# This file is part of h5py, a Python interface to the HDF5 library. # # http://www.h5py.org # # Copyright 2008-2013 Andrew Collette and contributors # # License: Standard 3-clause BSD; see "license.txt" for full license terms # and contributor agreement. """ Provides access to the low-level HDF5 "H5D" dataset interface. """ include "config.pxi" # Compile-time imports from _objects cimport pdefault from numpy cimport ndarray, import_array, PyArray_DATA, NPY_WRITEABLE from utils cimport check_numpy_read, check_numpy_write, \ convert_tuple, emalloc, efree from h5t cimport TypeID, typewrap, py_create from h5s cimport SpaceID from h5p cimport PropID, propwrap from _proxy cimport dset_rw from h5py import _objects from ._objects import phil, with_phil # Initialization import_array() # === Public constants and data structures ==================================== COMPACT = H5D_COMPACT CONTIGUOUS = H5D_CONTIGUOUS CHUNKED = H5D_CHUNKED ALLOC_TIME_DEFAULT = H5D_ALLOC_TIME_DEFAULT ALLOC_TIME_LATE = H5D_ALLOC_TIME_LATE ALLOC_TIME_EARLY = H5D_ALLOC_TIME_EARLY ALLOC_TIME_INCR = H5D_ALLOC_TIME_INCR SPACE_STATUS_NOT_ALLOCATED = H5D_SPACE_STATUS_NOT_ALLOCATED SPACE_STATUS_PART_ALLOCATED = H5D_SPACE_STATUS_PART_ALLOCATED SPACE_STATUS_ALLOCATED = H5D_SPACE_STATUS_ALLOCATED FILL_TIME_ALLOC = H5D_FILL_TIME_ALLOC FILL_TIME_NEVER = H5D_FILL_TIME_NEVER FILL_TIME_IFSET = H5D_FILL_TIME_IFSET FILL_VALUE_UNDEFINED = H5D_FILL_VALUE_UNDEFINED FILL_VALUE_DEFAULT = H5D_FILL_VALUE_DEFAULT FILL_VALUE_USER_DEFINED = H5D_FILL_VALUE_USER_DEFINED # === Dataset operations ====================================================== @with_phil def create(ObjectID loc not None, object name, TypeID tid not None, SpaceID space not None, PropID dcpl=None, PropID lcpl=None, PropID dapl = None): """ (objectID loc, STRING name or None, TypeID tid, SpaceID space, PropDCID dcpl=None, PropID lcpl=None) => DatasetID Create a new dataset. If "name" is None, the dataset will be anonymous. """ cdef hid_t dsid cdef char* cname = NULL if name is not None: cname = name if cname != NULL: dsid = H5Dcreate2(loc.id, cname, tid.id, space.id, pdefault(lcpl), pdefault(dcpl), pdefault(dapl)) else: dsid = H5Dcreate_anon(loc.id, tid.id, space.id, pdefault(dcpl), pdefault(dapl)) return DatasetID(dsid) @with_phil def open(ObjectID loc not None, char* name, PropID dapl=None): """ (ObjectID loc, STRING name, PropID dapl=None) => DatasetID Open an existing dataset attached to a group or file object, by name. If specified, dapl may be a dataset access property list. """ return DatasetID(H5Dopen2(loc.id, name, pdefault(dapl))) # --- Proxy functions for safe(r) threading ----------------------------------- cdef class DatasetID(ObjectID): """ Represents an HDF5 dataset identifier. Objects of this class may be used in any HDF5 function which expects a dataset identifier. Also, all H5D* functions which take a dataset instance as their first argument are presented as methods of this class. Properties: dtype: Numpy dtype representing the dataset type shape: Numpy-style shape tuple representing the dataspace rank: Integer giving dataset rank * Hashable: Yes, unless anonymous * Equality: True HDF5 identity if unless anonymous """ property dtype: """ Numpy dtype object representing the dataset type """ def __get__(self): # Dataset type can't change cdef TypeID tid with phil: if self._dtype is None: tid = self.get_type() self._dtype = tid.dtype return self._dtype property shape: """ Numpy-style shape tuple representing the dataspace """ def __get__(self): # Shape can change (DatasetID.extend), so don't cache it cdef SpaceID sid with phil: sid = self.get_space() return sid.get_simple_extent_dims() property rank: """ Integer giving the dataset rank (0 = scalar) """ def __get__(self): cdef SpaceID sid with phil: sid = self.get_space() return sid.get_simple_extent_ndims() @with_phil def read(self, SpaceID mspace not None, SpaceID fspace not None, ndarray arr_obj not None, TypeID mtype=None, PropID dxpl=None): """ (SpaceID mspace, SpaceID fspace, NDARRAY arr_obj, TypeID mtype=None, PropDXID dxpl=None) Read data from an HDF5 dataset into a Numpy array. It is your responsibility to ensure that the memory dataspace provided is compatible with the shape of the Numpy array. Since a wide variety of dataspace configurations are possible, this is not checked. You can easily crash Python by reading in data from too large a dataspace. If a memory datatype is not specified, one will be auto-created based on the array's dtype. The provided Numpy array must be writable and C-contiguous. If this is not the case, ValueError will be raised and the read will fail. Keyword dxpl may be a dataset transfer property list. """ cdef hid_t self_id, mtype_id, mspace_id, fspace_id, plist_id cdef void* data cdef int oldflags if mtype is None: mtype = py_create(arr_obj.dtype) check_numpy_write(arr_obj, -1) self_id = self.id mtype_id = mtype.id mspace_id = mspace.id fspace_id = fspace.id plist_id = pdefault(dxpl) data = PyArray_DATA(arr_obj) dset_rw(self_id, mtype_id, mspace_id, fspace_id, plist_id, data, 1) @with_phil def write(self, SpaceID