# -*- coding: utf-8 -*-
__author__ = """John Kirkham"""
__email__ = "kirkhamj@janelia.hhmi.org"
import itertools
import numbers
import warnings
import dask
import dask.array
import dask.delayed
import numpy
import pims
from . import _utils
[docs]def imread(fname, nframes=1, *, arraytype="numpy"):
"""
Read image data into a Dask Array.
Provides a simple, fast mechanism to ingest image data into a
Dask Array.
Parameters
----------
fname : str
A glob like string that may match one or multiple filenames.
nframes : int, optional
Number of the frames to include in each chunk (default: 1).
arraytype : str, optional
Array type for dask chunks. Available options: "numpy", "cupy".
Returns
-------
array : dask.array.Array
A Dask Array representing the contents of all image files.
"""
if not isinstance(nframes, numbers.Integral):
raise ValueError("`nframes` must be an integer.")
if (nframes != -1) and not (nframes > 0):
raise ValueError("`nframes` must be greater than zero.")
if arraytype == "numpy":
arrayfunc = numpy.asanyarray
elif arraytype == "cupy": # pragma: no cover
import cupy
arrayfunc = cupy.asanyarray
with pims.open(fname) as imgs:
shape = (len(imgs),) + imgs.frame_shape
dtype = numpy.dtype(imgs.pixel_type)
if nframes == -1:
nframes = shape[0]
if nframes > shape[0]:
warnings.warn(
"`nframes` larger than number of frames in file."
" Will truncate to number of frames in file.",
RuntimeWarning
)
elif shape[0] % nframes != 0:
warnings.warn(
"`nframes` does not nicely divide number of frames in file."
" Last chunk will contain the remainder.",
RuntimeWarning
)
lower_iter, upper_iter = itertools.tee(itertools.chain(
range(0, shape[0], nframes),
[shape[0]]
))
next(upper_iter)
a = []
for i, j in zip(lower_iter, upper_iter):
a.append(dask.array.from_delayed(
dask.delayed(_utils._read_frame)(fname, slice(i, j),
arrayfunc=arrayfunc),
(j - i,) + shape[1:],
dtype,
meta=arrayfunc([])
))
a = dask.array.concatenate(a)
return a