Source code for

"""bundletrajectory - a module for I/O from large MD simulations.

The BundleTrajectory class writes trajectory into a directory with the
following structure, except we now use JSON instead of pickle,
so this text needs updating::

    filename.bundle (dir)
        metadata.json          Data about the file format, and about which
                               data is present.
        frames                 The number of frames (ascii file)
        F0 (dir)               Frame number 0
            smalldata.ulm      Small data structures in a dictionary
                               (pbc, cell, ...)
            numbers.ulm        Atomic numbers
            positions.ulm      Positions
            momenta.ulm        Momenta
        F1 (dir)

There is a folder for each frame, and the data is in the ASE Ulm format.

import os
import sys
import shutil
import time
from pathlib import Path

import numpy as np

from ase import Atoms
# The system json module causes memory leaks!  Use ase's own.
# import json
from import jsonio
from import open as ulmopen
from ase.parallel import paropen, world, barrier
from ase.calculators.singlepoint import (SinglePointCalculator,

[docs]class BundleTrajectory: """Reads and writes atoms into a .bundle directory. The BundleTrajectory is an alternative way of storing trajectories, intended for large-scale molecular dynamics simulations, where a single flat file becomes unwieldy. Instead, the data is stored in directory, a 'bundle' (the name bundle is inspired from bundles in Mac OS, which are really just directories the user is supposed to think of as a single file-like unit). Parameters: filename: The name of the directory. Preferably ending in .bundle. mode (optional): The file opening mode. 'r' means open for reading, 'w' for writing and 'a' for appending. Default: 'r'. If opening in write mode, and the filename already exists, the old file is renamed to .bak (any old .bak file is deleted), except if the existing file is empty. atoms (optional): The atoms that will be written. Can only be specified in write or append mode. If not specified, the atoms must be given as an argument to the .write() method instead. backup=True: Use backup=False to disable renaming of an existing file. backend='ulm': Request a backend. Currently only 'ulm' is supported. Only honored when writing. singleprecision=False: Store floating point data in single precision (ulm backend only). """ slavelog = True # Log from all nodes def __init__(self, filename, mode='r', atoms=None, backup=True, backend='ulm', singleprecision=False): self.state = 'constructing' self.filename = filename self.pre_observers = [] # callback functions before write is performed self.post_observers = [] # callback functions after write is performed self.master = world.rank == 0 self.extra_data = [] self.singleprecision = singleprecision self._set_defaults() if mode == 'r': if atoms is not None: raise ValueError('You cannot specify atoms in read mode.') self._open_read() elif mode == 'w': self._open_write(atoms, backup, backend) elif mode == 'a': self._open_append(atoms) else: raise ValueError('Unknown mode: ' + str(mode)) def _set_defaults(self): "Set default values for internal parameters." self.version = 1 self.subtype = 'normal' self.datatypes = {'positions': True, 'numbers': 'once', 'tags': 'once', 'masses': 'once', 'momenta': True, 'forces': True, 'energy': True, 'energies': False, 'stress': False, 'magmoms': True} def _set_backend(self, backend): """Set the backed doing the actual I/O.""" if backend is not None: self.backend_name = backend if self.backend_name == 'ulm': self.backend = UlmBundleBackend(self.master, self.singleprecision) else: raise NotImplementedError( 'This version of ASE cannot use BundleTrajectory ' 'with backend "%s"' % self.backend_name)
[docs] def write(self, atoms=None): """Write the atoms to the file. If the atoms argument is not given, the atoms object specified when creating the trajectory object is used. """ # Check that we are in write mode if self.state == 'prewrite': self.state = 'write' assert self.nframes == 0 elif self.state != 'write': raise RuntimeError('Cannot write in ' + self.state + ' mode.') if atoms is None: atoms = self.atoms for image in atoms.iterimages(): self._write_atoms(image)
