Source code for numcodecs.zfpy

from contextlib import suppress
from importlib.metadata import PackageNotFoundError, version
import warnings

_zfpy = None

_zfpy_version: tuple = ()
with suppress(PackageNotFoundError):
    _zfpy_version = tuple(map(int, version("zfpy").split(".")))

if _zfpy_version:
    # Check NumPy version
    _numpy_version: tuple = tuple(map(int, version("numpy").split('.')))
    if _numpy_version >= (2, 0, 0) and _zfpy_version <= (1, 0, 1):  # pragma: no cover
        _zfpy_version = ()
        warnings.warn(
            "NumPy version >= 2.0.0 detected. The zfpy library is incompatible with this version of NumPy. "
            "Please downgrade to NumPy < 2.0.0 or wait for an update from zfpy.",
            UserWarning,
        )
    else:
        with suppress(ImportError):
            import zfpy as _zfpy

if _zfpy:
    from .abc import Codec
    from .compat import ndarray_copy, ensure_contiguous_ndarray, ensure_bytes
    import numpy as np

    # noinspection PyShadowingBuiltins
[docs] class ZFPY(Codec): """Codec providing compression using zfpy via the Python standard library. Parameters ---------- mode : integer One of the zfpy mode choice, e.g., ``zfpy.mode_fixed_accuracy``. tolerance : double, optional A double-precision number, specifying the compression accuracy needed. rate : double, optional A double-precision number, specifying the compression rate needed. precision : int, optional A integer number, specifying the compression precision needed. """ codec_id = "zfpy" def __init__( self, mode=_zfpy.mode_fixed_accuracy, tolerance=-1, rate=-1, precision=-1, compression_kwargs=None, ): self.mode = mode if mode == _zfpy.mode_fixed_accuracy: self.compression_kwargs = {"tolerance": tolerance} elif mode == _zfpy.mode_fixed_rate: self.compression_kwargs = {"rate": rate} elif mode == _zfpy.mode_fixed_precision: self.compression_kwargs = {"precision": precision} self.tolerance = tolerance self.rate = rate self.precision = precision
[docs] def encode(self, buf): # not flatten c-order array and raise exception for f-order array if not isinstance(buf, np.ndarray): raise TypeError( "The zfp codec does not support none numpy arrays." f" Your buffers were {type(buf)}." ) if buf.flags.c_contiguous: flatten = False else: raise ValueError( "The zfp codec does not support F order arrays. " f"Your arrays flags were {buf.flags}." ) buf = ensure_contiguous_ndarray(buf, flatten=flatten) # do compression return _zfpy.compress_numpy(buf, write_header=True, **self.compression_kwargs)
[docs] def decode(self, buf, out=None): # normalise inputs buf = ensure_bytes(buf) if out is not None: out = ensure_contiguous_ndarray(out) # do decompression dec = _zfpy.decompress_numpy(buf) # handle destination if out is not None: return ndarray_copy(dec, out) else: return dec
def __repr__(self): r = "%s(mode=%r, tolerance=%s, rate=%s, precision=%s)" % ( type(self).__name__, self.mode, self.tolerance, self.rate, self.precision, ) return r