.float32) - bg
#print (type(imb))
imc = fix_frelon_lines(imb, block=128)
s = sigma_cut(imc)
m = imc > s
cleanmask = m.astype(np.int8)
cImageD11.clean_mask(m.astype(np.int8), cleanmask)
spar = to_coo(imc, cleanmask, fname)
spar.sigma_cut = s
spar.con_labels()
spar.max_labels()
print(fname, spar.nmlabel)
return spar
def binary_clean(mask, out=None):
"""
Remove the one pixel stuff
"""
if out is None:
out = np.zeros(mask.shape, np.int8)
npx = cImageD11.clean_mask(mask.astype(np.int8), out)
return npx, out
def test1(self):
testmask = np.zeros(self.src.shape, np.int8)
npx = cImageD11.clean_mask(self.src.astype(np.int8), testmask)
if 0:
print('npx=', npx)
print(self.src)
print(self.src.view(dtype=np.int8))
print(testmask)
print(testmask.sum())
self.assertTrue(self.target.sum() == npx)
self.assertTrue((testmask == self.target).all())
def filt(self, input):
cln = np.empty(input.shape, 'b')
npx = cImageD11.clean_mask(input, cln)
return cln
import numpy as np from ImageD11 import cImageD11 m = np.zeros((10,10),np.int8) mm = m.copy() m[5,5:7]=1 m[2,2]=1 cImageD11.clean_mask(m, mm) print(mm)
