pyodide/benchmark/benchmarks/l2norm.py

#from: http://stackoverflow.com/questions/7741878/how-to-apply-numpy-linalg-norm-to-each-row-of-a-matrix/7741976#7741976
#setup: import numpy as np ; N = 1000; x = np.random.rand(N,N)
#run: l2norm(x)

#pythran export l2norm(float64[][])
import numpy as np


def l2norm(x):
    return np.sqrt(np.einsum('ij,ij->i', x, x))
Adding benchmarks 2018-04-05 22:07:33 +00:00			`#from: http://stackoverflow.com/questions/7741878/how-to-apply-numpy-linalg-norm-to-each-row-of-a-matrix/7741976#7741976`
			`#setup: import numpy as np ; N = 1000; x = np.random.rand(N,N)`
			`#run: l2norm(x)`

			`#pythran export l2norm(float64[][])`
			`import numpy as np`
Clean up and improve some benchmarks 2018-10-03 12:38:48 +00:00

Adding benchmarks 2018-04-05 22:07:33 +00:00			`def l2norm(x):`
Clean up and improve some benchmarks 2018-10-03 12:38:48 +00:00			`return np.sqrt(np.einsum('ij,ij->i', x, x))`