2020-05-05 17:16:33 +0200 | received badge | ● Scholar (source) |
2020-05-05 17:16:26 +0200 | commented answer | update package scipy sorry, I should have edited my comment, I hadn't restarted sage (maybe...), but it seems to work, Thanks! |
2020-05-05 16:15:22 +0200 | commented answer | update package scipy I did this, but sage still gives (and I checked if it was using the newer features of simpy, which is not): although: |
2020-05-05 13:39:38 +0200 | asked a question | update package scipy Hi! I would like to update the scipy package used by sage. It uses 1.2 while I would like to use 1.4 (which I have on my system, but don't mind installing in sage's python toolchain). Is this possible? Thanks |
2020-05-03 21:25:52 +0200 | received badge | ● Student (source) |
2020-05-02 18:57:42 +0200 | commented question | minimization without constraints gives error for multiple dimension is there a way to use sum([x,y]) for x=var('x')?, with x and y in R^5 |
2020-05-02 18:33:07 +0200 | commented question | minimization without constraints gives error for multiple dimension you are right, it should have been as below, and then x domain is now the one I want thanks, I'll try again like so |
2020-05-02 18:19:26 +0200 | received badge | ● Editor (source) |
2020-05-02 18:13:49 +0200 | commented answer | minimization without constraints gives error for multiple dimension I saw the documentation, yes. But my example above should also work, and I think I'm still able to compute gradents by hand. Even if there is an error I don't think it's the one being yielded by sage. Moreover, it should work for a function that is not symbolic. |
2020-05-02 14:20:45 +0200 | asked a question | minimization without constraints gives error for multiple dimension I'm trying to use What am I doing wrong? the gradient return a vector (correctly so). Shouldn't this work? |