def readfiles(filestrlist):
Ilist=[]
Ierrlist=[]
Qlist=[]
hkllist=[]
thlist=[]
mydatalist=[]
for myfilestr in filestrlist:
mydatareader=readncnr.datareader()
mydata=mydatareader.readbuffer(myfilestr)
filename=mydata.metadata['file_info']['filename']
h=mydata.metadata['q_center']['h_center']
k=mydata.metadata['q_center']['k_center']
l=mydata.metadata['q_center']['l_center']
hkl='('+str(h)+' '+str(k)+' '+str(l)+')'
Q=np.array([h,k,l],'float64')
print 'hkl',hkl
print 'file', filename
if len(Ilist)==0:
mon0=mydata.metadata['count_info']['monitor']
mon0=82500
mon=mydata.metadata['count_info']['monitor']
I_orig=np.array(mydata.data['counts'],'Float64')
#node.measured_data.data['counts_err']=N.array(node.measured_data.data['counts_err'],'Float64')
I_norm=I_orig*mon0/mon
I_norm_err=np.sqrt(I_orig)*mon0/mon
Ilist.append(I_norm)
Ierrlist.append(I_norm_err)
Qlist.append(Q)
hkllist.append(hkl)
th=np.array(mydata.data['a3'])
thlist.append(th)
mydatalist.append(mydata)
return Qlist, thlist,Ilist, Ierrlist,hkllist,mydatalist
def readfiles(filestrlist):
Ilist = []
Ierrlist = []
Qlist = []
hkllist = []
thlist = []
mydatalist = []
for myfilestr in filestrlist:
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
filename = mydata.metadata['file_info']['filename']
h = mydata.metadata['q_center']['h_center']
k = mydata.metadata['q_center']['k_center']
l = mydata.metadata['q_center']['l_center']
hkl = '(' + str(h) + ' ' + str(k) + ' ' + str(l) + ')'
Q = np.array([h, k, l], 'float64')
print 'hkl', hkl
print 'file', filename
if len(Ilist) == 0:
mon0 = mydata.metadata['count_info']['monitor']
mon0 = 82500
mon = mydata.metadata['count_info']['monitor']
I_orig = np.array(mydata.data['counts'], 'Float64')
#node.measured_data.data['counts_err']=N.array(node.measured_data.data['counts_err'],'Float64')
I_norm = I_orig * mon0 / mon
I_norm_err = np.sqrt(I_orig) * mon0 / mon
Ilist.append(I_norm)
Ierrlist.append(I_norm_err)
Qlist.append(Q)
hkllist.append(hkl)
th = np.array(mydata.data['a3'])
thlist.append(th)
mydatalist.append(mydata)
return Qlist, thlist, Ilist, Ierrlist, hkllist, mydatalist
def readfiles(flist,tol=1e-4):
mydatareader=readncnr.datareader()
H=[]#N.array([])
I=[]#N.array([])
Ierr=[]#N.array([])
monlist=[]
count=0
myfirstdata=mydatareader.readbuffer(flist[0])
mon0=myfirstdata.metadata['count_info']['monitor']
print 'mon0',mon0
qtree=Qtree()
Qtree.mon0=mon0
#flist=flist[0:12]
for currfile in flist:
#print 'MAIN READ',currfile
mydata=mydatareader.readbuffer(currfile)
mydata.data['counts_err']=N.sqrt(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
mydata.data['counts']=N.array(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
mydata.metadata['count_info']['monitor']=mon0
qtree.addnode(copy.deepcopy(mydata))
#print 'readloop'
#print 'q in loop', qtree.qlist[0].q
for qnode in qtree.qlist:
print qnode.q['h_center'],qnode.q['k_center'],qnode.q['l_center'],len(qnode.th),qnode.th
#print qtree.qlist
return qtree
def readfiles(filestrlist):
Ilist = []
Ierrlist = []
Qlist = []
hkllist = []
thlist = []
mydatalist = []
for myfilestr in filestrlist:
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
filename = mydata.metadata["file_info"]["filename"]
h = mydata.metadata["q_center"]["h_center"]
k = mydata.metadata["q_center"]["k_center"]
l = mydata.metadata["q_center"]["l_center"]
hkl = "(" + str(h) + " " + str(k) + " " + str(l) + ")"
Q = np.array([h, k, l], "float64")
print "hkl", hkl
print "file", filename
if len(Ilist) == 0:
mon0 = mydata.metadata["count_info"]["monitor"]
mon0 = 82500
mon = mydata.metadata["count_info"]["monitor"]
I_orig = np.array(mydata.data["counts"], "Float64")
