B dk@sdZddlmZddlZddlZddlmZmZddl m Z m Z m Z m Z mZmZmZmZddl mZdd lmZmZmZmZdd l mZdd l mZdd lmZGd ddeeZGdddZGdddZGdddZdS)z> Implements support for high-level access to HDF5 groups. )contextmanagerN)filename_decodefilename_encode)h5h5gh5ih5oh5rh5th5lh5p)base)HLObjectMutableMappingHDF5phil with_phil)dataset)datatype) vds_supportcs"eZdZdZfddZeejZe ej ej Be ej ej Bd.ddZ d/ddZerxd0d d Zed1d d Zd2ddZddZddZeddZd3ddZddZeddZeddZeddZed d!Zed"d#Zd4d$d%Zd&d'Z d(d)Z!d*d+Z"ed,d-Z#Z$S)5Groupz Represents an HDF5 group. c s8t*t|tjstd|t|WdQRXdS)zF Create a new Group object by binding to a low-level GroupID. z%s is not a GroupIDN)r isinstancerZGroupID ValueErrorsuper__init__)selfbind) __class__@/var/www/html/venv/lib/python3.7/site-packages/h5py/_hl/group.pyr"s  zGroup.__init__Nc Cs^|dkrtj}t>|j|dd\}}|r4tjnd}tj|j |||d}t|SQRXdS)a4 Create and return a new subgroup. Name may be absolute or relative. Fails if the target name already exists. track_order Track dataset/group/attribute creation order under this group if True. If None use global default h5.get_config().track_order. NT)lcpl)r!gcpl) r get_config track_orderr_er_gcpl_crt_orderrcreateid)rnamer$r!r"gidrrr create_group0s  zGroup.create_groupc Ksd|krtj|d<d|kr0||d|d<d|krJ||d|d<t`|}|r||}d|dkr|dd\}}||}tj |||||f|}t |} | SQRXdS)a9 Create a new HDF5 dataset name Name of the dataset (absolute or relative). Provide None to make an anonymous dataset. shape Dataset shape. Use "()" for scalar datasets. Required if "data" isn't provided. dtype Numpy dtype or string. If omitted, dtype('f') will be used. Required if "data" isn't provided; otherwise, overrides data array's dtype. data Provide data to initialize the dataset. If used, you can omit shape and dtype arguments. Keyword-only arguments: chunks (Tuple or int) Chunk shape, or True to enable auto-chunking. Integers can be used for 1D shape. maxshape (Tuple or int) Make the dataset resizable up to this shape. Use None for axes you want to be unlimited. Integers can be used for 1D shape. compression (String or int) Compression strategy. Legal values are 'gzip', 'szip', 'lzf'. If an integer in range(10), this indicates gzip compression level. Otherwise, an integer indicates the number of a dynamically loaded compression filter. compression_opts Compression settings. This is an integer for gzip, 2-tuple for szip, etc. If specifying a dynamically loaded compression filter number, this must be a tuple of values. scaleoffset (Integer) Enable scale/offset filter for (usually) lossy compression of integer or floating-point data. For integer data, the value of scaleoffset is the number of bits to retain (pass 0 to let HDF5 determine the minimum number of bits necessary for lossless compression). For floating point data, scaleoffset is the number of digits after the decimal place to retain; stored values thus have absolute error less than 0.5*10**(-scaleoffset). shuffle (T/F) Enable shuffle filter. fletcher32 (T/F) Enable fletcher32 error detection. Not permitted in conjunction with the scale/offset filter. fillvalue (Scalar) Use this value for uninitialized parts of the dataset. track_times (T/F) Enable dataset creation timestamps. track_order (T/F) Track attribute creation order if True. If omitted use global default h5.get_config().track_order. external (Iterable of tuples) Sets the external storage property, thus designating that the dataset will be stored in one or more non-HDF5 files external to the HDF5 file. Adds each tuple of (name, offset, size) to the dataset's list of external files. Each name must be a str, bytes, or os.PathLike; each offset and size, an integer. If only a name is given instead of an iterable of tuples, it is equivalent to [(name, 0, h5py.h5f.UNLIMITED)]. efile_prefix (String) External dataset file prefix for dataset access property list. Does not persist in the file. virtual_prefix (String) Virtual dataset file prefix for dataset access property list. Does not persist in the file. allow_unknown_filter (T/F) Do not check that the