def _write_atoms(self, atoms): # OK, it is a real atoms object. Write it. self._call_observers(self.pre_observers) self.log('Beginning to write frame ' + str(self.nframes)) framedir = self._make_framedir(self.nframes) # Check which data should be written the first time: # Modify datatypes so any element of type 'once' becomes true # for the first frame but false for subsequent frames. datatypes = {} for k, v in self.datatypes.items(): if v == 'once': v = (self.nframes == 0) datatypes[k] = v # Write 'small' data structures. They are written jointly. smalldata = {'pbc': atoms.get_pbc(), 'cell': atoms.get_cell(), 'natoms': atoms.get_global_number_of_atoms(), 'constraints': atoms.constraints} if datatypes.get('energy'): try: smalldata['energy'] = atoms.get_potential_energy() except (RuntimeError, PropertyNotImplementedError): self.datatypes['energy'] = False if datatypes.get('stress'): try: smalldata['stress'] = atoms.get_stress() except PropertyNotImplementedError: self.datatypes['stress'] = False self.backend.write_small(framedir, smalldata) # Write the large arrays. if datatypes.get('positions'): self.backend.write(framedir, 'positions', atoms.get_positions()) if datatypes.get('numbers'): self.backend.write(framedir, 'numbers', atoms.get_atomic_numbers()) if datatypes.get('tags'): if atoms.has('tags'): self.backend.write(framedir, 'tags', atoms.get_tags()) else: self.datatypes['tags'] = False if datatypes.get('masses'): if atoms.has('masses'): self.backend.write(framedir, 'masses', atoms.get_masses()) else: self.datatypes['masses'] = False if datatypes.get('momenta'): if atoms.has('momenta'): self.backend.write(framedir, 'momenta', atoms.get_momenta()) else: self.datatypes['momenta'] = False if datatypes.get('magmoms'): if atoms.has('initial_magmoms'): self.backend.write(framedir, 'magmoms', atoms.get_initial_magnetic_moments()) else: self.datatypes['magmoms'] = False if datatypes.get('forces'): try: x = atoms.get_forces() except (RuntimeError, PropertyNotImplementedError): self.datatypes['forces'] = False else: self.backend.write(framedir, 'forces', x) del x if datatypes.get('energies'): try: x = atoms.get_potential_energies() except (RuntimeError, PropertyNotImplementedError): self.datatypes['energies'] = False else: self.backend.write(framedir, 'energies', x) del x # Write any extra data for (label, source, once) in self.extra_data: if self.nframes == 0 or not once: if source is not None: x = source() else: x = atoms.get_array(label) self.backend.write(framedir, label, x) del x if once: self.datatypes[label] = 'once' else: self.datatypes[label] = True # Finally, write metadata if it is the first frame if self.nframes == 0: metadata = {'datatypes': self.datatypes} self._write_metadata(metadata) self._write_nframes(self.nframes + 1) self._call_observers(self.post_observers) self.log('Done writing frame ' + str(self.nframes)) self.nframes += 1
[docs] def select_data(self, data, value): """Selects if a given data type should be written. Data can be written in every frame (specify True), in the first frame only (specify 'only') or not at all (specify False). Not all data types support the 'only' keyword, if not supported it is interpreted as True. The following data types are supported, the letter in parenthesis indicates the default: positions (T), numbers (O), tags (O), masses (O), momenta (T), forces (T), energy (T), energies (F), stress (F), magmoms (T) If a given property is not present during the first write, it will be not be saved at all. """ if value not in (True, False, 'once'): raise ValueError('Unknown write mode') if data not in self.datatypes: raise ValueError('Unsupported data type: ' + data) self.datatypes[data] = value
[docs] def set_extra_data(self, name, source=None, once=False): """Adds extra data to be written. Parameters: name: The name of the data. source (optional): If specified, a callable object returning the data to be written. If not specified it is instead assumed that the atoms contains the data as an array of the same name. once (optional): If specified and True, the data will only be written to the first frame. """ self.extra_data.append((name, source, once))
