# $Id: VS.py,v 1.4 2005-07-14 01:36:41 gosselin_a Exp $ # $Log: not supported by cvs2svn $ # Revision 1.3 2004/08/02 17:06:20 gosselin # pyhdf-0.7.2 # # Revision 1.2 2004/08/02 15:36:04 gosselin # pyhdf-0.7-1 # # Author: Andre Gosselin # Maurice-Lamontagne Institute # gosselina@dfo-mpo.gc.ca """ VS (Vdata table) API (:mod:`pyhdf.VS`) ====================================== A module of the pyhdf package implementing the VS (Vdata table) API of the NCSA HDF4 library. Introduction ------------ VS is one of the modules composing pyhdf, a python package implementing the NCSA HDF library and letting one manage HDF files from within a python program. Two versions of the HDF library currently exist, version 4 and version 5. pyhdf only implements version 4 of the library. Many different APIs are to be found inside the HDF4 specification. Currently, pyhdf implements just a few of those: the SD, VS and V APIs. Other APIs should be added in the future (GR, AN, etc). VS allows the definition of structured data tables inside an HDF file. Those tables are designated as "vdatas" (the name has to do with data associated with the "vertices" of geometrical models, the storage of which the API was originally designed for). A vdata is composed of a fixed number of columns (also called fields), where a column can store a fixed number of data values, all of the same type. The number of values allowed inside a field is called the "order" of the field. A table is composed of a varying number of rows (also called records), a record representing the sequence of values stored in each field of the vdata. A vdata is associated with a descriptive name, and likewise each field of the vdata. A vdata can also be tagged with a "class" to further describe the vdata purpose. Records and fields are identified by a zero-based index. An arbitrary number of attributes of different types can be attached to a vdata as a whole, or to its individual fields. An attribute is a (name, value) pair, where "value" can be of many types, and be either single or multi-valued. The number of values stored in an attribute is called the "order" of the attribute. The following example illustrates a simple vdata that could be stored inside an HDF file. See section "Programming models" for an example program implementing this vdata. INVENTORY (experimental status) ====== =========== === ======== ======== partid description qty wght(lb) price($) ====== =========== === ======== ======== Q1234 bolt 12 0.01 0.05 B5432 brush 10 0.4 4.25 S7613 scissor 2 0.2 3.75 ====== =========== === ======== ======== The vdata is composed of 5 fields. 3 records are shown (of course, a vdata can store much more than that). "INVENTORY" would be the vdata name, and "partid", "description", etc, would be the field names. The data type varies between fields. "partid" and "description" would be of "multicharacter" type (aka "string"), "qty" would be a integer, and "wght" and "price" would be floats. The text in parentheses could be stored as attributes. A "status" attribute could be defined for the table as a whole, and given the value "experimental". Likewise, a "unit" attribute could be associated with fields "wght" and "price", and given the values "lb" and "$", resp. The VS API allows one to create, locate and open a vdata inside an HDF file, update and append records inside it, read records randomly or sequentially, and access and update the vdata and field attributes. Attributes can be read and written using the familiar python "dot notation", and records can be read and written by indexing and slicing the vdata as if it were a python sequence. VS module key features ---------------------- VS key features are as follows. - pyhdf implements almost every routine of the original VS API. Only a few have been ignored, most of them being of a rare use: - VSgetblocksize() / VSsetblocksize() - VSsetnumblocks() - VSlone - It is quite straightforward to go from a C version to a python version of a program accessing the VS API, and to learn VS usage by referring to the C API documentation. - A few high-level python methods have been developed to ease programmers task. Of greatest interest are the following: - Access to attributes through the familiar "dot notation". - Indexing and slicing a vdata to read and write its records, similarly to a python sequence. - Easy retrieval of info on a vdata and its fields. - Easy creation of vdatas. Accessing the VS module ----------------------- To access the VS module a python program can say one of: >>> import pyhdf.VS # must prefix names with "pyhdf.VS." >>> from pyhdf import VS # must prefix names with "VS." >>> from pyhdf.VS import * # names need no prefix This document assumes the last import style is used. VS is not self-contained, and needs functionality provided by another pyhdf module, namely the HDF module. This module must thus be imported also: >>> from .HDF import * Package components ------------------ pyhdf is a proper Python package, eg a collection of modules stored under a directory whose name is that of the package and which stores an __init__.py file. Following the normal installation procedure, this directory will be /site-packages/pyhdf', where stands for the python installation directory. For each HDF API exists a corresponding set of modules. The following modules are related to the VS API. _hdfext C extension module responsible for wrapping the HDF C library for all python modules hdfext python module implementing some utility functions complementing the _hdfext extension module error defines the HDF4Error exception HDF python module providing support to the VS module VS python module wrapping the VS API routines inside an OOP framework _hdfext and hdfext were generated using the SWIG preprocessor. SWIG is however *not* needed to run the package. Those two modules are meant to do their work in the background, and should never be called directly. Only HDF and VS should be imported by the user program. Prerequisites ------------- The following software must be installed in order for VS to work. HDF (v4) library pyhdf does *not* include the HDF4 library, which must be installed separately. HDF is available at: "https://portal.hdfgroup.org/display/support/Download+HDF4". Numeric is also needed by the SD module. See the SD module documentation. Documentation ------------- pyhdf has been written so as to stick as closely as possible to the naming conventions and calling sequences documented inside the "HDF User s Guide" manual. Even if pyhdf gives an OOP twist to the C API, the manual can be easily used as a documentary source for pyhdf, once the class to which a function belongs has been identified, and of course once requirements imposed by the Python language have been taken into account. Consequently, this documentation will not attempt to provide an exhaustive coverage of the HDF VS API. For this, the user is referred to the above manual. The documentation of each pyhdf method will indicate the name of the equivalent routine as it is found inside the C API. This document (in both its text and html versions) has been completely produced using "pydoc", the Python documentation generator (which made its debut in the 2.1 Python release). pydoc can also be used as an on-line help tool. For example, to know everything about the VS.VD class, say: >>> from pydoc import help >>> from pyhdf.VS import * >>> help(VD) To be more specific and get help only for the read() method of the VD class: >>> help(VD.read) pydoc can also be called from the command line, as in:: % pydoc pyhdf.VS.VD # doc for the whole VD class % pydoc pyhdf.VS.VD.read # doc for the VD.read method Summary of differences between the pyhdf and C VS API ----------------------------------------------------- Most of the differences between the pyhdf and C VS API can be summarized as follows. - In the C API, every function returns an integer status code, and values computed by the function are returned through one or more pointers passed as arguments. - In pyhdf, error statuses are returned through the Python exception mechanism, and values are returned as the method result. When the C API specifies that multiple values are returned, pyhdf returns a sequence of values, which are ordered similarly to the pointers in the C function argument list. Error handling -------------- All errors reported by the C VS API with a SUCCESS/FAIL error code are reported by pyhdf using the Python exception mechanism. When the C library reports a FAIL status, pyhdf raises an HDF4Error exception (a subclass of Exception) with a descriptive message. Unfortunately, the C library is rarely informative about the cause of the error. pyhdf does its best to try to document the error, but most of the time cannot do more than saying "execution error". VS needs support from the HDF module ------------------------------------ The VS module is not self-contained (countrary to the SD module). It requires help from the HDF module, namely: - the HDF.HDF class to open and close the HDF file, and initialize the VS interface - the HDF.HC class to provide different sorts of constants (opening modes, data types, etc). A program wanting to