File image.py has 800 lines of code (exceeds 250 allowed). Consider refactoring.

Open

import warnings
from collections import Counter
from pathlib import Path
from typing import Any
from typing import Callable

File transform.py has 514 lines of code (exceeds 250 allowed). Consider refactoring.

Open

import copy
import numbers
import warnings
from abc import ABC
from abc import abstractmethod

File random_affine.py has 424 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from numbers import Number
from typing import Optional
from typing import Sequence
from typing import Tuple
from typing import Union

File random_labels_to_image.py has 420 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from typing import List
from typing import Optional
from typing import Sequence
from typing import Tuple

File io.py has 388 lines of code (exceeds 250 allowed). Consider refactoring.

Open

import warnings
from pathlib import Path
from typing import Optional
from typing import Tuple
from typing import Union

File subject.py has 382 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from __future__ import annotations

import copy
import pprint
from typing import TYPE_CHECKING

File utils.py has 362 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from __future__ import annotations

import ast
import gzip
import inspect

File queue.py has 346 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from itertools import islice
from typing import Iterator
from typing import List
from typing import Optional

Image has 31 functions (exceeds 20 allowed). Consider refactoring.

Open

class Image(dict):
    r"""TorchIO image.

    For information about medical image orientation, check out `NiBabel docs`_,
    the `3D Slicer wiki`_, `Graham Wideman's website`_, `FSL docs`_ or

Function apply_transform has a Cognitive Complexity of 24 (exceeds 5 allowed). Consider refactoring.

Open

    def apply_transform(self, subject: Subject) -> Subject:
        original_image = subject.get(self.image_key)

        label_map_image = subject[self.label_key]
        label_map = label_map_image.data

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File random_elastic_deformation.py has 302 lines of code (exceeds 250 allowed). Consider refactoring.

Open

import warnings
from numbers import Number
from typing import Sequence
from typing import Tuple
from typing import Union

Function guess_external_viewer has a Cognitive Complexity of 22 (exceeds 5 allowed). Consider refactoring.

Open

def guess_external_viewer() -> Optional[Path]:
    """Guess the path to an executable that could be used to visualize images.

    Currently, it looks for 1) ITK-SNAP and 2) 3D Slicer. Implemented
    for macOS and Windows.

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Function ensure_4d has a Cognitive Complexity of 20 (exceeds 5 allowed). Consider refactoring.

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def ensure_4d(tensor: TypeData, num_spatial_dims=None) -> torch.Tensor:
    # I wish named tensors were properly supported in PyTorch
    tensor = torch.as_tensor(tensor)
    num_dimensions = tensor.ndim
    if num_dimensions == 4:

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File random_motion.py has 275 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from collections import defaultdict
from typing import Dict
from typing import List
from typing import Sequence
from typing import Tuple

File resample.py has 274 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from collections.abc import Iterable
from numbers import Number
from pathlib import Path
from typing import Optional
from typing import Sized

Function plot_volume has a Cognitive Complexity of 18 (exceeds 5 allowed). Consider refactoring.

Open

def plot_volume(
    image: Image,
    radiological=True,
    channel=-1,  # default to foreground for binary maps
    axes=None,

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File histogram_standardization.py has 262 lines of code (exceeds 250 allowed). Consider refactoring.

Open

from pathlib import Path
from typing import Callable
from typing import Dict
from typing import Iterable
from typing import Optional

Function _get_subjects has a Cognitive Complexity of 17 (exceeds 5 allowed). Consider refactoring.

Open

    def _get_subjects(
        self,
        root_dir: Path,
        train: bool,
        ignore_empty: bool,

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Function get_subjects_from_batch has a Cognitive Complexity of 16 (exceeds 5 allowed). Consider refactoring.

Open

def get_subjects_from_batch(batch: Dict) -> List:
    """Get list of subjects from collated batch.

    Args:
        batch: Dictionary generated by a :class:`tio.SubjectsLoader`

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Function apply_transform has a Cognitive Complexity of 15 (exceeds 5 allowed). Consider refactoring.

Open

    def apply_transform(self, subject: Subject) -> Subject:
        if self.check_shape:
            subject.check_consistent_spatial_shape()
        default_value: float
        for image in self.get_images(subject):

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