def fetchPDBLigand(cci, filename=None):
"""Fetch PDB ligand data from PDB_ for chemical component *cci*.
*cci* may be 3-letter chemical component identifier or a valid XML
filename. If *filename* is given, XML file will be saved with that name.
If you query ligand data frequently, you may configure ProDy to save XML
files in your computer. Set ``ligand_xml_save`` option **True**, i.e.
``confProDy(ligand_xml_save=True)``. Compressed XML files will be save
to ProDy package folder, e.g. :file:`/home/user/.prody/pdbligands`. Each
file is around 5Kb when compressed.
This function is compatible with PDBx/PDBML v 4.0.
Ligand data is returned in a dictionary. Ligand coordinate atom data with
*model* and *ideal* coordinate sets are also stored in this dictionary.
Note that this dictionary will contain data that is present in the XML
file and all Ligand Expo XML files do not contain every possible data
field. So, it may be better if you use :meth:`dict.get` instead of
indexing the dictionary, e.g. to retrieve formula weight (or relative
molar mass) of the chemical component use ``data.get('formula_weight')``
instead of ``data['formula_weight']`` to avoid exceptions when this data
field is not found in the XML file. URL and/or path of the XML file are
returned in the dictionary with keys ``url`` and ``path``, respectively.
Following example downloads data for ligand STI (a.k.a. Gleevec and
Imatinib) and calculates RMSD between model (X-ray structure 1IEP) and
ideal (energy minimized) coordinate sets:
.. ipython:: python
from prody import *
ligand_data = fetchPDBLigand('STI')
ligand_data['model_coordinates_db_code']
ligand_model = ligand_data['model']
ligand_ideal = ligand_data['ideal']
transformation = superpose(ligand_ideal.noh, ligand_model.noh)
calcRMSD(ligand_ideal.noh, ligand_model.noh)"""
if not isinstance(cci, str):
raise TypeError('cci must be a string')
if isfile(cci):
inp = openFile(cci)
xml = inp.read()
inp.close()
url = None
path = cci
cci = splitext(splitext(split(cci)[1])[0])[0].upper()
elif len(cci) > 4 or not cci.isalnum():
raise ValueError('cci must be 3-letters long and alphanumeric or '
'a valid filename')
else:
xml = None
cci = cci.upper()
if SETTINGS.get('ligand_xml_save'):
folder = join(getPackagePath(), 'pdbligands')
if not isdir(folder):
makePath(folder)
xmlgz = path = join(folder, cci + '.xml.gz')
if isfile(xmlgz):
with openFile(xmlgz) as inp:
xml = inp.read()
else:
path = None
#url = ('http://ligand-expo.rcsb.org/reports/{0[0]}/{0}/{0}'
# '.xml'.format(cci.upper()))
url = 'http://www.pdb.org/pdb/files/ligand/{0}.xml'.format(cci.upper())
if not xml:
#'http://www.pdb.org/pdb/files/ligand/{0}.xml'
try:
inp = openURL(url)
except IOError:
raise IOError('XML file for ligand {0} is not found online'
.format(cci))
else:
xml = inp.read()
inp.close()
if filename:
out = openFile(filename, mode='w', folder=folder)
out.write(xml)
out.close()
if SETTINGS.get('ligand_xml_save'):
with openFile(xmlgz, 'w') as out:
out.write(xml)
import xml.etree.cElementTree as ET
root = ET.XML(xml)
if (root.get('{http://www.w3.org/2001/XMLSchema-instance}'
'schemaLocation') !=
'http://pdbml.pdb.org/schema/pdbx-v40.xsd pdbx-v40.xsd'):
LOGGER.warn('XML is not in PDBx/PDBML v 4.0 format, resulting '
'dictionary may not contain all data fields')
ns = root.tag[:root.tag.rfind('}')+1]
len_ns = len(ns)
dict_ = {'url': url, 'path': path}
for child in list(root.find(ns + 'chem_compCategory')[0]):
tag = child.tag[len_ns:]
if tag.startswith('pdbx_'):
tag = tag[5:]
dict_[tag] = child.text
dict_['formula_weight'] = float(dict_.get('formula_weight'))
identifiers_and_descriptors = []
results = root.find(ns + 'pdbx_chem_comp_identifierCategory')
if results:
identifiers_and_descriptors.extend(results)
