def init_dataset(self):
data_path = os.path.join(self.test_folder, "data.h5")
data_key = "data"
with open_file(data_path, "a") as f:
f.create_dataset(data_key, data=np.random.rand(*self.shape))
tmp_folder = os.path.join(self.test_folder, "tmp-init")
raw_name = "test-raw"
scales = [[2, 2, 2]]
add_image(data_path, data_key, self.root, self.dataset_name, raw_name,
resolution=(1, 1, 1), chunks=(64, 64, 64), scale_factors=scales,
tmp_folder=tmp_folder, target="local", max_jobs=self.max_jobs)
def init_dataset(self):
data_path = os.path.join(self.test_folder, "data.h5")
data_key = "data"
with open_file(data_path, "a") as f:
f.create_dataset(data_key, data=np.random.rand(*self.shape))
seg_path = os.path.join(self.test_folder, "seg.h5")
with open_file(seg_path, "a") as f:
f.create_dataset(data_key,
data=np.random.randint(0, 100, size=self.shape))
scales = [[2, 2, 2]]
max_jobs = min(4, mp.cpu_count())
tmp_folder = os.path.join(self.test_folder, "tmp-init-raw")
mobie.add_image(data_path,
data_key,
self.root,
self.dataset_name,
self.raw_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
tmp_folder = os.path.join(self.test_folder, "tmp-init-seg")
mobie.add_segmentation(seg_path,
data_key,
self.root,
self.dataset_name,
self.seg_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
display_settings = [
mobie.metadata.get_image_display("image-group-0", [self.raw_name]),
mobie.metadata.get_segmentation_display("segmentation-group-1",
[self.seg_name]),
]
source_transforms = [
mobie.metadata.get_affine_source_transform(
[self.raw_name, self.seg_name], np.random.rand(12))
]
mobie.create_view(os.path.join(self.root, self.dataset_name),
"my-view", [[self.raw_name], [self.seg_name]],
display_settings=display_settings,
source_transforms=source_transforms)
def test_add_image_with_dataset(self):
self.init_dataset()
dataset_folder = os.path.join(self.root, self.dataset_name)
im_name = "extra-im"
tmp_folder = os.path.join(self.test_folder, "tmp-im")
scales = [[2, 2, 2]]
add_image(self.im_path, self.im_key,
self.root, self.dataset_name, im_name,
resolution=(1, 1, 1), scale_factors=scales,
chunks=(64, 64, 64), tmp_folder=tmp_folder,
target="local", max_jobs=self.max_jobs)
self.check_data(dataset_folder, im_name)
def test_init_from_tif(self):
shape = (32, 128, 128)
im_folder = os.path.join(self.test_folder, "im-stack")
self.make_tif_data(im_folder, shape)
dataset_name = "test"
raw_name = "test-raw"
scales = [[1, 2, 2], [1, 2, 2], [2, 2, 2]]
add_image(im_folder, "*.tif", self.root, dataset_name, raw_name,
resolution=(0.25, 1, 1), chunks=(16, 64, 64),
scale_factors=scales, tmp_folder=self.tmp_folder,
target="local", max_jobs=self.max_jobs)
self.check_dataset(os.path.join(self.root, dataset_name), shape, raw_name)
def init_h5_dataset(
self, dataset_name, raw_name, shape, file_format="bdv.n5", func=None, int_to_uint=False
):
data_path = os.path.join(self.test_folder, "data.h5")
data_key = "data"
self.make_hdf5_data(data_path, data_key, shape, func)
n_jobs = 1 if file_format == "bdv.hdf5" else self.max_jobs
scales = [[2, 2, 2], [2, 2, 2], [2, 2, 2]]
add_image(data_path, data_key, self.root, dataset_name, raw_name,
resolution=(1, 1, 1), chunks=(32, 32, 32),
scale_factors=scales,
tmp_folder=self.tmp_folder,
file_format=file_format,
target="local", max_jobs=n_jobs,
int_to_uint=int_to_uint)
def init_dataset(self):
data_path = os.path.join(self.test_folder, 'data.h5')
data_key = 'data'
with open_file(data_path, 'a') as f:
f.create_dataset(data_key, data=np.random.rand(*self.shape))
tmp_folder = os.path.join(self.test_folder, 'tmp-init')
raw_name = 'test-raw'
scales = [[2, 2, 2]]
add_image(data_path,
data_key,
self.root,
self.dataset_name,
raw_name,
resolution=(1, 1, 1),
chunks=(64, 64, 64),
scale_factors=scales,
tmp_folder=tmp_folder)
