apply¶
- kgpy.ctis.inversion.mart.antialias.apply(data, x_axis_index=-3, y_axis_index=-2, user_provided_kernel=False, kernel=<Quantity [0.25, 0.5, 0.25]>)¶
Apply the antialias kernel to the cube data, for use in MART related inversion problems. :type data:
numpy.ndarray:param data: :type x_axis_index:int:param x_axis_index: axis in data that is the spatial x-axis :type y_axis_index:int:param y_axis_index: axis in data that is the spatial y-axis :type user_provided_kernel:bool:param user_provided_kernel: if True, do not use calc_kernel to calculate the convolution kernel, instead using a kernel provided by the user. :type kernel:astropy.units.quantity.Quantity:param kernel: 1-dimensional kernel to be given to calc_kernel to generate the convolution kernel, or, if user_provided_kernel True, this kernel is handed directly to the convolution :rtype:numpy.ndarray:return: antialiased version of data