if molType == 'protein':
n_points = 200
else:
# Less critical for DNA, RNA, ...
n_points = 100
for atom_type in ('H','C','N'):
#atom_type = 'H'
ref_cutoff = None
normalise = True
exclude_outliers = 4.
n_iterations = 1
print 'Reading raw data...'
full_set = getPickledDict(os.path.join("../originalData/results/",database))
for entry in full_set.keys():
if full_set[entry].has_key(molType):
full_set[entry] = full_set[entry][molType]
else:
del(full_set[entry])
print 'Running estimation for full set...'
full_ref, full_stats, full_bounds, full_processed = run_estimation(full_set, n=1, n_points=n_points,
ref_cutoff=ref_cutoff,
atom_type=atom_type,
molType = molType)
if atom_type == 'C' and molType == 'protein':
def getVascoRerefInfo(self):
#
# Get VASCO reference info
#
dateStamp = "20100225"
stats = getPickledDict(os.path.join(self.vascoRefDataPath,"stats_%s.pp" % dateStamp))
bounds = getPickledDict(os.path.join(self.vascoRefDataPath,"bounds_%s.pp" % dateStamp))
self.rerefInfo = {}
for molType in ('protein',):#'RNA'):
if molType == 'protein':
group0 = {'arg': ('cz',), #@UnusedVariable
'asn': ('cg',),
'asp': ('cg',),
'gln': ('cd',),
'glu': ('cd',),
'phe': ('cg',),
'trp': ('cd2','ce2'),
'tyr': ('cg', 'cz')}
group1 = {'arg': ('cz',),
'asn': ('cg',),
'asp': ('cg',),
'gln': ('cd',),
'glu': ('cd',),
'phe': ('cg',),
'trp': ('cd2','ce2'),
'tyr': ('cg', 'cz'),
'*': ('c',)}
group2 = {'his': ('cd2', 'ce1'),
'phe': ('cd1', 'cd2', 'ce1', 'ce2', 'cz'),
'trp': ('cd1', 'ce3', 'ch2', 'cz2', 'cz3'),
'tyr': ('cd1', 'cd2', 'ce1', 'ce2')}
group4 = {'*': ('c',)}
if molType == 'protein':
n_points = 200 #@UnusedVariable
else:
# Less critical for DNA, RNA, ...
n_points = 100 #@UnusedVariable
for atom_type in ('H','C','N'):
"""
#atom_type = 'H'
ref_cutoff = None
normalise = True
exclude_outliers = 4.
n_iterations = 1
print 'Reading raw data...'
full_set = getPickledDict(os.path.join("../originalData/results/",database))
for entry in full_set.keys():
if full_set[entry].has_key(molType):
full_set[entry] = full_set[entry][molType]
else:
del(full_set[entry])
print 'Running estimation for full set...'
full_ref, full_stats, full_bounds, full_processed = run_estimation(full_set, n=1, n_points=n_points,
ref_cutoff=ref_cutoff,
atom_type=atom_type,
molType = molType)
"""
if atom_type == 'C' and molType == 'protein':
#sel0 = make_selection(group0)
sel1 = make_selection(group1)
sel2 = make_selection(group2)