[docs] def close(self): "Closes the trajectory." self.state = 'closed' lf = getattr(self, 'logfile', None) self.backend.close(log=lf) if lf is not None: lf.close() del self.logfile
[docs] def log(self, text): """Write to the log file in the bundle. Logging is only possible in write/append mode. This function is mainly for internal use, but can also be called by the user. """ if not (self.master or self.slavelog): return text = time.asctime() + ': ' + text if hasattr(self, 'logfile'): # Logging enabled if self.logfile is None: # Logfile not yet open try: self.logdata.append(text) except AttributeError: self.logdata = [text] else: self.logfile.write(text + '\n') self.logfile.flush() else: raise RuntimeError('Cannot write to log file in mode ' + self.state)
# __getitem__ is the main reading method. def __getitem__(self, n): return self._read(n) def _read(self, n): """Read an atoms object from the BundleTrajectory.""" if self.state != 'read': raise IOError('Cannot read in %s mode' % (self.state,)) if n < 0: n += self.nframes if n < 0 or n >= self.nframes: raise IndexError('Trajectory index %d out of range [0, %d[' % (n, self.nframes)) framedir = os.path.join(self.filename, 'F' + str(n)) framezero = os.path.join(self.filename, 'F0') smalldata = self.backend.read_small(framedir) data = {} data['pbc'] = smalldata['pbc'] data['cell'] = smalldata['cell'] data['constraint'] = smalldata['constraints'] if self.subtype == 'split': self.backend.set_fragments(smalldata['fragments']) self.atom_id, dummy = self.backend.read_split(framedir, 'ID') else: self.atom_id = None atoms = Atoms(**data) natoms = smalldata['natoms'] for name in ('positions', 'numbers', 'tags', 'masses', 'momenta'): if self.datatypes.get(name): atoms.arrays[name] = self._read_data(framezero, framedir, name, self.atom_id) assert len(atoms.arrays[name]) == natoms # Create the atoms object if self.datatypes.get('energy'): if self.datatypes.get('forces'): forces =, 'forces') else: forces = None if self.datatypes.get('magmoms'): magmoms =, 'magmoms') else: magmoms = None calc = SinglePointCalculator(atoms, energy=smalldata.get('energy'), forces=forces, stress=smalldata.get('stress'), magmoms=magmoms) atoms.calc = calc return atoms
[docs] def read_extra_data(self, name, n=0): """Read extra data stored alongside the atoms. Currently only used to read data stored by an NPT dynamics object. The data is not associated with individual atoms. """ if self.state != 'read': raise IOError('Cannot read extra data in %s mode' % (self.state,)) # Handle negative n. if n < 0: n += self.nframes if n < 0 or n >= self.nframes: raise IndexError('Trajectory index %d out of range [0, %d[' % (n, self.nframes)) framedir = os.path.join(self.filename, 'F' + str(n)) framezero = os.path.join(self.filename, 'F0') return self._read_data(framezero, framedir, name, self.atom_id)
def _read_data(self, f0, f, name, atom_id): "Read single data item." if self.subtype == 'normal': if self.datatypes[name] == 'once': d =, name) else: d =, name) elif self.subtype == 'split': if self.datatypes[name] == 'once': d, issplit = self.backend.read_split(f0, name) atom_id, dummy = self.backend.read_split(f0, 'ID') else: d, issplit = self.backend.read_split(f, name) if issplit: assert atom_id is not None assert len(d) == len(atom_id) d[atom_id] = np.array(d) return d def __len__(self): return self.nframes def _open_log(self): if not (self.master or self.slavelog): return if self.master: lfn = os.path.join(self.filename, 'log.txt') else: lfn = os.path.join(self.filename, ('log-node%d.txt' % (world.rank,))) self.logfile = open(lfn, 'a', 1) # Append to log if it exists. if hasattr(self, 'logdata'): for text in self.logdata: self.logfile.write(text + '\n') self.logfile.flush() del self.logdata def _open_write(self, atoms, backup, backend): "Open a bundle trajectory for writing." self._set_backend(backend) self.logfile = None # enable delayed logging self.atoms = atoms if os.path.exists(self.filename): # The output directory already exists. barrier() # all must have time to see it exists if not self.is_bundle(self.filename, allowempty=True): raise IOError( 'Filename "' + self.filename + '" already exists, but is not a BundleTrajectory.' + ' Cowardly refusing to remove it.') if self.is_empty_bundle(self.filename): barrier() self.log('Deleting old "%s" as it is empty' % (self.filename,)) self.delete_bundle(self.filename) elif not backup: barrier() self.log('Deleting old "%s" as backup is turned off.' % (self.filename,)) self.delete_bundle(self.filename) else: barrier() # Make a backup file bakname = self.filename + '.bak' if os.path.exists(bakname): barrier() # All must see it exists self.log('Deleting old backup file "%s"' % (bakname,)) self.delete_bundle(bakname) self.log('Renaming "%s" to "%s"' % (self.filename, bakname)) self._rename_bundle(self.filename, bakname) # Ready to create a new bundle. barrier() self.log('Creating new "%s"' % (self.filename,)) self._make_bundledir(self.filename) self.state = 'prewrite' self._write_metadata({}) self._write_nframes(0) # Mark new bundle as empty self._open_log() self.nframes = 0 def _open_read(self): "Open a bundle trajectory for reading." if not os.path.exists(self.filename): raise IOError('File not found: ' + self.filename) if not self.is_bundle(self.filename): raise IOError('Not a BundleTrajectory: ' + self.filename) self.state = 'read' # Read the metadata metadata = self._read_metadata() self.metadata = metadata if metadata['version'] > self.version: raise NotImplementedError( 'This version of ASE cannot read a BundleTrajectory version ' + str(metadata['version'])) if metadata['subtype'] not in ('normal', 'split'): raise NotImplementedError( 'This version of ASE cannot read BundleTrajectory subtype ' + metadata['subtype']) self.subtype = metadata['subtype'] if metadata['backend'] == 'ulm': self.singleprecision = metadata['ulm.singleprecision'] self._set_backend(metadata['backend']) self.nframes = self._read_nframes() if self.nframes == 0: raise IOError('Empty BundleTrajectory') self.datatypes = metadata['datatypes'] try: self.pythonmajor = metadata['python_ver'][0] except KeyError: self.pythonmajor = 2 # Assume written with Python 2. # We need to know if we are running Python 3.X and try to read # a bundle written with Python 2.X self.backend.readpy2 = (self.pythonmajor == 2) self.state = 'read' def _open_append(self, atoms): if not os.path.exists(self.filename): # OK, no old bundle. Open as for write instead. barrier() self._open_write(atoms, False) return if not self.is_bundle(self.filename): raise IOError('Not a BundleTrajectory: ' + self.filename) self.state = 'read' metadata = self._read_metadata() self.metadata = metadata if metadata['version'] != self.version: raise NotImplementedError( 'Cannot append to a BundleTrajectory version ' '%s (supported version is %s)' % (str(metadata['version']), str(self.version))) if metadata['subtype'] not in ('normal', 'split'): raise NotImplementedError( 'This version of ASE cannot append to BundleTrajectory ' 'subtype ' + metadata['subtype']) self.subtype = metadata['subtype'] if metadata['backend'] == 'ulm': self.singleprecision = metadata['ulm.singleprecision'] self._set_backend(metadata['backend']) self.nframes = self._read_nframes() self._open_log() self.log('Opening "%s" in append mode (nframes=%i)' % (self.filename, self.nframes)) self.state = 'write' self.atoms = atoms @property def path(self): return Path(self.filename) @property def metadata_path(self): return self.path / 'metadata.json' def _write_nframes(self, n): "Write the number of frames in the bundle." assert self.state == 'write' or self.state == 'prewrite' with paropen(self.path / 'frames', 'w') as fd: fd.write(str(n) + '\n') def _read_nframes(self): "Read the number of frames." return int((self.path / 'frames').read_text()) def _write_metadata(self, metadata): """Write the metadata file of the bundle. Modifies the medadata dictionary! """ # Add standard fields that must always be present. assert self.state == 'write' or self.state == 'prewrite' metadata['format'] = 'BundleTrajectory' metadata['version'] = self.version metadata['subtype'] = self.subtype metadata['backend'] = self.backend_name if self.backend_name == 'ulm': metadata['ulm.singleprecision'] = self.singleprecision metadata['python_ver'] = tuple(sys.version_info) encode = jsonio.MyEncoder(indent=4).encode fido = encode(metadata) with paropen(self.metadata_path, 'w') as fd: fd.write(fido) def _read_metadata(self): """Read the metadata.""" assert self.state == 'read' return jsonio.decode(self.metadata_path.read_text())