# node.measured_data.data['counts_err']=N.array(node.measured_data.data['counts_err'],'Float64')
I_norm = I_orig * mon0 / mon
I_norm_err = np.sqrt(I_orig) * mon0 / mon
Ilist.append(I_norm)
Ierrlist.append(I_norm_err)
Qlist.append(Q)
hkllist.append(hkl)
th = np.array(mydata.data["a3"])
thlist.append(th)
mydatalist.append(mydata)
return Qlist, thlist, Ilist, Ierrlist, hkllist, mydatalist
def readfiles(flist, tol=1e-4):
mydatareader = readncnr.datareader()
H = [] #N.array([])
I = [] #N.array([])
Ierr = [] #N.array([])
monlist = []
count = 0
myfirstdata = mydatareader.readbuffer(flist[0])
mon0 = myfirstdata.metadata['count_info']['monitor']
print 'mon0', mon0
#flist=flist[0:12]
datalist = []
for currfile in flist:
#print 'MAIN READ',currfile
mydata = mydatareader.readbuffer(currfile)
mydata.data['counts_err'] = N.sqrt(
mydata.data['counts']
) * mon0 / mydata.metadata['count_info']['monitor']
mydata.data['counts'] = N.array(
mydata.data['counts']
) * mon0 / mydata.metadata['count_info']['monitor']
datalist.append(mydata)
#print qtree.qlist
return datalist
def readfiles(flist,tol=1e-4):
mydatareader=readncnr.datareader()
H=[]#N.array([])
I=[]#N.array([])
Ierr=[]#N.array([])
monlist=[]
count=0
myfirstdata=mydatareader.readbuffer(flist[0])
mon0=myfirstdata.metadata['count_info']['monitor']
print 'mon0',mon0
qtree=Qtree()
Qtree.mon0=mon0
#flist=flist[0:12]
for currfile in flist:
#print 'MAIN READ',currfile
mydata=mydatareader.readbuffer(currfile)
mydata.data['counts_err']=N.sqrt(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
mydata.data['counts']=N.array(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
mydata.metadata['count_info']['monitor']=mon0
qtree.addnode(copy.deepcopy(mydata))
#print 'readloop'
#print 'q in loop', qtree.qlist[0].q
for qnode in qtree.qlist:
print qnode.q['h_center'],qnode.q['k_center'],qnode.q['l_center'],len(qnode.th),qnode.th
#print qtree.qlist
return qtree
def read_data(myfilestr):
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
qz = N.array(mydata.data['qx'])
I = N.array(mydata.data['detector'], 'float64')
Ierr = N.sqrt(I)
mon = mydata.data['monitor'][0]
return qz, I, Ierr, mon
def read_fpx(myfilestr, key='smplgfrot'):
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
qz = N.array(mydata.data[key])
I = N.array(mydata.data['detector'], 'float64')
Ierr = N.sqrt(I)
mon = mydata.data['monitor'][0]
return qz, I, Ierr, mon
def read_fpx(myfilestr, key="smplgfrot"):
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
qz = N.array(mydata.data[key])
I = N.array(mydata.data["detector"], "float64")
Ierr = N.sqrt(I)
mon = mydata.data["monitor"][0]
return qz, I, Ierr, mon
def read_data(myfilestr):
mydatareader = readncnr.datareader()
mydata = mydatareader.readbuffer(myfilestr)
qz = N.array(mydata.data["qx"])
I = N.array(mydata.data["detector"], "float64")
Ierr = N.sqrt(I)
mon = mydata.data["monitor"][0]
return qz, I, Ierr, mon
def read_fpx(myfilestr,key='smplgfrot'):
mydatareader=readncnr.datareader()
mydata=mydatareader.readbuffer(myfilestr)
qz=N.array(mydata.data[key])
I=N.array(mydata.data['detector'],'float64')
Ierr=N.sqrt(I)
mon=mydata.data['monitor'][0]
return qz,I,Ierr,mon
def read_data(myfilestr):
mydatareader=readncnr.datareader()
mydata=mydatareader.readbuffer(myfilestr)
qz=N.array(mydata.data['qx'])
I=N.array(mydata.data['detector'],'float64')
Ierr=N.sqrt(I)
mon=mydata.data['monitor'][0]
return qz,I,Ierr,mon
def readfiles(flist, mon0=None):
mydatareader = readncnr.datareader()
#Qx=N.array([])
#Qy=N.array([])
#Qz=N.array([])
#tth=N.array([])
#Counts=N.array([])
#T=N.array([])
tth = []
Counts = []
Counts_err = []
T = []
i = 0
for currfile in flist:
#print currfile
mydata = mydatareader.readbuffer(currfile)
#print mydata.data.keys()
if i == 0:
