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