'Input two maps, their resolutions(required) and contours(optional)'
)
print 'reading map1'
if c1 is None:
Name1, emmap1, c1 = map_contour(m1, t=1.5)
else:
Name1 = os.path.basename(m1).split('.')[0]
emmap1 = MapParser.readMRC(m1)
print 'reading map2'
if c2 is None:
Name2, emmap2, c2 = map_contour(m2, t=1.5)
else:
Name2 = os.path.basename(m2).split('.')[0]
emmap2 = MapParser.readMRC(m2)
if not sc.mapComparison(emmap1, emmap2):
if None in [r1, r2]:
sys.exit(
'Input two maps, their resolutions(required) and contours(optional)'
)
emmap1._crop_box(c1, 0.5)
emmap2._crop_box(c2, 0.5)
if r1 > 1.25 * r2:
emmap_2 = lpfilter(emmap2, r1)
emmap1, emmap2 = match_grid(emmap1, emmap_2, c1, c2)
elif r2 > 1.25 * r1:
emmap_1 = lpfilter(emmap1, r2)
emmap1, emmap2 = match_grid(emmap_1, emmap2, c1, c2)
else:
emmap1, emmap2 = match_grid(emmap1, emmap2, c1, c2)
def score_cmd(session, comparators, compared, rez_comparators, rez_compared, contours_comparators, contour_compared):
sc = ScoringFunctions()
blurrer = StructureBlurrer()
# Loop through these to be compared
idx = 0
scores = []
for comparator in comparators:
emmap1 = None
emmap2 = None
if type(comparator) is AtomicStructure:
if type(compared) is AtomicStructure:
# Both models
if None in ([rez_compared] + rez_comparators):
print("Please provide the resolution for all models")
return
bms1 = chimera_to_tempy_model(compared)
bms2 = chimera_to_tempy_model(comparator)
emmap1 = model_contour( bms1, rez_compared, emmap=False,t=0.5)
if contours_comparators[idx] is None:
emmap2 = model_contour(bms2, rez_comparators[idx],emmap=False,t=0.5)
else:
emmap2 = blur_model(bms2, rez_comparators[idx], emmap=False)
else:
# 0 - map, 1 - model
if rez_comparators[idx] == None:
print("Please provide the resolution for the model.")
return
emmap1 = chimera_to_tempy_map(compared)
bms = chimera_to_tempy_model(comparator)
emmap2 = blurrer.gaussian_blur(bms, rez_compared, densMap=emmap1)
else:
if type(compared) is AtomicStructure:
# 0 - model, 1 - map
if rez_compared == None:
print("Please provide the resolution for the model.")
return
emmap2 = chimera_to_tempy_map(comparator)
bms = chimera_to_tempy_model(compared)
emmap1 = blurrer.gaussian_blur(bms, rez_compared, densMap=emmap2)
else:
# 0 - map, 1 - map
emmap1 = chimera_to_tempy_map(compared)
emmap2 = chimera_to_tempy_map(comparator)
c1 = contour_compared
# Contouring
if c1 == None:
c1 = map_contour(emmap1,t=1.5)
c2 = contours_comparators[idx]
# This kinda makes no sense and could be tricky
if c2 == None:
c2 = map_contour(emmap2,t=1.5)
# Some kind of fix if the maps don't match?
# Resize, resample or blur of somekind
if not sc.mapComparison(emmap1,emmap2):
emmap1._crop_box(c1,0.5)
emmap2._crop_box(c2,0.5)
if rez_compared > 1.25*rez_comparators[idx]:
emmap_2 = lpfilter(emmap2,rez_compared)
emmap1, emmap2 = match_grid(emmap1,emmap_2,c1,c2)
elif rez_comparators[idx] > 1.25*rez_compared:
emmap_1 = lpfilter(emmap1,rez_comparators[idx])
emmap1, emmap2 = match_grid(emmap_1,emmap2,c1,c2)
else:
emmap1, emmap2 = match_grid(emmap1,emmap2,c1,c2)
nmi = 0.0
try:
nmi = sc.MI(emmap1,emmap2,c1,c2,1,None,None,True)
if nmi < 0.0: nmi = 0.0
except:
print('Exception for NMI score')
print_exc()
nmi = 0.0
scores.append(nmi)
idx+=1
return scores
def test_tempy_nmi(self):
''' Test the tempy nmi score based on the files
provided. Use this as a baseline for the second
chimeraX test. '''
path_test = "./"
m = os.path.join(path_test, 'emd_5168.map')