if mon0 == None:
mon0 = mydata.metadata['count_info']['monitor']
#a=mydata.metadata['lattice']['a']
#b=mydata.metadata['lattice']['b']
#c=mydata.metadata['lattice']['c']
mon = mydata.metadata['count_info']['monitor']
wl = 2.35916
#c=2*wl/N.sin(N.deg2rad(N.array(tth))/2)
#tth.append(2*wl/N.sin(N.deg2rad(N.array(mydata.data['a4'])/2)))
tth.append(N.array(mydata.data['a4']))
Counts.append(N.array(mydata.data['counts']) * mon0 / mon)
Counts_err.append(N.sqrt(N.array(mydata.data['counts'])) * mon0 / mon)
#T.append(N.array(mydata.data['temp'])) #What we probably want
Tave = N.array(mydata.data['temp']).mean()
T.append(N.ones(tth[i].size) * Tave)
#Qx=N.concatenate((Qx,N.array(mydata.data['qx'])*2*pi/a))
#Qy=N.concatenate((Qy,N.array(mydata.data['qy'])*2*pi/b))
#Qz=N.concatenate((Qz,N.array(mydata.data['qz'])*2*pi/c))
#tth=N.concatenate((tth,N.array(mydata.data['a4'])))
#Counts=N.concatenate((Counts,N.array(mydata.data['counts'])*mon0/mon))
#T=N.concatenate((T,N.array(mydata.data['temp'])))
i = i + 1
#xa,ya,za=prep_data2(Qx,Qy,Counts);
#print 'xa',xa.min(),xa.max()
#print 'qx',Qx.min(),Qx.max()
#x,y,z=grid(Qx,Qz,Counts)
return tth, T, Counts, Counts_err, mon0
def readfiles(flist,mon0=None):
mydatareader=readncnr.datareader()
#Qx=N.array([])
#Qy=N.array([])
#Qz=N.array([])
#tth=N.array([])
#Counts=N.array([])
#T=N.array([])
tth=[]
Counts=[]
Counts_err=[]
T=[]
i=0
for currfile in flist:
#print currfile
mydata=mydatareader.readbuffer(currfile)
#print mydata.data.keys()
if i==0:
if mon0==None:
mon0=mydata.metadata['count_info']['monitor']
#a=mydata.metadata['lattice']['a']
#b=mydata.metadata['lattice']['b']
#c=mydata.metadata['lattice']['c']
mon=mydata.metadata['count_info']['monitor']
wl=2.35916
#c=2*wl/N.sin(N.deg2rad(N.array(tth))/2)
#tth.append(2*wl/N.sin(N.deg2rad(N.array(mydata.data['a4'])/2)))
tth.append(N.array(mydata.data['a4']))
Counts.append(N.array(mydata.data['counts'])*mon0/mon)
Counts_err.append(N.sqrt(N.array(mydata.data['counts']))*mon0/mon)
#T.append(N.array(mydata.data['temp'])) #What we probably want
Tave=N.array(mydata.data['temp']).mean()
T.append(N.ones(tth[i].size)*Tave)
#Qx=N.concatenate((Qx,N.array(mydata.data['qx'])*2*pi/a))
#Qy=N.concatenate((Qy,N.array(mydata.data['qy'])*2*pi/b))
#Qz=N.concatenate((Qz,N.array(mydata.data['qz'])*2*pi/c))
#tth=N.concatenate((tth,N.array(mydata.data['a4'])))
#Counts=N.concatenate((Counts,N.array(mydata.data['counts'])*mon0/mon))
#T=N.concatenate((T,N.array(mydata.data['temp'])))
i=i+1
#xa,ya,za=prep_data2(Qx,Qy,Counts);
#print 'xa',xa.min(),xa.max()
#print 'qx',Qx.min(),Qx.max()
#x,y,z=grid(Qx,Qz,Counts)
return tth,T,Counts,Counts_err,mon0
def readfiles(flist,tol=1e-4):
mydatareader=readncnr.datareader()
H=[]#N.array([])
I=[]#N.array([])
Ierr=[]#N.array([])
monlist=[]
count=0
myfirstdata=mydatareader.readbuffer(flist[0])
mon0=myfirstdata.metadata['count_info']['monitor']
print 'mon0',mon0
#flist=flist[0:12]
datalist=[]
for currfile in flist:
#print 'MAIN READ',currfile
mydata=mydatareader.readbuffer(currfile)
mydata.data['counts_err']=N.sqrt(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
mydata.data['counts']=N.array(mydata.data['counts'])*mon0/mydata.metadata['count_info']['monitor']
datalist.append(mydata)
#print qtree.qlist
return datalist
def readfiles(flist):
mydatareader=readncnr.datareader()
Qx=N.array([])
Qy=N.array([])
Qz=N.array([])
Counts=N.array([])
for currfile in flist:
#print currfile
mydata=mydatareader.readbuffer(currfile)
#print mydata.data.keys()
a=mydata.metadata['lattice']['a']
b=mydata.metadata['lattice']['b']
c=mydata.metadata['lattice']['c']
Qx=N.concatenate((Qx,N.array(mydata.data['qx'])*2*pi/a))
Qy=N.concatenate((Qy,N.array(mydata.data['qy'])*2*pi/b))
