def exercise_cns_input () :
from mmtbx.regression import make_fake_anomalous_data
pdb_file, mtz_file = make_fake_anomalous_data.generate_cd_cl_inputs(
file_base="tst_cmdline_cns")
from iotbx.file_reader import any_file
mtz_in = any_file("tst_cmdline_cns.mtz")
f_obs = mtz_in.file_server.miller_arrays[0].average_bijvoet_mates()
flags = mtz_in.file_server.miller_arrays[1].average_bijvoet_mates()
f = open("tst_cmdline_cns.hkl", "w")
out = StringIO()
f_obs.export_as_cns_hkl(
file_object=out,
r_free_flags=flags)
# get rid of embedded symmetry
for line in out.getvalue().splitlines() :
if (not "{" in line) :
f.write("%s\n" % line)
f.close()
cmdline = mmtbx.command_line.load_model_and_data(
args=["tst_cmdline_cns.pdb", "tst_cmdline_cns.hkl"],
master_phil=mmtbx.command_line.generic_simple_input_phil(),
process_pdb_file=False,
create_fmodel=True,
out=null_out())
out = StringIO()
cmdline.crystal_symmetry.show_summary(f=out)
assert (out.getvalue() == """\
Unit cell: (21.362, 23.436, 23.594, 90, 90, 90)
Space group: P 1 (No. 1)
"""), out.getvalue()
def exercise():
from mmtbx.command_line import refine_anomalous_substructure
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
pdb_file, mtz_file = generate_cd_cl_inputs(file_base="tst_anom_ref")
groups = refine_anomalous_substructure.run(args=[pdb_file, mtz_file],
out=null_out())
assert len(groups) == 2
def exercise_anomalous_maps_misc():
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
import mmtbx.utils
from iotbx import file_reader
mtz_file, pdb_file = generate_cd_cl_inputs(file_base="tst_mmtbx_maps_misc")
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
xrs = pdb_in.file_object.xray_structure_simple()
for s in xrs.scatterers():
if (s.scattering_type == "Cd2+"):
s.fp = -0.29
s.fdp = 2.676
s.flags.set_use_fp_fdp(True)
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
flags = mtz_in.file_server.miller_arrays[0]
flags = flags.customized_copy(data=flags.data() == 1)
fmodel = mmtbx.utils.fmodel_simple(f_obs=f_obs,
r_free_flags=flags,
xray_structures=[xrs],
scattering_table="n_gaussian",
skip_twin_detection=True)
map_coeffs = fmodel.map_coefficients(map_type="anom_residual",
exclude_free_r_reflections=True)
map_anom = map_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map_unpadded()
for s in xrs.scatterers():
if (s.scattering_type == "Cd2+"):
assert (map_anom.eight_point_interpolation(s.site) < 0)
elif (s.scattering_type == 'Cl1-'):
assert (map_anom.eight_point_interpolation(s.site) > 10)
# this simply checks whether anomalous data will cause problems when
# mixed with other options (i.e. array size errors)
map2 = fmodel.map_coefficients(map_type="2mFo-DFc",
exclude_free_r_reflections=True)
def exercise():
from mmtbx.command_line import refine_anomalous_substructure
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
pdb_file, mtz_file = generate_cd_cl_inputs(file_base="tst_anom_ref")
groups = refine_anomalous_substructure.run(args=[pdb_file, mtz_file], out=null_out())
assert len(groups) == 2
def exercise () :
from mmtbx.command_line import refine_anomalous_substructure
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
mtz_file, pdb_file = generate_cd_cl_inputs(
file_base = "tst_mmtbx_substructure")
# XXX for some reason even though I'm using synthetic data, it ends up with
# an extra water with a peak height of 3.1
anom_groups = refine_anomalous_substructure.run(