results = root.find(ns + 'pdbx_chem_comp_descriptorCategory')
if results:
identifiers_and_descriptors.extend(results)
for child in identifiers_and_descriptors:
program = child.get('program').replace(' ', '_')
type_ = child.get('type').replace(' ', '_')
dict_[program + '_' + type_] = child[0].text
dict_[program + '_version'] = child.get('program_version')
dict_['audits'] = [(audit.get('action_type'), audit.get('date'))
for audit in
list(root.find(ns + 'pdbx_chem_comp_auditCategory'))]
atoms = list(root.find(ns + 'chem_comp_atomCategory'))
n_atoms = len(atoms)
ideal_coords = np.zeros((n_atoms, 3))
model_coords = np.zeros((n_atoms, 3))
atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype)
elements = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['element'].dtype)
resnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['resname'].dtype)
charges = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype)
resnums = np.ones(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype)
alternate_atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype)
leaving_atom_flags = np.zeros(n_atoms, np.bool)
aromatic_flags = np.zeros(n_atoms, np.bool)
stereo_configs = np.zeros(n_atoms, np.bool)
ordinals = np.zeros(n_atoms, int)
name2index = {}
for i, atom in enumerate(atoms):
data = dict([(child.tag[len_ns:], child.text) for child in list(atom)])
name = data.get('pdbx_component_atom_id', 'X')
name2index[name] = i
atomnames[i] = name
elements[i] = data.get('type_symbol', 'X')
resnames[i] = data.get('pdbx_component_comp_id', 'UNK')
charges[i] = float(data.get('charge', 0))
alternate_atomnames[i] = data.get('alt_atom_id', 'X')
leaving_atom_flags[i] = data.get('pdbx_leaving_atom_flag') == 'Y'
aromatic_flags[i] = data.get('pdbx_atomatic_flag') == 'Y'
stereo_configs[i] = data.get('pdbx_stereo_config') == 'Y'
ordinals[i] = int(data.get('pdbx_ordinal', 0))
model_coords[i, 0] = float(data.get('model_Cartn_x', 0))
model_coords[i, 1] = float(data.get('model_Cartn_y', 0))
model_coords[i, 2] = float(data.get('model_Cartn_z', 0))
ideal_coords[i, 0] = float(data.get('pdbx_model_Cartn_x_ideal', 0))
ideal_coords[i, 1] = float(data.get('pdbx_model_Cartn_y_ideal', 0))
ideal_coords[i, 2] = float(data.get('pdbx_model_Cartn_z_ideal', 0))
pdbid = dict_.get('model_coordinates_db_code')
if pdbid:
model = AtomGroup(cci + ' model ({0})'.format(pdbid))
else:
model = AtomGroup(cci + ' model')
model.setCoords(model_coords)
model.setNames(atomnames)
model.setResnames(resnames)
model.setResnums(resnums)
model.setElements(elements)
model.setCharges(charges)
model.setFlags('leaving_atom_flags', leaving_atom_flags)
model.setFlags('aromatic_flags', aromatic_flags)
model.setFlags('stereo_configs', stereo_configs)
model.setData('ordinals', ordinals)
model.setData('alternate_atomnames', alternate_atomnames)
dict_['model'] = model
ideal = model.copy()
ideal.setTitle(cci + ' ideal')
ideal.setCoords(ideal_coords)
dict_['ideal'] = ideal
bonds = []
warned = set()
for bond in list(root.find(ns + 'chem_comp_bondCategory') or bonds):
name_1 = bond.get('atom_id_1')
name_2 = bond.get('atom_id_2')
try:
bonds.append((name2index[name_1], name2index[name_2]))
except KeyError:
if name_1 not in warned and name_1 not in name2index:
warned.add(name_1)
LOGGER.warn('{0} specified {1} in bond category is not '
'a valid atom name.'.format(repr(name_1), cci))
if name_2 not in warned and name_2 not in name2index:
warned.add(name_2)
LOGGER.warn('{0} specified {1} in bond category is not '
'a valid atom name.'.format(repr(name_2), cci))
if bonds:
bonds = np.array(bonds, int)
model.setBonds(bonds)
ideal.setBonds(bonds)
return dict_
def fetchPDBLigand(cci, filename=None):
"""Fetch PDB ligand data from PDB_ for chemical component *cci*.
