def loadModel(filename):
dm = DataManager() # Initialize the DataManager and call it dm
dm.set_overwrite(
True) # tell the DataManager to overwrite files with the same name
#print("Reading file")
manager = dm.get_model(filename)
return manager
def __init__(self,
program_class,
custom_process_arguments=None,
logger=None,
*args,
**kwargs):
'''
'''
# program name
self.prog = os.getenv('LIBTBX_DISPATCHER_NAME')
if (self.prog is None):
self.prog = sys.argv[0]
self.prefix = self.prog.split('.')[-1]
# PHIL filenames
self.data_filename = self.prefix + '_data.eff'
self.modified_filename = self.prefix + '_modified.eff'
self.all_filename = self.prefix + '_all.eff'
# terminal width
self.text_width = 79
# print header
border = '-' * self.text_width
description = border + program_class.description + border
epilog = border + program_class.epilog
super(CCTBXParser, self).__init__(
prog=self.prog,
description=description,
epilog=epilog,
formatter_class=argparse.RawDescriptionHelpFormatter,
*args,
**kwargs)
# default values
self.program_class = program_class
self.custom_process_arguments = custom_process_arguments
self.logger = logger
if (self.logger is None):
self.logger = logging.getLogger('main')
self.data_manager = DataManager(datatypes=program_class.datatypes,
logger=self.logger)
# add PHIL converters if available
if (len(program_class.phil_converters) > 0):
iotbx.phil.default_converter_registry = \
libtbx.phil.extended_converter_registry(
additional_converters=program_class.phil_converters,
base_registry=iotbx.phil.default_converter_registry)
# set up master and working PHIL scopes
self.master_phil = iotbx.phil.parse(program_class.master_phil_str,
process_includes=True)
required_output_phil = iotbx.phil.parse(
ProgramTemplate.output_phil_str)
self.master_phil.adopt_scope(required_output_phil)
self.working_phil = None
self.add_default_options()
def test_02():
data_dir = os.path.dirname(os.path.abspath(__file__))
data_d7 = os.path.join(data_dir, 'data', 'D7.ccp4')
# find_separated atoms in a map
dm = DataManager()
mm = dm.get_real_map(data_d7)
sites_cart = mm.trace_atoms_in_map(dist_min=1, n_atoms=10)
assert sites_cart.size() == 10 # Note: zero if not available
def loadModel(filename):
dm = DataManager() # Initialize the DataManager and call it dm
dm.set_overwrite(
True) # tell the DataManager to overwrite files with the same name
#print("Reading file")
model = dm.get_model(filename)
#print("Processing model")
#model.process_input_model(make_restraints=True)
# removed because Restraints Manager will not operate
# on unfamiliar residues KPB 6/10/2021
return model
def run(args, log=sys.stdout):
print("-"*79, file=log)
print(legend, file=log)
print("-"*79, file=log)
inputs = mmtbx.utils.process_command_line_args(args = args,
master_params = master_params(),
suppress_symmetry_related_errors = True)
params = inputs.params.extract()
# model
broadcast(m="Input PDB:", log=log)
file_names = inputs.pdb_file_names
if(len(file_names) != 1): raise Sorry("PDB file has to given.")
from iotbx.data_manager import DataManager
dm = DataManager()
dm.set_overwrite(True)
model = dm.get_model(file_names[0])
# map
broadcast(m="Input map:", log=log)
if(inputs.ccp4_map is None): raise Sorry("Map file has to given.")
from iotbx.map_model_manager import map_model_manager
mam = map_model_manager(model = model, map_manager = inputs.ccp4_map,
wrapping = params.wrapping,
ignore_symmetry_conflicts = params.ignore_symmetry_conflicts)
mam.model().setup_scattering_dictionaries(
scattering_table=params.scattering_table)
mam.model().get_xray_structure().show_summary(f=log, prefix=" ")
inputs.ccp4_map.show_summary(prefix=" ")
# estimate resolution
d_min = params.resolution
if(d_min is None):
raise Sorry("Map resolution must be given.")
print(" d_min: %6.4f"%d_min, file=log)
#
result_obj = compdiff(
map_data_obs = mam.map_manager().map_data(), # NOTE this will always wrap map
xrs = mam.model().get_xray_structure(),
d_min = d_min,
vector_map = False)
output_map_manager=mam.map_manager().customized_copy(
map_data=result_obj.map_result)
dm.write_real_map_file(output_map_manager, "map_model_difference_1.ccp4")
#
result_obj = compdiff(
map_data_obs = mam.map_manager().map_data(),
xrs = mam.model().get_xray_structure(),
d_min = d_min,
vector_map = True)
output_map_manager=mam.map_manager().customized_copy(
map_data=result_obj.map_result)
dm.write_real_map_file(output_map_manager, "map_model_difference_2.ccp4")
def read_map_and_model(file_name_1, file_name_2):
'''
Identify which file is map and which is model, read in and
create map_model_manager
'''
map_file_name = None
model_file_name = None
for f in [file_name_1, file_name_2]:
for ending in ['.ccp4', '.mrc', '.map']:
if f.endswith(ending):
map_file_name = f
for ending in ['.pdb', '.cif']:
if f.endswith(ending):
model_file_name = f
if not map_file_name or not model_file_name:
raise Sorry("Unable to identify map and model from %s and %s" %
(file_name_1, file_name_2))
from iotbx.data_manager import DataManager
from iotbx.map_model_manager import map_model_manager
dm = DataManager()
dm.process_real_map_file(map_file_name)
mm = dm.get_real_map(map_file_name)
dm.process_model_file(model_file_name)
model = dm.get_model(model_file_name)
mam = map_model_manager(model=model, map_manager=mm)
return mam
def test_default_filenames():
datatypes = [
'model', 'ncs_spec', 'phil', 'real_map', 'restraint', 'sequence'
]
extensions = ['cif', 'ncs_spec', 'eff', 'mrc', 'cif', 'seq']
dm = DataManager(datatypes)
for datatype, extension in zip(datatypes, extensions):
filename = getattr(
dm, 'get_default_output_{datatype}_filename'.format(
datatype=datatype))()
assert filename == 'cctbx_program.' + extension
filename = dm.get_default_output_model_filename(extension='.abc')
assert filename == 'cctbx_program.abc'
def exercise_ss_creation_crash():
pdb_str = """
CRYST1 145.350 135.090 157.320 90.00 90.00 90.00 P 1
SCALE1 0.006880 0.000000 0.000000 0.00000
SCALE2 0.000000 0.007402 0.000000 0.00000
SCALE3 0.000000 0.000000 0.006356 0.00000
ATOM 1 N ASN A 1 47.095 160.279 31.220 1.00 30.00 N
ATOM 2 CA ASN A 1 65.985 120.233 34.727 1.00 30.00 C
ATOM 3 C ASN A 1 56.657 138.700 33.374 1.00 30.00 C
ATOM 4 O ASN A 1 56.353 138.977 34.561 1.00 30.00 O
ATOM 5 CB ASN A 1 65.238 120.133 36.068 1.00 30.00 C
ATOM 6 CG ASN A 1 66.087 119.360 37.057 1.00 30.00 C
ATOM 7 OD1 ASN A 1 65.746 118.217 37.441 1.00 30.00 O
ATOM 8 ND2 ASN A 1 67.240 119.920 37.395 1.00 30.00 N
ATOM 9 N ASN A 2 56.939 137.441 33.021 1.00 30.00 N
ATOM 10 CA ASN A 2 67.135 117.384 35.354 1.00 30.00 C
ATOM 11 C ASN A 2 74.935 104.398 35.546 1.00 30.00 C
ATOM 12 O ASN A 2 74.423 104.166 34.444 1.00 30.00 O
ATOM 13 CB ASN A 2 65.828 116.703 35.809 1.00 30.00 C
ATOM 14 CG ASN A 2 66.092 115.518 36.718 1.00 30.00 C
ATOM 15 OD1 ASN A 2 66.641 114.515 36.266 1.00 30.00 O
ATOM 16 ND2 ASN A 2 65.744 115.556 38.000 1.00 30.00 N
ATOM 17 N ASN A 3 76.102 103.886 35.920 1.00 30.00 N
ATOM 18 CA ASN A 3 68.960 115.076 35.163 1.00 30.00 C
ATOM 19 C ASN A 3 86.047 90.376 35.591 1.00 30.00 C
ATOM 20 O ASN A 3 87.134 90.903 35.535 1.00 30.00 O
ATOM 21 CB ASN A 3 70.251 115.882 34.903 1.00 30.00 C
ATOM 22 CG ASN A 3 71.023 116.208 36.192 1.00 30.00 C
ATOM 23 OD1 ASN A 3 70.637 117.096 36.957 1.00 30.00 O
ATOM 24 ND2 ASN A 3 72.106 115.481 36.436 1.00 30.00 N
ATOM 25 OXT ASN A 3 85.912 89.104 36.045 1.00 30.00 O
TER
END
"""
with open("exercise_ss_creation_crash_model.pdb","w") as fo:
fo.write(pdb_str)
from iotbx.data_manager import DataManager
dm=DataManager()
params = mmtbx.model.manager.get_default_pdb_interpretation_params()
params.pdb_interpretation.secondary_structure.enabled=True
model = dm.get_model('exercise_ss_creation_crash_model.pdb')
model.set_pdb_interpretation_params(params)
model.process_input_model(make_restraints=True)
def run(prefix="tst_00_mmtbx_building_ligands"):
# Ligand file
with open("%s.pdb"%prefix,"w") as fo:
fo.write(pdb_str)
# Read map and model
from iotbx.data_manager import DataManager
dm = DataManager()
map_file = libtbx.env.find_in_repositories(
relative_path="mmtbx/building/ligands/tst_00_mmtbx_building_ligands.map",
test=os.path.isfile)
mm = dm.get_real_map(map_file)
model = dm.get_model("%s.pdb"%prefix)
model.set_crystal_symmetry(mm.crystal_symmetry())
model.process(make_restraints=True)
# Create map_model_manager
mmm = iotbx.map_model_manager.map_model_manager(map_manager=mm, model=model)
# Build ligand
o = ligands.lifi.run(map_model_manager = mmm, d_min = 2.5)
def read_model(filename):
from iotbx.data_manager import DataManager
dm = DataManager()
dm.set_overwrite(True)
dm.process_model_file(filename)
model = dm.get_model(filename)
model.add_crystal_symmetry_if_necessary()
return model
def read_map_and_model(file_name_1,
file_name_2,
regression_directory=None,
prefix=None):
'''
Identify which file is map and which is model, read in and
create map_model_manager
If regression_directory is specified, look there for these files, assuming
prefix of $PHENIX/modules/phenix_regression/
'''
if regression_directory and not prefix:
import libtbx.load_env
prefix = libtbx.env.under_dist(module_name="phenix_regression",
path=regression_directory,
test=os.path.isdir)
if prefix:
file_name_1 = os.path.join(prefix, file_name_1)
file_name_2 = os.path.join(prefix, file_name_2)
map_file_name = None
model_file_name = None
for f in [file_name_1, file_name_2]:
for ending in ['.ccp4', '.mrc', '.map']:
if f.endswith(ending):
map_file_name = f
for ending in ['.pdb', '.cif']:
if f.endswith(ending):
model_file_name = f
if not map_file_name or not model_file_name:
raise Sorry("Unable to guess map and model from %s and %s" %
(file_name_1, file_name_2))
from iotbx.data_manager import DataManager
from iotbx.map_model_manager import map_model_manager
dm = DataManager()
dm.process_real_map_file(map_file_name)
mm = dm.get_real_map(map_file_name)
dm.process_model_file(model_file_name)
model = dm.get_model(model_file_name)
mam = map_model_manager(model=model, map_manager=mm)
return mam
def run(args):
show_citation()
if (len(args) != 1):
raise Sorry("Need to provide CCP4 formatted map file.")
# map
dm = DataManager()
dm.set_overwrite(True)
map_manager = dm.get_real_map(args[0])
map_manager.shift_origin()
cs = map_manager.crystal_symmetry()
m = map_manager.map_data().as_double()
# show general statistics
show_overall_statistics(m=m, header="Map basic info (%s):" % args[0])
# HE
m_he = maptbx.volume_scale(map=m, n_bins=10000).map_data()
show_overall_statistics(m=m_he, header="Rank-scaled (HE) map info:")
#
file_name = args[0] + "_rank_scaled.ccp4"
he_map_manager = map_manager.customized_copy(map_data=m_he)
he_map_manager.add_label("Histogram-equalized map")
dm.write_real_map_file(he_map_manager, file_name)
def test_sequence_datatype():
# 1sar.fa
seq_filename = 'test_seq.fa'
seq_str = '''>1SAR A
DVSGTVCLSALPPEATDTLNLIASDGPFPYSQDGVVFQNRESVLPTQSYGYYHEYTVITPGARTRGTRRIICGEATQEDY
YTGDHYATFSLIDQTC
'''
with open(seq_filename, 'w') as f:
f.write(seq_str)
dm = DataManager(['sequence'])
dm.process_sequence_file(seq_filename)
assert seq_filename in dm.get_sequence_names()
seq = dm.get_sequence()
new_str = dm.get_sequence_as_string(seq_filename)
for a, b in zip(new_str, seq_str):
assert a == b
os.remove(seq_filename)
def test_model_and_restraint():
# from 3tpj
model_str = '''
CRYST1 104.428 128.690 76.662 90.00 90.00 90.00 C 2 2 21
ATOM 5877 O URE A 403 -37.796 -38.296 5.693 1.00 15.43 O
ATOM 5878 C URE A 403 -36.624 -38.509 5.800 1.00 20.53 C
ATOM 5879 N2 URE A 403 -36.191 -39.836 6.120 1.00 27.82 N
ATOM 5880 N1 URE A 403 -35.679 -37.450 5.644 1.00 21.36 N
ATOM 5881 HN11 URE A 403 -34.792 -37.617 5.732 1.00 25.63 H
ATOM 5882 HN12 URE A 403 -35.965 -36.613 5.445 1.00 25.63 H
ATOM 5883 HN21 URE A 403 -35.307 -40.015 6.211 1.00 33.38 H
ATOM 5884 HN22 URE A 403 -36.801 -40.499 6.221 1.00 33.38 H
'''
restraint_str = '''
#
data_comp_list
loop_
_chem_comp.id
_chem_comp.three_letter_code
_chem_comp.name
_chem_comp.group
_chem_comp.number_atoms_all
_chem_comp.number_atoms_nh
_chem_comp.desc_level
URE URE Unknown ligand 8 4 .
