add deepmd/hdf5 format

dpdata/deepmd/hdf5.py

@@ -0,0 +1,149 @@
+"""Utils for deepmd/hdf5 format."""
+import h5py
+import numpy as np
+
+from wcmatch.glob import globfilter
+
+
+__all__ = ['to_system_data', 'dump']
+
+def to_system_data(f: h5py.File,
+                   folder: str, 
+                   type_map: list = None,
+                   labels: bool = True) :
+    """Load a HDF5 file.
+
+    Parameters
+    ----------
+    f : h5py.File
+        HDF5 file object
+    folder : str
+        path in the HDF5 file
+    type_map : list
+        type map
+    labels : bool
+        labels
+    """
+    g = f[folder] if folder else f
+
+    data = {}
+    data['atom_types'] = g['type.raw'][:]
+    ntypes = np.max(data['atom_types']) + 1
+    natoms = data['atom_types'].size
+    data['atom_numbs'] = []
+    for ii in range (ntypes) :
+        data['atom_numbs'].append(np.count_nonzero(data['atom_types'] == ii))
+    data['atom_names'] = []
+    # if find type_map.raw, use it
+    if 'type_map.raw' in g.keys():
+        my_type_map = list(np.char.decode(g['type_map.raw'][:]))
+    # else try to use arg type_map 
+    elif type_map is not None:
+        my_type_map = type_map
+    # in the last case, make artificial atom names
+    else:
+        my_type_map = []
+        for ii in range(ntypes) :
+            my_type_map.append('Type_%d' % ii)
+    assert(len(my_type_map) >= len(data['atom_numbs']))
+    for ii in range(len(data['atom_numbs'])) :
+        data['atom_names'].append(my_type_map[ii])
+
+    data['orig'] = np.zeros([3])
+    if 'nopbc' in g.keys():
+        data['nopbc'] = True
+    sets = globfilter(g.keys(), 'set.*')
+
+    data_types = {
+        'cells': {'fn': 'box', 'labeled': False, 'shape': (3,3), 'required': 'nopbc' not in data},
+        'coords': {'fn': 'coord', 'labeled': False, 'shape': (natoms,3), 'required': True},
+        'energies': {'fn': 'energy', 'labeled': True, 'shape': tuple(), 'required': False},
+        'forces': {'fn': 'force', 'labeled': True, 'shape': (natoms,3), 'required': False},
+        'virials': {'fn': 'virial', 'labeled': True, 'shape': (3,3), 'required': False},
+    }
+
+    for dt, prop in data_types.items():
+        all_data = []
+
+        for ii in sets:
+            set = g[ii]
+            fn = '%s.npy' % prop['fn']
+            if fn in set.keys():
+                dd = set[fn][:]
+                nframes = dd.shape[0]
+                all_data.append(np.reshape(dd, (nframes, *prop['shape'])))
+            elif prop['required']:
+                raise RuntimeError("%s/%s/%s not found" % (folder, ii, fn))
+
+        if len(all_data) > 0 :
+            data[dt] = np.concatenate(all_data, axis = 0)
+    return data
+
+def dump(f: h5py.File,
+         folder: str,
+         data: dict,
+         set_size = 5000,
+         comp_prec = np.float32,
+         ) -> None:
+    """Dump data to a HDF5 file.
+
+    Parameters
+    ----------
+    f : h5py.File
+        HDF5 file object
+    folder : str
+        path in the HDF5 file
+    data : dict
+        System or LabeledSystem data
+    set_size : int, default: 5000
+        size of a set
+    comp_prec : np.dtype, default: np.float32
+        precision of data
+    """
+    # if folder is None, use the root of the file
+    if folder:
+        if folder in f:
+            del f[folder]
+        g = f.create_group(folder)
+    else:
+        g = f
+    # dump raw (array in fact)
+    g.create_dataset('type.raw', data=data['atom_types'])    
+    g.create_dataset('type_map.raw', data=np.array(data['atom_names'], dtype='S'))
+    # BondOrder System
+    if "bonds" in data:
+        g.create_dataset("bonds.raw", data=data['bonds'])
+    if "formal_charges" in data:
+        g.create_dataset("formal_charges.raw", data=data['formal_charges'])
+    # reshape frame properties and convert prec
+    nframes = data['cells'].shape[0]
+
+    nopbc = data.get("nopbc", False)
+    reshaped_data = {}
+
+    data_types = {
+        'cells': {'fn': 'box', 'shape': (nframes, 9), 'dump': not nopbc},
+        'coords': {'fn': 'coord',  'shape': (nframes, -1), 'dump': True},
+        'energies': {'fn': 'energy', 'shape': (nframes,), 'dump': True},
+        'forces': {'fn': 'force', 'shape': (nframes, -1), 'dump': True},
+        'virials': {'fn': 'virial', 'shape': (nframes, 9), 'dump': True},
+    }
+    for dt, prop in data_types.items():
+        if dt in data:
+            if prop['dump']:
+                reshaped_data[dt] = np.reshape(data[dt], prop['shape']).astype(comp_prec)
+
+    # dump frame properties: cell, coord, energy, force and virial
+    nsets = nframes // set_size
+    if set_size * nsets < nframes :
+        nsets += 1
+    for ii in range(nsets) :
+        set_stt = ii * set_size
+        set_end = (ii+1) * set_size
+        set_folder = g.create_group('set.%03d' % ii)
+        for dt, prop in data_types.items():
+            if dt in reshaped_data:
+                set_folder.create_dataset('%s.npy' % prop['fn'], data=reshaped_data[dt][set_stt:set_end])
+
+    if nopbc:
+       g.create_dataset("nopbc", True)

dpdata/plugins/deepmd.py

@@ -1,6 +1,8 @@
 import dpdata.deepmd.raw
 import dpdata.deepmd.comp
+import dpdata.deepmd.hdf5
 import numpy as np
+import h5py
 from dpdata.format import Format
 