access HDF vdatas will almost always need to execute the following minimal set of calls: >>> from pyhdf.HDF import * >>> from pyhdf.VS import * >>> hdfFile = HDF(name, HC.xxx)# open HDF file >>> vs = hdfFile.vstart() # initialize VS interface on HDF file >>> ... # manipulate vdatas through "vs" >>> vs.end() # terminate VS interface >>> hdfFile.close() # close HDF file Classes summary --------------- pyhdf wraps the VS API using different python classes:: VS HDF VS interface VD vdata VDField vdata field VDattr attribute (either at the vdata or field level) In more detail:: VS The VS class implements the VS (Vdata) interface applied to an HDF file. This class encapsulates the hdf instance, and all the top-level functions of the VS API. To create a VS instance, call the vstart() method of an HDF instance. methods: constructors: attach() open an existing vdata given its name or reference number, or create a new one, returning a VD instance create() create a new vdata and define its structure, returning a VD instance creating and initializing a simple vdata storedata() create a single-field vdata and initialize its values closing the interface end() close the VS interface on the HDF file searching find() get a vdata reference number given its name next() get the reference number of the vdata following a given one inquiry vdatainfo() return info about all the vdatas in the HDF file VD The VD class describes a vdata. It encapsulates the VS instance to which the vdata belongs, and the vdata identifier. To instantiate a VD class, call the attach() or create() method of a VS class instance. methods: constructors attr() create a VDAttr instance representing a vdata attribute; "dot notation" can also be used to access a vdata attribute field() return a VDField instance representing a given field of the vdata closing vdata detach() end access to the vdata defining fields fdefine() define the name, type and order of a new field setfields() define the field names and field order for the read() and write() methods; also used to initialize the structure of a vdata previously created with the VS.attach() method reading and writing note: a vdata can be indexed and sliced like a python sequence read() return the values of a number of records starting at the current record position seek() reset the current record position seekend() seek past the last record tell() return the current record position write() write a number of records starting at the current record position inquiry attrinfo() return info about all the vdata attributes fexist() check if a vdata contains a given set of fields fieldinfo() return info about all the vdata fields findattr() locate an attribute, returning a VDAttr instance if found inquire() return info about the vdata sizeof() return the size in bytes of one or more fields VDField The VDField class represents a vdata field. It encapsulates the VD instance to which the field belongs, and the field index number. To instantiate a VDField, call the field() method of a VD class instance. methods: constructors: attr() return a VDAttr instance representing an attribute of the field; "dot notation" can also be used to get/set an attribute. inquiry attrinfo() return info about all the field attributes find() locate an attribute, returning a VDAttr instance if found VDAttr The VDAttr class encapsulates methods used to set and query attributes defined at the level either of the vdata or the vdata field. To create an instance of this class, call the attr() or findattr() methods of a VD instance (for vdata attributes), or call the attr() or find() methods of a VDField instance (for field attributes). methods: get / set get() get the attribute value set() set the attribute value info info() retrieve info about the attribute Data types ---------- Data types come into play when first defining vdata fields and attributes, and later when querying the definition of those fields and attributes. Data types are specified using the symbolic constants defined inside the HC class of the HDF module. - CHAR and CHAR8 (equivalent): an 8-bit character. - UCHAR, UCHAR8 and UINT8 (equivalent): unsigned 8-bit values (0 to 255) - INT8: signed 8-bit values (-128 to 127) - INT16: signed 16-bit values - UINT16: unsigned 16 bit values - INT32: signed 32 bit values - UINT32: unsigned 32 bit values - FLOAT32: 32 bit floating point values (C floats) - FLOAT64: 64 bit floating point values (C doubles) There is no explicit "string" type. To simulate a string, set the field or attribute type to CHAR, and set the field or attribute "order" to a value of 'n' > 1. This creates and "array of characters", close to a string (except that strings will always be of length 'n', right-padded with spaces if necessary). Attribute access: low and high level ------------------------------------ The VS API allow setting attributes on vdatas and vdata fields. Attributes can be of many types (int, float, char) of different bit lengths (8, 16, 32, 64 bits), and can be single or multi-valued. Values of a multi-valued attribute must all be of the same type. Attributes can be set and queried in two different ways. First, given a VD instance (describing a vdata object) or a VDField instance (describing a vdata field), the attr() method of that instance is called to create a VDAttr instance representing the wanted attribute (possibly non existent). The set() method of this VDAttr instance is then called to define the attribute value, creating it if it does not already exist. The get() method returns the current attribute value. Here is an example. >>> from pyhdf.HDF import * >>> from pyhdf.VS import * >>> f = HDF('test.hdf', HC.WRITE) # Open file 'test.hdf' in write mode >>> vs = f.vstart() # init vdata interface >>> vd = vs.attach('vtest', 1) # attach vdata 'vtest' in write mode >>> attr = vd.attr('version') # prepare to define the 'version' attribute # on the vdata >>> attr.set(HC.CHAR8,'1.0') # set attribute 'version' to string '1.0' >>> print(attr.get()) # get and print attribute value >>> fld = vd.field('fld1') # obtain a field instance for field 'fld1' >>> attr = fld.attr('range') # prepare to define attribute 'range' on # this field >>> attr.set(HC.INT32,(-10, 15)) # set attribute 'range' to a pair of ints >>> print(attr.get()) # get and print attribute value >>> vd.detach() # "close" the vdata >>> vs.end() # terminate the vdata interface >>> f.close() # close the HDF file The second way consists of setting/querying an attribute as if it were a normal python class attribute, using the usual dot notation. Above example then becomes: >>> from pyhdf.HDF import * >>> from pyhdf.VS import * >>> f = HDF('test.hdf', HC.WRITE) # Open file 'test.hdf' in write mode >>> vs = f.vstart() # init vdata interface >>> vd = vs.attach('vtest', 1) # attach vdata 'vtest' in write mode >>> vd.version = '1.0' # create vdata attribute 'version', # setting it to string '1.0' >>> print(vd.version) # print attribute value >>> fld = vd.field('fld1') # obtain a field instance for field 'fld1' >>> fld.range = (-10, 15) # create field attribute 'range', setting # it to the pair of ints (-10, 15) >>> print(fld.range) # print attribute value >>> vd.detach() # "close" the vdata >>> vs.end() # terminate the vdata interface >>> f.close() # close the HDF file Note how the dot notation greatly simplifies and clarifies the code. Some latitude is however lost by manipulating attributes in that way, because the pyhdf package, not the programmer, is then responsible of setting the attribute type. The attribute type is chosen to be one of: =========== ==================================== HC.CHAR8 if the attribute value is a string HC.INT32 if all attribute values are integers HC.FLOAT64 otherwise =========== ==================================== The first way of handling attribute values must be used if one wants to define an attribute of any other type (for ex. 8 or 16 bit integers, signed or unsigned). Also, only a VDAttr instance gives access to attribute info, through its info() method. However, accessing HDF attributes as if they were python attributes raises an important issue. There must exist a way to assign generic attributes to the python objects without requiring those attributes to be converted to HDF attributes. pyhdf uses the following rule: an attribute whose name starts with an underscore ('_') is either a "predefined" attribute (see below) or a standard python attribute. Otherwise, the attribute is handled as an HDF attribute. Also, HDF attributes are not stored inside the object dictionary: the python dir() function will not list them. Attribute values can be updated, but it is illegal to try to change the value type, or the attribute order (number of values). This is important for attributes holding string values. An attribute initialized with an 'n' character string is simply a character attribute of order 'n' (eg a character array of length 'n'). If 'vd' is a vdata and we initialize its 'a1' attribute as 'vd.a1 = "abcdef"', then a subsequent update attempt like 'vd.a1 = "12"' will fail, because we then try to change the order of the attribute (from 6 to 2). It is mandatory to keep the length of