def extra_fit(selection='(all)',
reference=None,
method='align',
zoom=1,
quiet=0,
_self=cmd,
**kwargs):
'''
DESCRIPTION
Like "intra_fit", but for multiple objects instead of
multiple states.
ARGUMENTS
selection = string: atom selection of multiple objects {default: all}
reference = string: reference object name {default: first object in selection}
method = string: alignment method (command that takes "mobile" and "target"
arguments, like "align", "super", "cealign" {default: align}
... extra arguments are passed to "method"
SEE ALSO
alignto, cmd.util.mass_align, align_all.py from Robert Campbell
'''
zoom, quiet = int(zoom), int(quiet)
models = cmd.get_object_list('(%s)' % selection)
if reference is None:
reference = models[0]
models = models[1:]
elif reference in models:
models.remove(reference)
if cmd.is_string(method):
if method in cmd.keyword:
method = cmd.keyword[method][0]
else:
print('Unknown method ' + str(method))
raise CmdException
for model in models:
x = method(mobile='(%s) and model %s' % (selection, model),
target='(%s) and model %s' % (selection, reference),
**kwargs)
if not quiet:
if cmd.is_sequence(x):
print('%-20s RMS = %8.3f (%d atoms)' % (model, x[0], x[1]))
elif isinstance(x, float):
print('%-20s RMS = %8.3f' % (model, x))
elif _self.is_dict(x) and 'RMSD' in x:
natoms = x.get('alignment_length', 0)
suffix = (' (%s atoms)' % natoms) if natoms else ''
print('%-20s RMS = %8.3f' % (model, x['RMSD']) + suffix)
else:
print('%-20s' % (model, ))
if zoom:
cmd.zoom(selection)
def extra_fit(selection='(all)', reference=None, method='align', zoom=1,
quiet=0, _self=cmd, **kwargs):
'''
DESCRIPTION
Like "intra_fit", but for multiple objects instead of
multiple states.
ARGUMENTS
selection = string: atom selection of multiple objects {default: all}
reference = string: reference object name {default: first object in selection}
method = string: alignment method (command that takes "mobile" and "target"
arguments, like "align", "super", "cealign" {default: align}
... extra arguments are passed to "method"
SEE ALSO
alignto, cmd.util.mass_align, align_all.py from Robert Campbell
'''
zoom, quiet = int(zoom), int(quiet)
sele_name = cmd.get_unused_name('_')
cmd.select(sele_name, selection) # for speed
models = cmd.get_object_list(sele_name)
if reference is None:
reference = models[0]
models = models[1:]
elif reference in models:
models.remove(reference)
else:
cmd.select(sele_name, reference, merge=1)
if cmd.is_string(method):
if method in cmd.keyword:
method = cmd.keyword[method][0]
else:
print('Unknown method:', method)
raise CmdException
for model in models:
x = method(mobile='%s and model %s' % (sele_name, model),
target='%s and model %s' % (sele_name, reference), **kwargs)
if not quiet:
if cmd.is_sequence(x):
print('%-20s RMS = %8.3f (%d atoms)' % (model, x[0], x[1]))
elif isinstance(x, float):
print('%-20s RMS = %8.3f' % (model, x))
elif isinstance(x, dict) and 'RMSD' in x:
natoms = x.get('alignment_length', 0)
suffix = (' (%s atoms)' % natoms) if natoms else ''
print('%-20s RMS = %8.3f' % (model, x['RMSD']) + suffix)
else:
print('%-20s' % (model,))
if zoom:
cmd.zoom(sele_name)
cmd.delete(sele_name)
def pmf(key, cutoff=7.0, selection1='(name CB)', selection2='', state=1, quiet=1):
'''
DESCRIPTION
Potential of Mean Force
ARGUMENTS
key = string: aaindex key
cutoff = float: distance cutoff {default: 7.0}
cutoff = (float, float): distance shell
selection1 = string: atom selection {default: (name CB)}
selection2 = string: atom selection {default: selection1}
NOTES
Does also support a list of keys and a list of cutoffs to deal with
multiple distance shells.
