Source code for neuroconv.datainterfaces.ophys.caiman.caimandatainterface
import warnings
from pydantic import FilePath
from ..basesegmentationextractorinterface import BaseSegmentationExtractorInterface
[docs]
class CaimanSegmentationInterface(BaseSegmentationExtractorInterface):
"""Data interface for CaimanSegmentationExtractor."""
display_name = "CaImAn Segmentation"
associated_suffixes = (".hdf5",)
info = "Interface for CaImAn segmentation data."
[docs]
@classmethod
def get_source_schema(cls) -> dict:
"""
Get the source schema for the CaImAn segmentation interface.
Returns
-------
dict
The schema dictionary containing input parameters and descriptions
for initializing the CaImAn segmentation interface.
"""
source_metadata = super().get_source_schema()
source_metadata["properties"]["file_path"]["description"] = "Path to .hdf5 file."
return source_metadata
def __init__(
self, file_path: FilePath, *args, verbose: bool = False
): # TODO: change to * (keyword only) on or after August 2026
"""
Parameters
----------
file_path : FilePath
Path to .hdf5 file.
verbose : bool, default False
Whether to print progress
"""
# Handle deprecated positional arguments
if args:
parameter_names = [
"verbose",
]
num_positional_args_before_args = 1 # file_path
if len(args) > len(parameter_names):
raise TypeError(
f"__init__() takes at most {len(parameter_names) + num_positional_args_before_args + 1} positional arguments but "
f"{len(args) + num_positional_args_before_args + 1} were given. "
"Note: Positional arguments are deprecated and will be removed on or after August 2026. "
"Please use keyword arguments."
)
positional_values = dict(zip(parameter_names, args))
passed_as_positional = list(positional_values.keys())
warnings.warn(
f"Passing arguments positionally to CaimanSegmentationInterface.__init__() is deprecated "
f"and will be removed on or after August 2026. "
f"The following arguments were passed positionally: {passed_as_positional}. "
"Please use keyword arguments instead.",
FutureWarning,
stacklevel=2,
)
verbose = positional_values.get("verbose", verbose)
super().__init__(file_path=file_path)
self.verbose = verbose