string attributes constant. Examples below show simple ways how this can be done. Predefined attributes --------------------- The VD and VDField classes support predefined attributes to get (and occasionnaly set) attribute values easily, without having to call a class method. The names of predefined attributes all start with an underscore ('_'). In the following tables, the RW column holds an X if the attribute is read/write. See the HDF User s guide for details about more "exotic" topics like "class", "faked vdata" and "tag". VD predefined attributes =========== == ========================== ============================= name RW description C library routine =========== == ========================== ============================= _class X class name VSgetclass/VSsetclass _fields list of field names VSgetfields _interlace X interlace mode VSgetinterlace/VSsetinterlace _isattr true if vdata is "faked" VSisattr by HDF to hold attributes _name X name of the vdata VSgetname/VSsetname _nattrs number of attributes VSfnattrs _nfields number of fields VFnfields _nrecs number of records VSelts _recsize record size (bytes) VSQueryvsize _refnum reference number VSQueryref _tag vdata tag VSQuerytag _tnattrs total number of vdata and VSnattrs field attributes =========== == ========================== ============================= VDField predefined attributes =========== == ========================== ============================= name RW description C library routine =========== == ========================== ============================= _esize external size (bytes) VFfieldesize _index index number VSfindex _isize internal size (bytes) VFfieldisize _name name VFfieldname _nattrs number of attributes VSfnattrs _order order (number of values) VFfieldorder _type field type (HC.xxx) VFfieldtype =========== == ========================== ============================= Record access: low and high level --------------------------------- vdata records can be read and written in two different ways. The first one consists of calling the basic I/O methods of the vdata: - seek() to set the current record position, if necessary; - read() to retrieve a given number of records from that position; - write() to write a given number of records starting at that position A second, higher level way, lets one see a vdata similarly to a python sequence, and access its contents using the familiar indexing and slicing notation in square brackets. Reading and writing a vdata as if it were a python sequence may often look simpler, and improve code legibility. Here are some examples of how a vdata 'vd' holding 3 fields could be read. >>> print(vd[0]) # print record 0 >>> print(vd[-1]) # print last record >>> print(vd[2:]) # print records 2 and those that follow >>> print(vd[:]) # print all records >>> print(vd[:,0]) # print field 0 of all records >>> print(vd[:3,:2]) # print first 2 fields of first 3 records As the above examples show, the usual python rules are obeyed regarding the interpretation of indexing and slicing values. Note that the vdata fields can be indexed and sliced, not only the records. The setfields() method can also be used to select a subset to the vdata fields (setfields() also let you reorder the fields). When the vdata is indexed (as opposed to being sliced), a single record is returned as a list of values. When the vdata is sliced, a list of records is always returned (thus a 2-level list), even if the slice contains only one record. A vdata can also be written similarly to a python sequence. When indexing the vdata (as opposed to slicing it), a single record must be assigned, and the record must be given as a sequence of values. It is legal to use as an index the current number of records in the vdata: the record is then appended to the vdata. When slicing the vdata, the records assigned to the slice must always be given as a list of records, even if only one record is assigned. Also, the number of records assigned must always match the width of the slice, except if the slice includes or goes past the last record of the vdata. In that case, the number of records assigned can exceed the width of the slice, and the extra records are appended to the vdata. So, to append records to vdata 'vd', simply assign records to the slice 'vd[vd._nrecs:]'. Note that, even if the 'field' dimension can be specified in the left-hand side expression, there is no real interest in doing so, since all fields must be specified when assigning a record to the vdata: it is an error to try to assign just a few of the fields. For example, given a vdata 'vd' holding 5 records, and lists 'reca', 'recb', etc, holding record values:: vd[0] = reca # updates record 0 vd[0,:] = reca # specifying fields is OK, but useless vd[0,1:] = reca[1:] # error: all fields must be assigned vd[1] = [recb, recc] # error: only one record allowed vd[5] = recc # append one record vd[1:3] = [reca,recb] # updates second and third record vd[1:4] = [reca, recb] # error: 3 records needed vd[5:] = [reca,recb] # appends 2 records to the vdata vd[4:] = [reca, recb] # updates last record, append one Programming models ------------------ Creating and initializing a new vdata ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ The following code can serve as a model for the creation and initialization of a new vdata. It implements the INVENTORY example described in the "Introduction" section:: from pyhdf.HDF import * from pyhdf.VS import * # Open HDF file and initialize the VS interface f = HDF('inventory.hdf', # Open file 'inventory.hdf' in write mode HC.WRITE|HC.CREATE) # creating it if it does not exist vs = f.vstart() # init vdata interface # Create vdata and define its structure vd = vs.create( # create a new vdata 'INVENTORY', # name of the vdata # fields of the vdata follow (('partid',HC.CHAR8, 5), # 5 char string ('description',HC.CHAR8, 10), # 10 char string field ('qty',HC.INT16, 1), # 1 16 bit int field ('wght',HC.FLOAT32, 1), # 1 32 bit float ('price',HC.FLOAT32,1) # 1 32 bit float )) # 5 fields allocated in the vdata # Set attributes on the vdata and its fields vd.field('wght').unit = 'lb' vd.field('price').unit = '$' # In order to be able to update a string attribute, it must # always be set to the same length. This sets 'status' to a 20 # char long, left-justified string, padded with spaces on the right. vd.status = "%-20s" % 'phase 1 done' # Store records vd.write(( # write 3 records ('Q1234', 'bolt',12, 0.01, 0.05), # record 1 ('B5432', 'brush', 10, 0.4, 4.25), # record 2 ('S7613', 'scissor', 2, 0.2, 3.75) # record 3 )) vd.detach() # "close" the vdata vs.end() # terminate the vdata interface f.close() # close the HDF file Note that is mandatory to always write whole records to the vdata. Note also the comments about the initialization of the 'status' vdata attribute. We want to be able update this attribute (see following examples). However, the VS API prohibits changing an attribute type when updating its value. Since the length (order) of an attribute is part of its type, we make sure of setting the attribute to a length long enough to accommodate the longest possible string we migh want to assign to the attribute. Appending records to a vdata ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ Appending records requires first seeking to the end of the vdata, to avoid overwriting existing records. The following code can serve as a model. The INVENTORY vdata created before is used:: from pyhdf.HDF import * from pyhdf.VS import * f = HDF('inventory.hdf', # Open 'inventory.hdf' in write mode HC.WRITE|HC.CREATE) # creating it if it does not exist vs = f.vstart() # init vdata interface vd = vs.attach('INVENTORY', 1) # attach 'INVENTORY' in write mode # Update the `status' vdata attribute. The attribute length must not # change. We call the attribute info() method, which returns a list # where number of values (eg string length) is stored at index 2. # We then assign a left justified string of exactly that length. len = vd.attr('status').info()[2] vd.status = '%-*s' % (len, 'phase 2 done') vd[vd._nrecs:] = ( # append 2 records ('A4321', 'axe', 5, 1.5, 25), # first record ('C3214', 'cup', 100, 0.1, 3.25) # second record ) vd.detach() # "close" the vdata vs.end() # terminate the vdata interface f.close() # close the HDF file Note how, when updating the value of the 'status' vdata attribute, we take care of assigning a value of the same length as that of the original value. Otherwise, the assignment would raise an exception. Records are written by assigning the vdata through a slicing expression, like a python sequence. By specifying the number of records as the start of the slice, the records are appended to the vdata. Updating records in a vdata ^^^^^^^^^^^^^^^^^^^^^^^^^^^ Updating requires seeking to the record to update before writing the new records. New data will overwrite this record and all records that follow, until a new seek is performed or the vdata is closed. Note that record numbering starts at 0. The following code can serve as a model. The INVENTORY vdata created before is used:: from pyhdf.HDF import * from pyhdf.VS import * f = HDF('inventory.hdf', # Open 'inventory.hdf' in