<commit_before>import numpy as np
import scipy.stats.stats as stat

from laserchicken.feature_extractor.abc import AbstractFeatureExtractor
from laserchicken.keys import point


class MinZFeatureExtractor(AbstractFeatureExtractor):
    """Extracts the maximum value on the z axis."""
    DEFAULT_MIN = float('NaN')

    @classmethod
    def requires(cls):
        return []

    @classmethod
    def provides(cls):
        return ['max_z']

    def extract(self, sourcepc, neighborhood, targetpc, targetindex, volume_description):
        if neighborhood:
            z = sourcepc[point]['z']['data'][neighborhood]
            min_z = np.min(z) if len(z) > 0 else self.DEFAULT_MIN
        else:
            min_z = np.NaN
        return min_z<commit_msg>fix provided name and comment in min_z<commit_after>import numpy as np
import scipy.stats.stats as stat

from laserchicken.feature_extractor.abc import AbstractFeatureExtractor
from laserchicken.keys import point


class MinZFeatureExtractor(AbstractFeatureExtractor):
    """Extracts the minimum value on the z axis."""
    DEFAULT_MIN = float('NaN')

    @classmethod
    def requires(cls):
        return []

    @classmethod
    def provides(cls):
        return ['min_z']

    def extract(self, sourcepc, neighborhood, targetpc, targetindex, volume_description):
        if neighborhood:
            z = sourcepc[point]['z']['data'][neighborhood]
            min_z = np.min(z) if len(z) > 0 else self.DEFAULT_MIN
        else:
            min_z = np.NaN
        return min_z
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{'dir': 'git-commits-cleaned', 'id': '5524210', 'n_tokens_mistral': 441, 'n_tokens_neox': 432, 'n_words': 125}