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# AsymmetricPercentileInterval

class astropy.visualization.AsymmetricPercentileInterval(lower_percentile=None, upper_percentile=None, n_samples=None)

  Bases: `BaseInterval`

  Interval based on a keeping a specified fraction of pixels (can be asymmetric).

  Parameters:
    lower_percentile `python:float` or `python:None`

      The lower percentile below which to ignore pixels. If None, then defaults to 0.

    upper_percentile `python:float` or `python:None`

      The upper percentile above which to ignore pixels. If None, then defaults to 100.

    n_samples `python:int`, optional

      Maximum number of values to use. If this is specified, and there are more values in the dataset as this, then values are randomly sampled from the array (with replacement).

  Methods Summary

  `__call__`(values[, clip, out]) | Transform values using this interval.
  `get_limits`(values) | Return the minimum and maximum value in the interval based on the values provided.

  Methods Documentation

  __call__(values, clip=True, out=None)

    Transform values using this interval.

    The `vmin` and `vmax` values are determined by the `get_limits` method.

    The following transformation is then applied to the values:

    \[{\rm result} = \frac{{\rm values} - v_{\rm min}} {v_{\rm max} - v_{\rm min}}\]

    If `clip` is `True` (default), the result is then clipped to the [0:1] range.

    Parameters:
      values numpy:array_like

        The input values.

      clip bool, optional

        If `True` (default), values outside the [0:1] range are clipped to the [0:1] range.

      out `ndarray`, optional

        If specified, the output values will be placed in this array (typically used for in-place calculations).

    Returns:
      result `ndarray`

        The transformed values.

  get_limits(values)

    Return the minimum and maximum value in the interval based on the values provided.

    Parameters:
      values `ndarray`

        The image values.

    Returns:
      vmin, vmax `python:float`

        The mininium and maximum image value in the interval.