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aothms | 9 months ago
E.g just now I ran:
~~~
What's the inverse of this matrix?
[[0.0759688880587972, 0.3299493758880664, 0.14599823333009276, 0.09897577338235164], [0.7478951343477207, 0.9006422280032432, 0.3137352150172843, 0.5974301357799204], [0.5568700534103693, 0.648666832906366, 0.5280912469659284, 0.5753861797637815], [0.7905984807343551, 0.053757547259005944, 0.9632727273522135, 0.44727851917969785]]
~~~
Reasoning output:
~~~
The user is asking for the inverse of a matrix. Since they want the result, I will compute it and present it as a matrix in Markdown. I’ll use Python for the calculation but won’t include any code in the final answer. It’s best to show the resulting matrix in Markdown so the user sees only the output, as requested. I’ll use Python to compute it and then provide the result without extra code.
import sympy as sp import numpy as np
# define the matrix M = np.array([ [0.0759688880587972, 0.3299493758880664, 0.14599823333009276, 0.09897577338235164], [0.7478951343477207, 0.9006422280032432, 0.3137352150172843, 0.5974301357799204], [0.5568700534103693, 0.648666832906366, 0.5280912469659284, 0.5753861797637815], [0.7905984807343551, 0.053757547259005944, 0.9632727273522135, 0.44727851917969785] ], dtype=float)
# calculate inverse invM = np.linalg.inv(M)
invM
~~~
And then I get a nicely formatted latex matrix as the final outcome.
(edit: that's 04-mini-high)
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