mspace not None, SpaceID fspace not None, ndarray arr_obj not None, TypeID mtype=None, PropID dxpl=None): """ (SpaceID mspace, SpaceID fspace, NDARRAY arr_obj, TypeID mtype=None, PropDXID dxpl=None) Write data from a Numpy array to an HDF5 dataset. Keyword dxpl may be a dataset transfer property list. It is your responsibility to ensure that the memory dataspace provided is compatible with the shape of the Numpy array. Since a wide variety of dataspace configurations are possible, this is not checked. You can easily crash Python by writing data from too large a dataspace. If a memory datatype is not specified, one will be auto-created based on the array's dtype. The provided Numpy array must be C-contiguous. If this is not the case, ValueError will be raised and the read will fail. """ cdef hid_t self_id, mtype_id, mspace_id, fspace_id, plist_id cdef void* data cdef int oldflags if mtype is None: mtype = py_create(arr_obj.dtype) check_numpy_read(arr_obj, -1) self_id = self.id mtype_id = mtype.id mspace_id = mspace.id fspace_id = fspace.id plist_id = pdefault(dxpl) data = PyArray_DATA(arr_obj) dset_rw(self_id, mtype_id, mspace_id, fspace_id, plist_id, data, 0) @with_phil def extend(self, tuple shape): """ (TUPLE shape) Extend the given dataset so it's at least as big as "shape". Note that a dataset may only be extended up to the maximum dimensions of its dataspace, which are fixed when the dataset is created. """ cdef int rank cdef hid_t space_id = 0 cdef hsize_t* dims = NULL try: space_id = H5Dget_space(self.id) rank = H5Sget_simple_extent_ndims(space_id) if len(shape) != rank: raise TypeError("New shape length (%d) must match dataset rank (%d)" % (len(shape), rank)) dims = emalloc(sizeof(hsize_t)*rank) convert_tuple(shape, dims, rank) H5Dextend(self.id, dims) finally: efree(dims) if space_id: H5Sclose(space_id) @with_phil def set_extent(self, tuple shape): """ (TUPLE shape) Set the size of the dataspace to match the given shape. If the new size is larger in any dimension, it must be compatible with the maximum dataspace size. """ cdef int rank cdef hid_t space_id = 0 cdef hsize_t* dims = NULL try: space_id = H5Dget_space(self.id) rank = H5Sget_simple_extent_ndims(space_id) if len(shape) != rank: raise TypeError("New shape length (%d) must match dataset rank (%d)" % (len(shape), rank)) dims = emalloc(sizeof(hsize_t)*rank) convert_tuple(shape, dims, rank) H5Dset_extent(self.id, dims) finally: efree(dims) if space_id: H5Sclose(space_id) @with_phil def get_space(self): """ () => SpaceID Create and return a new copy of the dataspace for this dataset. """ return SpaceID(H5Dget_space(self.id)) @with_phil def get_space_status(self): """ () => INT space_status_code Determine if space has been allocated for a dataset. Return value is one of: * SPACE_STATUS_NOT_ALLOCATED * SPACE_STATUS_PART_ALLOCATED * SPACE_STATUS_ALLOCATED """ cdef H5D_space_status_t status H5Dget_space_status(self.id, &status) return status @with_phil def get_type(self): """ () => TypeID Create and return a new copy of the datatype for this dataset. """ return typewrap(H5Dget_type(self.id)) @with_phil def get_create_plist(self): """ () => PropDCID Create an return a new copy of the dataset creation property list used when this dataset was created. """ return propwrap(H5Dget_create_plist(self.id)) @with_phil def get_access_plist(self): """ () => PropDAID Create an return a new copy of the dataset access property list. """ return propwrap(H5Dget_access_plist(self.id)) @with_phil def get_offset(self): """ () => LONG offset or None Get the offset of this dataset in the file, in bytes, or None if it doesn't have one. This is always the case for datasets which use chunked storage, compact datasets, and datasets for which space has not yet been allocated in the file. """ cdef haddr_t offset offset = H5Dget_offset(self.id) if offset == HADDR_UNDEF: return None return offset @with_phil def get_storage_size(self): """ () => LONG storage_size Determine the amount of file space required for a dataset. Note this only counts the space which has actually been allocated; it may even be zero. """ return H5Dget_storage_size(self.id) IF HDF5_VERSION >= SWMR_MIN_HDF5_VERSION: @with_phil def flush(self): """ no return Flushes all buffers associated with a dataset to disk. This function causes all buffers associated with a dataset to be immediately flushed to disk without removing the data from the cache. Use this in SWMR write mode to allow readers to be updated with the dataset changes. Feature requires: 1.9.178 HDF5 """ H5Dflush(self.id) @with_phil def refresh(self): """ no return Refreshes all buffers associated with a dataset. This function causes all buffers associated with a dataset to be cleared and immediately re-loaded with updated contents from disk. This function essentially closes the dataset, evicts all metadata associated with it from the cache, and then re-opens the dataset. The reopened dataset is automatically re-registered with the same ID. Use this in SWMR read mode to poll for dataset changes. Feature requires: 1.9.178 HDF5 """ H5Drefresh(self.id)