def test1(prefix="tst_mp4"):
"""
Illustrating failure in twin refine tutorial data, discovered 2/26/2018.
"""
with open("%s.pdb" % prefix, 'w') as f:
f.write(pdb_txt)
result = molprobity.run(args=['%s.pdb' % prefix])
def exercise_cdl():
pdb_raw = """
ATOM 1270 N LEU A 199 6.903 55.119 -0.416 1.00 25.48 N
ATOM 1271 CA LEU A 199 7.726 56.192 -0.941 1.00 25.93 C
ATOM 1272 C LEU A 199 6.996 56.972 -2.047 1.00 26.39 C
ATOM 1273 O LEU A 199 7.020 58.180 -2.064 1.00 25.38 O
ATOM 1274 CB LEU A 199 9.033 55.633 -1.490 1.00 25.66 C
ATOM 1278 N ARG A 200 6.361 56.258 -2.980 1.00 27.31 N
ATOM 1279 CA ARG A 200 5.576 56.913 -3.993 1.00 28.53 C
ATOM 1280 C ARG A 200 4.520 57.823 -3.397 1.00 27.54 C
ATOM 1281 O ARG A 200 4.397 58.949 -3.851 1.00 27.50 O
ATOM 1282 CB ARG A 200 4.933 55.879 -4.899 1.00 30.38 C
ATOM 1289 N ALA A 201 3.790 57.365 -2.357 1.00 26.90 N
ATOM 1290 CA ALA A 201 2.764 58.200 -1.713 1.00 26.49 C
ATOM 1291 C ALA A 201 3.406 59.407 -1.045 1.00 26.59 C
ATOM 1292 O ALA A 201 2.866 60.516 -1.082 1.00 26.58 O
ATOM 1293 CB ALA A 201 1.959 57.412 -0.715 1.00 25.11 C
ATOM 1294 N ARG A 202 4.566 59.205 -0.419 1.00 25.66 N
ATOM 1295 CA ARG A 202 5.245 60.296 0.240 1.00 26.93 C
ATOM 1296 C ARG A 202 5.676 61.346 -0.767 1.00 26.93 C
ATOM 1297 O ARG A 202 5.555 62.541 -0.489 1.00 25.79 O
ATOM 1298 CB ARG A 202 6.493 59.779 0.996 1.00 28.25 C
ATOM 1305 N ILE A 203 6.154 60.912 -1.931 1.00 26.99 N
ATOM 1306 CA ILE A 203 6.611 61.848 -2.965 1.00 27.49 C
ATOM 1307 C ILE A 203 5.430 62.674 -3.480 1.00 28.29 C
ATOM 1308 O ILE A 203 5.548 63.905 -3.624 1.00 27.82 O
ATOM 1309 CB ILE A 203 7.322 61.125 -4.075 1.00 28.09 C
ATOM 1313 N SER A 204 4.288 62.025 -3.678 1.00 27.96 N
ATOM 1314 CA SER A 204 3.119 62.736 -4.184 1.00 28.04 C
ATOM 1315 C SER A 204 2.683 63.793 -3.199 1.00 28.16 C
ATOM 1316 O SER A 204 2.311 64.910 -3.605 1.00 28.25 O
ATOM 1317 CB SER A 204 1.962 61.780 -4.504 1.00 27.64 C
"""
pdb_raw_2 = """\
REMARK 3 GEOSTD + MON.LIB. + CDL v1.2
""" + pdb_raw
open("tst_molprobity_cdl_1.pdb", "w").write(pdb_raw)
open("tst_molprobity_cdl_2.pdb", "w").write(pdb_raw_2)
files = ["tst_molprobity_cdl_1.pdb", "tst_molprobity_cdl_2.pdb"]
rmsds = [0.9019, 0.8769]
for file_name, rmsd, cdl_expected in zip(files, rmsds, [False, True]):
result = molprobity.run(args=[file_name, "flags.clashscore=False"],
ignore_missing_modules=True,
out=null_out()).validation
assert approx_equal(result.rms_angles(), rmsd, eps=0.001), rmsd
if cdl_expected:
out = StringIO()
result.show(out=out)
assert (
"Geometry Restraints Library: GeoStd + Monomer Library + CDL v1.2"
in out.getvalue())
else:
out = StringIO()
result.show(out=out)
assert ("CDL" not in out.getvalue())
def exercise_cdl () :
pdb_raw = """
ATOM 1270 N LEU A 199 6.903 55.119 -0.416 1.00 25.48 N
ATOM 1271 CA LEU A 199 7.726 56.192 -0.941 1.00 25.93 C
ATOM 1272 C LEU A 199 6.996 56.972 -2.047 1.00 26.39 C
ATOM 1273 O LEU A 199 7.020 58.180 -2.064 1.00 25.38 O
ATOM 1274 CB LEU A 199 9.033 55.633 -1.490 1.00 25.66 C
ATOM 1278 N ARG A 200 6.361 56.258 -2.980 1.00 27.31 N
ATOM 1279 CA ARG A 200 5.576 56.913 -3.993 1.00 28.53 C
ATOM 1280 C ARG A 200 4.520 57.823 -3.397 1.00 27.54 C
ATOM 1281 O ARG A 200 4.397 58.949 -3.851 1.00 27.50 O
ATOM 1282 CB ARG A 200 4.933 55.879 -4.899 1.00 30.38 C
ATOM 1289 N ALA A 201 3.790 57.365 -2.357 1.00 26.90 N
