def exercise_clashscore():
if (not libtbx.env.has_module(name="probe")):
print "Skipping exercise_clashscore(): probe not configured"
return
pdb_io = pdb.input(source_info=None, lines=pdb_str_1)
pdb_hierarchy = pdb_io.construct_hierarchy()
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy,
fast=False,
condensed_probe=True,
out=null_out())
for unpickle in [False, True]:
if unpickle:
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 35.29, eps=0.01)
bad_clashes_list = cs.results
assert ([c.format_old() for c in bad_clashes_list] == [
' A 72 ARG HG2 A 72 ARG O :1.048',
' A 71 LEU HA A 71 LEU HD12 :0.768',
' A 72 ARG CG A 72 ARG O :0.720'
]), [c.format_old() for c in bad_clashes_list]
#test nuclear distances
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy,
fast=False,
condensed_probe=True,
nuclear=True)
for unpickle in [False, True]:
if (unpickle):
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 58.82, eps=0.01)
bad_clashes_list = cs.results
assert ([c.format_old() for c in bad_clashes_list] == [
' A 72 ARG HG2 A 72 ARG O :1.085',
' A 71 LEU HA A 71 LEU HD12 :0.793',
' A 72 ARG CG A 72 ARG O :0.720',
' A 72 ARG HD3 A 72 ARG HH11 :0.669',
' A 72 ARG HB3 A 72 ARG HE :0.647'
]), [c.format_old() for c in bad_clashes_list]
#test B factor cutoff
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy,
fast=False,
condensed_probe=True,
b_factor_cutoff=40)
for unpickle in [False, True]:
if (unpickle):
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 35.29, eps=0.01)
c_score_b_cutoff = cs.get_clashscore_b_cutoff()
assert approx_equal(c_score_b_cutoff, 39.47, eps=0.01)
bad_clashes_list = cs.results
assert ([c.format_old() for c in bad_clashes_list] == [
' A 72 ARG HG2 A 72 ARG O :1.048',
' A 71 LEU HA A 71 LEU HD12 :0.768',
' A 72 ARG CG A 72 ARG O :0.720'
]), [c.format_old() for c in bad_clashes_list]
def exercise () :
from mmtbx.regression.make_fake_anomalous_data import generate_calcium_inputs
from mmtbx.command_line import find_peaks_holes
mtz_file, pdb_file = generate_calcium_inputs(
file_base = "tst_find_peaks_holes", anonymize = True)
out = StringIO()
peaks_holes = find_peaks_holes.run(
args=[pdb_file, mtz_file],
out=out)
peaks_holes.save_pdb_file(file_name="tst_fph_peaks.pdb", log=null_out())
p = easy_pickle.dumps(peaks_holes)
s = peaks_holes.get_summary()
sp = easy_pickle.dumps(s)
out2 = StringIO()
s.show(out=out2)
lines = out2.getvalue().splitlines()
assert (""" anomalous H2O (anomalous > 3): 1""" in lines)
assert (""" anomalous non-water atoms: 0""" in lines)
assert (""" mFo-DFc > 9: 0""" in lines)
peaks_holes = find_peaks_holes.run(
args=[pdb_file, mtz_file, "filter_peaks_by_2fofc=1.0"],
out=null_out())
out3 = StringIO()
peaks_holes.get_summary().show(out=out3)
lines = out3.getvalue().splitlines()
assert (""" anomalous > 3: 0""" in lines)
out3 = StringIO()
peaks_holes = find_peaks_holes.run(
args=[pdb_file, mtz_file, "include_peaks_near_model=True",],
out=out3)
lines = out3.getvalue().splitlines()
assert (""" mFo-DFc > 9: 1""" in lines)
os.remove(mtz_file)
os.remove(pdb_file)
def exercise_clashscore ():
if (not libtbx.env.has_module(name="probe")):
print "Skipping exercise_clashscore(): probe not configured"
return
pdb_io = pdb.input(source_info=None, lines=pdb_str_1)
pdb_hierarchy = pdb_io.construct_hierarchy()
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy, out=null_out())
for unpickle in [False, True] :
if (unpickle) :
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 35.29, eps=0.01)
bad_clashes_list = cs.results
assert ([ c.format_old() for c in bad_clashes_list ] ==
[' A 72 ARG HG2 A 72 ARG O :-1.038',
' A 72 ARG CG A 72 ARG O :-0.465',
' A 71 LEU HA A 71 LEU HD12 :-0.446'])
#test nuclear distances
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy, nuclear=True)
for unpickle in [False, True] :
if (unpickle) :
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 58.82, eps=0.01)
bad_clashes_list = cs.results
assert ([ c.format_old() for c in bad_clashes_list ] ==
[ ' A 72 ARG HG2 A 72 ARG O :-1.082',
' A 72 ARG CG A 72 ARG O :-0.622',
' A 71 LEU HA A 71 LEU HD12 :-0.535',
' A 72 ARG HB3 A 72 ARG HE :-0.475',
' A 72 ARG HD3 A 72 ARG HH11 :-0.451'])
#test B factor cutoff
cs = clashscore.clashscore(pdb_hierarchy=pdb_hierarchy, b_factor_cutoff=40)
for unpickle in [False, True] :
if (unpickle) :
cs = loads(dumps(cs))
c_score = cs.get_clashscore()
assert approx_equal(c_score, 35.29, eps=0.01)
c_score_b_cutoff = cs.get_clashscore_b_cutoff()
assert approx_equal(c_score_b_cutoff, 39.47, eps=0.01)
bad_clashes_list = cs.results
assert ([ c.format_old() for c in bad_clashes_list ] ==
[' A 72 ARG HG2 A 72 ARG O :-1.038',
' A 72 ARG CG A 72 ARG O :-0.465',
' A 71 LEU HA A 71 LEU HD12 :-0.446'])
def exercise_heavy () :
from mmtbx.regression import make_fake_anomalous_data
from mmtbx.command_line import validate_waters
import mmtbx.ions.utils
from iotbx.file_reader import any_file
file_base = "tst_validate_waters_1"
pdb_file = make_fake_anomalous_data.write_pdb_input_cd_cl(file_base=file_base)
mtz_file = make_fake_anomalous_data.generate_mtz_file(
file_base="tst_validate_waters_1",
d_min=1.5,
anomalous_scatterers=[
group_args(selection="element CD", fp=-0.29, fdp=2.676),
group_args(selection="element CL", fp=0.256, fdp=0.5),
])
pdb_in = any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
hierarchy, n = mmtbx.ions.utils.anonymize_ions(hierarchy, log=null_out())
hierarchy.write_pdb_file("%s_start.pdb" % file_base,
crystal_symmetry=pdb_in.file_object.crystal_symmetry())
args = ["tst_validate_waters_1_start.pdb", "tst_validate_waters_1.mtz",
"skip_twin_detection=True"]
results = validate_waters.run(args=args, out=null_out())
out = StringIO()
results.show(out=out)
s = easy_pickle.dumps(results)
r2 = easy_pickle.loads(s)
out2 = StringIO()
r2.show(out=out2)
assert not show_diff(out.getvalue(), out2.getvalue())
assert (results.n_bad >= 1) and (results.n_heavy == 2)
def exercise () :
for module in ["reduce", "probe", "phenix_regression"] :
if (not libtbx.env.has_module(module)) :
print "%s not available, skipping" % module
return
from mmtbx.command_line import validation_summary
from iotbx import file_reader
import iotbx.pdb.hierarchy
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent",
test=os.path.isfile)
out = StringIO()
summary = validation_summary.run(args=[regression_pdb], out=out)
assert approx_equal(summary.clashscore, 13.597, eps=0.001), "clashscore %s is not 13.597(0.0001)" % summary.clashscore
ss = easy_pickle.dumps(summary)
sss = easy_pickle.loads(ss)
out_1 = StringIO()
out_2 = StringIO()
summary.show(out=out_1)
sss.show(out=out_2)
assert out_1.getvalue() == out_2.getvalue()
pdb_in = file_reader.any_file(regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
new_hierarchy = iotbx.pdb.hierarchy.root()
for i in range(5) :
model = hierarchy.only_model().detached_copy()
model.id = str(i+1)
new_hierarchy.append_model(model)
open("tst_validation_summary.pdb", "w").write(new_hierarchy.as_pdb_string())
out2 = StringIO()
summary = validation_summary.run(args=["tst_validation_summary.pdb"],
out=out2)
assert (type(summary).__name__ == 'ensemble')
print "OK"
def exercise_heavy():
from mmtbx.regression import make_fake_anomalous_data
from mmtbx.command_line import validate_waters
import mmtbx.ions.utils
from iotbx.file_reader import any_file
file_base = "tst_validate_waters_1"
pdb_file = make_fake_anomalous_data.write_pdb_input_cd_cl(
file_base=file_base)
mtz_file = make_fake_anomalous_data.generate_mtz_file(
file_base="tst_validate_waters_1",
d_min=1.5,
anomalous_scatterers=[
group_args(selection="element CD", fp=-0.29, fdp=2.676),
group_args(selection="element CL", fp=0.256, fdp=0.5),
])
pdb_in = any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
hierarchy, n = mmtbx.ions.utils.anonymize_ions(hierarchy, log=null_out())
hierarchy.write_pdb_file(
"%s_start.pdb" % file_base,
crystal_symmetry=pdb_in.file_object.crystal_symmetry())
args = [
"tst_validate_waters_1_start.pdb", "tst_validate_waters_1.mtz",
"skip_twin_detection=True"
]
results = validate_waters.run(args=args, out=null_out())
out = StringIO()
results.show(out=out)
s = easy_pickle.dumps(results)
r2 = easy_pickle.loads(s)
out2 = StringIO()
r2.show(out=out2)
assert not show_diff(out.getvalue(), out2.getvalue())
assert (results.n_bad >= 1) and (results.n_heavy == 2)
def exercise():
for module in ["reduce", "probe", "phenix_regression"]:
if not libtbx.env.has_module(module):
print "%s not available, skipping" % module
return
from mmtbx.command_line import validation_summary
from iotbx import file_reader
import iotbx.pdb.hierarchy
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent", test=os.path.isfile
)
out = StringIO()
summary = validation_summary.run(args=[regression_pdb], out=out)
assert approx_equal(summary.clashscore, 13.597, eps=0.0001)
ss = easy_pickle.dumps(summary)
sss = easy_pickle.loads(ss)
out_1 = StringIO()
out_2 = StringIO()
summary.show(out=out_1)
sss.show(out=out_2)
assert out_1.getvalue() == out_2.getvalue()
pdb_in = file_reader.any_file(regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
new_hierarchy = iotbx.pdb.hierarchy.root()
for i in range(5):
model = hierarchy.only_model().detached_copy()
model.id = str(i + 1)
new_hierarchy.append_model(model)
open("tst_validation_summary.pdb", "w").write(new_hierarchy.as_pdb_string())
out2 = StringIO()
summary = validation_summary.run(args=["tst_validation_summary.pdb"], out=out2)
assert type(summary).__name__ == "ensemble"
print "OK"
def pickle_unpickle(result):
result2 = loads(dumps(result))
out1 = StringIO()
out2 = StringIO()
result.show(out=out1)
result2.show(out=out2)
assert (out1.getvalue() == out2.getvalue())
def pickle_unpickle (result) : result2 = loads(dumps(result)) out1 = StringIO() out2 = StringIO() result.show(out=out1) result2.show(out=out2) assert (out1.getvalue() == out2.getvalue())
def test_pickle_consistency_and_size(result):
all_out = StringIO()
result.show(out=all_out)
result_pkl_str = dumps(result)
pkl_size = len(result_pkl_str)
if (pkl_size >= 100000):
print("Oversized pickle:", pkl_size)
show_pickled_object_sizes(result)
raise OverflowError()
assert (pkl_size < 100000), pkl_size # limit pickle size
result_pkl = loads(result_pkl_str)
all_out_pkl = StringIO()
result_pkl.show(out=all_out_pkl)
assert not show_diff(all_out.getvalue(), all_out_pkl.getvalue())
def test_pickle_consistency_and_size (result) :
all_out = StringIO()
result.show(out=all_out)
result_pkl_str = dumps(result)
pkl_size = len(result_pkl_str)
if (pkl_size >= 100000) :
print "Oversized pickle:", pkl_size
show_pickled_object_sizes(result)
raise OverflowError()
assert (pkl_size < 100000), pkl_size # limit pickle size
result_pkl = loads(result_pkl_str)
all_out_pkl = StringIO()
result_pkl.show(out=all_out_pkl)
assert not show_diff(all_out.getvalue(), all_out_pkl.getvalue())
def exercise(n, use_dumps=False):
from libtbx import easy_pickle
import time
obj = []
for i in range(n):
obj.append([i,i])
for dgz in ["", ".gz"]:
t0 = time.time()
if (use_dumps):
print("dumps/loads")
pickle_string = easy_pickle.dumps(obj=obj)
else:
file_name = "test.dat"+dgz
print(file_name)
easy_pickle.dump(file_name=file_name, obj=obj)
print(" dump: %.2f s" % (time.time()-t0))
del obj
t0 = time.time()
if (use_dumps):
obj = easy_pickle.loads(pickle_string)
else:
obj = easy_pickle.load(file_name=file_name)
print(" load buffered: %.2f s" % (time.time()-t0))
if (use_dumps):
break
else:
del obj
t0 = time.time()
obj = easy_pickle.load(
file_name=file_name, faster_but_using_more_memory=False)
print(" load direct: %.2f s" % (time.time()-t0))
# XXX pickling and unpickling of libtbx.Auto
# couldn't think of a better place to test this...
from libtbx import Auto
a = easy_pickle.dumps(Auto)
b = easy_pickle.loads(a)
assert (b is Auto) and (b == Auto)
def exercise(n, use_dumps=False):
from libtbx import easy_pickle
import time
obj = []
for i in xrange(n):
obj.append([i,i])
for dgz in ["", ".gz"]:
t0 = time.time()
if (use_dumps):
print "dumps/loads"
pickle_string = easy_pickle.dumps(obj=obj)
else:
file_name = "test.dat"+dgz
print file_name
easy_pickle.dump(file_name=file_name, obj=obj)
print " dump: %.2f s" % (time.time()-t0)
del obj
t0 = time.time()
if (use_dumps):
obj = easy_pickle.loads(pickle_string)
else:
obj = easy_pickle.load(file_name=file_name)
print " load buffered: %.2f s" % (time.time()-t0)
if (use_dumps):
break
else:
del obj
t0 = time.time()
obj = easy_pickle.load(
file_name=file_name, faster_but_using_more_memory=False)
print " load direct: %.2f s" % (time.time()-t0)
# XXX pickling and unpickling of libtbx.Auto
# couldn't think of a better place to test this...
from libtbx import Auto
a = easy_pickle.dumps(Auto)
b = easy_pickle.loads(a)
assert (b is Auto) and (b == Auto)
def exercise_rna () :
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb2goz_refmac_tls.ent",
test=op.isfile)
if (regression_pdb is None):
print "Skipping exercise_regression(): input pdb (pdb2goz_refmac_tls.ent) not available"
return
result = molprobity.run(args=[regression_pdb], out=null_out()).validation
assert (result.rna is not None)
out = StringIO()
result.show(out=out)
assert ("2/58 pucker outliers present" in out.getvalue())
result = loads(dumps(result))
out2 = StringIO()
result.show(out=out2)
assert (out2.getvalue() == out.getvalue())
def exercise_rna():
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb2goz_refmac_tls.ent",
test=op.isfile)
if (regression_pdb is None):
print "Skipping exercise_regression(): input pdb (pdb2goz_refmac_tls.ent) not available"
return
result = molprobity.run(args=[regression_pdb], out=null_out()).validation
assert (result.rna is not None)
out = StringIO()
result.show(out=out)
assert ("2/58 pucker outliers present" in out.getvalue())
result = loads(dumps(result))
out2 = StringIO()
result.show(out=out2)
assert (out2.getvalue() == out.getvalue())
def exercise_cbetadev():
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent", test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_cbetadev(): input pdb (pdb1jxt.ent) not available"
return
from mmtbx.validation import cbetadev
from iotbx import file_reader
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
validation = cbetadev.cbetadev(pdb_hierarchy=hierarchy, outliers_only=True)
assert approx_equal(validation.get_weighted_outlier_percent(),
4.40420846587)
for unpickle in [False, True]:
if unpickle:
validation = loads(dumps(validation))
assert (validation.n_outliers == len(validation.results) == 6)
assert ([cb.id_str() for cb in validation.results] == [
' A 7 AILE', ' A 8 BVAL', ' A 8 CVAL', ' A 30 BTHR',
' A 39 BTHR', ' A 43 BASP'
])
assert approx_equal([cb.deviation for cb in validation.results], [
0.25977096732623106, 0.2577218834868609, 0.6405578498280606,
0.81238828498566, 0.9239566035292618, 0.5001892640352836
])
out = StringIO()
validation.show_old_output(out=out, verbose=True)
assert not show_diff(
out.getvalue(), """\
pdb:alt:res:chainID:resnum:dev:dihedralNABB:Occ:ALT:
pdb :A:ile: A: 7 : 0.260: -46.47: 0.45:A:
pdb :B:val: A: 8 : 0.258: 80.92: 0.30:B:
pdb :C:val: A: 8 : 0.641: -53.98: 0.20:C:
pdb :B:thr: A: 30 : 0.812: -76.98: 0.30:B:
pdb :B:thr: A: 39 : 0.924: 56.41: 0.30:B:
pdb :B:asp: A: 43 : 0.500: 7.56: 0.25:B:
SUMMARY: 6 C-beta deviations >= 0.25 Angstrom (Goal: 0)
""")
# Now with all residues
validation = cbetadev.cbetadev(pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True]:
if unpickle:
validation = loads(dumps(validation))
for outlier in validation.results:
assert (len(outlier.xyz) == 3)
assert (validation.n_outliers == 6)
assert (len(validation.results) == 51)
out = StringIO()
validation.show_old_output(out=out, verbose=True)
assert not show_diff(
out.getvalue(), """\
pdb:alt:res:chainID:resnum:dev:dihedralNABB:Occ:ALT:
pdb : :thr: A: 1 : 0.102: 11.27: 1.00: :
pdb :A:thr: A: 2 : 0.022: -49.31: 0.67:A:
pdb : :cys: A: 3 : 0.038: 103.68: 1.00: :
pdb : :cys: A: 4 : 0.047:-120.73: 1.00: :
pdb : :pro: A: 5 : 0.069:-121.41: 1.00: :
pdb : :ser: A: 6 : 0.052: 112.87: 1.00: :
pdb :A:ile: A: 7 : 0.260: -46.47: 0.45:A:
pdb :B:ile: A: 7 : 0.153: 122.97: 0.55:B:
pdb :A:val: A: 8 : 0.184:-155.36: 0.50:A:
pdb :B:val: A: 8 : 0.258: 80.92: 0.30:B:
pdb :C:val: A: 8 : 0.641: -53.98: 0.20:C:
pdb : :ala: A: 9 : 0.061: -82.84: 1.00: :
pdb :A:arg: A: 10 : 0.023: 172.25: 1.00:A:
pdb : :ser: A: 11 : 0.028:-129.11: 1.00: :
pdb :A:asn: A: 12 : 0.021: -80.80: 0.50:A:
pdb :B:asn: A: 12 : 0.199: 50.01: 0.50:B:
pdb :A:phe: A: 13 : 0.067: -37.32: 0.65:A:
pdb :B:phe: A: 13 : 0.138: 19.24: 0.35:B:
pdb : :asn: A: 14 : 0.065: -96.35: 1.00: :
pdb : :val: A: 15 : 0.138: -96.63: 1.00: :
pdb : :cys: A: 16 : 0.102: -28.64: 1.00: :
pdb : :arg: A: 17 : 0.053:-106.79: 1.00: :
pdb : :leu: A: 18 : 0.053:-141.51: 1.00: :
pdb : :pro: A: 19 : 0.065:-146.95: 1.00: :
pdb : :thr: A: 21 : 0.086: 53.80: 1.00: :
pdb :A:pro: A: 22 : 0.092: -83.39: 0.55:A:
pdb :A:glu: A: 23 : 0.014:-179.53: 0.50:A:
pdb :B:glu: A: 23 : 0.050:-179.78: 0.50:B:
pdb : :ala: A: 24 : 0.056: -88.96: 1.00: :
pdb : :leu: A: 25 : 0.084:-106.42: 1.00: :
pdb : :cys: A: 26 : 0.074: -94.70: 1.00: :
pdb : :ala: A: 27 : 0.056: -62.15: 1.00: :
pdb : :thr: A: 28 : 0.056:-114.82: 1.00: :
pdb :A:tyr: A: 29 : 0.068: 0.22: 0.65:A:
pdb :A:thr: A: 30 : 0.180: 103.27: 0.70:A:
pdb :B:thr: A: 30 : 0.812: -76.98: 0.30:B:
pdb : :cys: A: 32 : 0.029: -84.07: 1.00: :
pdb : :ile: A: 33 : 0.048:-119.17: 1.00: :
pdb : :ile: A: 34 : 0.045: 99.02: 1.00: :
pdb : :ile: A: 35 : 0.052:-128.24: 1.00: :
pdb : :pro: A: 36 : 0.084:-142.29: 1.00: :
pdb : :ala: A: 38 : 0.039: 50.01: 1.00: :
pdb :A:thr: A: 39 : 0.093: -96.63: 0.70:A:
pdb :B:thr: A: 39 : 0.924: 56.41: 0.30:B:
pdb : :cys: A: 40 : 0.013:-144.11: 1.00: :
pdb : :pro: A: 41 : 0.039: -97.09: 1.00: :
pdb :A:asp: A: 43 : 0.130:-146.91: 0.75:A:
pdb :B:asp: A: 43 : 0.500: 7.56: 0.25:B:
pdb : :tyr: A: 44 : 0.085:-143.63: 1.00: :
pdb : :ala: A: 45 : 0.055: 33.32: 1.00: :
pdb : :asn: A: 46 : 0.066: -50.46: 1.00: :
SUMMARY: 6 C-beta deviations >= 0.25 Angstrom (Goal: 0)
""")
# Auxilary function: extract_atoms_from_residue_group
from mmtbx.validation.cbetadev import extract_atoms_from_residue_group
from iotbx import pdb
pdb_1 = pdb.input(source_info=None,
lines="""\
ATOM 1185 N ASER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1186 N BSER A 146 24.758 37.100 16.337 0.50 16.79 N
ATOM 1187 CA ASER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1188 CA BSER A 146 24.237 37.427 17.662 0.50 16.87 C
ATOM 1189 C ASER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1190 C BSER A 146 22.792 36.945 17.783 0.50 15.94 C
ATOM 1191 O ASER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1192 O BSER A 146 22.091 36.741 16.779 0.50 15.17 O
ATOM 1193 CB ASER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1194 CB BSER A 146 24.321 38.940 17.904 0.50 17.48 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """
).construct_hierarchy()
pdb_2 = pdb.input(source_info=None,
lines="""\
ATOM 1185 N SER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1187 CA SER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1189 C SER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1191 O SER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1193 CB ASER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1194 CB BSER A 146 24.321 38.940 17.904 0.50 17.48 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """
).construct_hierarchy()
pdb_3 = pdb.input(source_info=None,
lines="""\
ATOM 1185 N SER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1187 CA SER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1189 C SER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1191 O SER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1193 CB SER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """
