torchio.data.sampler.label.LabelSampler.get_probability_map() - Code Metrics - Inspection of "Refactor image samplers" - fepegar/torchio - Measure and Improve Code Quality continuously with Scrutinizer

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Pull Request — master (#175)

by Fernando

created 2020-05-31 13:53 UTC

LabelSampler.get_probability_map() A

↳ Parent: torchio.data.sampler.label

Complexity

Conditions

Size

Total Lines	11
Code Lines	7

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	2
eloc	7
nop	2
dl	0
loc	11
rs	10
c	0
b	0
f	0

from .weighted import WeightedSampler


class LabelSampler(WeightedSampler):
    r"""Extract random patches containing labeled voxels.

    This iterable dataset yields patches whose center value is greater than 0
    in the :py:attr:`label_name`.

    Args:
        patch_size: Tuple of integers :math:`(d, h, w)` to generate patches
            of size :math:`d \times h \times w`.
            If a single number :math:`n` is provided,
            :math:`d = h = w = n`.
        label_name: Name of the label image in the sample that will be used to
            generate the sampling probability map.
    """
    def __init__(self, patch_size, label_name):
        super().__init__(patch_size, probability_map=label_name)

    def get_probability_map(self, sample):
        """Return binarized image for sampling."""
        if self.probability_map_name in sample:
            data = sample[self.probability_map_name].data > 0.5
        else:
            message = (
                f'Image "{self.probability_map_name}"'
                f' not found in subject sample: {sample}'
            )
            raise KeyError(message)
        return data


1			from .weighted import WeightedSampler
2
3
4			class LabelSampler(WeightedSampler):
5			r"""Extract random patches containing labeled voxels.
6
7			This iterable dataset yields patches whose center value is greater than 0
8			in the :py:attr:`label_name`.
9
10			Args:
11			patch_size: Tuple of integers :math:`(d, h, w)` to generate patches
12			of size :math:`d \times h \times w`.
13			If a single number :math:`n` is provided,
14			:math:`d = h = w = n`.
15			label_name: Name of the label image in the sample that will be used to
16			generate the sampling probability map.
17			"""
18			def __init__(self, patch_size, label_name):
19			super().__init__(patch_size, probability_map=label_name)
20
21			def get_probability_map(self, sample):
22			"""Return binarized image for sampling."""
23			if self.probability_map_name in sample:
24			data = sample[self.probability_map_name].data > 0.5
25			else:
26			message = (
27			f'Image "{self.probability_map_name}"'
28			f' not found in subject sample: {sample}'
29			)
30			raise KeyError(message)
31			return data
32

fepegar / torchio

Pull Request — master (#175)

LabelSampler.get_probability_map() A

Complexity

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