Qz=N.concatenate((Qz,N.array(mydata.data['qz'])*2*pi/c))
Counts=N.concatenate((Counts,N.array(mydata.data['counts'])))
#xa,ya,za=prep_data2(Qx,Qy,Counts);
#print 'xa',xa.min(),xa.max()
#print 'qx',Qx.min(),Qx.max()
#x,y,z=grid(Qx,Qz,Counts)
return Qx,Qz,Counts
def readmeshfiles(mydirectory,myfilebase,myend):
myfilebaseglob=myfilebase+'*.'+myend
print myfilebaseglob
flist = SU.ffind(mydirectory, shellglobs=(myfilebaseglob,))
#SU.printr(flist)
mydatareader=readncnr.datareader()
temp1=N.array([])
temp2=N.array([])
temp3=N.array([])
Counts1=N.array([])
Counts2=N.array([])
Counts3=N.array([])
errors1=N.array([])
errors2=N.array([])
errors3=N.array([])
mydata=mydatareader.readbuffer(flist[0])
mon0=mydata.metadata['count_info']['monitor']
for currfile in flist:
#print currfile
mydata=mydatareader.readbuffer(currfile)
#print mydata.data.keys()
#print mydata.__dict__
#print mydata.metadata.keys()
qcenter=mydata.metadata['q_center']
hc,kc,lc=qcenter['h_center'],qcenter['k_center'],qcenter['l_center']
mon=mydata.metadata['count_info']['monitor']
curr_counts=N.array(mydata.data['counts'])
curr_error=N.sqrt(curr_counts)*mon0/mon
curr_counts=curr_counts*mon0/mon
curr_temp=N.array(mydata.data['temp'])
if hc==1.004:
Counts1=N.concatenate((Counts1,curr_counts))
temp1=N.concatenate((temp1,curr_temp))
errors1=N.concatenate((errors1,curr_error))
elif hc==1.036:
Counts2=N.concatenate((Counts2,curr_counts))
temp2=N.concatenate((temp2,curr_temp))
errors2=N.concatenate((errors2,curr_error))
elif hc==2.0:
Counts3=N.concatenate((Counts3,curr_counts))
temp3=N.concatenate((temp3,curr_temp))
errors3=N.concatenate((errors3,curr_error))
#print
#Qx=N.concatenate((Qx,N.array(mydata.data['qx'])))
#Qy=N.concatenate((Qy,N.array(mydata.data['qy'])))
#Qz=N.concatenate((Qz,N.array(mydata.data['qz'])))
#Counts=N.concatenate((Counts,N.array(mydata.data['counts'])))
#print Qx
#print Qy
#print Counts
dataset={}
dataset['Counts1']=Counts1
dataset['Counts2']=Counts2
dataset['Counts3']=Counts3
dataset['temp1']=temp1
dataset['temp2']=temp2
dataset['temp3']=temp3
dataset['errors1']=errors1
dataset['errors2']=errors2
dataset['errors3']=errors3
return dataset
for i in len(data.get(Ei))
thetaA = N.radians(data.get(a6)[i]/2.0)
arg = asin(N.pi/(0.69472*dA*sqrt(double(data.get(Ei)[i]))))
norm = (Ei^1.5) / tan(arg)
cotThetaA = 1/tan(thetaA)
resCor = norm/(cotThetaA * (Ef^1.5))
N.exp((ki/kf) ** 3) * (1/N.tan(thetaM)) / (1/N.cot(thetaA))
''
if __name__=="__main__":
#Currently for testing purposes only
#coeff = establish_correction_coefficients("monitor_correction_coordinates.txt")
#print coeff
#metadata, data = readFile("bt7 sample data.txt")
#print metadata
#print data
myfilestr=r'EscanQQ7HorNSF91831.bt7'
mydatareader=R.datareader()
mydata=mydatareader.readbuffer(myfilestr)
#print mydata.data.keys()
#print mydata.data.get('lattice')
setup_data_structure(mydata)
#print mydata.data
#print mydata.metadata
qtree.addnode(copy.deepcopy(mydata))
#print 'readloop'
#print 'q in loop', qtree.qlist[0].q
for qnode in qtree.qlist:
print qnode.q['h_center'],qnode.q['k_center'],qnode.q['l_center'],len(qnode.th),qnode.th
#print qtree.qlist
return qtree
if __name__=='__main__':
myfilestr=r'C:\Ce2RhIn8\Mar10_2009\magsc035.bt9'
#myfilestr=r'c:\bifeo3xtal\jan8_2008\9175\fpx53418.bt7'
#myfilestr=r'c:\13165\13165\data\MagHigh56784.bt7'
#myfilestr=r'c:\13176\data\CeOFeAs57255.bt7.out'
mydatareader=readncnr.datareader()
mydata=mydatareader.readbuffer(myfilestr)
