pecans.utilities.general_utils.ensure_n_args_to_return(n_args, args_iterable, fill_val=None)[source]

Create a tuple of arguments to return that is guaranteed to have a certain number of elements

Since Python does tuple expansion, you can return a tuple from a function and have each element of the tuple expanded into individual return values. For example:

def return_tuple():
    return ('a','b','c')

x, y, z = return_tuple()

would put 'a' into x, 'b' into y, and 'c' into z. However, this means that there must be exactly one or three variables to receive the output of return_tuple(), i.e. x, y = return_tuple() would fail. This can be a problem if a function is trying to return a dynamic number of values, since it means the call would have to account for that. This function will create a tuple with a guaranteed number of values.

Parameters:

  • n_args (int) – how many return values you want the tuple to contain

  • args_iterable (list or tuple) – an iterable (currently only tuples and lists supported) that contains <= n_args elements to return.

  • fill_val (any) – optional, the value to append to the returned tuple to fill it out. Default is None.

Returns:

the tuple form of args_iterable with exactly n_args elements

Return type:

tuple

pecans.utilities.general_utils.gaussian(center_x, sigma_x, x, center_y=None, sigma_y=None, y=None, center_z=None, sigma_z=None, z=None, normalized=True)[source]

Compute a Gaussian curve. Currently only implemented for 1D

Parameters:

  • center (float) – the center point in the same coordinates as x, y, and z

  • sigma (float) – the sigma width in the same units as x, y, and z

  • x (numpy.ndarray) – the x-coordinate to compute the Gaussian along.

  • y (numpy.ndarray) – the y-coordinate to compute the Gaussian along.

  • z (numpy.ndarray) – the z-coordinate to compute the Gaussian along.

  • normalized (bool) – whether or not to normalize the gaussian so that its area is 1. Default is True.

Returns:

an array of size nx-by-ny-by-nz.

Return type:

numpy.ndarray.