MemoryError: Unable to allocate array with shape (114671, 114671) and data type float64

I get the following error: MemoryError: Unable to allocate array with shape (114671, 114671) and data type float64

Defining Ordinary Kriging as:

gridx = np.arange(min_x, max_x, 1)
gridy = np.arange(min_y, max_y, 1)

# Ordinary Kriging
OK = OrdinaryKriging(x, y, z, variogram_model='exponential',
                       verbose=False, enable_plotting=True, coordinates_type='geographic')

z1, ss = OK.execute('grid', gridx, gridy)

Where, min_x = 8084396 min_y = 12073405 max_x = 8084864 max_y = 12073894

I understand that grid_x and grid_y arrays are too big. What can I do in this case to make this work?

[MuellerSeb]

That is really interesting! Thanks for sharing.

[mjziebarth]

To chime in, having written that part of the code:

That part of the code is a fairly simple implementation of the third equation of the section Computational formulas of this Wikipedia article. It was written using a simple vectorized version of the equation which creates a number of temporary arrays corresponding to terms of the rather large equation.

If you are working so tightly at your RAM limit, these additional terms could be the icing on the cake. Apart from random subsampling, you could try to work in Euclidean space (see #149), if you don’t explicitly want to use the great-circle distance at large distances. Specifically, this would mean to compute Euclidean coordinates x,y,z from your latitudes and longitudes, and then kriging without the coordinates_type='geographic' option. Maybe this saves just enough temporary arrays to fit into your RAM.

Hope that helps!