# print mydata.__dict__
# print mydata.additional_metadata
# print mydata.metadata
# print mydata.metadata['file_info']['scantype']
# print mydata.metadata['collimations']
# print mydata.metadata['dspacing']['monochromator_dspacing']
# print mydata.metadata['dspacing']['analyzer_dspacing']
# print mydata.metadata['lattice']['a']
# print mydata.metadata['lattice']['b']
# print mydata.metadata['lattice']['c']
# print mydata.metadata['lattice']['alpha']
# print mydata.metadata['lattice']['beta']
# print mydata.metadata['lattice']['gamma']
# print mydata.metadata['motor3']['step']
def __init__(self, filename):
self.data = []
self.standards = read_standards()
f = file(filename, 'r')
t = []
template = {}
for s in self.standards:
template[s] = [None]
s = f.read()
f.close()
f = file(filename, 'r')
if s[0] == '#':
print 'hey'
for lines in f:
lines = lines.split()
if len(lines) == 0:
continue
if lines[0] == '#Columns':
t.append(lines[1:])
break
else:
if lines[0][1:] in self.standards:
pass
else:
self.standards[lines[0][1:]] = Standard(
metadata=True).__dict__
template[lines[0][1:]] = lines[1:] or [None]
for lines in f:
if lines[0] == '#': break
t.append(lines.split())
f.close()
for s in t[0]:
if s in self.standards:
self.standards[s]['metadata'] = False
else:
self.standards[s] = Standard().__dict__
template[s] = [None]
for i in range(1, len(t)):
self.data.append(copy.copy(template))
for j in range(len(t[0])):
try:
self.data[i - 1][t[0][j]] = [float(t[i][j])]
except ValueError:
self.data[i - 1][t[0][j]] = [t[i][j]]
self.detectors = set(['Detector', '_Detector'])
for s in self.standards:
if s[:8] == 'Analyzer' and s[-5:] == 'Group':
self.detectors = self.detectors | set(self.data[0][s])
for d in self.data[0][s]:
self.detectors.add('_' + d)
for d in self.detectors:
if d in self.standards and d[0] is not '_':
if '_' + d not in self.standards:
self.standards['_' + d] = Standard().__dict__
for p in self.data:
p['_' + d] = p[d]
elif 'fpx' in filename or 'fpt' in filename and s[0] != '#':
fields = []
date = []
first = True
for lines in f:
if first:
first = False
spl = lines.split()
for i in range(len(spl)):
try:
if int(spl[i]) in range(1, 7):
fields.append('A' + spl[i])
except:
if spl[i] == 'Intensity':
fields.append('Detector')
date = spl[i + 1:]
break
self.standards = {'Date': Standard(metadata=True).__dict__}
for s in fields:
self.standards[s] = Standard(metadata=False).__dict__
else:
newdata = {}
spl = lines.split()
for i in range(len(spl)):
try:
newdata[fields[i]] = [float(spl[i])]
except:
pass
newdata['Date'] = date
self.data.append(newdata)
else:
reader = readncnr3.datareader()
mydata = reader.readbuffer(filename)
try:
template['Collimations'] = [
mydata.metadata['collimations']['coll1'],
mydata.metadata['collimations']['coll2'],
mydata.metadata['collimations']['coll3'],
mydata.metadata['collimations']['coll4']
]
self.standards['Collimations'] = Standard(
metadata=True).__dict__
except:
pass
try:
template['Lattice'] = [
mydata.metadata['lattice']['a'],
mydata.metadata['lattice']['b'],
mydata.metadata['lattice']['c'],
mydata.metadata['lattice']['alpha'],
mydata.metadata['lattice']['beta'],
mydata.metadata['lattice']['gamma']
]
except:
pass
try:
for sl in mydata.metadata['count_info']:
inStandards = False
for s in self.standards:
if s.lower().split() == ''.join(sl.split('_')):
inStandards = True
template[s] = [mydata.metadata['count_info'][s]]
if not inStandards:
s = sl.split('_')
for i in range(len(s)):
s[i] = s[i].capitalize()
s = ''.join(s)
template[s] = [mydata.metadata['count_info'][s]]
self.standards[s] = Standard(metadata=True).__dict__
except:
pass
try:
template['MonoSpacing'] = [
mydata.metadata['dspacing']['monochromator_dspacing']
]
template['AnaSpacing'] = [
mydata.metadata['dspacing']['analyzer_dspacing']
]
except:
pass
try:
template['FixedE'] = [
mydata.metadata['energy_info']['efixed'],
mydata.metadata['energy_info']['ef']
]
except:
pass
try:
