# Source code for tables.filters

    """Functionality related with filters in a PyTables file."""

    import warnings
    import numpy as np

    from . import utilsextension, blosc_compressor_list, blosc_compcode_to_compname
    from .exceptions import FiltersWarning
    from packaging.version import Version

    import tables as tb

    blosc_version = Version(tb.which_lib_version("blosc")[1])

    __docformat__ = 'reStructuredText'
    """The format of documentation strings in this module."""

    all_complibs = ['zlib', 'lzo', 'bzip2', 'blosc']
    all_complibs += ['blosc:%s' % cname for cname in blosc_compressor_list()]

    """List of all compression libraries."""

    foreign_complibs = ['szip']
    """List of known but unsupported compression libraries."""

    default_complib = 'zlib'
    """The default compression library."""

    _shuffle_flag = 0x1
    _fletcher32_flag = 0x2
    _rounding_flag = 0x4
    _bitshuffle_flag = 0x8

    class Filters:
        """Container for filter properties.

        This class is meant to serve as a container that keeps information about
        the filter properties associated with the chunked leaves, that is Table,
        CArray, EArray and VLArray.

        Instances of this class can be directly compared for equality.

        Parameters
        ----------
        complevel : int
            Specifies a compression level for data. The allowed
            range is 0-9. A value of 0 (the default) disables
            compression.
        complib : str
            Specifies the compression library to be used. Right now, 'zlib' (the
            default), 'lzo', 'bzip2' and 'blosc' are supported. Additional
            compressors for Blosc like 'blosc:blosclz' ('blosclz' is the default in
            case the additional compressor is not specified), 'blosc:lz4',
            'blosc:lz4hc', 'blosc:snappy', 'blosc:zlib' and 'blosc:zstd' are
            supported too. Specifying a compression library which is not available
            in the system issues a FiltersWarning and sets the library to the
            default one.
        shuffle : bool
            Whether or not to use the *Shuffle* filter in the HDF5
            library. This is normally used to improve the compression
            ratio. A false value disables shuffling and a true one enables
            it. The default value depends on whether compression is
            enabled or not; if compression is enabled, shuffling defaults
            to be enabled, else shuffling is disabled. Shuffling can only
            be used when compression is enabled.
        bitshuffle : bool
            Whether or not to use the *BitShuffle* filter in the Blosc
            library. This is normally used to improve the compression
            ratio. A false value disables bitshuffling and a true one
            enables it. The default value is disabled.
        fletcher32 : bool
            Whether or not to use the
            *Fletcher32* filter in the HDF5 library.
            This is used to add a checksum on each data chunk. A false
            value (the default) disables the checksum.
        least_significant_digit : int
            If specified, data will be truncated (quantized). In conjunction
            with enabling compression, this produces 'lossy', but
            significantly more efficient compression. For example, if
            *least_significant_digit=1*, data will be quantized using
            ``around(scale*data)/scale``, where ``scale = 2**bits``, and
            bits is determined so that a precision of 0.1 is retained (in
            this case bits=4). Default is *None*, or no quantization.

            .. note::

                quantization is only applied if some form of compression is
                enabled

        Examples
        --------

        This is a small example on using the Filters class::

            import numpy as np
            import tables as tb

            fileh = tb.open_file('test5.h5', mode='w')
            atom = Float32Atom()
            filters = Filters(complevel=1, complib='blosc', fletcher32=True)
            arr = fileh.create_earray(fileh.root, 'earray', atom, (0,2),
                                     "A growable array", filters=filters)

            # Append several rows in only one call
            arr.append(np.array([[1., 2.],
                                 [2., 3.],
                                 [3., 4.]], dtype=np.float32))

            # Print information on that enlargeable array
            print("Result Array:")
            print(repr(arr))
            fileh.close()

        This enforces the use of the Blosc library, a compression level of 1 and a
        Fletcher32 checksum filter as well. See the output of this example::

            Result Array:
            /earray (EArray(3, 2), fletcher32, shuffle, blosc(1)) 'A growable array'
            type = float32
            shape = (3, 2)
            itemsize = 4
            nrows = 3
            extdim = 0
            flavor = 'numpy'
            byteorder = 'little'

        .. rubric:: Filters attributes

        .. attribute:: fletcher32

            Whether the *Fletcher32* filter is active or not.

        .. attribute:: complevel

            The compression level (0 disables compression).

        .. attribute:: complib

            The compression filter used (irrelevant when compression is not
            enabled).

        .. attribute:: shuffle

            Whether the *Shuffle* filter is active or not.

        .. attribute:: bitshuffle

            Whether the *BitShuffle* filter is active or not (Blosc only).