args=[mtz_file, pdb_file, "skip_twin_detection=True", "map_sigma_min=4"],
out=null_out())
assert (len(anom_groups) == 2)
print "OK"
def exercise():
from mmtbx.command_line import refine_anomalous_substructure
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
mtz_file, pdb_file = generate_cd_cl_inputs(
file_base="tst_mmtbx_substructure")
# XXX for some reason even though I'm using synthetic data, it ends up with
# an extra water with a peak height of 3.1
anom_groups = refine_anomalous_substructure.run(args=[
mtz_file, pdb_file, "skip_twin_detection=True", "map_sigma_min=4"
],
out=null_out())
assert (len(anom_groups) == 2)
print("OK")
def exercise_example () :
from mmtbx.regression import make_fake_anomalous_data
pdb_file, mtz_file = make_fake_anomalous_data.generate_cd_cl_inputs(
file_base="tst_cmdline_example")
script = os.path.join(libtbx.env.dist_path("mmtbx"), "examples",
"simple_command_line_cc.py")
assert os.path.isfile(script)
args = [
"mmtbx.python",
"\"%s\"" % script,
pdb_file,
mtz_file,
"skip_twin_detection=True",
]
result = easy_run.fully_buffered(" ".join(args)).raise_if_errors()
assert ("""CC(obs-calc): 0.999""" in result.stdout_lines)
def exercise () :
from mmtbx.command_line import compute_map_coefficients
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
from iotbx import file_reader
mtz_file, pdb_file = generate_cd_cl_inputs(
file_base="tst_map_coeffs_simple")
args = [mtz_file, pdb_file, "map_type=anom_residual",
"skip_twin_detection=True"]
out = StringIO()
compute_map_coefficients.run(args=args, out=out)
assert """Using wavelength = 1.116 from PDB header""" in out.getvalue()
assert os.path.isfile("tst_map_coeffs_simple_anom_residual.mtz")
mtz_in = file_reader.any_file("tst_map_coeffs_simple_anom_residual.mtz")
assert (mtz_in.file_server.miller_arrays[0].info().label_string() ==
"ANOM_DIFF,PHANOM_DIFF")
print "OK"
def exercise_anomalous_maps_misc () :
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
import mmtbx.utils
from iotbx import file_reader
mtz_file, pdb_file = generate_cd_cl_inputs(
file_base = "tst_mmtbx_maps_misc")
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
xrs = pdb_in.file_object.xray_structure_simple()
for s in xrs.scatterers() :
if (s.scattering_type == "Cd2+") :
s.fp = -0.29
s.fdp = 2.676
s.flags.set_use_fp_fdp(True)
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
flags = mtz_in.file_server.miller_arrays[0]
flags = flags.customized_copy(data=flags.data()==1)
fmodel = mmtbx.utils.fmodel_simple(
f_obs=f_obs,
r_free_flags=flags,
xray_structures=[xrs],
scattering_table="n_gaussian",
skip_twin_detection=True)
map_coeffs = fmodel.map_coefficients(
map_type="anom_residual",
exclude_free_r_reflections=True)
map_anom = map_coeffs.fft_map(
resolution_factor=0.25).apply_sigma_scaling().real_map_unpadded()
for s in xrs.scatterers() :
if (s.scattering_type == "Cd2+") :
assert (map_anom.eight_point_interpolation(s.site) < 0)
elif (s.scattering_type == 'Cl1-') :
assert (map_anom.eight_point_interpolation(s.site) > 10)
# this simply checks whether anomalous data will cause problems when
# mixed with other options (i.e. array size errors)
map2 = fmodel.map_coefficients(
map_type="2mFo-DFc",
exclude_free_r_reflections=True)
def exercise () :
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
