def peaksearch(self, frm):
# -> f.pixels['localmax']
sparseframe.sparse_localmax(frm)
# -> f.pixels['connectedpixels']
sparseframe.sparse_connected_pixels(frm,
threshold=np.finfo(np.float32).min)
# which localmax peaks overlap each other
adj = sparseframe.overlaps(frm, 'localmax', frm, 'connectedpixels')
r, c = self.adj2overlap(adj)
return frm, r, c
def newpks(hf):
""" do a peak search in a sparse frame series """
blbs = []
with h5py.File(hf, "r") as h:
stem = list(h)[0]
grp = h[stem]
for g in range(900):
f = sparseframe.from_hdf_group(grp[str(g)])
sparseframe.sparse_localmax(f)
blbs.append(sparseframe.sparse_moments(f, "intensity", "localmax"))
return stem, blbs
def newpks(hf, g='measurement/frelon3'):
""" do a peak search in a sparse frame series """
blbs = []
with h5py.File(hf, "r") as h:
# sort as numbers:
dsu = [(float(v), v) for v in list(h)]
dsu.sort()
for _, scan in dsu:
print(scan, end=" ")
sys.stdout.flush()
if g is None:
gscan = h[scan]
else:
gscan = h[scan][g]
for fgrp in sorted(list(gscan)):
f = sparseframe.from_hdf_group(gscan[fgrp])
sparseframe.sparse_localmax(f)
blbs.append(
sparseframe.sparse_moments(f, "intensity", "localmax"))
return blbs