requested filter is available for use. This should only be used with ``write_direct_chunk``, where the caller compresses the data before handing it to h5py. rdcc_nbytes Total size of the dataset's chunk cache in bytes. The default size is 1024**2 (1 MiB). rdcc_w0 The chunk preemption policy for this dataset. This must be between 0 and 1 inclusive and indicates the weighting according to which chunks which have been fully read or written are penalized when determining which chunks to flush from cache. A value of 0 means fully read or written chunks are treated no differently than other chunks (the preemption is strictly LRU) while a value of 1 means fully read or written chunks are always preempted before other chunks. If your application only reads or writes data once, this can be safely set to 1. Otherwise, this should be set lower depending on how often you re-read or re-write the same data. The default value is 0.75. rdcc_nslots The number of chunk slots in the dataset's chunk cache. Increasing this value reduces the number of cache collisions, but slightly increases the memory used. Due to the hashing strategy, this value should ideally be a prime number. As a rule of thumb, this value should be at least 10 times the number of chunks that can fit in rdcc_nbytes bytes. For maximum performance, this value should be set approximately 100 times that number of chunks. The default value is 521. r$ efile_prefixvirtual_prefix/rN) rr#r$r%rlstriprsplit require_grouprZ make_new_dsetDataset) rr)shapedtypedatakwdsgroup parent_pathdsiddsetrrr create_datasetCs c   zGroup.create_datasetc CshtZ|}|r@||}d|dkr@|dd\}}||}|j|||d}t|}WdQRX|S)amCreate a new virtual dataset in this group. See virtual datasets in the docs for more information. name (str) Name of the new dataset layout (VirtualLayout) Defines the sources for the virtual dataset fillvalue The value to use where there is no data. r.r)r) fillvalueN)rr%r/r0r1Z make_datasetrr2)rr)layoutr<r7r8r9r:rrr create_virtual_datasets   zGroup.create_virtual_datasetccs6ddlm}|||||jj}|V||||dS)aAssemble a virtual dataset in this group. This is used as a context manager:: with f.build_virtual_dataset('virt', (10, 1000), np.uint32) as layout: layout[0] = h5py.VirtualSource('foo.h5', 'data', (1000,)) name (str) Name of the new dataset shape (tuple) Shape of the dataset dtype A numpy dtype for data read from the virtual dataset maxshape (tuple, optional) Maximum dimensions if the dataset can grow. Use None for unlimited dimensions. fillvalue The value used where no data is available. r) VirtualLayoutN)vdsr?filefilenamer>)rr)r3r4maxshaper<r?r=rrr build_virtual_datasets zGroup.build_virtual_datasetFc Ks`d|kr||d|d<d|kr4||d|d<t||krZ|j|f||f|St|trj|f}y$tj|||f|}t|}Wn,tk r||}t d|j j YnX||j kr d|krt d|j |fn&|d|j kr t d|j |df|r0||jkrRt d|j|fn"t||jsRt d|j|f|SQRXd S) a Open a dataset, creating it if it doesn't exist. If keyword "exact" is False (default), an existing dataset must have the same shape and a conversion-compatible dtype to be returned. If True, the shape and dtype must match exactly. If keyword "maxshape" is given, the maxshape and dtype must match instead. If any of the keywords "rdcc_nslots", "rdcc_nbytes", or "rdcc_w0" are given, they will be used to configure the dataset's chunk cache. Other dataset keywords (see create_dataset) may be provided, but are only used if a new dataset is to be created. Raises TypeError if an incompatible object already exists, or if the shape, maxshape or dtype don't match according to the above rules. r,r-z'Incompatible object (%s) already existsrCz+Shapes do not match (existing %s vs new %s)z/Max shapes do not match (existing %s vs new %s)z6Datatypes do not exactly match (existing %s vs new %s)z7Datatypes cannot be safely cast (existing %s vs new %s)N)r%rr;rintrZ open_dsetr2KeyError TypeErrorr__name__r3rCr4numpyZcan_cast)rr)r3r4exactr6r9r:rrr require_datasets4   zGroup.require_datasetcKsvxdD]}||t||qW|j}|d||d|dk|j|jkrh|d|j|j|f|S)a? Create a dataset similar to `other`. name