p = os.path.join(path_test, 'emd_5170.map')
sc = ScoringFunctions()
rez1 = 6.6
rez2 = 15.0
Name1, emmap1, c1 = map_contour(m, t=1.5)
Name2, emmap2, c2 = map_contour(p, t=1.5)
print(rez1, rez2, c1, c2, emmap1.apix, emmap2.apix)
if not sc.mapComparison(emmap1, emmap2):
emmap1._crop_box(c1, 0.5)
emmap2._crop_box(c2, 0.5)
if rez1 > 1.25 * rez2:
emmap_2 = lpfilter(emmap2, rez1)
emmap1, emmap2 = match_grid(emmap1, emmap_2, c1, c2)
elif rez2 > 1.25 * rez1:
emmap_1 = lpfilter(emmap1, rez2)
emmap1, emmap2 = match_grid(emmap_1, emmap2, c1, c2)
else:
emmap1, emmap2 = match_grid(emmap1, emmap2, c1, c2)
nmi = 0
try:
nmi = sc.MI(emmap1, emmap2, c1, c2, 1, None, None, True)
if nmi < 0.0: nmi = 0.0
except:
self.assertTrue(False)
print_exc()
nmi = 0.0
self.assertTrue(abs(round(nmi, 5) - 1.0492) < 0.001)
# Now test with a model and map
p = os.path.join(path_test, '1J6Z.pdb')
m = os.path.join(path_test, 'emd_5168_monomer.mrc')
res = 6.6
Name1 = os.path.basename(m).split('.')[0]
Name2 = os.path.basename(p).split('.')[0]
emmap1 = MapParser.readMRC(m)
structure_instance = PDBParser.read_PDB_file(Name2,
p,
hetatm=False,
water=False)
blurrer = StructureBlurrer()
emmap2 = blurrer.gaussian_blur(structure_instance, res, densMap=emmap1)
c1 = 9.7
c2 = 1.0
nmi = 0
try:
nmi = sc.MI(emmap1, emmap2, c1, c2, 1, None, None, True)
if nmi < 0.0: nmi = 0.0
except:
self.assertTrue(False)
print_exc()
nmi = 0.0
self.assertTrue(abs(round(nmi, 5) - 1.0575) < 0.001)
def score(session, atomic_model1 = None, map_model1 = None, atomic_model2 = None, map_model2 = None, rez1 = None, rez2 = None, c1 = None, c2 = None):
""" Generate the NMI score for 2 maps or 1 map and 1 model. """
sc = ScoringFunctions()
# We have choices - 1 map and one model, 2 maps or 2 models
emmap1 = None
emmap2 = None
blurrer = StructureBlurrer()
if atomic_model1 != None and map_model1 != None:
# 1 map 1 model
if rez1 == None:
print("Please provide the resolution for the model.")
return
emmap1 = chimera_to_tempy_map(map_model1)
bms = chimera_to_tempy_model(atomic_model1)
emmap2 = blurrer.gaussian_blur(bms, rez1, densMap=emmap1)
elif map_model1 != None and map_model2 != None:
# 2 maps
emmap1 = chimera_to_tempy_map(map_model1)
emmap2 = chimera_to_tempy_map(map_model2)
elif atomic_model1 != None and atomic_model2 != None:
# 2 models
if None in [rez1,rez2]:
print("Please provide the resolution for both model")
return
bms1 = chimera_to_tempy_model(atomic_model1)
bms2 = chimera_to_tempy_model(atomic_model2)
emmap1 = model_contour( bms1, rez1, emmap=False,t=0.5)
if c2 is None:
emmap2 = model_contour(bms2, rez2,emmap=False,t=0.5)
else:
emmap2 = blur_model( bms2, rez2, emmap=False)
else:
print("Error. Must have 1 model and 1 map, 2 maps or 2 models")
return
# Contouring
if c1 == None:
c1 = map_contour(emmap1,t=1.5)
if c2 == None:
c2 = map_contour(emmap2,t=1.5)
# Some kind of fix if the maps don't match?
# Resize, resample or blur of somekind
if not sc.mapComparison(emmap1,emmap2):
emmap1._crop_box(c1,0.5)
emmap2._crop_box(c2,0.5)
if rez1 > 1.25*rez2:
emmap_2 = lpfilter(emmap2,rez1)
emmap1, emmap2 = match_grid(emmap1,emmap_2,c1,c2)
elif rez2 > 1.25*rez1:
emmap_1 = lpfilter(emmap1,rez2)
emmap1, emmap2 = match_grid(emmap_1,emmap2,c1,c2)
else:
emmap1, emmap2 = match_grid(emmap1,emmap2,c1,c2)
nmi = 0.0
try:
nmi = sc.MI(emmap1,emmap2,c1,c2,1,None,None,True)
if nmi < 0.0: nmi = 0.0
except:
print('Exception for NMI score')
print_exc()
nmi = 0.0
return nmi