 
@@ -54,3 +56,49 @@ def from_labeled_system(self, file_name, type_map=None, **kwargs):
         return dpdata.deepmd.comp.to_system_data(file_name, type_map=type_map, labels=True)
 
     MultiMode = Format.MultiModes.Directory
+
+@Format.register("deepmd/hdf5")
+class DeePMDCompFormat(Format):
+    """HDF5 format for DeePMD-kit.
+
+    Examples
+    --------
+    Dump a MultiSystems to a HDF5 file:
+    >>> import dpdata
+    >>> dpdata.MultiSystems().from_deepmd_npy("data").to_deepmd_hdf5("data.hdf5")
+    """
+    def from_system(self, file_name, type_map=None, **kwargs):
+        s = file_name.split("#")
+        name = s[1] if len(s) > 1 else ""
+        with h5py.File(s[0], 'r') as f:
+            return dpdata.deepmd.hdf5.to_system_data(f, name, type_map=type_map, labels=False)
+
+    def from_labeled_system(self, file_name, type_map=None, **kwargs):
+        s = file_name.split("#")
+        name = s[1] if len(s) > 1 else ""
+        with h5py.File(s[0], 'r') as f:
+            return dpdata.deepmd.hdf5.to_system_data(f, name, type_map=type_map, labels=True)
+
+    def to_system(self,
+                  data : dict,
+                  file_name : str,
+                  set_size : int = 5000, 
+                  comp_prec : np.dtype = np.float32,
+                  **kwargs):
+        s = file_name.split("#")
+        name = s[1] if len(s) > 1 else ""
+        mode = 'a' if name else 'w'
+        with h5py.File(s[0], mode) as f:
+            dpdata.deepmd.hdf5.dump(f, name, data, set_size = set_size, comp_prec = comp_prec)
+
+    def from_multi_systems(self,
+                  directory,
+                  **kwargs):
+        with h5py.File(directory, 'r') as f:
+            return ["%s#%s" % (directory, ff) for ff in f.keys()]
+
+    def to_multi_systems(self,
+                  formulas,
+                  directory,
+                  **kwargs):
+        return ["%s#%s" % (directory, ff) for ff in formulas]

setup.py

@@ -12,7 +12,7 @@
         readme = f.read()
 
 # install_requires = ['xml']
-install_requires=['numpy>=1.14.3', 'monty', 'scipy']
+install_requires=['numpy>=1.14.3', 'monty', 'scipy', 'h5py', 'wcmatch']
 
 setuptools.setup(
     name="dpdata",

tests/test_deepmd_hdf5.py

@@ -0,0 +1,45 @@
+import os
+import numpy as np
+import unittest
+from context import dpdata
+from comp_sys import CompLabeledSys, CompSys, IsPBC
+
+class TestDeepmdLoadDumpComp(unittest.TestCase, CompLabeledSys, IsPBC):
+    def setUp (self) :
+        self.system_1 = dpdata.LabeledSystem('poscars/OUTCAR.h2o.md', 
+                                             fmt = 'vasp/outcar')
+        self.system_1.to_deepmd_hdf5('tmp.deepmd.hdf5', 
+                                    prec = np.float64, 
+                                    set_size = 2)        
+
+        self.system_2 = dpdata.LabeledSystem('tmp.deepmd.hdf5', 
+                                             fmt = 'deepmd/hdf5',
+                                             type_map = ['O', 'H'])
+        self.places = 6
+        self.e_places = 6
+        self.f_places = 6
+        self.v_places = 6
+
+    def tearDown(self) :
+        if os.path.exists('tmp.deepmd.hdf5'):
+            os.remove('tmp.deepmd.hdf5')
+
+
+class TestDeepmdCompNoLabels(unittest.TestCase, CompSys, IsPBC) :
+    def setUp (self) :
+        self.system_1 = dpdata.System('poscars/POSCAR.h2o.md',
+                                      fmt = 'vasp/poscar')
+        self.system_1.to_deepmd_hdf5('tmp.deepmd.hdf5', 
+                                    prec = np.float64, 
+                                    set_size = 2)        
+        self.system_2 = dpdata.System('tmp.deepmd.hdf5', 
+                                      fmt = 'deepmd/hdf5',
+                                      type_map = ['O', 'H'])
+        self.places = 6
+        self.e_places = 6
+        self.f_places = 6
+        self.v_places = 6
+
+    def tearDown(self) :
+        if os.path.exists('tmp.deepmd.hdf5'):
+            os.remove('tmp.deepmd.hdf5')