*cci* may be 3-letter chemical component identifier or a valid XML
filename. If *filename* is given, XML file will be saved with that name.
If you query ligand data frequently, you may configure ProDy to save XML
files in your computer. Set ``ligand_xml_save`` option **True**, i.e.
``confProDy(ligand_xml_save=True)``. Compressed XML files will be save
to ProDy package folder, e.g. :file:`/home/user/.prody/pdbligands`. Each
file is around 5Kb when compressed.
This function is compatible with PDBx/PDBML v 4.0.
Ligand data is returned in a dictionary. Ligand coordinate atom data with
*model* and *ideal* coordinate sets are also stored in this dictionary.
Note that this dictionary will contain data that is present in the XML
file and all Ligand Expo XML files do not contain every possible data
field. So, it may be better if you use :meth:`dict.get` instead of
indexing the dictionary, e.g. to retrieve formula weight (or relative
molar mass) of the chemical component use ``data.get('formula_weight')``
instead of ``data['formula_weight']`` to avoid exceptions when this data
field is not found in the XML file. URL and/or path of the XML file are
returned in the dictionary with keys ``url`` and ``path``, respectively.
Following example downloads data for ligand STI (a.k.a. Gleevec and
Imatinib) and calculates RMSD between model (X-ray structure 1IEP) and
ideal (energy minimized) coordinate sets:
.. ipython:: python
from prody import *
ligand_data = fetchPDBLigand('STI')
ligand_data['model_coordinates_db_code']
ligand_model = ligand_data['model']
ligand_ideal = ligand_data['ideal']
transformation = superpose(ligand_ideal.noh, ligand_model.noh)
calcRMSD(ligand_ideal.noh, ligand_model.noh)"""
if not isinstance(cci, str):
raise TypeError('cci must be a string')
if isfile(cci):
inp = openFile(cci)
xml = inp.read()
inp.close()
url = None
path = cci
cci = splitext(splitext(split(cci)[1])[0])[0].upper()
elif len(cci) > 4 or not cci.isalnum():
raise ValueError('cci must be 3-letters long and alphanumeric or '
'a valid filename')
else:
xml = None
cci = cci.upper()
if SETTINGS.get('ligand_xml_save'):
folder = join(getPackagePath(), 'pdbligands')
if not isdir(folder):
makePath(folder)
xmlgz = path = join(folder, cci + '.xml.gz')
if isfile(xmlgz):
with openFile(xmlgz) as inp:
xml = inp.read()
else:
path = None
#url = ('http://ligand-expo.rcsb.org/reports/{0[0]}/{0}/{0}'
# '.xml'.format(cci.upper()))
url = 'http://files.rcsb.org/ligands/download/{0}.xml'.format(
cci.upper())
if not xml:
#'http://www.pdb.org/pdb/files/ligand/{0}.xml'
try:
inp = openURL(url)
except IOError:
raise IOError(
'XML file for ligand {0} is not found online'.format(cci))
else:
xml = inp.read()
inp.close()
if filename:
out = openFile(filename, mode='w', folder=folder)
out.write(xml)
out.close()
if SETTINGS.get('ligand_xml_save'):
with openFile(xmlgz, 'w') as out:
out.write(xml)
import xml.etree.cElementTree as ET
root = ET.XML(xml)
if (root.get('{http://www.w3.org/2001/XMLSchema-instance}'
'schemaLocation') !=
'http://pdbml.pdb.org/schema/pdbx-v40.xsd pdbx-v40.xsd'):
LOGGER.warn('XML is not in PDBx/PDBML v 4.0 format, resulting '
'dictionary may not contain all data fields')
ns = root.tag[:root.tag.rfind('}') + 1]
len_ns = len(ns)
dict_ = {'url': url, 'path': path}
for child in list(root.find(ns + 'chem_compCategory')[0]):
tag = child.tag[len_ns:]
if tag.startswith('pdbx_'):
tag = tag[5:]
dict_[tag] = child.text
dict_['formula_weight'] = float(dict_.get('formula_weight'))
identifiers_and_descriptors = []
results = root.find(ns + 'pdbx_chem_comp_identifierCategory')
if results:
identifiers_and_descriptors.extend(results)
results = root.find(ns + 'pdbx_chem_comp_descriptorCategory')
if results:
identifiers_and_descriptors.extend(results)