from mmtbx.command_line import mtz2map
import mmtbx.utils
from iotbx import file_reader
from scitbx.array_family import flex
mtz_file, pdb_file = generate_cd_cl_inputs(file_base = "tst_mmtbx_mtz2map")
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
xrs = pdb_in.file_object.xray_structure_simple()
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
f_obs_mean = f_obs.average_bijvoet_mates()
flags = mtz_in.file_server.miller_arrays[1]
flags = flags.customized_copy(data=flags.data()==1)
fmodel = mmtbx.utils.fmodel_simple(
f_obs=f_obs,
r_free_flags=flags,
xray_structures=[xrs],
scattering_table="n_gaussian",
skip_twin_detection=True)
assert f_obs.anomalous_flag()
mtz_data = f_obs.as_mtz_dataset(column_root_label="F")
#mtz_data.add_miller_array(
# miller_array=f_obs.average_bijvoet_mates(),
# column_root_label="F_mean")
mtz_data.add_miller_array(
miller_array=fmodel.f_model(),
column_root_label="FMODEL")
mtz_data.add_miller_array(
miller_array=fmodel.f_model().average_bijvoet_mates().phases(deg=True),
column_root_label="PHI",
column_types="P")
mtz_data.add_miller_array(
miller_array=f_obs_mean.customized_copy(
data=flex.double(f_obs_mean.data().size(), 0.95),
sigmas=None).set_observation_type(None),
column_root_label="FOM",
column_types="W")
two_fofc_map = fmodel.map_coefficients(map_type="2mFo-DFc")
fofc_map = fmodel.map_coefficients(map_type="mFo-Dfc")
anom_map = fmodel.map_coefficients(map_type="anom")
mtz_data.add_miller_array(
miller_array=two_fofc_map.average_bijvoet_mates(),
column_root_label="2FOFCWT")
mtz_data.add_miller_array(
miller_array=fmodel.map_coefficients(map_type="mFo-DFc"),
column_root_label="FOFCWT")
mtz_data.add_miller_array(
miller_array=fmodel.map_coefficients(map_type="anom"),
column_root_label="ANOM")
mtz_data.add_miller_array(flags,
column_root_label="FreeR_flag")
map_file = "tst_mmtbx_mtz2map_map_coeffs.mtz"
mtz_data.mtz_object().write(map_file)
# exercise defaults with PDB file
file_info = mtz2map.run([pdb_file, map_file], log=null_out())
file_info = [ (os.path.basename(fn), desc) for fn, desc in file_info ]
assert (file_info == [
('tst_mmtbx_mtz2map_map_coeffs_2mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_anom.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_4.ccp4', 'CCP4 map')
])
# without PDB file
file_info_2 = mtz2map.run([map_file], log=null_out())
file_info_2 = [ (os.path.basename(fn), desc) for fn, desc in file_info_2 ]
assert file_info_2 == file_info, file_info_2
# with FMODEL
file_info_3 = mtz2map.run([pdb_file, map_file, "include_fmodel=True"],
log=null_out())
file_info_3 = [ (os.path.basename(fn), desc) for fn, desc in file_info_3 ]
assert (file_info_3 == [
('tst_mmtbx_mtz2map_map_coeffs_fmodel.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_2mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_anom.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_5.ccp4', 'CCP4 map')
])
# exercise bad parameter
try :
file_info = mtz2map.run([pdb_file, "1yjp_mtz2map_map_coeffs.mtz",
"output.directory=1yjp_mtz2map_map_coeffs.mtz"],
log=null_out())
except Sorry :
pass
else :
raise Exception_expected
# bad atom selection
try :
file_info = mtz2map.run([pdb_file, map_file, "selection=\"resname ZN\""],
log=null_out())
except Sorry, s :
assert (str(s) == "No atoms found matching the specified selection.")