).construct_hierarchy()
rg1 = pdb_1.only_model().only_chain().only_residue_group()
rg2 = pdb_2.only_model().only_chain().only_residue_group()
rg3 = pdb_3.only_model().only_chain().only_residue_group()
all_relevant_atoms_1 = extract_atoms_from_residue_group(rg1)
all_relevant_atoms_2 = extract_atoms_from_residue_group(rg2)
all_relevant_atoms_3 = extract_atoms_from_residue_group(rg3)
keys_1 = [sorted([k for k in a.keys()]) for a in all_relevant_atoms_1]
keys_2 = [sorted([k for k in a.keys()]) for a in all_relevant_atoms_2]
keys_3 = [sorted([k for k in a.keys()]) for a in all_relevant_atoms_3]
assert keys_1 == [[' C ', ' CA ', ' CB ', ' N '],
[' C ', ' CA ', ' CB ', ' N ']]
assert keys_2 == [[' C ', ' CA ', ' CB ', ' N '],
[' C ', ' CA ', ' CB ', ' N ']]
assert keys_3 == [[' C ', ' CA ', ' CB ', ' N ']]
print "OK"
def exercise_ramalyze():
from mmtbx.rotamer.rotamer_eval import find_rotarama_data_dir
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/jcm.pdb", test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_ramalyze(): input pdb (jcm.pdb) not available"
return
if (find_rotarama_data_dir(optional=True) is None):
print "Skipping exercise_ramalyze(): rotarama_data directory not available"
return
from iotbx import file_reader
# Exercise 1
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
hierarchy.atoms().reset_i_seq()
r = ramalyze.ramalyze(pdb_hierarchy=hierarchy, outliers_only=True)
out = StringIO()
r.show_old_output(out=out)
output = out.getvalue()
assert output.count("OUTLIER") == 100
assert output.count("Favored") == 0
assert output.count("Allowed") == 0
assert output.count("General") == 64
assert output.count("Glycine") == 6
assert output.count("Trans-proline") == 1
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 4
assert output.count("Isoleucine or valine") == 25
assert (len(r.outlier_selection()) == 494)
outlier_ids = set([])
atoms = hierarchy.atoms()
for i_seq in r.outlier_selection():
atom = atoms[i_seq]
atom_group = atoms[i_seq].parent()
outlier_ids.add(atom_group.id_str())
outliers1 = sorted([o.atom_group_id_str() for o in r.results])
outliers2 = sorted(list(outlier_ids))
assert (outliers1 == outliers2)
r = ramalyze.ramalyze(pdb_hierarchy=hierarchy, outliers_only=False)
for unpickle in [False, True]:
if unpickle:
r = loads(dumps(r))
for outlier in r.results:
assert (len(outlier.xyz) == 3)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("OUTLIER") == 100
assert output.count("Favored") == 463
assert output.count("Allowed") == 162
assert output.count("General") == 514
assert output.count("Glycine") == 39
assert output.count("Trans-proline") == 23
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 21
assert output.count("Isoleucine or valine") == 128
numtotal = r.get_phi_psi_residues_count()
assert r.get_outliers_count_and_fraction() == (100, 100. / numtotal)
assert r.get_allowed_count_and_fraction() == (162, 162. / numtotal)
assert r.get_favored_count_and_fraction() == (463, 463. / numtotal)
assert r.get_general_count_and_fraction() == (514, 514. / numtotal)
assert r.get_gly_count_and_fraction() == (39, 39. / numtotal)
assert r.get_trans_pro_count_and_fraction() == (23, 23. / numtotal)
assert r.get_cis_pro_count_and_fraction() == (0, 0. / numtotal)
assert r.get_prepro_count_and_fraction() == (21, 21. / numtotal)
assert r.get_ileval_count_and_fraction() == (128, 128. / numtotal)
#assert numtotal == 75+154+494 #reasons for this math unclear
assert numtotal == 725
output_lines = output.splitlines()
assert len(output_lines) == 725
selected_lines = []
for x in [
0, 1, 168, 169, 715, 716, 717, 718, 719, 720, 721, 722, 723,
724
]:
selected_lines.append(output_lines[x])
assert not show_diff(
"\n".join(selected_lines), """\
A 15 SER:35.07:-83.26:131.88:Favored:General
A 16 SER:0.74:-111.53:71.36:Allowed:General
A 191 ASP:2.66:-42.39:121.87:Favored:Pre-proline
A 192 PRO:0.31:-39.12:-31.84:Allowed:Trans-proline
B 368 LYS:56.44:-62.97:-53.28:Favored:General
B 369 GLU:8.89:-44.36:-45.50:Favored:General
B 370 LYS:40.00:-50.00:-39.06:Favored:General
B 371 VAL:68.24:-60.38:-51.85:Favored:Isoleucine or valine
B 372 LEU:0.02:-61.13:-170.23:OUTLIER:General
B 373 ARG:0.02:60.09:-80.26:OUTLIER:General
B 374 ALA:0.13:-37.21:-36.12:Allowed:General
B 375 LEU:11.84:-89.81:-41.45:Favored:General
B 376 ASN:84.33:-58.30:-41.39:Favored:General
B 377 GLU:30.88:-56.79:-21.74:Favored:General""")
assert (len(r.outlier_selection()) == 494)
# Exercise 2
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent", test=os.path.isfile)
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
hierarchy.atoms().reset_i_seq()
r = ramalyze.ramalyze(pdb_hierarchy=hierarchy, outliers_only=True)
out = StringIO()
r.show_old_output(out=out)
output = out.getvalue()
assert output.count("Favored") == 0
assert output.count("Allowed") == 0
assert output.count("OUTLIER") == 0
r = ramalyze.ramalyze(pdb_hierarchy=hierarchy, outliers_only=False)
for unpickle in [False, True]:
if unpickle:
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("Favored") == 50
assert output.count("Allowed") == 1
assert output.count("OUTLIER") == 0
assert output.count("General") == 29
assert output.count("Glycine") == 4
assert output.count("Trans-proline") == 5
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 5
assert output.count("Isoleucine or valine") == 8
numtotal = r.get_phi_psi_residues_count()
assert r.get_outliers_count_and_fraction() == (0, 0. / numtotal)
assert r.get_allowed_count_and_fraction() == (1, 1. / numtotal)
assert r.get_favored_count_and_fraction() == (43, 43. / numtotal)
#print r.get_general_count_and_fraction()
assert r.get_general_count_and_fraction() == (25, 25. / numtotal)
assert r.get_gly_count_and_fraction() == (4, 4. / numtotal)
assert r.get_trans_pro_count_and_fraction() == (5, 5. / numtotal)
assert r.get_cis_pro_count_and_fraction() == (0, 0. / numtotal)
assert r.get_prepro_count_and_fraction() == (5, 5. / numtotal)
assert r.get_ileval_count_and_fraction() == (5, 5. / numtotal)
output_lines = output.splitlines()
assert len(output_lines) == 51
selected_lines = []
for x in [0, 1, 5, 6, 7, 8, 9, 47, 48, 49, 50]:
selected_lines.append(output_lines[x])
assert not show_diff(
"\n".join(selected_lines), """\
A 2 ATHR:33.85:-106.92:144.23:Favored:General
A 3 ACYS:47.07:-132.54:137.26:Favored:General
A 7 AILE:98.76:-61.91:-44.35:Favored:Isoleucine or valine
A 7 BILE:61.50:-56.21:-51.56:Favored:Isoleucine or valine
A 8 AVAL:23.11:-50.35:-49.64:Favored:Isoleucine or valine
A 8 BVAL:12.01:-83.20:-12.14:Favored:Isoleucine or valine
A 8 CVAL:73.11:-61.22:-36.49:Favored:Isoleucine or valine
A 43 AASP:51.81:-94.64:5.45:Favored:General
A 43 BASP:56.98:-88.69:-0.12:Favored:General
A 44 TYR:1.76:-133.10:58.75:Allowed:General
A 45 ALA:57.37:-86.61:-8.57:Favored:General""")
# Exercise 3: 2plx excerpt (unusual icode usage)
import iotbx.pdb.hierarchy
pdb_io = iotbx.pdb.hierarchy.input(pdb_string="""\
ATOM 1468 N GLY A 219 3.721 21.322 10.752 1.00 14.12 N
ATOM 1469 CA GLY A 219 3.586 21.486 12.188 1.00 14.85 C
ATOM 1470 C GLY A 219 4.462 20.538 12.995 1.00 15.63 C
ATOM 1471 O GLY A 219 5.513 20.090 12.512 1.00 14.55 O
ATOM 1472 N CYS A 220 4.036 20.213 14.235 1.00 15.02 N
ATOM 1473 CA CYS A 220 4.776 19.228 15.068 1.00 15.56 C
ATOM 1474 C CYS A 220 3.773 18.322 15.741 1.00 14.69 C
ATOM 1475 O CYS A 220 2.799 18.828 16.338 1.00 15.54 O
ATOM 1476 CB CYS A 220 5.620 19.906 16.174 1.00 15.72 C
ATOM 1477 SG CYS A 220 6.762 21.133 15.448 1.00 15.45 S
ATOM 1478 N ALA A 221A 4.054 17.017 15.707 1.00 14.77 N
ATOM 1479 CA ALA A 221A 3.274 16.015 16.507 1.00 14.01 C
ATOM 1480 C ALA A 221A 1.774 15.992 16.099 1.00 14.50 C
ATOM 1481 O ALA A 221A 0.875 15.575 16.881 1.00 14.46 O
ATOM 1482 CB ALA A 221A 3.440 16.318 17.935 1.00 12.28 C
ATOM 1483 N GLN A 221 1.523 16.390 14.848 1.00 14.52 N
ATOM 1484 CA GLN A 221 0.159 16.391 14.325 1.00 15.19 C
ATOM 1485 C GLN A 221 -0.229 15.044 13.717 1.00 14.43 C
ATOM 1486 O GLN A 221 0.641 14.280 13.307 1.00 16.88 O
ATOM 1487 CB GLN A 221 0.002 17.491 13.272 1.00 16.41 C
ATOM 1488 CG GLN A 221 0.253 18.906 13.805 1.00 16.52 C
ATOM 1489 CD GLN A 221 -0.640 19.181 14.995 1.00 17.87 C
ATOM 1490 OE1 GLN A 221 -1.857 19.399 14.826 1.00 13.54 O
ATOM 1491 NE2 GLN A 221 -0.050 19.149 16.228 1.00 16.18 N
ATOM 1492 N LYS A 222 -1.537 14.773 13.694 1.00 14.34 N
ATOM 1493 CA LYS A 222 -2.053 13.536 13.125 1.00 15.07 C
ATOM 1494 C LYS A 222 -1.679 13.455 11.655 1.00 14.88 C
ATOM 1495 O LYS A 222 -1.856 14.424 10.883 1.00 14.32 O
""")
r = ramalyze.ramalyze(pdb_hierarchy=pdb_io.hierarchy, outliers_only=False)
assert (len(r.results) == 3)
def test_multi_axis_goniometer():
from libtbx.test_utils import approx_equal
from scitbx.array_family import flex
alpha = 50
omega = -10
kappa = 30
phi = 20
direction = "-y"
from dxtbx.model.goniometer import KappaGoniometer
kappa_omega_scan = KappaGoniometer(alpha, omega, kappa, phi, direction,
"omega")
axes = (
kappa_omega_scan.get_phi_axis(),
kappa_omega_scan.get_kappa_axis(),
kappa_omega_scan.get_omega_axis(),
)
angles = (
kappa_omega_scan.get_phi_angle(),
kappa_omega_scan.get_kappa_angle(),
kappa_omega_scan.get_omega_angle(),
)
# First test a kappa goniometer with omega as the scan axis
axes = flex.vec3_double(axes)
angles = flex.double(angles)
names = flex.std_string(("phi", "kappa", "omega"))
scan_axis = 2
multi_axis_omega_scan = GoniometerFactory.multi_axis(
axes, angles, names, scan_axis)
assert approx_equal(
multi_axis_omega_scan.get_fixed_rotation(),
kappa_omega_scan.get_fixed_rotation(),
)
assert approx_equal(multi_axis_omega_scan.get_rotation_axis(),
kappa_omega_scan.get_rotation_axis())
recycle_omega = MultiAxisGoniometer.from_dict(
multi_axis_omega_scan.to_dict())
assert approx_equal(recycle_omega.get_axes(),
multi_axis_omega_scan.get_axes())
assert approx_equal(recycle_omega.get_angles(),
multi_axis_omega_scan.get_angles())
assert recycle_omega.get_scan_axis(
) == multi_axis_omega_scan.get_scan_axis()
# Now test a kappa goniometer with phi as the scan axis
kappa_phi_scan = KappaGoniometer(alpha, omega, kappa, phi, direction,
"phi")
scan_axis = 0
multi_axis_phi_scan = GoniometerFactory.multi_axis(axes, angles, names,
scan_axis)
assert approx_equal(multi_axis_phi_scan.get_fixed_rotation(),
kappa_phi_scan.get_fixed_rotation())
assert approx_equal(
matrix.sqr(multi_axis_phi_scan.get_setting_rotation()) *
multi_axis_phi_scan.get_rotation_axis_datum(),
kappa_phi_scan.get_rotation_axis(),
)
assert approx_equal(multi_axis_phi_scan.get_rotation_axis(),
kappa_phi_scan.get_rotation_axis())
recycle_phi = MultiAxisGoniometer.from_dict(multi_axis_phi_scan.to_dict())
assert approx_equal(recycle_phi.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle_phi.get_angles(),
multi_axis_phi_scan.get_angles())
assert recycle_phi.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
s = easy_pickle.dumps(multi_axis_phi_scan)
recycle = easy_pickle.loads(s)
assert recycle == multi_axis_phi_scan
assert approx_equal(recycle.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
recycle.set_angles((0, 90, 180))
assert approx_equal(recycle.get_angles(), (0, 90, 180))
new_axes = flex.vec3_double((
(0.99996, -0.00647, -0.00659),
(0.91314, 0.27949, -0.29674),
(1.00000, -0.00013, -0.00064),
))
recycle.set_axes(new_axes)
assert approx_equal(recycle.get_axes(), new_axes)
# Check exception is raised if scan axis is out range
try:
GoniometerFactory.multi_axis(axes, angles, names, 3)
except RuntimeError:
pass
else:
raise Exception_expected
# Single axis is just a special case of a multi axis goniometer
single_axis = GoniometerFactory.multi_axis(flex.vec3_double(((1, 0, 0), )),
flex.double((0, )),
flex.std_string(("PHI", )), 0)
assert single_axis.get_fixed_rotation() == (1, 0, 0, 0, 1, 0, 0, 0, 1)
assert single_axis.get_setting_rotation() == (1, 0, 0, 0, 1, 0, 0, 0, 1)
assert single_axis.get_rotation_axis() == (1, 0, 0)
def exercise_ramalyze():
from mmtbx.rotamer.rotamer_eval import find_rotarama_data_dir
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/jcm.pdb",
test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_ramalyze(): input pdb (jcm.pdb) not available"
return
if (find_rotarama_data_dir(optional=True) is None):
print "Skipping exercise_ramalyze(): rotarama_data directory not available"
return
from iotbx import file_reader
# Exercise 1
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
hierarchy.atoms().reset_i_seq()
r = ramalyze.ramalyze(
pdb_hierarchy=hierarchy,
outliers_only=True)
out = StringIO()
r.show_old_output(out=out)
output = out.getvalue()
assert output.count("OUTLIER") == 100
assert output.count("Favored") == 0
assert output.count("Allowed") == 0
assert output.count("General") == 64
assert output.count("Glycine") == 6
assert output.count("Trans-proline") == 1
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 4
assert output.count("Isoleucine or valine") == 25
assert (len(r.outlier_selection()) == 788)
outlier_ids = set([])
atoms = hierarchy.atoms()
for i_seq in r.outlier_selection() :
atom = atoms[i_seq]
atom_group = atoms[i_seq].parent()
outlier_ids.add(atom_group.id_str())
outliers1 = sorted([ o.atom_group_id_str() for o in r.results ])
outliers2 = sorted(list(outlier_ids))
assert (outliers1 == outliers2)
r = ramalyze.ramalyze(
pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True] :
if unpickle :
r = loads(dumps(r))
for outlier in r.results :
assert (len(outlier.xyz) == 3)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("OUTLIER") == 100
assert output.count("Favored") == 461
assert output.count("Allowed") == 162
assert output.count("General") == 513
assert output.count("Glycine") == 39
assert output.count("Trans-proline") == 23
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 21
assert output.count("Isoleucine or valine") == 127
numtotal = r.get_phi_psi_residues_count()
assert r.get_outliers_count_and_fraction() == (100, 100./numtotal)
assert r.get_allowed_count_and_fraction() == (162, 162./numtotal)
assert r.get_favored_count_and_fraction() == (461, 461./numtotal)
assert r.get_general_count_and_fraction() == (513, 513./numtotal)
assert r.get_gly_count_and_fraction() == (39, 39./numtotal)
assert r.get_trans_pro_count_and_fraction() == (23, 23./numtotal)
assert r.get_cis_pro_count_and_fraction() == (0, 0./numtotal)
assert r.get_prepro_count_and_fraction() == (21, 21./numtotal)
assert r.get_ileval_count_and_fraction() == (127, 127./numtotal)
assert numtotal == 75+154+494
output_lines = output.splitlines()
assert len(output_lines) == 723
selected_lines = []
for x in [0, 1, 168, 169, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722]:
selected_lines.append(output_lines[x])
assert not show_diff("\n".join(selected_lines), """\
A 15 SER:35.07:-83.26:131.88:Favored:General
A 16 SER:0.74:-111.53:71.36:Allowed:General
A 191 ASP:2.66:-42.39:121.87:Favored:Pre-proline
A 192 PRO:0.31:-39.12:-31.84:Allowed:Trans-proline
B 368 LYS:56.44:-62.97:-53.28:Favored:General
B 369 GLU:8.89:-44.36:-45.50:Favored:General
B 370 LYS:40.00:-50.00:-39.06:Favored:General
B 371 VAL:68.24:-60.38:-51.85:Favored:Isoleucine or valine
B 372 LEU:0.02:-61.13:-170.23:OUTLIER:General
B 373 ARG:0.02:60.09:-80.26:OUTLIER:General
B 374 ALA:0.13:-37.21:-36.12:Allowed:General
B 375 LEU:11.84:-89.81:-41.45:Favored:General
B 376 ASN:84.33:-58.30:-41.39:Favored:General
B 377 GLU:30.88:-56.79:-21.74:Favored:General""")
assert (len(r.outlier_selection()) == 788)
# Exercise 2
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent",
test=os.path.isfile)
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
hierarchy.atoms().reset_i_seq()
r = ramalyze.ramalyze(
pdb_hierarchy=hierarchy,
outliers_only=True)
out = StringIO()
r.show_old_output(out=out)
output = out.getvalue()
assert output.count("Favored") == 0
assert output.count("Allowed") == 0
assert output.count("OUTLIER") == 0
r = ramalyze.ramalyze(
pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True] :
if unpickle :
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("Favored") == 47
assert output.count("Allowed") == 1
assert output.count("OUTLIER") == 0
assert output.count("General") == 27
assert output.count("Glycine") == 4
assert output.count("Trans-proline") == 4
assert output.count("Cis-proline") == 0
assert output.count("Pre-proline") == 5
assert output.count("Isoleucine or valine") == 8
numtotal = r.get_phi_psi_residues_count()
assert r.get_outliers_count_and_fraction() == (0, 0./numtotal)
assert r.get_allowed_count_and_fraction() == (1, 1./numtotal)
assert r.get_favored_count_and_fraction() == (47, 47./numtotal)
assert r.get_general_count_and_fraction() == (27, 27./numtotal)
assert r.get_gly_count_and_fraction() == (4, 4./numtotal)
assert r.get_trans_pro_count_and_fraction() == (4, 4./numtotal)
assert r.get_cis_pro_count_and_fraction() == (0, 0./numtotal)
assert r.get_prepro_count_and_fraction() == (5, 5./numtotal)
assert r.get_ileval_count_and_fraction() == (8, 8./numtotal)
output_lines = output.splitlines()
assert len(output_lines) == 48
selected_lines = []
for x in [0, 1, 6, 7, 8, 9, 10, 44, 45, 46, 47]:
selected_lines.append(output_lines[x])
assert not show_diff("\n".join(selected_lines), """\
A 2 ATHR:33.85:-106.92:144.23:Favored:General
A 2 BTHR:37.07:-97.44:137.00:Favored:General
A 7 AILE:98.76:-61.91:-44.35:Favored:Isoleucine or valine
A 7 BILE:61.50:-56.21:-51.56:Favored:Isoleucine or valine
A 8 AVAL:23.11:-50.35:-49.64:Favored:Isoleucine or valine
A 8 BVAL:12.01:-83.20:-12.14:Favored:Isoleucine or valine
A 8 CVAL:73.11:-61.22:-36.49:Favored:Isoleucine or valine
A 43 AASP:51.81:-94.64:5.45:Favored:General
A 43 BASP:56.98:-88.69:-0.12:Favored:General
A 44 TYR:1.76:-133.10:58.75:Allowed:General
A 45 ALA:57.37:-86.61:-8.57:Favored:General""")
# Exercise 3: 2plx excerpt (unusual icode usage)
import iotbx.pdb.hierarchy
pdb_io = iotbx.pdb.hierarchy.input(pdb_string="""\
ATOM 1468 N GLY A 219 3.721 21.322 10.752 1.00 14.12 N
ATOM 1469 CA GLY A 219 3.586 21.486 12.188 1.00 14.85 C
ATOM 1470 C GLY A 219 4.462 20.538 12.995 1.00 15.63 C
ATOM 1471 O GLY A 219 5.513 20.090 12.512 1.00 14.55 O
ATOM 1472 N CYS A 220 4.036 20.213 14.235 1.00 15.02 N
ATOM 1473 CA CYS A 220 4.776 19.228 15.068 1.00 15.56 C
ATOM 1474 C CYS A 220 3.773 18.322 15.741 1.00 14.69 C
ATOM 1475 O CYS A 220 2.799 18.828 16.338 1.00 15.54 O
ATOM 1476 CB CYS A 220 5.620 19.906 16.174 1.00 15.72 C
ATOM 1477 SG CYS A 220 6.762 21.133 15.448 1.00 15.45 S
ATOM 1478 N ALA A 221A 4.054 17.017 15.707 1.00 14.77 N
ATOM 1479 CA ALA A 221A 3.274 16.015 16.507 1.00 14.01 C
ATOM 1480 C ALA A 221A 1.774 15.992 16.099 1.00 14.50 C
ATOM 1481 O ALA A 221A 0.875 15.575 16.881 1.00 14.46 O
ATOM 1482 CB ALA A 221A 3.440 16.318 17.935 1.00 12.28 C
ATOM 1483 N GLN A 221 1.523 16.390 14.848 1.00 14.52 N
ATOM 1484 CA GLN A 221 0.159 16.391 14.325 1.00 15.19 C
ATOM 1485 C GLN A 221 -0.229 15.044 13.717 1.00 14.43 C
ATOM 1486 O GLN A 221 0.641 14.280 13.307 1.00 16.88 O
ATOM 1487 CB GLN A 221 0.002 17.491 13.272 1.00 16.41 C
ATOM 1488 CG GLN A 221 0.253 18.906 13.805 1.00 16.52 C
ATOM 1489 CD GLN A 221 -0.640 19.181 14.995 1.00 17.87 C
ATOM 1490 OE1 GLN A 221 -1.857 19.399 14.826 1.00 13.54 O
ATOM 1491 NE2 GLN A 221 -0.050 19.149 16.228 1.00 16.18 N
ATOM 1492 N LYS A 222 -1.537 14.773 13.694 1.00 14.34 N
ATOM 1493 CA LYS A 222 -2.053 13.536 13.125 1.00 15.07 C
ATOM 1494 C LYS A 222 -1.679 13.455 11.655 1.00 14.88 C
ATOM 1495 O LYS A 222 -1.856 14.424 10.883 1.00 14.32 O
""")
r = ramalyze.ramalyze(
pdb_hierarchy=pdb_io.hierarchy,
outliers_only=False)
assert (len(r.results) == 3)
def test_goniometer():
'''A test class for the goniometer class.'''