[docs] @staticmethod def is_bundle(filename, allowempty=False): """Check if a filename exists and is a BundleTrajectory. If allowempty=True, an empty folder is regarded as an empty BundleTrajectory.""" filename = Path(filename) if not filename.is_dir(): return False if allowempty and not os.listdir(filename): return True # An empty BundleTrajectory metaname = filename / 'metadata.json' if metaname.is_file(): mdata = jsonio.decode(metaname.read_text()) else: return False try: return mdata['format'] == 'BundleTrajectory' except KeyError: return False
[docs] @staticmethod def is_empty_bundle(filename): """Check if a filename is an empty bundle. Assumes that it is a bundle.""" if not os.listdir(filename): return True # Empty folders are empty bundles. with open(os.path.join(filename, 'frames'), 'rb') as fd: nframes = int( # File may be removed by the master immediately after this. barrier() return nframes == 0
[docs] @classmethod def delete_bundle(cls, filename): "Deletes a bundle." if world.rank == 0: # Only the master deletes if not cls.is_bundle(filename, allowempty=True): raise IOError( 'Cannot remove "%s" as it is not a bundle trajectory.' % (filename,)) if os.path.islink(filename): # A symbolic link to a bundle. Only remove the link. os.remove(filename) else: # A real bundle shutil.rmtree(filename) else: # All other tasks wait for the directory to go away. while os.path.exists(filename): time.sleep(1) # The master may not proceed before all tasks have seen the # directory go away, as it might otherwise create a new bundle # with the same name, fooling the wait loop in _make_bundledir. barrier()
def _rename_bundle(self, oldname, newname): "Rename a bundle. Used to create the .bak" if self.master: os.rename(oldname, newname) else: while os.path.exists(oldname): time.sleep(1) # The master may not proceed before all tasks have seen the # directory go away. barrier() def _make_bundledir(self, filename): """Make the main bundle directory. Since all MPI tasks might write to it, all tasks must wait for the directory to appear. """ self.log('Making directory ' + filename) assert not os.path.isdir(filename) barrier() if self.master: os.mkdir(filename) else: i = 0 while not os.path.isdir(filename): time.sleep(1) i += 1 if i > 10: self.log('Waiting %d seconds for %s to appear!' % (i, filename)) def _make_framedir(self, frame): """Make subdirectory for the frame. As only the master writes to it, no synchronization between MPI tasks is necessary. """ framedir = os.path.join(self.filename, 'F' + str(frame)) if self.master: self.log('Making directory ' + framedir) os.mkdir(framedir) return framedir
[docs] def pre_write_attach(self, function, interval=1, *args, **kwargs): """Attach a function to be called before writing begins. function: The function or callable object to be called. interval: How often the function is called. Default: every time (1). All other arguments are stored, and passed to the function. """ if not callable(function): raise ValueError('Callback object must be callable.') self.pre_observers.append((function, interval, args, kwargs))
[docs] def post_write_attach(self, function, interval=1, *args, **kwargs): """Attach a function to be called after writing ends. function: The function or callable object to be called. interval: How often the function is called. Default: every time (1). All other arguments are stored, and passed to the function. """ if not callable(function): raise ValueError('Callback object must be callable.') self.post_observers.append((function, interval, args, kwargs))
