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# Classifiers classes reference

This module supports HSI cube supervised classifiers. They are NormXCorr, SID and SAM. For each classifier three differents plotting are availables.

See the file `test_cls.py` for an example.

## NormXCorr

class `classifiers.``NormXCorr`

  Classify a HSI cube using the normalized cross correlation algorithm and a spectral library.

  `classify`(M, E, threshold=0.01)

    Classify the HSI cube M with the spectral library E.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      E: numpy array
        A spectral library (N x p).
      threshold: float [default 0.1] or list
        - If float, threshold is applied on all the signals.
        - If a list, individual threshold is applied on each signal, in this case the list must have the same number of threshold values than the number of signals.
        - Threshold have values between 0.0 and 1.0.
    Returns: numpy array
      A class map (m x n x 1).
  `display`(colorMap='Accent', suffix=None)

    Plot the class map on a IPython Notebook.

    Parameters:
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the title.
  `display_single_map`(lib_idx, constrained=True, suffix=None)

    Plot individual classified map on a IPython Notebook. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the title.
  `get_NormXCorr_map`()
    Returns: numpy array
      The NormXCorr array (m x n x signals number).
  `get_single_map`(lib_idx, constrained=True)

    Get individual classified map. See plot_single_map for a description.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        A number between 1 and the number of signals in the library.
      constrained: boolean [default True]
        See plot_single_map for a description.
    Returns: numpy array
      The individual map (m x n x 1) associated to the lib_idx endmember.
  `plot`(path, colorMap='Accent', suffix=None)

    Plot the class map.

    Parameters:
      path: string
        The path where to put the plot.
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_histo`(path, suffix=None)

    Plot the histogram.

    Parameters:
      path: string
        The path where to put the plot.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_single_map`(path, lib_idx, constrained=True, suffix=None)

    Plot individual classified map. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the file name.

## SAM

class `classifiers.``SAM`

  Classify a HSI cube using the spectral angle mapper algorithm and a spectral library.

  `classify`(M, E, threshold=0.1)

    Classify the HSI cube M with the spectral library E.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      E: numpy array
        A spectral library (N x p).
      threshold: float [default 0.1] or list
        - If float, threshold is applied on all the signals.
        - If a list, individual threshold is applied on each signal, in this case the list must have the same number of threshold values than the number of signals.
        - Threshold have values between 0.0 and 1.0.
    Returns: numpy array
      A class map (m x n x 1).
  `display`(colorMap='Accent', suffix=None)

    Plot the class map on a IPython Notebook.

    Parameters:
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the title.
  `display_single_map`(lib_idx, constrained=True, suffix=None)

    Plot individual classified map on a IPython Notebook. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the title.
  `get_angles_map`()
    Returns: numpy array
      The angles array (m x n x signals number).
  `get_angles_stats`()
    Returns: dic
      Angles stats.
  `get_single_map`(lib_idx, constrained=True)

    Get individual classified map. See plot_single_map for a description.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        A number between 1 and the number of signals in the library.
      constrained: boolean [default True]
        See plot_single_map for a description.
    Returns: numpy array
      The individual map (m x n x 1) associated to the lib_idx endmember.
  `plot`(path, colorMap='Accent', suffix=None)

    Plot the class map.

    Parameters:
      path: string
        The path where to put the plot.
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_histo`(path, suffix=None)

    Plot the histogram.

    Parameters:
      path: string
        The path where to put the plot.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_single_map`(path, lib_idx, constrained=True, suffix=None)

    Plot individual classified map. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the file name.

## SID

class `classifiers.``SID`

  Classify a HSI cube using the spectral information divergence algorithm and a spectral library.

  `classify`(M, E, threshold=0.1)

    Classify the HSI cube M with the spectral library E.

    Parameters:
      M: numpy array
        A HSI cube (m x n x p).
      E: numpy array
        A spectral library (N x p).
      threshold: float [default 0.1] or list
        - If float, threshold is applied on all the signals.
        - If a list, individual threshold is applied on each signal, in this case the list must have the same number of threshold values than the number of signals.
        - Threshold have values between 0.0 and 1.0.
    Returns: numpy array
      A class map (m x n x 1).
  `display`(colorMap='Accent', suffix=None)

    Plot the class map on a IPython Notebook.

    Parameters:
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the title.
  `display_single_map`(lib_idx, constrained=True, suffix=None)

    Plot individual classified map on a IPython Notebook. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the title.
  `get_SID_map`()
    Returns: numpy array
      The SID array (m x n x signals number).
  `get_single_map`(lib_idx, constrained=True)

    Get individual classified map. See plot_single_map for a description.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        A number between 1 and the number of signals in the library.
      constrained: boolean [default True]
        See plot_single_map for a description.
    Returns: numpy array
      The individual map (m x n x 1) associated to the lib_idx endmember.
  `plot`(path, colorMap='Accent', suffix=None)

    Plot the class map.

    Parameters:
      path: string
        The path where to put the plot.
      colorMap: string [default ‘Accent’]
        A color map element of [‘Accent’, ‘Dark2’, ‘Paired’, ‘Pastel1’, ‘Pastel2’, ‘Set1’, ‘Set2’, ‘Set3’], “Accent” is the default and it fall back on “Jet”.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_histo`(path, suffix=None)

    Plot the histogram.

    Parameters:
      path: string
        The path where to put the plot.
      suffix: string [default None]
        Add a suffix to the file name.
  `plot_single_map`(path, lib_idx, constrained=True, suffix=None)

    Plot individual classified map. One for each signal. Note that each individual map is constrained by the others. This function is usefull to see the individual map that compose the final class map returned by the classify method. It help to define the signals library. See the constrained parameter below.

    Parameters:
      path: string
        The path where to put the plot.
      lib_idx: int or string
        - A number between 1 and the number of signals in the library.
        - ‘all’, plot all the individual maps.
      constrained: boolean [default True]
        - If constrained is True, print the individual maps as they compose the final class map. Any potential intersection is removed in favor of the lower value level for SAM and SID, or the nearest to 1 for NormXCorr. Use this one to understand the final class map.
        - If constrained is False, print the individual maps without intersection removed, as they are generated. Use this one to have the real match.
      suffix: string [default None]
        Add a suffix to the file name.

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