#
data_comp_URE
#
loop_
_chem_comp_atom.comp_id
_chem_comp_atom.atom_id
_chem_comp_atom.type_symbol
_chem_comp_atom.type_energy
_chem_comp_atom.partial_charge
_chem_comp_atom.x
_chem_comp_atom.y
_chem_comp_atom.z
URE C C C . 0.4968 -0.0000 -0.0000
URE O O O . 1.7184 -0.0000 -0.0000
URE N1 N NH2 . -0.2180 -0.0000 1.2381
URE N2 N NH2 . -0.2180 0.0000 -1.2381
URE HN11 H HNH2 . 0.2355 -0.0000 2.0237
URE HN12 H HNH2 . -1.1251 0.0000 1.2382
URE HN21 H HNH2 . 0.2355 0.0000 -2.0237
URE HN22 H HNH2 . -1.1251 -0.0000 -1.2382
#
loop_
_chem_comp_bond.comp_id
_chem_comp_bond.atom_id_1
_chem_comp_bond.atom_id_2
_chem_comp_bond.type
_chem_comp_bond.value_dist
_chem_comp_bond.value_dist_esd
URE C O double 1.222 0.020
URE C N1 single 1.430 0.020
URE C N2 single 1.430 0.020
URE N1 HN11 single 0.907 0.020
URE N1 HN12 single 0.907 0.020
URE N2 HN21 single 0.907 0.020
URE N2 HN22 single 0.907 0.020
#
loop_
_chem_comp_angle.comp_id
_chem_comp_angle.atom_id_1
_chem_comp_angle.atom_id_2
_chem_comp_angle.atom_id_3
_chem_comp_angle.value_angle
_chem_comp_angle.value_angle_esd
URE N2 C N1 120.00 3.000
URE N2 C O 120.00 3.000
URE N1 C O 120.00 3.000
URE HN12 N1 HN11 120.00 3.000
URE HN12 N1 C 120.00 3.000
URE HN11 N1 C 120.00 3.000
URE HN22 N2 HN21 120.00 3.000
URE HN22 N2 C 120.00 3.000
URE HN21 N2 C 120.00 3.000
#
loop_
_chem_comp_tor.comp_id
_chem_comp_tor.id
_chem_comp_tor.atom_id_1
_chem_comp_tor.atom_id_2
_chem_comp_tor.atom_id_3
_chem_comp_tor.atom_id_4
_chem_comp_tor.value_angle
_chem_comp_tor.value_angle_esd
_chem_comp_tor.period
URE CONST_01 HN11 N1 C O 0.00 0.0 0
URE CONST_02 HN12 N1 C O 180.00 0.0 0
URE CONST_03 HN21 N2 C O -0.00 0.0 0
URE CONST_04 HN22 N2 C O 180.00 0.0 0
URE CONST_05 HN21 N2 C N1 180.00 0.0 0
URE CONST_06 HN22 N2 C N1 -0.00 0.0 0
URE CONST_07 HN11 N1 C N2 -180.00 0.0 0
URE CONST_08 HN12 N1 C N2 -0.00 0.0 0
#
loop_
_chem_comp_plane_atom.comp_id
_chem_comp_plane_atom.plane_id
_chem_comp_plane_atom.atom_id
_chem_comp_plane_atom.dist_esd
URE plan-1 C 0.020
URE plan-1 O 0.020
URE plan-1 N1 0.020
URE plan-1 N2 0.020
URE plan-1 HN11 0.020
URE plan-1 HN12 0.020
URE plan-1 HN21 0.020
URE plan-1 HN22 0.020
'''
model_filename = 'ure.pdb'
restraint_filename = 'ure.cif'
dm = DataManager(['model', 'restraint'])
dm.write_model_file(model_str, filename=model_filename, overwrite=True)
dm.write_restraint_file(restraint_str,
filename=restraint_filename,
overwrite=True)
# fails because no restraints are loaded
dm.process_model_file(model_filename)
model = dm.get_model()
try:
model.get_restraints_manager()
except Sorry:
pass
# automatically add restraints
dm.process_restraint_file(restraint_filename)
model = dm.get_model()
model.get_restraints_manager()
os.remove(model_filename)
os.remove(restraint_filename)
def test_01():
data_dir = os.path.dirname(os.path.abspath(__file__))
data_ccp4 = os.path.join(data_dir, 'data',
'non_zero_origin_map.ccp4')
data_pdb = os.path.join(data_dir, 'data',
'non_zero_origin_map.ccp4')
dm = DataManager(['miller_array','real_map', 'phil'])
dm.set_overwrite(True)
dm.process_real_map_file(data_ccp4)
# test writing and reading file
mm = dm.get_real_map()
mm.shift_origin()
mm.show_summary()
dm.write_map_with_map_manager(mm, filename='test_map_manager.ccp4', overwrite=True)
# get map_data
map_data=mm.map_data()
assert approx_equal(map_data[15,10,19], 0.38,eps=0.01)
# get crystal_symmetry
cs=mm.crystal_symmetry()
assert approx_equal(cs.unit_cell().parameters()[0] ,22.41,eps=0.01)
# and full cell symmetry
full_cs=mm.unit_cell_crystal_symmetry()
assert approx_equal(full_cs.unit_cell().parameters()[0] ,149.4066,eps=0.01)
# write map directly:
mm.write_map('test_direct.ccp4')
# read back directly
new_mm=map_manager('test_direct.ccp4')
assert (not new_mm.is_similar(mm))
new_mm.shift_origin()
assert mm.is_similar(new_mm)
# deep_copy
new_mm=mm.deep_copy()
assert new_mm.is_similar(mm)
# customized_copy
new_mm=mm.customized_copy(map_data=mm.map_data().deep_copy())
assert new_mm.is_similar(mm)
# Initialize with parameters
mm_para=map_manager(
unit_cell_grid= mm.unit_cell_grid,
unit_cell_crystal_symmetry= mm.unit_cell_crystal_symmetry(),
origin_shift_grid_units= mm.origin_shift_grid_units,
map_data=mm.map_data())
assert mm_para.is_similar(mm)
# Adjust origin and gridding:
mm_read=map_manager(data_ccp4)
mm_read.set_origin_and_gridding((10,10,10),gridding=(100,100,100))
assert (not mm_read.is_similar(mm))
assert (not mm_read.already_shifted())
# Adjust origin and gridding should fail if origin already shifted:
mm_read=map_manager(data_ccp4)
mm_read.shift_origin()
mm_read.set_origin_and_gridding((10,10,10),gridding=(100,100,100))
assert (mm_read.is_similar(mm)) # not shifted as it failed
assert (mm_read.already_shifted())
# Set input_file name
mm_read.set_input_file_name('test input_file')
assert mm_read.input_file_name=='test input_file'
# Set program name
mm_read.set_program_name('test program')
assert mm_read.program_name=='test program'
# Set limitation
mm_read.add_limitation('map_is_sharpened')
assert mm_read.limitations==['map_is_sharpened']
# Add a label
mm_read.add_label('TEST LABEL')
assert mm_read.labels[0]=='TEST LABEL'
mm_read.write_map('map_with_labels.mrc')
new_mm=map_manager('map_with_labels.mrc')
assert 'TEST LABEL' in new_mm.labels
assert new_mm.is_in_limitations('map_is_sharpened')
assert new_mm.labels[0].find('test program')>-1
# Read a map directly
mm_read=map_manager(data_ccp4)
mm_read.shift_origin()
assert mm_read.is_similar(mm)
# Set log
import sys
mm.set_log(sys.stdout)
# Add map_data
mm_read.replace_map_data(map_data=mm.map_data().deep_copy())
assert mm_read.is_similar(mm)
dm.process_real_map_file('test_map_manager.ccp4')
new_mm=dm.get_real_map('test_map_manager.ccp4')
new_mm.show_summary()
assert (not new_mm.is_similar(mm))
new_mm.shift_origin()
new_mm.show_summary()
assert new_mm.is_similar(mm)
os.remove('test_map_manager.ccp4')
# Convert to map coeffs, write out, read back, convert back to map
map_coeffs = mm.map_as_fourier_coefficients(high_resolution = 3)
mtz_dataset = map_coeffs.as_mtz_dataset(column_root_label='F')
mtz_object=mtz_dataset.mtz_object()
dm.write_miller_array_file(mtz_object, filename="map_coeffs.mtz")
# Note these Fourier coeffs correspond to working map (not original position)
array_labels=dm.get_miller_array_labels("map_coeffs.mtz")
labels=array_labels[0]
dm.get_reflection_file_server(filenames=["map_coeffs.mtz"],labels=[labels])
miller_arrays=dm.get_miller_arrays()
new_map_coeffs=miller_arrays[0]
map_data_from_map_coeffs=mm.fourier_coefficients_as_map(
map_coeffs=new_map_coeffs)
mm_from_map_coeffs=mm.customized_copy(map_data=map_data_from_map_coeffs)
assert mm_from_map_coeffs.is_similar(mm)
def test_model_datatype():
import mmtbx.monomer_library.server
try:
mon_lib_srv = mmtbx.monomer_library.server.server()
except mmtbx.monomer_library.server.MonomerLibraryServerError:
print(
"Can not initialize monomer_library, skipping test_model_datatype."
