Hi - I'm using matplotlib.tri.LinearTriInterpolator to regrid data from an
unstructured 2d triangular grid, to a structured grid. It works great on
smaller datasets, but when I try to regrid a larger dataset I get the
following error:
---------------------------------------------------------------------------MemoryError
Traceback (most recent call last)
File <timed exec>:1, in <module>
File ~/.conda/envs/pangeo/lib/python3.8/site-packages/matplotlib/tri/triinterpolate.py:265,
in LinearTriInterpolator.__call__(self, x, y) 264 def
__call__(self, x, y):--> 265 return self._interpolate_multikeys(x,
y, tri_index=None, 266
return_keys=('z',))[0]
File ~/.conda/envs/pangeo/lib/python3.8/site-packages/matplotlib/tri/triinterpolate.py:163,
in TriInterpolator._interpolate_multikeys(self, x, y, tri_index,
return_keys) 160 if x.shape != y.shape: 161 raise
ValueError("x and y shall have same shapes." 162
" Given: {0} and {1}".format(x.shape, y.shape))--> 163 x =
np.ravel(x) 164 y = np.ravel(y) 165 x_scaled = x/self._unit_x
File <__array_function__ internals>:180, in ravel(*args, **kwargs)
File ~/.conda/envs/pangeo/lib/python3.8/site-packages/numpy/core/fromnumeric.py:1859,
in ravel(a, order) 1857 return asarray(a).ravel(order=order)
1858 else:-> 1859 return asanyarray(a).ravel(order=order)
MemoryError: Unable to allocate 13.2 GiB for an array with shape
(1767600000,) and data type float64
Is there a version of matplotlib.tri that uses Dask, to enable
regridding of larger datasets?
Thanks
Jim