def exercise():
from mmtbx.regression.make_fake_anomalous_data import generate_cd_cl_inputs
from mmtbx.command_line import mtz2map
import mmtbx.utils
from iotbx import file_reader
from scitbx.array_family import flex
mtz_file, pdb_file = generate_cd_cl_inputs(file_base="tst_mmtbx_mtz2map")
pdb_in = file_reader.any_file(pdb_file)
hierarchy = pdb_in.file_object.hierarchy
xrs = pdb_in.file_object.xray_structure_simple()
mtz_in = file_reader.any_file(mtz_file)
f_obs = mtz_in.file_server.miller_arrays[0]
f_obs_mean = f_obs.average_bijvoet_mates()
flags = mtz_in.file_server.miller_arrays[1]
flags = flags.customized_copy(data=flags.data() == 1)
fmodel = mmtbx.utils.fmodel_simple(f_obs=f_obs,
r_free_flags=flags,
xray_structures=[xrs],
scattering_table="n_gaussian",
skip_twin_detection=True)
assert f_obs.anomalous_flag()
mtz_data = f_obs.as_mtz_dataset(column_root_label="F")
#mtz_data.add_miller_array(
# miller_array=f_obs.average_bijvoet_mates(),
# column_root_label="F_mean")
mtz_data.add_miller_array(miller_array=fmodel.f_model(),
column_root_label="FMODEL")
mtz_data.add_miller_array(
miller_array=fmodel.f_model().average_bijvoet_mates().phases(deg=True),
column_root_label="PHI",
column_types="P")
mtz_data.add_miller_array(miller_array=f_obs_mean.customized_copy(
data=flex.double(f_obs_mean.data().size(),
0.95), sigmas=None).set_observation_type(None),
column_root_label="FOM",
column_types="W")
two_fofc_map = fmodel.map_coefficients(map_type="2mFo-DFc")
fofc_map = fmodel.map_coefficients(map_type="mFo-Dfc")
anom_map = fmodel.map_coefficients(map_type="anom")
mtz_data.add_miller_array(
miller_array=two_fofc_map.average_bijvoet_mates(),
column_root_label="2FOFCWT")
mtz_data.add_miller_array(
miller_array=fmodel.map_coefficients(map_type="mFo-DFc"),
column_root_label="FOFCWT")
mtz_data.add_miller_array(
miller_array=fmodel.map_coefficients(map_type="anom"),
column_root_label="ANOM")
mtz_data.add_miller_array(flags, column_root_label="FreeR_flag")
map_file = "tst_mmtbx_mtz2map_map_coeffs.mtz"
mtz_data.mtz_object().write(map_file)
# exercise defaults with PDB file
file_info = mtz2map.run([pdb_file, map_file], log=null_out())
file_info = [(os.path.basename(fn), desc) for fn, desc in file_info]
assert (file_info == [
('tst_mmtbx_mtz2map_map_coeffs_2mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_anom.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_4.ccp4', 'CCP4 map')
])
# without PDB file
file_info_2 = mtz2map.run([map_file], log=null_out())
file_info_2 = [(os.path.basename(fn), desc) for fn, desc in file_info_2]
assert file_info_2 == file_info, file_info_2
# with FMODEL
file_info_3 = mtz2map.run([pdb_file, map_file, "include_fmodel=True"],
log=null_out())
file_info_3 = [(os.path.basename(fn), desc) for fn, desc in file_info_3]
assert (file_info_3 == [
('tst_mmtbx_mtz2map_map_coeffs_fmodel.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_2mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_mFo-DFc.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_anom.ccp4', 'CCP4 map'),
('tst_mmtbx_mtz2map_map_coeffs_5.ccp4', 'CCP4 map')
])
# exercise bad parameter
try:
file_info = mtz2map.run([
pdb_file, "1yjp_mtz2map_map_coeffs.mtz",
"output.directory=1yjp_mtz2map_map_coeffs.mtz"
],
log=null_out())
except Sorry:
pass
else:
raise Exception_expected
# bad atom selection
try:
file_info = mtz2map.run(
[pdb_file, map_file, "selection=\"resname ZN\""], log=null_out())
except Sorry, s:
assert (str(s) == "No atoms found matching the specified selection.")
