Module ops

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common operations on numpy arrays

Author: odenas

Functions

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fit(x, axis=None, nans=0.0)
scale values of x in the interval [-1, 1]

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standardize(x, axis=None, nans=0.0)
transform each component of flattened X examples to 0 mean and 1 std So the values of track t at position i are 0 mean and 1 std

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Variables

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__package__ = 'dimer'

Function Details

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fit(x, axis=None, nans=0.0)

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scale values of x in the interval [-1, 1]

Parameters:

x - ndarray
axis - passed to numpy.max and numpy.min
nans - if nan values are produced replace them with this

Returns:

scaled values of x

standardize(x, axis=None, nans=0.0)

source code

transform each component of flattened X examples to 0 mean and 1 std So the values of track t at position i are 0 mean and 1 std

x: a pandas data panel of the form <anchors> X <tracks> X <genome position> return: (the shifted input, the mean for each input component, the sd of each input component) the latter 2 are arrays of shape(<tracks>, <genome position>)