for sl in mydata.metadata['file_info']:
inStandards = False
for s in self.standards:
if s.lower().split().join('_') == sl:
inStandards = True
template[s] = [mydata.metadata['file_info'][s]]
if not inStandards:
s = sl.split('_')
for i in range(len(s)):
s[i] = s[i].capitalize()
s = ' '.join(s)
template[s] = [mydata.metadata['file_info'][s]]
self.standards[s] = Standard(metadata=True).__dict__
except:
pass
try:
template['HField'] = [
mydata.metadata['magnetic_field']['hfield']
]
self.standards['HField'] = Standard(metadata=True).__dict__
except:
pass
try:
template['AnalyzerMosaic'] = [
mydata.metadata['mosaic']['mosaic_analyzer']
]
self.standards['AnalyzerMosaic'] = Standard(
metadata=True).__dict__
template['MonochromatorMosaic'] = [
mydata.metadata['mosaic']['mosaic_monochromator']
]
self.standards['MonochromatorMosaic'] = Standard(
metadata=True).__dict__
template['SampleMosaic'] = [
mydata.metadata['mosaic']['mosaic_sample']
]
self.standards['SampleMosaic'] = Standard(
metadata=True).__dict__
except:
pass
try:
template['Orient'] = [
mydata.metadata['orient1']['h'],
mydata.metadata['orient1']['k'],
mydata.metadata['orient1']['l'],
mydata.metadata['orient2']['h'],
mydata.metadata['orient2']['k'],
mydata.metadata['orient2']['l']
]
except:
pass
areMotors = True
motors = []
try:
for i in range(6):
motors.append([
mydata.metadata['motor' + str(1 + i)]['start'],
mydata.metadata['motor' + str(1 + i)]['step']
])
except:
#print mydata.metadata
areMotors = False
try:
for p in mydata.data:
pcorr = p.split('_')
for i in range(len(pcorr)):
pcorr[i] = pcorr[i].capitalize()
pcorr = ''.join(pcorr)
if pcorr not in self.standards and pcorr not in [
'Qx', 'Qy', 'Qz', 'Counts'
]:
self.standards[pcorr] = Standard(
metadata=False).__dict__
count = 0
while (True):
print 'hey'
try:
newdata = copy.copy(template)
for p in mydata.data:
pcorr = p.split('_')
for i in range(len(pcorr)):
pcorr[i] = pcorr[i].capitalize()
pcorr = ''.join(pcorr)
if pcorr[0] == 'Q':
if pcorr[1] == 'x':
pcorr = 'QX'
elif pcorr[1] == 'y':
pcorr = 'QY'
elif pcorr[1] == 'z':
pcorr = 'QZ'
if pcorr == 'Counts':
pcorr = 'Detector'
newdata[pcorr] = [mydata.data[p][count]]
if (areMotors):
for i in range(len(motors)):
newdata['A' + str(i + 1)] = [
motors[i][0] + motors[i][1] * count
]
self.data.append(newdata)
count += 1
except:
break
except:
pass
def readmeshfiles(mydirectory, myfilebase, myend):
myfilebaseglob = myfilebase + '*.' + myend
print myfilebaseglob
flist = SU.ffind(mydirectory, shellglobs=(myfilebaseglob, ))
#SU.printr(flist)
mydatareader = readncnr.datareader()
temp1 = N.array([])
temp2 = N.array([])
temp3 = N.array([])
Counts1 = N.array([])
Counts2 = N.array([])
Counts3 = N.array([])
errors1 = N.array([])
errors2 = N.array([])
errors3 = N.array([])
mydata = mydatareader.readbuffer(flist[0])
mon0 = mydata.metadata['count_info']['monitor']
for currfile in flist:
#print currfile
mydata = mydatareader.readbuffer(currfile)
#print mydata.data.keys()
#print mydata.__dict__
#print mydata.metadata.keys()
qcenter = mydata.metadata['q_center']
hc, kc, lc = qcenter['h_center'], qcenter['k_center'], qcenter[
'l_center']
mon = mydata.metadata['count_info']['monitor']
curr_counts = N.array(mydata.data['counts'])
curr_error = N.sqrt(curr_counts) * mon0 / mon
curr_counts = curr_counts * mon0 / mon
curr_temp = N.array(mydata.data['temp'])
if hc == 1.004:
Counts1 = N.concatenate((Counts1, curr_counts))
temp1 = N.concatenate((temp1, curr_temp))
errors1 = N.concatenate((errors1, curr_error))
elif hc == 1.036:
Counts2 = N.concatenate((Counts2, curr_counts))
temp2 = N.concatenate((temp2, curr_temp))
errors2 = N.concatenate((errors2, curr_error))
elif hc == 2.0:
Counts3 = N.concatenate((Counts3, curr_counts))
