asmatrix(scalar * m.A)

or I noticed the other day that scalar division works ok, so if you know scalar is != 0,

m / (1.0/scalar)

where m is a numpy.matrix, of course.

I find myself repeatedly getting bitten by this, since I'm writing code that does lots of lerping between vectors.

This is pretty dang ugly to see all over the place:

vlerp = asmatrix((1-t) * v1.A + t * v2.A )

when it should just be

vlerp = (1-t)*v1 + t*v2

yeh yeh, I should write a function...

--bb

On 3/9/06, **Sven Schreiber** <
svetosch@gmx.net> wrote:

Travis Oliphant schrieb:

> Bill Baxter wrote:

>

>> Multiplying a matrix times a scalar seems to return junk for some reason:

>>

>> >>> A = numpy.asmatrix(numpy.rand(1,2))

>> >>> A

>> matrix([[ 0.30604211 , 0.98475225]])

>> >>> A * 0.2

>> matrix([[ 6.12084210e-002, 7.18482614e-290]])

>> >>> 0.2 * A

>> matrix([[ 6.12084210e-002, 7.18482614e-290]])

>> >>> numpy.__version__

>> '0.9.5'

>>

> This should be fixed in SVN.

>

>

I have just been bitten by this bug, so I would like to ask when to

expect the next release. And/or are there any workarounds?

Thanks,

Sven

--

William V. Baxter III

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