Name of the dataset (absolute or relative). Provide None to make an anonymous dataset. other The dataset which the new dataset should mimic. All properties, such as shape, dtype, chunking, ... will be taken from it, but no data or attributes are being copied. Any dataset keywords (see create_dataset) may be provided, including shape and dtype, in which case the provided values take precedence over those from `other`. ) r3r4chunks compressionZcompression_optsZ scaleoffsetshuffleZ fletcher32r<Z track_timesr$rrC) setdefaultgetattrr(Zget_create_plistZget_obj_track_timesZget_attr_creation_orderrCr3r;)rr)otherZkwupdatekZdcplrrr create_dataset_like-s   zGroup.create_dataset_likec CsHt:||kr||S||}t|ts:td|jj|SQRXdS)zReturn a group, creating it if it doesn't exist. TypeError is raised if something with that name already exists that isn't a group. z'Incompatible object (%s) already existsN)rr+rrrGrrH)rr)grprrr r1Ms  zGroup.require_groupcCst|tjr,t||j}|dkrhtdntStStdWdQRXdS)a Retrieve an item or other information. "name" given only: Return the item, or "default" if it doesn't exist "getclass" is True: Return the class of object (Group, Dataset, etc.), or "default" if nothing with that name exists "getlink" is True: Return HardLink, SoftLink or ExternalLink instances. Return "default" if nothing with that name exists. "getlink" and "getclass" are True: Return HardLink, SoftLink and ExternalLink classes. Return "default" if nothing with that name exists. Example: >>> cls = group.get('foo', getclass=True) >>> if cls == SoftLink: zUnknown object typezUnknown link typeN)rrFr get_infor(r%r^Z TYPE_GROUPrZ TYPE_DATASETrr2ZTYPE_NAMED_DATATYPErrarGlinksr Z TYPE_SOFTSoftLinkZget_val_dZ TYPE_EXTERNAL ExternalLinkrZ TYPE_HARDHardLink)rr)defaultZgetclassZgetlinktypecodeZ linkbytesZ filebytesrrr getts@   z Group.getc Cst|j|dd\}}t|tr>tj|j|j|||jdnt|trj|jj j |||j ||jdnt|t rt |j}|jj j||||j ||jdnRt|tjrtj|dd}|j|j||dn$|jd|d}tj|j|j||dWdQRXdS)a6 Add an object to the group. The name must not already be in use. The action taken depends on the type of object assigned: Named HDF5 object (Dataset, Group, Datatype) A hard link is created at "name" which points to the given object. SoftLink or ExternalLink Create the corresponding link. Numpy ndarray The array is converted to a dataset object, with default settings (contiguous storage, etc.). Numpy dtype Commit a copy of the datatype as a named datatype in the file. Anything else Attempt to convert it to an ndarray and store it. Scalar values are stored as scalar datasets. Raise ValueError if we can't understand the resulting array dtype. T)r!)r!rU)ZlogicalN)r5)rr%rrr linkr(r\rgrfZ create_softpathrirrBZcreate_externalrIr4r Z py_createcommitr;)rr)objr!fnZhtypeZdsrrr __setitem__s  "   zGroup.__setitem__cCs|j||dS)z* Delete (unlink) an item from this group. N)r(unlinkr%)rr)rrr __delitem__szGroup.__delitem__cCs |jS)z* Number of members attached to this group )r(Z get_num_objs)rrrr __len__sz Group.__len__ccs$x|jD]}||Vq WdS)z Iterate over member names N)r(__iter__rh)rxrrr rwszGroup.__iter__ccs$x|jD]}||Vq WdS)z- Iterate over member names in reverse order. N)r( __reversed__rh)rrxrrr ryszGroup.__reversed__cCs|||jkS)z Test if a member name exists )r%r()rr)rrr __contains__szGroup.__contains__c Cs&tt|trd} n|} |}t|trl|dk r8|} q| dkrTtt|j} qtt|| j} nt|trt dn|} |}d} |r| t j O} |r| t j O} |r| t j O} |r| t jO} |r| t jO} | rttj} | | nd} t |j|| |j|| | tjWdQRXdS)aCopy an object or group. The source can be a path, Group, Dataset, or Datatype object. The destination can be either a path or a Group object. The source and destinations need not be in the same file. If the source is a Group object, all objects contained in that group will be copied recursively. When the destination is a Group object, by default the target will be created in that group with its current name (basename of obj.name). You can override that by setting "name" to a string. There are various options which all default to "False": - shallow: copy only immediate members