axis = (1, 0, 0)
fixed = (1, 0, 0, 0, 1, 0, 0, 0, 1)
xg = Goniometer(axis, fixed)
assert (len(xg.get_rotation_axis()) == 3)
assert (len(xg.get_fixed_rotation()) == 9)
assert (compare_tuples(xg.get_rotation_axis(), axis))
assert (compare_tuples(xg.get_fixed_rotation(), fixed))
single = goniometer_factory.single_axis()
assert (len(single.get_rotation_axis()) == 3)
assert (len(single.get_fixed_rotation()) == 9)
assert (compare_tuples(single.get_rotation_axis(), axis))
assert (compare_tuples(single.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'omega')
assert (len(kappa.get_rotation_axis()) == 3)
assert (len(kappa.get_fixed_rotation()) == 9)
assert (compare_tuples(kappa.get_rotation_axis(), axis))
assert (compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'omega')
assert (len(kappa.get_rotation_axis()) == 3)
assert (len(kappa.get_fixed_rotation()) == 9)
assert (compare_tuples(kappa.get_rotation_axis(), axis))
assert (compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'phi')
assert (len(kappa.get_rotation_axis()) == 3)
assert (len(kappa.get_fixed_rotation()) == 9)
assert (compare_tuples(kappa.get_rotation_axis(), axis))
assert (compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 30.0, 0.0, '-y', 'omega')
assert (len(kappa.get_rotation_axis()) == 3)
assert (len(kappa.get_fixed_rotation()) == 9)
assert (compare_tuples(kappa.get_rotation_axis(), axis))
assert (not compare_tuples(kappa.get_fixed_rotation(), fixed))
import libtbx.load_env
import os
dxtbx_dir = libtbx.env.dist_path('dxtbx')
image = os.path.join(dxtbx_dir, 'tests', 'phi_scan_001.cbf')
cbf = goniometer_factory.imgCIF(image)
kappa = goniometer_factory.kappa(50.0, -10.0, 30.0, 0.0, '-y', 'phi')
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
image = os.path.join(dxtbx_dir, 'tests', 'omega_scan.cbf')
cbf = goniometer_factory.imgCIF(image)
kappa = goniometer_factory.kappa(50.0, -10.0, 30.0, 20.0, '-y', 'omega')
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
print 'OK'
def show_pickled_object_sizes(result):
result_pkl = dumps(result)
print("result", len(result_pkl))
show_pickle_sizes(result, " ")
def exercise_cbetadev():
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent",
test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_cbetadev(): input pdb (pdb1jxt.ent) not available"
return
from mmtbx.validation import cbetadev
from iotbx import file_reader
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
validation = cbetadev.cbetadev(
pdb_hierarchy=hierarchy,
outliers_only=True)
for unpickle in [False, True] :
if unpickle :
validation = loads(dumps(validation))
assert (validation.n_outliers == len(validation.results) == 6)
assert ([ cb.id_str() for cb in validation.results ] ==
[' A 7 AILE', ' A 8 BVAL', ' A 8 CVAL', ' A 30 BTHR',
' A 39 BTHR', ' A 43 BASP'])
assert approx_equal([ cb.deviation for cb in validation.results ],
[0.25977096732623106, 0.2577218834868609, 0.6405578498280606,
0.81238828498566, 0.9239566035292618, 0.5001892640352836])
out = StringIO()
validation.show_old_output(out=out, verbose=True)
assert not show_diff(out.getvalue(),
"""\
pdb:alt:res:chainID:resnum:dev:dihedralNABB:Occ:ALT:
pdb :A:ile: A: 7 : 0.260: -46.47: 0.45:A:
pdb :B:val: A: 8 : 0.258: 80.92: 0.30:B:
pdb :C:val: A: 8 : 0.641: -53.98: 0.20:C:
pdb :B:thr: A: 30 : 0.812: -76.98: 0.30:B:
pdb :B:thr: A: 39 : 0.924: 56.41: 0.30:B:
pdb :B:asp: A: 43 : 0.500: 7.56: 0.25:B:
SUMMARY: 6 C-beta deviations >= 0.25 Angstrom (Goal: 0)
""")
# Now with all residues
validation = cbetadev.cbetadev(
pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True] :
if unpickle :
validation = loads(dumps(validation))
for outlier in validation.results :
assert (len(outlier.xyz) == 3)
assert (validation.n_outliers == 6)
assert (len(validation.results) == 51)
out = StringIO()
validation.show_old_output(out=out, verbose=True)
assert not show_diff(out.getvalue(), """\
pdb:alt:res:chainID:resnum:dev:dihedralNABB:Occ:ALT:
pdb : :thr: A: 1 : 0.102: 11.27: 1.00: :
pdb :A:thr: A: 2 : 0.022: -49.31: 0.67:A:
pdb : :cys: A: 3 : 0.038: 103.68: 1.00: :
pdb : :cys: A: 4 : 0.047:-120.73: 1.00: :
pdb : :pro: A: 5 : 0.069:-121.41: 1.00: :
pdb : :ser: A: 6 : 0.052: 112.87: 1.00: :
pdb :A:ile: A: 7 : 0.260: -46.47: 0.45:A:
pdb :B:ile: A: 7 : 0.153: 122.97: 0.55:B:
pdb :A:val: A: 8 : 0.184:-155.36: 0.50:A:
pdb :B:val: A: 8 : 0.258: 80.92: 0.30:B:
pdb :C:val: A: 8 : 0.641: -53.98: 0.20:C:
pdb : :ala: A: 9 : 0.061: -82.84: 1.00: :
pdb :A:arg: A: 10 : 0.023: 172.25: 1.00:A:
pdb : :ser: A: 11 : 0.028:-129.11: 1.00: :
pdb :A:asn: A: 12 : 0.021: -80.80: 0.50:A:
pdb :B:asn: A: 12 : 0.199: 50.01: 0.50:B:
pdb :A:phe: A: 13 : 0.067: -37.32: 0.65:A:
pdb :B:phe: A: 13 : 0.138: 19.24: 0.35:B:
pdb : :asn: A: 14 : 0.065: -96.35: 1.00: :
pdb : :val: A: 15 : 0.138: -96.63: 1.00: :
pdb : :cys: A: 16 : 0.102: -28.64: 1.00: :
pdb : :arg: A: 17 : 0.053:-106.79: 1.00: :
pdb : :leu: A: 18 : 0.053:-141.51: 1.00: :
pdb : :pro: A: 19 : 0.065:-146.95: 1.00: :
pdb : :thr: A: 21 : 0.086: 53.80: 1.00: :
pdb :A:pro: A: 22 : 0.092: -83.39: 0.55:A:
pdb :A:glu: A: 23 : 0.014:-179.53: 0.50:A:
pdb :B:glu: A: 23 : 0.050:-179.78: 0.50:B:
pdb : :ala: A: 24 : 0.056: -88.96: 1.00: :
pdb : :leu: A: 25 : 0.084:-106.42: 1.00: :
pdb : :cys: A: 26 : 0.074: -94.70: 1.00: :
pdb : :ala: A: 27 : 0.056: -62.15: 1.00: :
pdb : :thr: A: 28 : 0.056:-114.82: 1.00: :
pdb :A:tyr: A: 29 : 0.068: 0.22: 0.65:A:
pdb :A:thr: A: 30 : 0.180: 103.27: 0.70:A:
pdb :B:thr: A: 30 : 0.812: -76.98: 0.30:B:
pdb : :cys: A: 32 : 0.029: -84.07: 1.00: :
pdb : :ile: A: 33 : 0.048:-119.17: 1.00: :
pdb : :ile: A: 34 : 0.045: 99.02: 1.00: :
pdb : :ile: A: 35 : 0.052:-128.24: 1.00: :
pdb : :pro: A: 36 : 0.084:-142.29: 1.00: :
pdb : :ala: A: 38 : 0.039: 50.01: 1.00: :
pdb :A:thr: A: 39 : 0.093: -96.63: 0.70:A:
pdb :B:thr: A: 39 : 0.924: 56.41: 0.30:B:
pdb : :cys: A: 40 : 0.013:-144.11: 1.00: :
pdb : :pro: A: 41 : 0.039: -97.09: 1.00: :
pdb :A:asp: A: 43 : 0.130:-146.91: 0.75:A:
pdb :B:asp: A: 43 : 0.500: 7.56: 0.25:B:
pdb : :tyr: A: 44 : 0.085:-143.63: 1.00: :
pdb : :ala: A: 45 : 0.055: 33.32: 1.00: :
pdb : :asn: A: 46 : 0.066: -50.46: 1.00: :
SUMMARY: 6 C-beta deviations >= 0.25 Angstrom (Goal: 0)
""")
# Auxilary function: extract_atoms_from_residue_group
from mmtbx.validation.cbetadev import extract_atoms_from_residue_group
from iotbx import pdb
pdb_1 = pdb.input(source_info=None, lines="""\
ATOM 1185 N ASER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1186 N BSER A 146 24.758 37.100 16.337 0.50 16.79 N
ATOM 1187 CA ASER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1188 CA BSER A 146 24.237 37.427 17.662 0.50 16.87 C
ATOM 1189 C ASER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1190 C BSER A 146 22.792 36.945 17.783 0.50 15.94 C
ATOM 1191 O ASER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1192 O BSER A 146 22.091 36.741 16.779 0.50 15.17 O
ATOM 1193 CB ASER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1194 CB BSER A 146 24.321 38.940 17.904 0.50 17.48 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """).construct_hierarchy()
pdb_2 = pdb.input(source_info=None, lines="""\
ATOM 1185 N SER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1187 CA SER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1189 C SER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1191 O SER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1193 CB ASER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1194 CB BSER A 146 24.321 38.940 17.904 0.50 17.48 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """).construct_hierarchy()
pdb_3 = pdb.input(source_info=None, lines="""\
ATOM 1185 N SER A 146 24.734 37.097 16.303 0.50 16.64 N
ATOM 1187 CA SER A 146 24.173 37.500 17.591 0.50 16.63 C
ATOM 1189 C SER A 146 22.765 36.938 17.768 0.50 15.77 C
ATOM 1191 O SER A 146 22.052 36.688 16.781 0.50 14.91 O
ATOM 1193 CB SER A 146 24.118 39.035 17.649 0.50 16.93 C
ATOM 1195 OG ASER A 146 23.183 39.485 18.611 0.50 17.56 O
ATOM 1196 OG BSER A 146 23.468 39.645 17.028 0.50 18.32 O """).construct_hierarchy()
rg1 = pdb_1.only_model().only_chain().only_residue_group()
rg2 = pdb_2.only_model().only_chain().only_residue_group()
rg3 = pdb_3.only_model().only_chain().only_residue_group()
all_relevant_atoms_1 = extract_atoms_from_residue_group(rg1)
all_relevant_atoms_2 = extract_atoms_from_residue_group(rg2)
all_relevant_atoms_3 = extract_atoms_from_residue_group(rg3)
keys_1 = [ sorted([ k for k in a.keys() ]) for a in all_relevant_atoms_1 ]
keys_2 = [ sorted([ k for k in a.keys() ]) for a in all_relevant_atoms_2 ]
keys_3 = [ sorted([ k for k in a.keys() ]) for a in all_relevant_atoms_3 ]
assert keys_1 == [[' C ',' CA ',' CB ',' N '],[' C ',' CA ',' CB ',' N ']]
assert keys_2 == [[' C ',' CA ',' CB ',' N '],[' C ',' CA ',' CB ',' N ']]
assert keys_3 == [[' C ', ' CA ', ' CB ', ' N ']]
print "OK"
def exercise_protein () :
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/3ifk.pdb",
test=op.isfile)
hkl_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/reflection_files/3ifk.mtz",
test=op.isfile)
if (pdb_file is None) :
print "phenix_regression not available, skipping."
return
args1 = [
pdb_file,
"outliers_only=True",
"output.prefix=tst_molprobity",
"--pickle",
"flags.xtriage=True",
]
result = molprobity.run(args=args1, out=null_out()).validation
out1 = StringIO()
result.show(out=out1)
result = loads(dumps(result))
out2 = StringIO()
result.show(out=out2)
assert (result.nqh_flips.n_outliers == 1)
assert (not "RNA validation" in out2.getvalue())
assert (out2.getvalue() == out1.getvalue())
dump("tst_molprobity.pkl", result)
mc = result.as_multi_criterion_view()
assert (result.neutron_stats is None)
mpscore = result.molprobity_score()
# percentiles
out4 = StringIO()
result.show_summary(out=out4, show_percentiles=True)
assert (""" Clashscore = 49.96 (percentile: 0.2)""" in
out4.getvalue())
# misc
assert approx_equal(result.r_work(), 0.237) # from PDB header
assert approx_equal(result.r_free(), 0.293) # from PDB header
assert approx_equal(result.d_min(), 2.03) # from PDB header
assert (result.d_max_min() is None)
assert approx_equal(result.rms_bonds(), 0.02585)
assert approx_equal(result.rms_angles(), 2.356740)
assert approx_equal(result.rama_favored(), 96.47059)
assert (result.cbeta_outliers() == 10)
assert approx_equal(result.molprobity_score(), 3.40, eps=0.01)
summary = result.summarize()
gui_fields = list(summary.iter_molprobity_gui_fields())
assert (len(gui_fields) == 6)
#result.show()
assert (str(mc.data()[2]) == ' A 5 THR rota,cb,clash')
import mmtbx.validation.molprobity
from iotbx import file_reader
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
flags = mmtbx.validation.molprobity.molprobity_flags()
flags.clashscore = False
flags.model_stats = False
flags.cbetadev = False
result = mmtbx.validation.molprobity.molprobity(
pdb_hierarchy=hierarchy,
flags=flags)
out3 = StringIO()
result.show_summary(out=out3)
assert not show_diff(out3.getvalue(), """\
Ramachandran outliers = 1.76 %
favored = 96.47 %
Rotamer outliers = 20.00 %
""")
# now with data
args2 = args1 + [ hkl_file, "--maps" ]
result, cmdline = molprobity.run(args=args2,
out=null_out(),
return_input_objects=True)
out = StringIO()
result.show(out=out)
stats = result.get_statistics_for_phenix_gui()
#print stats
stats = result.get_polygon_statistics(["r_work","r_free","adp_mean_all",
"angle_rmsd", "bond_rmsd", "clashscore"])
#print stats
assert approx_equal(result.r_work(), 0.2276, eps=0.001)
assert approx_equal(result.r_free(), 0.2805, eps=0.001)
assert approx_equal(result.d_min(), 2.0302, eps=0.0001)
assert approx_equal(result.d_max_min(), [34.546125, 2.0302], eps=0.0001)
assert approx_equal(result.rms_bonds(), 0.02585)
assert approx_equal(result.rms_angles(), 2.356740)
assert approx_equal(result.rama_favored(), 96.47059)
assert (result.cbeta_outliers() == 10)
assert approx_equal(result.unit_cell().parameters(),
(55.285, 58.851, 67.115,90,90,90))
assert (str(result.space_group_info()) == "P 21 21 21")
bins = result.fmodel_statistics_by_resolution()
assert (len(bins) == 10)
assert approx_equal(result.atoms_to_observations_ratio(), 0.09755,
eps=0.0001)
assert approx_equal(result.b_iso_mean(), 31.11739)
assert op.isfile("tst_molprobity_maps.mtz")
assert approx_equal(result.atoms_to_observations_ratio(), 0.0975493)
bins = result.fmodel_statistics_by_resolution()
#bins.show()
bin_plot = result.fmodel_statistics_graph_data()
lg = bin_plot.format_loggraph()
# fake fmodel_neutron
fmodel_neutron = cmdline.fmodel.deep_copy()
result2 = mmtbx.validation.molprobity.molprobity(
pdb_hierarchy=cmdline.pdb_hierarchy,
fmodel=cmdline.fmodel,
fmodel_neutron=fmodel_neutron,
geometry_restraints_manager=cmdline.geometry,
nuclear=True,
keep_hydrogens=True)
stats = result2.get_statistics_for_phenix_gui()
assert ('R-work (neutron)' in [ label for (label, stat) in stats ])
def exercise_1():
pdb_raw = """\
ATOM 1134 N LYS A 82 5.933 36.285 21.572 1.00 70.94 N
ATOM 1135 CA LYS A 82 6.564 37.423 20.931 1.00 76.69 C
ATOM 1136 C LYS A 82 5.553 38.547 20.756 1.00 78.75 C
ATOM 1137 O LYS A 82 5.325 39.038 19.654 1.00 86.47 O
ATOM 1138 CB LYS A 82 7.179 37.024 19.583 1.00 82.32 C
ATOM 1139 CG LYS A 82 8.190 38.035 19.048 0.00 70.34 C
ATOM 1140 CD LYS A 82 9.429 38.129 19.944 0.00 67.69 C
ATOM 1141 CE LYS A 82 9.983 39.545 20.014 0.00 64.44 C
ATOM 1142 NZ LYS A 82 10.933 39.832 18.908 0.00 61.45 N
ATOM 1143 H LYS A 82 5.139 36.115 21.291 1.00 85.12 H
ATOM 1144 HA LYS A 82 7.279 37.749 21.501 1.00 92.03 H
ATOM 1145 HB2 LYS A 82 6.469 36.939 18.928 1.00 98.78 H
ATOM 1146 HB3 LYS A 82 7.636 36.175 19.687 1.00 98.78 H
ATOM 1147 HG2 LYS A 82 8.476 37.762 18.163 0.00 84.41 H
ATOM 1148 HG3 LYS A 82 7.775 38.912 19.011 0.00 84.41 H
ATOM 1149 HD2 LYS A 82 9.193 37.853 20.843 0.00 81.23 H
ATOM 1150 HD3 LYS A 82 10.122 37.551 19.589 0.00 81.23 H
ATOM 1151 HE2 LYS A 82 9.249 40.177 19.952 0.00 77.33 H
ATOM 1152 HE3 LYS A 82 10.453 39.662 20.854 0.00 77.33 H
ATOM 1153 HZ1 LYS A 82 11.237 40.666 18.977 0.00 73.75 H
ATOM 1154 HZ2 LYS A 82 10.523 39.738 18.123 0.00 73.75 H
ATOM 1155 HZ3 LYS A 82 11.621 39.269 18.944 0.00 73.75 H
ATOM 1156 N LYS A 83 4.936 38.927 21.866 1.00 75.79 N
ATOM 1157 CA LYS A 83 4.177 40.172 21.966 1.00 82.80 C
ATOM 1158 C LYS A 83 4.081 40.508 23.460 1.00 86.23 C
ATOM 1159 O LYS A 83 2.978 40.521 24.017 1.00 79.81 O
ATOM 1160 CB LYS A 83 2.790 40.044 21.332 1.00 79.16 C
ATOM 1161 CG LYS A 83 2.038 41.342 21.175 0.00 70.42 C
ATOM 1162 CD LYS A 83 2.072 41.803 19.735 0.00 66.90 C
ATOM 1163 CE LYS A 83 1.295 43.089 19.552 0.00 62.46 C
ATOM 1164 NZ LYS A 83 1.004 43.350 18.118 0.00 60.73 N
ATOM 1165 H LYS A 83 4.940 38.470 22.594 1.00 90.95 H
ATOM 1166 HA LYS A 83 4.658 40.885 21.518 1.00 99.36 H
ATOM 1167 HB2 LYS A 83 2.251 39.459 21.887 1.00 95.00 H
ATOM 1168 HB3 LYS A 83 2.890 39.655 20.449 1.00 95.00 H
ATOM 1169 HG2 LYS A 83 1.113 41.213 21.435 0.00 84.51 H
ATOM 1170 HG3 LYS A 83 2.453 42.024 21.726 0.00 84.51 H
ATOM 1171 HD2 LYS A 83 2.992 41.962 19.471 0.00 80.28 H
ATOM 1172 HD3 LYS A 83 1.672 41.123 19.171 0.00 80.28 H
ATOM 1173 HE2 LYS A 83 0.452 43.024 20.027 0.00 74.95 H
ATOM 1174 HE3 LYS A 83 1.818 43.830 19.896 0.00 74.95 H
ATOM 1175 HZ1 LYS A 83 0.521 42.683 17.780 0.00 72.87 H
ATOM 1176 HZ2 LYS A 83 1.764 43.417 17.661 0.00 72.87 H
ATOM 1177 HZ3 LYS A 83 0.548 44.109 18.034 0.00 72.87 H
ATOM 3630 N ASN A 242 -5.454 -3.027 1.145 0.00 67.69 N
ATOM 3631 CA ASN A 242 -4.759 -2.535 -0.037 0.00 65.44 C
ATOM 3632 C ASN A 242 -5.734 -2.397 -1.208 0.00 63.57 C
ATOM 3633 O ASN A 242 -6.425 -3.357 -1.552 0.00 63.94 O
ATOM 3634 CB ASN A 242 -3.626 -3.503 -0.392 0.00 63.13 C
ATOM 3635 CG ASN A 242 -2.802 -3.044 -1.576 0.00 63.58 C
ATOM 3636 OD1 ASN A 242 -2.524 -1.862 -1.731 0.00 65.52 O
ATOM 3637 ND2 ASN A 242 -2.399 -3.988 -2.416 0.00 62.17 N
ATOM 3638 H ASN A 242 -5.562 -3.880 1.129 0.00 81.22 H
ATOM 3639 HA ASN A 242 -4.375 -1.665 0.151 0.00 78.53 H
ATOM 3640 HB2 ASN A 242 -3.032 -3.587 0.370 0.00 75.76 H
ATOM 3641 HB3 ASN A 242 -4.007 -4.368 -0.611 0.00 75.76 H
ATOM 3642 HD21 ASN A 242 -1.929 -3.779 -3.104 0.00 74.60 H
ATOM 3643 HD22 ASN A 242 -2.609 -4.810 -2.272 0.00 74.60 H
ATOM 2 CA ALYS A 32 10.574 8.177 11.768 0.40 71.49 C
ATOM 3 CB ALYS A 32 9.197 8.686 12.246 0.40 74.71 C
ATOM 2 CA BLYS A 32 10.574 8.177 11.768 0.40 71.49 C
ATOM 3 CB BLYS A 32 9.197 8.686 12.246 0.40 74.71 C
ATOM 5 CA AVAL A 33 11.708 5.617 14.332 0.50 71.42 C
ATOM 6 CB AVAL A 33 11.101 4.227 14.591 0.50 71.47 C
ATOM 5 CA BVAL A 33 11.708 5.617 14.332 0.40 71.42 C
ATOM 6 CB BVAL A 33 11.101 4.227 14.591 0.40 71.47 C
TER
ATOM 1 N GLU X 18 -13.959 12.159 -6.598 1.00260.08 N
ATOM 2 CA GLU X 18 -13.297 13.465 -6.628 1.00269.83 C
ATOM 3 C GLU X 18 -11.946 13.282 -7.309 1.00269.18 C
ATOM 4 CB GLU X 18 -13.128 14.035 -5.210 1.00261.96 C
ATOM 5 CG GLU X 18 -14.455 14.401 -4.522 1.00263.56 C
ATOM 6 CD GLU X 18 -14.291 15.239 -3.242 1.00264.89 C
ATOM 7 OE1 GLU X 18 -14.172 14.646 -2.143 1.00264.24 O
ATOM 8 OE2 GLU X 18 -14.309 16.498 -3.306 1.00264.37 O1-
HETATM 614 S SO4 B 101 14.994 20.601 10.862 0.00 7.02 S
HETATM 615 O1 SO4 B 101 14.234 20.194 12.077 0.00 7.69 O
HETATM 616 O2 SO4 B 101 14.048 21.062 9.850 0.00 9.28 O
HETATM 617 O3 SO4 B 101 15.905 21.686 11.261 0.00 8.01 O
HETATM 618 O4 SO4 B 101 15.772 19.454 10.371 0.00 8.18 O
TER
HETATM 122 O HOH S 1 5.334 8.357 8.032 1.00 0.00 O
HETATM 123 O HOH S 2 5.396 15.243 10.734 1.00202.95 O
HETATM 124 O HOH S 3 -25.334 18.357 18.032 0.00 20.00 O
"""
mon_lib_srv = server.server()
ener_lib = server.ener_lib()
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
processed_pdb_file = pdb_interpretation.process(
mon_lib_srv=mon_lib_srv,
ener_lib=ener_lib,
raw_records=pdb_in.hierarchy.as_pdb_string(crystal_symmetry=xrs),
crystal_symmetry=xrs,
log=null_out())
pdb_in.hierarchy.atoms().reset_i_seq()
mstats = model_properties.model_statistics(
pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=processed_pdb_file.all_chain_proxies,
ignore_hd=True)
out = StringIO()
mstats.show(out=out)
#print out.getvalue()
assert not show_diff(
out.getvalue(), """\
Overall:
Number of atoms = 50 (anisotropic = 0)
B_iso: mean = 96.0 max = 269.8 min = 0.0
Occupancy: mean = 0.47 max = 1.00 min = 0.00
warning: 22 atoms with zero occupancy
69 total B-factor or occupancy problem(s) detected
Atoms or residues with zero occupancy:
LYS A 82 CG occ=0.00
LYS A 82 CD occ=0.00
LYS A 82 CE occ=0.00
LYS A 82 NZ occ=0.00
LYS A 83 CG occ=0.00
LYS A 83 CD occ=0.00
LYS A 83 CE occ=0.00
LYS A 83 NZ occ=0.00
ASN A 242 (all) occ=0.00
SO4 B 101 (all) occ=0.00
HOH S 3 O occ=0.00
Macromolecules:
Number of atoms = 42 (anisotropic = 0)
B_iso: mean = 108.0 max = 269.8 min = 60.7
Occupancy: mean = 0.51 max = 1.00 min = 0.00
warning: 16 atoms with zero occupancy
59 total B-factor or occupancy problem(s) detected
Ligands:
Number of atoms = 5 (anisotropic = 0)
B_iso: mean = 8.0 max = 9.3 min = 7.0
Occupancy: mean = 0.00 max = 0.00 min = 0.00
warning: 5 atoms with zero occupancy
6 total B-factor or occupancy problem(s) detected
Waters:
Number of atoms = 3 (anisotropic = 0)
B_iso: mean = 74.3 max = 202.9 min = 0.0
Occupancy: mean = 0.67 max = 1.00 min = 0.00
warning: 1 atoms with zero occupancy
4 total B-factor or occupancy problem(s) detected
(Hydrogen atoms not included in overall counts.)