for child in identifiers_and_descriptors:
program = child.get('program').replace(' ', '_')
type_ = child.get('type').replace(' ', '_')
dict_[program + '_' + type_] = child[0].text
dict_[program + '_version'] = child.get('program_version')
dict_['audits'] = [
(audit.get('action_type'), audit.get('date'))
for audit in list(root.find(ns + 'pdbx_chem_comp_auditCategory'))
]
atoms = list(root.find(ns + 'chem_comp_atomCategory'))
n_atoms = len(atoms)
ideal_coords = np.zeros((n_atoms, 3))
model_coords = np.zeros((n_atoms, 3))
atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype)
elements = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['element'].dtype)
resnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['resname'].dtype)
charges = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype)
resnums = np.ones(n_atoms, dtype=ATOMIC_FIELDS['charge'].dtype)
alternate_atomnames = np.zeros(n_atoms, dtype=ATOMIC_FIELDS['name'].dtype)
leaving_atom_flags = np.zeros(n_atoms, np.bool)
aromatic_flags = np.zeros(n_atoms, np.bool)
stereo_configs = np.zeros(n_atoms, np.bool)
ordinals = np.zeros(n_atoms, int)
name2index = {}
for i, atom in enumerate(atoms):
data = dict([(child.tag[len_ns:], child.text) for child in list(atom)])
name = data.get('pdbx_component_atom_id', 'X')
name2index[name] = i
atomnames[i] = name
elements[i] = data.get('type_symbol', 'X')
resnames[i] = data.get('pdbx_component_comp_id', 'UNK')
charges[i] = float(data.get('charge', 0))
alternate_atomnames[i] = data.get('alt_atom_id', 'X')
leaving_atom_flags[i] = data.get('pdbx_leaving_atom_flag') == 'Y'
aromatic_flags[i] = data.get('pdbx_atomatic_flag') == 'Y'
stereo_configs[i] = data.get('pdbx_stereo_config') == 'Y'
ordinals[i] = int(data.get('pdbx_ordinal', 0))
model_coords[i, 0] = float(data.get('model_Cartn_x', 0))
model_coords[i, 1] = float(data.get('model_Cartn_y', 0))
model_coords[i, 2] = float(data.get('model_Cartn_z', 0))
ideal_coords[i, 0] = float(data.get('pdbx_model_Cartn_x_ideal', 0))
ideal_coords[i, 1] = float(data.get('pdbx_model_Cartn_y_ideal', 0))
ideal_coords[i, 2] = float(data.get('pdbx_model_Cartn_z_ideal', 0))
pdbid = dict_.get('model_coordinates_db_code')
if pdbid:
model = AtomGroup(cci + ' model ({0})'.format(pdbid))
else:
model = AtomGroup(cci + ' model')
model.setCoords(model_coords)
model.setNames(atomnames)
model.setResnames(resnames)
model.setResnums(resnums)
model.setElements(elements)
model.setCharges(charges)
model.setFlags('leaving_atom_flags', leaving_atom_flags)
model.setFlags('aromatic_flags', aromatic_flags)
model.setFlags('stereo_configs', stereo_configs)
model.setData('ordinals', ordinals)
model.setData('alternate_atomnames', alternate_atomnames)
dict_['model'] = model
ideal = model.copy()
ideal.setTitle(cci + ' ideal')
ideal.setCoords(ideal_coords)
dict_['ideal'] = ideal
bonds = []
warned = set()
for bond in list(root.find(ns + 'chem_comp_bondCategory') or bonds):
name_1 = bond.get('atom_id_1')
name_2 = bond.get('atom_id_2')
try:
bonds.append((name2index[name_1], name2index[name_2]))
except KeyError:
if name_1 not in warned and name_1 not in name2index:
warned.add(name_1)
LOGGER.warn('{0} specified {1} in bond category is not '
'a valid atom name.'.format(repr(name_1), cci))
if name_2 not in warned and name_2 not in name2index:
warned.add(name_2)
LOGGER.warn('{0} specified {1} in bond category is not '
'a valid atom name.'.format(repr(name_2), cci))
if bonds:
bonds = np.array(bonds, int)
model.setBonds(bonds)
ideal.setBonds(bonds)
return dict_
def parseNMD(filename, type=NMA):
"""Returns :class:`.NMA` and :class:`.AtomGroup` instances storing data
parsed from *filename* in :file:`.nmd` format. Type should be :class:`.NMA`
or a subclass such as :class:`.PCA`, :class:`.ANM`, or :class:`.GNM`."""