write mode HC.WRITE|HC.CREATE) # creating it if it does not exist vs = f.vstart() # init vdata interface vd = vs.attach('INVENTORY', 1) # attach 'INVENTORY' in write mode # Update the `status' vdata attribute. The attribute length must not # change. We call the attribute info() method, which returns a list # where number of values (eg string length) is stored at index 2. # We then assign a left justified string of exactly that length. len = vd.attr('status').info()[2] vd.status = '%-*s' % (len, 'phase 3 done') # Update record at index 1 (second record) vd[1] = ('Z4367', 'surprise', 10, 3.1, 44.5) # Update record at index 4, and all those that follow vd[4:] = ( ('QR231', 'toy', 12, 2.5, 45), ('R3389', 'robot', 3, 45, 2000) ) vd.detach() # "close" the vdata vs.end() # terminate the vdata interface f.close() # close the HDF file Reading a vdata ^^^^^^^^^^^^^^^ The following example shows how read the vdata attributes and sequentially maneuver through its records. Note how we use the exception mechanism to break out of the reading loop when we reach the end of the vdata:: from pyhdf.HDF import * from pyhdf.VS import * f = HDF('inventory.hdf') # open 'inventory.hdf' in read mode vs = f.vstart() # init vdata interface vd = vs.attach('INVENTORY') # attach 'INVENTORY' in read mode # Display some vdata attributes print "status:", vd.status print "vdata: ", vd._name # predefined attribute: vdata name print "nrecs: ", vd._nrecs # predefined attribute: num records # Display value of attribute 'unit' for all fields on which # this attribute is set print "units: ", for fieldName in vd._fields: # loop over all field names try: # instantiate field and obtain value of attribute 'unit' v = vd.field(fieldName).unit print "%s: %s" % (fieldName, v), except: # no 'unit' attribute: ignore pass print "" print "" # Display table header. header = "%-7s %-12s %3s %4s %8s" % tuple(vd._fields) print "-" * len(header) print header print "-" * len(header) # Loop over the vdata records, displaying each record as a table row. # Current record position is 0 after attaching the vdata. while 1: try: rec = vd.read() # read next record # equivalent to: # rec = vd[vd.tell()] print "%-7s %-12s %3d %4.1f %8.2f" % tuple(rec[0]) except HDF4Error: # end of vdata reached break vd.detach() # "close" the vdata vs.end() # terminate the vdata interface f.close() # close the HDF file In the previous example, the reading/displaying loop can be greatly simplified by rewriting it as follows:: from pyhdf.HDF import * from pyhdf.VS import * f = HDF('inventory.hdf') # open 'inventory.hdf' in read mode vs = f.vstart() # init vdata interface vd = vs.attach('INVENTORY') # attach 'INVENTORY' in read mode .... # Read all records at once, and loop over the sequence. for rec in vd[:]: print "%-7s %-12s %3d %4.1f %8.2f" % tuple(rec) vd.detach() # "close" the vdata ... The indexing expression 'vd[:]' returns the complete set of records, which can then be looped over using a 'for' statement. This style of loop is quite clean, and should look very familiar to python adepts. """ import os, sys, types from . import hdfext as _C from . import six from .six.moves import xrange from .HC import HC from .error import HDF4Error, _checkErr # List of names we want to be imported by an "from pyhdf.VS import *" # statement __all__ = ['VS', 'VD', 'VDField', 'VDAttr'] class VS(object): """The VS class implements the VS (Vdata) interface applied to an HDF file. To instantiate a VS class, call the vstart() method of an HDF instance. """ def __init__(self, hinst): # Not to be called directly by the user. # A VS object is instantiated using the vstart() # method of an HDF instance. # Args: # hinst HDF instance # Returns: # A VS instance # # C library equivalent : Vstart (rather: Vinitialize) # Private attributes: # _hdf_inst: HDF instance # Note: Vstart is just a macro; use 'Vinitialize' instead status = _C.Vinitialize(hinst._id) _checkErr('VS', status, "cannot initialize VS interface") self._hdf_inst = hinst def __del__(self): """Delete the instance, first calling the end() method if not already done. """ try: if self._hdf_inst: self.end() except: pass def end(self): """Close the VS interface. Args:: No argument Returns:: None C library equivalent : Vend """ # Note: Vend is just a macro; use 'Vfinish' instead _checkErr('end', _C.Vfinish(self._hdf_inst._id), "cannot terminate VS interface") self._hdf_inst = None vend = end # For backward compatibility def attach(self, num_name, write=0): """Locate an existing vdata or create a new vdata in the HDF file, returning a VD instance. Args:: num_name Name or reference number of the vdata. An existing vdata can be specified either through its reference number or its name. Use -1 to create a new vdata. Note that uniqueness is not imposed on vdatas names, whereas refnums are guaranteed to be unique. Thus knowledge of its reference number may be the only way to get at a wanted vdata. write Set to 0 to open the vdata in read-only mode, set to 1 to open it in write mode Returns:: VD instance representing the vdata C library equivalent : VSattach After creating a new vdata (num_name == -1), fields must be defined using method fdefine() of the VD instance, and those fields must be allocated to the vdata with method setfields(). Same results can be achieved, but more simply, by calling the create() method of the VS instance. """ mode = write and 'w' or 'r' if isinstance(num_name, str): num = self.find(num_name) else: num = num_name vd = _C.VSattach(self._hdf_inst._id, num, mode) if vd < 0: _checkErr('attach', vd, 'cannot attach vdata') return VD(self, vd) def create(self, name, fields): """Create a new vdata, setting its name and allocating its fields. Args:: name Name to assign to the vdata fields Sequence of field definitions. Each field definition is a sequence with the following elements in order: - field name - field type (one of HC.xxx constants) - field order (number of values) Fields are allocated to the vdata in the given order Returns:: VD instance representing the created vdata Calling the create() method is equivalent to the following calls: - vd = attach(-1,1), to create a new vdata and open it in write mode - vd._name = name, to set the vdata name - vd.fdefine(...), to define the name, type and order of each field - vd.setfields(...), to allocate fields to the vdata C library equivalent : no equivalent """ try: # Create new vdata (-1), open in write mode (1) vd = self.attach(-1, 1) # Set vdata name vd._name = name # Define fields allNames = [] for name, type, order in fields: vd.fdefine(name, type, order) allNames.append(name) # Allocate fields to the vdata vd.setfields(*allNames) return vd except HDF4Error as msg: raise HDF4Error("error creating vdata (%s)" % msg) def find(self, vName): """Get the reference number of a vdata given its name. The vdata can then be opened (attached) by passing this reference number to the attach() method. Args:: vName Name of the vdata for which the reference number is needed. vdatas names are not guaranteed to be unique. When more than one vdata bear the same name, find() will return the refnum of the first one founmd. Returns:: vdata reference number. 0 is returned if the vdata does not exist. C library equivalent : VSfind """ refNum = _C.VSfind(self._hdf_inst._id, vName) _checkErr("find", refNum, "cannot find vdata %s" % vName) return refNum def next(self, vRef): """Get the reference number of the vdata following a given vdata. Args:: vRef Reference number of the vdata preceding the one we require. Set to -1 to get the first vdata in the HDF file. Knowing its reference number, the vdata can then be opened (attached) by passing this reference number to the attach() method. Returns:: Reference number of the vdata following the one given by argument vref An exception is raised if no vdata follows the one given by vRef. C library equivalent : VSgetid """ num = _C.VSgetid(self._hdf_inst._id, vRef) _checkErr('next', num, 'cannot get next vdata') return num def vdatainfo(self, listAttr=0): """Return info about all the file vdatas. Args:: listAttr Set to 0 to ignore vdatas used to store attribute values, 1 to list them (see the VD._isattr readonly attribute) Returns:: List of vdata descriptions. Each vdata is described as a 9-element tuple, composed of the following: - vdata name - vdata class - vdata reference number - vdata number of records - vdata number of fields - vdata number of attributes - vdata record size in bytes - vdata tag number - vdata interlace mode C library equivalent : no equivalent """ lst = [] ref = -1 # start at beginning while True: try: nxtRef = self.next(ref) except HDF4Error: # no vdata left break # Attach the vdata and check for an "attribute" vdata. ref = nxtRef vdObj = self.attach(ref) if listAttr or not vdObj._isattr: # Append a list of vdata properties. lst.append((vdObj._name, vdObj._class, vdObj._refnum, vdObj._nrecs, vdObj._nfields, vdObj._nattrs, vdObj._recsize, vdObj._tag, vdObj._interlace)) vdObj.detach() return lst def storedata(self, fieldName, values, data_type, vName, vClass): """Create and initialize a single field vdata, returning the vdata reference number. Args:: fieldName Name