""")
assert (len(mstats.all.bad_adps) == 1)
assert (mstats.all.n_zero_b == 1)
mstats2 = loads(dumps(mstats))
out1 = StringIO()
out2 = StringIO()
mstats.show(out=out1)
mstats2.show(out=out2)
assert (out1.getvalue() == out2.getvalue())
# now with ignore_hd=False
mstats3 = model_properties.model_statistics(
pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=processed_pdb_file.all_chain_proxies,
ignore_hd=False)
out2 = StringIO()
mstats3.show(out=out2)
assert (out2.getvalue() != out.getvalue())
assert (""" LYS A 83 HZ3 occ=0.00""" in out2.getvalue())
outliers = mstats3.all.as_gui_table_data(include_zoom=True)
assert (len(outliers) == 86)
# test with all_chain_proxies undefined
mstats4 = model_properties.model_statistics(pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=None,
ignore_hd=False)
outliers = mstats4.all.as_gui_table_data(include_zoom=True)
assert (len(outliers) == 86)
def exercise_rotalyze():
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/jcm.pdb",
test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_rotalyze(): input pdb (jcm.pdb) not available"
return
if (find_rotarama_data_dir(optional=True) is None):
print "Skipping exercise_rotalyze(): rotarama_data directory not available"
return
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
r = rotalyze.rotalyze(
pdb_hierarchy=hierarchy,
outliers_only=True)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("OUTLIER") == 246, output.count("OUTLIER")
assert output.count(":") == 984, output.count(":")
output_lines = output.splitlines()
assert len(output_lines) == 123
for lines in output_lines:
assert float(lines[12:15]) <= 1.0
r = rotalyze.rotalyze(
pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True] :
if unpickle :
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
for outlier in r.results :
assert (len(outlier.xyz) == 3)
output = out.getvalue()
assert output.count("OUTLIER") == 246
assert output.count(":") == 5144, output.count(":")
assert output.count("p") == 120
assert output.count("m") == 324
assert output.count("t") == 486
output_lines = output.splitlines()
#for line in output_lines:
# print line
#STOP()
assert len(output_lines) == 643
line_indices = [0,1,2,42,43,168,169,450,587,394,641,642]
# top500 version
line_values = [
" A 14 MET:1.00:3.3:29.2:173.3:287.9::Favored:ptm",
" A 15 SER:1.00:0.1:229.0::::OUTLIER:OUTLIER",
" A 16 SER:1.00:4.2:277.9::::Favored:m",
" A 58 ASN:1.00:2.0:252.4:343.6:::Favored:m-20",
" A 59 ILE:1.00:2.0:84.2:186.7:::Allowed:pt",
" A 202 GLU:1.00:0.4:272.7:65.9:287.8::OUTLIER:OUTLIER",
" A 203 ILE:1.00:5.0:292.9:199.6:::Favored:mt",
" B 154 THR:1.00:0.1:356.0::::OUTLIER:OUTLIER",
" B 316 TYR:1.00:5.4:153.7:68.6:::Favored:t80",
" B 86 ASP:1.00:2.2:321.4:145.1:::Favored:m-20",
" B 377 GLU:1.00:45.3:311.7:166.2:160.1::Favored:mt-10",
" B 378 THR:1.00:23.5:309.4::::Favored:m"]
# top8000 version
line_values = [
" A 14 MET:1.00:1.3:29.2:173.3:287.9::Allowed:ptm",
" A 15 SER:1.00:0.1:229.0::::OUTLIER:OUTLIER",
" A 16 SER:1.00:3.0:277.9::::Favored:m",
" A 58 ASN:1.00:1.0:252.4:343.6:::Allowed:m-40",
" A 59 ILE:1.00:0.5:84.2:186.7:::Allowed:pt",
" A 202 GLU:1.00:0.0:272.7:65.9:287.8::OUTLIER:OUTLIER",
" A 203 ILE:1.00:1.0:292.9:199.6:::Allowed:mt",
" B 154 THR:1.00:0.0:356.0::::OUTLIER:OUTLIER",
" B 316 TYR:1.00:4.1:153.7:68.6:::Favored:t80",
" B 86 ASP:1.00:0.4:321.4:145.1:::Allowed:m-30",
" B 377 GLU:1.00:15.0:311.7:166.2:160.1::Favored:mt-10",
" B 378 THR:1.00:17.0:309.4::::Favored:m",
]
for idx, val in zip(line_indices, line_values) :
assert (output_lines[idx] == val), (idx, output_lines[idx])
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent",
test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_ramalyze(): input pdb (pdb1jxt.ent) not available"
return
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
r = rotalyze.rotalyze(
pdb_hierarchy=hierarchy,
outliers_only=True)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue().strip()
assert output == ""
r = rotalyze.rotalyze(
pdb_hierarchy=hierarchy,
outliers_only=False)
for unpickle in [False, True] :
if unpickle :
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert not show_diff(output,"""\
A 1 THR:1.00:95.4:299.5::::Favored:m
A 2 ATHR:0.67:49.5:56.1::::Favored:p
A 2 BTHR:0.33:90.4:298.1::::Favored:m
A 3 CYS:1.00:12.9:310.5::::Favored:m
A 4 CYS:1.00:91.6:293.1::::Favored:m
A 5 PRO:1.00:78.8:30.2:319.7:33.8::Favored:Cg_endo
A 6 SER:1.00:90.1:68.4::::Favored:p
A 7 AILE:0.45:49.6:290.8:178.2:::Favored:mt
A 7 BILE:0.55:6.5:284.4:298.4:::Favored:mm
A 8 AVAL:0.50:1.1:156.7::::Allowed:t
A 8 BVAL:0.30:5.1:71.3::::Favored:p
A 8 CVAL:0.20:69.8:172.1::::Favored:t
A 10 AARG:0.65:24.7:176.8:66.5:63.9:180.0:Favored:tpp-160
A 10 BARG:0.35:17.5:176.8:72.8:66.4:171.9:Favored:tpp-160
A 11 SER:1.00:51.6:300.9::::Favored:m
A 12 AASN:0.50:93.9:286.1:343.8:::Favored:m-40
A 12 BASN:0.50:98.9:288.4:337.6:::Favored:m-40
A 13 APHE:0.65:45.1:187.2:276.4:::Favored:t80
A 13 BPHE:0.35:86.1:179.6:263.1:::Favored:t80
A 14 ASN:1.00:95.2:289.6:333.0:::Favored:m-40
A 15 VAL:1.00:42.3:168.2::::Favored:t
A 16 CYS:1.00:40.8:176.5::::Favored:t
A 17 ARG:1.00:21.4:289.7:282.8:288.6:158.7:Favored:mmm160
A 18 LEU:1.00:65.0:287.2:173.3:::Favored:mt
A 19 PRO:1.00:43.6:24.4:324.8:31.6::Favored:Cg_endo
A 21 THR:1.00:5.7:314.0::::Favored:m
A 22 APRO:0.55:87.5:333.5:34.0:333.8::Favored:Cg_exo
A 23 AGLU:0.50:86.9:290.9:187.1:341.8::Favored:mt-10
A 23 BGLU:0.50:91.7:292.0:183.8:339.2::Favored:mt-10
A 25 ALEU:0.50:95.7:294.4:173.6:::Favored:mt
A 26 CYS:1.00:83.0:295.0::::Favored:m
A 28 THR:1.00:29.6:52.9::::Favored:p
A 29 ATYR:0.65:18.5:161.8:67.8:::Favored:t80
A 29 BTYR:0.35:0.4:191.3:322.7:::Allowed:t80
A 30 ATHR:0.70:60.8:57.4::::Favored:p
A 30 BTHR:0.30:6.6:78.1::::Favored:p
A 32 CYS:1.00:61.4:301.7::::Favored:m
A 33 ILE:1.00:36.6:66.5:173.4:::Favored:pt
A 34 AILE:0.70:60.9:303.6:167.6:::Favored:mt
A 34 BILE:0.30:31.4:308.5:296.8:::Favored:mm
A 35 ILE:1.00:45.6:62.4:170.0:::Favored:pt
A 36 PRO:1.00:36.2:22.5:330.5:24.8::Favored:Cg_endo
A 39 ATHR:0.70:14.0:311.0::::Favored:m
A 39 BTHR:0.30:13.1:288.8::::Favored:m
A 40 CYS:1.00:81.4:294.4::::Favored:m
A 41 PRO:1.00:35.4:34.4:317.5:33.1::Favored:Cg_endo
A 43 AASP:0.75:24.8:56.5:340.3:::Favored:p0
A 43 BASP:0.25:43.2:59.6:349.3:::Favored:p0
A 44 TYR:1.00:85.3:290.9:85.1:::Favored:m-80
A 46 ASN:1.00:38.7:301.6:117.9:::Favored:m110
""")
def test_goniometer():
"""A test class for the goniometer class."""
axis = (1, 0, 0)
fixed = (1, 0, 0, 0, 1, 0, 0, 0, 1)
xg = Goniometer(axis, fixed)
assert len(xg.get_rotation_axis()) == 3
assert len(xg.get_fixed_rotation()) == 9
_compare_tuples(xg.get_rotation_axis(), axis)
_compare_tuples(xg.get_fixed_rotation(), fixed)
single = GoniometerFactory.single_axis()
assert len(single.get_rotation_axis()) == 3
assert len(single.get_fixed_rotation()) == 9
_compare_tuples(single.get_rotation_axis(), axis)
_compare_tuples(single.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "phi")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 30.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
with pytest.raises(AssertionError):
_compare_tuples(kappa.get_fixed_rotation(), fixed)
import libtbx.load_env
dxtbx_dir = libtbx.env.dist_path("dxtbx")
image = os.path.join(dxtbx_dir, "tests", "phi_scan_001.cbf")
assert GoniometerFactory.imgCIF(image)
kappa = GoniometerFactory.kappa(50.0, -10.0, 30.0, 0.0, "-y", "phi")
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
image = os.path.join(dxtbx_dir, "tests", "omega_scan.cbf")
assert GoniometerFactory.imgCIF(image)
kappa = GoniometerFactory.kappa(50.0, -10.0, 30.0, 20.0, "-y", "omega")
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
def copy (self, preserve_changes=True) :
if preserve_changes :
return easy_pickle.loads(easy_pickle.dumps(self))
else :
return self.copy_master()
def exercise_protein():
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/3ifk.pdb", test=op.isfile)
hkl_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/reflection_files/3ifk.mtz",
test=op.isfile)
if (pdb_file is None):
print "phenix_regression not available, skipping."
return
args1 = [
pdb_file,
"outliers_only=True",
"output.prefix=tst_molprobity",
"--pickle",
"flags.xtriage=True",
]
result = molprobity.run(args=args1, out=null_out()).validation
out1 = StringIO()
result.show(out=out1)
result = loads(dumps(result))
out2 = StringIO()
result.show(out=out2)
assert (result.nqh_flips.n_outliers == 6)
assert (not "RNA validation" in out2.getvalue())
assert (out2.getvalue() == out1.getvalue())
dump("tst_molprobity.pkl", result)
mc = result.as_multi_criterion_view()
assert (result.neutron_stats is None)
mpscore = result.molprobity_score()
# percentiles
out4 = StringIO()
result.show_summary(out=out4, show_percentiles=True)
assert (""" Clashscore = 49.59"""
in out4.getvalue()), out4.getvalue()
# misc
assert approx_equal(result.r_work(), 0.237) # from PDB header
assert approx_equal(result.r_free(), 0.293) # from PDB header
assert approx_equal(result.d_min(), 2.03) # from PDB header
assert (result.d_max_min() is None)
assert approx_equal(result.rms_bonds(), 0.02585)
assert approx_equal(result.rms_angles(), 2.356740)
assert approx_equal(result.rama_favored(), 96.47059)
assert (result.cbeta_outliers() == 10)
assert approx_equal(result.molprobity_score(), 3.39, eps=0.01)
summary = result.summarize()
gui_fields = list(summary.iter_molprobity_gui_fields())
assert (len(gui_fields) == 6)
#result.show()
assert (str(mc.data()[2]) == ' A 5 THR rota,cb,clash')
import mmtbx.validation.molprobity
from iotbx import file_reader
pdb_in = file_reader.any_file(pdb_file)
model = mmtbx.model.manager(pdb_in.file_object.input)
result = mmtbx.validation.molprobity.molprobity(model)
out3 = StringIO()
result.show_summary(out=out3)
assert """\
Ramachandran outliers = 1.76 %
favored = 96.47 %
Rotamer outliers = 20.00 %
""" in out3.getvalue()
# now with data
args2 = args1 + [hkl_file, "--maps"]
result, cmdline = molprobity.run(args=args2,
out=null_out(),
return_input_objects=True)
out = StringIO()
result.show(out=out)
stats = result.get_statistics_for_phenix_gui()
#print stats
stats = result.get_polygon_statistics([
"r_work", "r_free", "adp_mean_all", "angle_rmsd", "bond_rmsd",
"clashscore"
])
#print stats
assert approx_equal(result.r_work(), 0.2276, eps=0.001)
assert approx_equal(result.r_free(), 0.2805, eps=0.001)
assert approx_equal(result.d_min(), 2.0302, eps=0.0001)
assert approx_equal(result.d_max_min(), [34.546125, 2.0302], eps=0.0001)
assert approx_equal(result.rms_bonds(), 0.02585)
assert approx_equal(result.rms_angles(), 2.356740)
assert approx_equal(result.rama_favored(), 96.47059)
assert (result.cbeta_outliers() == 10)
assert approx_equal(result.unit_cell().parameters(),
(55.285, 58.851, 67.115, 90, 90, 90))
assert (str(result.space_group_info()) == "P 21 21 21")
bins = result.fmodel_statistics_by_resolution()
assert (len(bins) == 10)
assert approx_equal(result.atoms_to_observations_ratio(),
0.09755,
eps=0.0001)
assert approx_equal(result.b_iso_mean(), 31.11739)
assert op.isfile("tst_molprobity_maps.mtz")
bins = result.fmodel_statistics_by_resolution()
#bins.show()
bin_plot = result.fmodel_statistics_graph_data()
lg = bin_plot.format_loggraph()
# fake fmodel_neutron
fmodel_neutron = cmdline.fmodel.deep_copy()
result2 = mmtbx.validation.molprobity.molprobity(
cmdline.model,
fmodel=cmdline.fmodel,
fmodel_neutron=fmodel_neutron,
nuclear=True,
keep_hydrogens=True)
stats = result2.get_statistics_for_phenix_gui()
assert ('R-work (neutron)' in [label for (label, stat) in stats])
def exercise () :
import libtbx.utils
if (libtbx.utils.detect_multiprocessing_problem() is not None) :
print "multiprocessing not available, skipping this test"
return
if (os.name == "nt"):
print "easy_mp fixed_func not supported under Windows, skipping this test"
return
from mmtbx.validation.sequence import validation, get_sequence_n_copies, \
get_sequence_n_copies_from_files
import iotbx.bioinformatics
import iotbx.pdb
from iotbx import file_reader
import libtbx.load_env # import dependency
from libtbx.test_utils import Exception_expected, contains_lines, approx_equal
from cStringIO import StringIO
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2 CA ARG A 10 -6.299 36.344 7.806 1.00 55.20 C
ATOM 25 CA TYR A 11 -3.391 33.962 7.211 1.00 40.56 C
ATOM 46 CA ALA A 12 -0.693 34.802 4.693 1.00 67.95 C
ATOM 56 CA ALA A 13 0.811 31.422 3.858 1.00 57.97 C
ATOM 66 CA GLY A 14 4.466 31.094 2.905 1.00 49.24 C
ATOM 73 CA ALA A 15 7.163 28.421 2.671 1.00 54.70 C
ATOM 83 CA ILE A 16 6.554 24.685 2.957 1.00 51.79 C
ATOM 102 CA LEU A 17 7.691 23.612 6.406 1.00 42.30 C
ATOM 121 CA PTY A 18 7.292 19.882 5.861 1.00 36.68 C
ATOM 128 CA PHE A 19 5.417 16.968 4.327 1.00 44.99 C
ATOM 148 CA GLY A 20 3.466 14.289 6.150 1.00 41.99 C
ATOM 155 CA GLY A 21 1.756 11.130 4.965 1.00 35.77 C
ATOM 190 CA ALA A 24 1.294 19.658 3.683 1.00 47.02 C
ATOM 200 CA VAL A 24A 2.361 22.009 6.464 1.00 37.13 C
ATOM 216 CA HIS A 25 2.980 25.633 5.535 1.00 42.52 C
ATOM 234 CA LEU A 26 4.518 28.425 7.577 1.00 47.63 C
ATOM 253 CA ALA A 27 2.095 31.320 7.634 1.00 38.61 C
ATOM 263 CA ARG A 28 1.589 34.719 9.165 1.00 37.04 C
END""")
seq1 = iotbx.bioinformatics.sequence("MTTPSHLSDRYELGEILGFGGMSEVHLARD".lower())
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq1],
log=null_out(),
nproc=1)
out = StringIO()
v.show(out=out)
assert contains_lines(out.getvalue(), """\
sequence identity: 76.47%
13 residue(s) missing from PDB chain (9 at start, 1 at end)
2 gap(s) in chain
4 mismatches to sequence
residue IDs: 12 13 15 24""")
cif_block = v.as_cif_block()
assert list(cif_block['_struct_ref.pdbx_seq_one_letter_code']) == [
'MTTPSHLSDRYELGEILGFGGMSEVHLARD']
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg'],
['10', '14', '16', '19', '24'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '21', '28'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_beg'],
['10', '14', '16', '19', '25'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_end'],
['11', '14', '17', '21', '29'])
assert cif_block['_struct_ref_seq.pdbx_seq_align_beg_ins_code'][4] == 'A'
seq2 = iotbx.bioinformatics.sequence("MTTPSHLSDRYELGEILGFGGMSEVHLA")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq2],
log=null_out(),
nproc=1)
out = StringIO()
v.show(out=out)
assert contains_lines(out.getvalue(), """\
1 residues not found in sequence
residue IDs: 28""")
try :
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[],
log=null_out(),
nproc=1)
except AssertionError :
pass
else :
raise Exception_expected
cif_block = v.as_cif_block()
assert list(cif_block['_struct_ref.pdbx_seq_one_letter_code']) == [
'MTTPSHLSDRYELGEILGFGGMSEVHLA-']
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '21', '27'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_end'],
['11', '14', '17', '21', '28'])
#
pdb_in2 = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2 CA ARG A 10 -6.299 36.344 7.806 1.00 55.20 C
ATOM 25 CA TYR A 11 -3.391 33.962 7.211 1.00 40.56 C
ATOM 46 CA ALA A 12 -0.693 34.802 4.693 1.00 67.95 C
ATOM 56 CA ALA A 13 0.811 31.422 3.858 1.00 57.97 C
ATOM 66 CA GLY A 14 4.466 31.094 2.905 1.00 49.24 C
ATOM 73 CA ALA A 15 7.163 28.421 2.671 1.00 54.70 C
ATOM 83 CA ILE A 16 6.554 24.685 2.957 1.00 51.79 C
ATOM 102 CA LEU A 17 7.691 23.612 6.406 1.00 42.30 C
TER
ATOM 1936 P G B 2 -22.947 -23.615 15.323 1.00123.20 P
ATOM 1959 P C B 3 -26.398 -26.111 19.062 1.00110.06 P
ATOM 1979 P U B 4 -29.512 -30.638 21.164 1.00101.06 P
ATOM 1999 P C B 5 -30.524 -36.109 21.527 1.00 92.76 P
ATOM 2019 P U B 6 -28.684 -41.458 21.223 1.00 87.42 P
ATOM 2062 P G B 8 -18.396 -45.415 21.903 1.00 80.35 P
ATOM 2085 P A B 9 -13.852 -43.272 24.156 1.00 77.76 P
ATOM 2107 P G B 10 -8.285 -44.242 26.815 1.00 79.86 P
END
""")