def _call_observers(self, obs): "Call pre/post write observers." for function, interval, args, kwargs in obs: if (self.nframes + 1) % interval == 0: function(*args, **kwargs)
class UlmBundleBackend: """Backend for BundleTrajectories stored as ASE Ulm files.""" def __init__(self, master, singleprecision): # Store if this backend will actually write anything self.writesmall = master self.writelarge = master self.singleprecision = singleprecision # Integer data may be downconverted to the following types self.integral_dtypes = ['uint8', 'int8', 'uint16', 'int16', 'uint32', 'int32', 'uint64', 'int64'] # Dict comprehensions not supported in Python 2.6 :-( self.int_dtype = dict((k, getattr(np, k)) for k in self.integral_dtypes) self.int_minval = dict((k, np.iinfo(self.int_dtype[k]).min) for k in self.integral_dtypes) self.int_maxval = dict((k, np.iinfo(self.int_dtype[k]).max) for k in self.integral_dtypes) self.int_itemsize = dict((k, np.dtype(self.int_dtype[k]).itemsize) for k in self.integral_dtypes) def write_small(self, framedir, smalldata): "Write small data to be written jointly." if self.writesmall: with ulmopen(os.path.join(framedir, 'smalldata.ulm'), 'w') as fd: fd.write(**smalldata) def write(self, framedir, name, data): "Write data to separate file." if self.writelarge: shape = data.shape dtype = str(data.dtype) stored_as = dtype all_identical = False # Check if it a type that can be stored with less space if np.issubdtype(data.dtype, np.integer): # An integer type, we may want to convert minval = data.min() maxval = data.max() # ulm cannot write np.bool_: all_identical = bool(minval == maxval) if all_identical: data = int(data.flat[0]) # Convert to standard integer else: for typ in self.integral_dtypes: if (minval >= self.int_minval[typ] and maxval <= self.int_maxval[typ] and data.itemsize > self.int_itemsize[typ]): # Convert to smaller type stored_as = typ data = data.astype(self.int_dtype[typ]) elif data.dtype == np.float32 or data.dtype == np.float64: all_identical = bool(data.min() == data.max()) if all_identical: data = float(data.flat[0]) # Convert to standard float elif data.dtype == np.float64 and self.singleprecision: # Downconvert double to single precision stored_as = 'float32' data = data.astype(np.float32) fn = os.path.join(framedir, name + '.ulm') with ulmopen(fn, 'w') as fd: fd.write(shape=shape, dtype=dtype, stored_as=stored_as, all_identical=all_identical, data=data) def read_small(self, framedir): "Read small data." with ulmopen(os.path.join(framedir, 'smalldata.ulm'), 'r') as fd: return fd.asdict() def read(self, framedir, name): "Read data from separate file." fn = os.path.join(framedir, name + '.ulm') with ulmopen(fn, 'r') as fd: if fd.all_identical: # Only a single data value data = np.zeros(fd.shape, dtype=getattr(np, fd.dtype)) + elif fd.dtype == fd.stored_as: # Easy, the array can be returned as-is. data = else: # Cast the data back data =, fd.dtype)) return data def read_info(self, framedir, name, split=None): """Read information about file contents without reading the data. Information is a dictionary containing as aminimum the shape and type. """ fn = os.path.join(framedir, name + '.ulm') if split is None or os.path.exists(fn): with ulmopen(fn, 'r') as fd: info = dict() info['shape'] = fd.shape info['type'] = fd.dtype info['stored_as'] = fd.stored_as info['identical'] = fd.all_identical return info else: info = dict() for i in range(split): fn = os.path.join(framedir, name + '_' + str(i) + '.ulm') with ulmopen(fn, 'r') as fd: if i == 0: info['shape'] = list(fd.shape) info['type'] = fd.dtype info['stored_as'] = fd.stored_as info['identical'] = fd.all_identical else: info['shape'][0] += fd.shape[0] assert info['type'] == fd.dtype info['identical'] = info['identical'] and fd.all_identical info['shape'] = tuple(info['shape']) return info def set_fragments(self, nfrag): self.nfrag = nfrag def read_split(self, framedir, name): """Read data from multiple files. Falls back to reading from single file if that is how data is stored. Returns the data and an object indicating if the data was really read from split files. The latter object is False if not read from split files, but is an array of the segment length if split files were used. """ data = [] if os.path.exists(os.path.join(framedir, name + '.ulm')): # Not stored in split form! return (, name), False) for i in range(self.nfrag): suf = '_%d' % (i,) data.append(, name + suf)) seglengths = [len(d) for d in data] return (np.concatenate(data), seglengths) def close(self, log=None): """Close anything that needs to be closed by the backend. The default backend does nothing here. """ pass
