Source code for darfix.io.dataset_io
__authors__ = ["J. Garriga"]
__license__ = "MIT"
__date__ = "12/06/2020"
import json
import numpy
from silx.io import fabioh5
from silx.io.url import DataUrl
from darfix.core.dataset import Data, ImageDataset
from darfix.core.dimension import AcquisitionDims
[docs]def save_to_json(
filename, dataset, original_dataset=None, hi_indices=None, li_indices=None
):
my_dict = {}
my_dict["dir"] = dataset.dir
my_dict["dataset"] = [url.file_path() for url in dataset.get_data().urls]
my_dict["shape"] = dataset.data.shape
my_dict["in_memory"] = dataset.in_memory
if original_dataset is not None:
my_dict["original_dataset"] = [
url.file_path() for url in original_dataset.get_data().urls
]
if hi_indices is not None:
my_dict["hi_indices"] = hi_indices.tolist()
if li_indices is not None:
my_dict["li_indices"] = li_indices.tolist()
if dataset.dims.ndim > 0:
my_dict["dims"] = dataset.dims.to_dict()
with open(filename + ".json", "w") as f:
json.dump(my_dict, f)
[docs]def load_from_json(filename):
hi_indices = li_indices = dims = None
with open(filename + ".json", "r") as f:
distro = json.load(f)
urls = numpy.array(
[DataUrl(file_path=url, scheme="fabio") for url in distro["dataset"]]
)
if "original_dataset" in distro:
original_dataset = distro["original_dataset"]
else:
original_dataset = distro["dataset"]
metadata = []
for filename in original_dataset:
fabio_reader = fabioh5.EdfFabioReader(file_name=filename)
metadata.append(fabio_reader)
fabio_reader.close()
metadata = numpy.array(metadata)
hi_indices = distro["hi_indices"] if "hi_indices" in distro else None
li_indices = distro["li_indices"] if "li_indices" in distro else None
if "dims" in distro:
dims = AcquisitionDims()
dims.from_dict(distro["dims"])
else:
dims = None
data = Data(urls, metadata, distro["in_memory"]).reshape(distro["shape"])
dataset = ImageDataset(
_dir=distro["dir"], data=data, in_memory=distro["in_memory"], dims=dims
)
return dataset, hi_indices, li_indices