def _get_trace_and_maxc(self, sid,fs=None,nf=None ):
from Get_Data import readframe_series
from XPCS_Functions import get_trace_and_maxc
imgs = readframe_series( sid, inDir )
print ('Doing trace analysis for sid_%s with %s frames'%(sid,noframes ))
trace, max_cts = get_trace_and_maxc(imgs,self.pixellist,self.qind,fs,nf)
return trace,max_cts
def _get_trace_and_maxc(self, sid, fs=None, nf=None):
from Get_Data import readframe_series
from XPCS_Functions import get_trace_and_maxc
imgs = readframe_series(sid, inDir)
print('Doing trace analysis for sid_%s with %s frames' %
(sid, noframes))
trace, max_cts = get_trace_and_maxc(imgs, self.pixellist, self.qind,
fs, nf)
return trace, max_cts
def __init__(self,):
""" DOCUMENT __init__( )
the initilization of the XPCS class
"""
from Get_Data import readframe_series
from XPCS_Functions import make_qlist,calqlist
#from Setup_file import qstart,qend,qwidth,noqs,sid, inDir
#from Setup_file import dimx,dimy,cenx,ceny, mask
self.version='version_1'
self.create_time='Octa_18_2015'
self.author='Yugang_Zhang_chx11id_nsls2_BNL'
self.email='*****@*****.**'
self.email2='*****@*****.**'
self.data = readframe_series( sid, inDir ) #read data with sid, and bg_id
self.qlist,self.qradi = make_qlist(qstart,qend,qwidth,noqs)
self.pixellist,self.qind,self.nopr,self.nopixels = calqlist(
self.qlist,self.qradi, dimx,dimy,
cenx,ceny,qmask=mask)
if min(self.qind)!=0:print ('The qmin is too small!')
def __init__(self, ):
""" DOCUMENT __init__( )
the initilization of the XPCS class
"""
from Get_Data import readframe_series
from XPCS_Functions import make_qlist, calqlist
#from Setup_file import qstart,qend,qwidth,noqs,sid, inDir
#from Setup_file import dimx,dimy,cenx,ceny, mask
self.version = 'version_1'
self.create_time = 'Octa_18_2015'
self.author = 'Yugang_Zhang_chx11id_nsls2_BNL'
self.email = '*****@*****.**'
self.email2 = '*****@*****.**'
self.data = readframe_series(sid,
inDir) #read data with sid, and bg_id
self.qlist, self.qradi = make_qlist(qstart, qend, qwidth, noqs)
self.pixellist, self.qind, self.nopr, self.nopixels = calqlist(
self.qlist, self.qradi, dimx, dimy, cenx, ceny, qmask=mask)
if min(self.qind) != 0: print('The qmin is too small!')
def XSVS_Single( self, sid, expose_time = 1.0, maxcts = 50,
do_bining = True,timebin = 2,timebin_level=None):
'''sid: give the sample name/folder
qRings: a pixel list for different qs
maxcts: the max counts for the lowest exposure time
bins:
if True, bin the images; bin number is timebines,
timebin_level gives the max level for bin
if Flase: just do histgram for the images
Return: expose time: a list with length as timebin_level
Bins: for each expose time, each Qs, shaped as [time_lev, Qs]
Histrogram_3D_Matrix: a histrogram, shaped as [time_lev, Qs]
HistStddev_all: a deviation of histrogram, shaped as [time_lev, Qs]
'''
from Get_Data import readframe_series
img = readframe_series( sid, inDir )
N = len(img)
if noframes>N:noframes_=N
else:noframes_=noframes
qRings = self.qRings
if do_bining:
if timebin_level is None:
timebin_level = int( np.log( noframes )/np.log(2)) # +1
time_list = [ 2**i for i in range(timebin_level)]
else:
timebin_level = 1
time_list = [ expose_time ]
Bins = np.zeros([timebin_level,noqs],dtype=object) #GlobalPDFArray_all is the Histrogram_3D_Matrix
Histrogram_3D_Matrix = np.zeros([timebin_level,noqs],dtype=object)
Histrogram2_3D_Matrix = np.zeros([timebin_level,noqs],dtype=object)
#this function is to calculate the deviation of histrogram
BinEdges = np.arange( maxcts )
#print BinEdges
#print img
for i,n in enumerate(time_list):
for j in range(noqs):
Bins[ i,j ]= np.arange( maxcts * time_list[i] )
###########################################################
print ('Running sample---%s'%(sid))
print ('Doing histrogram for %s frames'%noframes_ )
buf=np.zeros([ timebin_level, timebin], dtype=object) #// matrix of buffers
cts=np.zeros(timebin_level)
cur=np.ones(timebin_level) * timebin
num= np.array(np.zeros( timebin_level ),dtype='int')
###############################################
#the loop for process of each frame
#print noframes_,noframes
for n in range(1,noframes_ +1 ):
#print n+ begframe-1,
cur[0]=1+cur[0]%timebin
ifg = img[ n + begframe-1 ].ravel()
ifg[ (np.where(ifg<0))[0] ]=0
buf[0, cur[0]-1 ]= np.array( ifg, dtype=float)
#img=[] #//save space
#self.process(lev=0, bufno=cur[0]-1 )
self.process(0,cur[0]-1, buf, num, qRings, Bins[ 0,0 ],
Histrogram2_3D_Matrix,Histrogram_3D_Matrix)
processing=1
lev=1
#print cts
if do_bining==False:processing = 0
while processing:
if cts[lev]:
prev= 1+ (cur[lev-1]-1-1+nobuf)%timebin
cur[lev]= 1+ cur[lev]%timebin
buf[lev,cur[lev]-1] = (
buf[lev-1,prev-1] + buf[lev-1,cur[lev-1]-1] ) #/2.
