On 04/16/2017 04:57 PM, Sergio Rojas wrote:
On 04/14/2017 04:21 AM, Peter Otten wrote:
Stephen P. Molnar wrote:
However, what I want to do is multiply each element ob D by each element
of s and sum all of the products.
If you *really* want this:
sum_of_all_products = s.sum() * D.sum()
example:
s = [a b c]
D = [[a1 a2]
[a3 a4]]
a*a1 + a*a2 + a*a3 + a*a4 = a * D.sum()
d := D.sum()
a*d + b*d + c*d = s.sum() * d
Even if that's what you want you should heed Steven's advice.
Nice example on "analyze before computing". Nevertheless,
A lazy man's approach to life might go using numpy ufunc.outer
[ https://docs.scipy.org/doc/numpy/reference/generated/numpy.ufunc.outer.html
]
In [1]: import numpy as np
In [2]: from sympy import symbols
In [3]: x1, y1, z1, x2, y2, z2, x3, y3, z3 = symbols('x1 y1 z1 x2 y2 z2 x3 y3 z3
...: ')
In [4]: x=np.array([[x1,y1,z1], [x2,y2,z2], [x3,y3,z3]])
In [5]: z=np.array([z1,z2,z3])
In [6]: print(np.multiply.outer(z,x))
[[[x1*z1 y1*z1 z1**2]
[x2*z1 y2*z1 z1*z2]
[x3*z1 y3*z1 z1*z3]]
[[x1*z2 y1*z2 z1*z2]
[x2*z2 y2*z2 z2**2]
[x3*z2 y3*z2 z2*z3]]
[[x1*z3 y1*z3 z1*z3]
[x2*z3 y2*z3 z2*z3]
[x3*z3 y3*z3 z3**2]]]
In [7]: np.multiply.outer(z,x).sum()
Out[7]: x1*z1 + x1*z2 + x1*z3 + x2*z1 + x2*z2 + x2*z3 + x3*z1 + x3*z2 + x3*z3 +
y1*z1 + y1*z2 + y1*z3 + y2*z1 + y2*z2 + y2*z3 + y3*z1 + y3*z2 + y3*z3 + z1**2 +
2*z1*z2 + 2*z1*z3 + z2**2 + 2*z2*z3 + z3**2
In [8]:
Sergio
https://www.packtpub.com/big-data-and-business-intelligence/numerical-and-scientific-computing-scipy-video
https://github.com/rojassergio/Learning-Scipy
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Thanks for the reply.
--
Stephen P. Molnar, Ph.D. Life is a fuzzy set
www.molecular-modeling.net Stochastic and multivariate
(614)312-7528 (c)
Skype: smolnar1
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