ATOM 1290 CA ALA A 201 2.764 58.200 -1.713 1.00 26.49 C
ATOM 1291 C ALA A 201 3.406 59.407 -1.045 1.00 26.59 C
ATOM 1292 O ALA A 201 2.866 60.516 -1.082 1.00 26.58 O
ATOM 1293 CB ALA A 201 1.959 57.412 -0.715 1.00 25.11 C
ATOM 1294 N ARG A 202 4.566 59.205 -0.419 1.00 25.66 N
ATOM 1295 CA ARG A 202 5.245 60.296 0.240 1.00 26.93 C
ATOM 1296 C ARG A 202 5.676 61.346 -0.767 1.00 26.93 C
ATOM 1297 O ARG A 202 5.555 62.541 -0.489 1.00 25.79 O
ATOM 1298 CB ARG A 202 6.493 59.779 0.996 1.00 28.25 C
ATOM 1305 N ILE A 203 6.154 60.912 -1.931 1.00 26.99 N
ATOM 1306 CA ILE A 203 6.611 61.848 -2.965 1.00 27.49 C
ATOM 1307 C ILE A 203 5.430 62.674 -3.480 1.00 28.29 C
ATOM 1308 O ILE A 203 5.548 63.905 -3.624 1.00 27.82 O
ATOM 1309 CB ILE A 203 7.322 61.125 -4.075 1.00 28.09 C
ATOM 1313 N SER A 204 4.288 62.025 -3.678 1.00 27.96 N
ATOM 1314 CA SER A 204 3.119 62.736 -4.184 1.00 28.04 C
ATOM 1315 C SER A 204 2.683 63.793 -3.199 1.00 28.16 C
ATOM 1316 O SER A 204 2.311 64.910 -3.605 1.00 28.25 O
ATOM 1317 CB SER A 204 1.962 61.780 -4.504 1.00 27.64 C
"""
pdb_raw_2 = """\
REMARK 3 GEOSTD + MON.LIB. + CDL v1.2
""" + pdb_raw
open("tst_molprobity_cdl_1.pdb", "w").write(pdb_raw)
open("tst_molprobity_cdl_2.pdb", "w").write(pdb_raw_2)
files = ["tst_molprobity_cdl_1.pdb","tst_molprobity_cdl_2.pdb"]
rmsds = [0.9019, 0.8769]
for file_name, rmsd, cdl_expected in zip(files, rmsds, [False, True]) :
result = molprobity.run(args=[file_name, "flags.clashscore=False"],
ignore_missing_modules=True,
out=null_out()).validation
assert approx_equal(result.rms_angles(), rmsd, eps=0.001), rmsd
if cdl_expected :
out = StringIO()
result.show(out=out)
assert ("conformation-dependent library" in out.getvalue())
else:
out = StringIO()
result.show(out=out)
assert ("conformation-dependent library" not in 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_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_01():
pdb_raw = """\
CRYST1 10.000 15.000 10.000 90.00 90.00 90.00 P 1
ATOM 6407 N GLY A 388 -0.783 9.368 -16.436 1.00 51.96 N
ATOM 6408 CA GLY A 388 -0.227 9.888 -15.197 1.00 54.04 C
ATOM 6409 C GLY A 388 -0.637 11.320 -14.897 1.00 55.86 C
ATOM 6410 O GLY A 388 -1.728 11.738 -15.347 1.00 56.70 O
ATOM 6411 OXT GLY A 388 0.129 12.024 -14.203 1.00 56.98 O
ATOM 6412 D GLY A 388 -0.460 9.727 -17.309 1.00 51.44 D
ATOM 6413 HA2 GLY A 388 -0.561 9.258 -14.385 1.00 54.07 H
ATOM 6414 HA3 GLY A 388 0.843 9.835 -15.243 1.00 54.13 H
TER 6415 GLY A 388
HETATM 6416 D D8U A 401 2.236 5.695 -12.992 1.00 15.23 D
HETATM 6417 O DOD A1001 -4.151 4.107 -16.592 1.00 13.40 O
HETATM 6418 D1 DOD A1001 -4.760 3.026 -11.326 1.00 15.45 D
HETATM 6419 D2 DOD A1001 -4.625 2.741 -13.845 1.00 14.81 D
"""
random.seed(12345)
flex.set_random_seed(12345)
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
pdb_in.hierarchy.atoms().reset_i_seq()
open("tst_validate_experimental.pdb",
"w").write(pdb_in.hierarchy.as_pdb_string(crystal_symmetry=xrs))
f_calc = abs(xrs.structure_factors(d_min=2.0).f_calc())
f_calc.set_observation_type_xray_amplitude()
flags = f_calc.generate_r_free_flags()
mtz = f_calc.as_mtz_dataset(column_root_label="F")
mtz.add_miller_array(flags, column_root_label="FreeR_flag")
mtz.mtz_object().write("tst_validate_experimental.mtz")
args = [
"tst_validate_experimental.pdb",
