def test_match(self):
a = np.array([0.0, 0.19,0.41,0.62,0.65,0.78,1.0])
b = np.array([0.0,0.10,0.21,0.39,0.61, 0.79,1.0])
ca,cb = find_neighbours(a,b)
ab = zip(*[a[ca],b[cb]])
self.assertFalse(ca[4])
self.assertFalse(cb[1])
self.assertListEqual(ab,[(0.0,0.0),(0.19,0.21),(0.41,0.39),(0.62,0.61),
(0.78,0.79),(1.0,1.0)])
def identify(peaks,unit_cell,space_group,name='phase',qmax=10):
'''Finds abd labels peaks that correspond to the provided parameters
This will only work if the spectrum is well calibrated. The peaks
are provided with hkl attributes and a new name
Parameters
==========
peaks : sequence
any sequence of Peak instances
unit_cell : list of floats
unit cell of the material in form [a,b,c,alpha,beta,gamma]
space_group : str or int
Hermann–Mauguin notation of the space group
name : string
new name to give peaks that are match
qmax : float
maximum q value for the last reflection
Returns
=======
subset : list, Peak
A list of those peaks that matched the unit cell
'''
from edxrd import calibration
from edxrd.tools import unitcell
cens = np.asarray([peak.centre.nominal_value for peak in peaks])
known,hkls = unitcell.get_unique_peaks(unit_cell,space_group,0,qmax)
known = np.asarray(known)
cancond,nwncond = calibration.find_neighbours(cens,known)
#known = known[nwncond]
#hkls = hkls[nwncond]
#matched = calibration.match(cens,known)
#peaks = [peak for i,peak in enumerate(peaks) if cancond[i] == True]
subset=[]
j=0
for i,peak in enumerate(peaks):
if cancond[i] == True:
peak.name = name+'_'+''.join([str(int(n)) for n in hkls[j]])
j+=1
subset.append(peak)
return subset