seq3 = iotbx.bioinformatics.sequence("AGCUUUGGAG")
v = validation(
pdb_hierarchy=pdb_in2.construct_hierarchy(),
sequences=[seq2,seq3],
log=null_out(),
nproc=1,
extract_coordinates=True)
out = StringIO()
v.show(out=out)
cif_block = v.as_cif_block()
assert approx_equal(cif_block['_struct_ref.pdbx_seq_one_letter_code'],
['MTTPSHLSDRYELGEILGFGGMSEVHLA', 'AGCUUUGGAG'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg'],
['10', '14', '16', '2', '6', '8'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '4', '6', '10'])
assert (len(v.chains[0].get_outliers_table()) == 3)
assert (len(v.get_table_data()) == 4)
assert approx_equal(
v.chains[0].get_mean_coordinate_for_alignment_range(11,11),
(-0.693, 34.802, 4.693))
assert approx_equal(
v.chains[0].get_mean_coordinate_for_alignment_range(11,14),
(2.93675, 31.43475, 3.53175))
assert (v.chains[0].get_highlighted_residues() == [11,12,14])
assert contains_lines(out.getvalue(), """\
3 mismatches to sequence
residue IDs: 12 13 15""")
assert contains_lines(out.getvalue(), """\
sequence identity: 87.50%
2 residue(s) missing from PDB chain (1 at start, 0 at end)
1 gap(s) in chain
1 mismatches to sequence
residue IDs: 5""")
s = easy_pickle.dumps(v)
seq4 = iotbx.bioinformatics.sequence("")
try :
v = validation(
pdb_hierarchy=pdb_in2.construct_hierarchy(),
sequences=[seq4],
log=null_out(),
nproc=1,
extract_coordinates=True)
except AssertionError :
pass
else :
raise Exception_expected
# check that nucleic acid chain doesn't get aligned against protein sequence
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 18932 P B DG D 1 -12.183 60.531 25.090 0.50364.79 P
ATOM 18963 P B DG D 2 -9.738 55.258 20.689 0.50278.77 P
ATOM 18994 P B DA D 3 -10.119 47.855 19.481 0.50355.17 P
ATOM 19025 P B DT D 4 -13.664 42.707 21.119 0.50237.06 P
ATOM 19056 P B DG D 5 -19.510 39.821 21.770 0.50255.45 P
ATOM 19088 P B DA D 6 -26.096 40.001 21.038 0.50437.49 P
ATOM 19120 P B DC D 7 -31.790 41.189 18.413 0.50210.00 P
ATOM 19149 P B DG D 8 -34.639 41.306 12.582 0.50313.99 P
ATOM 19179 P B DA D 9 -34.987 38.244 6.813 0.50158.92 P
ATOM 19210 P B DT D 10 -32.560 35.160 1.082 0.50181.38 P
HETATM19241 P BTSP D 11 -27.614 30.137 0.455 0.50508.17 P
""")
sequences, _ = iotbx.bioinformatics.fasta_sequence_parse.parse(
""">4GFH:A|PDBID|CHAIN|SEQUENCE
MSTEPVSASDKYQKISQLEHILKRPDTYIGSVETQEQLQWIYDEETDCMIEKNVTIVPGLFKIFDEILVNAADNKVRDPS
MKRIDVNIHAEEHTIEVKNDGKGIPIEIHNKENIYIPEMIFGHLLTSSNYDDDEKKVTGGRNGYGAKLCNIFSTEFILET
ADLNVGQKYVQKWENNMSICHPPKITSYKKGPSYTKVTFKPDLTRFGMKELDNDILGVMRRRVYDINGSVRDINVYLNGK
SLKIRNFKNYVELYLKSLEKKRQLDNGEDGAAKSDIPTILYERINNRWEVAFAVSDISFQQISFVNSIATTMGGTHVNYI
TDQIVKKISEILKKKKKKSVKSFQIKNNMFIFINCLIENPAFTSQTKEQLTTRVKDFGSRCEIPLEYINKIMKTDLATRM
FEIADANEENALKKSDGTRKSRITNYPKLEDANKAGTKEGYKCTLVLTEGDSALSLAVAGLAVVGRDYYGCYPLRGKMLN
VREASADQILKNAEIQAIKKIMGLQHRKKYEDTKSLRYGHLMIMTDQDHDGSHIKGLIINFLESSFPGLLDIQGFLLEFI
TPIIKVSITKPTKNTIAFYNMPDYEKWREEESHKFTWKQKYYKGLGTSLAQEVREYFSNLDRHLKIFHSLQGNDKDYIDL
AFSKKKADDRKEWLRQYEPGTVLDPTLKEIPISDFINKELILFSLADNIRSIPNVLDGFKPGQRKVLYGCFKKNLKSELK
VAQLAPYVSECTAYHHGEQSLAQTIIGLAQNFVGSNNIYLLLPNGAFGTRATGGKDAAAARYIYTELNKLTRKIFHPADD
PLYKYIQEDEKTVEPEWYLPILPMILVNGAEGIGTGWSTYIPPFNPLEIIKNIRHLMNDEELEQMHPWFRGWTGTIEEIE
PLRYRMYGRIEQIGDNVLEITELPARTWTSTIKEYLLLGLSGNDKIKPWIKDMEEQHDDNIKFIITLSPEEMAKTRKIGF
YERFKLISPISLMNMVAFDPHGKIKKYNSVNEILSEFYYVRLEYYQKRKDHMSERLQWEVEKYSFQVKFIKMIIEKELTV
TNKPRNAIIQELENLGFPRFNKEGKPYYGSPNDEIAEQINDVKGATSDEEDEESSHEDTENVINGPEELYGTYEYLLGMR
IWSLTKERYQKLLKQKQEKETELENLLKLSAKDIWNTDLKAFEVGYQEFLQRDAEAR
>4GFH:D|PDBID|CHAIN|SEQUENCE
GGATGACGATX
""")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=sequences,
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing == 0
assert v.chains[0].n_missing_end == 0
assert v.chains[0].n_missing_start == 0
assert len(v.chains[0].alignment.matches()) == 11
#
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2 CA GLY A 1 1.367 0.551 0.300 1.00 7.71 C
ATOM 6 CA CYS A 2 2.782 3.785 1.683 1.00 5.18 C
ATOM 12 CA CYS A 3 -0.375 5.128 3.282 1.00 5.21 C
ATOM 18 CA SER A 4 -0.870 2.048 5.492 1.00 7.19 C
ATOM 25 CA LEU A 5 2.786 2.056 6.642 1.00 6.78 C
ATOM 33 CA PRO A 6 3.212 4.746 9.312 1.00 7.03 C
ATOM 40 CA PRO A 7 6.870 5.690 8.552 1.00 7.97 C
ATOM 47 CA CYS A 8 6.021 6.070 4.855 1.00 6.48 C
ATOM 53 CA ALA A 9 2.812 8.041 5.452 1.00 7.15 C
ATOM 58 CA LEU A 10 4.739 10.382 7.748 1.00 8.36 C
ATOM 66 CA SER A 11 7.292 11.200 5.016 1.00 7.00 C
ATOM 73 CA ASN A 12 4.649 11.435 2.264 1.00 5.40 C
ATOM 81 CA PRO A 13 1.879 13.433 3.968 1.00 5.97 C
ATOM 88 CA ASP A 14 0.485 15.371 0.986 1.00 7.70 C
ATOM 96 CA TYR A 15 0.565 12.245 -1.180 1.00 6.55 C
ATOM 108 CA CYS A 16 -1.466 10.260 1.363 1.00 7.32 C
ATOM 113 N NH2 A 17 -2.612 12.308 2.058 1.00 8.11 N
""")
seq = iotbx.bioinformatics.sequence("GCCSLPPCALSNPDYCX")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing == 0
assert v.chains[0].n_missing_end == 0
assert v.chains[0].n_missing_start == 0
assert len(v.chains[0].alignment.matches()) == 17
#
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2518 CA PRO C 3 23.450 -5.848 45.723 1.00 85.24 C
ATOM 2525 CA GLY C 4 20.066 -4.416 44.815 1.00 79.25 C
ATOM 2529 CA PHE C 5 19.408 -0.913 46.032 1.00 77.13 C
ATOM 2540 CA GLY C 6 17.384 -1.466 49.208 1.00 83.44 C
ATOM 2544 CA GLN C 7 17.316 -5.259 49.606 1.00 89.25 C
ATOM 2553 CA GLY C 8 19.061 -6.829 52.657 1.00 90.67 C
""")
sequences, _ = iotbx.bioinformatics.fasta_sequence_parse.parse(
""">1JN5:A|PDBID|CHAIN|SEQUENCE
MASVDFKTYVDQACRAAEEFVNVYYTTMDKRRRLLSRLYMGTATLVWNGNAVSGQESLSEFFEMLPSSEFQISVVDCQPV
HDEATPSQTTVLVVICGSVKFEGNKQRDFNQNFILTAQASPSNTVWKIASDCFRFQDWAS
>1JN5:B|PDBID|CHAIN|SEQUENCE
APPCKGSYFGTENLKSLVLHFLQQYYAIYDSGDRQGLLDAYHDGACCSLSIPFIPQNPARSSLAEYFKDSRNVKKLKDPT
LRFRLLKHTRLNVVAFLNELPKTQHDVNSFVVDISAQTSTLLCFSVNGVFKEVDGKSRDSLRAFTRTFIAVPASNSGLCI
VNDELFVRNASSEEIQRAFAMPAPTPSSSPVPTLSPEQQEMLQAFSTQSGMNLEWSQKCLQDNNWDYTRSAQAFTHLKAK
GEIPEVAFMK
>1JN5:C|PDBID|CHAIN|SEQUENCE
GQSPGFGQGGSV
""")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=sequences,
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 3
assert v.chains[0].n_missing_end == 3
assert v.chains[0].identity == 1.0
assert v.chains[0].alignment.match_codes == 'iiimmmmmmiii'
#
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2 CA ALA A 2 -8.453 57.214 -12.754 1.00 52.95 C
ATOM 7 CA LEU A 3 -8.574 59.274 -9.471 1.00 24.33 C
ATOM 15 CA ARG A 4 -12.178 60.092 -8.575 1.00 28.40 C
ATOM 26 CA GLY A 5 -14.170 61.485 -5.667 1.00 26.54 C
ATOM 30 CA THR A 6 -17.784 60.743 -4.783 1.00 31.78 C
ATOM 37 CA VAL A 7 -19.080 64.405 -4.464 1.00 21.31 C
""")
seq = iotbx.bioinformatics.sequence("XALRGTV")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 1
assert v.chains[0].n_missing_end == 0
assert v.chains[0].identity == 1.0
assert v.chains[0].alignment.match_codes == 'immmmmm'
#
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 2171 CA ASP I 355 5.591 -11.903 1.133 1.00 41.60 C
ATOM 2175 CA PHE I 356 7.082 -8.454 0.828 1.00 39.82 C
ATOM 2186 CA GLU I 357 5.814 -6.112 -1.877 1.00 41.12 C
ATOM 2195 CA GLU I 358 8.623 -5.111 -4.219 1.00 42.70 C
ATOM 2199 CA ILE I 359 10.346 -1.867 -3.363 1.00 43.32 C
ATOM 2207 CA PRO I 360 11.658 0.659 -5.880 1.00 44.86 C
ATOM 2214 CA GLU I 361 14.921 -0.125 -7.592 1.00 44.32 C
ATOM 2219 CA GLU I 362 15.848 3.489 -6.866 1.00 44.27 C
HETATM 2224 CA TYS I 363 16.482 2.005 -3.448 1.00 44.52 C
""")
seq = iotbx.bioinformatics.sequence("NGDFEEIPEEYL")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 2
assert v.chains[0].n_missing_end == 1
assert v.chains[0].identity == 1.0
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 450 CA ASN A 1 37.242 41.665 44.160 1.00 35.89 C
ATOM 458 CA GLY A 2 37.796 38.269 42.523 1.00 30.13 C
HETATM 463 CA AMSE A 3 35.878 39.005 39.326 0.54 22.83 C
HETATM 464 CA BMSE A 3 35.892 39.018 39.323 0.46 22.96 C
ATOM 478 CA ILE A 4 37.580 38.048 36.061 1.00 22.00 C
ATOM 486 CA SER A 5 37.593 40.843 33.476 1.00 18.73 C
ATOM 819 CA ALA A 8 25.982 34.781 27.220 1.00 18.43 C
ATOM 824 CA ALA A 9 23.292 32.475 28.614 1.00 19.60 C
HETATM 830 CA BMSE A 10 22.793 30.814 25.223 0.41 22.60 C
HETATM 831 CA CMSE A 10 22.801 30.850 25.208 0.59 22.54 C
ATOM 845 CA GLU A 11 26.504 30.054 24.966 1.00 25.19 C
ATOM 854 CA GLY A 12 25.907 28.394 28.320 1.00 38.88 C
""")
seq = iotbx.bioinformatics.sequence("NGMISAAAAMEG")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
assert v.chains[0].alignment.a == 'NGMISXXAAMEG'
assert v.chains[0].alignment.b == 'NGMISAAAAMEG'
pdb_in = iotbx.pdb.input(source_info=None, lines="""\
ATOM 4615 CA ALA C 1 1.000 1.000 1.000 1.00 10.00
ATOM 4622 CA ALA C 2 1.000 1.000 1.000 1.00 10.00
ATOM 4627 CA ALA C 3 1.000 1.000 1.000 1.00 10.00
ATOM 4634 CA ALA C 4 1.000 1.000 1.000 1.00 10.00
ATOM 4646 CA ALA C 5 1.000 1.000 1.000 1.00 10.00
ATOM 4658 CA ALA C 6 1.000 1.000 1.000 1.00 10.00
ATOM 4664 CA ALA C 7 1.000 1.000 1.000 1.00 10.00
ATOM 4669 CA ALA C 8 1.000 1.000 1.000 1.00 10.00
ATOM 4680 CA ARG C 9 1.000 1.000 1.000 1.00 10.00
ATOM 4690 CA GLY C 10 1.000 1.000 1.000 1.00 10.00
ATOM 4698 CA PRO C 11 1.000 1.000 1.000 1.00 10.00
ATOM 4705 CA LYS C 12 1.000 1.000 1.000 1.00 10.00
ATOM 4712 CA TRP C 13 1.000 1.000 1.000 1.00 10.00
ATOM 4726 CA GLU C 14 1.000 1.000 1.000 1.00 10.00
ATOM 4738 CA SER C 15 1.000 1.000 1.000 1.00 10.00
ATOM 4744 CA THR C 16 1.000 1.000 1.000 1.00 10.00
ATOM 4751 CA GLY C 17 1.000 1.000 1.000 1.00 10.00
ATOM 4755 CA TYR C 18 1.000 1.000 1.000 1.00 10.00
ATOM 4767 CA PHE C 19 1.000 1.000 1.000 1.00 10.00
ATOM 4778 CA ALA C 20 1.000 1.000 1.000 1.00 10.00
ATOM 4786 CA ALA C 21 1.000 1.000 1.000 1.00 10.00
ATOM 4798 CA TRP C 22 1.000 1.000 1.000 1.00 10.00
ATOM 4812 CA GLY C 23 1.000 1.000 1.000 1.00 10.00
ATOM 4816 CA GLN C 24 1.000 1.000 1.000 1.00 10.00
ATOM 4822 CA GLY C 25 1.000 1.000 1.000 1.00 10.00
ATOM 4826 CA THR C 26 1.000 1.000 1.000 1.00 10.00
ATOM 4833 CA LEU C 27 1.000 1.000 1.000 1.00 10.00
ATOM 4841 CA VAL C 28 1.000 1.000 1.000 1.00 10.00
ATOM 4848 CA THR C 29 1.000 1.000 1.000 1.00 10.00
ATOM 4855 CA VAL C 30 1.000 1.000 1.000 1.00 10.00
ATOM 4862 CA SER C 31 1.000 1.000 1.000 1.00 10.00
ATOM 4868 CA SER C 32 1.000 1.000 1.000 1.00 10.00
END
""")
seq = iotbx.bioinformatics.sequence(
"AAAAAAAARGKWESPAALLKKAAWCSGTLVTVSSASAPKWKSTSGCYFAAPWNKRALRVTVLQSS")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,)
out = StringIO()
v.show(out=out)
# all tests below here have additional dependencies
if (not libtbx.env.has_module("ksdssp")) :
print "Skipping advanced tests (require ksdssp module)"
return
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/1ywf.pdb",
test=os.path.isfile)
if (pdb_file is not None) :
seq = iotbx.bioinformatics.sequence("MGSSHHHHHHSSGLVPRGSHMAVRELPGAWNFRDVADTATALRPGRLFRSSELSRLDDAGRATLRRLGITDVADLRSSREVARRGPGRVPDGIDVHLLPFPDLADDDADDSAPHETAFKRLLTNDGSNGESGESSQSINDAATRYMTDEYRQFPTRNGAQRALHRVVTLLAAGRPVLTHCFAGKDRTGFVVALVLEAVGLDRDVIVADYLRSNDSVPQLRARISEMIQQRFDTELAPEVVTFTKARLSDGVLGVRAEYLAAARQTIDETYGSLGGYLRDAGISQATVNRMRGVLLG")
pdb_in = file_reader.any_file(pdb_file, force_type="pdb")
hierarchy = pdb_in.file_object.hierarchy
v = validation(
pdb_hierarchy=hierarchy,
sequences=[seq],
log=null_out(),
nproc=1,
include_secondary_structure=True,
extract_coordinates=True)
out = StringIO()
v.show(out=out)
aln1, aln2, ss = v.chains[0].get_alignment(include_sec_str=True)
assert ("HHH" in ss) and ("LLL" in ss) and ("---" in ss)
cif_block = v.as_cif_block()
assert cif_block['_struct_ref.pdbx_seq_one_letter_code'] == seq.sequence
assert list(
cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg']) == ['4', '117']
assert list(
cif_block['_struct_ref_seq.pdbx_auth_seq_align_end']) == ['85', '275']
assert list(cif_block['_struct_ref_seq.seq_align_beg']) == ['1', '114']
assert list(cif_block['_struct_ref_seq.seq_align_end']) == ['82', '272']
# determine relative counts of sequences and chains
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=4,
out=null_out())
assert (n_seq == 1)
hierarchy = hierarchy.deep_copy()
chain2 = hierarchy.only_model().chains()[0].detached_copy()
hierarchy.only_model().append_chain(chain2)
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=2,
out=null_out())
assert (n_seq == 1)
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq],
copies_from_xtriage=2,
out=null_out())
assert (n_seq == 4)
try :
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq] * 3,
copies_from_xtriage=2,
out=null_out())
except Sorry, s :
assert ("round number" in str(s))
else :
raise Exception_expected
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq] * 3,
copies_from_xtriage=2,
force_accept_composition=True,
out=null_out())
assert (n_seq == 1)
try :
n_seq = get_sequence_n_copies(
pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=1,
out=null_out())
except Sorry, s :
assert ("less than" in str(s))
def show_pickled_object_sizes (result) : result_pkl = dumps(result) print "result", len(result_pkl) show_pickle_sizes(result, " ")
def exercise_simple():
# extracted from 1lyz, with hydrogens from reduce
pdb_in = """
ATOM 1 N LYS A 1 3.296 9.888 10.739 1.00 7.00 N
ATOM 2 CA LYS A 1 2.439 10.217 9.791 1.00 6.00 C
ATOM 3 C LYS A 1 2.439 11.997 9.160 1.00 6.00 C
ATOM 4 O LYS A 1 2.637 12.656 10.107 1.00 8.00 O
ATOM 5 CB LYS A 1 0.659 10.086 8.844 1.00 6.00 C
ATOM 6 CG LYS A 1 0.198 10.415 8.086 1.00 6.00 C
ATOM 7 CD LYS A 1 -1.187 10.086 8.212 1.00 6.00 C
ATOM 8 CE LYS A 1 -2.175 10.086 7.264 1.00 6.00 C
ATOM 9 NZ LYS A 1 -3.527 9.869 7.288 1.00 7.00 N
ATOM 0 H1 LYS A 1 3.156 9.045 10.986 1.00 7.00 H
ATOM 0 H2 LYS A 1 4.127 9.972 10.431 1.00 7.00 H
ATOM 0 H3 LYS A 1 3.184 10.425 11.440 1.00 7.00 H
ATOM 0 HA LYS A 1 2.772 9.314 9.912 1.00 6.00 H
ATOM 0 HB2 LYS A 1 0.584 9.128 8.712 1.00 6.00 H
ATOM 0 HB3 LYS A 1 0.046 10.323 9.557 1.00 6.00 H
ATOM 0 HG2 LYS A 1 0.310 11.376 8.015 1.00 6.00 H
ATOM 0 HG3 LYS A 1 0.563 10.027 7.276 1.00 6.00 H
ATOM 0 HD2 LYS A 1 -1.193 9.186 8.573 1.00 6.00 H
ATOM 0 HD3 LYS A 1 -1.516 10.674 8.910 1.00 6.00 H
ATOM 0 HE2 LYS A 1 -2.097 10.964 6.860 1.00 6.00 H
ATOM 0 HE3 LYS A 1 -1.857 9.444 6.610 1.00 6.00 H
ATOM 0 HZ1 LYS A 1 -3.725 9.170 6.774 1.00 7.00 H
ATOM 0 HZ2 LYS A 1 -3.787 9.706 8.123 1.00 7.00 H
ATOM 0 HZ3 LYS A 1 -3.949 10.590 6.982 1.00 7.00 H
ATOM 10 N VAL A 2 2.637 12.722 7.707 1.00 7.00 N
ATOM 11 CA VAL A 2 2.307 14.172 7.580 1.00 6.00 C
ATOM 12 C VAL A 2 0.857 14.041 6.949 1.00 6.00 C
ATOM 13 O VAL A 2 0.659 13.843 5.875 1.00 8.00 O
ATOM 14 CB VAL A 2 3.625 14.172 6.759 1.00 6.00 C
ATOM 15 CG1 VAL A 2 3.494 15.491 6.317 1.00 6.00 C
ATOM 16 CG2 VAL A 2 4.746 13.843 7.580 1.00 6.00 C
ATOM 0 H VAL A 2 2.920 12.338 6.992 1.00 7.00 H
ATOM 0 HA VAL A 2 2.195 14.925 8.181 1.00 6.00 H
ATOM 0 HB VAL A 2 3.767 13.528 6.048 1.00 6.00 H
ATOM 0 HG11 VAL A 2 4.250 15.721 5.755 1.00 6.00 H
ATOM 0 HG12 VAL A 2 2.674 15.582 5.808 1.00 6.00 H
ATOM 0 HG13 VAL A 2 3.467 16.087 7.081 1.00 6.00 H
ATOM 0 HG21 VAL A 2 5.554 13.850 7.043 1.00 6.00 H
ATOM 0 HG22 VAL A 2 4.827 14.495 8.294 1.00 6.00 H
ATOM 0 HG23 VAL A 2 4.620 12.960 7.962 1.00 6.00 H
END
"""
pdb_file = "tst_validate_restraints_simple.pdb"
open(pdb_file, "w").write(pdb_in)
v1 = run_validation(pdb_file, ignore_hd=True)
out1 = StringIO()
v1.show(out=out1)
assert ("""
----------Chiral volumes----------
atoms ideal model delta sigma residual deviation
A 1 LYS CA
A 1 LYS N
A 1 LYS C
A 1 LYS CB 2.57 1.12 1.45 2.00e-01 5.25e+01 7.2*sigma
""" in "\n".join([l.rstrip() for l in out1.getvalue().splitlines()]))
s = easy_pickle.dumps(v1)
v1p = easy_pickle.loads(s)
out1p = StringIO()
v1p.show(out=out1p)
assert (out1.getvalue() == out1p.getvalue())
v2 = run_validation(pdb_file, ignore_hd=False)
out2 = StringIO()
v2.show(out=out2)
assert (out2.getvalue() != out1.getvalue())
assert ("""\
A 1 LYS HA 110.00 57.00 53.00 3.00e+00 3.12e+02 17.7*sigma
A 1 LYS N
A 1 LYS CA