temp3 = N.concatenate((temp3, curr_temp))
errors3 = N.concatenate((errors3, curr_error))
#print
#Qx=N.concatenate((Qx,N.array(mydata.data['qx'])))
#Qy=N.concatenate((Qy,N.array(mydata.data['qy'])))
#Qz=N.concatenate((Qz,N.array(mydata.data['qz'])))
#Counts=N.concatenate((Counts,N.array(mydata.data['counts'])))
#print Qx
#print Qy
#print Counts
dataset = {}
dataset['Counts1'] = Counts1
dataset['Counts2'] = Counts2
dataset['Counts3'] = Counts3
dataset['temp1'] = temp1
dataset['temp2'] = temp2
dataset['temp3'] = temp3
dataset['errors1'] = errors1
dataset['errors2'] = errors2
dataset['errors3'] = errors3
return dataset
def __init__(self,filename):
self.data = []
self.standards = read_standards()
f = file(filename, 'r')
t = []
template = {}
for s in self.standards:
template[s] = [None]
s = f.read()
f.close()
f = file(filename, 'r')
if s[0] == '#':
print 'hey'
for lines in f:
lines = lines.split()
if len(lines) == 0:
continue
if lines[0] == '#Columns':
t.append(lines[1:])
break
else:
if lines[0][1:] in self.standards:
pass
else:
self.standards[lines[0][1:]] = Standard(metadata = True).__dict__
template[lines[0][1:]] = lines[1:] or [None]
for lines in f:
if lines[0] == '#': break
t.append(lines.split())
f.close()
for s in t[0]:
if s in self.standards:
self.standards[s]['metadata'] = False
else:
self.standards[s] = Standard().__dict__
template[s] = [None]
for i in range(1,len(t)):
self.data.append(copy.copy(template))
for j in range(len(t[0])):
try:
self.data[i-1][t[0][j]] = [float(t[i][j])]
except ValueError:
self.data[i-1][t[0][j]] = [t[i][j]]
self.detectors = set(['Detector','_Detector'])
for s in self.standards:
if s[:8] == 'Analyzer' and s[-5:] == 'Group':
self.detectors = self.detectors | set(self.data[0][s])
for d in self.data[0][s]:
self.detectors.add('_' + d)
for d in self.detectors:
if d in self.standards and d[0] is not '_':
if '_' + d not in self.standards:
self.standards['_' + d] = Standard().__dict__
for p in self.data:
p['_' + d] = p[d]
elif 'fpx' in filename or 'fpt' in filename and s[0] != '#':
fields = []
date = []
first = True
for lines in f:
if first:
first = False
spl = lines.split()
for i in range(len(spl)):
try:
if int(spl[i]) in range(1,7):
fields.append('A'+spl[i])
except:
if spl[i] == 'Intensity':
fields.append('Detector')
date = spl[i+1:]
break
self.standards = {'Date': Standard(metadata = True).__dict__}
for s in fields:
self.standards[s] = Standard(metadata = False).__dict__
else:
newdata = {}
spl = lines.split()
for i in range(len(spl)):
try:
newdata[fields[i]] = [float(spl[i])]
except:
pass
newdata['Date'] = date
self.data.append(newdata)
else:
reader = readncnr3.datareader()
mydata = reader.readbuffer(filename)
try:
template['Collimations'] = [mydata.metadata['collimations']['coll1'],mydata.metadata['collimations']['coll2'],mydata.metadata['collimations']['coll3'],mydata.metadata['collimations']['coll4']]
self.standards['Collimations'] = Standard(metadata = True).__dict__
except:
pass
try:
template['Lattice'] = [mydata.metadata['lattice']['a'],mydata.metadata['lattice']['b'],mydata.metadata['lattice']['c'],mydata.metadata['lattice']['alpha'],mydata.metadata['lattice']['beta'],mydata.metadata['lattice']['gamma']]
except:
pass
try:
for sl in mydata.metadata['count_info']:
inStandards = False
for s in self.standards:
if s.lower().split() == ''.join(sl.split('_')):
inStandards = True
template[s] = [mydata.metadata['count_info'][s]]
if not inStandards:
s = sl.split('_')
for i in range(len(s)):
s[i] = s[i].capitalize()
s = ''.join(s)
template[s] = [mydata.metadata['count_info'][s]]
self.standards[s] = Standard(metadata = True).__dict__
except:
pass
try:
