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Refactor ZarrIO #34

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Refactor ZarrIO #34

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145 changes: 76 additions & 69 deletions linc_convert/modalities/lsm/mosaic.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,21 +23,17 @@
from linc_convert.utils.math import ceildiv
from linc_convert.utils.orientation import center_affine, orientation_to_affine
from linc_convert.utils.zarr import make_compressor

from linc_convert.models.zarr_config import ZarrConfig
mosaic = cyclopts.App(name="mosaic", help_format="markdown")
lsm.command(mosaic)


@mosaic.default
def convert(
inp: str,
out: str = None,
*,
chunk: int = 128,
compressor: str = "blosc",
compressor_opt: str = "{}",
zarr_config: ZarrConfig,
max_load: int = 512,
nii: bool = False,
orientation: str = "coronal",
center: bool = True,
thickness: float | None = None,
Expand Down Expand Up @@ -91,6 +87,12 @@
voxel_size
Voxel size along the X, Y and Z dimension, in micron.
"""
out: str = zarr_config.out
chunk: int = zarr_config.chunk
compressor: str = zarr_config.compressor
compressor_opt: str = zarr_config.compressor_opt
print(compressor_opt, type(compressor_opt))
nii: bool = zarr_config.nii
if isinstance(compressor_opt, str):
compressor_opt = ast.literal_eval(compressor_opt)

Expand Down Expand Up @@ -242,69 +244,74 @@

# build pyramid using median windows
level = 0
while any(x > 1 for x in omz[str(level)].shape[-3:]):
prev_array = omz[str(level)]
prev_shape = prev_array.shape[-3:]
level += 1

new_shape = list(map(lambda x: max(1, x // 2), prev_shape))
if all(x < chunk for x in new_shape):
break
print("Compute level", level, "with shape", new_shape)
omz.create_dataset(str(level), shape=[nchannels, *new_shape], **opt)
new_array = omz[str(level)]

nz, ny, nx = prev_array.shape[-3:]
ncz = ceildiv(nz, max_load)
ncy = ceildiv(ny, max_load)
ncx = ceildiv(nx, max_load)

for cz in range(ncz):
for cy in range(ncy):
for cx in range(ncx):
print(f"chunk ({cz}, {cy}, {cx}) / ({ncz}, {ncy}, {ncx})", end="\r")

dat = prev_array[
...,
cz * max_load : (cz + 1) * max_load,
cy * max_load : (cy + 1) * max_load,
cx * max_load : (cx + 1) * max_load,
]
crop = [0 if x == 1 else x % 2 for x in dat.shape[-3:]]
slicer = [slice(-1) if x else slice(None) for x in crop]
dat = dat[(Ellipsis, *slicer)]
pz, py, px = dat.shape[-3:]

dat = dat.reshape(
[
nchannels,
max(pz // 2, 1),
min(pz, 2),
max(py // 2, 1),
min(py, 2),
max(px // 2, 1),
min(px, 2),
]
)
dat = dat.transpose([0, 1, 3, 5, 2, 4, 6])
dat = dat.reshape(
[
nchannels,
max(pz // 2, 1),
max(py // 2, 1),
max(px // 2, 1),
-1,
]
)
dat = np.median(dat, -1)

new_array[
...,
cz * max_load // 2 : (cz + 1) * max_load // 2,
cy * max_load // 2 : (cy + 1) * max_load // 2,
cx * max_load // 2 : (cx + 1) * max_load // 2,
] = dat

# while any(x > 1 for x in omz[str(level)].shape[-3:]):
# prev_array = omz[str(level)]
# prev_shape = prev_array.shape[-3:]
# level += 1

# new_shape = list(map(lambda x: max(1, x // 2), prev_shape))
# if all(x < chunk for x in new_shape):
# break
# print("Compute level", level, "with shape", new_shape)
# omz.create_dataset(str(level), shape=[nchannels, *new_shape], **opt)
# new_array = omz[str(level)]

# nz, ny, nx = prev_array.shape[-3:]
# ncz = ceildiv(nz, max_load)
# ncy = ceildiv(ny, max_load)
# ncx = ceildiv(nx, max_load)

# for cz in range(ncz):
# for cy in range(ncy):
# for cx in range(ncx):
# print(f"chunk ({cz}, {cy}, {cx}) / ({ncz}, {ncy}, {ncx})", end="\r")

Check failure on line 267 in linc_convert/modalities/lsm/mosaic.py

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Ruff (E501) 

linc_convert/modalities/lsm/mosaic.py:267:89: E501 Line too long (90 > 88)

# dat = prev_array[
# ...,
# cz * max_load : (cz + 1) * max_load,
# cy * max_load : (cy + 1) * max_load,
# cx * max_load : (cx + 1) * max_load,
# ]
# crop = [0 if x == 1 else x % 2 for x in dat.shape[-3:]]
# slicer = [slice(-1) if x else slice(None) for x in crop]
# dat = dat[(Ellipsis, *slicer)]
# pz, py, px = dat.shape[-3:]

# dat = dat.reshape(
# [
# nchannels,
# max(pz // 2, 1),
# min(pz, 2),
# max(py // 2, 1),
# min(py, 2),
# max(px // 2, 1),
# min(px, 2),
# ]
# )
# dat = dat.transpose([0, 1, 3, 5, 2, 4, 6])
# dat = dat.reshape(
# [
# nchannels,
# max(pz // 2, 1),
# max(py // 2, 1),
# max(px // 2, 1),
# -1,
# ]
# )
# dat = np.median(dat, -1)

# new_array[
# ...,
# cz * max_load // 2 : (cz + 1) * max_load // 2,
# cy * max_load // 2 : (cy + 1) * max_load // 2,
# cx * max_load // 2 : (cx + 1) * max_load // 2,
# ] = dat
#
nxyz = np.array(fullshape)
default_layers = int(np.ceil(np.log2(np.max(nxyz / chunk)))) + 1
nblevel = max(default_layers, 1)
from linc_convert.modalities.psoct._utils import generate_pyramid
generate_pyramid(omz, levels=nblevel-1,ndim = len(fullshape)+1)
print("")
nblevel = level

Expand Down
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