Hello.
I want to vectorize this operation, which below is implemented as a
for-loop:
def smoothing_loop( y ): #y is an array with noisy values
ybar = []
ybar.append( y[0] )
#Smoothing with a loop
length = size( y )
for i in range( 1, length -1 ):
ybar.append( .5 * ( y[ i-1 ] + y[ i + 1 ] ) )
e.g. y = [ 1, 2, 3, 4, 5, 6 ,7 ,8, 9 ]
ybar = [ 1, (1 + 3)*.5,(2 + 4)*.5,(3 + 5)*.5,..., (n-1 + n+1)*.5 ], n =
1,...len(y) -1
How do I make a vectorized version of this, I will prefer not to
utilize Map or similar functions, but numeric instead.
Regards,
Ronny Mandal 1 1365
"RonnyM" <ro*****@math.uio.no> wrote in message
news:11**********************@u72g2000cwu.googlegr oups.com... e.g. y = [ 1, 2, 3, 4, 5, 6 ,7 ,8, 9 ]
ybar = [ 1, (1 + 3)*.5,(2 + 4)*.5,(3 + 5)*.5,..., (n-1 + n+1)*.5 ], n = 1,...len(y) -1 How do I make a vectorized version of this, I will prefer not to utilize Map or similar functions, but numeric instead.
You treat the first element asymmetrically, so that does not vectorize.
The rest does: import numpy as N y=N.arange(1,10) slice1 = slice(0,-2,1) slice2 = slice(2,None,1) ybar = 0.5*(y[slice1]+y[slice2]) ybar
array([ 2., 3., 4., 5., 6., 7., 8.])
hth,
Alan Isaac This thread has been closed and replies have been disabled. Please start a new discussion. Similar topics
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