of the single field in the vadata to create values Sequence of values to store in the field;. Each value can itself be a sequence, in which case the field will be multivalued (all second-level sequences must be of the same length) data_type Values type (one of HC.xxx constants). All values must be of the same type vName Name of the vdata to create vClass Vdata class (string) Returns:: vdata reference number C library equivalent : VHstoredata / VHstoredatam """ # See if the field is multi-valued. nrecs = len(values) if type(values[0]) in [list, tuple]: order = len(values[0]) # Replace input list with a flattened list. newValues = [] for el in values: for e in el: newValues.append(e) values = newValues else: order = 1 n_values = nrecs * order if data_type == HC.CHAR8: buf = _C.array_byte(n_values) # Allow values to be passed as a string. # Noop if a list is passed. values = list(values) for n in range(n_values): values[n] = ord(values[n]) elif data_type in [HC.UCHAR8, HC.UINT8]: buf = _C.array_byte(n_values) elif data_type == HC.INT8: # SWIG refuses negative values here. We found that if we # pass them as byte values, it will work. buf = _C.array_int8(n_values) values = list(values) for n in range(n_values): v = values[n] if v >= 0: v &= 0x7f else: v = abs(v) & 0x7f if v: v = 256 - v else: v = 128 # -128 in 2s complement values[n] = v elif data_type == HC.INT16: buf = _C.array_int16(n_values) elif data_type == HC.UINT16: buf = _C.array_uint16(n_values) elif data_type == HC.INT32: buf = _C.array_int32(n_values) elif data_type == HC.UINT32: buf = _C.array_uint32(n_values) elif data_type == HC.FLOAT32: buf = _C.array_float32(n_values) elif data_type == HC.FLOAT64: buf = _C.array_float64(n_values) else: raise HDF4Error("storedata: illegal or unimplemented data_type") for n in range(n_values): buf[n] = values[n] if order == 1: vd = _C.VHstoredata(self._hdf_inst._id, fieldName, buf, nrecs, data_type, vName, vClass) else: vd = _C.VHstoredatam(self._hdf_inst._id, fieldName, buf, nrecs, data_type, vName, vClass, order) _checkErr('storedata', vd, 'cannot create vdata') return vd class VD(object): """The VD class encapsulates the functionality of a vdata. To instantiate a VD class, call the attach() or the create() method of a VS class instance.""" def __init__(self, vsinst, id): # This constructor is not intended to be called directly # by the user program. The attach() method of an # VS class instance should be called instead. # Arg: # vsinst VS instance from which the call is made # id vdata reference number # Private attributes: # _vs_inst VS instance to which the vdata belongs # _id vdata identifier # _offset current record offset # _setfields last arg to setfields() self._vs_inst = vsinst self._id = id self._offset = 0 self._setfields = None def __getattr__(self, name): """Some vdata properties can be queried/set through the following attributes. Their names all start with an "_" to avoid clashes with user-defined attributes. Most are read-only. Only the _class, _fields, _interlace and _name can be modified. _fields and _interlace can only be set once. Name RO Description C library routine ----- -- ----------------- ----------------- _class class name VSgetclass _fields X field names VSgetfields _interlace interlace mode VSgetinterlace _isattr X attribute vs real vdata VSisattr _name name VSgetname _nattrs X number of attributes VSfnattrs _nfields X number of fields VFnfields _nrecs X number of records VSelts _recsize X record size VSQueryvsize _refnum X reference number VSQueryref _tag X tag VSQuerytag _tnattrs X total number of attr. VSnattrs """ # Check for a user defined attribute first. att = self.attr(name) if att._index is not None: # Then the attribute exists return att.get() # Check for a predefined attribute elif name == "_class": status, nm = _C.VSgetclass(self._id) _checkErr('_class', status, 'cannot get vdata class') return nm elif name == "_fields": n, fields = _C.VSgetfields(self._id) _checkErr('_fields', n, "cannot get vdata field names") return fields.split(',') elif name == "_interlace": mode = _C.VSgetinterlace(self._id) _checkErr('_interlace', mode, "cannot get vdata interlace mode") return mode elif name == "_isattr": return _C.VSisattr(self._id) elif name == "_name": status, nm = _C.VSgetname(self._id) _checkErr('_name', status, 'cannot get vdata name') return nm elif name == "_nattrs": n = _C.VSfnattrs(self._id, -1) # -1: vdata attributes _checkErr("_nfields", n, "cannot retrieve number of attributes") return n elif name == "_nfields": n = _C.VFnfields(self._id) _checkErr("_nfields", n, "cannot retrieve number of fields") return n elif name == "_nrecs": n = _C.VSelts(self._id) _checkErr('_nrecs', n, 'cannot get vdata number of records') return n elif name == "_recsize": return self.inquire()[3] elif name == "_refnum": n = _C.VSQueryref(self._id) _checkErr('refnum', n, 'cannot get reference number') return n elif name == "_tag": n = _C.VSQuerytag(self._id) _checkErr('_tag', n, 'cannot get tag') return n elif name == "_tnattrs": n = _C.VSnattrs(self._id) _checkErr('_tnattrs', n, 'execution error') return n raise AttributeError def __setattr__(self, name, value): # A name starting with an underscore will be treated as # a standard python attribute, and as an HDF attribute # otherwise. # Forbid assigning to our predefined attributes if name in ["_fields", "_isattr", "_nattrs", "_nfields", "_nrecs", "_recsize", "_refnum", "_tag", "_tnattrs"]: raise AttributeError("%s: read-only attribute" % name) # Handle the 3 VS attributes: _class, _interlace # and _name. _interlace can only be set once. elif name == "_class": _checkErr(name, _C.VSsetclass(self._id, value), 'cannot set _class property') elif name == "_interlace": _checkErr(name, _C.VSsetinterlace(self._id, value), 'cannot set _interlace property') elif name == "_name": _checkErr(name, _C.VSsetname(self._id, value), 'cannot set _name property') # Try to set the attribute. else: _setattr(self, name, value) def __getitem__(self, elem): # This method is called when the vdata is read # like a Python sequence. # Parse the indexing expression. start, count = self.__buildStartCount(elem) # Reset current position if necessary. if self._offset != start[0]: self.seek(start[0]) # Get records. A negative count means that an index was used. recs = self.read(abs(count[0])) # See if all the fields must be returned. f0 = start[1] if f0 == 0 and count[1] == self._nfields: out = recs else: # Return only a subset of the vdata fields. out = [] f1 = f0 + count[1] for r in recs: out.append(r[f0:f1]) # If an index was used (not a slice), return the record as # a list, instead of returning it inside a 2-level list, if count[0] < 0: return out[0] return out def __setitem__(self, elem, data): # This method is called when the vdata is written # like a Python sequence. # # When indexing the vdata, 'data' must specify exactly # one record, which must be specified as a sequence. If the index is # equal to the current number of records, the record # is appended to the vdata. # # When slicing the vdata, 'data' must specify a list of records. # The number of records in the top level-list must match the width # of the slice, except if the slice extends past the end of the # vdata. In that case, extra records can be specified in the list, # which will be appended to the vdata. In other words, # to append records to vdata 'vd', assign records to # the slice 'vd[vd._nrecs:]'. # # For ex., given a vdata 'vd' holding 5 records, and lists # 'reca', 'recb', etc holding record values: # vd[0] = reca # updates record 0 # vd[1] = [recb, recc] # error: only one record allowed # vd[1:3] = [reca,recb] # updates second and third record # vd[1:4] = [reca, recb] # error: 3 records needed # vd[5:] = [reca,recb] # appends 2 records to the vdata # Check that arg is a list. if not type(data) in [tuple, list]: raise HDF4Error("record(s) must be specified as a list") start, count = self.