# TODO Fix this one!
sel3 = make_sel3(stats[atom_type][3], sel1+sel2)
sel4 = make_selection(group4)
tmpEntry = {'tmpEntry': self.entry}
#set_group0 = select_entries(tmpEntry, sel0)
set_group1 = select_entries(tmpEntry, sel1)
set_group2 = select_entries(tmpEntry, sel2)
set_group3 = select_entries(tmpEntry, sel3)
set_group4 = select_entries(tmpEntry, sel4)
groups = {1: set_group1, 2: set_group2, 3: set_group3, 4: set_group4}
else:
groups = {None: self.entry}
for i, group in groups.items():
if atom_type == 'C' and molType == 'protein':
useBounds = bounds[atom_type][i]
useStats = stats[atom_type][i]
else:
useBounds = bounds[atom_type]
useStats = stats[atom_type]
if group.has_key('tmpEntry'):
group = group['tmpEntry']
(rerefValue,rerefError,_void) = estimate_reference_single(group, useStats, useBounds, entry_name='temp', atom_type=atom_type,
exclude_outliers=False,molType=molType,verbose=False)
#print atom_type, i
if rerefValue != None:
rerefValue = -rerefValue
self.rerefInfo[(atom_type,i)] = (rerefValue,rerefError)
#
# Print out info
#
atomKeys = self.rerefInfo.keys()
atomKeys.sort()
if self.showMessages:
for atomKey in atomKeys:
print atomKey,
print self.rerefInfo[atomKey]
def getVascoRerefInfo(self):
#
# Get VASCO reference info
#
dateStamp = "20100225"
stats = getPickledDict(
os.path.join(self.vascoRefDataPath, "stats_%s.pp" % dateStamp))
bounds = getPickledDict(
os.path.join(self.vascoRefDataPath, "bounds_%s.pp" % dateStamp))
self.rerefInfo = {}
for molType in ('protein', ): #'RNA'):
if molType == 'protein':
group0 = {
'arg': ('cz', ), #@UnusedVariable
'asn': ('cg', ),
'asp': ('cg', ),
'gln': ('cd', ),
'glu': ('cd', ),
'phe': ('cg', ),
'trp': ('cd2', 'ce2'),
'tyr': ('cg', 'cz')
}
group1 = {
'arg': ('cz', ),
'asn': ('cg', ),
'asp': ('cg', ),
'gln': ('cd', ),
'glu': ('cd', ),
'phe': ('cg', ),
'trp': ('cd2', 'ce2'),
'tyr': ('cg', 'cz'),
'*': ('c', )
}
group2 = {
'his': ('cd2', 'ce1'),
'phe': ('cd1', 'cd2', 'ce1', 'ce2', 'cz'),
'trp': ('cd1', 'ce3', 'ch2', 'cz2', 'cz3'),
'tyr': ('cd1', 'cd2', 'ce1', 'ce2')
}
group4 = {'*': ('c', )}
if molType == 'protein':
n_points = 200 #@UnusedVariable
else:
# Less critical for DNA, RNA, ...
n_points = 100 #@UnusedVariable
for atom_type in ('H', 'C', 'N'):
"""
#atom_type = 'H'
ref_cutoff = None
normalise = True
exclude_outliers = 4.
n_iterations = 1
print 'Reading raw data...'
full_set = getPickledDict(os.path.join("../originalData/results/",database))
for entry in full_set.keys():
if full_set[entry].has_key(molType):
full_set[entry] = full_set[entry][molType]
else:
del(full_set[entry])
print 'Running estimation for full set...'
full_ref, full_stats, full_bounds, full_processed = run_estimation(full_set, n=1, n_points=n_points,
ref_cutoff=ref_cutoff,
atom_type=atom_type,
molType = molType)
"""
if atom_type == 'C' and molType == 'protein':
#sel0 = make_selection(group0)
sel1 = make_selection(group1)
sel2 = make_selection(group2)
# TODO Fix this one!
sel3 = make_sel3(stats[atom_type][3], sel1 + sel2)
sel4 = make_selection(group4)
tmpEntry = {'tmpEntry': self.entry}
#set_group0 = select_entries(tmpEntry, sel0)
set_group1 = select_entries(tmpEntry, sel1)
set_group2 = select_entries(tmpEntry, sel2)
set_group3 = select_entries(tmpEntry, sel3)
set_group4 = select_entries(tmpEntry, sel4)
groups = {
1: set_group1,
2: set_group2,
3: set_group3,
4: set_group4
}
else:
groups = {None: self.entry}
for i, group in groups.items():
if atom_type == 'C' and molType == 'protein':
useBounds = bounds[atom_type][i]
useStats = stats[atom_type][i]
else:
useBounds = bounds[atom_type]
useStats = stats[atom_type]
if group.has_key('tmpEntry'):
group = group['tmpEntry']
(rerefValue, rerefError,
_void) = estimate_reference_single(group,
useStats,
useBounds,
entry_name='temp',
atom_type=atom_type,
exclude_outliers=False,
molType=molType,
verbose=False)
#print atom_type, i
if rerefValue != None:
rerefValue = -rerefValue
self.rerefInfo[(atom_type, i)] = (rerefValue, rerefError)
#
# Print out info
#
atomKeys = self.rerefInfo.keys()
atomKeys.sort()
if self.showMessages:
for atomKey in atomKeys:
print atomKey,
print self.rerefInfo[atomKey]