"tst_validate_experimental.mtz",
]
args.append("flags.clashscore=%s" % libtbx.env.has_module("probe"))
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
assert result.real_space is not None
ds = result.data_stats
assert (ds.n_free > 0)
def exercise_01 () :
pdb_raw = """\
CRYST1 10.000 15.000 10.000 90.00 90.00 90.00 P 1
ATOM 6407 N GLY A 388 -0.783 9.368 -16.436 1.00 51.96 N
ATOM 6408 CA GLY A 388 -0.227 9.888 -15.197 1.00 54.04 C
ATOM 6409 C GLY A 388 -0.637 11.320 -14.897 1.00 55.86 C
ATOM 6410 O GLY A 388 -1.728 11.738 -15.347 1.00 56.70 O
ATOM 6411 OXT GLY A 388 0.129 12.024 -14.203 1.00 56.98 O
ATOM 6412 D GLY A 388 -0.460 9.727 -17.309 1.00 51.44 D
ATOM 6413 HA2 GLY A 388 -0.561 9.258 -14.385 1.00 54.07 H
ATOM 6414 HA3 GLY A 388 0.843 9.835 -15.243 1.00 54.13 H
TER 6415 GLY A 388
HETATM 6416 D D8U A 401 2.236 5.695 -12.992 1.00 15.23 D
HETATM 6417 O DOD A1001 -4.151 4.107 -16.592 1.00 13.40 O
HETATM 6418 D1 DOD A1001 -4.760 3.026 -11.326 1.00 15.45 D
HETATM 6419 D2 DOD A1001 -4.625 2.741 -13.845 1.00 14.81 D
"""
random.seed(12345)
flex.set_random_seed(12345)
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
pdb_in.hierarchy.atoms().reset_i_seq()
open("tst_validate_experimental.pdb", "w").write(
pdb_in.hierarchy.as_pdb_string(crystal_symmetry=xrs))
f_calc =abs( xrs.structure_factors(d_min=2.0).f_calc())
f_calc.set_observation_type_xray_amplitude()
flags = f_calc.generate_r_free_flags()
mtz = f_calc.as_mtz_dataset(column_root_label="F")
mtz.add_miller_array(flags, column_root_label="FreeR_flag")
mtz.mtz_object().write("tst_validate_experimental.mtz")
args = [
"tst_validate_experimental.pdb",
"tst_validate_experimental.mtz",
]
args.append("flags.clashscore=%s" % libtbx.env.has_module("probe"))
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
assert result.real_space is not None
ds = result.data_stats
assert (ds.n_free > 0)
def runMolprobity(args, out=sys.stdout):
import sys, re
from mmtbx.command_line import molprobity
molprobity.run(args, out=out)
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_synthetic () :
from mmtbx.regression import tst_build_alt_confs
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=tst_build_alt_confs.pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
fc = abs(xrs.structure_factors(d_min=1.5).f_calc())
flags = fc.resolution_filter(d_min=1.6).generate_r_free_flags()
ls = fc.lone_set(other=flags)
# case 1: no work set in high-res shell
flags2 = ls.array(data=flex.bool(ls.size(), True))
flags_all = flags.concatenate(other=flags2)
mtz_out = fc.as_mtz_dataset(column_root_label="F")
mtz_out.add_miller_array(flags_all, column_root_label="FreeR_flag")
mtz_out.mtz_object().write("tst_molprobity_1.mtz")
open("tst_molprobity_1.pdb", "w").write(tst_build_alt_confs.pdb_raw)
args = [
"tst_molprobity_1.pdb",
"tst_molprobity_1.mtz",
"--kinemage",
"--maps",
"flags.clashscore=False",
"flags.xtriage=True",
]
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# case 2: no test set in high-res shell
flags2 = ls.array(data=flex.bool(ls.size(), False))
flags_all = flags.concatenate(other=flags2)
mtz_out = fc.as_mtz_dataset(column_root_label="F")
mtz_out.add_miller_array(flags_all, column_root_label="FreeR_flag")
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# case 3: multi-MODEL structure