)
return
# 1yjp
model_str = '''
CRYST1 21.937 4.866 23.477 90.00 107.08 90.00 P 1 21 1 2
ORIGX1 1.000000 0.000000 0.000000 0.00000
ORIGX2 0.000000 1.000000 0.000000 0.00000
ORIGX3 0.000000 0.000000 1.000000 0.00000
SCALE1 0.045585 0.000000 0.014006 0.00000
SCALE2 0.000000 0.205508 0.000000 0.00000
SCALE3 0.000000 0.000000 0.044560 0.00000
ATOM 1 N GLY A 1 -9.009 4.612 6.102 1.00 16.77 N
ATOM 2 CA GLY A 1 -9.052 4.207 4.651 1.00 16.57 C
ATOM 3 C GLY A 1 -8.015 3.140 4.419 1.00 16.16 C
ATOM 4 O GLY A 1 -7.523 2.521 5.381 1.00 16.78 O
ATOM 5 N ASN A 2 -7.656 2.923 3.155 1.00 15.02 N
ATOM 6 CA ASN A 2 -6.522 2.038 2.831 1.00 14.10 C
ATOM 7 C ASN A 2 -5.241 2.537 3.427 1.00 13.13 C
ATOM 8 O ASN A 2 -4.978 3.742 3.426 1.00 11.91 O
ATOM 9 CB ASN A 2 -6.346 1.881 1.341 1.00 15.38 C
ATOM 10 CG ASN A 2 -7.584 1.342 0.692 1.00 14.08 C
ATOM 11 OD1 ASN A 2 -8.025 0.227 1.016 1.00 17.46 O
ATOM 12 ND2 ASN A 2 -8.204 2.155 -0.169 1.00 11.72 N
ATOM 13 N ASN A 3 -4.438 1.590 3.905 1.00 12.26 N
ATOM 14 CA ASN A 3 -3.193 1.904 4.589 1.00 11.74 C
ATOM 15 C ASN A 3 -1.955 1.332 3.895 1.00 11.10 C
ATOM 16 O ASN A 3 -1.872 0.119 3.648 1.00 10.42 O
ATOM 17 CB ASN A 3 -3.259 1.378 6.042 1.00 12.15 C
ATOM 18 CG ASN A 3 -2.006 1.739 6.861 1.00 12.82 C
ATOM 19 OD1 ASN A 3 -1.702 2.925 7.072 1.00 15.05 O
ATOM 20 ND2 ASN A 3 -1.271 0.715 7.306 1.00 13.48 N
ATOM 21 N GLN A 4 -1.005 2.228 3.598 1.00 10.29 N
ATOM 22 CA GLN A 4 0.384 1.888 3.199 1.00 10.53 C
ATOM 23 C GLN A 4 1.435 2.606 4.088 1.00 10.24 C
ATOM 24 O GLN A 4 1.547 3.843 4.115 1.00 8.86 O
ATOM 25 CB GLN A 4 0.656 2.148 1.711 1.00 9.80 C
ATOM 26 CG GLN A 4 1.944 1.458 1.213 1.00 10.25 C
ATOM 27 CD GLN A 4 2.504 2.044 -0.089 1.00 12.43 C
ATOM 28 OE1 GLN A 4 2.744 3.268 -0.190 1.00 14.62 O
ATOM 29 NE2 GLN A 4 2.750 1.161 -1.091 1.00 9.05 N
ATOM 30 N GLN A 5 2.154 1.821 4.871 1.00 10.38 N
ATOM 31 CA GLN A 5 3.270 2.361 5.640 1.00 11.39 C
ATOM 32 C GLN A 5 4.594 1.768 5.172 1.00 11.52 C
ATOM 33 O GLN A 5 4.768 0.546 5.054 1.00 12.05 O
ATOM 34 CB GLN A 5 3.056 2.183 7.147 1.00 11.96 C
ATOM 35 CG GLN A 5 1.829 2.950 7.647 1.00 10.81 C
ATOM 36 CD GLN A 5 1.344 2.414 8.954 1.00 13.10 C
ATOM 37 OE1 GLN A 5 0.774 1.325 9.002 1.00 10.65 O
ATOM 38 NE2 GLN A 5 1.549 3.187 10.039 1.00 12.30 N
ATOM 39 N ASN A 6 5.514 2.664 4.856 1.00 11.99 N
ATOM 40 CA ASN A 6 6.831 2.310 4.318 1.00 12.30 C
ATOM 41 C ASN A 6 7.854 2.761 5.324 1.00 13.40 C
ATOM 42 O ASN A 6 8.219 3.943 5.374 1.00 13.92 O
ATOM 43 CB ASN A 6 7.065 3.016 2.993 1.00 12.13 C
ATOM 44 CG ASN A 6 5.961 2.735 2.003 1.00 12.77 C
ATOM 45 OD1 ASN A 6 5.798 1.604 1.551 1.00 14.27 O
ATOM 46 ND2 ASN A 6 5.195 3.747 1.679 1.00 10.07 N
ATOM 47 N TYR A 7 8.292 1.817 6.147 1.00 14.70 N
ATOM 48 CA TYR A 7 9.159 2.144 7.299 1.00 15.18 C
ATOM 49 C TYR A 7 10.603 2.331 6.885 1.00 15.91 C
ATOM 50 O TYR A 7 11.041 1.811 5.855 1.00 15.76 O
ATOM 51 CB TYR A 7 9.061 1.065 8.369 1.00 15.35 C
ATOM 52 CG TYR A 7 7.665 0.929 8.902 1.00 14.45 C
ATOM 53 CD1 TYR A 7 6.771 0.021 8.327 1.00 15.68 C
ATOM 54 CD2 TYR A 7 7.210 1.756 9.920 1.00 14.80 C
ATOM 55 CE1 TYR A 7 5.480 -0.094 8.796 1.00 13.46 C
ATOM 56 CE2 TYR A 7 5.904 1.649 10.416 1.00 14.33 C
ATOM 57 CZ TYR A 7 5.047 0.729 9.831 1.00 15.09 C
ATOM 58 OH TYR A 7 3.766 0.589 10.291 1.00 14.39 O
ATOM 59 OXT TYR A 7 11.358 2.999 7.612 1.00 17.49 O
TER 60 TYR A 7
HETATM 61 O HOH A 8 -6.471 5.227 7.124 1.00 22.62 O
HETATM 62 O HOH A 9 10.431 1.858 3.216 1.00 19.71 O
HETATM 63 O HOH A 10 -11.286 1.756 -1.468 1.00 17.08 O
HETATM 64 O HOH A 11 11.808 4.179 9.970 1.00 23.99 O
HETATM 65 O HOH A 12 13.605 1.327 9.198 1.00 26.17 O
HETATM 66 O HOH A 13 -2.749 3.429 10.024 1.00 39.15 O
HETATM 67 O HOH A 14 -1.500 0.682 10.967 1.00 43.49 O
MASTER 238 0 0 0 0 0 0 6 66 1 0 1
END
'''
# test reading/writing PDB
test_filename = 'test_model.pdb'
test_output_filename = 'test_model_output.pdb'
test_eff = 'model.eff'
dm = DataManager(['model'])
dm.process_model_str(test_filename, model_str)
dm.write_model_file(model_str,
filename=test_output_filename,
overwrite=True)
m = dm.get_model(test_output_filename)
assert test_output_filename in dm.get_model_names()
dm.write_model_file(m, overwrite=True)
pdb_filename = 'cctbx_program.pdb'
assert os.path.exists(pdb_filename)
dm.process_model_file(pdb_filename)
assert not dm.get_model(pdb_filename).input_model_format_cif()
dm.write_model_file(m, test_filename, overwrite=True)
# test reading PDB writing CIF
test_filename = 'test_model.pdb'
test_output_filename = 'test_model.cif'
dm = DataManager(['model'])
dm.process_model_str(test_filename, model_str)
m = dm.get_model(test_filename)
dm.write_model_file(m,
filename=test_output_filename,
format='cif',
overwrite=True)
m = dm.get_model(test_output_filename)
assert test_output_filename in dm.get_model_names()
dm.write_model_file(m, overwrite=True)
cif_filename = 'cctbx_program.cif'
assert os.path.exists(cif_filename)
dm.process_model_file(cif_filename)
assert dm.get_model(cif_filename).input_model_format_cif()
# test type
assert dm.get_model_type() == 'x_ray'
dm.set_model_type(test_filename, 'neutron')
assert dm.get_model_type() == 'neutron'
phil_scope = dm.export_phil_scope()
extract = phil_scope.extract()
assert extract.data_manager.model[0].type == 'neutron'
with open(test_eff, 'w') as f:
f.write(phil_scope.as_str())
new_phil_scope = iotbx.phil.parse(file_name=test_eff)
new_dm = DataManager(['model'])
new_dm.load_phil_scope(new_phil_scope)
assert new_dm.get_model_type(test_filename) == 'neutron'
new_dm = DataManager(['model'])
try:
new_dm.set_default_model_type('nonsense')
except Sorry:
pass
new_dm.set_default_model_type('electron')
new_dm.process_model_file(test_filename)
assert new_dm.get_model_type() == 'electron'
assert len(new_dm.get_model_names()) == 1
assert len(new_dm.get_model_names(model_type='electron')) == 1
assert len(new_dm.get_model_names(model_type='neutron')) == 0
os.remove(test_eff)
os.remove(test_filename)
# test reading/writing CIF
test_filename = 'test_model_datatype.cif'
dm.write_model_file(dm.get_model().model_as_mmcif(),
filename=test_filename,
overwrite=True)
dm.process_model_file(test_filename)
os.remove(test_filename)
assert test_filename in dm.get_model_names()
m = dm.get_model(test_filename)
dm.write_model_file(m, overwrite=True)
cif_filename = 'cctbx_program.cif'
assert os.path.exists(cif_filename)
dm.process_model_file(cif_filename)
assert dm.get_model(cif_filename).input_model_format_cif()
os.remove(pdb_filename)
os.remove(cif_filename)
# test pdb_interpretation
extract = mmtbx.model.manager.get_default_pdb_interpretation_params()
extract.pdb_interpretation.use_neutron_distances = True
dm.update_pdb_interpretation_for_model(test_filename, extract)
assert dm.get_model(test_filename).restraints_manager is None
def test_data_manager():
a = DataManager(['model'])
a.add_model('a', 'b')
a.add_model('c', 'd')
assert a.get_model() == 'b'
assert a.get_model('a') == 'b'
assert a.get_model('c') == 'd'
assert a.get_model_names() == ['a', 'c']
assert a.has_models()
assert a.has_models(exact_count=True, expected_n=2)
assert not a.has_models(expected_n=3, raise_sorry=False)
# exporting phil
working_phil = a.export_phil_scope()
assert len(working_phil.extract().data_manager.model) == 2
# data tracking
try:
a.has_models(expected_n=3, raise_sorry=True)
except Sorry:
pass
try:
a.has_models(exact_count=True, raise_sorry=True)
except Sorry:
pass
a.set_default_model('c')
assert a.get_model() == 'd'
assert a.get_model_names() == ['a', 'c'
] or a.get_model_names() == ['c', 'a']
a.remove_model('c')
try:
a.get_model()
except Sorry:
pass
try:
a.get_model('missing')
except Sorry:
pass
try:
a.set_default_model('missing')
except Sorry:
pass
a = DataManager(datatypes=['sequence', 'phil'])
assert a.get_sequence_names() == []
assert not hasattr(a, 'get_model')
# phil functions
test_phil_str = '''
data_manager {
phil_files = data_manager_test.eff
}
'''
with open('data_manager_test.eff', 'w') as f:
f.write(test_phil_str)
# loading file with get function
assert len(a.get_phil_names()) == 0
p = a.get_phil('data_manager_test.eff')
assert type(p) == libtbx.phil.scope
assert 'data_manager_test.eff' in a.get_phil_names()
# loading file with phil
a = DataManager(datatypes=['phil'])
test_phil = iotbx.phil.parse(test_phil_str)
a.load_phil_scope(test_phil)
assert 'data_manager_test.eff' in a.get_phil_names()
assert a.get_default_phil_name() == 'data_manager_test.eff'
os.remove('data_manager_test.eff')
# writing
a = DataManager(datatypes=['model', 'phil', 'sequence'])
a.add_model('a', 'b')
a.add_phil('c', 'd')
a.add_sequence('e', 'f')
a.write_model_file(a.get_model(), filename='a.dat', overwrite=True)
a.write_phil_file(a.get_phil(), filename='c.dat', overwrite=True)
a.write_sequence_file(a.get_sequence(), filename='e.dat', overwrite=True)
with open('a.dat', 'r') as f:
lines = f.readlines()
assert lines[0] == 'b'
os.remove('a.dat')
os.remove('c.dat')
os.remove('e.dat')
def exercise(file_name=None, pdb_file_name = None, map_file_name = None ,
split_pdb_file_name = None,
out = sys.stdout):
# Set up source data
if not os.path.isfile(file_name):
raise Sorry("Missing the file: %s" %(file_name)+"\n")
print ("Reading from %s" %(file_name))
from iotbx.map_manager import map_manager
m = map_manager(file_name)
print ("Header information from %s:" %(file_name))
m.show_summary(out = out)
map_data = m.map_data().deep_copy()
crystal_symmetry = m.crystal_symmetry()
unit_cell_parameters = m.crystal_symmetry().unit_cell().parameters()
print ("\nMap origin: %s Extent %s" %( map_data.origin(), map_data.all()))
print ("Original unit cell, not just unit cell of part in this file): %s" %(
str(unit_cell_parameters)))
grid_point = (1, 2, 3)
if map_data.origin() != (0, 0, 0): # make sure it is inside
from scitbx.matrix import col
grid_point = tuple (col(grid_point)+col(map_data.origin()))
print ("\nValue of map_data at grid point %s: %.3f" %(str(grid_point),
map_data[grid_point]))
print ("Map data is %s" %(type(map_data)))
random_position = (10, 5, 7.9)
point_frac = crystal_symmetry.unit_cell().fractionalize(random_position)
value_at_point_frac = map_data.eight_point_interpolation(point_frac)
print ("Value of map_data at coordinates %s: %.3f" %(
str(random_position), value_at_point_frac))
map_data_as_float = map_data.as_float()
print ("Map data as float is %s" %(type(map_data_as_float)))
# make a little model
sites_cart = flex.vec3_double( ((8, 10, 12), (14, 15, 16)))
model = model_manager.from_sites_cart(
atom_name = ' CA ',
resname = 'ALA',
chain_id = 'A',
b_iso = 30.,
occ = 1.,
scatterer = 'C',
sites_cart = sites_cart,
crystal_symmetry = crystal_symmetry)