""" in "\n".join([l.rstrip() for l in out2.getvalue().splitlines()]))
#
# C-alpha-only model (from 3b5d)
pdb_raw = """\
CRYST1 115.100 43.700 76.400 90.00 108.10 90.00 C 1 2 1 8
ATOM 1 CA TYR A 6 -7.551 -11.355 -17.946 1.00148.04 C
ATOM 2 CA LEU A 7 -8.052 -8.804 -20.730 1.00310.75 C
ATOM 3 CA GLY A 8 -10.874 -6.691 -19.353 1.00158.95 C
ATOM 4 CA GLY A 9 -9.359 -7.332 -15.966 1.00217.68 C
ATOM 5 CA ALA A 10 -5.806 -6.508 -16.946 1.00239.12 C
ATOM 6 CA ILE A 11 -7.024 -3.514 -18.905 1.00103.16 C
ATOM 7 CA LEU A 12 -10.023 -2.071 -17.056 1.00230.80 C
ATOM 8 CA ALA A 13 -7.313 -1.820 -14.420 1.00141.04 C
"""
pdb_file = "tst_validate_restraints_calpha.pdb"
open(pdb_file, "w").write(pdb_raw)
v1 = run_validation(pdb_file, ignore_hd=True)
def copy(self, preserve_changes=True):
if preserve_changes:
return easy_pickle.loads(easy_pickle.dumps(self))
else:
return self.copy_master()
def test_multi_axis_goniometer():
from libtbx.test_utils import approx_equal
from scitbx.array_family import flex
alpha = 50
omega = -10
kappa = 30
phi = 20
direction = '-y'
from dxtbx.model.goniometer import KappaGoniometer
kappa_omega_scan = KappaGoniometer(
alpha, omega, kappa, phi, direction, 'omega')
axes = (kappa_omega_scan.get_phi_axis(), kappa_omega_scan.get_kappa_axis(),
kappa_omega_scan.get_omega_axis())
angles = (kappa_omega_scan.get_phi_angle(), kappa_omega_scan.get_kappa_angle(),
kappa_omega_scan.get_omega_angle())
# First test a kappa goniometer with omega as the scan axis
axes = flex.vec3_double(axes)
angles = flex.double(angles)
names = flex.std_string(('phi', 'kappa', 'omega'))
scan_axis = 2
multi_axis_omega_scan = goniometer_factory.multi_axis(
axes, angles, names, scan_axis)
assert approx_equal(multi_axis_omega_scan.get_fixed_rotation(), kappa_omega_scan.get_fixed_rotation())
assert approx_equal(multi_axis_omega_scan.get_rotation_axis(), kappa_omega_scan.get_rotation_axis())
recycle_omega = MultiAxisGoniometer.from_dict(multi_axis_omega_scan.to_dict())
assert approx_equal(recycle_omega.get_axes(), multi_axis_omega_scan.get_axes())
assert approx_equal(recycle_omega.get_angles(), multi_axis_omega_scan.get_angles())
assert recycle_omega.get_scan_axis() == multi_axis_omega_scan.get_scan_axis()
# Now test a kappa goniometer with phi as the scan axis
kappa_phi_scan = KappaGoniometer(
alpha, omega, kappa, phi, direction, 'phi')
scan_axis = 0
multi_axis_phi_scan = goniometer_factory.multi_axis(
axes, angles, names, scan_axis)
assert approx_equal(multi_axis_phi_scan.get_fixed_rotation(), kappa_phi_scan.get_fixed_rotation())
from scitbx import matrix
assert approx_equal(matrix.sqr(multi_axis_phi_scan.get_setting_rotation()) * multi_axis_phi_scan.get_rotation_axis(), kappa_phi_scan.get_rotation_axis())
recycle_phi = MultiAxisGoniometer.from_dict(multi_axis_phi_scan.to_dict())
assert approx_equal(recycle_phi.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle_phi.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle_phi.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
s = easy_pickle.dumps(multi_axis_phi_scan)
recycle = easy_pickle.loads(s)
assert recycle == multi_axis_phi_scan
assert approx_equal(recycle.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
recycle.set_angles((0,90,180))
assert approx_equal(recycle.get_angles(), (0, 90, 180))
new_axes = (0.9, 0.1, 0.0), (0.6427876096865394, -0.766044443118978, 0.0), (1.0, 0.0, 0.0)
new_axes = flex.vec3_double(
((0.99996, -0.00647, -0.00659), (0.91314, 0.27949, -0.29674),
(1.00000, -0.00013, -0.00064)))
recycle.set_axes(new_axes)
assert approx_equal(recycle.get_axes(), new_axes)
# Check exception is raised if scan axis is out range
try: goniometer_factory.multi_axis(axes, angles, names, 3)
except RuntimeError, e: pass
else: raise Exception_expected
# Single axis is just a special case of a multi axis goniometer
single_axis = goniometer_factory.multi_axis(
flex.vec3_double(((1,0,0),)), flex.double((0,)), flex.std_string(('PHI',)), 0)
assert single_axis.get_fixed_rotation() == (1,0,0,0,1,0,0,0,1)
assert single_axis.get_setting_rotation() == (1,0,0,0,1,0,0,0,1)
assert single_axis.get_rotation_axis() == (1,0,0)
print 'OK'
def test_multi_axis_goniometer():
from libtbx.test_utils import approx_equal
from scitbx.array_family import flex
alpha = 50
omega = -10
kappa = 30
phi = 20
direction = '-y'
from dxtbx.model.goniometer import KappaGoniometer
kappa_omega_scan = KappaGoniometer(alpha, omega, kappa, phi, direction,
'omega')
axes = (kappa_omega_scan.get_phi_axis(), kappa_omega_scan.get_kappa_axis(),
kappa_omega_scan.get_omega_axis())
angles = (kappa_omega_scan.get_phi_angle(),
kappa_omega_scan.get_kappa_angle(),
kappa_omega_scan.get_omega_angle())
# First test a kappa goniometer with omega as the scan axis
axes = flex.vec3_double(axes)
angles = flex.double(angles)
names = flex.std_string(('phi', 'kappa', 'omega'))
scan_axis = 2
multi_axis_omega_scan = goniometer_factory.multi_axis(
axes, angles, names, scan_axis)
assert approx_equal(multi_axis_omega_scan.get_fixed_rotation(),
kappa_omega_scan.get_fixed_rotation())
assert approx_equal(multi_axis_omega_scan.get_rotation_axis(),
kappa_omega_scan.get_rotation_axis())
recycle_omega = MultiAxisGoniometer.from_dict(
multi_axis_omega_scan.to_dict())
assert approx_equal(recycle_omega.get_axes(),
multi_axis_omega_scan.get_axes())
assert approx_equal(recycle_omega.get_angles(),
multi_axis_omega_scan.get_angles())
assert recycle_omega.get_scan_axis(
) == multi_axis_omega_scan.get_scan_axis()
# Now test a kappa goniometer with phi as the scan axis
kappa_phi_scan = KappaGoniometer(alpha, omega, kappa, phi, direction,
'phi')
scan_axis = 0
multi_axis_phi_scan = goniometer_factory.multi_axis(
axes, angles, names, scan_axis)
assert approx_equal(multi_axis_phi_scan.get_fixed_rotation(),
kappa_phi_scan.get_fixed_rotation())
from scitbx import matrix
assert approx_equal(
matrix.sqr(multi_axis_phi_scan.get_setting_rotation()) *
multi_axis_phi_scan.get_rotation_axis_datum(),
kappa_phi_scan.get_rotation_axis())
assert approx_equal(multi_axis_phi_scan.get_rotation_axis(),
kappa_phi_scan.get_rotation_axis())
recycle_phi = MultiAxisGoniometer.from_dict(multi_axis_phi_scan.to_dict())
assert approx_equal(recycle_phi.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle_phi.get_angles(),
multi_axis_phi_scan.get_angles())
assert recycle_phi.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
s = easy_pickle.dumps(multi_axis_phi_scan)
recycle = easy_pickle.loads(s)
assert recycle == multi_axis_phi_scan
assert approx_equal(recycle.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
recycle.set_angles((0, 90, 180))
assert approx_equal(recycle.get_angles(), (0, 90, 180))
new_axes = (0.9, 0.1, 0.0), (0.6427876096865394, -0.766044443118978,
0.0), (1.0, 0.0, 0.0)
new_axes = flex.vec3_double(
((0.99996, -0.00647, -0.00659), (0.91314, 0.27949, -0.29674),
(1.00000, -0.00013, -0.00064)))
recycle.set_axes(new_axes)
assert approx_equal(recycle.get_axes(), new_axes)
# Check exception is raised if scan axis is out range
try:
goniometer_factory.multi_axis(axes, angles, names, 3)
except RuntimeError, e:
pass
def test_goniometer():
'''A test class for the goniometer class.'''
axis = (1, 0, 0)
fixed = (1, 0, 0, 0, 1, 0, 0, 0, 1)
xg = Goniometer(axis, fixed)
assert(len(xg.get_rotation_axis()) == 3)
assert(len(xg.get_fixed_rotation()) == 9)
assert(compare_tuples(xg.get_rotation_axis(), axis))
assert(compare_tuples(xg.get_fixed_rotation(), fixed))
single = goniometer_factory.single_axis()
assert(len(single.get_rotation_axis()) == 3)
assert(len(single.get_fixed_rotation()) == 9)
assert(compare_tuples(single.get_rotation_axis(), axis))
assert(compare_tuples(single.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'omega')
assert(len(kappa.get_rotation_axis()) == 3)
assert(len(kappa.get_fixed_rotation()) == 9)
assert(compare_tuples(kappa.get_rotation_axis(), axis))
assert(compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'omega')
assert(len(kappa.get_rotation_axis()) == 3)
assert(len(kappa.get_fixed_rotation()) == 9)
assert(compare_tuples(kappa.get_rotation_axis(), axis))
assert(compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 0.0, 0.0, '-y', 'phi')
assert(len(kappa.get_rotation_axis()) == 3)
assert(len(kappa.get_fixed_rotation()) == 9)
assert(compare_tuples(kappa.get_rotation_axis(), axis))
assert(compare_tuples(kappa.get_fixed_rotation(), fixed))
kappa = goniometer_factory.kappa(50.0, 0.0, 30.0, 0.0, '-y', 'omega')
assert(len(kappa.get_rotation_axis()) == 3)
assert(len(kappa.get_fixed_rotation()) == 9)
assert(compare_tuples(kappa.get_rotation_axis(), axis))
assert(not compare_tuples(kappa.get_fixed_rotation(), fixed))
import libtbx.load_env
import os
dxtbx_dir = libtbx.env.dist_path('dxtbx')
image = os.path.join(dxtbx_dir, 'tests', 'phi_scan_001.cbf')
cbf = goniometer_factory.imgCIF(image)
kappa = goniometer_factory.kappa(50.0, -10.0, 30.0, 0.0, '-y', 'phi')
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
image = os.path.join(dxtbx_dir, 'tests', 'omega_scan.cbf')
cbf = goniometer_factory.imgCIF(image)
kappa = goniometer_factory.kappa(50.0, -10.0, 30.0, 20.0, '-y', 'omega')
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
print 'OK'
def exercise():
import libtbx.utils
if (libtbx.utils.detect_multiprocessing_problem() is not None):
print "multiprocessing not available, skipping this test"
return
if (os.name == "nt"):
print "easy_mp fixed_func not supported under Windows, skipping this test"
return
from mmtbx.validation.sequence import validation, get_sequence_n_copies, \
get_sequence_n_copies_from_files
import iotbx.bioinformatics
import iotbx.pdb
from iotbx import file_reader
import libtbx.load_env # import dependency
from libtbx.test_utils import Exception_expected, contains_lines, approx_equal
from cStringIO import StringIO
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2 CA ARG A 10 -6.299 36.344 7.806 1.00 55.20 C
ATOM 25 CA TYR A 11 -3.391 33.962 7.211 1.00 40.56 C
ATOM 46 CA ALA A 12 -0.693 34.802 4.693 1.00 67.95 C
ATOM 56 CA ALA A 13 0.811 31.422 3.858 1.00 57.97 C
ATOM 66 CA GLY A 14 4.466 31.094 2.905 1.00 49.24 C
ATOM 73 CA ALA A 15 7.163 28.421 2.671 1.00 54.70 C
ATOM 83 CA ILE A 16 6.554 24.685 2.957 1.00 51.79 C
ATOM 102 CA LEU A 17 7.691 23.612 6.406 1.00 42.30 C
ATOM 121 CA PTY A 18 7.292 19.882 5.861 1.00 36.68 C
ATOM 128 CA PHE A 19 5.417 16.968 4.327 1.00 44.99 C
ATOM 148 CA GLY A 20 3.466 14.289 6.150 1.00 41.99 C
ATOM 155 CA GLY A 21 1.756 11.130 4.965 1.00 35.77 C
ATOM 190 CA ALA A 24 1.294 19.658 3.683 1.00 47.02 C
ATOM 200 CA VAL A 24A 2.361 22.009 6.464 1.00 37.13 C
ATOM 216 CA HIS A 25 2.980 25.633 5.535 1.00 42.52 C
ATOM 234 CA LEU A 26 4.518 28.425 7.577 1.00 47.63 C
ATOM 253 CA ALA A 27 2.095 31.320 7.634 1.00 38.61 C
ATOM 263 CA ARG A 28 1.589 34.719 9.165 1.00 37.04 C
END""")
seq1 = iotbx.bioinformatics.sequence(
"MTTPSHLSDRYELGEILGFGGMSEVHLARD".lower())
v = validation(pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq1],
log=null_out(),
nproc=1)
out = StringIO()
v.show(out=out)
assert contains_lines(
out.getvalue(), """\
sequence identity: 76.47%
13 residue(s) missing from PDB chain (9 at start, 1 at end)
2 gap(s) in chain
4 mismatches to sequence
residue IDs: 12 13 15 24""")
cif_block = v.as_cif_block()
assert list(cif_block['_struct_ref.pdbx_seq_one_letter_code']) == [
'MTTPSHLSDRYELGEILGFGGMSEVHLARD'
]
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg'],
['10', '14', '16', '19', '24'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '21', '28'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_beg'],
['10', '14', '16', '19', '25'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_end'],
['11', '14', '17', '21', '29'])
assert cif_block['_struct_ref_seq.pdbx_seq_align_beg_ins_code'][4] == 'A'
seq2 = iotbx.bioinformatics.sequence("MTTPSHLSDRYELGEILGFGGMSEVHLA")
v = validation(pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq2],
log=null_out(),
nproc=1)
out = StringIO()
v.show(out=out)
assert contains_lines(
out.getvalue(), """\
1 residues not found in sequence
residue IDs: 28""")
try:
v = validation(pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[],
log=null_out(),
nproc=1)
except AssertionError:
pass
else:
raise Exception_expected
cif_block = v.as_cif_block()
assert list(cif_block['_struct_ref.pdbx_seq_one_letter_code']) == [
'MTTPSHLSDRYELGEILGFGGMSEVHLA-'
]
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '21', '27'])
assert approx_equal(cif_block['_struct_ref_seq.db_align_end'],
['11', '14', '17', '21', '28'])
#
pdb_in2 = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2 CA ARG A 10 -6.299 36.344 7.806 1.00 55.20 C
ATOM 25 CA TYR A 11 -3.391 33.962 7.211 1.00 40.56 C
ATOM 46 CA ALA A 12 -0.693 34.802 4.693 1.00 67.95 C
ATOM 56 CA ALA A 13 0.811 31.422 3.858 1.00 57.97 C
ATOM 66 CA GLY A 14 4.466 31.094 2.905 1.00 49.24 C
ATOM 73 CA ALA A 15 7.163 28.421 2.671 1.00 54.70 C
ATOM 83 CA ILE A 16 6.554 24.685 2.957 1.00 51.79 C
ATOM 102 CA LEU A 17 7.691 23.612 6.406 1.00 42.30 C
TER
ATOM 1936 P G B 2 -22.947 -23.615 15.323 1.00123.20 P
ATOM 1959 P C B 3 -26.398 -26.111 19.062 1.00110.06 P
ATOM 1979 P U B 4 -29.512 -30.638 21.164 1.00101.06 P
ATOM 1999 P C B 5 -30.524 -36.109 21.527 1.00 92.76 P
ATOM 2019 P U B 6 -28.684 -41.458 21.223 1.00 87.42 P
ATOM 2062 P G B 8 -18.396 -45.415 21.903 1.00 80.35 P
ATOM 2085 P A B 9 -13.852 -43.272 24.156 1.00 77.76 P
ATOM 2107 P G B 10 -8.285 -44.242 26.815 1.00 79.86 P
END
""")
seq3 = iotbx.bioinformatics.sequence("AGCUUUGGAG")
v = validation(pdb_hierarchy=pdb_in2.construct_hierarchy(),
sequences=[seq2, seq3],
log=null_out(),
nproc=1,
extract_coordinates=True)
out = StringIO()
v.show(out=out)
cif_block = v.as_cif_block()
assert approx_equal(cif_block['_struct_ref.pdbx_seq_one_letter_code'],
['MTTPSHLSDRYELGEILGFGGMSEVHLA', 'AGCUUUGGAG'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg'],
['10', '14', '16', '2', '6', '8'])
assert approx_equal(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end'],
['11', '14', '17', '4', '6', '10'])
assert (len(v.chains[0].get_outliers_table()) == 3)
assert (len(v.get_table_data()) == 4)
assert approx_equal(
v.chains[0].get_mean_coordinate_for_alignment_range(11, 11),
(-0.693, 34.802, 4.693))
assert approx_equal(
v.chains[0].get_mean_coordinate_for_alignment_range(11, 14),
(2.93675, 31.43475, 3.53175))
assert (v.chains[0].get_highlighted_residues() == [11, 12, 14])
assert contains_lines(
out.getvalue(), """\
3 mismatches to sequence
residue IDs: 12 13 15""")
assert contains_lines(
out.getvalue(), """\
sequence identity: 87.50%
2 residue(s) missing from PDB chain (1 at start, 0 at end)
1 gap(s) in chain
1 mismatches to sequence
residue IDs: 5""")
s = easy_pickle.dumps(v)
seq4 = iotbx.bioinformatics.sequence("")
try:
v = validation(pdb_hierarchy=pdb_in2.construct_hierarchy(),
sequences=[seq4],
log=null_out(),
nproc=1,
extract_coordinates=True)
except AssertionError:
pass
else:
raise Exception_expected
# check that nucleic acid chain doesn't get aligned against protein sequence
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 18932 P B DG D 1 -12.183 60.531 25.090 0.50364.79 P
ATOM 18963 P B DG D 2 -9.738 55.258 20.689 0.50278.77 P
ATOM 18994 P B DA D 3 -10.119 47.855 19.481 0.50355.17 P
ATOM 19025 P B DT D 4 -13.664 42.707 21.119 0.50237.06 P
ATOM 19056 P B DG D 5 -19.510 39.821 21.770 0.50255.45 P
ATOM 19088 P B DA D 6 -26.096 40.001 21.038 0.50437.49 P
ATOM 19120 P B DC D 7 -31.790 41.189 18.413 0.50210.00 P
ATOM 19149 P B DG D 8 -34.639 41.306 12.582 0.50313.99 P
ATOM 19179 P B DA D 9 -34.987 38.244 6.813 0.50158.92 P
ATOM 19210 P B DT D 10 -32.560 35.160 1.082 0.50181.38 P
HETATM19241 P BTSP D 11 -27.614 30.137 0.455 0.50508.17 P
""")
sequences, _ = iotbx.bioinformatics.fasta_sequence_parse.parse(
