def all_vs_all(filename='rms_matrix.txt'):
AllObj=cmd.get_names("public_objects") # not temps created by alignment or selections
matrix = []
for x in AllObj:
x_to_all = []
for y in AllObj:
rmsd = cmd.rms( x, y, cutoff=10)#[0] # super-inclusive
x_to_all.append(rmsd)
matrix.append(x_to_all)
print matrix
outfile = open(filename,'w')
# No names 'on top' -- we can figure these out from the vertical ordering
# and they're way too long...
#for name in AllObj:
# outfile.write("\t%s" % name)
#outfile.write("\n")
maxlen = 0
for obj in AllObj:
if maxlen < len(obj):
maxlen = len(obj)
print_allobj = []
for obj in AllObj:
while len(obj) < maxlen:
obj += ' '
print_allobj.append(obj)
ni = 0
for x in matrix:
outfile.write(print_allobj[ni])
ni += 1
for y in x:
outfile.write("\t%0.2f" % y)
outfile.write("\n")
def testFit(self):
cmd.fragment("gly", "m1")
cmd.create("m2", "m1")
rms = cmd.fit("m1", "m2")
self.assertEqual(rms, 0.0)
rms = cmd.rms("m1", "m2")
self.assertEqual(rms, 0.0)
rms = cmd.rms_cur("m1", "m2")
self.assertEqual(rms, 0.0)
def testFit(self):
cmd.fragment("gly", "m1")
cmd.create("m2", "m1")
rms = cmd.fit("m1", "m2")
self.assertEqual(rms, 0.0)
rms = cmd.rms("m1", "m2")
self.assertEqual(rms, 0.0)
rms = cmd.rms_cur("m1", "m2")
self.assertEqual(rms, 0.0)
def ens_rmsd(ens_selection,
ref_selection,
log_name = None):
'''
DESCRIPTION
Prints RMSD per structure in ensemble w.r.t. a reference structure
USAGE
ens_rmsd ensemble_selection, reference_selection, name, log,
ARGUMENTS
log = name of log file
verbose = calculates structure by structure RMSD for ensemble w.r.t. a single reference structure
EXAMPLE
ens_rmsd ensemble_selection, reference_selection, name = 'rmsd', log 'ens.log'
'''
if log_name == None:
log = LogWriter(sys.stdout, 'log.txt')
else:
log = LogWriter(sys.stdout, log_name+'.txt')
# initialize arrays
ens_selection = ens_selection + ' and not resn hoh'
ref_selection = ref_selection + ' and not resn hoh'
rmsd_states = []
mean_coords = None
number_models = cmd.count_states(ens_selection)
# get models, mean coords
print >> log, '\nRMSD by state'
print >> log, '\n State | RMSD'
for i in range(number_models):
ens_coords = cmd.get_model(ens_selection,state=i+1).get_coord_list()
ref_coords = cmd.get_model(ref_selection,state=1).get_coord_list()
atom_sqr_dev = []
for atom in xrange(len(ref_coords)):
x = ref_coords[atom]
y = ens_coords[atom]
atom_sqr_dev.append(distance(x,y)**2)
rmsd = math.sqrt(sum(atom_sqr_dev) / len(atom_sqr_dev))
rmsd_states.append(rmsd)
print >> log, ' %5d | %5.3f '%(i+1, rmsd)
print_array_stats(array = rmsd_states,
log = log)
print '\nRMSD all states : %5.3f '%(cmd.rms(ens_selection, ref_selection))
def rms_per_residue(sel1, sel2):
atoms1 = get_atoms(sel1, ["chain", "resi"])
atoms2 = get_atoms(sel2, ["chain", "resi"])
resis1 = set(zip(atoms1.resi, atoms1.chain))
resis2 = set(zip(atoms2.resi, atoms2.chain))
labels = []
values = []
for resi, chain in resis1:
labels.append(f"{resi}{chain}")
values.append(
pm.rms(
f"({sel1}) and resi {resi} and chain {chain}",
f"({sel2}) and resi {resi} and chain {chain}",
))
ax = sb.lineplot(labels, values)
ax.set_title("RMS per residue")
ax.set_xticklabels(labels, rotation=45, ha="right")
plt.show()
cmd.create("trg", "ref", 1, a, quiet=0)
cmd.alter_state(a, "trg", "x=x+random()/2")
cmd.alter_state(a, "trg", "y=y+random()/2")
cmd.alter_state(a, "trg", "z=z+random()/2", quiet=0)
cmd.frame(1)
print "%8.3f" % cmd.fit("ref", "trg")
# asdf
for a in xrange(1, 14):
print a,
print "%8.3f" % cmd.fit("ref and resi %d" % a, "trg"),
print "%8.3f" % cmd.rms("ref", "trg"),
print "%8.3f" % cmd.rms_cur("ref", "trg")
cmd.frame(10)
print "%8.3f" % cmd.fit("ref", "trg")
for a in xrange(1, 14):
print a,
print "%8.3f" % cmd.fit("ref and resi %d" % a, "trg"),
print "%8.3f" % cmd.rms("ref", "trg"),
print "%8.3f" % cmd.rms_cur("ref", "trg")
a = 1
print "%8.3f" % cmd.fit("ref", "trg")
for b in xrange(1, 11):
for a in xrange(1, 11):
cmd.create("trg", "ref", 1, a, quiet=0)
cmd.alter_state(a, "trg", "x=x+random()/2")
cmd.alter_state(a, "trg", "y=y+random()/2")
cmd.alter_state(a, "trg", "z=z+random()/2", quiet=0)
cmd.frame(1)
print "%8.3f" % cmd.fit("ref", "trg")
# asdf
for a in xrange(1, 14):
print a,
print "%8.3f" % cmd.fit("ref and resi %d" % a, "trg"),
print "%8.3f" % cmd.rms("ref", "trg"),
print "%8.3f" % cmd.rms_cur("ref", "trg")
cmd.frame(10)
print "%8.3f" % cmd.fit("ref", "trg")
for a in xrange(1, 14):
print a,
print "%8.3f" % cmd.fit("ref and resi %d" % a, "trg"),
print "%8.3f" % cmd.rms("ref", "trg"),
print "%8.3f" % cmd.rms_cur("ref", "trg")
a = 1
print "%8.3f" % cmd.fit("ref", "trg")
for b in xrange(1, 11):
cmd._dump_floats(cmd.intra_fit("trg and resi %d" % a, b))
def align_rms(target1, target2):
cmd.load(target1, "t1")
cmd.load(target2, "t2")
cmd.align("t1", "t2")
return cmd.rms("t1 and resn unk", "t2 and resn unk")