# XXX This is not a very sophisticated test - it only ensures that the
# program does not crash. We need a test for expected output...
hierarchy = pdb_in.hierarchy
model2 = hierarchy.only_model().detached_copy()
hierarchy.append_model(model2)
hierarchy.models()[0].id = "1"
hierarchy.models()[1].id = "2"
open("tst_molprobity_multi_model.pdb", "w").write(hierarchy.as_pdb_string())
args = [
"tst_molprobity_multi_model.pdb",
"tst_molprobity_1.mtz",
"--kinemage",
"--maps",
"flags.clashscore=False",
]
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# test rotamer distributions
open("tst_molprobity_misc1.pdb", "w").write(tst_build_alt_confs.pdb_raw)
args = [
"tst_molprobity_1.pdb",
"rotamer_library=8000",
"outliers_only=False",
"flags.clashscore=False",
]
out = StringIO()
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
result.show(outliers_only=False, out=out)
assert (""" A 7 TYR m-80 93.10 299.6,92.0""" in
out.getvalue()), out.getvalue()
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_synthetic () :
from mmtbx.regression import tst_build_alt_confs
pdb_in = iotbx.pdb.hierarchy.input(pdb_string=tst_build_alt_confs.pdb_raw)
xrs = pdb_in.input.xray_structure_simple()
fc = abs(xrs.structure_factors(d_min=1.5).f_calc())
flags = fc.resolution_filter(d_min=1.6).generate_r_free_flags()
ls = fc.lone_set(other=flags)
# case 1: no work set in high-res shell
flags2 = ls.array(data=flex.bool(ls.size(), True))
flags_all = flags.concatenate(other=flags2)
mtz_out = fc.as_mtz_dataset(column_root_label="F")
mtz_out.add_miller_array(flags_all, column_root_label="FreeR_flag")
mtz_out.mtz_object().write("tst_molprobity_1.mtz")
open("tst_molprobity_1.pdb", "w").write(tst_build_alt_confs.pdb_raw)
args = [
"tst_molprobity_1.pdb",
"tst_molprobity_1.mtz",
"--kinemage",
"--maps",
"flags.clashscore=False",
"flags.xtriage=True",
]
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# case 2: no test set in high-res shell
flags2 = ls.array(data=flex.bool(ls.size(), False))
flags_all = flags.concatenate(other=flags2)
mtz_out = fc.as_mtz_dataset(column_root_label="F")
mtz_out.add_miller_array(flags_all, column_root_label="FreeR_flag")
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# case 3: multi-MODEL structure
# XXX This is not a very sophisticated test - it only ensures that the
# program does not crash. We need a test for expected output...
hierarchy = pdb_in.hierarchy
model2 = hierarchy.only_model().detached_copy()
hierarchy.append_model(model2)
hierarchy.models()[0].id = "1"
hierarchy.models()[1].id = "2"
open("tst_molprobity_multi_model.pdb", "w").write(hierarchy.as_pdb_string())
args = [
"tst_molprobity_multi_model.pdb",
"tst_molprobity_1.mtz",
"--kinemage",
"--maps",
]
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
out = StringIO()
result.show(out=out)
# test rotamer distributions
open("tst_molprobity_misc1.pdb", "w").write(tst_build_alt_confs.pdb_raw)
args = [
"tst_molprobity_1.pdb",
"rotamer_library=8000",
]
out = StringIO()
result = molprobity.run(args=args,
ignore_missing_modules=True,
out=null_out()).validation
result.show(outliers_only=False, out=out)