# Move map and a model to place origin at (0, 0, 0)
# map data is new copy but model is shifted in place.
from iotbx.map_model_manager import map_model_manager
mam = map_model_manager(
map_manager = m,
model = model.deep_copy(),
)
# Read in map and model and split up
dm = DataManager()
aa = dm.get_map_model_manager(model_file=pdb_file_name,
map_files=map_file_name)
bb = dm.get_map_model_manager(model_file=split_pdb_file_name,
map_files=map_file_name)
for selection_method in ['by_chain', 'by_segment','supplied_selections',
'boxes']:
if selection_method == 'boxes':
choices = [True, False]
else:
choices = [True]
if selection_method == 'by_chain':
mask_choices = [True,False]
else:
mask_choices = [False]
for select_final_boxes_based_on_model in choices:
for skip_empty_boxes in choices:
for mask_choice in mask_choices:
if mask_choice: # use split model
a=bb.deep_copy()
else: # usual
a=aa.deep_copy()
print ("\nRunning split_up_map_and_model with \n"+
"select_final_boxes_based_on_model="+
"%s skip_empty_boxes=%s selection_method=%s" %(
select_final_boxes_based_on_model,skip_empty_boxes,selection_method))
if selection_method == 'by_chain':
print ("Mask around unused atoms: %s" %(mask_choice))
box_info = a.split_up_map_and_model_by_chain(
mask_around_unselected_atoms=mask_choice)
elif selection_method == 'by_segment':
box_info = a.split_up_map_and_model_by_segment()
elif selection_method == 'supplied_selections':
selection = a.model().selection('all')
box_info = a.split_up_map_and_model_by_supplied_selections(
selection_list = [selection])
elif selection_method == 'boxes':
box_info = a.split_up_map_and_model_by_boxes(
skip_empty_boxes = skip_empty_boxes,
select_final_boxes_based_on_model =
select_final_boxes_based_on_model)
print (selection_method,skip_empty_boxes,
len(box_info.selection_list),
box_info.selection_list[0].count(True))
assert (selection_method,skip_empty_boxes,
len(box_info.selection_list),
box_info.selection_list[0].count(True)) in [
('by_chain',True,3,19),
("by_chain",True,1,86,),
("by_segment",True,1,86,),
("supplied_selections",True,1,86,),
("boxes",True,13,1,),
("boxes",False,36,0,),
("boxes",True,13,1,),
("boxes",False,36,0,),
]
# Change the coordinates in one box
small_model = box_info.mmm_list[0].model()
small_sites_cart = small_model.get_sites_cart()
from scitbx.matrix import col
small_sites_cart += col((1,0,0))
small_model.set_crystal_symmetry_and_sites_cart(
sites_cart = small_sites_cart,
crystal_symmetry = small_model.crystal_symmetry())
# Put everything back together
a.merge_split_maps_and_models(box_info = box_info)
mam.box_all_maps_around_model_and_shift_origin()
shifted_crystal_symmetry = mam.model().crystal_symmetry()
shifted_model = mam.model()
shifted_map_data = mam.map_data()
print ("\nOriginal map origin (grid units):", map_data.origin())
print ("Original model:\n", model.model_as_pdb())
print ("Shifted map origin:", shifted_map_data.origin())
print ("Shifted model:\n", shifted_model.model_as_pdb())
# Save the map_model manager
mam_dc=mam.deep_copy()
print ("dc",mam)
print ("dc mam_dc",mam_dc)
# Mask map around atoms
mam=mam_dc.deep_copy()
print ("dc mam_dc dc",mam_dc)
print (mam)
mam.mask_all_maps_around_atoms(mask_atoms_atom_radius = 3,
set_outside_to_mean_inside=True, soft_mask=False)
print ("Mean before masking", mam.map_data().as_1d().min_max_mean().mean)
assert approx_equal(mam.map_data().as_1d().min_max_mean().mean,
-0.0585683621466)
print ("Max before masking", mam.map_data().as_1d().min_max_mean().max)
assert approx_equal(mam.map_data().as_1d().min_max_mean().max,
-0.0585683621466)
# Mask map around atoms, with soft mask
mam=mam_dc.deep_copy()
mam.mask_all_maps_around_atoms(mask_atoms_atom_radius = 3, soft_mask = True,
soft_mask_radius = 5, set_outside_to_mean_inside=True)
print ("Mean after first masking", mam.map_data().as_1d().min_max_mean().mean)
assert approx_equal(mam.map_data().as_1d().min_max_mean().mean,
-0.00177661714805)
print ("Max after first masking", mam.map_data().as_1d().min_max_mean().max)
assert approx_equal(mam.map_data().as_1d().min_max_mean().max,
0.236853733659)
# Mask map around atoms again
mam.mask_all_maps_around_atoms(mask_atoms_atom_radius = 3,
set_outside_to_mean_inside = True, soft_mask=False)
print ("Mean after second masking", mam.map_data().as_1d().min_max_mean().mean)
assert approx_equal(mam.map_data().as_1d().min_max_mean().mean,
-0.0585683621466)
print ("Max after second masking", mam.map_data().as_1d().min_max_mean().max)
assert approx_equal(mam.map_data().as_1d().min_max_mean().max,
-0.0585683621466)
# Mask around edges
mam=mam_dc.deep_copy()
mam.mask_all_maps_around_edges( soft_mask_radius = 3)
print ("Mean after masking edges", mam.map_data().as_1d().min_max_mean().mean)
assert approx_equal(mam.map_data().as_1d().min_max_mean().mean,
0.0155055604192)
print ("Max after masking edges", mam.map_data().as_1d().min_max_mean().max)
assert approx_equal(mam.map_data().as_1d().min_max_mean().max,
0.249827131629)
print ("\nWriting map_data and model in shifted position (origin at 0, 0, 0)")
output_file_name = 'shifted_map.ccp4'
print ("Writing to %s" %(output_file_name))
mrcfile.write_ccp4_map(
file_name = output_file_name,
crystal_symmetry = shifted_crystal_symmetry,
map_data = shifted_map_data, )
output_file_name = 'shifted_model.pdb'
f = open(output_file_name, 'w')
print (shifted_model.model_as_pdb(), file=f)
f.close()
print ("\nWriting map_data and model in original position (origin at %s)" %(
str(mam.map_manager().origin_shift_grid_units)))
output_file_name = 'new_map_original_position.ccp4'
print ("Writing to %s" %(output_file_name))
mrcfile.write_ccp4_map(
file_name = output_file_name,
crystal_symmetry = shifted_crystal_symmetry,
map_data = shifted_map_data,
origin_shift_grid_units = mam.map_manager().origin_shift_grid_units)
print (shifted_model.model_as_pdb())
output_pdb_file_name = 'new_model_original_position.pdb'
f = open(output_pdb_file_name, 'w')
print (shifted_model.model_as_pdb(), file=f)
f.close()
# Write as mmcif
output_cif_file_name = 'new_model_original_position.cif'
f = open(output_cif_file_name, 'w')
print (shifted_model.model_as_mmcif(),file = f)
f.close()
# Read the new map and model
import iotbx.pdb
new_model = model_manager(
model_input = iotbx.pdb.input(
source_info = None,
lines = flex.split_lines(open(output_pdb_file_name).read())),
crystal_symmetry = crystal_symmetry)
assert new_model.model_as_pdb() == model.model_as_pdb()
new_model_from_cif = model_manager(
model_input = iotbx.pdb.input(
source_info = None,
lines = flex.split_lines(open(output_cif_file_name).read())),
crystal_symmetry = crystal_symmetry)
assert new_model_from_cif.model_as_pdb() == model.model_as_pdb()
# Read and box the original file again in case we modified m in any
# previous tests
m = map_manager(file_name)
mam=map_model_manager(model=model.deep_copy(),map_manager=m)
mam.box_all_maps_around_model_and_shift_origin()
file_name = output_file_name
print ("Reading from %s" %(file_name))
new_map = iotbx.mrcfile.map_reader(file_name = file_name, verbose = False)
new_map.data = new_map.data.shift_origin()
print ("Header information from %s:" %(file_name))
new_map.show_summary(out = out)
assert new_map.map_data().origin() == mam.map_manager().map_data().origin()
assert new_map.crystal_symmetry().is_similar_symmetry(mam.map_manager().crystal_symmetry())
# make a map_model_manager with lots of maps and model and ncs
from mmtbx.ncs.ncs import ncs
ncs_object=ncs()
ncs_object.set_unit_ncs()
mam = map_model_manager(
map_manager = m,
ncs_object = ncs_object,
map_manager_1 = m.deep_copy(),
map_manager_2 = m.deep_copy(),
extra_model_list = [model.deep_copy(),model.deep_copy()],
extra_model_id_list = ["model_1","model_2"],
extra_map_manager_list = [m.deep_copy(),m.deep_copy()],
extra_map_manager_id_list = ["extra_1","extra_2"],
model = model.deep_copy(),
)
# make a map_model_manager with lots of maps and model and ncs and run
# with wrapping and ignore_symmetry_conflicts on
from mmtbx.ncs.ncs import ncs
ncs_object=ncs()
ncs_object.set_unit_ncs()
m.set_ncs_object(ncs_object.deep_copy())
mam2 = map_model_manager(
map_manager = m.deep_copy(),
ncs_object = ncs_object.deep_copy(),
map_manager_1 = m.deep_copy(),
map_manager_2 = m.deep_copy(),
extra_model_list = [model.deep_copy(),model.deep_copy()],
extra_model_id_list = ["model_1","model_2"],
extra_map_manager_list = [m.deep_copy(),m.deep_copy()],
extra_map_manager_id_list = ["extra_1","extra_2"],
model = model.deep_copy(),
ignore_symmetry_conflicts = True,
wrapping = m.wrapping(),
)
assert mam.map_manager().is_similar(mam2.map_manager())
assert mam.map_manager().is_similar(mam2.map_manager_1())
for m in mam2.map_managers():
assert mam.map_manager().is_similar(m)
assert mam.model().shift_cart() == mam2.model().shift_cart()
assert mam.model().shift_cart() == mam2.get_model_by_id('model_2').shift_cart()
print ("OK")
def exercise(file_name, out=sys.stdout):
# Set up source data
if not os.path.isfile(file_name):
raise Sorry("Missing the file: %s" % (file_name) + "\n")
print("Reading from %s" % (file_name))
from iotbx.map_manager import map_manager
m = map_manager(file_name)
# make a little model
sites_cart = flex.vec3_double(((8, 10, 12), (14, 15, 16)))
model = model_manager.from_sites_cart(
atom_name=' CA ',
resname='ALA',
chain_id='A',
b_iso=30.,
occ=1.,
scatterer='C',
sites_cart=sites_cart,
crystal_symmetry=m.crystal_symmetry())
# make a map_model_manager with lots of maps and model and ncs
from iotbx.map_model_manager import map_model_manager
from mmtbx.ncs.ncs import ncs
ncs_object = ncs()
ncs_object.set_unit_ncs()
mask_mm = m.deep_copy()
mask_mm.set_is_mask(True)
mam = map_model_manager(
map_manager=m,
ncs_object=ncs_object,
map_manager_1=m.deep_copy(),
map_manager_2=m.deep_copy(),
extra_map_manager_list=[m.deep_copy(),
m.deep_copy(),
m.deep_copy()],
extra_map_manager_id_list=["extra_1", "extra_2", "map_manager_mask"],
model=model.deep_copy(),
)
print(mam.map_manager())
print(mam.model())
print(mam.map_manager_1())
print(mam.map_manager_2())
print(mam.map_manager_mask())
print(mam.map_manager().ncs_object())
all_map_names = mam.map_id_list()
for id in all_map_names:
print("Map_manager %s: %s " % (id, mam.get_map_manager_by_id(id)))
dm = DataManager(['model', 'miller_array', 'real_map', 'phil', 'ncs_spec'])
dm.set_overwrite(True)
# Create a model with ncs
from iotbx.regression.ncs.tst_ncs import pdb_str_5
file_name = 'tst_mam.pdb'
f = open(file_name, 'w')
print(pdb_str_5, file=f)
f.close()
# Generate map data from this model (it has ncs)
mmm = map_model_manager()
mmm.generate_map(box_cushion=0, file_name=file_name, n_residues=500)
ncs_mam = mmm.deep_copy()
ncs_mam_copy = mmm.deep_copy()
# Make sure this model has 126 sites (42 sites times 3-fold ncs)
assert ncs_mam.model().get_sites_cart().size() == 126
assert approx_equal(ncs_mam.model().get_sites_cart()[0],
(23.560999999999996, 8.159, 10.660000000000002))
# Get just unique part (42 sites)
unique_mam = ncs_mam.extract_all_maps_around_model(
select_unique_by_ncs=True)
assert unique_mam.model().get_sites_cart().size() == 42
assert approx_equal(unique_mam.model().get_sites_cart()[0],
(18.740916666666664, 13.1794, 16.10544))
# Make sure that the extraction did not change the original but does change
# the extracted part
assert (unique_mam.model().get_sites_cart()[0] !=
ncs_mam.model().get_sites_cart()[0]
) # it was a deep copy so original stays
# Shift back the extracted part and make sure it matches the original now
shifted_back_unique_model = mmm.get_model_from_other(
unique_mam.deep_copy())
assert approx_equal(shifted_back_unique_model.get_sites_cart()[0],
(23.560999999999996, 8.158999999999997, 10.66))
# Change the extracted model
sites_cart = unique_mam.model().get_sites_cart()
sites_cart[0] = (1, 1, 1)
unique_mam.model().get_hierarchy().atoms().set_xyz(sites_cart)
# Note; setting xyz in hierarchy does not set xrs by itself. do that now:
unique_mam.model().set_sites_cart_from_hierarchy(multiply_ncs=False)
# Make sure we really changed it
assert approx_equal(unique_mam.model().get_sites_cart()[0], (1, 1, 1))
# Now propagate all the changes in this unique part to entire original model
# using NCS
ncs_mam.propagate_model_from_other(other=unique_mam,
model_id='model',
other_model_id='model')
# ...and check that copy 1 and copy 2 both change
assert approx_equal(
ncs_mam.model().get_sites_cart()[0],
(5.820083333333333, -4.020400000000001, -4.445440000000001))
assert approx_equal(
ncs_mam.model().get_sites_cart()[42],
(38.41904613024224, 17.233251085893276, 2.5547442135142524))
# Find ncs from map or model
nn = ncs_mam_copy
nn.write_map('ncs.ccp4')
nn.write_model('ncs.pdb')
ncs_object = nn.get_ncs_from_model()
dm.write_ncs_spec_file(ncs_object, 'ncs.ncs_spec')
print("NCS from map", ncs_object)
nn.set_ncs_object(ncs_object)
print("NCS now: ", nn.ncs_object())
nn.get_ncs_from_map(ncs_object=ncs_object)
print("ncs cc:", nn.ncs_cc())
assert approx_equal(nn.ncs_cc(), 0.961915979834, eps=0.01)
# Make a deep_copy
dc = mam.deep_copy()
new_mam = mam.deep_copy()
assert mam.map_manager().map_data()[0] == new_mam.map_manager().map_data(
)[0]
# Make a customized_copy
new_mam = mam.customized_copy(model_dict={'model': mam.model()})
assert new_mam.model() is mam.model()
assert not new_mam.map_dict() is mam.map_dict()
new_mam = mam.customized_copy(model_dict={'model': mam.model()},
map_dict=mam.map_dict())
assert new_mam.model() is mam.model()
assert new_mam.map_dict() is mam.map_dict()
print(mam)
# Add a map
mam = dc.deep_copy()
print(mam.map_id_list())
assert len(mam.map_id_list()) == 6
mam.add_map_manager_by_id(mam.map_manager().deep_copy(), 'new_map_manager')
print(mam.map_id_list())
assert len(mam.map_id_list()) == 7
# duplicate a map
mam = dc.deep_copy()
print(mam.map_id_list())
assert len(mam.map_id_list()) == 6
mam.duplicate_map_manager('map_manager', 'new_map_manager')
print(mam.map_id_list())
assert len(mam.map_id_list()) == 7
# resolution_filter a map
mam = dc.deep_copy()
print(mam.map_id_list())
mam.duplicate_map_manager('map_manager', 'new_map_manager')
mam.resolution_filter(map_id='new_map_manager', d_min=3.5, d_max=6)
# Add a model
mam = dc.deep_copy()
print(mam.model_id_list())
assert len(mam.model_id_list()) == 1
mam.add_model_by_id(mam.model().deep_copy(), 'new_model')
print(mam.model_id_list())
assert len(mam.model_id_list()) == 2
# Initialize a map
mam1 = new_mam.deep_copy()
mam1.initialize_maps(map_value=6)
assert mam1.map_manager().map_data()[225] == 6
# Create mask around density and apply to all maps
mam1 = new_mam.deep_copy()
mam1.mask_all_maps_around_density(
solvent_content=0.5,
soft_mask=True,
)
s = (mam1.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1024, 2048))
# Create mask around edges and apply to all maps
mam1 = new_mam.deep_copy()
mam1.mask_all_maps_around_edges()
s = (mam1.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1176, 2048))
# Create a soft mask around model and apply to all maps
new_mam.mask_all_maps_around_atoms(mask_atoms_atom_radius=8,
soft_mask=True)
s = (new_mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1944, 2048))
# Create a soft mask around model and do not do anything with it
new_mam.create_mask_around_atoms(mask_atoms_atom_radius=8, soft_mask=True)
s = (new_mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1944, 2048))
# Create a soft mask around model and do not do anything with it, wrapping =true
dummy_mam = new_mam.deep_copy()
dummy_mam.map_manager().set_wrapping(True)
dummy_mam.create_mask_around_atoms(mask_atoms_atom_radius=8,
soft_mask=True)
s = (dummy_mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1944, 2048))
# Create a sharp mask around model and do not do anything with it
new_mam.create_mask_around_atoms(soft_mask=False, mask_atoms_atom_radius=8)
s = (new_mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (138, 2048))
# Mask around edges and do not do anything with it
mam = dc.deep_copy()
mam.create_mask_around_edges()
s = (mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1176, 2048))
# Mask around density and to not do anything with it
mam = dc.deep_copy()
mam.create_mask_around_density(soft_mask=False)
s = (mam.get_map_manager_by_id('mask').map_data() > 0.5)
assert approx_equal((s.count(True), s.size()), (1000, 2048))
# Apply the current mask to one map
mam.apply_mask_to_map('map_manager')
s = (mam.map_manager().map_data() > 0.)
