Data Types
A module with various data-types used throughout Data-CAT.
Index
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The default datatype of |
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The datatype of the |
API
- dataCAT.dtype.ATOMS_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.atoms
.
Most field names are based on to their, identically named, counterpart as produced by
readpdb()
, the data in question being stored in theAtom.properties.pdb_info
block.There are six exception to this general rule:
symbol
: Based onAtom.symbol
.charge
: Based onAtom.properties.charge
.charge_float
: Based onAtom.properties.charge_float
.
>>> from dataCAT.dtype import ATOMS_DTYPE >>> print(repr(ATOMS_DTYPE)) dtype([('IsHeteroAtom', '?'), ('SerialNumber', '<i2'), ('Name', 'S4'), ('ResidueName', 'S3'), ('ChainId', 'S1'), ('ResidueNumber', '<i2'), ('x', '<f4'), ('y', '<f4'), ('z', '<f4'), ('Occupancy', '<f4'), ('TempFactor', '<f4'), ('symbol', 'S4'), ('charge', 'i1'), ('charge_float', '<f8')])
- dataCAT.dtype.BONDS_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.bonds
.
Field names are based on to their, identically named, counterpart in
plams.Bond
.>>> from dataCAT.dtype import BONDS_DTYPE >>> print(repr(BONDS_DTYPE)) dtype([('atom1', '<i4'), ('atom2', '<i4'), ('order', 'i1')])
- dataCAT.dtype.ATOM_COUNT_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.atom_count
.
>>> from dataCAT.dtype import ATOM_COUNT_DTYPE >>> print(repr(ATOM_COUNT_DTYPE)) dtype('int32')
- dataCAT.dtype.BOND_COUNT_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.bond_count
.
>>> from dataCAT.dtype import BOND_COUNT_DTYPE >>> print(repr(BOND_COUNT_DTYPE)) dtype('int32')
- dataCAT.dtype.LIG_IDX_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.index
as used by the ligand database.
>>> import h5py >>> from dataCAT.dtype import LIG_IDX_DTYPE >>> print(repr(LIG_IDX_DTYPE)) dtype([('ligand', 'O'), ('ligand anchor', 'O')]) >>> h5py.check_string_dtype(LIG_IDX_DTYPE.fields['ligand'][0]) string_info(encoding='ascii', length=None) >>> h5py.check_string_dtype(LIG_IDX_DTYPE.fields['ligand anchor'][0]) string_info(encoding='ascii', length=None)
- dataCAT.dtype.QD_IDX_DTYPE : numpy.dtype = ...
The datatype of
PDBContainer.index
as used by the QD database.
>>> import h5py >>> from dataCAT.dtype import QD_IDX_DTYPE >>> print(repr(QD_IDX_DTYPE)) dtype([('core', 'O'), ('core anchor', 'O'), ('ligand', 'O'), ('ligand anchor', 'O')]) >>> h5py.check_string_dtype(QD_IDX_DTYPE.fields['core'][0]) string_info(encoding='ascii', length=None) >>> h5py.check_string_dtype(QD_IDX_DTYPE.fields['core anchor'][0]) string_info(encoding='ascii', length=None) >>> h5py.check_string_dtype(QD_IDX_DTYPE.fields['ligand'][0]) string_info(encoding='ascii', length=None) >>> h5py.check_string_dtype(QD_IDX_DTYPE.fields['ligand anchor'][0]) string_info(encoding='ascii', length=None)
- dataCAT.dtype.BACKUP_IDX_DTYPE : numpy.dtype = ...
The default datatype of
PDBContainer.index
.
>>> from dataCAT.dtype import BACKUP_IDX_DTYPE >>> print(repr(BACKUP_IDX_DTYPE)) dtype('int32')
- dataCAT.dtype.DT_DTYPE : numpy.dtype = ...
The datatype of the
"date"
dataset created bycreate_hdf5_log()
.
Field names are based on their, identically named, counterpart in the
datetime
class.>>> from dataCAT.dtype import DT_DTYPE >>> print(repr(DT_DTYPE)) dtype([('year', '<i2'), ('month', 'i1'), ('day', 'i1'), ('hour', 'i1'), ('minute', 'i1'), ('second', 'i1'), ('microsecond', '<i4')])
- dataCAT.dtype.VERSION_DTYPE : numpy.dtype = ...
The datatype of the
"version"
dataset created bycreate_hdf5_log()
.
Field names are based on their, identically named, counterpart in the
nanoutils.VersionInfo
namedtuple.>>> from dataCAT.dtype import VERSION_DTYPE >>> print(repr(VERSION_DTYPE)) dtype([('major', 'i1'), ('minor', 'i1'), ('micro', 'i1')])
- dataCAT.dtype.INDEX_DTYPE : numpy.dtype = ...
The datatype of the
"index"
dataset created bycreate_hdf5_log()
.
Used for representing a ragged array of 32-bit integers.
>>> import h5py >>> from dataCAT.dtype import INDEX_DTYPE >>> print(repr(INDEX_DTYPE)) dtype('O') >>> h5py.check_vlen_dtype(INDEX_DTYPE) dtype('int32')
- dataCAT.dtype.MSG_DTYPE : numpy.dtype = ...
The datatype of the
"message"
dataset created bycreate_hdf5_log()
.
Used for representing variable-length ASCII strings.
>>> import h5py >>> from dataCAT.dtype import MSG_DTYPE >>> print(repr(MSG_DTYPE)) dtype('O') >>> h5py.check_string_dtype(MSG_DTYPE) string_info(encoding='ascii', length=None)
- dataCAT.dtype.FORMULA_DTYPE : numpy.dtype = ...
The datatype of the
"/ligand/properties/formula"
dataset..
Used for representing variable-length ASCII strings.
>>> import h5py >>> from dataCAT.dtype import FORMULA_DTYPE >>> print(repr(FORMULA_DTYPE)) dtype('O') >>> h5py.check_string_dtype(FORMULA_DTYPE) string_info(encoding='ascii', length=None)
- dataCAT.dtype.LIG_COUNT_DTYPE : numpy.dtype = ...
The datatype of the
"/qd/properties/ligand count"
dataset..
>>> from dataCAT.dtype import LIG_COUNT_DTYPE >>> print(repr(LIG_COUNT_DTYPE)) dtype('int32')