text: """
  ========================================================
  Finite Mixture Model Image Analysis (:mod:`mango.fmm`)
  ========================================================
  
  .. currentmodule:: mango.fmm
  
  Statistical image analysis module.
  
  Statistical Tests
  =================
  
  .. autosummary::
     :toctree: generated/
  
     gaussian_pvalue - Generates a Normal-Distribution P-value image.
     chi_squared_pvalue - Generates a Chi-Squared-Distribution P-value image.
     non_central_chi_squared_pvalue - Generates a Non-Central-Chi-Squared-Distribution P-value image.
     generalised_chi_squared_pvalue - Generates a Non-Central-Chi-Squared-Distribution P-value image.
     PValueSidednessType - Used to specify whether *two-sided* or *one-sided* P-values are generated.
     gchisqrd - Generalised Chi-Squared distribution factory function.
     
     
  Classes
  =======
  
  .. autosummary::
     :toctree: generated/
  
     GenChiSqrd - Generalised Chi-Squared distribution.
  """
  import mango
  import sys
  if sys.platform.startswith('linux'):
      import DLFCN as dl
      _flags = sys.getdlopenflags()
      sys.setdlopenflags(dl.RTLD_NOW|dl.RTLD_GLOBAL)
      from . import _mango_open_fmm
      sys.setdlopenflags(_flags)
  else:
      from . import _mango_open_fmm
  
  from ._mango_open_fmm import *
  from mango.utils import ModuleObjectFactory as _ModuleObjectFactory
  
  _factory = _ModuleObjectFactory(_mango_open_fmm)
  
  # Sphinx doco class only.
  class GenChiSqrd(_mango_open_fmm._gchisqrd_float64):
      __doc__ = _mango_open_fmm._gchisqrd_float64.__doc__
  
  
  def gchisqrd(coeffs, noncentralities, dtype="float64"):
      """
      Returns Generalised Chi-Squared distribution object (:obj:`GenChiSqrd`).
      
      :type coeffs: :obj:`numpy.array`
      :param coeffs: :samp:`(n,)` shaped array of sum coefficients.
      :type noncentralities: :obj:`numpy.array`
      :param noncentralities: :samp:`(n,)` shaped array of non-centrality (:samp:`(mean/stdd)**2`) parameters.
      
      :rtype: :obj:`GenChiSqrd`
      :return: Generalised Chi-Squared distribution object.
      
      """
      return _factory.create(classNamePrefix="_gchisqrd_", dtype=dtype, **{"coeffs":coeffs, "noncentralities":noncentralities})
  
  if (mango.haveRestricted):
      from ._Hist2dPeaks import *
  
  __all__ = [s for s in dir() if not s.startswith('_')]
  
  from .MixtureModel import *
  from .Gaussian import *
  from .MixtureModelFitPlotter import *
  
  if (mango.haveRestricted):
      from .SkewNormal import *
      from .SummedMixtureModel import *
      from ._MaxLikelihoodUtils import *
      from ._BinnedGmmEm import *
      from ._BinnedSummedGmmEm import *
      from ._PwGaussianMixelMixtureModel import *
      from ._fmm import *
  