assert approx_equal((s.count(True), s.size()), (640, 2048))
s = (mam.map_manager().map_data() != 0.)
assert approx_equal((s.count(True), s.size()), (1000, 2048))
assert approx_equal((mam.map_manager().map_data()[225]), -0.0418027862906)
# Apply any mask to one map
mam.apply_mask_to_map('map_manager', mask_id='mask')
s = (mam.map_manager().map_data() > 0.)
assert approx_equal((s.count(True), s.size()), (640, 2048))
s = (mam.map_manager().map_data() != 0.)
assert approx_equal((s.count(True), s.size()), (1000, 2048))
assert approx_equal((mam.map_manager().map_data()[225]), -0.0418027862906)
# Apply the mask to all maps
mam.apply_mask_to_maps()
s = (mam.map_manager().map_data() > 0.)
assert approx_equal((s.count(True), s.size()), (640, 2048))
s = (mam.map_manager().map_data() != 0.)
assert approx_equal((s.count(True), s.size()), (1000, 2048))
assert approx_equal((mam.map_manager().map_data()[225]), -0.0418027862906)
# Apply the mask to all maps, setting outside value to mean inside
mam.apply_mask_to_maps(set_outside_to_mean_inside=True)
s = (mam.map_manager().map_data() > 0.)
assert approx_equal((s.count(True), s.size()), (1688, 2048))
s = (mam.map_manager().map_data() != 0.)
assert approx_equal((s.count(True), s.size()), (2048, 2048))
assert approx_equal((mam.map_manager().map_data()[2047]), -0.0759598612785)
s = (mam.get_map_manager_by_id('mask').map_data() > 0).as_1d()
inside = mam.map_manager().map_data().as_1d().select(s)
outside = mam.map_manager().map_data().as_1d().select(~s)
assert approx_equal(
(inside.min_max_mean().max, outside.min_max_mean().max),
(0.335603952408, 0.0239064293122))
# Make a new map and model, get mam and box with selection
mmm = map_model_manager()
mmm.generate_map(box_cushion=0, wrapping=True)
mam = mmm
mam_dc = mam.deep_copy()
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((18, 25, 20), (18, 25, 20)))
# Get local fsc or randomized map
dc = mam_dc.deep_copy()
dc.map_manager().set_wrapping(False)
map_coeffs = dc.map_manager().map_as_fourier_coefficients(d_min=3)
from cctbx.development.create_models_or_maps import generate_map
new_mm_1 = generate_map(map_coeffs=map_coeffs,
d_min=3,
low_resolution_real_space_noise_fraction=1,
high_resolution_real_space_noise_fraction=50,
map_manager=dc.map_manager(),
random_seed=124321)
new_mm_2 = generate_map(map_coeffs=map_coeffs,
d_min=3,
low_resolution_real_space_noise_fraction=1,
high_resolution_real_space_noise_fraction=50,
map_manager=dc.map_manager(),
random_seed=734119)
dc.add_map_manager_by_id(new_mm_1, 'map_manager_1')
dc.add_map_manager_by_id(new_mm_2, 'map_manager_2')
cc = dc.map_map_cc()
fsc_curve = dc.map_map_fsc()
dc.set_log(sys.stdout)
dc.local_fsc(n_boxes=1)
# Get map-map FSC
dc = mam_dc.deep_copy()
dc.duplicate_map_manager(map_id='map_manager', new_map_id='filtered')
dc.resolution_filter(d_min=3.5, d_max=10, map_id='filtered')
dc.create_mask_around_atoms()
fsc_curve = dc.map_map_fsc(map_id_1='map_manager',
map_id_2='filtered',
mask_id='mask',
resolution=3.5,
fsc_cutoff=0.97)
assert approx_equal(fsc_curve.d_min, 3.91175024213, eps=0.01)
assert approx_equal(fsc_curve.fsc.fsc[-1], 0.695137718033)
# Get map-map CC
dc = mam_dc.deep_copy()
dc.duplicate_map_manager(map_id='map_manager', new_map_id='filtered')
dc.resolution_filter(d_min=3.5, d_max=6, map_id='filtered')
cc = dc.map_map_cc('map_manager', 'filtered')
assert approx_equal(cc, 0.706499206126)
# Get map-map CC with mask
dc = mam_dc.deep_copy()
dc.duplicate_map_manager(map_id='map_manager', new_map_id='filtered')
dc.create_mask_around_density(mask_id='filtered')
cc = dc.map_map_cc('map_manager', 'filtered', mask_id='mask')
assert approx_equal(cc, 0.411247493741)
# box around model
mam = mam_dc.deep_copy()
mam.box_all_maps_around_model_and_shift_origin(
selection_string="resseq 221:221")
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((18, 25, 20), (24, 20, 20)))
# extract_around_model (get new mam)
new_mam_dc = mam_dc.extract_all_maps_around_model(
selection_string="resseq 221:221")
new_mm_1a = new_mam_dc.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1a.map_data().all()),
((18, 25, 20), (24, 20, 20)))
assert approx_equal(new_mm_1.map_data(), new_mm_1a.map_data())
# box around_density
mam2 = mam_dc.deep_copy()
mam2.box_all_maps_around_density_and_shift_origin(box_cushion=0)
new_mm_2 = mam2.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_2.map_data().all()),
((18, 25, 20), (16, 23, 18)))
# extract_around_density (get new mam)
mam2 = mam_dc.deep_copy()
mam2_b = mam2.extract_all_maps_around_density(box_cushion=0)
new_mm_2 = mam2_b.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_2.map_data().all()),
((18, 25, 20), (16, 23, 18)))
# Repeat as map_model_manager:
mmm = mam_dc.as_map_model_manager().deep_copy()
mmm.box_all_maps_around_model_and_shift_origin(
selection_string="resseq 221:221")
new_mm_1a = mmm.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1a.map_data().all()),
((24, 20, 20), (24, 20, 20)))
assert approx_equal(new_mm_1.map_data(), new_mm_1a.map_data())
# box around density
mam.box_all_maps_around_density_and_shift_origin(box_cushion=0)
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (22, 18, 18)))
# extract around density (get new mam)
mam1 = mam_dc.deep_copy()
mam1.extract_all_maps_around_density(box_cushion=0)
new_mm_1 = mam1.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (18, 25, 20)))
# create mask around density, then box around mask (i.e., box around density)
mam.create_mask_around_density(soft_mask=False)
mam.box_all_maps_around_mask_and_shift_origin(box_cushion=3)
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (22, 18, 18)))
# box with bounds
mam.box_all_maps_with_bounds_and_shift_origin(lower_bounds=(10, 10, 10),
upper_bounds=(15, 15, 15))
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (6, 6, 6)))
# extract with bounds
mam = mam_dc.deep_copy()
mam_1 = mam.extract_all_maps_with_bounds(lower_bounds=(10, 10, 10),
upper_bounds=(15, 15, 15))
new_mm_1 = mam_1.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (6, 6, 6)))
# box with unique
mam = mam_dc.deep_copy()
mam.box_all_maps_around_unique_and_shift_origin(molecular_mass=2500,
resolution=3)
new_mm_1 = mam.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (18, 25, 20)))
# extract with unique
mam = mam_dc.deep_copy()
mam_1 = mam.extract_all_maps_around_unique(molecular_mass=2500,
resolution=3)
new_mm_1 = mam_1.map_manager()
assert approx_equal((mmm.map_data().all(), new_mm_1.map_data().all()),
((24, 20, 20), (18, 25, 20)))
# extract a box and then restore model into same reference as current mam
mam = mam_dc.deep_copy()
mam.box_all_maps_with_bounds_and_shift_origin(lower_bounds=(2, 2, 2),
upper_bounds=(17, 17, 17))
print("mam:",
mam.model().get_sites_cart()[0],
mam.map_manager().origin_is_zero())
# extract a box
box_mam = mam.extract_all_maps_with_bounds(lower_bounds=(10, 10, 10),
upper_bounds=(15, 15, 15))
box_model = box_mam.model()
matched_box_model = mam.get_model_from_other(box_mam)
assert approx_equal(matched_box_model.get_sites_cart()[0],
mam.model().get_sites_cart()[0])
# Convert a map to fourier coefficients
mam = mam_dc.deep_copy()
ma = mam.map_as_fourier_coefficients(d_min=3)
assert approx_equal(ma.d_min(), 3.01655042414)
mam.add_map_from_fourier_coefficients(ma, map_id='new_map_manager')
cc = flex.linear_correlation(
mam.get_map_manager_by_id('map_manager').map_data().as_1d(),
mam.get_map_manager_by_id(
'new_map_manager').map_data().as_1d()).coefficient()
assert (cc >= 0.99)
# Get map-model CC
dc = mam_dc.extract_all_maps_around_model(
selection_string="(name ca or name cb or name c or name o) " +
"and resseq 221:221",
box_cushion=0)
cc = dc.map_model_cc(resolution=3)
assert approx_equal(cc, 0.450025539936)
# Remove model outside map
dc.remove_model_outside_map(boundary=0)
assert (mam_dc.model().get_sites_cart().size(),
dc.model().get_sites_cart().size()) == (86, 4)
# shift a model to match the map
dc = mam_dc.extract_all_maps_around_model(
selection_string="(name ca or name cb or name c or name o) " +
"and resseq 221:221",
box_cushion=0)
actual_model = dc.model().deep_copy()
working_model = dc.model().deep_copy()
working_model.set_shift_cart((0, 0, 0))
working_model.set_sites_cart(working_model.get_sites_cart() -
actual_model.shift_cart())
dc.shift_any_model_to_match(working_model)
assert approx_equal(actual_model.get_sites_cart()[0],
working_model.get_sites_cart()[0])
def test_miller_array_datatype():
data_dir = os.path.dirname(os.path.abspath(__file__))
data_mtz = os.path.join(data_dir, 'data',
'insulin_unmerged_cutted_from_ccp4.mtz')
dm = DataManager(['miller_array', 'phil'])
dm.process_miller_array_file(data_mtz)
# test labels
labels = [
'M_ISYM', 'BATCH', 'I,SIGI,merged', 'IPR,SIGIPR,merged',
'FRACTIONCALC', 'XDET', 'YDET', 'ROT', 'WIDTH', 'LP', 'MPART', 'FLAG',
'BGPKRATIOS'
]
for label in dm.get_miller_array_labels():
assert label in labels
assert len(dm.get_miller_arrays()) == len(dm.get_miller_array_labels())
# test access by label
label = dm.get_miller_array_labels()[3]
new_label = dm.get_miller_arrays(labels=[label])[0].info().label_string()
assert label == new_label
# test custom PHIL
dm.write_phil_file(dm.export_phil_scope().as_str(),
filename='test.phil',
overwrite=True)
loaded_phil = iotbx.phil.parse(file_name='test.phil')
new_dm = DataManager(['miller_array', 'phil'])
new_dm.load_phil_scope(loaded_phil)
assert data_mtz == new_dm.get_default_miller_array_name()
for label in new_dm.get_miller_array_labels():
assert label in labels
os.remove('test.phil')
# test type
assert dm.get_miller_array_type() == 'x_ray'
label = labels[3]
dm.set_miller_array_type(data_mtz, label, 'electron')
assert dm.get_miller_array_type(label=label) == 'electron'
dm.write_phil_file(dm.export_phil_scope().as_str(),
filename='test_phil',
overwrite=True)
loaded_phil = iotbx.phil.parse(file_name='test_phil')
new_dm.load_phil_scope(loaded_phil)
assert new_dm.get_miller_array_type(label=label) == 'electron'
new_dm = DataManager(['miller_array'])
try:
new_dm.set_default_miller_array_type('q')
except Sorry:
pass
new_dm.set_default_miller_array_type('neutron')
new_dm.process_miller_array_file(data_mtz)
assert new_dm.get_miller_array_type(label=label) == 'neutron'
os.remove('test_phil')
# test writing file
arrays = dm.get_miller_arrays()
dataset = arrays[2].as_mtz_dataset(column_root_label='label1')
dataset.add_miller_array(miller_array=arrays[3],
column_root_label='label2')
mtz_object = dataset.mtz_object()
dm.write_miller_array_file(mtz_object, filename='test.mtz', overwrite=True)
dm.process_miller_array_file('test.mtz')
new_labels = dm.get_miller_array_labels('test.mtz')
assert 'label1,SIGlabel1' in new_labels
assert 'label2,SIGlabel2' in new_labels
os.remove('test.mtz')
# test file server
fs1 = dm.get_reflection_file_server()
fs2 = dm.get_reflection_file_server([data_mtz, data_mtz])
assert 2 * len(fs1.miller_arrays) == len(fs2.miller_arrays)
cs = crystal.symmetry(
unit_cell=dm.get_miller_arrays()[0].crystal_symmetry().unit_cell(),
space_group_symbol='P1')
fs = dm.get_reflection_file_server(crystal_symmetry=cs)
assert fs.crystal_symmetry.is_similar_symmetry(cs)
assert not fs.crystal_symmetry.is_similar_symmetry(
dm.get_miller_arrays()[0].crystal_symmetry())
fs = dm.get_reflection_file_server(labels=['I,SIGI,merged'])
assert len(fs.get_miller_arrays(None)) == 1