__buildStartCount(elem, setitem=1) # Records cannot be partially written. if start[1] != 0 or count[1] != self._nfields: raise HDF4Error("each vdata field must be written") # If an index (as opposed to a slice) was applied to the # vdata, a single record must be passed. Since write() requires # a 2-level list, wrap this record inside a list. if count[0] < 0: if len(data) != self._nfields: raise HDF4Error("record does not specify all fields") data = [data] # A slice was used. The slice length must match the number of # records, except if the end of the slice equals the number # of records. Then, extra recors can be specified, which will # be appended to the vdata. else: if count[0] != len(data): if start[0] + count[0] != self._nrecs: raise HDF4Error("illegal number of records") # Reset current record position if necessary. if self._offset != start[0]: self.seek(start[0]) # Write records. recs = self.write(data) def __del__(self): """Delete the instance, first calling the detach() method if not already done. """ try: if self._id: self.detach() except: pass def detach(self): """Terminate access to the vdata. Args:: no argument Returns:: None C library equivalent : VSdetach """ _checkErr('detach', _C.VSdetach(self._id), "cannot detach vdata") self._id = None def fdefine(self, name, type, order): """Define a field. To initialize a newly created vdata with fields created with fdefine(), assign a tuple of field names to the _fields attribute or call the setfields() method. Args:: name field name type field data type (one of HC.xxx) order field order (number of values in the field) Returns:: None C library equivalent : VSfdefine """ _checkErr('fdefine', _C.VSfdefine(self._id, name, type, order), 'cannot define field') def setfields(self, *fldNames): """Define the name and order of the fields to access with the read() and write() methods. Args:: fldNames variable length argument specifying one or more vdata field names Returns:: None C library equivalent : VSsetfields setfields() indicates how to perform the matching between the vdata fields and the values passed to the write() method or returned by the read() method. For example, if the vdata contains fields 'a', 'b' and 'c' and a "setfields('c','a')" call is made, read() will thereafter return for each record the values of field 'c' and 'a', in that order. Field 'b' will be ignored. When writing to a vdata, setfields() has a second usage. It is used to initialize the structure of the vdata, that is, the name and order of the fields that it will contain. The fields must have been previously defined by calls to the fdefine() method. Following that first call, setfields() can be called again to change the order in which the record values will be passed to the write() method. However, since it is mandatory to write whole records, subsequent calls to setfields() must specify every field name: only the field order can be changed. """ _checkErr('setfields', _C.VSsetfields(self._id, ','.join(fldNames)), 'cannot execute') self._setfields = fldNames # remember for read/write routines def field(self, name_index): """Get a VDField instance representing a field of the vdata. Args:: name_index name or index number of the field Returns:: VDfield instance representing the field C library equivalent : no equivalent """ # Transform a name to an index number if isinstance(name_index, str): status, index = _C.VSfindex(self._id, name_index) _checkErr('field', status, "illegal field name: %s" % name_index) else: n = _C.VFnfields(self._id) _checkErr('field', n, 'cannot execute') index = name_index if index >= n: raise HDF4Error("field: illegal index number") return VDField(self, index) def seek(self, recIndex): """Seek to the beginning of the record identified by its record index. A succeeding read will load this record in memory. Args:: recIndex index of the record in the vdata; numbering starts at 0. Legal values range from 0 (start of vdata) to the current number of records (at end of vdata). Returns:: record index An exception is raised if an attempt is made to seek beyond the last record. The C API prohibits seeking past the next-to-last record, forcing one to read the last record to advance to the end of the vdata. The python API removes this limitation. Seeking to the end of the vdata can also be done by calling method ``seekend()``. C library equivalent : VSseek """ if recIndex > self._nrecs - 1: if recIndex == self._nrecs: return self.seekend() else: raise HDF4Error("attempt to seek past last record") n = _C.VSseek(self._id, recIndex) _checkErr('seek', n, 'cannot seek') self._offset = n return n def seekend(self): """Set the current record position past the last vdata record. Subsequent write() calls will append records to the vdata. Args:: no argument Returns:: index of the last record plus 1 C library equivalent : no equivalent """ try: # Seek to the next-to-last record position n = self.seek(self._nrecs - 1) # updates _offset # Read last record, ignoring values self.read(1) # updates _offset return self._nrecs except HDF4Error: raise HDF4Error("seekend: cannot execute") def tell(self): """Return current record position in the vdata. Args:: no argument Returns:: current record position; 0 is at start of vdata. C library equivalent : no equivalent """ return self._offset def read(self, nRec=1): """Retrieve the values of a number of records, starting at the current record position. The current record position is advanced by the number of records read. Current position is 0 after "opening" the vdata with the attach() method. Args:: nRec number of records to read Returns:: 2-level list. First level is a sequence of records, second level gives the sequence of values for each record. The values returned for each record are those of the fields specified in the last call to method setfields(), in that order. The complete vdata field set is returned if setfields() has not been called. An exception is raised if the current record position is already at the end of the vdata when read() is called. This exception can be caught as an "end of vdata" indication to exit a loop which scans each record of the vdata. Otherwise, the number of records to be read is lowered to the number of records remaining in the vdata, if that number is less than the number asked for by parameter 'nRec'. Setting 'nRec' to an arbitrarily large value can thus be used to retrieve the remaining records in the vdata. C library equivalent : VSread """ # Validate number of records to read vs the current offset. # Return "end of vdata" exception if already at end of vdata # otherwise "clip" the number of records if it exceeds the # number of remaining records in the vdata. n = self._nrecs if self._offset == n: raise HDF4Error("end of vdata reached") if self._offset + nRec > n: nRec = self._offset + nRec - n fields = self._setfields or self._fields nFields = len(fields) fieldList = ','.join(fields) _checkErr('read', _C.VSsetfields(self._id, fieldList), 'error defining fields to read') # Allocate a buffer to store the packed records. bufSize = self.sizeof(fields) * nRec bigBuf = _C.array_byte(bufSize) # Read records nRead = _C.VSread(self._id, bigBuf, nRec, 0) # 0: FULL_INTERLACE _checkErr('read', nRead, 'read error') self._offset += nRec # Allocate an array to store a pointer to the field buffer. fldArr = _C.new_array_voidp(1) # Initialize return value values = [] for numRec in range(nRead): v = [] for numFld in range(nFields): v.append(None) values.append(v) # Unpack each field in turn. for numFld in range(nFields): fld = self.field(fields[numFld]) data_type = fld._type order = fld._order n_values = order * nRead # Allocate a buffer to store the field values. if data_type in [HC.CHAR8, HC.UCHAR8, HC.UINT8]: buf = _C.array_byte(n_values) elif data_type == HC.INT8: buf = _C.array_int8(n_values) elif data_type == HC.INT16: buf = _C.array_int16(n_values) elif data_type == HC.UINT16: buf = _C.array_uint16(n_values) elif data_type == HC.INT32: buf = _C.array_int32(n_values) elif data_type == HC.UINT32: buf = _C.array_uint32(n_values) elif data_type == HC.FLOAT32: buf = _C.array_float32(n_values) elif data_type == HC.FLOAT64: buf = _C.array_float64(n_values) else: raise HDF4Error("read: illegal or unupported type %d" % \ data_type) # Unpack the field values. _C.array_voidp_setitem(fldArr, 0, buf) _checkErr('read', _C.VSfpack(self._id, 1, fieldList, bigBuf, bufSize, nRead, fld._name, fldArr), "cannot execute") # Extract values from the field buffer. k = 0 for numRec in range(nRead): if order == 1: values[numRec][numFld] = buf[k] k += 1 else: # Handle strings specially if data_type == HC.CHAR8: s = '' for i in range(order): v = buf[k] if v != 0: s += chr(v) k += 1 values[numRec][numFld] = s # Return field values as a list else: values[numRec][numFld] = [] for i in range(order): values[numRec][numFld].append(buf[k]) k += 1 del buf return values def write(self, values): """Write records to the vdata. Writing starts at the current record position, which is advanced by the number of records written. Args:: values: 2-level sequence. First level is a sequence of records. A second level gives the sequence of record values. It is mandatory to always write whole records. Thus every record field must appear at the second level. The record values are ordered according the list of field names set in the last call to the setfields() method. The ordre of the complete vdata field set is used if setfields() has not been called. Returns:: number of records written To append to a vdata already holding 'n' records, it is necessary to first move the current record position to 'n-1' with a call to method seek(), then to call method read() for the side effect of advancing the current record position past this last record. Method seekend() does just that. C library equivalent : VSwrite """ nFields = self._nfields # Fields give the order the record values, as defined in the # last call to setfields() fields = self._setfields or self._fields # We must pack values using the effective field order in the vdata fieldList = ','.join(self._fields) # Validate the values argument. if nFields != len(fields): raise HDF4Error("write: must write whole records") if type(values) not in [list, tuple]: raise HDF4Error("write: values must be a sequence") nRec = len(values) for n in range(nRec): rec = values[n] if type(rec) not in [list, tuple]: raise HDF4Error("write: records must be given as sequences") # Make