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# Endmembers extraction classes

## ATGP

class `eea.``ATGP`

  Automatic target generation process endmembers induction algorithm.

  `display`(info, suffix=None)

    Display the endmembers to a IPython Notebook.

    Parameters:
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the title.
  `extract`(M, q, normalize=False, mask=None)

    Extract the endmembers.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      q: int
        Number of endmembers to be induced (positive integer > 0).
      normalize: boolean [default False]
        Normalize M before unmixing.
      mask: numpy array [default None]
        A binary mask, if True the corresponding signal is part of the endmembers search.
    Returns: numpy array
      Set of induced endmembers (N x p).
    References:
      A. Plaza y C.-I. Chang, “Impact of Initialization on Design of Endmember Extraction Algorithms”, Geoscience and Remote Sensing, IEEE Transactions on, vol. 44, no. 11, pgs. 3397-3407, 2006.
  `get_idx`()
    Returns: numpy array
      Array of indices into the HSI cube corresponding to the induced endmembers
  `plot`(path, info, suffix=None)

    Plot the endmembers.

    Parameters:
      path: string
        The path where to put the plot.
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the file name.

## FIPPI

class `eea.``FIPPI`

  Fast Iterative Pixel Purity Index (FIPPI) endmembers induction algorithm.

  `display`(info, suffix=None)

    Display the endmembers to a IPython Notebook.

    Parameters:
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the title.
  `extract`(M, q=None, maxit=None, normalize=False)

    Extract the endmembers.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      q: int [default None]
        Number of endmembers to be induced, if None use HfcVd to determine the number of endmembers to induce.
      maxit: int [default None]
        Maximum number of iterations. Default = 3*q.
      normalize: boolean [default False]
        Normalize M before unmixing.
    Returns: numpy array
      Set of induced endmembers (N x p).
    References:
      Chang, C.-I., “A fast iterative algorithm for implementation of pixel purity index”, Geoscience and Remote Sensing Letters, IEEE, vol. 3, no. 1, pags. 63-67, 2006.
  `get_idx`()
    Returns: numpy array
      Array of indices into the HSI cube corresponding to the induced endmembers.
  `plot`(path, info, suffix=None)

    Plot the endmembers.

    Parameters:
      path: string
        The path where to put the plot.
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the file name.

## NFINDR

class `eea.``NFINDR`

  N-FINDR endmembers induction algorithm.

  `display`(info, suffix=None)

    Display the endmembers to a IPython Notebook.

    Parameters:
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the title.
  `extract`(M, q, transform=None, maxit=None, normalize=False, ATGP_init=False, mask=None)

    Extract the endmembers.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      q: int
        The number of endmembers to be induced.
      transform: numpy array [default None]
        The transformed ‘M’ cube by MNF (m x n x components). In this case the number of components must == q-1. If None, the built-in call to PCA is used to transform M in q-1 components.
      maxit: int [default None]
        The maximum number of iterations. Default is 3*p.
      normalize: boolean [default False]
        If True, M is normalized before doing the endmembers induction.
      ATGP_init: boolean [default False]
        Use ATGP to generate the first endmembers set instead of a random selection.
      mask: numpy array [default None]
        A binary mask, when True the corresponding signal is part of the endmembers search.
    Returns: numpy array
      Set of induced endmembers (N x p).
    References:
      Winter, M. E., “N-FINDR: an algorithm for fast autonomous spectral end-member determination in hyperspectral data”, presented at the Imaging Spectrometry V, Denver, CO, USA, 1999, vol. 3753, pgs. 266-275.
    Note:
      The division by (factorial(p-1)) is an invariant for this algorithm, for this reason it is skipped.
  `get_idx`()
    Returns : numpy array
      Array of indices into the HSI cube corresponding to the induced endmembers
  `get_iterations`()
    Returns : int
      The number of iterations.
  `plot`(path, info, suffix=None)

    Plot the endmembers.

    Parameters:
      path: string
        The path where to put the plot.
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the file name.

## PPI

class `eea.``PPI`

  Performs the pixel purity index algorithm for endmember finding.

  `display`(info, suffix=None)

    Display the endmembers to a IPython Notebook.

    Parameters:
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the title.
  `extract`(M, q, numSkewers=10000, normalize=False)

    Extract the endmembers.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      q: int
        Number of endmembers to find.
      numSkewers: int [default 10000]
        Number of “skewer” vectors to project data onto. In general, recommendation from the literature is 10000 skewers.
    Returns: numpy array
      Recovered endmembers (N x p).
  `get_idx`()
    Returns: numpy array
      Array of indices into the HSI cube corresponding to the induced endmembers
  `plot`(path, info, suffix=None)

    Plot the endmembers.

    Parameters:
      path: string
        The path where to put the plot.
      info: dictionary
        - info[‘wavelength’] : a wavelengths list (1D python list).
        - info[‘wavelength units’] : the x axis label, ‘Unknown’ if not specified.
      suffix: string [default None]
        Suffix to add to the file name.

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