Commit b3f9a797 by Julia Garriga Ferrer

### [core][imageregistration] Change docstring for improve_linear_shift

parent 8283ae8c
 ... @@ -171,16 +171,13 @@ def normalize(x): ... @@ -171,16 +171,13 @@ def normalize(x): def improve_linear_shift(data, v, h, epsilon, steps, nimages=None, shift_approach="linear"): def improve_linear_shift(data, v, h, epsilon, steps, nimages=None, shift_approach="linear"): """ """ Function to find the best shift between the images. It loops ``h_max * h_step`` times, Function to find the best shift between the images. It loops ``steps`` times, applying a different shift each, and trying to find the one that has the best result. applying a different shift each, and trying to find the one that has the best result. :param array_like data: The stack of images. :param array_like data: The stack of images. :param 2-dimensional array_like v: The vector with the direction of the shift. :param 2-dimensional array_like v: The vector with the direction of the shift. :param number h_max: The maximum value that h can achieve, being h the shift between :param float epsilon: Maximum value of h images divided by the vector v (i.e the coordinates of the shift in base v). :param int steps: Number of different tries of h. :param number h_step: Spacing between the ``h`` tried. For any `` shift = h * v * idx``, where ``idx`` is the index of the image to apply the shift to, this is the distance between two adjacent values of h. :param int nimages: The number of images to be used to find the best shift. It has to :param int nimages: The number of images to be used to find the best shift. It has to be smaller or equal as the length of the data. If it is smaller, the images used be smaller or equal as the length of the data. If it is smaller, the images used are chosen using `numpy.random.choice`, without replacement. are chosen using `numpy.random.choice`, without replacement. ... ...
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