NumericLookup

NumericLookup.py

import numpy as np

class NumericLookup(dict):
    """
    Extends *dict* type to provide a lookup by value(s), including numpy arrays.

    Methods
    -------
    keys_from_value
    first_key_from_value

    References
    ----------
    :cite:`Mansencalc`

    Examples
    --------
    >>> test = NumericLookup(abc=100.001, defg=102.3, hij=123)
    >>> test.first_key_from_value(100)
    'abc'
    >>> tests = NumericLookup(abc=100.001, defg=99.99999999, hij=100.00111)
    >>> sorted(tests.keys_from_value(100))  # noqa
    ['abc', 'defg']

    Notes
    -----
    Stolen from the colour.utilities.Lookup; modified to permit lookups by np arrays
    """
    
    def keys_from_value(self, value, rtol=1e-05, atol=1e-08):
        """
        Gets the keys with given value.

        Parameters
        ----------
        value : object
            Value.

        rtol : float
            The relative tolerance parameter (see Notes).
        atol : float
            The absolute tolerance parameter (see Notes).
        equal_nan : bool
            Whether to compare NaN's as equal.  If True, NaN's in `a` will be
            considered equal to NaN's in `b` in the output array.

        Returns
        -------
        object
            Keys.
        """

        keys = []
        for key, data in self.items():
            try:

                matching = np.allclose(data, value, rtol=rtol, atol=atol)
            except ValueError:
                matching = all((data == value,))

            if matching:
                keys.append(key)

        return keys

    def first_key_from_value(self, value, rtol=1e-05, atol=1e-08):
        """
        Gets the first key with given value.

        Parameters
        ----------
        value : object
            Value.
        rtol : float
            The relative tolerance parameter (see Notes).
        atol : float
            The absolute tolerance parameter (see Notes).
        equal_nan : bool
            Whether to compare NaN's as equal.  If True, NaN's in `a` will be
            considered equal to NaN's in `b` in the output array.

        Returns
        -------
        object
            Key.
        """

        try:
            return self.keys_from_value(value, rtol=rtol, atol=atol)[0]
        except IndexError:
            pass