[docs]def read_bundletrajectory(filename, index=-1): """Reads one or more atoms objects from a BundleTrajectory. Arguments: filename: str The name of the bundle (really a directory!) index: int An integer specifying which frame to read, or an index object for reading multiple frames. Default: -1 (reads the last frame). """ traj = BundleTrajectory(filename, mode='r') for i in range(*index.indices(len(traj))): yield traj[i]
[docs]def write_bundletrajectory(filename, images, append=False): """Write image(s) to a BundleTrajectory. Write also energy, forces, and stress if they are already calculated. """ if append: mode = 'a' else: mode = 'w' traj = BundleTrajectory(filename, mode=mode) if hasattr(images, 'get_positions'): images = [images] for atoms in images: # Avoid potentially expensive calculations: calc = atoms.calc if hasattr(calc, 'calculation_required'): for quantity in ('energy', 'forces', 'stress', 'magmoms'): traj.select_data(quantity, not calc.calculation_required(atoms, [quantity])) traj.write(atoms) traj.close()
def print_bundletrajectory_info(filename): """Prints information about a BundleTrajectory. Mainly intended to be called from a command line tool. """ if not BundleTrajectory.is_bundle(filename): raise ValueError('Not a BundleTrajectory!') if BundleTrajectory.is_empty_bundle(filename): print(filename, 'is an empty BundleTrajectory.') return # Read the metadata fn = os.path.join(filename, 'metadata.json') with open(fn, 'r') as fd: metadata = jsonio.decode( print('Metadata information of BundleTrajectory "%s":' % (filename,)) for k, v in metadata.items(): if k != 'datatypes': print(" %s: %s" % (k, v)) with open(os.path.join(filename, 'frames'), 'rb') as fd: nframes = int( print('Number of frames: %i' % (nframes,)) print('Data types:') for k, v in metadata['datatypes'].items(): if v == 'once': print(' %s: First frame only.' % (k,)) elif v: print(' %s: All frames.' % (k,)) # Look at first frame if metadata['backend'] == 'ulm': backend = UlmBundleBackend(True, False) else: raise NotImplementedError('Backend %s not supported.' % (metadata['backend'],)) frame = os.path.join(filename, 'F0') small = backend.read_small(frame) print('Contents of first frame:') for k, v in small.items(): if k == 'constraints': if v: print(' {} constraints are present'.format(len(v))) else: print(' Constraints are absent.') elif k == 'pbc': print(' Periodic boundary conditions: %s' % (str(v),)) elif k == 'natoms': print(' Number of atoms: %i' % (v,)) elif hasattr(v, 'shape'): print(' %s: shape = %s, type = %s' % (k, str(v.shape), str(v.dtype))) if k == 'cell': print(' [[%12.6f, %12.6f, %12.6f],' % tuple(v[0])) print(' [%12.6f, %12.6f, %12.6f],' % tuple(v[1])) print(' [%12.6f, %12.6f, %12.6f]]' % tuple(v[2])) else: print(' %s: %s' % (k, str(v))) # Read info from separate files. if metadata['subtype'] == 'split': nsplit = small['fragments'] else: nsplit = False for k, v in metadata['datatypes'].items(): if v and k not in small: info = backend.read_info(frame, k, nsplit) infoline = ' %s: ' % (k,) for k, v in info.items(): infoline += '%s = %s, ' % (k, str(v)) infoline = infoline[:-2] + '.' # Fix punctuation. print(infoline) class PickleBundleBackend: # Leave placeholder class so importing asap3 won't crash. pass def main(): import optparse parser = optparse.OptionParser( usage='python -m ' 'a.bundle [b.bundle ...]', description='Print information about ' 'the contents of one or more bundletrajectories.') opts, args = parser.parse_args() for name in args: print_bundletrajectory_info(name) if __name__ == '__main__': main()