# interpolate_replace_nans¶

astropy.convolution.interpolate_replace_nans(array, kernel, convolve=<function convolve at 0x7fc9dd64fea0>, **kwargs)[source]

Given a data set containing NaNs, replace the NaNs by interpolating from neighboring data points with a given kernel.

Parameters: array : numpy.ndarray Array to be convolved with kernel. It can be of any dimensionality, though only 1, 2, and 3d arrays have been tested. kernel : The convolution kernel. The number of dimensions should match those for the array. The dimensions do not have to be odd in all directions, unlike in the non-fft convolve function. The kernel will be normalized if normalize_kernel is set. It is assumed to be centered (i.e., shifts may result if your kernel is asymmetric). The kernel must be normalizable (i.e., its sum cannot be zero). convolve : One of the two convolution functions defined in this package. newarray : numpy.ndarray A copy of the original array with NaN pixels replaced with their interpolated counterparts