def debug(log, msg, level=logging.DEBUG):
"""
do logging
"""
levelName = _getLevelName(level)
exec('log.%s(msg)' % levelName)
level = _getLevel(level)
if log.getEffectiveLevel() <= level:
try:
Y.refresh()
except:
pass
else:
pass
def debug(log, msg, level=logging.DEBUG):
"""
do logging
"""
levelName = _getLevelName(level)
exec('log.%s(msg)' % levelName)
level = _getLevel(level)
if log.getEffectiveLevel() <= level:
try:
Y.refresh()
except:
pass
else:
pass
def main(*args):
"""
aks for filenames
tells you finished files using shell Messages
"""
import wx
from Priithon.all import Y
dlg = wx.FileDialog(None,
'Choose image files',
style=wx.OPEN | wx.MULTIPLE | wx.CHANGE_DIR)
if dlg.ShowModal() == wx.ID_OK:
fns = dlg.GetPaths()
if fns:
if isinstance(fns, basestring):
fns = [fns]
for fn in fns:
#out = os.path.extsep.join((fn, DEF_EXT))
out = byteSwap(fn) #, out, DEF_BYTE)
if hasattr(Y, 'shellMessage'):
Y.shellMessage(out.join(('#', '---done\n')))
else:
print out.join(('#', '---done\n'))
Y.refresh()
def beads_analyzeBeads(fn,
thre_sigma=1.,
refwave=2,
nbeads=60,
win=5,
maxdist=600,
maxrefdist=5): #0.6, maxrefdist=0.005):
"""
maxdist: nm
maxrefdist: nm
return dic
"""
from PriCommon import mrcIO, imgFilters, imgFit, imgGeo, microscope
from Priithon.all import Y
h = mrcIO.MrcReader(fn)
if refwave >= h.nw:
raise ValueError, 'reference wave does not exists'
shape = h.hdr.Num[::-1].copy()
shape[0] /= (h.hdr.NumTimes * h.hdr.NumWaves)
pzyx = h.hdr.d[::-1]
NA = 1.35
difflimitYX = microscope.resolution(NA, h.hdr.wave[refwave]) / 1000.
difflimit = N.array([difflimitYX * 2, difflimitYX, difflimitYX]) / pzyx
print 'diffraction limit (px) is:', difflimit
simres = difflimit / 1.5 #2.
arr = h.get3DArr(w=refwave).copy()
ndim = arr.ndim
me = arr.mean()
sd = arr.std()
thre = me + sd * thre_sigma
sigma = 1.5
zyxs = []
#found = []
sigmas = []
i = 0
pmax = 0
failed = 0
while i < nbeads:
Y.refresh()
amax, z, y, x = U.findMax(arr)
zyx = N.array((z, y, x), N.float32)
#found.append(zyx)
zyx0 = N.where(zyx > simres, zyx - simres, 0).astype(N.int)
zyx1 = N.where(zyx + simres < shape, zyx + simres, shape).astype(N.int)
rmslice = [slice(*zyx) for zyx in zip(zyx0, zyx1)]
if failed > 10:
raise RuntimeError
break
elif amax == pmax:
arr[rmslice] = me
elif amax > thre:
# Gaussian fitting
try:
ret, check = imgFit.fitGaussianND(arr, [z, y, x][-ndim:],
sigma, win)
except IndexError: # too close to the edge
arr[rmslice] = me
print 'Index Error, too close to the edge', z, y, x
failed += 1
continue
if check == 5:
arr[rmslice] = me
print 'fit failed', z, y, x
failed += 1
continue
# retreive results
v = ret[1]
zyx = ret[2:2 + ndim]
sigma = ret[2 + ndim:2 + ndim * 2]
if any(sigma) < 1:
sigma = N.where(sigma < 1, 1, sigma)
# check if the result is inside the image
if N.any(zyx < 0) or N.any(zyx > (shape)):
print 'fitting results outside the image', zyx, z, y, x, rmslice
arr[rmslice] = me
failed += 1
continue # too close to the edge
# remove the point
imgFilters.mask_gaussianND(arr, zyx, v, sigma)
# check if the bead is too close to the exisisting ones
skipped = """
if len(found):#zyxs):
close = imgGeo.closeEnough(zyx, found, difflimit*2)#zyxs, difflimit*2)
if N.any(close):
if len(zyxs):
close = imgGeo.closeEnough(zyx, zyxs, difflimit*2)
if N.any(close):
idx = close.argmax()
already = zyxs.pop(idx)
#print 'too close', zyx, already
print 'found in the previous list'
continue"""
# remove beads too close to the edge
if N.any(zyx < 2) or N.any(zyx > (shape - 2)):
print 'too close to the edge', zyx
if N.any(arr[rmslice] > thre):
arr[rmslice] = me
failed += 1
continue # too close to the edge
