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Transcribed Image Text:Using DASK in Python to solve this problem.
Given a dask array, compute the difference along axis 0 using mean squared error
This can be done without loops -- think outside of the box! This also needs to work
for 1D, 2D, 3D, 4D, etc.
def sequential_MSE_axis0 (anArray):
# this does use the earlier MSE implementation
n_elements_axis0 = anArray. shape [0] - 1
anArray.shape[0]
results = da.zeros(n_elements_axis0)
for i in range(n_elements_axis0):
results[i] = MSE (anArray[i], anArray[i+1])
return results
Complete the function below. Don't call . compute()
Test
Result
oneDda.arange(4); print (all (isclose(a, b) for a, b in
zip (MSE_axis0 (oneD), [1., 1., 1.])))
twoD =
True
da.arange(4).reshape((2,2)); print (all(isclose(a, b) for a,
True
b in zip (MSE_axis 0 (twoD), [4.])))
=
threeD da.arange(8).reshape((2, 2,2)); print (all(isclose(a, b).
for a, b in zip (MSE_axis0 (threeD).compute(), [16.])))
True
def MSE_axis0 (anArray):
## WRITE YOUR CODE HERE
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