miller_array = fs.get_amplitudes(None, None, True, None, None)
assert miller_array.info().label_string() == 'I,as_amplitude_array,merged'
for label in dm.get_miller_array_labels():
dm.set_miller_array_type(label=label, array_type='electron')
fs = dm.get_reflection_file_server(array_type='x_ray')
assert len(fs.get_miller_arrays(None)) == 0
fs = dm.get_reflection_file_server(array_type='electron')
assert len(fs.get_miller_arrays(None)) == 13
fs = dm.get_reflection_file_server(
filenames=[data_mtz],
labels=[['I,SIGI,merged', 'IPR,SIGIPR,merged']],
array_type='neutron')
assert len(fs.get_miller_arrays(None)) == 0
for label in ['I,SIGI,merged', 'IPR,SIGIPR,merged']:
dm.set_miller_array_type(label=label, array_type='x_ray')
fs = dm.get_reflection_file_server(
filenames=[data_mtz],
labels=[['I,SIGI,merged', 'IPR,SIGIPR,merged']],
array_type='x_ray')
assert len(fs.get_miller_arrays(data_mtz)) == 2
fs = dm.get_reflection_file_server(filenames=[data_mtz],
array_type='x_ray')
assert len(fs.get_miller_arrays(data_mtz)) == 2
fs = dm.get_reflection_file_server(filenames=[data_mtz],
array_type='electron')
assert len(fs.get_miller_arrays(data_mtz)) == 11
# test subset of labels
label_subset = labels[3:8]
dm = DataManager(['miller_array', 'phil'])
dm.process_miller_array_file(data_mtz)
dm._miller_array_labels[data_mtz] = label_subset
dm.set_miller_array_type(label=label_subset[2], array_type='electron')
assert dm.get_miller_array_type(label=label_subset[2]) == 'electron'
dm.write_phil_file(dm.export_phil_scope().as_str(),
filename='test.phil',
overwrite=True)
loaded_phil = iotbx.phil.parse(file_name='test.phil')
new_dm = DataManager(['miller_array', 'phil'])
new_dm.load_phil_scope(loaded_phil)
assert new_dm.get_miller_array_type(label=label_subset[2]) == 'electron'
fs = new_dm.get_reflection_file_server(array_type='x_ray')
assert len(fs.get_miller_arrays(None)) == 4
fs = new_dm.get_reflection_file_server(array_type='electron')
assert len(fs.get_miller_arrays(None)) == 1
os.remove('test.phil')
label_subset = list()
dm = DataManager(['miller_array', 'phil'])
dm.process_miller_array_file(data_mtz)
dm._miller_array_labels[data_mtz] = label_subset
dm.write_phil_file(dm.export_phil_scope().as_str(),
filename='test.phil',
overwrite=True)
loaded_phil = iotbx.phil.parse(file_name='test.phil')
new_dm = DataManager(['miller_array', 'phil'])
new_dm.load_phil_scope(loaded_phil)
fs = new_dm.get_reflection_file_server(array_type='x_ray')
assert len(fs.get_miller_arrays(None)) == 13
fs = new_dm.get_reflection_file_server(array_type='electron')
assert len(fs.get_miller_arrays(None)) == 0
os.remove('test.phil')
def create_model_from_file(path_to_pdb_file): from iotbx.data_manager import DataManager # Load in the DataManager dm = DataManager() # Initialize the DataManager and call it dm model = dm.get_model(path_to_pdb_file) return model
def test_map_mixins():
regression_dir = libtbx.env.find_in_repositories(
relative_path='phenix_regression/maps')
if not regression_dir:
print('Skipping test, phenix_regression missing')
return
dm = DataManager(['real_map'])
assert not hasattr(dm, 'has_real_maps_or_map_coefficients')
assert hasattr(dm, 'has_real_maps')
assert not hasattr(dm, 'has_map_coefficients')
dm = DataManager(['map_coefficients'])
assert not hasattr(dm, 'has_real_maps_or_map_coefficients')
assert not hasattr(dm, 'has_real_maps')
assert hasattr(dm, 'has_map_coefficients')
dm = DataManager()
assert hasattr(dm, 'has_real_maps_or_map_coefficients')
assert hasattr(dm, 'has_real_maps')
assert hasattr(dm, 'has_map_coefficients')
cwd = os.getcwd()
model_file = os.path.join(regression_dir, 'test_maps4.pdb')
mtz_file = os.path.join(regression_dir, 'test_maps4.mtz')
make_map([
model_file, mtz_file, 'output.directory={cwd}'.format(cwd=cwd),
'output.prefix=tmm'
],
use_output_directory=False,
log=null_out())
real_map_file = 'tmm_2mFo-DFc_map.ccp4'
map_coefficients_file = 'tmm_map_coeffs.mtz'
assert not dm.has_real_maps_or_map_coefficients(expected_n=1,
exact_count=True)
dm.process_real_map_file(real_map_file)
assert dm.has_real_maps(expected_n=1, exact_count=True)
assert dm.has_real_maps_or_map_coefficients(expected_n=1, exact_count=True)
dm.process_map_coefficients_file(map_coefficients_file)
assert dm.has_map_coefficients(expected_n=1, exact_count=True)
assert not dm.has_real_maps_or_map_coefficients(expected_n=1,
exact_count=True)
assert dm.has_real_maps_or_map_coefficients(expected_n=1,
exact_count=False)
assert dm.has_real_maps_or_map_coefficients(expected_n=2, exact_count=True)
os.remove(real_map_file)
os.remove(map_coefficients_file)
def test_real_map_datatype():
data_dir = os.path.dirname(os.path.abspath(__file__))
data_ccp4 = os.path.join(data_dir, 'data', 'non_zero_origin_map.ccp4')
dm = DataManager(['real_map', 'phil'])
dm.process_real_map_file(data_ccp4)
assert dm.has_real_maps()
# test custom PHIL
dm.write_phil_file(dm.export_phil_scope().as_str(),
filename='test.phil',
overwrite=True)
loaded_phil = iotbx.phil.parse(file_name='test.phil')
new_dm = DataManager(['real_map', 'phil'])
new_dm.load_phil_scope(loaded_phil)
assert data_ccp4 == new_dm.get_default_real_map_name()
os.remove('test.phil')
# test writing and reading file
mm = dm.get_real_map()
mm.shift_origin()
dm.write_real_map_file(mm, filename='test.ccp4', overwrite=True)
dm.process_real_map_file('test.ccp4')
new_mm = dm.get_real_map('test.ccp4')
assert not new_mm.is_similar(mm)
new_mm.shift_origin()
assert new_mm.is_similar(mm)
os.remove('test.ccp4')
def main():
dm = DataManager()
dm.process_model_str('testing', model_1yjp)
model = dm.get_model()
rc = model.restraints_as_geo(force=True)
rc = check_geo(rc)
assert rc == count_1yjp, check_diff(rc, count_1yjp)
dm = DataManager()
dm.process_model_str('testing', model_1yjp_with_waters)
model = dm.get_model()
rc = model.restraints_as_geo(force=True)
rc = check_geo(rc)
assert rc == count_1yjp_with_waters, rc
params = model.get_default_pdb_interpretation_params()
edits_1yjp = params.geometry_restraints.edits
edits_1yjp.bond[0].action = 'add'
edits_1yjp.bond[0].atom_selection_1 = 'resname HOH and resid 10 and name O'
edits_1yjp.bond[
0].atom_selection_2 = 'resname ASN and resid 2 and name ND2'
edits_1yjp.bond[0].distance_ideal = 2.1
edits_1yjp.bond[0].sigma = 0.1
model.set_pdb_interpretation_params(params)
rc = model.restraints_as_geo(force=True)
rc = check_geo(rc)
current = count_1yjp_with_waters.copy()
current['User supplied restraints'] = 1
current['Nonbonded interactions'] = 1176
assert rc == current, check_diff(rc, current)
edits_1yjp.angle[0].action = 'add'
edits_1yjp.angle[
0].atom_selection_1 = 'resname HOH and resid 10 and name O'
edits_1yjp.angle[
0].atom_selection_2 = 'resname ASN and resid 2 and name ND2'
edits_1yjp.angle[
0].atom_selection_3 = 'resname ASN and resid 2 and name CG'
edits_1yjp.angle[0].angle_ideal = 21.9
edits_1yjp.angle[0].sigma = 1.1
model.set_pdb_interpretation_params(params)
rc = model.restraints_as_geo(force=True)
rc = check_geo(rc)
current = count_1yjp_with_waters.copy()
current['User supplied restraints'] = 1
current['User supplied angle restraints'] = 1
current['Nonbonded interactions'] = 1176
assert rc == current, check_diff(rc, current)
edits_1yjp.dihedral[0].action = 'add'
edits_1yjp.dihedral[
0].atom_selection_1 = 'resname HOH and resid 10 and name O'
edits_1yjp.dihedral[
0].atom_selection_2 = 'resname ASN and resid 2 and name ND2'
edits_1yjp.dihedral[
0].atom_selection_3 = 'resname ASN and resid 2 and name CG'
edits_1yjp.dihedral[
0].atom_selection_4 = 'resname ASN and resid 2 and name CB'
edits_1yjp.dihedral[0].angle_ideal = 121.9
edits_1yjp.dihedral[0].sigma = 1.12
edits_1yjp.dihedral[0].periodicity = 10
model.set_pdb_interpretation_params(params)
rc = model.restraints_as_geo(force=True)
rc = check_geo(rc)
current = count_1yjp_with_waters.copy()
current['User supplied restraints'] = 1
current['User supplied angle restraints'] = 1
current['User supplied torsion angle restraints'] = 1
#current[' sinusoidal'] = 16
current['Nonbonded interactions'] = 1176
assert rc == current, check_diff(rc, current)
print('OK')
def test_default_filenames():
datatypes = [
'model', 'ncs_spec', 'phil', 'real_map', 'restraint', 'sequence'
]
extensions = ['cif', 'ncs_spec', 'eff', 'mrc', 'cif', 'seq']
dm = DataManager(datatypes)
for datatype, extension in zip(datatypes, extensions):
filename = getattr(
dm, 'get_default_output_{datatype}_filename'.format(
datatype=datatype))()
assert filename == 'cctbx_program.' + extension
filename = dm.get_default_output_model_filename(extension='.abc')
assert filename == 'cctbx_program.abc'
class TestProgram(ProgramTemplate):
master_phil_str = """
output {
serial = 0
.type = int
}
"""
master_phil = iotbx.phil.parse(TestProgram.master_phil_str)
required_output_phil = iotbx.phil.parse(ProgramTemplate.output_phil_str)
master_phil.adopt_scope(required_output_phil)
working_phil = iotbx.phil.parse(ProgramTemplate.master_phil_str)
params = master_phil.fetch(working_phil).extract()
p = ProgramTemplate(dm, params, master_phil)
assert dm.get_default_output_filename() == 'cctbx_program_000'
dm.set_overwrite(True)
dm.write_model_file('abc') # cctbx_program_000.cif
dm.write_phil_file('123') # cctbx_program_000.eff
dm.write_phil_file('456') # cctbx_program_001.eff
dm.write_model_file('def') # cctbx_program_001.cif
assert dm.get_default_output_filename() == 'cctbx_program_001'
dm.write_sequence_file('ghi') # cctbx_program_001.seq
dm.write_sequence_file('hkl') # cctbx_program_002.seq
assert dm.get_default_output_filename() == 'cctbx_program_002'
assert os.path.isfile('cctbx_program_000.cif')
assert os.path.isfile('cctbx_program_001.cif')
assert os.path.isfile('cctbx_program_000.eff')
assert os.path.isfile('cctbx_program_001.eff')
assert os.path.isfile('cctbx_program_001.seq')
assert os.path.isfile('cctbx_program_002.seq')
os.remove('cctbx_program_000.cif')
os.remove('cctbx_program_001.cif')
os.remove('cctbx_program_000.eff')
os.remove('cctbx_program_001.eff')
os.remove('cctbx_program_001.seq')
os.remove('cctbx_program_002.seq')
# test output.filename, output.file_name
assert p.get_default_output_filename() == 'cctbx_program_002'
assert p.get_default_output_filename(filename='abc') == 'abc'
working_phil_str = 'output.filename=def'
working_phil = iotbx.phil.parse(working_phil_str)
params = master_phil.fetch(working_phil).extract()
p = ProgramTemplate(dm, params, master_phil)
assert params.output.filename == params.output.file_name == 'def'
assert p.get_default_output_filename() == 'def'
assert dm.get_default_output_filename() == 'def'
working_phil_str = 'output.file_name=ghi'
working_phil = iotbx.phil.parse(working_phil_str)
params = master_phil.fetch(working_phil).extract()
p = ProgramTemplate(dm, params, master_phil)
assert params.output.filename == params.output.file_name == 'ghi'
assert p.get_default_output_filename() == 'ghi'
assert dm.get_default_output_filename() == 'ghi'
def RunProbeTests(inFileName):
#========================================================================
# Call the test functions for the libraries we test.
ret = probeext.DotSpheres_test()
assert len(ret) == 0, "DotSpheres_test() failed: " + ret
ret = probeext.SpatialQuery_test()
assert len(ret) == 0, "SpatialQuery_test() failed: " + ret
ret = probeext.Scoring_test()
assert len(ret) == 0, "Scoring_test() failed: " + ret
AtomTypes.Test()
Helpers.Test()