        """

        @property
        def shuffle_bitshuffle(self):
            """Encode NoShuffle (0), Shuffle (1) and BitShuffle (2) filters."""
            if (self.shuffle and self.bitshuffle):
                raise ValueError(
                    "Shuffle and BitShuffle cannot be active at the same time")
            if not (self.shuffle or self.bitshuffle):
                return 0
            if self.shuffle:
                return 1
            if self.bitshuffle:
                return 2

        @classmethod
        def _from_leaf(cls, leaf):
            # Get a dictionary with all the filters
            parent = leaf._v_parent
            filters_dict = utilsextension.get_filters(parent._v_objectid,
                                                      leaf._v_name)
            if filters_dict is None:
                filters_dict = {}  # not chunked

            # Keyword arguments are all off
            kwargs = dict(complevel=0, shuffle=False, bitshuffle=False,
                          fletcher32=False, least_significant_digit=None,
                          _new=False)
            for (name, values) in filters_dict.items():
                if name == 'deflate':
                    name = 'zlib'
                if name in all_complibs:
                    kwargs['complib'] = name
                    if name == "blosc":
                        kwargs['complevel'] = values[4]
                        if values[5] == 1:
                            # Shuffle filter is internal to blosc
                            kwargs['shuffle'] = True
                        elif values[5] == 2:
                            # Shuffle filter is internal to blosc
                            kwargs['bitshuffle'] = True
                        # From Blosc 1.3 on, parameter 6 is used for the compressor
                        if len(values) > 6:
                            cname = blosc_compcode_to_compname(values[6])
                            kwargs['complib'] = "blosc:%s" % cname
                    else:
                        kwargs['complevel'] = values[0]
                elif name in foreign_complibs:
                    kwargs['complib'] = name
                    kwargs['complevel'] = 1  # any nonzero value will do
                elif name in ['shuffle', 'fletcher32']:
                    kwargs[name] = True
            return cls(**kwargs)

        @classmethod
        def _unpack(cls, packed):
            """Create a new `Filters` object from a packed version.

            >>> Filters._unpack(0)
            Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None)
            >>> Filters._unpack(0x101)
            Filters(complevel=1, complib='zlib', shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None)
            >>> Filters._unpack(0x30109)
            Filters(complevel=9, complib='zlib', shuffle=True, bitshuffle=False, fletcher32=True, least_significant_digit=None)
            >>> Filters._unpack(0x3010A)
            Traceback (most recent call last):
              ...
            ValueError: compression level must be between 0 and 9
            >>> Filters._unpack(0x1)
            Traceback (most recent call last):
              ...
            ValueError: invalid compression library id: 0

            """

            kwargs = {'_new': False}

            # Byte 0: compression level.
            kwargs['complevel'] = complevel = packed & 0xff
            packed >>= 8

            # Byte 1: compression library id (0 for none).
            if complevel > 0:
                complib_id = int(packed & 0xff)
                if not (0 < complib_id <= len(all_complibs)):
                    raise ValueError("invalid compression library id: %d"
                                     % complib_id)
                kwargs['complib'] = all_complibs[complib_id - 1]
            packed >>= 8

            # Byte 2: parameterless filters.
            kwargs['shuffle'] = packed & _shuffle_flag
            kwargs['bitshuffle'] = packed & _bitshuffle_flag
            kwargs['fletcher32'] = packed & _fletcher32_flag
            has_rounding = packed & _rounding_flag
            packed >>= 8

            # Byte 3: least significant digit.
            if has_rounding:
                kwargs['least_significant_digit'] = np.int8(packed & 0xff)
            else:
                kwargs['least_significant_digit'] = None

            return cls(**kwargs)

        def _pack(self):
            """Pack the `Filters` object into a 64-bit NumPy integer."""

            packed = np.int64(0)

            # Byte 3: least significant digit.
            if self.least_significant_digit is not None:
                # assert isinstance(self.least_significant_digit, numpy.int8)
                packed |= self.least_significant_digit
            packed <<= 8

            # Byte 2: parameterless filters.
            if self.shuffle:
                packed |= _shuffle_flag
            if self.bitshuffle:
                packed |= _bitshuffle_flag
            if self.fletcher32:
                packed |= _fletcher32_flag
            if self.least_significant_digit:
                packed |= _rounding_flag
            packed <<= 8

            # Byte 1: compression library id (0 for none).
            if self.complevel > 0:
                packed |= all_complibs.index(self.complib) + 1
            packed <<= 8

