watson_ladd's profile - activity

Is there no way to make pip work with NSS instead?

Worst this happens when installing the SSL module also.

Fresh install on Mac OS X 10.14.6

$sage -pip install pycryptodome

WARNING: pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available. WARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'SSLError("Can't connect to HTTPS URL because the SSL module is not available.")': /simple/pycryptodome/ ERROR: Could not find a version that satisfies the requirement pycryptodome (from versions: none) ERROR: No matching distribution found for pycryptodome WARNING: pip is configured with locations that require TLS/SSL, however the ssl module in Python is not available. Could not fetch URL https://pypi.org/simple/pip/: There was a problem confirming the ssl certificate: HTTPSConnectionPool(host='pypi.org', port=443): Max retries exceeded with url: /simple/pip/ (Caused by SSLError("Can't connect to HTTPS URL because the SSL module is not available.")) - skipping

What I want is a function that given a matrix $A$ and vector $v$ will return a vector $x$ such that $Ax=v$ and will determine if this $x$ is unique or not, while doing a minimal amount of work. Currently I am using right nullity and the solve_right function separately, which I think results in some redundancy. Any advice on what I should do? There doesn't seem to be an obvious solution from the manual.

I have a script I am running many times with a .spyx file. Unfortunately each compilation creates a large temporary file, and these are eating up my disk quota so it now no longer runs. What do I do to avoid this situation? Ideally I compile once and sage uses that for all executions.

I have a bunch of matrices with integer coefficients that simultaneously commute. I know that there is a basis that simultaneously diagonalizes all of them, and I want to find it exactly so that I can recover all the corresponding eigenvalues as algebraic numbers.

I've tried casting to QQbar and using eigenvectors, but this occasionally tries to divide by zero for no reason I can discern. Any ideas?

Consider the following code

r = QQbar.polynomial_root(x^5-x-1,CIF(RIF(0.1, 0.2), RIF(1.0, 1.1))
F,_,_ = number_field_elements_from_algebraics(r)
F(r)

Even though r can be coerced into an element of F, this coercion doesn't happen. What is the right thing for me to do? I'm interested in computing an algebraic number field that will contain a bunch of eigenvalues and want to express all the eigenvalues as elements of the number field. I've done the obvious workaround but the limitation expressed in the sample above isn't great.

So I solved the problem by going straight to Pari's qfisom routine that the is_globally_isomorphic routine eventually calls. The script generates the p-neighbors and checks for isometry, so all the forms are positive definite, but determining this is extremely expensive as currently implemented and overshadows the cost of the isomorphism testing.

To do this if $q1$ and $q2$ are the Gram matricies I write:

T = g1.__pari()__.qfisom(g2.__pari__())

and T is either False or the transformation matrix I want.

I have a script that generates a bunch of locally isomorphic quadratic forms and then tests them for global isometry. This script is too slow. Looking at profiling data much of the runtime is spent in the Quadratic forms class computing the useless local invariants and very little in the Pari qfisom calls. What can I do to cut down on this overhead?