sure each record is complete. if len(rec) != nFields: raise HDF4Error("write: records must specify every field") # Allocate a buffer to store the packed records. bufSize = self._recsize * nRec bigBuf = _C.array_byte(bufSize) # Allocate an array to store a pointer to the field buffer. fldArr = _C.new_array_voidp(1) # Pack each field in turn. for numFld in range(nFields): fld = self.field(fields[numFld]) data_type = fld._type order = fld._order n_values = order * nRec # Allocate a buffer to store the field values. if data_type in [HC.CHAR8, HC.UCHAR8, HC.UINT8]: buf = _C.array_byte(n_values) elif data_type == HC.INT8: buf = _C.array_int8(n_values) elif data_type == HC.INT16: buf = _C.array_int16(n_values) elif data_type == HC.UINT16: buf = _C.array_uint16(n_values) elif data_type == HC.INT32: buf = _C.array_int32(n_values) elif data_type == HC.UINT32: buf = _C.array_uint32(n_values) elif data_type == HC.FLOAT32: buf = _C.array_float32(n_values) elif data_type == HC.FLOAT64: buf = _C.array_float64(n_values) else: raise HDF4Error("write: illegal or unupported type %d" % \ data_type) # Load the field buffer with values. k = 0 for numRec in range(nRec): val = values[numRec][numFld] # Single-valued field if order == 1: buf[k] = val k += 1 # Multi-valued field else: # Handle strings specially. if data_type == HC.CHAR8: if not isinstance(val, str): raise HDF4Error("char fields must be set with strings") n = len(val) for i in range(order): buf[k] = i < n and ord(val[i]) or 0 k += 1 # Should validate field elements ... elif type(val) not in [list, tuple]: raise HDF4Error("multi-values fields must be given as sequences") else: for i in range(order): buf[k] = val[i] k += 1 # Store address of the field buffer in first position # of the field array. Pack the field values. _C.array_voidp_setitem(fldArr, 0, buf) # fldArr[0] = buf _checkErr('write', _C.VSfpack(self._id, 0, fieldList, bigBuf, bufSize, nRec, fld._name, fldArr), "cannot execute") del buf # Write the packed records. n = _C.VSwrite(self._id, bigBuf, nRec, 0) # 0: FULL_INTERLACE _checkErr('write', n, 'cannot execute') self._offset += nRec return n def inquire(self): """Retrieve info about the vdata. Args:: no argument Returns:: 5-element tuple with the following elements: -number of records in the vdata -interlace mode -list of vdata field names -size in bytes of the vdata record -name of the vdata C library equivalent : VSinquire """ status, nRecs, interlace, fldNames, size, vName = \ _C.VSinquire(self._id) _checkErr('inquire', status, "cannot query vdata info") return nRecs, interlace, fldNames.split(','), size, vName def fieldinfo(self): """Retrieve info about all vdata fields. Args:: no argument Returns:: list where each element describes a field of the vdata; each field is described by an 7-element tuple containing the following elements: - field name - field data type (one of HC.xxx constants) - field order - number of attributes attached to the field - field index number - field external size - field internal size C library equivalent : no equivalent """ lst = [] for n in range(self._nfields): fld = self.field(n) lst.append((fld._name, fld._type, fld._order, fld._nattrs, fld._index, fld._esize, fld._isize)) return lst def sizeof(self, fields): """Retrieve the size in bytes of the given fields. Args:: fields sequence of field names to query Returns:: total size of the fields in bytes C library equivalent : VSsizeof """ if type(fields) in [tuple, list]: str = ','.join(fields) else: str = fields n = _C.VSsizeof(self._id, str) _checkErr('sizeof', n, "cannot retrieve field sizes") return n def fexist(self, fields): """Check if a vdata contains a given set of fields. Args:: fields sequence of field names whose presence in the vdata must be checked Returns:: true (1) if the given fields are present false (0) otherwise C library equivalent : VSfexist """ if type(fields) in [tuple, list]: str = ','.join(fields) else: str = fields ret = _C.VSfexist(self._id, str) if ret < 0: return 0 else: return 1 def attr(self, name_or_index): """Create a VDAttr instance representing a vdata attribute. Args:: name_or_index attribute name or index number; if a name is given, the attribute may not exist; in that case, it will be created when the VSAttr instance set() method is called Returns:: VSAttr instance for the attribute. Call the methods of this class to query, read or set the attribute. C library equivalent : no equivalent """ return VDAttr(self, name_or_index, -1) # -1: vdata attribute def findattr(self, name): """Search the vdata for a given attribute. Args:: name attribute name Returns:: if found, VDAttr instance describing the attribute None otherwise C library equivalent : VSfindattr """ try: att = self.attr(name) if att._index is None: att = None except HDF4Error: att = None return att def attrinfo(self): """Return info about all the vdata attributes. Args:: no argument Returns:: dictionary describing each vdata attribute; for each attribute a (name,data) pair is added to the dictionary, where 'data' is a tuple holding: - attribute data type (one of HC.xxx constants) - attribute order - attribute value - attribute size in bytes C library equivalent : no equivalent """ dic = {} for n in range(self._nattrs): att = self.attr(n) name, type, order, size = att.info() dic[name] = (type, order, att.get(), size) return dic def __buildStartCount(self, elem, setitem=0): # Called by __getitem__() and __setitem__() methods # to parse the expression used inside square brackets to # index/slice a vdata. # If 'setitem' is set, the call comes from __setitem__() # We then allow the start value to be past the last record # so as to be able to append to the vdata. # # Return a 2-element tuple: # - tuple of the start indices along the vdata dimensions # - tuple of the count values along the vdata dimensions # a count of -1 indicates that an index, not a slice # was applied on the correcponding dimension. # Make sure the indexing expression does not exceed the # vdata number of dimensions (2). if isinstance(elem, tuple): if len(elem) > 2: raise HDF4Error("illegal indexing expression") else: # Convert single index to sequence elem = [elem] start = [] count = [] shape = [self._nrecs, self._nfields] n = -1 for e in elem: n += 1 # Simple index if isinstance(e, int): is_slice = False if e < 0: e += shape[n] if e < 0 or e >= shape[n]: if e == shape[n] and setitem: pass else: raise HDF4Error("index out of range") beg = e end = e + 1 # Slice index elif isinstance(e, slice): is_slice = True # None or 0 means not specified if e.start: beg = e.start if beg < 0: beg += shape[n] else: beg = 0 # None or maxint means not specified if e.stop and e.stop != sys.maxsize: end = e.stop if end < 0: end += shape[n] else: end = shape[n] # Bug else: raise ValueError("invalid indexing expression") # Clip end index and compute number of elements to get if end > shape[n]: end = shape[n] if beg > end: beg = end if is_slice: cnt = end - beg else: cnt = -1 start.append(beg) count.append(cnt) if n == 0: start.append(0) count.append(shape[1]) return start, count class VDField(object): """The VDField class represents a vdata field. To create a VDField instance, call the field() method of a VD class instance. """ def __init__(self, vdinst, fIndex): # This method should not be called directly by the user program. # To create a VDField instance, obtain a VD class instance and # call its field() method. # Args: # vdinst VD instance to which the field belongs # fIndex field index # # Private attributes: # _vd_inst VD instance to which the field belongs # _idx field index self._vd_inst = vdinst self._idx = fIndex def __getattr__(self, name): """Some field properties can be queried through the following read-only attributes. Their names all start with an "_" to avoid clashes with user-defined attributes. Name Description C library routine ----- ------------------- ----------------- _esize field external size VFfieldesize _index field index number VSfindex _isize field internal size VFfieldisize _name field name VFfieldname _nattrs number of attributes VSfnattrs _order field order VFfieldorder _type field type VFfieldtype """ # Check for a user defined attribute first. att = self.attr(name) if att._index is not None: # Then the attribute exists return att.get() # Check for a predefined attribute. elif name == "_esize": n = _C.VFfieldesize(self._vd_inst._id, self._idx) _checkErr('_esize', n, "execution error") return n elif name == "_index": return self._idx elif name == "_isize": n = _C.VFfieldisize(self._vd_inst._id, self._idx) _checkErr('_isize', n, "execution error") return n elif name == "_name": n = _C.VFfieldname(self._vd_inst._id, self._idx) _checkErr('_name', n, "execution error") return n elif name == "_nattrs": n = _C.VSfnattrs(self._vd_inst._id, self._idx) _checkErr('_nattrs', n, "execution error") return n elif name == "_order": n = _C.VFfieldorder(self._vd_inst._id, self._idx) _checkErr('_order', n, "execution error") return n elif name == "_type": type = _C.VFfieldtype(self._vd_inst._id, self._idx) _checkErr('_type', type, 'cannot retrieve field type') return type raise AttributeError def __setattr__(self, name, value): # Forbid