            # Byte 0: compression level.
            packed |= self.complevel

            return packed

        def __init__(self, complevel=0, complib=default_complib,
                     shuffle=True, bitshuffle=False, fletcher32=False,
                     least_significant_digit=None, _new=True):

            if not (0 <= complevel <= 9):
                raise ValueError("compression level must be between 0 and 9")

            if _new and complevel > 0:
                # These checks are not performed when loading filters from disk.
                if complib not in all_complibs:
                    raise ValueError(
                        "compression library ``%s`` is not supported; "
                        "it must be one of: %s"
                        % (complib, ", ".join(all_complibs)))
                if utilsextension.which_lib_version(complib) is None:
                    warnings.warn("compression library ``%s`` is not available; "
                                  "using ``%s`` instead"
                                  % (complib, default_complib), FiltersWarning)
                    complib = default_complib  # always available

            complevel = int(complevel)
            complib = str(complib)
            shuffle = bool(shuffle)
            bitshuffle = bool(bitshuffle)
            fletcher32 = bool(fletcher32)
            if least_significant_digit is not None:
                least_significant_digit = np.int8(least_significant_digit)

            if complevel == 0:
                # Override some inputs when compression is not enabled.
                complib = None  # make it clear there is no compression
                shuffle = False  # shuffling and not compressing makes no sense
                least_significant_digit = None
            elif complib not in all_complibs:
                # Do not try to use a meaningful level for unsupported libs.
                complevel = -1

            self.complevel = complevel
            """The compression level (0 disables compression)."""

            self.complib = complib
            """The compression filter used (irrelevant when compression is
            not enabled).
            """

            self.shuffle = shuffle
            """Whether the *Shuffle* filter is active or not."""

            self.bitshuffle = bitshuffle
            """Whether the *BitShuffle* filter is active or not."""

            if (self.complib and
                    self.bitshuffle and
                    not self.complib.startswith('blosc')):
                raise ValueError("BitShuffle can only be used inside Blosc")

            if self.shuffle and self.bitshuffle:
                # BitShuffle has priority in case both are specified
                self.shuffle = False

            if (self.bitshuffle and
                    blosc_version < tb.req_versions.min_blosc_bitshuffle_version):
                raise ValueError(f"This Blosc library does not have support for "
                                 f"the bitshuffle filter.  Please update to "
                                 f"Blosc >= "
                                 f"{tb.req_versions.min_blosc_bitshuffle_version}")

            self.fletcher32 = fletcher32
            """Whether the *Fletcher32* filter is active or not."""

            self.least_significant_digit = least_significant_digit
            """The least significant digit to which data shall be truncated."""

        def __repr__(self):
            args = []
            if self.complevel >= 0:  # meaningful compression level
                args.append(f'complevel={self.complevel}')
            if self.complevel != 0:  # compression enabled (-1 or > 0)
                args.append(f'complib={self.complib!r}')
            args.append(f'shuffle={self.shuffle}')
            args.append(f'bitshuffle={self.bitshuffle}')
            args.append(f'fletcher32={self.fletcher32}')
            args.append(f'least_significant_digit={self.least_significant_digit}')
            return f'{self.__class__.__name__}({", ".join(args)})'

        def __str__(self):
            return repr(self)

        def __eq__(self, other):
            if not isinstance(other, self.__class__):
                return False
            for attr in self.__dict__:
                if getattr(self, attr) != getattr(other, attr):
                    return False
            return True

        # XXX: API incompatible change for PyTables 3 line
        # Overriding __eq__ blocks inheritance of __hash__ in 3.x
        # def __hash__(self):
        #    return hash((self.__class__, self.complevel, self.complib,
        #                 self.shuffle, self.bitshuffle, self.fletcher32))

        def copy(self, **override):
            """Get a copy of the filters, possibly overriding some arguments.

            Constructor arguments to be overridden must be passed as keyword
            arguments.

            Using this method is recommended over replacing the attributes of an
            instance, since instances of this class may become immutable in the
            future::

                >>> filters1 = Filters()
                >>> filters2 = filters1.copy()
                >>> filters1 == filters2
                True
                >>> filters1 is filters2
                False
                >>> filters3 = filters1.copy(complevel=1) #doctest: +ELLIPSIS
                Traceback (most recent call last):
                ...
                ValueError: compression library ``None`` is not supported...
                >>> filters3 = filters1.copy(complevel=1, complib='zlib')
                >>> print(filters1)
                Filters(complevel=0, shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None)
                >>> print(filters3)
                Filters(complevel=1, complib='zlib', shuffle=False, bitshuffle=False, fletcher32=False, least_significant_digit=None)
                >>> filters1.copy(foobar=42) #doctest: +ELLIPSIS
                Traceback (most recent call last):
                ...
                TypeError: ...__init__() got an unexpected keyword argument 'foobar'

            """

            newargs = self.__dict__.copy()
            newargs.update(override)
            return self.__class__(**newargs)

    def _test():
        """Run ``doctest`` on this module."""

        import doctest
        doctest.testmod()

    if __name__ == '__main__':
        _test()