#========================================================================
# Now ensure that we can use the C++-wrapped classes as intended to make sure
# that the wrapping code or parameters have not changed.
#========================================================================
# Make sure we can get at the DotSphere objects and their methods
cache = probeext.DotSphereCache(10)
sphere1 = cache.get_sphere(1)
dots = sphere1.dots()
#========================================================================
# Make sure we can fill in an ExtraAtomInfoList and pass it to scoring
# Generate an example data model with a small molecule in it
if inFileName is not None and len(inFileName) > 0:
# Read a model from a file using the DataManager
dm = DataManager()
dm.process_model_file(inFileName)
model = dm.get_model(inFileName)
else:
# Generate a small-molecule model using the map model manager
mmm = map_model_manager(
) # get an initialized instance of the map_model_manager
mmm.generate_map(
) # get a model from a generated small library model and calculate a map for it
model = mmm.model() # get the model
# Fix up bogus unit cell when it occurs by checking crystal symmetry.
cs = model.crystal_symmetry()
if (cs is None) or (cs.unit_cell() is None):
model = shift_and_box_model(model=model)
# Get the list of all atoms in the model
atoms = model.get_atoms()
# Get the bonding information we'll need to exclude our bonded neighbors.
try:
p = mmtbx.model.manager.get_default_pdb_interpretation_params()
model.process(make_restraints=True,
pdb_interpretation_params=p) # make restraints
geometry = model.get_restraints_manager().geometry
sites_cart = model.get_sites_cart() # cartesian coordinates
bond_proxies_simple, asu = \
geometry.get_all_bond_proxies(sites_cart = sites_cart)
except Exception as e:
raise Exception("Could not get bonding information for input file: " +
str(e))
bondedNeighbors = Helpers.getBondedNeighborLists(atoms,
bond_proxies_simple)
# Traverse the hierarchy and look up the extra data to be filled in.
ret = Helpers.getExtraAtomInfo(model)
extra = ret.extraAtomInfo
# Construct a SpatialQuery and fill in the atoms. Ensure that we can make a
# query within 1000 Angstroms of the origin.
sq = probeext.SpatialQuery(atoms)
nb = sq.neighbors((0, 0, 0), 0, 1000)
# Construct a DotScorer object.
# Find the radius of each atom in the structure and construct dot spheres for
# them. Find the atoms that are bonded to them and add them to an excluded list.
# Then compute the score for each of them and report the summed score over the
# whole molecule the way that Reduce will.
ds = probeext.DotScorer(extra)
total = 0
badBumpTotal = 0
for a in atoms:
rad = extra.getMappingFor(a).vdwRadius
assert rad > 0, "Invalid radius for atom look-up: " + a.name + " rad = " + str(
rad)
sphere = cache.get_sphere(rad)
# Excluded atoms that are bonded to me or to one of my neightbors.
# It has the side effect of excluding myself if I have any neighbors.
# Construct as a set to avoid duplicates.
exclude = set()
for n in bondedNeighbors[a]:
exclude.add(n)
for n2 in bondedNeighbors[n]:
exclude.add(n2)
exclude = list(exclude)
dots = sphere.dots()
res = ds.score_dots(a, 1.0, sq, rad * 3, 0.25, exclude, sphere.dots(),
sphere.density(), False)
total += res.totalScore()
if res.hasBadBump:
badBumpTotal += 1
# Test calling the single-dot checking code as will be used by Probe to make sure
# all of the Python linkage is working
dotOffset = [1, 0, 0]
check = ds.check_dot(atoms[0], dotOffset, 1, atoms, [atoms[0]])
overlapType = check.overlapType
# Test calling the interaction_type method to be sure Python linkage is working
interactionType = ds.interaction_type(check.overlapType, check.gap)
def Test(inFileName = None):
#========================================================================
# Make sure we can fill in mmtbx.probe.ExtraAtomInfoList info.
# Generate an example data model with a small molecule in it unless we
# were given a file name on the command line.
if inFileName is not None and len(inFileName) > 0:
# Read a model from a file using the DataManager
dm = DataManager()
dm.process_model_file(inFileName)
model = dm.get_model(inFileName)
else:
# Generate a small-molecule model using the map model manager
mmm=map_model_manager() # get an initialized instance of the map_model_manager
mmm.generate_map() # get a model from a generated small library model and calculate a map for it
model = mmm.model() # get the model
# Fill in an ExtraAtomInfoList with an entry for each atom in the hierarchy.
# We first find the largest i_seq sequence number in the model and reserve that
# many entries so we will always be able to fill in the entry for an atom.
atoms = model.get_atoms()
maxI = atoms[0].i_seq
for a in atoms:
if a.i_seq > maxI:
maxI = a.i_seq
extra = []
for i in range(maxI+1):
extra.append(probe.ExtraAtomInfo())
# Traverse the hierarchy and look up the extra data to be filled in.
# Get a list of all the atoms in the chain while we're at it
at = AtomTypes()
ph = model.get_hierarchy()
for m in ph.models():
for chain in m.chains():
for rg in chain.residue_groups():
for ag in rg.atom_groups():
for a in ag.atoms():
ei, warn = at.FindProbeExtraAtomInfo(a)
extra[a.i_seq] = ei
# User code should test for and print warnings
#if len(warn) > 0:
# print(warn)
#========================================================================
# Find an Oxygen atom and ask for its radii with explicit Hydrogen, implicit Hydrogen,
# and Nuclear radii.
o = None
ph = model.get_hierarchy()
for a in ph.models()[0].atoms():
if a.element.strip() == 'O':
o = a
assert o is not None, "AtomTypes.Test(): Could not find Oxygen (internal test failure)"
explicitH = AtomTypes(useNeutronDistances = False,
useImplicitHydrogenDistances = False).FindProbeExtraAtomInfo(o)[0].vdwRadius
implicitH = AtomTypes(useNeutronDistances = False,
useImplicitHydrogenDistances = True).FindProbeExtraAtomInfo(o)[0].vdwRadius
neutronH = AtomTypes(useNeutronDistances = True,
useImplicitHydrogenDistances = False).FindProbeExtraAtomInfo(o)[0].vdwRadius
assert explicitH != implicitH, "AtomTypes.Test(): Implicit and explicit Oxygen radii did not differ as expected"
#========================================================================
# Check MaximumVDWRadius, calling it twice to make sure both the cached and non-cached
# results work.
for i in range(2):
assert at.MaximumVDWRadius() == 2.5, "AtomTypes.Test(): Unexpected MaximumVDWRadius(): got "+str(MaximumVDWRadius())+", expected 2.5"
#========================================================================
# Check IsAromatic() to ensure it gives results when expected and not when not.
aromaticChecks = [
['PHE', 'CE2', True],
[' U', 'HN3', True],
['ASN', 'O', False]
]
for a in aromaticChecks:
assert IsAromatic(a[0],a[1]) == a[2], "AtomTypes.Test(): {} {} not marked as aromatic {}".format(a[0],a[1],a[2])
def get_statistics(self):
if self.json_data['success_composition'] is False:
return
make_sub_header('Get statistics', out=self.logger)
self.save_json()
success = True
self.json_data['success_statistics'] = None
sc, r_sc = None, None
self.pickle_data.min_reso = None
self.pickle_data.d_inv = None
self.pickle_data.r_d_inv = None
self.pickle_data.d_inv_half = None
self.pickle_data.fsc_model = None
self.pickle_data.r_fsc_model = None
self.pickle_data.fsc_half = None
if self.json_data['restraints_file']:
cif_file = self.json_data['restraints_file']
cif_objects = monomer_library.server.read_cif(file_name=to_str(cif_file))
cif_objects = [(cif_file, cif_objects)]
else: cif_objects = None
for p, fn in zip(('', 'r_'),
[self.json_data['pdb_file_updated'], self.json_data['pdb_file_refined']]):
# TODO which file to use for initial!!
if (not fn or not os.path.isfile(fn)): continue
if p=='': print('Initial model', file=self.logger)
if p=='r_': print('\nRefined model', file=self.logger)
dm = DataManager()
dm.process_real_map_file(self.json_data['map_file'])
map_inp = dm.get_real_map(self.json_data['map_file'])
#map_inp = iotbx.ccp4_map.map_reader(file_name = self.json_data['map_file'])
map_inp_1, map_inp_2 = None, None
if self.json_data['map_file_1'] is not None:
#map_inp_1 = iotbx.ccp4_map.map_reader(file_name = self.json_data['map_file_1'])
dm.process_real_map_file(self.json_data['map_file_1'])
map_inp_1 = dm.get_real_map(self.json_data['map_file_1'])
#map_data_1 = map_inp_1.map_data()
if self.json_data['map_file_2'] is not None:
dm.process_real_map_file(self.json_data['map_file_2'])
map_inp_2 = dm.get_real_map(self.json_data['map_file_2'])
#map_inp_2 = iotbx.ccp4_map.map_reader(file_name = self.json_data['map_file_2'])
#map_data_2 = map_inp_2.map_data()
print('\tGet model class with restraints...', file=self.logger)
pdb_inp = iotbx.pdb.input(file_name = fn)
try:
model = mmtbx.model.manager(
model_input = pdb_inp,
restraint_objects = cif_objects,
build_grm = True,
stop_for_unknowns = False,
crystal_symmetry = map_inp.crystal_symmetry(),
log = null_out())
except Exception as e:
#success = False
self.json_data['success_statistics'] = False
msg = traceback.format_exc()
print(msg, file=self.logger)
self.write_log(
step = 'Statistics: Model class (with restraints) from pdb ',
msg = msg)
self.save_json()
continue
if not success: continue
# Emringer
if self.resolution < 4.0:
print('\tCalculate Emringer score', file=self.logger)
try:
emringer_score = self.get_emringer_score(
model = model.deep_copy(),
map_inp = map_inp.deep_copy())
self.json_data[p+'emringer'] = emringer_score
except Exception as e:
msg = traceback.format_exc()
print(msg, file=self.logger)
self.write_log(step = 'EMRinger failed ', msg = msg)