assigning to our predefined attributes if name in ["_esize", "_index", "_isize", "_name", "_nattrs", "_order", "_type"]: raise AttributeError("%s: read-only attribute" % name) # Try to set the attribute. else: _setattr(self, name, value) def attr(self, name_or_index): """Create a VDAttr instance representing a field attribute. Args:: name_or_index attribute name or index number; if a name is specified, the attribute may not exist; in that case, it will be created when the VDAttr instance set() method is called; if an index number is specified, the attribute must exist Returns:: VSAttr instance for the attribute. Call the methods of this class to query, read or set the attribute. C library equivalent : no equivalent """ return VDAttr(self, name_or_index, self._idx) def find(self, name): """Search the field for a given attribute. Args:: name attribute name Returns:: if found, VDAttr instance describing the attribute None otherwise C library equivalent : VSfindattr """ try: att = self.attr(name) if att._index is None: att = None except HDF4Error: att = None return att def attrinfo(self): """Return info about all the field attributes. Args:: no argument Returns:: dictionary describing each vdata attribute; for each attribute a (name,data) pair is added to the dictionary, where 'data' is a tuple holding: - attribute data type (one of HC.xxx constants) - attribute order - attribute value - attribute size in bytes C library equivalent : no equivalent """ dic = {} for n in range(self._nattrs): att = self.attr(n) name, type, order, size = att.info() dic[name] = (type, order, att.get(), size) return dic class VDAttr(object): """The VDAttr class encapsulates methods used to set and query attributes defined at the level either of the vdata or of the vdata field. To create an instance of this class, call the attr() method of a VD (vdata) or VDField (vdata field) instance. """ def __init__(self, obj, name_or_index, fIndex): # This constructor should not be called directly by the user # program. The attr() method of a VD (vdata) or VDField # (vdata field) must be called to instantiate this class. # Args: # obj object instance (VD or VDField) to which the # attribute belongs # name_or_index name or index of the attribute; if a name is # given, an attribute with that name will be # searched, if not found, a new index number will # be generated # fIndex field index, or -1 if the attribute belongs # to the vdata # Private attributes: # _vd_inst VD instance # _vdf_inst VDField instance or None # _index attribute index or None # _name attribute name or None # _fIndex field index, or -1 obj is a VD instance if isinstance(obj, VD): self._vd_inst = obj self._vdf_instance = None self._fIndex = -1 else: self._vd_inst = obj._vd_inst self._vdf_inst = obj self._fIndex = fIndex # Name is given. Attribute may exist or not. if isinstance(name_or_index, type('')): self._name = name_or_index self._index = _C.VSfindattr(self._vd_inst._id, self._fIndex, self._name); if self._index < 0: self._index = None # Index is given. Attribute Must exist. else: self._index = name_or_index status, self._name, data_type, n_values, size = \ _C.VSattrinfo(self._vd_inst._id, self._fIndex, self._index) _checkErr('attr', status, 'non-existent attribute') def get(self): """Retrieve the attribute value. Args:: no argument Returns:: attribute value(s); a list is returned if the attribute is made up of more than one value, except in the case of a string-valued attribute (data type HC.CHAR8) where the values are returned as a string C library equivalent : VSgetattr """ # Make sure th attribute exists. if self._index is None: raise HDF4Error("non existent attribute") # Obtain attribute type and the number of values. status, aName, data_type, n_values, size = \ _C.VSattrinfo(self._vd_inst._id, self._fIndex, self._index) _checkErr('get', status, 'illegal parameters') # Get attribute value. convert = _array_to_ret if data_type == HC.CHAR8: buf = _C.array_byte(n_values) convert = _array_to_str elif data_type in [HC.UCHAR8, HC.UINT8]: buf = _C.array_byte(n_values) elif data_type == HC.INT8: buf = _C.array_int8(n_values) elif data_type == HC.INT16: buf = _C.array_int16(n_values) elif data_type == HC.UINT16: buf = _C.array_uint16(n_values) elif data_type == HC.INT32: buf = _C.array_int32(n_values) elif data_type == HC.UINT32: buf = _C.array_uint32(n_values) elif data_type == HC.FLOAT32: buf = _C.array_float32(n_values) elif data_type == HC.FLOAT64: buf = _C.array_float64(n_values) else: raise HDF4Error("get: attribute index %d has an "\ "illegal or unupported type %d" % \ (self._index, data_type)) status = _C.VSgetattr(self._vd_inst._id, self._fIndex, self._index, buf) _checkErr('get', status, 'illegal attribute ') return convert(buf, n_values) def set(self, data_type, values): """Set the attribute value. Args:: data_type : attribute data type (see constants HC.xxx) values : attribute value(s); specify a list to create a multi-valued attribute; a string valued attribute can be created by setting 'data_type' to HC.CHAR8 and 'values' to the corresponding string If the attribute already exists, it will be updated. However, it is illegal to try to change its data type or its order (number of values). Returns:: None C library equivalent : VSsetattr """ try: n_values = len(values) except: values = [values] n_values = 1 if data_type == HC.CHAR8: buf = _C.array_byte(n_values) # Allow values to be passed as a string. # Noop if a list is passed. values = list(values) for n in range(n_values): if not isinstance(values[n], int): values[n] = ord(values[n]) elif data_type in [HC.UCHAR8, HC.UINT8]: buf = _C.array_byte(n_values) elif data_type == HC.INT8: # SWIG refuses negative values here. We found that if we # pass them as byte values, it will work. buf = _C.array_int8(n_values) values = list(values) for n in range(n_values): v = values[n] if v >= 0: v &= 0x7f else: v = abs(v) & 0x7f if v: v = 256 - v else: v = 128 # -128 in 2s complement values[n] = v elif data_type == HC.INT16: buf = _C.array_int16(n_values) elif data_type == HC.UINT16: buf = _C.array_uint16(n_values) elif data_type == HC.INT32: buf = _C.array_int32(n_values) elif data_type == HC.UINT32: buf = _C.array_uint32(n_values) elif data_type == HC.FLOAT32: buf = _C.array_float32(n_values) elif data_type == HC.FLOAT64: buf = _C.array_float64(n_values) else: raise HDF4Error("set: illegal or unimplemented data_type") for n in range(n_values): buf[n] = values[n] status = _C.VSsetattr(self._vd_inst._id, self._fIndex, self._name, data_type, n_values, buf) _checkErr('attr', status, 'cannot execute') # Update the attribute index self._index = _C.VSfindattr(self._vd_inst._id, self._fIndex, self._name); if self._index < 0: raise HDF4Error("set: error retrieving attribute index") def info(self): """Retrieve info about the attribute. Args:: no argument Returns:: 4-element tuple with the following components: -attribute name -attribute data type (one of HC.xxx constants) -attribute order (number of values) -attribute size in bytes C library equivalent : VSattrinfo """ # Make sure the attribute exists. if self._index is None: raise HDF4Error("non existent attribute") status, name, type, order, size = \ _C.VSattrinfo(self._vd_inst._id, self._fIndex, self._index) _checkErr('info', status, "execution error") return name, type, order, size ########################### # Support functions ########################### def _setattr(obj, name, value): # Called by the __setattr__ method of the VD and VDField objects. # # obj instance on which the attribute is set # name attribute name # value attribute value if isinstance(value, six.string_types): value = value.encode('utf8') # Treat a name starting with and underscore as that of a # standard python instance attribute. if name[0] == '_': obj.__dict__[name] = value return # Treat everything else as an HDF attribute. if type(value) not in [list, tuple]: value = [value] typeList = [] for v in value: t = type(v) # Prohibit mixing numeric types and strings. if t in [int, float] and \ not bytes in typeList: if t not in typeList: typeList.append(t) # Prohibit sequence of strings or a mix of numbers and string. elif t == bytes and not typeList: typeList.append(t) else: typeList = [] break if bytes in typeList: xtype = HC.CHAR8 value = value[0] # double is "stronger" than int elif float in typeList: xtype = HC.FLOAT64 elif int in typeList: xtype = HC.INT32 else: raise HDF4Error("Illegal attribute value") # Assign value try: a = obj.attr(name) a.set(xtype, value) except HDF4Error as msg: raise HDF4Error("cannot set attribute: %s" % msg) def _array_to_ret(buf, nValues): # Convert array 'buf' to a scalar or a list. if nValues == 1: ret = buf[0] else: ret = [] for i in xrange(nValues): ret.append(buf[i]) return ret def _array_to_str(buf, nValues): # Convert array of bytes 'buf' to a string. # Return empty string if there is no value. if nValues == 0: return "" # When there is just one value, _array_to_ret returns a scalar # over which we cannot iterate. if nValues == 1: chrs = [chr(buf[0])] else: chrs = [chr(b) for b in _array_to_ret(buf, nValues)] # Strip NULL at end if chrs[-1] == '\0': del chrs[-1] return ''.join(chrs)