EXAMPLES
# distance dependent c-beta contact potentials
pmf SIMK990101, 5, /2x19//A//CB
pmf SIMK990102, [5, 7.5], /2x19//A//CB
pmf [SIMK990101, SIMK990102, SIMK990103], [0, 5, 7.5, 10], /2x19//A//CB
# interface potential
sidechaincenters 2x19_scc, 2x19
pmf KESO980102, 7.0, /2x19_scc//A, /2x19_scc//B
distance /2x19_scc//A, /2x19_scc//B, cutoff=7.0
'''
from pymol import cmd, stored
from chempy import cpv
if cmd.is_string(key):
if key.lstrip().startswith('['):
key = cmd.safe_alpha_list_eval(key)
else:
key = [key]
if cmd.is_string(cutoff):
cutoff = eval(cutoff)
if not cmd.is_sequence(cutoff):
cutoff = [cutoff]
if len(cutoff) == len(key):
cutoff = [0.0] + list(cutoff)
if len(cutoff) != len(key) + 1:
print('Error: Number of keys and number of cutoffs inconsistent')
return
state = int(state)
quiet = int(quiet)
if len(selection2) == 0:
selection2 = selection1
if not quiet and len(key) > 1:
print('Distance shells:')
for i in range(len(key)):
print('%s %.1f-%.1f' % (key[i], cutoff[i], cutoff[i + 1]))
idmap = dict()
cmd.iterate_state(state, '(%s) or (%s)' % (selection1, selection2),
'idmap[model,index] = [(resn,name),(x,y,z)]', space={'idmap': idmap})
twoN = cmd.count_atoms(selection1) + cmd.count_atoms(selection2)
pairs = cmd.find_pairs(selection1, selection2, cutoff=max(cutoff),
state1=state, state2=state)
if len(pairs) == 0:
print('Empty pair list')
return 0.0
matrix = list(map(get, key))
for i in matrix:
assert isinstance(i, MatrixRecord)
i_list = list(range(len(key)))
u_sum = 0
count = 0
for id1, id2 in pairs:
a1 = idmap[id1]
a2 = idmap[id2]
r = cpv.distance(a1[1], a2[1])
for i in i_list:
if cutoff[i] <= r and r < cutoff[i + 1]:
try:
aa1 = to_one_letter_code[a1[0][0]]
aa2 = to_one_letter_code[a2[0][0]]
u_sum += matrix[i].get(aa1, aa2)
count += 1
except:
print('Failed for', a1[0], a2[0])
value = float(u_sum) / twoN
if not quiet:
print('PMF: %.4f (%d contacts, %d residues)' % (value, count, twoN))
return value
def pmf(key,
cutoff=7.0,
selection1='(name CB)',
selection2='',
state=1,
quiet=1):
'''
DESCRIPTION
Potential of Mean Force
ARGUMENTS
key = string: aaindex key
cutoff = float: distance cutoff {default: 7.0}
cutoff = (float, float): distance shell
selection1 = string: atom selection {default: (name CB)}
selection2 = string: atom selection {default: selection1}
NOTES
Does also support a list of keys and a list of cutoffs to deal with
multiple distance shells.
EXAMPLES
# distance dependent c-beta contact potentials
pmf SIMK990101, 5, /2x19//A//CB
pmf SIMK990102, [5, 7.5], /2x19//A//CB
pmf [SIMK990101, SIMK990102, SIMK990103], [0, 5, 7.5, 10], /2x19//A//CB
# interface potential
sidechaincenters 2x19_scc, 2x19
pmf KESO980102, 7.0, /2x19_scc//A, /2x19_scc//B
distance /2x19_scc//A, /2x19_scc//B, cutoff=7.0
'''
from pymol import cmd, stored
from chempy import cpv
if cmd.is_string(key):
if key.lstrip().startswith('['):
key = cmd.safe_alpha_list_eval(key)
else:
key = [key]
if cmd.is_string(cutoff):
cutoff = eval(cutoff)
if not cmd.is_sequence(cutoff):
cutoff = [cutoff]
if len(cutoff) == len(key):
cutoff = [0.0] + list(cutoff)
if len(cutoff) != len(key) + 1:
print 'Error: Number of keys and number of cutoffs inconsistent'
return
state = int(state)
quiet = int(quiet)
if len(selection2) == 0:
selection2 = selection1
if not quiet and len(key) > 1:
print 'Distance shells:'
for i in range(len(key)):
print '%s %.1f-%.1f' % (key[i], cutoff[i], cutoff[i + 1])
idmap = dict()
cmd.iterate_state(state,
'(%s) or (%s)' % (selection1, selection2),
'idmap[model,index] = [(resn,name),(x,y,z)]',
space={'idmap': idmap})
twoN = cmd.count_atoms(selection1) + cmd.count_atoms(selection2)
pairs = cmd.find_pairs(selection1,
selection2,
cutoff=max(cutoff),
state1=state,
state2=state)
if len(pairs) == 0:
print 'Empty pair list'
return 0.0
matrix = map(get, key)
for i in matrix:
assert isinstance(i, MatrixRecord)
i_list = range(len(key))
u_sum = 0
count = 0
for id1, id2 in pairs:
a1 = idmap[id1]
a2 = idmap[id2]
r = cpv.distance(a1[1], a2[1])
for i in i_list:
if cutoff[i] <= r and r < cutoff[i + 1]:
try:
aa1 = to_one_letter_code[a1[0][0]]
aa2 = to_one_letter_code[a2[0][0]]
u_sum += matrix[i].get(aa1, aa2)
count += 1
except:
print 'Failed for', a1[0], a2[0]
value = float(u_sum) / twoN
if not quiet:
print 'PMF: %.4f (%d contacts, %d residues)' % (value, count, twoN)
return value