cts[lev]=0
#self.process(lev= lev, bufno= cur[lev]-1 , n=n)
self.process(lev,cur[lev]-1, buf, num, qRings, Bins[ lev,0 ],
Histrogram2_3D_Matrix,Histrogram_3D_Matrix)
lev+=1
if lev<timebin_level:processing = 1
else:processing = 0
else:
cts[lev]=1 #// set flag to process next time
processing=0 #// can stop until more images are accumulated
if isnan( Histrogram_3D_Matrix[0,0][0] ):
print (n)
HistStddev_all = np.power( ( Histrogram2_3D_Matrix -
np.power(Histrogram_3D_Matrix ,2)), .5)
#expost = time_list
self.time_list = np.array( time_list ) *expose_time
self.timebin_level=timebin_level
self.noframes = noframes
return Bins, Histrogram_3D_Matrix, HistStddev_all
def XSVS_Single(self,
sid,
expose_time=1.0,
maxcts=50,
do_bining=True,
timebin=2,
timebin_level=None):
'''sid: give the sample name/folder
qRings: a pixel list for different qs
maxcts: the max counts for the lowest exposure time
bins:
if True, bin the images; bin number is timebines,
timebin_level gives the max level for bin
if Flase: just do histgram for the images
Return: expose time: a list with length as timebin_level
Bins: for each expose time, each Qs, shaped as [time_lev, Qs]
Histrogram_3D_Matrix: a histrogram, shaped as [time_lev, Qs]
HistStddev_all: a deviation of histrogram, shaped as [time_lev, Qs]
'''
from Get_Data import readframe_series
img = readframe_series(sid, inDir)
N = len(img)
if noframes > N: noframes_ = N
else: noframes_ = noframes
qRings = self.qRings
if do_bining:
if timebin_level is None:
timebin_level = int(np.log(noframes) / np.log(2)) # +1
time_list = [2**i for i in range(timebin_level)]
else:
timebin_level = 1
time_list = [expose_time]
Bins = np.zeros(
[timebin_level, noqs],
dtype=object) #GlobalPDFArray_all is the Histrogram_3D_Matrix
Histrogram_3D_Matrix = np.zeros([timebin_level, noqs], dtype=object)
Histrogram2_3D_Matrix = np.zeros([timebin_level, noqs], dtype=object)
#this function is to calculate the deviation of histrogram
BinEdges = np.arange(maxcts)
#print BinEdges
#print img
for i, n in enumerate(time_list):
for j in range(noqs):
Bins[i, j] = np.arange(maxcts * time_list[i])
###########################################################
print('Running sample---%s' % (sid))
print('Doing histrogram for %s frames' % noframes_)
buf = np.zeros([timebin_level, timebin],
dtype=object) #// matrix of buffers
cts = np.zeros(timebin_level)
cur = np.ones(timebin_level) * timebin
num = np.array(np.zeros(timebin_level), dtype='int')
###############################################
#the loop for process of each frame
#print noframes_,noframes
for n in range(1, noframes_ + 1):
#print n+ begframe-1,
cur[0] = 1 + cur[0] % timebin
ifg = img[n + begframe - 1].ravel()
ifg[(np.where(ifg < 0))[0]] = 0
buf[0, cur[0] - 1] = np.array(ifg, dtype=float)
#img=[] #//save space
#self.process(lev=0, bufno=cur[0]-1 )
self.process(0, cur[0] - 1, buf, num, qRings, Bins[0, 0],
Histrogram2_3D_Matrix, Histrogram_3D_Matrix)
processing = 1
lev = 1
#print cts
if do_bining == False: processing = 0
while processing:
if cts[lev]:
prev = 1 + (cur[lev - 1] - 1 - 1 + nobuf) % timebin
cur[lev] = 1 + cur[lev] % timebin
buf[lev,
cur[lev] - 1] = (buf[lev - 1, prev - 1] +
buf[lev - 1, cur[lev - 1] - 1]) #/2.
cts[lev] = 0
#self.process(lev= lev, bufno= cur[lev]-1 , n=n)
self.process(lev, cur[lev] - 1, buf, num, qRings, Bins[lev,
0],
Histrogram2_3D_Matrix, Histrogram_3D_Matrix)
lev += 1
if lev < timebin_level: processing = 1
else: processing = 0
else:
cts[lev] = 1 #// set flag to process next time
processing = 0 #// can stop until more images are accumulated
if isnan(Histrogram_3D_Matrix[0, 0][0]):
print(n)
HistStddev_all = np.power(
(Histrogram2_3D_Matrix - np.power(Histrogram_3D_Matrix, 2)), .5)
#expost = time_list
self.time_list = np.array(time_list) * expose_time
self.timebin_level = timebin_level
self.noframes = noframes
return Bins, Histrogram_3D_Matrix, HistStddev_all