if isinstance(type, str):
type = type.upper().strip()
if 'ANM' in type:
type = ANM
elif 'GNM' in type:
type = GNM
elif 'PCA' in type or 'EDA' in type:
type = PCA
elif type == 'NMA':
type = NMA
else:
type = None
if not issubclass(type, NMA):
raise TypeError('type must be NMA, ANM, GNM, or PCA')
atomic = {}
atomic.update([(label, None) for label in NMD_LABEL_MAP])
atomic['coordinates'] = None
atomic['name'] = None
modes = []
with open(filename) as nmd:
for i, line in enumerate(nmd):
try:
label, data = line.split(None, 1)
except ValueError:
pass
if label == 'mode':
modes.append((i + 1, data))
elif label in atomic:
if atomic[label] is None:
atomic[label] = (i + 1, data)
else:
LOGGER.warn('Data label {0} is found more than once in '
'{1}.'.format(repr(label), repr(filename)))
name = atomic.pop('name', '')[1].strip() or splitext(split(filename)[1])[0]
ag = AtomGroup(name)
dof = None
n_atoms = None
line, coords = atomic.pop('coordinates', None)
if coords is not None:
coords = np.fromstring(coords, dtype=float, sep=' ')
dof = coords.shape[0]
if dof % 3 != 0:
LOGGER.warn('Coordinate data in {0} at line {1} is corrupt '
'and will be omitted.'.format(repr(filename), line))
else:
n_atoms = dof // 3
coords = coords.reshape((n_atoms, 3))
ag.setCoords(coords)
from prody.atomic import ATOMIC_FIELDS
for label, data in atomic.items(): # PY3K: OK
if data is None:
continue
line, data = data
data = data.split()
if n_atoms is None:
n_atoms = len(data)
dof = n_atoms * 3
elif len(data) != n_atoms:
LOGGER.warn('Data with label {0} in {1} at line {2} is '
'corrupt, expected {2} values, parsed {3}.'.format(
repr(label), repr(filename), line, n_atoms,
len(data)))
continue
label = NMD_LABEL_MAP[label]
data = np.array(data, dtype=ATOMIC_FIELDS[label].dtype)
ag.setData(label, data)
if not modes:
return None, ag
length = len(modes[0][1].split())
is3d = length > n_atoms + 2
if dof is None:
dof = length - (length % 3)
elif not is3d: # GNM
dof = n_atoms
array = np.zeros((dof, len(modes)))
less = 0
eigvals = []
count = 0
for i, (line, mode) in enumerate(modes):
mode = np.fromstring(mode, dtype=float, sep=' ')
diff = len(mode) - dof
if diff < 0 or diff > 2:
LOGGER.warn('Mode data in {0} at line {1} is corrupt.'.format(
repr(filename), line))
continue
array[:, i - less] = mode[diff:]
count += 1
eigvals.append(mode[:diff])
if count == 0:
return None, ag
try:
eigvals = np.array(eigvals, dtype=float)
except TypeError:
LOGGER.warn('Failed to parse eigenvalues from {0}.'.format(
repr(filename)))
if eigvals.shape[1] > 2:
LOGGER.warn('Failed to parse eigenvalues from {0}.'.format(
repr(filename)))
eigvals = None
elif eigvals.shape[1] == 1:
if np.all(eigvals % 1 == 0):
LOGGER.warn('Failed to parse eigenvalues from {0}.'.format(
repr(filename)))
eigvals = None
else:
eigvals = eigvals.flatten()**2
else:
eigvals = eigvals[:, 1]**2
nma = type(name)
if type != PCA:
eigvals = 1. / eigvals
if count != array.shape[1]:
array = array[:, :count].copy()
nma.setEigens(array, eigvals)
return nma, ag
def parseNMD(filename, type=None):
"""Return :class:`.NMA` and :class:`.AtomGroup` instances storing data
parsed from *filename* in :file:`.nmd` format. Type of :class:`.NMA`
instance, e.g. :class:`.PCA`, :class:`.ANM`, or :class:`.GNM` will
be determined based on mode data."""