def setUp(self):
os.makedirs(self.tmp_folder, exist_ok=True)
data_path = os.path.join(self.tmp_folder, "data.h5")
data_key = "data"
shape = (64, 64, 64)
with open_file(data_path, "a") as f:
f.create_dataset(data_key, data=np.random.rand(*shape))
scales = [[2, 2, 2]]
max_jobs = min(4, mp.cpu_count())
tmp_folder = os.path.join(self.tmp_folder, "tmp-init-raw")
mobie.add_image(data_path,
data_key,
self.data_folder,
"test-ds",
"raw",
resolution=(1, 1, 1),
chunks=(32, 32, 32),
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
def init_ds(self):
import h5py
from mobie import add_image
os.makedirs(self.root, exist_ok=True)
path = os.path.join(self.root, "data.h5")
with h5py.File(path, "w") as f:
f.create_dataset("data", data=np.random.rand(2, 64, 64))
sources = []
for ii in range(4):
im_name = f"image-{ii}"
add_image(path,
"data",
self.root,
"ds",
im_name,
resolution=(1, 1, 1),
scale_factors=[[2, 2, 2]],
chunks=(1, 32, 32),
tmp_folder=os.path.join(self.root, f"tmp-{ii}"),
max_jobs=min(4, multiprocessing.cpu_count()))
sources.append(im_name)
return sources
def setUp(self):
os.makedirs(self.root)
in_key = "data"
resolution = (1.0, 1.0, 1.0)
scale_factors = [[2, 2, 2]]
chunks = (32, 32, 32)
max_jobs = min(4, mp.cpu_count())
for view_id in range(self.n_views):
view_name = f"view-{view_id}"
in_path = f"{self.root}/data-{view_id}.h5"
with h5py.File(in_path, "w") as f:
f.create_dataset(in_key, data=np.random.rand(64, 64, 64))
tmp_folder = os.path.join(self.tmp_root, f"view-{view_id}")
mobie.add_image(in_path,
in_key,
self.root,
self.ds_name,
view_name,
resolution,
scale_factors,
chunks,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
input_file = os.path.join(example_input_data, 'em_overview.tif')
# This is the name that will be given to the image source in mobie.
raw_name = 'em-raw'
unit = 'nanometer'
resolution = (1., 10., 10.)
chunks = (1, 512, 512)
scale_factors = 4 * [[1, 2, 2]]
mobie.add_image(
input_path=input_file,
input_key='', # the input is a single tif image, so we leave input_key blank
root=mobie_project_folder,
dataset_name=dataset_name,
image_name=raw_name,
resolution=resolution,
chunks=chunks,
scale_factors=scale_factors,
is_default_dataset=True, # mark this dataset as the default dataset that will be loaded by mobie
target=target,
max_jobs=max_jobs,
unit=unit
)
tomo_names = ['27_tomogram.tif', '29_tomogram.tif']
unit = 'nanometer'
resolution = [5., 5., 5.]
chunks = (32, 128, 128)
scale_factors = [[1, 2, 2], [1, 2, 2],
[1, 2, 2], [1, 2, 2],
[2, 2, 2]]
def init_dataset(self):
data_path = os.path.join(self.test_folder, "data.h5")
data_key = "data"
with open_file(data_path, "a") as f:
f.create_dataset(data_key, data=np.random.rand(*self.shape))
seg_path = os.path.join(self.test_folder, "seg.h5")
with open_file(seg_path, "a") as f:
f.create_dataset(data_key,
data=np.random.randint(0, 100, size=self.shape))
scales = [[2, 2, 2]]
max_jobs = min(4, mp.cpu_count())
tmp_folder = os.path.join(self.test_folder, "tmp-init-raw")
mobie.add_image(data_path,
data_key,
self.root,
self.dataset_name,
self.raw_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
tmp_folder = os.path.join(self.test_folder, "tmp-init-extra")
mobie.add_image(data_path,
data_key,
self.root,
self.dataset_name,
self.extra_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
tmp_folder = os.path.join(self.test_folder, "tmp-init-seg")
mobie.add_segmentation(seg_path,
data_key,
self.root,
self.dataset_name,
self.seg_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
tmp_folder = os.path.join(self.test_folder, "tmp-init-extra_seg")
mobie.add_segmentation(seg_path,
data_key,
self.root,
self.dataset_name,
self.extra_seg_name,
resolution=(1, 1, 1),
chunks=self.chunks,
scale_factors=scales,
tmp_folder=tmp_folder,
max_jobs=max_jobs)