""">4GFH:A|PDBID|CHAIN|SEQUENCE
MSTEPVSASDKYQKISQLEHILKRPDTYIGSVETQEQLQWIYDEETDCMIEKNVTIVPGLFKIFDEILVNAADNKVRDPS
MKRIDVNIHAEEHTIEVKNDGKGIPIEIHNKENIYIPEMIFGHLLTSSNYDDDEKKVTGGRNGYGAKLCNIFSTEFILET
ADLNVGQKYVQKWENNMSICHPPKITSYKKGPSYTKVTFKPDLTRFGMKELDNDILGVMRRRVYDINGSVRDINVYLNGK
SLKIRNFKNYVELYLKSLEKKRQLDNGEDGAAKSDIPTILYERINNRWEVAFAVSDISFQQISFVNSIATTMGGTHVNYI
TDQIVKKISEILKKKKKKSVKSFQIKNNMFIFINCLIENPAFTSQTKEQLTTRVKDFGSRCEIPLEYINKIMKTDLATRM
FEIADANEENALKKSDGTRKSRITNYPKLEDANKAGTKEGYKCTLVLTEGDSALSLAVAGLAVVGRDYYGCYPLRGKMLN
VREASADQILKNAEIQAIKKIMGLQHRKKYEDTKSLRYGHLMIMTDQDHDGSHIKGLIINFLESSFPGLLDIQGFLLEFI
TPIIKVSITKPTKNTIAFYNMPDYEKWREEESHKFTWKQKYYKGLGTSLAQEVREYFSNLDRHLKIFHSLQGNDKDYIDL
AFSKKKADDRKEWLRQYEPGTVLDPTLKEIPISDFINKELILFSLADNIRSIPNVLDGFKPGQRKVLYGCFKKNLKSELK
VAQLAPYVSECTAYHHGEQSLAQTIIGLAQNFVGSNNIYLLLPNGAFGTRATGGKDAAAARYIYTELNKLTRKIFHPADD
PLYKYIQEDEKTVEPEWYLPILPMILVNGAEGIGTGWSTYIPPFNPLEIIKNIRHLMNDEELEQMHPWFRGWTGTIEEIE
PLRYRMYGRIEQIGDNVLEITELPARTWTSTIKEYLLLGLSGNDKIKPWIKDMEEQHDDNIKFIITLSPEEMAKTRKIGF
YERFKLISPISLMNMVAFDPHGKIKKYNSVNEILSEFYYVRLEYYQKRKDHMSERLQWEVEKYSFQVKFIKMIIEKELTV
TNKPRNAIIQELENLGFPRFNKEGKPYYGSPNDEIAEQINDVKGATSDEEDEESSHEDTENVINGPEELYGTYEYLLGMR
IWSLTKERYQKLLKQKQEKETELENLLKLSAKDIWNTDLKAFEVGYQEFLQRDAEAR
>4GFH:D|PDBID|CHAIN|SEQUENCE
GGATGACGATX
""")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=sequences,
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing == 0
assert v.chains[0].n_missing_end == 0
assert v.chains[0].n_missing_start == 0
assert len(v.chains[0].alignment.matches()) == 11
#
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2 CA GLY A 1 1.367 0.551 0.300 1.00 7.71 C
ATOM 6 CA CYS A 2 2.782 3.785 1.683 1.00 5.18 C
ATOM 12 CA CYS A 3 -0.375 5.128 3.282 1.00 5.21 C
ATOM 18 CA SER A 4 -0.870 2.048 5.492 1.00 7.19 C
ATOM 25 CA LEU A 5 2.786 2.056 6.642 1.00 6.78 C
ATOM 33 CA PRO A 6 3.212 4.746 9.312 1.00 7.03 C
ATOM 40 CA PRO A 7 6.870 5.690 8.552 1.00 7.97 C
ATOM 47 CA CYS A 8 6.021 6.070 4.855 1.00 6.48 C
ATOM 53 CA ALA A 9 2.812 8.041 5.452 1.00 7.15 C
ATOM 58 CA LEU A 10 4.739 10.382 7.748 1.00 8.36 C
ATOM 66 CA SER A 11 7.292 11.200 5.016 1.00 7.00 C
ATOM 73 CA ASN A 12 4.649 11.435 2.264 1.00 5.40 C
ATOM 81 CA PRO A 13 1.879 13.433 3.968 1.00 5.97 C
ATOM 88 CA ASP A 14 0.485 15.371 0.986 1.00 7.70 C
ATOM 96 CA TYR A 15 0.565 12.245 -1.180 1.00 6.55 C
ATOM 108 CA CYS A 16 -1.466 10.260 1.363 1.00 7.32 C
ATOM 113 N NH2 A 17 -2.612 12.308 2.058 1.00 8.11 N
""")
seq = iotbx.bioinformatics.sequence("GCCSLPPCALSNPDYCX")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing == 0
assert v.chains[0].n_missing_end == 0
assert v.chains[0].n_missing_start == 0
assert len(v.chains[0].alignment.matches()) == 17
#
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2518 CA PRO C 3 23.450 -5.848 45.723 1.00 85.24 C
ATOM 2525 CA GLY C 4 20.066 -4.416 44.815 1.00 79.25 C
ATOM 2529 CA PHE C 5 19.408 -0.913 46.032 1.00 77.13 C
ATOM 2540 CA GLY C 6 17.384 -1.466 49.208 1.00 83.44 C
ATOM 2544 CA GLN C 7 17.316 -5.259 49.606 1.00 89.25 C
ATOM 2553 CA GLY C 8 19.061 -6.829 52.657 1.00 90.67 C
""")
sequences, _ = iotbx.bioinformatics.fasta_sequence_parse.parse(
""">1JN5:A|PDBID|CHAIN|SEQUENCE
MASVDFKTYVDQACRAAEEFVNVYYTTMDKRRRLLSRLYMGTATLVWNGNAVSGQESLSEFFEMLPSSEFQISVVDCQPV
HDEATPSQTTVLVVICGSVKFEGNKQRDFNQNFILTAQASPSNTVWKIASDCFRFQDWAS
>1JN5:B|PDBID|CHAIN|SEQUENCE
APPCKGSYFGTENLKSLVLHFLQQYYAIYDSGDRQGLLDAYHDGACCSLSIPFIPQNPARSSLAEYFKDSRNVKKLKDPT
LRFRLLKHTRLNVVAFLNELPKTQHDVNSFVVDISAQTSTLLCFSVNGVFKEVDGKSRDSLRAFTRTFIAVPASNSGLCI
VNDELFVRNASSEEIQRAFAMPAPTPSSSPVPTLSPEQQEMLQAFSTQSGMNLEWSQKCLQDNNWDYTRSAQAFTHLKAK
GEIPEVAFMK
>1JN5:C|PDBID|CHAIN|SEQUENCE
GQSPGFGQGGSV
""")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=sequences,
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 3
assert v.chains[0].n_missing_end == 3
assert v.chains[0].identity == 1.0
assert v.chains[0].alignment.match_codes == 'iiimmmmmmiii'
#
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2 CA ALA A 2 -8.453 57.214 -12.754 1.00 52.95 C
ATOM 7 CA LEU A 3 -8.574 59.274 -9.471 1.00 24.33 C
ATOM 15 CA ARG A 4 -12.178 60.092 -8.575 1.00 28.40 C
ATOM 26 CA GLY A 5 -14.170 61.485 -5.667 1.00 26.54 C
ATOM 30 CA THR A 6 -17.784 60.743 -4.783 1.00 31.78 C
ATOM 37 CA VAL A 7 -19.080 64.405 -4.464 1.00 21.31 C
""")
seq = iotbx.bioinformatics.sequence("XALRGTV")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 1
assert v.chains[0].n_missing_end == 0
assert v.chains[0].identity == 1.0
assert v.chains[0].alignment.match_codes == 'immmmmm'
#
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 2171 CA ASP I 355 5.591 -11.903 1.133 1.00 41.60 C
ATOM 2175 CA PHE I 356 7.082 -8.454 0.828 1.00 39.82 C
ATOM 2186 CA GLU I 357 5.814 -6.112 -1.877 1.00 41.12 C
ATOM 2195 CA GLU I 358 8.623 -5.111 -4.219 1.00 42.70 C
ATOM 2199 CA ILE I 359 10.346 -1.867 -3.363 1.00 43.32 C
ATOM 2207 CA PRO I 360 11.658 0.659 -5.880 1.00 44.86 C
ATOM 2214 CA GLU I 361 14.921 -0.125 -7.592 1.00 44.32 C
ATOM 2219 CA GLU I 362 15.848 3.489 -6.866 1.00 44.27 C
HETATM 2224 CA TYS I 363 16.482 2.005 -3.448 1.00 44.52 C
""")
seq = iotbx.bioinformatics.sequence("NGDFEEIPEEYL")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].n_missing_start == 2
assert v.chains[0].n_missing_end == 1
assert v.chains[0].identity == 1.0
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 450 CA ASN A 1 37.242 41.665 44.160 1.00 35.89 C
ATOM 458 CA GLY A 2 37.796 38.269 42.523 1.00 30.13 C
HETATM 463 CA AMSE A 3 35.878 39.005 39.326 0.54 22.83 C
HETATM 464 CA BMSE A 3 35.892 39.018 39.323 0.46 22.96 C
ATOM 478 CA ILE A 4 37.580 38.048 36.061 1.00 22.00 C
ATOM 486 CA SER A 5 37.593 40.843 33.476 1.00 18.73 C
ATOM 819 CA ALA A 8 25.982 34.781 27.220 1.00 18.43 C
ATOM 824 CA ALA A 9 23.292 32.475 28.614 1.00 19.60 C
HETATM 830 CA BMSE A 10 22.793 30.814 25.223 0.41 22.60 C
HETATM 831 CA CMSE A 10 22.801 30.850 25.208 0.59 22.54 C
ATOM 845 CA GLU A 11 26.504 30.054 24.966 1.00 25.19 C
ATOM 854 CA GLY A 12 25.907 28.394 28.320 1.00 38.88 C
""")
seq = iotbx.bioinformatics.sequence("NGMISAAAAMEG")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
assert v.chains[0].alignment.a == 'NGMISXXAAMEG'
assert v.chains[0].alignment.b == 'NGMISAAAAMEG'
pdb_in = iotbx.pdb.input(source_info=None,
lines="""\
ATOM 4615 CA ALA C 1 1.000 1.000 1.000 1.00 10.00
ATOM 4622 CA ALA C 2 1.000 1.000 1.000 1.00 10.00
ATOM 4627 CA ALA C 3 1.000 1.000 1.000 1.00 10.00
ATOM 4634 CA ALA C 4 1.000 1.000 1.000 1.00 10.00
ATOM 4646 CA ALA C 5 1.000 1.000 1.000 1.00 10.00
ATOM 4658 CA ALA C 6 1.000 1.000 1.000 1.00 10.00
ATOM 4664 CA ALA C 7 1.000 1.000 1.000 1.00 10.00
ATOM 4669 CA ALA C 8 1.000 1.000 1.000 1.00 10.00
ATOM 4680 CA ARG C 9 1.000 1.000 1.000 1.00 10.00
ATOM 4690 CA GLY C 10 1.000 1.000 1.000 1.00 10.00
ATOM 4698 CA PRO C 11 1.000 1.000 1.000 1.00 10.00
ATOM 4705 CA LYS C 12 1.000 1.000 1.000 1.00 10.00
ATOM 4712 CA TRP C 13 1.000 1.000 1.000 1.00 10.00
ATOM 4726 CA GLU C 14 1.000 1.000 1.000 1.00 10.00
ATOM 4738 CA SER C 15 1.000 1.000 1.000 1.00 10.00
ATOM 4744 CA THR C 16 1.000 1.000 1.000 1.00 10.00
ATOM 4751 CA GLY C 17 1.000 1.000 1.000 1.00 10.00
ATOM 4755 CA TYR C 18 1.000 1.000 1.000 1.00 10.00
ATOM 4767 CA PHE C 19 1.000 1.000 1.000 1.00 10.00
ATOM 4778 CA ALA C 20 1.000 1.000 1.000 1.00 10.00
ATOM 4786 CA ALA C 21 1.000 1.000 1.000 1.00 10.00
ATOM 4798 CA TRP C 22 1.000 1.000 1.000 1.00 10.00
ATOM 4812 CA GLY C 23 1.000 1.000 1.000 1.00 10.00
ATOM 4816 CA GLN C 24 1.000 1.000 1.000 1.00 10.00
ATOM 4822 CA GLY C 25 1.000 1.000 1.000 1.00 10.00
ATOM 4826 CA THR C 26 1.000 1.000 1.000 1.00 10.00
ATOM 4833 CA LEU C 27 1.000 1.000 1.000 1.00 10.00
ATOM 4841 CA VAL C 28 1.000 1.000 1.000 1.00 10.00
ATOM 4848 CA THR C 29 1.000 1.000 1.000 1.00 10.00
ATOM 4855 CA VAL C 30 1.000 1.000 1.000 1.00 10.00
ATOM 4862 CA SER C 31 1.000 1.000 1.000 1.00 10.00
ATOM 4868 CA SER C 32 1.000 1.000 1.000 1.00 10.00
END
""")
seq = iotbx.bioinformatics.sequence(
"AAAAAAAARGKWESPAALLKKAAWCSGTLVTVSSASAPKWKSTSGCYFAAPWNKRALRVTVLQSS")
v = validation(
pdb_hierarchy=pdb_in.construct_hierarchy(),
sequences=[seq],
log=null_out(),
nproc=1,
)
out = StringIO()
v.show(out=out)
# all tests below here have additional dependencies
if (not libtbx.env.has_module("ksdssp")):
print "Skipping advanced tests (require ksdssp module)"
return
pdb_file = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/1ywf.pdb", test=os.path.isfile)
if (pdb_file is not None):
seq = iotbx.bioinformatics.sequence(
"MGSSHHHHHHSSGLVPRGSHMAVRELPGAWNFRDVADTATALRPGRLFRSSELSRLDDAGRATLRRLGITDVADLRSSREVARRGPGRVPDGIDVHLLPFPDLADDDADDSAPHETAFKRLLTNDGSNGESGESSQSINDAATRYMTDEYRQFPTRNGAQRALHRVVTLLAAGRPVLTHCFAGKDRTGFVVALVLEAVGLDRDVIVADYLRSNDSVPQLRARISEMIQQRFDTELAPEVVTFTKARLSDGVLGVRAEYLAAARQTIDETYGSLGGYLRDAGISQATVNRMRGVLLG"
)
pdb_in = file_reader.any_file(pdb_file, force_type="pdb")
hierarchy = pdb_in.file_object.hierarchy
v = validation(pdb_hierarchy=hierarchy,
sequences=[seq],
log=null_out(),
nproc=1,
include_secondary_structure=True,
extract_coordinates=True)
out = StringIO()
v.show(out=out)
aln1, aln2, ss = v.chains[0].get_alignment(include_sec_str=True)
assert ("HHH" in ss) and ("LLL" in ss) and ("---" in ss)
cif_block = v.as_cif_block()
assert cif_block[
'_struct_ref.pdbx_seq_one_letter_code'] == seq.sequence
assert list(cif_block['_struct_ref_seq.pdbx_auth_seq_align_beg']) == [
'4', '117'
]
assert list(cif_block['_struct_ref_seq.pdbx_auth_seq_align_end']) == [
'85', '275'
]
assert list(cif_block['_struct_ref_seq.seq_align_beg']) == ['1', '114']
assert list(
cif_block['_struct_ref_seq.seq_align_end']) == ['82', '272']
# determine relative counts of sequences and chains
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=4,
out=null_out())
assert (n_seq == 1)
hierarchy = hierarchy.deep_copy()
chain2 = hierarchy.only_model().chains()[0].detached_copy()
hierarchy.only_model().append_chain(chain2)
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=2,
out=null_out())
assert (n_seq == 1)
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq],
copies_from_xtriage=2,
out=null_out())
assert (n_seq == 4)
try:
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq] * 3,
copies_from_xtriage=2,
out=null_out())
except Sorry, s:
assert ("round number" in str(s))
else:
raise Exception_expected
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq] * 3,
copies_from_xtriage=2,
force_accept_composition=True,
out=null_out())
assert (n_seq == 1)
try:
n_seq = get_sequence_n_copies(pdb_hierarchy=hierarchy,
sequences=[seq] * 4,
copies_from_xtriage=1,
out=null_out())
except Sorry, s:
assert ("less than" in str(s))
def test_goniometer():
"""A test class for the goniometer class."""
axis = (1, 0, 0)
fixed = (1, 0, 0, 0, 1, 0, 0, 0, 1)
xg = Goniometer(axis, fixed)
assert len(xg.get_rotation_axis()) == 3
assert len(xg.get_fixed_rotation()) == 9
_compare_tuples(xg.get_rotation_axis(), axis)
_compare_tuples(xg.get_fixed_rotation(), fixed)
single = GoniometerFactory.single_axis()
assert len(single.get_rotation_axis()) == 3
assert len(single.get_fixed_rotation()) == 9
_compare_tuples(single.get_rotation_axis(), axis)
_compare_tuples(single.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 0.0, 0.0, "-y", "phi")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
_compare_tuples(kappa.get_fixed_rotation(), fixed)
kappa = GoniometerFactory.kappa(50.0, 0.0, 30.0, 0.0, "-y", "omega")
assert len(kappa.get_rotation_axis()) == 3
assert len(kappa.get_fixed_rotation()) == 9
_compare_tuples(kappa.get_rotation_axis(), axis)
with pytest.raises(AssertionError):
_compare_tuples(kappa.get_fixed_rotation(), fixed)
image = Path(__file__).parent / "phi_scan_001.cbf"
assert GoniometerFactory.imgCIF(str(image))
kappa = GoniometerFactory.kappa(50.0, -10.0, 30.0, 0.0, "-y", "phi")
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
image = Path(__file__).parent / "omega_scan.cbf"
assert GoniometerFactory.imgCIF(str(image))
kappa = GoniometerFactory.kappa(50.0, -10.0, 30.0, 20.0, "-y", "omega")
s = easy_pickle.dumps(kappa)
kappa2 = easy_pickle.loads(s)
assert kappa == kappa2
def exercise_simple () :
# extracted from 1lyz, with hydrogens from reduce
pdb_in = """
ATOM 1 N LYS A 1 3.296 9.888 10.739 1.00 7.00 N
ATOM 2 CA LYS A 1 2.439 10.217 9.791 1.00 6.00 C
ATOM 3 C LYS A 1 2.439 11.997 9.160 1.00 6.00 C
ATOM 4 O LYS A 1 2.637 12.656 10.107 1.00 8.00 O
ATOM 5 CB LYS A 1 0.659 10.086 8.844 1.00 6.00 C
ATOM 6 CG LYS A 1 0.198 10.415 8.086 1.00 6.00 C
ATOM 7 CD LYS A 1 -1.187 10.086 8.212 1.00 6.00 C
ATOM 8 CE LYS A 1 -2.175 10.086 7.264 1.00 6.00 C
ATOM 9 NZ LYS A 1 -3.527 9.869 7.288 1.00 7.00 N
ATOM 0 H1 LYS A 1 3.156 9.045 10.986 1.00 7.00 H
ATOM 0 H2 LYS A 1 4.127 9.972 10.431 1.00 7.00 H
ATOM 0 H3 LYS A 1 3.184 10.425 11.440 1.00 7.00 H
ATOM 0 HA LYS A 1 2.772 9.314 9.912 1.00 6.00 H
ATOM 0 HB2 LYS A 1 0.584 9.128 8.712 1.00 6.00 H
ATOM 0 HB3 LYS A 1 0.046 10.323 9.557 1.00 6.00 H
ATOM 0 HG2 LYS A 1 0.310 11.376 8.015 1.00 6.00 H
ATOM 0 HG3 LYS A 1 0.563 10.027 7.276 1.00 6.00 H
ATOM 0 HD2 LYS A 1 -1.193 9.186 8.573 1.00 6.00 H
ATOM 0 HD3 LYS A 1 -1.516 10.674 8.910 1.00 6.00 H
ATOM 0 HE2 LYS A 1 -2.097 10.964 6.860 1.00 6.00 H
ATOM 0 HE3 LYS A 1 -1.857 9.444 6.610 1.00 6.00 H
ATOM 0 HZ1 LYS A 1 -3.725 9.170 6.774 1.00 7.00 H
ATOM 0 HZ2 LYS A 1 -3.787 9.706 8.123 1.00 7.00 H
ATOM 0 HZ3 LYS A 1 -3.949 10.590 6.982 1.00 7.00 H
ATOM 10 N VAL A 2 2.637 12.722 7.707 1.00 7.00 N
ATOM 11 CA VAL A 2 2.307 14.172 7.580 1.00 6.00 C
ATOM 12 C VAL A 2 0.857 14.041 6.949 1.00 6.00 C
ATOM 13 O VAL A 2 0.659 13.843 5.875 1.00 8.00 O
ATOM 14 CB VAL A 2 3.625 14.172 6.759 1.00 6.00 C
ATOM 15 CG1 VAL A 2 3.494 15.491 6.317 1.00 6.00 C
ATOM 16 CG2 VAL A 2 4.746 13.843 7.580 1.00 6.00 C
ATOM 0 H VAL A 2 2.920 12.338 6.992 1.00 7.00 H
ATOM 0 HA VAL A 2 2.195 14.925 8.181 1.00 6.00 H
ATOM 0 HB VAL A 2 3.767 13.528 6.048 1.00 6.00 H
ATOM 0 HG11 VAL A 2 4.250 15.721 5.755 1.00 6.00 H
ATOM 0 HG12 VAL A 2 2.674 15.582 5.808 1.00 6.00 H
ATOM 0 HG13 VAL A 2 3.467 16.087 7.081 1.00 6.00 H
ATOM 0 HG21 VAL A 2 5.554 13.850 7.043 1.00 6.00 H
ATOM 0 HG22 VAL A 2 4.827 14.495 8.294 1.00 6.00 H
ATOM 0 HG23 VAL A 2 4.620 12.960 7.962 1.00 6.00 H
END
"""
pdb_file = "tst_validate_restraints_simple.pdb"
open(pdb_file, "w").write(pdb_in)
v1 = run_validation(pdb_file, ignore_hd=True)
out1 = StringIO()
v1.show(out=out1)
assert ("""
----------Chiral volumes----------
atoms ideal model delta sigma residual deviation
A 1 LYS CA
A 1 LYS N
A 1 LYS C
A 1 LYS CB 2.57 1.12 1.45 2.00e-01 5.25e+01 7.2*sigma
""" in "\n".join([ l.rstrip() for l in out1.getvalue().splitlines() ]))
s = easy_pickle.dumps(v1)
v1p = easy_pickle.loads(s)
out1p = StringIO()
v1p.show(out=out1p)
assert (out1.getvalue() == out1p.getvalue())
v2 = run_validation(pdb_file, ignore_hd=False)
out2 = StringIO()
v2.show(out=out2)
assert (out2.getvalue() != out1.getvalue())
assert ("""\
A 1 LYS HA 110.00 57.00 53.00 3.00e+00 3.12e+02 17.7*sigma
A 2 VAL N
A 2 VAL CA
""" in "\n".join([ l.rstrip() for l in out2.getvalue().splitlines() ]))
#
# C-alpha-only model (from 3b5d)
pdb_raw = """\
CRYST1 115.100 43.700 76.400 90.00 108.10 90.00 C 1 2 1 8
ATOM 1 CA TYR A 6 -7.551 -11.355 -17.946 1.00148.04 C
ATOM 2 CA LEU A 7 -8.052 -8.804 -20.730 1.00310.75 C
ATOM 3 CA GLY A 8 -10.874 -6.691 -19.353 1.00158.95 C
ATOM 4 CA GLY A 9 -9.359 -7.332 -15.966 1.00217.68 C
ATOM 5 CA ALA A 10 -5.806 -6.508 -16.946 1.00239.12 C
ATOM 6 CA ILE A 11 -7.024 -3.514 -18.905 1.00103.16 C
ATOM 7 CA LEU A 12 -10.023 -2.071 -17.056 1.00230.80 C
ATOM 8 CA ALA A 13 -7.313 -1.820 -14.420 1.00141.04 C
"""
pdb_file = "tst_validate_restraints_calpha.pdb"
open(pdb_file, "w").write(pdb_raw)
v1 = run_validation(pdb_file, ignore_hd=True)
def test_multi_axis_goniometer():
from libtbx.test_utils import approx_equal
