Fix ZFPY contiguous array error when used in Zarr

[tasansal]

Fixes #812

With Zarr v3 and using zarr.codecs.ZFPY as serializer, the ZFP compressor logic in numcodecs complains that it is not F-order data. The chunk data neither C/F contiguous when it is a sliced view of an existing array. I traced it down to the logic here, and this PR addresses the issue.

numcodecs/numcodecs/zfpy.py

Lines 80 to 87 in e0ddee6

	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)

By making the check more explicit and applying np.ascontiguous after ensuring it not F-order, the issue goes away.

---

Reproducer

import numpy as np
import asyncio
import zarr
from zarr.storage import MemoryStore
from zarr import create_array
from zarr.codecs import numcodecs

# fixed accuracy
zfp = numcodecs.ZFPY(mode=4, tolerance=0.001)
store = MemoryStore()

zfp_arr = create_array(
    store,
    shape=(100, 100, 100),
    chunks=(50, 50, 100),
    dtype="float32",
    serializer=zfp,
    compressors=None
)

rng = np.random.default_rng()
data = rng.random(zfp_arr.shape)
zfp_arr[:] = data

Raises:

ValueError: The zfp codec does not support F order arrays. Your arrays flags were   C_CONTIGUOUS : False
  F_CONTIGUOUS : False
  OWNDATA : False
  WRITEABLE : True
  ALIGNED : True
  WRITEBACKIFCOPY : False
.

If we look at the chunk slices' numpy flags:

>>> data[:50, :50, :].flags.c_contiguous
False
>>> data[:50, 50:, :].flags.c_contiguous
False
>>> data[50:, 50:, :].flags.c_contiguous
False
>>> data[50:, :50, :].flags.c_contiguous
False

TODO:

• Unit tests and/or doctests in docstrings
• Tests pass locally
• Docstrings and API docs for any new/modified user-facing classes and functions
• Changes documented in docs/release.rst
• Docs build locally
• GitHub Actions CI passes
• Test coverage to 100% (Codecov passes)