of a group. - expand_soft: expand soft links into new objects. - expand_external: expand external links into new objects. - expand_refs: copy objects that are pointed to by references. - without_attrs: copy object without copying attributes. Example: >>> f = File('myfile.hdf5', 'w') >>> f.create_group("MyGroup") >>> list(f.keys()) ['MyGroup'] >>> f.copy('MyGroup', 'MyCopy') >>> list(f.keys()) ['MyGroup', 'MyCopy'] .Nz(Destination must be path or Group objectr)rrrrppbasenamer get_namer(rGr ZCOPY_SHALLOW_HIERARCHY_FLAGZCOPY_EXPAND_SOFT_LINK_FLAGZCOPY_EXPAND_EXT_LINK_FLAGZCOPY_EXPAND_REFERENCE_FLAGZCOPY_WITHOUT_ATTR_FLAGrr'Z OBJECT_COPYZset_copy_objectcopyr%rZdlcpl) rsourcedestr)ZshallowZ expand_softZexpand_externalZ expand_refsZ without_attrs source_path dest_pathflagsZcopyplrrr rs@'           z Group.copyc CsJt<||krdS|jjj|||j|||j|jdWdQRXdS)z Move a link to a new location in the file. If "source" is a hard link, this effectively renames the object. If "source" is a soft or external link, the link itself is moved, with its value unmodified. N)rUr!)rr(rfmover%r\Z_lcpl)rrrrrr rTs z Group.movec s,tfdd}tj|SQRXdS)a Recursively visit all names in this group and subgroups (HDF5 1.8). You supply a callable (function, method or callable object); it will be called exactly once for each link in this group and every group below it. Your callable must conform to the signature: func() => Returning None continues iteration, returning anything else stops and immediately returns that value from the visit method. No particular order of iteration within groups is guaranteed. Example: >>> # List the entire contents of the file >>> f = File("foo.hdf5") >>> list_of_names = [] >>> f.visit(list_of_names.append) cs|S)z1 Call the function with the text name, not bytes )rh)r))funcrrr proxyvszGroup.visit..proxyN)rr visitr()rrrr)rrr rasz Group.visitc s,tfdd}tj|SQRXdS)aV Recursively visit names and objects in this group (HDF5 1.8). You supply a callable (function, method or callable object); it will be called exactly once for each link in this group and every group below it. Your callable must conform to the signature: func(, ) => Returning None continues iteration, returning anything else stops and immediately returns that value from the visit method. No particular order of iteration within groups is guaranteed. Example: # Get a list of all datasets in the file >>> mylist = [] >>> def func(name, obj): ... if isinstance(obj, Dataset): ... mylist.append(name) ... >>> f = File('foo.hdf5') >>> f.visititems(func) cs|}||S)z, Use the text name of the object, not bytes )rh)r))rrrr rs zGroup.visititems..proxyN)rr rr()rrrr)rrr visititems{szGroup.visititemscCs6|s d}n(|jdk rd|jnd}d|t|f}|S)Nzz"%s"z (anonymous)z)r)len)rrVZnamestrrrr __repr__s zGroup.__repr__)N)NNN)N)NN)F)NFF)NFFFFF)%rH __module__ __qualname____doc__rrr'Z GROUP_CREATEr&Zset_link_creation_orderZCRT_ORDER_TRACKEDZCRT_ORDER_INDEXEDZset_attr_creation_orderr+r;rr>rrDrKrSr1rrdrmrsrurvrwryrzrrrrr __classcell__rr)rr rs>    x   5   D.      Q rc@seZdZdZdS)rjz Represents a hard link in an HDF5 file. Provided only so that Group.get works in a sensible way. Has no other function. N)rHrrrrrrr rjsrjc@s,eZdZdZeddZddZddZdS) rgz Represents a symbolic ("soft") link in an HDF5 file. The path may be absolute or relative. No checking is performed to ensure that the target actually exists. cCs|jS)z6 Soft link value. Not guaranteed to be a valid path. )_path)rrrr rosz SoftLink.pathcCst||_dS)N)rZr)rrorrr rszSoftLink.__init__cCs d|jS)Nz)ro)rrrr rszSoftLink.__repr__N)rHrrrpropertyrorrrrrr rgs rgc@s8eZdZdZeddZeddZddZdd Zd S) riz Represents an HDF5 external link. Paths may be absolute or relative. No checking is performed to ensure either the target or file exists. cCs|jS)z5 Soft link path, i.e. the part inside the HDF5 file. )r)rrrr roszExternalLink.pathcCs|jS)z3 Path to the external HDF5 file in the filesystem. ) _filename)rrrr rBszExternalLink.filenamecCstt||_||_dS)N)rrrr)rrBrorrr rszExternalLink.__init__cCsd|j|jfS)Nz" s& (