# TODO: save as success_statistics False?
# Rama-z score
try:
rama_z_score = rama_z.rama_z(
models = [model],
log = self.logger)
z_scores = rama_z_score.get_z_scores()
self.json_data[p+'z_score'] = z_scores['W'][0]
except Exception as e:
msg = traceback.format_exc()
print(msg, file=self.logger)
self.write_log(step = 'Rama z-score failed ', msg = msg)
# base = map_and_model.input(
# map_manager = map_inp,
# map_manager_1 = map_inp_1,
# map_manager_2 = map_inp_2,
# model = model,
# box = True)
checked = map_model_manager(
map_manager = map_inp,
map_manager_1 = map_inp_1,
map_manager_2 = map_inp_2,
model = model,
wrapping = None)
checked.box_all_maps_around_model_and_shift_origin()
params = validation_cryoem.master_params().extract()
params.resolution = self.resolution
params.slim = False
if (p == ''):
print('\tGet map parameters...', file=self.logger)
self.get_map_parameters(base = checked)
print('\tRun Mtriage...', file=self.logger)
try:
o = validation_cryoem.validation(
model = checked.model(),
map_data = checked.map_data(),
map_data_1 = checked.map_data_1(),
map_data_2 = checked.map_data_2(),
params = params)
except Exception as e:
# success = False
self.json_data['success_statistics'] = False
msg = traceback.format_exc()
print(msg, file=self.logger)
self.write_log(step = 'Statistics ', msg = msg)
self.save_json()
continue
print('\tStore info in pkl...', file=self.logger)
o_dict = self.fill_dictionary(o)
if (p == ''):
self.json_data['o'] = o_dict
sc = o.model.get_sites_cart()
elif (p == 'r_'):
self.json_data['o_refined'] = o_dict
r_sc = o.model.get_sites_cart()
if o is not None:
if o.model_vs_data is not None:
if o.model_vs_data.cc is not None:
if o.model_vs_data.cc.cc_per_chain is not None:
if (p == ''):
self.pickle_data.cc_per_chain = o.model_vs_data.cc.cc_per_chain
if (p == 'r_'):
self.pickle_data.r_cc_per_chain = o.model_vs_data.cc.cc_per_chain
if o.model_vs_data.cc.cc_per_residue is not None:
if (p == ''):
self.pickle_data.cc_per_residue = o.model_vs_data.cc.cc_per_residue
if (p == 'r_'):
self.pickle_data.r_cc_per_residue = o.model_vs_data.cc.cc_per_residue
if o.model_stats.geometry.ramachandran.ramalyze is not None:
rl = o.model_stats.geometry.ramachandran.ramalyze
if (p == ''): self.pickle_data.ramalyze = rl
if (p == 'r_'): self.pickle_data.r_ramalyze = rl
# values for the curve go up to very high reso, get highest reso limit
# if o is not None:
# reso_list = [self.json_data['d_pdb'],self.json_data['d_cif'],
# self.json_data['d_map'], self.json_data['o']['d99'],
# self.json_data['o']['d_model'], self.json_data['o']['d_fsc']]
# else:
# reso_list = [self.json_data['d_pdb'],self.json_data['d_cif'],
# self.json_data['d_map']]
# min_reso = min([elem for elem in reso_list if elem is not None])
# self.pickle_data.min_reso = min_reso
min_reso = self.resolution
self.pickle_data.min_reso = self.resolution
# apply some arbitrary buffer
min_reso = min_reso - 0.5
if o is not None:
masked = o.data_stats.masked
if (masked.fsc_curve_model is not None):
if ((masked.fsc_curve_model.d_inv is not None) and
(masked.fsc_curve_model.fsc is not None)):
if (p == ''):
self.pickle_data.d_inv = masked.fsc_curve_model.d_inv
self.pickle_data.fsc_model = masked.fsc_curve_model.fsc
if (p == 'r_'):
self.pickle_data.r_d_inv = masked.fsc_curve_model.d_inv
self.pickle_data.r_fsc_model = masked.fsc_curve_model.fsc
if (p == ''):
if (masked.fsc_curve is not None):
if (masked.fsc_curve.fsc is not None):
if ((masked.fsc_curve.fsc.d_inv is not None) and
(masked.fsc_curve.fsc.fsc is not None)):
self.pickle_data.d_inv_half = masked.fsc_curve.fsc.d_inv
self.pickle_data.fsc_half = masked.fsc_curve.fsc.fsc
if o is not None:
print("\nd99 :", o.data_stats.masked.d99)
print("d_model :", o.data_stats.masked.d_model)
print("d_fsc :", o.data_stats.masked.d_fsc)
print("ramachandran.outliers:", o.model_stats.geometry.ramachandran.outliers)
print("cc_mask :", o.model_vs_data.cc.cc_mask)
print("cc_box :", o.model_vs_data.cc.cc_box)
if sc is not None and r_sc is not None:
self.json_data['rmsd'] = sc.rms_difference(r_sc)
if self.json_data['success_statistics'] is not False:
self.json_data['success_statistics'] = success
def test_01():
# Source data
data_dir = os.path.dirname(os.path.abspath(__file__))
data_ccp4 = os.path.join(data_dir, 'data', 'non_zero_origin_map.ccp4')
data_pdb = os.path.join(data_dir, 'data', 'non_zero_origin_model.pdb')
data_ncs_spec = os.path.join(data_dir, 'data',
'non_zero_origin_ncs_spec.ncs_spec')
# Read in data
dm = DataManager(['ncs_spec', 'model', 'real_map', 'phil'])
dm.set_overwrite(True)
map_file = data_ccp4
dm.process_real_map_file(map_file)
mm = dm.get_real_map(map_file)
model_file = data_pdb
dm.process_model_file(model_file)
model = dm.get_model(model_file)
ncs_file = data_ncs_spec
dm.process_ncs_spec_file(ncs_file)
ncs = dm.get_ncs_spec(ncs_file)
mmm = map_model_manager(model=model,
map_manager_1=mm.deep_copy(),
map_manager_2=mm.deep_copy(),
ncs_object=ncs,
wrapping=False)
mmm.add_map_manager_by_id(map_id='external_map',
map_manager=mmm.map_manager().deep_copy())
mmm.set_resolution(3)
mmm.set_log(sys.stdout)
dc = mmm.deep_copy()
# Model sharpening
mmm = dc.deep_copy()
tls_info = mmm.tls_from_map(
n_bins=10,
model_id='model',
map_id='map_manager',
iterations=1,
)
tlso = tls_info.tlso_list[0]
print("t:", tlso.t)
print("l:", tlso.l)
print("s:", tlso.s)
print("origin:", tlso.origin)
assert approx_equal(
tlso.t,
(1.180418902258779, 1.1747521845606608, 1.178996799712174,
-0.08474662674769494, -0.022609295693646402, 0.0649209491344932))
assert approx_equal(
tlso.l,
(-0.002159404807991249, -0.002107964765763024, 0.0008301439376854558,
-5.973347993775719e-05, -0.000134276871934738, -9.05515898670584e-05))
assert approx_equal(
tlso.s,
(2.9348223335616302e-08, 5.52441087256425e-09, -5.382459681103171e-09,
4.3530347434547015e-09, -2.3559464233595e-08, 4.217968590464982e-09,
-4.380707049750269e-09, 1.9232725033868253e-09,
-5.788759082799497e-09))
assert approx_equal(
tlso.origin,
(-64.70331931297399, -62.30573551948903, -63.743687240164604))
print("TLS: ", tlso.t, tlso.l, tlso.s, tlso.origin)
def exercise_around_model():
from cctbx.maptbx.box import make_list_symmetric
a = [3, 4, 5, 3, 9, 1, 6, 3, 2, 5, 6, 6]
new_a = make_list_symmetric(a)
from scitbx.array_family import flex
aa = flex.double(a)
new_aa = flex.double(new_a)
assert (aa.size(), new_aa.size()) == (12, 12)
assert aa.min_max_mean().mean == new_aa.min_max_mean().mean
print(a, new_a)
a = [3, 4, 5, 3, 8, 1, 6, 7, 3, 2, 5, 6, 6]
new_a = make_list_symmetric(a)
from scitbx.array_family import flex
aa = flex.double(a)
new_aa = flex.double(new_a)
print(a, new_a)
assert (aa.size(), new_aa.size()) == (13, 13)
assert aa.min_max_mean().mean == new_aa.min_max_mean().mean
mam = get_random_structure_and_map(use_static_structure=True)
map_data_orig = mam.mm.map_data().deep_copy()
sites_frac_orig = mam.model.get_sites_frac().deep_copy()
sites_cart_orig = mam.model.get_sites_cart().deep_copy()
cs_orig = mam.model.crystal_symmetry()
box = cctbx.maptbx.box.around_model(map_manager=mam.mm,
model=mam.model.deep_copy(),
box_cushion=10,
wrapping=True)
new_mm1 = box.map_manager()
new_mm2 = box.apply_to_map(map_manager=mam.mm.deep_copy())
assert approx_equal(new_mm1.map_data(), new_mm2.map_data())
new_model1 = box.model()
new_model2 = box.apply_to_model(model=mam.model.deep_copy())
assert new_model1.crystal_symmetry().is_similar_symmetry(
new_model2.crystal_symmetry())
assert new_model1.crystal_symmetry().is_similar_symmetry(
box.crystal_symmetry)
assert approx_equal(new_model1.get_sites_cart()[0],
(19.705233333333336, 15.631525, 13.5040625))
# make sure things did change
assert new_mm2.map_data().size() != map_data_orig.size()
# make sure things are changed in-place and are therefore different from start
assert box.map_manager().map_data().size() != map_data_orig.size()
assert box.model().get_sites_frac() != sites_frac_orig
assert box.model().get_sites_cart() != sites_cart_orig
assert (not cs_orig.is_similar_symmetry(box.model().crystal_symmetry()))
# make sure box, model and map_manager remember original crystal symmetry
assert cs_orig.is_similar_symmetry(
box.map_manager().unit_cell_crystal_symmetry())
assert cs_orig.is_similar_symmetry(
box.map_manager().unit_cell_crystal_symmetry())
assert approx_equal(
box.model().shift_cart(),
[5.229233333333334, 5.061524999999999, 5.162062499999999])
assert box.model().unit_cell_crystal_symmetry().is_similar_symmetry(
cs_orig)
assert (not box.model().crystal_symmetry().is_similar_symmetry(cs_orig))
assert approx_equal(
box.model()._figure_out_hierarchy_to_output(
do_not_shift_back=False).atoms().extract_xyz()[0],
(14.476, 10.57, 8.342))
# make sure we can stack shifts
sel = box.model().selection("resseq 219:219")
m_small = box.model().select(selection=sel)
assert approx_equal(box.model().shift_cart(), m_small.shift_cart())
# Now box again:
small_box = cctbx.maptbx.box.around_model(map_manager=mam.mm,
model=mam.model.deep_copy(),
box_cushion=5,
wrapping=True)
# Make sure nothing was zeroed out in this map (wrapping = True)
assert new_mm1.map_data().as_1d().count(0) == 0
# Now without wrapping...
box = cctbx.maptbx.box.around_model(map_manager=mam.mm,
model=mam.model.deep_copy(),
box_cushion=10,
wrapping=False)
# make sure things are changed in-place and are therefore different from start
assert box.map_manager().map_data().size() != map_data_orig.size()
assert box.model().get_sites_frac() != sites_frac_orig
assert box.model().get_sites_cart() != sites_cart_orig
assert (not cs_orig.is_similar_symmetry(box.model().crystal_symmetry()))
# make sure box, model and map_manager remember original crystal symmetry
assert cs_orig.is_similar_symmetry(
box.model().unit_cell_crystal_symmetry())
assert cs_orig.is_similar_symmetry(
box.map_manager().unit_cell_crystal_symmetry())
assert box.map_manager().map_data().as_1d().count(0) == 81264
# Now specify bounds directly
new_box = cctbx.maptbx.box.with_bounds(map_manager=mam.mm.deep_copy(),
lower_bounds=(-7, -7, -7),
upper_bounds=(37, 47, 39),
wrapping=False)
new_model = new_box.apply_to_model(mam.model.deep_copy())
# make sure things are changed in-place and are therefore different from start
assert new_box.map_manager().map_data().size() != map_data_orig.size()
assert new_model.get_sites_frac() != sites_frac_orig
assert new_model.get_sites_cart() != sites_cart_orig
assert (not cs_orig.is_similar_symmetry(new_model.crystal_symmetry()))
# make sure box, model and map_manager remember original crystal symmetry
assert cs_orig.is_similar_symmetry(
box.model().unit_cell_crystal_symmetry())
assert cs_orig.is_similar_symmetry(
box.map_manager().unit_cell_crystal_symmetry())
assert box.map_manager().map_data().as_1d().count(0) == 81264
# Now specify bounds directly and init with model
box = cctbx.maptbx.box.with_bounds(map_manager=mam.mm.deep_copy(),
lower_bounds=(-7, -7, -7),
upper_bounds=(37, 47, 39),
wrapping=False,
model=mam.model.deep_copy())
new_model = box.model()
# make sure things are changed in-place and are therefore different from start
assert box.map_manager().map_data().size() != map_data_orig.size()
assert new_model.get_sites_frac() != sites_frac_orig
assert new_model.get_sites_cart() != sites_cart_orig
assert (not cs_orig.is_similar_symmetry(new_model.crystal_symmetry()))
# make sure box, model and map_manager remember original crystal symmetry
assert cs_orig.is_similar_symmetry(
box.model().unit_cell_crystal_symmetry())
assert cs_orig.is_similar_symmetry(
box.map_manager().unit_cell_crystal_symmetry())
assert box.map_manager().map_data().as_1d().count(0) == 81264
# Extract using around_unique
data_dir = os.path.dirname(os.path.abspath(__file__))
data_ccp4 = os.path.join(data_dir, 'data', 'D7.ccp4')
data_ncs = os.path.join(data_dir, 'data', 'D7.ncs_spec')
data_seq = os.path.join(data_dir, 'data', 'D7.seq')
dm = DataManager(['real_map', 'phil', 'ncs_spec', 'sequence'])
dm.process_real_map_file(data_ccp4)
mm = dm.get_real_map(data_ccp4)
dm.process_ncs_spec_file(data_ncs)
ncs_obj = dm.get_ncs_spec(data_ncs)
dm.process_sequence_file(data_seq)
sequence = dm.get_sequence(data_seq)
sequence_as_text = sequence[0].sequence
map_model_mgr = map_model_manager(map_manager=mm, ncs_object=ncs_obj)
mm = map_model_mgr.map_manager()
mm.show_summary()
box = cctbx.maptbx.box.around_unique(
map_manager=mm.deep_copy(),
resolution=3,
box_cushion=1,
sequence=sequence_as_text,
soft_mask=True,
wrapping=False,
)
box.map_manager().write_map('new_box.ccp4')
# run again from map_manager
map_model_mgr.box_all_maps_around_unique_and_shift_origin(
resolution=3,
box_cushion=1,
sequence=sequence_as_text,
soft_mask=True,
)
# Get bounds around density
box = cctbx.maptbx.box.around_density(map_manager=mam.mm.deep_copy(),
wrapping=False)
# Create a mask
mm = mam.mm.deep_copy()
mm.create_mask_around_density(
resolution=3,
molecular_mass=2100,
sequence="GAVAGA",
solvent_content=0.5,
)
mask_mm = mm.get_mask_as_map_manager()
assert approx_equal(
(mask_mm.map_data().count(0), mask_mm.map_data().count(1),
mask_mm.map_data().size()), (19184, 19216, 38400))
# Box around the mask
box = cctbx.maptbx.box.around_mask(
map_manager=mam.mm.deep_copy(),
mask_as_map_manager=mask_mm,
wrapping=False,
)
assert (box.gridding_first, box.gridding_last) == ([0, 0, 0], [29, 39, 31])
# Box around the mask with cubic box
box = cctbx.maptbx.box.around_mask(
map_manager=mam.mm.deep_copy(),
mask_as_map_manager=mask_mm,
use_cubic_boxing=True,
wrapping=False,
)
assert (box.gridding_first, box.gridding_last) == ([1, 6, 2], [30, 35, 31])
#
# IF you are about to change this - THINK TWICE!
#
from libtbx.introspection import getfullargspec
r = getfullargspec(cctbx.maptbx.box.around_model.__init__)
assert r.args == [
'self', 'map_manager', 'model', 'box_cushion', 'wrapping',
'model_can_be_outside_bounds', 'stay_inside_current_map',
'use_cubic_boxing', 'require_match_unit_cell_crystal_symmetry', 'log'
], r.args
r = getfullargspec(cctbx.maptbx.box.with_bounds.__init__)
assert r.args == [
'self', 'map_manager', 'lower_bounds', 'upper_bounds', 'model',
'wrapping', 'model_can_be_outside_bounds', 'stay_inside_current_map',
'use_cubic_boxing', 'log'
], r.args
print("OK")
