December 2017
Intermediate to advanced
386 pages
10h 42m
English
Content preview from SciPy Recipes
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How to do it...
We have the following functions and parameters:
| Parameters |
a : (..., M, M) array_like Coefficient matrix. b : {(..., M,), (..., M, K)}, array_like Ordinate or dependent variable values. |
| Returns |
x : {(..., M,), (..., M, K)} ndarray Solution to the system a x = b. The returned shape is identical to b. |
| Raises |
LinAlgError If a is singular or not square. |
Broadcasting rules apply; see the numpy.linalg documentation for details. The solutions are computed using the LAPACK _gesv routine it must be square and of full-rank, that is, all rows (or, equivalently, columns) must be linearly independent; if either is not true, use lstsq for the least-squares best solution of the system/equation.
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.