Abundance maps classes

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FCLS

class abundance_maps.FCLS

Performs fully constrained least squares. Fully constrained least squares is least squares with the abundance sum-to-one constraint (ASC) and the abundance nonnegative constraint (ANC).

display(colorMap='jet', suffix=None)

Plot the abundance maps on a IPython Notebook.

Parameters:

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the title.

map(M, U, normalize=False)

Performs fully constrained least squares of each pixel in M using the endmember signatures of U.

Parameters:

M: numpy array

A HSI cube (m x n x p).

U: numpy array

A spectral library of endmembers (q x p).

normalize: boolean [default False]

If True, M and U are normalized before doing the signals mapping.

Returns: numpy array

An abundance maps (m x n x q).

plot(path, colorMap='jet', suffix=None)

Plot the abundance maps.

Parameters:

path: string

The path where to put the plot.

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the file name.

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NNLS

class abundance_maps.NNLS

NNLS performs non-negative constrained least squares with the abundance nonnegative constraint (ANC). Utilizes the method of Bro.

display(colorMap='jet', suffix=None)

Plot the abundance maps on a IPython Notebook.

Parameters:

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the title.

map(M, U, normalize=False)

NNLS performs non-negative constrained least squares of each pixel in M using the endmember signatures of U.

Parameters:

M: numpy array

A HSI cube (m x n x p).

U: numpy array

A spectral library of endmembers (q x p).

normalize: boolean [default False]

If True, M and U are normalized before doing the signals mapping.

Returns: numpy array

An abundance maps (m x n x q).

plot(path, colorMap='jet', suffix=None)

Plot the abundance maps.

Parameters:

path: string

The path where to put the plot.

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the file name.

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UCLS

class abundance_maps.UCLS

Performs unconstrained least squares abundance estimation.

display(colorMap='jet', suffix=None)

Plot the abundance maps on a IPython Notebook.

Parameters:

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the title.

map(M, U, normalize=False)

Performs unconstrained least squares abundance estimation on the HSI cube M using the signals library U.

Parameters:

M: numpy array

A HSI cube (m x n x p).

U: numpy array

A spectral library of endmembers (q x p).

normalize: boolean [default False]

If True, M and U are normalized before doing the signals mapping.

Returns: numpy array

An abundance maps (m x n x q).

plot(path, colorMap='jet', suffix=None)

Plot the abundance maps.

Parameters:

path: string

The path where to put the plot.

colorMap: string [default jet]

A matplotlib color map.

suffix: string [default None]

Suffix to add to the file name.