def plot_gaussian(self, x=None, unit=None, wrap_at=None, label=None, xlabel=None, show=False, **kwargs)

Plot the gaussian distribution that would result from calling BaseDistribution.to_gaussian with the same arguments.

Note that for distributions in which BaseDistribution.to_gaussian calls BaseDistribution.to_histogram under-the-hood, this could result in slightly different distributions for each call.

Arguments

x (array, optional, default=None): the numpy array at which to sample the value on the x-axis. If unit is not None, the value of x are assumed to be in the original units BaseDistribution.unit, not unit. If not provided or None, x will be based to cover the 99.9% of all distributions (see BaseDistribution.interval) with 1000 points and 10% padding.
unit (astropy.unit, optional, default=None): units to use along the x-axis. Astropy must be installed.
wrap_at (float, None, or False, optional, default=None): value to use for wrapping. See BaseDistribution.wrap. If not provided or None, will use the value from BaseDistribution.wrap_at. Note: wrapping is computed before changing units, so wrap_at must be provided according to BaseDistribution.unit not unit.
label (string, optional, default=None): override the label on the x-axis. If not provided or None, will use BaseDistribution.label. Will only be used if show=True. Unit will automatically be appended. Will be ignored if xlabel is provided.
xlabel (string, optional, default=None): override the label on the x-axis without appending the unit. Will override label.
show (bool, optional, default=True): whether to show the resulting matplotlib figure.
**kwargs: keyword arguments for sigma, N, bins, range will be passed on to BaseDistribution.to_gaussian (must be accepted by the given distribution type). All other keyword arguments will be passed on to Gaussian.plot_pdf on the resulting distribution.

Returns