"""
Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""

import argparse
import pathlib


class Args(argparse.ArgumentParser):
    """
    Defines global default arguments.
    """

    def __init__(self, **overrides):
        """
        Args:
            **overrides (dict, optional): Keyword arguments used to override default argument values
        """

        super().__init__(formatter_class=argparse.ArgumentDefaultsHelpFormatter)

        self.add_argument('--seed', default=42, type=int, help='Seed for random number generators')
        self.add_argument('--resolution', default=320, type=int, help='Resolution of images')

        # Data parameters
        self.add_argument('--challenge', choices=['singlecoil', 'multicoil'], required=True,
                          help='Which challenge')
        self.add_argument('--data-path', type=pathlib.Path, required=True,
                          help='Path to the dataset')
        self.add_argument('--sample-rate', type=float, default=1.,
                          help='Fraction of total volumes to include')

        # Mask parameters
        self.add_argument('--mask-type', choices=['random', 'equispaced'], default='random',
                          help='The type of mask function to use')
        self.add_argument('--accelerations', nargs='+', default=[4, 8], type=int,
                          help='Ratio of k-space columns to be sampled. If multiple values are '
                               'provided, then one of those is chosen uniformly at random for '
                               'each volume.')
        self.add_argument('--center-fractions', nargs='+', default=[0.08, 0.04], type=float,
                          help='Fraction of low-frequency k-space columns to be sampled. Should '
                               'have the same length as accelerations')

        # Override defaults with passed overrides
        self.set_defaults(**overrides)

25713b8da5e3f485b4d6040bed5c708d22a90402
<mask token>


class Args(argparse.ArgumentParser):
    <mask token>
    <mask token>

<mask token>


class Args(argparse.ArgumentParser):
    <mask token>

    def __init__(self, **overrides):
        """
        Args:
            **overrides (dict, optional): Keyword arguments used to override default argument values
        """
        super().__init__(formatter_class=argparse.ArgumentDefaultsHelpFormatter
            )
        self.add_argument('--seed', default=42, type=int, help=
            'Seed for random number generators')
        self.add_argument('--resolution', default=320, type=int, help=
            'Resolution of images')
        self.add_argument('--challenge', choices=['singlecoil', 'multicoil'
            ], required=True, help='Which challenge')
        self.add_argument('--data-path', type=pathlib.Path, required=True,
            help='Path to the dataset')
        self.add_argument('--sample-rate', type=float, default=1.0, help=
            'Fraction of total volumes to include')
        self.add_argument('--mask-type', choices=['random', 'equispaced'],
            default='random', help='The type of mask function to use')
        self.add_argument('--accelerations', nargs='+', default=[4, 8],
            type=int, help=
            'Ratio of k-space columns to be sampled. If multiple values are provided, then one of those is chosen uniformly at random for each volume.'
            )
        self.add_argument('--center-fractions', nargs='+', default=[0.08, 
            0.04], type=float, help=
            'Fraction of low-frequency k-space columns to be sampled. Should have the same length as accelerations'
            )
        self.set_defaults(**overrides)

<mask token>


class Args(argparse.ArgumentParser):
    """
    Defines global default arguments.
    """

    def __init__(self, **overrides):
        """
        Args:
            **overrides (dict, optional): Keyword arguments used to override default argument values
        """
        super().__init__(formatter_class=argparse.ArgumentDefaultsHelpFormatter
            )
        self.add_argument('--seed', default=42, type=int, help=
            'Seed for random number generators')
        self.add_argument('--resolution', default=320, type=int, help=
            'Resolution of images')
        self.add_argument('--challenge', choices=['singlecoil', 'multicoil'
            ], required=True, help='Which challenge')
        self.add_argument('--data-path', type=pathlib.Path, required=True,
            help='Path to the dataset')
        self.add_argument('--sample-rate', type=float, default=1.0, help=
            'Fraction of total volumes to include')
        self.add_argument('--mask-type', choices=['random', 'equispaced'],
            default='random', help='The type of mask function to use')
        self.add_argument('--accelerations', nargs='+', default=[4, 8],
            type=int, help=
            'Ratio of k-space columns to be sampled. If multiple values are provided, then one of those is chosen uniformly at random for each volume.'
            )
        self.add_argument('--center-fractions', nargs='+', default=[0.08, 
            0.04], type=float, help=
            'Fraction of low-frequency k-space columns to be sampled. Should have the same length as accelerations'
            )
        self.set_defaults(**overrides)

<mask token>
import argparse
import pathlib


class Args(argparse.ArgumentParser):
    """
    Defines global default arguments.
    """

    def __init__(self, **overrides):
        """
        Args:
            **overrides (dict, optional): Keyword arguments used to override default argument values
        """
        super().__init__(formatter_class=argparse.ArgumentDefaultsHelpFormatter
            )
        self.add_argument('--seed', default=42, type=int, help=
            'Seed for random number generators')
        self.add_argument('--resolution', default=320, type=int, help=
            'Resolution of images')
        self.add_argument('--challenge', choices=['singlecoil', 'multicoil'
            ], required=True, help='Which challenge')
        self.add_argument('--data-path', type=pathlib.Path, required=True,
            help='Path to the dataset')
        self.add_argument('--sample-rate', type=float, default=1.0, help=
            'Fraction of total volumes to include')
        self.add_argument('--mask-type', choices=['random', 'equispaced'],
            default='random', help='The type of mask function to use')
        self.add_argument('--accelerations', nargs='+', default=[4, 8],
            type=int, help=
            'Ratio of k-space columns to be sampled. If multiple values are provided, then one of those is chosen uniformly at random for each volume.'
            )
        self.add_argument('--center-fractions', nargs='+', default=[0.08, 
            0.04], type=float, help=
            'Fraction of low-frequency k-space columns to be sampled. Should have the same length as accelerations'
            )
        self.set_defaults(**overrides)

"""
Copyright (c) Facebook, Inc. and its affiliates.

This source code is licensed under the MIT license found in the
LICENSE file in the root directory of this source tree.
"""

import argparse
import pathlib


class Args(argparse.ArgumentParser):
    """
    Defines global default arguments.
    """

    def __init__(self, **overrides):
        """
        Args:
            **overrides (dict, optional): Keyword arguments used to override default argument values
        """

        super().__init__(formatter_class=argparse.ArgumentDefaultsHelpFormatter)

        self.add_argument('--seed', default=42, type=int, help='Seed for random number generators')
        self.add_argument('--resolution', default=320, type=int, help='Resolution of images')

        # Data parameters
        self.add_argument('--challenge', choices=['singlecoil', 'multicoil'], required=True,
                          help='Which challenge')
        self.add_argument('--data-path', type=pathlib.Path, required=True,
                          help='Path to the dataset')
        self.add_argument('--sample-rate', type=float, default=1.,
                          help='Fraction of total volumes to include')

        # Mask parameters
        self.add_argument('--mask-type', choices=['random', 'equispaced'], default='random',
                          help='The type of mask function to use')
        self.add_argument('--accelerations', nargs='+', default=[4, 8], type=int,
                          help='Ratio of k-space columns to be sampled. If multiple values are '
                               'provided, then one of those is chosen uniformly at random for '
                               'each volume.')
        self.add_argument('--center-fractions', nargs='+', default=[0.08, 0.04], type=float,
                          help='Fraction of low-frequency k-space columns to be sampled. Should '
                               'have the same length as accelerations')

        # Override defaults with passed overrides
        self.set_defaults(**overrides)