assert not isinstance(type, NMA), 'type must be NMA, ANM, GNM, or PCA'
atomic = {}
atomic.update([(label, None) for label in NMD_LABEL_MAP])
atomic['coordinates'] = None
atomic['name'] = None
modes = []
with open(filename) as nmd:
for i, line in enumerate(nmd):
try:
label, data = line.split(None, 1)
except ValueError:
pass
if label == 'mode':
modes.append((i + 1, data))
elif label in atomic:
if atomic[label] is None:
atomic[label] = (i + 1, data)
else:
LOGGER.warn('Data label {0} is found more than once in '
'{1}.'.format(repr(label), repr(filename)))
name = atomic.pop('name', '')[1].strip() or splitext(split(filename)[1])[0]
ag = AtomGroup(name)
dof = None
n_atoms = None
line, coords = atomic.pop('coordinates', None)
if coords is not None:
coords = np.fromstring(coords, dtype=float, sep=' ')
dof = coords.shape[0]
if dof % 3 != 0:
LOGGER.warn('Coordinate data in {0} at line {1} is corrupt '
'and will be omitted.'.format(repr(filename), line))
else:
n_atoms = dof / 3
coords = coords.reshape((n_atoms, 3))
ag.setCoords(coords)
from prody.atomic import ATOMIC_FIELDS
for label, data in atomic.items(): # PY3K: OK
if data is None:
continue
line, data = data
data = data.split()
if n_atoms is None:
n_atoms = len(data)
dof = n_atoms * 3
elif len(data) != n_atoms:
LOGGER.warn('Data with label {0} in {1} at line {2} is '
'corrupt, expected {2} values, parsed {3}.'.format(
repr(label), repr(filename), line, n_atoms, len(data)))
continue
label = NMD_LABEL_MAP[label]
data = np.array(data, dtype=ATOMIC_FIELDS[label].dtype)
ag.setData(label, data)
if not modes:
return None, ag
length = len(modes[0][1].split())
is3d = length > n_atoms + 2
if dof is None:
dof = length - (length % 3)
elif not is3d: # GNM
dof = n_atoms
array = np.zeros((dof, len(modes)))
less = 0
eigvals = []
count = 0
for i, (line, mode) in enumerate(modes):
mode = np.fromstring(mode, dtype=float, sep=' ')
diff = len(mode) - dof
if diff < 0 or diff > 2:
LOGGER.warn('Mode data in {0} at line {1} is corrupt.'
.format(repr(filename), line))
continue
array[:, i - less] = mode[diff:]
count += 1
eigvals.append(mode[:diff])
if count == 0:
return None, ag
try:
eigvals = np.array(eigvals, dtype=float)
except TypeError:
LOGGER.warn('Failed to parse eigenvalues from {0}.'
.format(repr(filename)))
if eigvals.shape[1] > 2:
LOGGER.warn('Failed to parse eigenvalues from {0}.'
.format(repr(filename)))
eigvals = None
elif eigvals.shape[1] == 1:
if np.all(eigvals % 1 == 0):
LOGGER.warn('Failed to parse eigenvalues from {0}.'
.format(repr(filename)))
eigvals = None
else:
eigvals = eigvals.flatten() ** 2
else:
eigvals = eigvals[:, 1] ** 2
if is3d:
if eigvals is not None and np.all(eigvals[:-1] >= eigvals[1:]):
nma = PCA(name)
else:
nma = ANM(name)
else:
nma = GNM(name)
if count != array.shape[1]:
array = array[:, :count].copy()
nma.setEigens(array, eigvals)
return nma, ag
