Touche.
DG
--- On Fri, 7/10/09, David Warde-Farley wrote:
> From: David Warde-Farley
> Subject: Re: [Numpy-discussion] an np.arange for arrays?
> To: "Discussion of Numerical Python"
> Date: Friday, July 10, 2009, 1:06 PM
> On 10-Jul-09, at 1:26 PM, David
>
On 10-Jul-09, at 1:26 PM, David Goldsmith wrote:
> grid = np.array([np.linspace(x[i],y[i],nrows) for i in
> range(len(x))]).T
Indeed, linspace will work, but careful with Python loops though,
it'll be 2x to 6x slower (based on my empirical fiddling) than the
solution involving mgrid.
In [3
11., 12., 13., 14.],
[ 7., 8., 9., 10., 11., 12., 13., 14., 15.],
[ 8., 9., 10., 11., 12., 13., 14., 15., 16.],
[ 9., 10., 11., 12., 13., 14., 15., 16., 17.],
[ 10., 11., 12., 13., 14., 15., 16., 17., 18.]])
DG
--- On Fri, 7/10/0
Oh cool, I couldn't figure out with mgrid.
here's what ended up with using broadcasting:
>>> import numpy as np
>>> X = np.zeros((10))
>>> Y = np.arange(10, 20)
>>> M = 10
>>> increments = np.arange(1, M+1)
>>> delta = Y - X
>>> dl = (delta / M).reshape(-1, 1)
>>> interps = dl * increments
>>> lin
On 10-Jul-09, at 1:25 AM, Chris Colbert wrote:
> actually what would be better is if i can pass two 1d arrays X and Y
> both size Nx1
> and get back a 2d array of size NxM where the [n,:] row is the linear
> interpolation of X[n] to Y[n]
This could be more efficient, but here's a solution using
actually what would be better is if i can pass two 1d arrays X and Y
both size Nx1
and get back a 2d array of size NxM where the [n,:] row is the linear
interpolation of X[n] to Y[n]
On Fri, Jul 10, 2009 at 1:16 AM, Chris Colbert wrote:
> If i have two arrays representing start points and end po
If i have two arrays representing start points and end points, is
there a function that will return a 2d array where each row is the
range(start, end, n) where n is a fixed number of steps and is the
same for all rows?
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