template['MonoSpacing'] = [mydata.metadata['dspacing']['monochromator_dspacing']]
template['AnaSpacing'] = [mydata.metadata['dspacing']['analyzer_dspacing']]
except:
pass
try:
template['FixedE'] = [mydata.metadata['energy_info']['efixed'], mydata.metadata['energy_info']['ef']]
except:
pass
try:
for sl in mydata.metadata['file_info']:
inStandards = False
for s in self.standards:
if s.lower().split().join('_') == sl:
inStandards = True
template[s] = [mydata.metadata['file_info'][s]]
if not inStandards:
s = sl.split('_')
for i in range(len(s)):
s[i] = s[i].capitalize()
s = ' '.join(s)
template[s] = [mydata.metadata['file_info'][s]]
self.standards[s] = Standard(metadata = True).__dict__
except:
pass
try:
template['HField'] = [mydata.metadata['magnetic_field']['hfield']]
self.standards['HField'] = Standard(metadata = True).__dict__
except:
pass
try:
template['AnalyzerMosaic'] = [mydata.metadata['mosaic']['mosaic_analyzer']]
self.standards['AnalyzerMosaic'] = Standard(metadata = True).__dict__
template['MonochromatorMosaic'] = [mydata.metadata['mosaic']['mosaic_monochromator']]
self.standards['MonochromatorMosaic'] = Standard(metadata = True).__dict__
template['SampleMosaic'] = [mydata.metadata['mosaic']['mosaic_sample']]
self.standards['SampleMosaic'] = Standard(metadata = True).__dict__
except:
pass
try:
template['Orient'] = [mydata.metadata['orient1']['h'], mydata.metadata['orient1']['k'],mydata.metadata['orient1']['l'],mydata.metadata['orient2']['h'],mydata.metadata['orient2']['k'], mydata.metadata['orient2']['l']]
except:
pass
areMotors = True
motors = []
try:
for i in range(6):
motors.append([mydata.metadata['motor'+str(1+i)]['start'], mydata.metadata['motor' + str(1+i)]['step']])
except:
#print mydata.metadata
areMotors = False
try:
for p in mydata.data:
pcorr = p.split('_')
for i in range(len(pcorr)):
pcorr[i] = pcorr[i].capitalize()
pcorr = ''.join(pcorr)
if pcorr not in self.standards and pcorr not in ['Qx','Qy','Qz','Counts']:
self.standards[pcorr] = Standard(metadata = False).__dict__
count = 0
while(True):
print 'hey'
try:
newdata = copy.copy(template)
for p in mydata.data:
pcorr = p.split('_')
for i in range(len(pcorr)):
pcorr[i] = pcorr[i].capitalize()
pcorr = ''.join(pcorr)
if pcorr[0] == 'Q':
if pcorr[1] == 'x':
pcorr = 'QX'
elif pcorr[1] == 'y':
pcorr = 'QY'
elif pcorr[1] == 'z':
pcorr = 'QZ'
if pcorr == 'Counts':
pcorr = 'Detector'
newdata[pcorr] = [mydata.data[p][count]]
if(areMotors):
for i in range(len(motors)):
newdata['A' + str(i+1)] = [motors[i][0] + motors[i][1] * count]
self.data.append(newdata)
count+=1
except:
break
except:
pass
qtree.addnode(copy.deepcopy(mydata))
#print 'readloop'
#print 'q in loop', qtree.qlist[0].q
for qnode in qtree.qlist:
print qnode.q['h_center'],qnode.q['k_center'],qnode.q['l_center'],len(qnode.th),qnode.th
#print qtree.qlist
return qtree
if __name__=='__main__':
myfilestr=r'C:\Ce2RhIn8\Mar10_2009\magsc035.bt9'
#myfilestr=r'c:\bifeo3xtal\jan8_2008\9175\fpx53418.bt7'
#myfilestr=r'c:\13165\13165\data\MagHigh56784.bt7'
#myfilestr=r'c:\13176\data\CeOFeAs57255.bt7.out'
mydatareader=readncnr.datareader()
mydata=mydatareader.readbuffer(myfilestr)
# print mydata.__dict__
# print mydata.additional_metadata
# print mydata.metadata
# print mydata.metadata['file_info']['scantype']
# print mydata.metadata['collimations']
# print mydata.metadata['dspacing']['monochromator_dspacing']
# print mydata.metadata['dspacing']['analyzer_dspacing']
# print mydata.metadata['lattice']['a']
# print mydata.metadata['lattice']['b']
# print mydata.metadata['lattice']['c']
# print mydata.metadata['lattice']['alpha']
# print mydata.metadata['lattice']['beta']
# print mydata.metadata['lattice']['gamma']
# print mydata.metadata['motor3']['step']