# remove beads with bad shape
elif N.any(sigma < 0.5) or N.any(sigma > 3):
print 'sigma too different from expected', sigma, zyx
if N.any(arr[rmslice] > thre):
arr[rmslice] = me
sigma = 1.5
failed += 1
continue
old = """
# remove beads too elliptic
elif sigma[1] / sigma[2] > 1.5 or sigma[2] / sigma[1] > 1.5:
print 'too elliptic', sigma[2] / sigma[1]
if N.any(arr[rmslice] > thre):
arr[rmslice] = me
#if (sigma[2] / sigma[1]) > 20:
#raise ValueError
sigma = 1.5
failed += 1
continue
elif N.any(sigma[-2:] > 3.0):
print 'sigma too large', sigma, zyx
if N.any(arr[rmslice] > thre):
arr[rmslice] = me
sigma = 1.5
failed += 1
continue
elif sigma[0] < 0.5 or sigma[0] > 3:
print 'sigma z too different from expected', sigma, zyx
if N.any(arr[rmslice] > thre):
arr[rmslice] = me
sigma = 1.5
failed += 1
continue
#elif imgGeo.closeEnough(zyx, N.array((17,719,810), N.float32), 4):
# raise RuntimeError"""
# add results
zyxs.append(zyx)
sigmas.append(sigma)
i += 1
pmax = amax
failed = 0
#print i
# maximum is below threshold
else:
break
del arr
sigmas = N.array(sigmas)
sigmaYX = N.mean(sigmas[:, 1:], axis=1)
sigmaZ = sigmas[:, 0]
idxyx = sigmaYX.argmax()
idxz = sigmaZ.argmax()
print 'sigmaYX', round(sigmaYX.mean(),
3), round(sigmaYX.min(),
3), round(sigmaYX.std(),
3), round(sigmaYX.max(),
3), zyxs[idxyx]
print 'sigmaZ', round(sigmaZ.mean(),
3), round(sigmaZ.min(),
3), round(sigmaZ.std(),
3), round(sigmaZ.max(),
3), zyxs[idxz]
# remove overlaps
zyxs2 = []
zyxs = N.array(zyxs)
for i, zyx in enumerate(zyxs):
close = imgGeo.closeEnough(zyx, zyxs, difflimit * 4)
if not N.any(close[:i]) and not N.any(close[i + 1:]):
#idx = close.argmax()
#already = zyxs.pop(idx)
zyxs2.append(zyx)
zyxs = zyxs2
waves = range(h.nw)
#waves.remove(refwave)
difdic = {}
removes = []
checks = 0
zeros = 0
toofars = 0
pzyx *= 1000
for w in waves:
if w == refwave:
continue
arr = h.get3DArr(w=w)
#me = arr.mean()
#sd = arr.std()
#thre = me + sd * thre_sigma
for zyx in zyxs:
key = tuple(zyx * pzyx)
if key in removes:
continue
#win0 = win
#while win0 >= 3:
try:
ret, check = imgFit.fitGaussianND(arr,
zyx,
sigma=sigma,
window=win) #0)
#break
except (IndexError, ValueError):
ret = zyx
check = 5
#win0 -= 2
#ret, check = imgFit.fitGaussianND(arr, zyx, sigma=sigma, window=3)
dif = (zyx - ret[2:5]) * pzyx
if check == 5 or (
w != refwave and N.any(N.abs(dif) > maxdist)) or (
w == refwave and N.any(N.abs(dif) > maxrefdist)
): #(N.all(dif == 0) or N.any(N.abs(dif) > maxdist))):
if check == 5:
checks += 1
#elif N.all(dif == 0):
#zeros += 1
elif w == refwave and N.any(N.abs(dif) > maxrefdist):
zeros += 1
elif N.any(N.abs(dif) > maxdist):
toofars += 1
#if N.any(N.abs(dif) > maxdist):
# raise ValueError
#raise RuntimeError
removes.append(key)
if difdic.has_key(key):
del difdic[key]
#elif not N.sum(dif) or N.any(dif > 10):
#raise RuntimeError, 'something is wrong'
else:
difdic.setdefault(key, [])
difdic[key].append(dif)
sigma = ret[5:8]
#del arr
h.close()
del arr
del h
print 'check:', checks, 'zeros:', zeros, 'toofars', toofars
# subtracting the center
newdic = {}
keys = difdic.keys()
newkeys = N.array(keys)
zmin = N.min(newkeys[:, 0])
center = (shape * pzyx) / 2.
#yx0 = (N.max(newkeys[:,1:], axis=0) - N.min(newkeys[:,1:], axis=0)) / 2.
newkeys[:, 0] -= zmin
newkeys[:, 1:] -= center[1:] #yx0
newkeys = [tuple(key) for key in newkeys]
items = [difdic[key] for key in keys]
newdic = dict(zip(newkeys, items))
difdic = newdic
# plot
P.figure(0, figsize=(8, 8))
keys = N.array(difdic.keys())
P.hold(0)
P.scatter(keys[:, 2], keys[:, 1], alpha=0.5)
P.xlabel('X (nm)')
P.ylabel('Y (nm)')
P.savefig(fn + '_fig0.png')
return difdic #, shape