from scitbx.array_family import flex
alpha = 50
omega = -10
kappa = 30
phi = 20
direction = '-y'
kappa_omega_scan = goniometer_factory.kappa(
alpha, omega, kappa, phi, direction, 'omega')
axes = (kappa_omega_scan.get_phi_axis(), kappa_omega_scan.get_kappa_axis(),
kappa_omega_scan.get_omega_axis())
angles = (kappa_omega_scan.get_phi_angle(), kappa_omega_scan.get_kappa_angle(),
kappa_omega_scan.get_omega_angle())
# First test a kappa goniometer with omega as the scan axis
axes = flex.vec3_double(axes)
angles = flex.double(angles)
scan_axis = 2
multi_axis_omega_scan = goniometer_factory.multi_axis(axes, angles, scan_axis)
assert approx_equal(multi_axis_omega_scan.get_fixed_rotation(), kappa_omega_scan.get_fixed_rotation())
assert approx_equal(multi_axis_omega_scan.get_rotation_axis(), kappa_omega_scan.get_rotation_axis())
recycle_omega = MultiAxisGoniometer.from_dict(multi_axis_omega_scan.to_dict())
assert approx_equal(recycle_omega.get_axes(), multi_axis_omega_scan.get_axes())
assert approx_equal(recycle_omega.get_angles(), multi_axis_omega_scan.get_angles())
assert recycle_omega.get_scan_axis() == multi_axis_omega_scan.get_scan_axis()
# Now test a kappa goniometer with phi as the scan axis
kappa_phi_scan = goniometer_factory.kappa(
alpha, omega, kappa, phi, direction, 'phi')
scan_axis = 0
multi_axis_phi_scan = goniometer_factory.multi_axis(axes, angles, scan_axis)
assert approx_equal(multi_axis_phi_scan.get_fixed_rotation(), kappa_phi_scan.get_fixed_rotation())
assert approx_equal(multi_axis_phi_scan.get_rotation_axis(), kappa_phi_scan.get_rotation_axis())
recycle_phi = MultiAxisGoniometer.from_dict(multi_axis_phi_scan.to_dict())
assert approx_equal(recycle_phi.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle_phi.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle_phi.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
s = easy_pickle.dumps(multi_axis_phi_scan)
recycle = easy_pickle.loads(s)
assert recycle == multi_axis_phi_scan
assert approx_equal(recycle.get_axes(), multi_axis_phi_scan.get_axes())
assert approx_equal(recycle.get_angles(), multi_axis_phi_scan.get_angles())
assert recycle.get_scan_axis() == multi_axis_phi_scan.get_scan_axis()
# Check exception is raised if scan axis is out range
try: goniometer_factory.multi_axis(axes, angles, 3)
except RuntimeError, e: pass
else: raise Exception_expected
# Single axis is just a special case of a multi axis goniometer
single_axis = goniometer_factory.multi_axis(
flex.vec3_double(((1,0,0),)), flex.double((0,)), 0)
assert single_axis.get_fixed_rotation() == (1,0,0,0,1,0,0,0,1)
assert single_axis.get_setting_rotation() == (1,0,0,0,1,0,0,0,1)
assert single_axis.get_rotation_axis() == (1,0,0)
print 'OK'
def exercise_rotalyze():
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/jcm.pdb", test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_rotalyze(): input pdb (jcm.pdb) not available"
return
if (find_rotarama_data_dir(optional=True) is None):
print "Skipping exercise_rotalyze(): rotarama_data directory not available"
return
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
r = rotalyze.rotalyze(pdb_hierarchy=hierarchy, outliers_only=True)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert output.count("OUTLIER") == 246, output.count("OUTLIER")
assert output.count(":") == 984, output.count(":")
output_lines = output.splitlines()
assert len(output_lines) == 123
for lines in output_lines:
assert float(lines[12:15]) <= 1.0
r = rotalyze.rotalyze(pdb_hierarchy=hierarchy, outliers_only=False)
for unpickle in [False, True]:
if unpickle:
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
for outlier in r.results:
assert (len(outlier.xyz) == 3)
output = out.getvalue()
assert output.count("OUTLIER") == 246
assert output.count(":") == 5144, output.count(":")
assert output.count("p") == 120
assert output.count("m") == 324
assert output.count("t") == 486
output_lines = output.splitlines()
#for line in output_lines:
# print line
#STOP()
assert len(output_lines) == 643
line_indices = [0, 1, 2, 42, 43, 168, 169, 450, 587, 394, 641, 642]
# top500 version
line_values = [
" A 14 MET:1.00:3.3:29.2:173.3:287.9::Favored:ptm",
" A 15 SER:1.00:0.1:229.0::::OUTLIER:OUTLIER",
" A 16 SER:1.00:4.2:277.9::::Favored:m",
" A 58 ASN:1.00:2.0:252.4:343.6:::Favored:m-20",
" A 59 ILE:1.00:2.0:84.2:186.7:::Allowed:pt",
" A 202 GLU:1.00:0.4:272.7:65.9:287.8::OUTLIER:OUTLIER",
" A 203 ILE:1.00:5.0:292.9:199.6:::Favored:mt",
" B 154 THR:1.00:0.1:356.0::::OUTLIER:OUTLIER",
" B 316 TYR:1.00:5.4:153.7:68.6:::Favored:t80",
" B 86 ASP:1.00:2.2:321.4:145.1:::Favored:m-20",
" B 377 GLU:1.00:45.3:311.7:166.2:160.1::Favored:mt-10",
" B 378 THR:1.00:23.5:309.4::::Favored:m"
]
# top8000 version
line_values = [
" A 14 MET:1.00:1.3:29.2:173.3:287.9::Allowed:ptm",
" A 15 SER:1.00:0.1:229.0::::OUTLIER:OUTLIER",
" A 16 SER:1.00:3.0:277.9::::Favored:m",
" A 58 ASN:1.00:1.0:252.4:343.6:::Allowed:m-40",
" A 59 ILE:1.00:0.5:84.2:186.7:::Allowed:pt",
" A 202 GLU:1.00:0.0:272.7:65.9:287.8::OUTLIER:OUTLIER",
" A 203 ILE:1.00:1.0:292.9:199.6:::Allowed:mt",
" B 154 THR:1.00:0.0:356.0::::OUTLIER:OUTLIER",
" B 316 TYR:1.00:4.1:153.7:68.6:::Favored:t80",
" B 86 ASP:1.00:0.4:321.4:145.1:::Allowed:m-30",
" B 377 GLU:1.00:15.0:311.7:166.2:160.1::Favored:mt-10",
" B 378 THR:1.00:17.0:309.4::::Favored:m",
]
for idx, val in zip(line_indices, line_values):
assert (output_lines[idx] == val), (idx, output_lines[idx])
regression_pdb = libtbx.env.find_in_repositories(
relative_path="phenix_regression/pdb/pdb1jxt.ent", test=os.path.isfile)
if (regression_pdb is None):
print "Skipping exercise_ramalyze(): input pdb (pdb1jxt.ent) not available"
return
pdb_in = file_reader.any_file(file_name=regression_pdb)
hierarchy = pdb_in.file_object.hierarchy
pdb_io = pdb.input(file_name=regression_pdb)
r = rotalyze.rotalyze(pdb_hierarchy=hierarchy, outliers_only=True)
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue().strip()
assert output == ""
r = rotalyze.rotalyze(pdb_hierarchy=hierarchy, outliers_only=False)
for unpickle in [False, True]:
if unpickle:
r = loads(dumps(r))
out = StringIO()
r.show_old_output(out=out, verbose=False)
output = out.getvalue()
assert not show_diff(
output, """\
A 1 THR:1.00:95.4:299.5::::Favored:m
A 2 ATHR:0.67:49.5:56.1::::Favored:p
A 2 BTHR:0.33:90.4:298.1::::Favored:m
A 3 CYS:1.00:12.9:310.5::::Favored:m
A 4 CYS:1.00:91.6:293.1::::Favored:m
A 5 PRO:1.00:78.8:30.2:319.7:33.8::Favored:Cg_endo
A 6 SER:1.00:90.1:68.4::::Favored:p
A 7 AILE:0.45:49.6:290.8:178.2:::Favored:mt
A 7 BILE:0.55:6.5:284.4:298.4:::Favored:mm
A 8 AVAL:0.50:1.1:156.7::::Allowed:t
A 8 BVAL:0.30:5.1:71.3::::Favored:p
A 8 CVAL:0.20:69.8:172.1::::Favored:t
A 10 AARG:0.65:24.7:176.8:66.5:63.9:180.0:Favored:tpp-160
A 10 BARG:0.35:17.5:176.8:72.8:66.4:171.9:Favored:tpp-160
A 11 SER:1.00:51.6:300.9::::Favored:m
A 12 AASN:0.50:93.9:286.1:343.8:::Favored:m-40
A 12 BASN:0.50:98.9:288.4:337.6:::Favored:m-40
A 13 APHE:0.65:45.1:187.2:276.4:::Favored:t80
A 13 BPHE:0.35:86.1:179.6:263.1:::Favored:t80
A 14 ASN:1.00:95.2:289.6:333.0:::Favored:m-40
A 15 VAL:1.00:42.3:168.2::::Favored:t
A 16 CYS:1.00:40.8:176.5::::Favored:t
A 17 ARG:1.00:21.4:289.7:282.8:288.6:158.7:Favored:mmm160
A 18 LEU:1.00:65.0:287.2:173.3:::Favored:mt
A 19 PRO:1.00:43.6:24.4:324.8:31.6::Favored:Cg_endo
A 21 THR:1.00:5.7:314.0::::Favored:m
A 22 APRO:0.55:87.5:333.5:34.0:333.8::Favored:Cg_exo
A 23 AGLU:0.50:86.9:290.9:187.1:341.8::Favored:mt-10
A 23 BGLU:0.50:91.7:292.0:183.8:339.2::Favored:mt-10
A 25 ALEU:0.50:95.7:294.4:173.6:::Favored:mt
A 26 CYS:1.00:83.0:295.0::::Favored:m
A 28 THR:1.00:29.6:52.9::::Favored:p
A 29 ATYR:0.65:18.5:161.8:67.8:::Favored:t80
A 29 BTYR:0.35:0.4:191.3:322.7:::Allowed:t80
A 30 ATHR:0.70:60.8:57.4::::Favored:p
A 30 BTHR:0.30:6.6:78.1::::Favored:p
A 32 CYS:1.00:61.4:301.7::::Favored:m
A 33 ILE:1.00:36.6:66.5:173.4:::Favored:pt
A 34 AILE:0.70:60.9:303.6:167.6:::Favored:mt
A 34 BILE:0.30:31.4:308.5:296.8:::Favored:mm
A 35 ILE:1.00:45.6:62.4:170.0:::Favored:pt
A 36 PRO:1.00:36.2:22.5:330.5:24.8::Favored:Cg_endo
A 39 ATHR:0.70:14.0:311.0::::Favored:m
A 39 BTHR:0.30:13.1:288.8::::Favored:m
A 40 CYS:1.00:81.4:294.4::::Favored:m
A 41 PRO:1.00:35.4:34.4:317.5:33.1::Favored:Cg_endo
A 43 AASP:0.75:24.8:56.5:340.3:::Favored:p0
A 43 BASP:0.25:43.2:59.6:349.3:::Favored:p0
A 44 TYR:1.00:85.3:290.9:85.1:::Favored:m-80
A 46 ASN:1.00:38.7:301.6:117.9:::Favored:m110
""")
def exercise_1 () :
pdb_raw = """\
ATOM 1134 N LYS A 82 5.933 36.285 21.572 1.00 70.94 N
ATOM 1135 CA LYS A 82 6.564 37.423 20.931 1.00 76.69 C
ATOM 1136 C LYS A 82 5.553 38.547 20.756 1.00 78.75 C
ATOM 1137 O LYS A 82 5.325 39.038 19.654 1.00 86.47 O
ATOM 1138 CB LYS A 82 7.179 37.024 19.583 1.00 82.32 C
ATOM 1139 CG LYS A 82 8.190 38.035 19.048 0.00 70.34 C
ATOM 1140 CD LYS A 82 9.429 38.129 19.944 0.00 67.69 C
ATOM 1141 CE LYS A 82 9.983 39.545 20.014 0.00 64.44 C
ATOM 1142 NZ LYS A 82 10.933 39.832 18.908 0.00 61.45 N
ATOM 1143 H LYS A 82 5.139 36.115 21.291 1.00 85.12 H
ATOM 1144 HA LYS A 82 7.279 37.749 21.501 1.00 92.03 H
ATOM 1145 HB2 LYS A 82 6.469 36.939 18.928 1.00 98.78 H
ATOM 1146 HB3 LYS A 82 7.636 36.175 19.687 1.00 98.78 H
ATOM 1147 HG2 LYS A 82 8.476 37.762 18.163 0.00 84.41 H
ATOM 1148 HG3 LYS A 82 7.775 38.912 19.011 0.00 84.41 H
ATOM 1149 HD2 LYS A 82 9.193 37.853 20.843 0.00 81.23 H
ATOM 1150 HD3 LYS A 82 10.122 37.551 19.589 0.00 81.23 H
ATOM 1151 HE2 LYS A 82 9.249 40.177 19.952 0.00 77.33 H
ATOM 1152 HE3 LYS A 82 10.453 39.662 20.854 0.00 77.33 H
ATOM 1153 HZ1 LYS A 82 11.237 40.666 18.977 0.00 73.75 H
ATOM 1154 HZ2 LYS A 82 10.523 39.738 18.123 0.00 73.75 H
ATOM 1155 HZ3 LYS A 82 11.621 39.269 18.944 0.00 73.75 H
ATOM 1156 N LYS A 83 4.936 38.927 21.866 1.00 75.79 N
ATOM 1157 CA LYS A 83 4.177 40.172 21.966 1.00 82.80 C
ATOM 1158 C LYS A 83 4.081 40.508 23.460 1.00 86.23 C
ATOM 1159 O LYS A 83 2.978 40.521 24.017 1.00 79.81 O
ATOM 1160 CB LYS A 83 2.790 40.044 21.332 1.00 79.16 C
ATOM 1161 CG LYS A 83 2.038 41.342 21.175 0.00 70.42 C
ATOM 1162 CD LYS A 83 2.072 41.803 19.735 0.00 66.90 C
ATOM 1163 CE LYS A 83 1.295 43.089 19.552 0.00 62.46 C
ATOM 1164 NZ LYS A 83 1.004 43.350 18.118 0.00 60.73 N
ATOM 1165 H LYS A 83 4.940 38.470 22.594 1.00 90.95 H
ATOM 1166 HA LYS A 83 4.658 40.885 21.518 1.00 99.36 H
ATOM 1167 HB2 LYS A 83 2.251 39.459 21.887 1.00 95.00 H
ATOM 1168 HB3 LYS A 83 2.890 39.655 20.449 1.00 95.00 H
ATOM 1169 HG2 LYS A 83 1.113 41.213 21.435 0.00 84.51 H
ATOM 1170 HG3 LYS A 83 2.453 42.024 21.726 0.00 84.51 H
ATOM 1171 HD2 LYS A 83 2.992 41.962 19.471 0.00 80.28 H
ATOM 1172 HD3 LYS A 83 1.672 41.123 19.171 0.00 80.28 H
ATOM 1173 HE2 LYS A 83 0.452 43.024 20.027 0.00 74.95 H
ATOM 1174 HE3 LYS A 83 1.818 43.830 19.896 0.00 74.95 H
ATOM 1175 HZ1 LYS A 83 0.521 42.683 17.780 0.00 72.87 H
ATOM 1176 HZ2 LYS A 83 1.764 43.417 17.661 0.00 72.87 H
ATOM 1177 HZ3 LYS A 83 0.548 44.109 18.034 0.00 72.87 H
ATOM 3630 N ASN A 242 -5.454 -3.027 1.145 0.00 67.69 N
ATOM 3631 CA ASN A 242 -4.759 -2.535 -0.037 0.00 65.44 C
ATOM 3632 C ASN A 242 -5.734 -2.397 -1.208 0.00 63.57 C
ATOM 3633 O ASN A 242 -6.425 -3.357 -1.552 0.00 63.94 O
ATOM 3634 CB ASN A 242 -3.626 -3.503 -0.392 0.00 63.13 C
ATOM 3635 CG ASN A 242 -2.802 -3.044 -1.576 0.00 63.58 C
ATOM 3636 OD1 ASN A 242 -2.524 -1.862 -1.731 0.00 65.52 O
ATOM 3637 ND2 ASN A 242 -2.399 -3.988 -2.416 0.00 62.17 N
ATOM 3638 H ASN A 242 -5.562 -3.880 1.129 0.00 81.22 H
ATOM 3639 HA ASN A 242 -4.375 -1.665 0.151 0.00 78.53 H
ATOM 3640 HB2 ASN A 242 -3.032 -3.587 0.370 0.00 75.76 H
ATOM 3641 HB3 ASN A 242 -4.007 -4.368 -0.611 0.00 75.76 H
ATOM 3642 HD21 ASN A 242 -1.929 -3.779 -3.104 0.00 74.60 H
ATOM 3643 HD22 ASN A 242 -2.609 -4.810 -2.272 0.00 74.60 H
ATOM 2 CA ALYS A 32 10.574 8.177 11.768 0.40 71.49 C
ATOM 3 CB ALYS A 32 9.197 8.686 12.246 0.40 74.71 C
ATOM 2 CA BLYS A 32 10.574 8.177 11.768 0.40 71.49 C
ATOM 3 CB BLYS A 32 9.197 8.686 12.246 0.40 74.71 C
ATOM 5 CA AVAL A 33 11.708 5.617 14.332 0.50 71.42 C
ATOM 6 CB AVAL A 33 11.101 4.227 14.591 0.50 71.47 C
ATOM 5 CA BVAL A 33 11.708 5.617 14.332 0.40 71.42 C
ATOM 6 CB BVAL A 33 11.101 4.227 14.591 0.40 71.47 C
TER
ATOM 1 N GLU X 18 -13.959 12.159 -6.598 1.00260.08 N
ATOM 2 CA GLU X 18 -13.297 13.465 -6.628 1.00269.83 C
ATOM 3 C GLU X 18 -11.946 13.282 -7.309 1.00269.18 C
ATOM 4 CB GLU X 18 -13.128 14.035 -5.210 1.00261.96 C
ATOM 5 CG GLU X 18 -14.455 14.401 -4.522 1.00263.56 C
ATOM 6 CD GLU X 18 -14.291 15.239 -3.242 1.00264.89 C
ATOM 7 OE1 GLU X 18 -14.172 14.646 -2.143 1.00264.24 O
ATOM 8 OE2 GLU X 18 -14.309 16.498 -3.306 1.00264.37 O1-
HETATM 614 S SO4 B 101 14.994 20.601 10.862 0.00 7.02 S
HETATM 615 O1 SO4 B 101 14.234 20.194 12.077 0.00 7.69 O
HETATM 616 O2 SO4 B 101 14.048 21.062 9.850 0.00 9.28 O
HETATM 617 O3 SO4 B 101 15.905 21.686 11.261 0.00 8.01 O
HETATM 618 O4 SO4 B 101 15.772 19.454 10.371 0.00 8.18 O
TER
HETATM 122 O HOH S 1 5.334 8.357 8.032 1.00 0.00 O
HETATM 123 O HOH S 2 5.396 15.243 10.734 1.00202.95 O
HETATM 124 O HOH S 3 -25.334 18.357 18.032 0.00 20.00 O
"""
mon_lib_srv = server.server()
ener_lib = server.ener_lib()
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
processed_pdb_file = pdb_interpretation.process(
mon_lib_srv=mon_lib_srv,
ener_lib=ener_lib,
raw_records=pdb_in.hierarchy.as_pdb_string(crystal_symmetry=xrs),
crystal_symmetry=xrs,
log=null_out())
pdb_in.hierarchy.atoms().reset_i_seq()
mstats = model_properties.model_statistics(
pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=processed_pdb_file.all_chain_proxies,
ignore_hd=True)
out = StringIO()
mstats.show(out=out)
#print out.getvalue()
assert not show_diff(out.getvalue(), """\
Overall:
Number of atoms = 50 (anisotropic = 0)
B_iso: mean = 96.0 max = 269.8 min = 0.0
Occupancy: mean = 0.47 max = 1.00 min = 0.00
warning: 22 atoms with zero occupancy
67 total B-factor or occupancy problem(s) detected
Atoms or residues with zero occupancy:
LYS A 82 CG occ=0.00
LYS A 82 CD occ=0.00
LYS A 82 CE occ=0.00
LYS A 82 NZ occ=0.00
LYS A 83 CG occ=0.00
LYS A 83 CD occ=0.00
LYS A 83 CE occ=0.00
LYS A 83 NZ occ=0.00
ASN A 242 (all) occ=0.00
SO4 B 101 (all) occ=0.00
HOH S 3 O occ=0.00
Macromolecules:
Number of atoms = 42 (anisotropic = 0)
B_iso: mean = 108.0 max = 269.8 min = 60.7
Occupancy: mean = 0.51 max = 1.00 min = 0.00
warning: 16 atoms with zero occupancy
57 total B-factor or occupancy problem(s) detected
Ligands:
Number of atoms = 5 (anisotropic = 0)
B_iso: mean = 8.0 max = 9.3 min = 7.0
Occupancy: mean = 0.00 max = 0.00 min = 0.00
warning: 5 atoms with zero occupancy
6 total B-factor or occupancy problem(s) detected
Waters:
Number of atoms = 3 (anisotropic = 0)
B_iso: mean = 74.3 max = 202.9 min = 0.0
Occupancy: mean = 0.67 max = 1.00 min = 0.00
warning: 1 atoms with zero occupancy
4 total B-factor or occupancy problem(s) detected
(Hydrogen atoms not included in overall counts.)
""")
assert (len(mstats.all.bad_adps) == 1)
assert (mstats.all.n_zero_b == 1)
mstats2 = loads(dumps(mstats))
out1 = StringIO()
out2 = StringIO()
mstats.show(out=out1)
mstats2.show(out=out2)
assert (out1.getvalue() == out2.getvalue())
# now with ignore_hd=False
mstats3 = model_properties.model_statistics(
pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=processed_pdb_file.all_chain_proxies,
ignore_hd=False)
out2 = StringIO()
mstats3.show(out=out2)
assert (out2.getvalue() != out.getvalue())
assert (""" LYS A 83 HZ3 occ=0.00""" in out2.getvalue())
outliers = mstats3.all.as_gui_table_data(include_zoom=True)
assert (len(outliers) == 84)
# test with all_chain_proxies undefined
mstats4 = model_properties.model_statistics(
pdb_hierarchy=pdb_in.hierarchy,
xray_structure=xrs,
all_chain_proxies=None,
ignore_hd=False)
outliers = mstats4.all.as_gui_table_data(include_zoom=True)
assert (len(outliers) == 84)