CVXPY is a Python-embedded modeling language for convex optimization problems inspired by the MATLAB package CVX.
Questions tagged [cvxpy]
609 questions
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Maximizing a Ratio/Percent
I'm using cvxpy to model a problem.
Inside a very large and complex LP, I create two continuous, affine (unconstrained) expressions:x and y.
Due to how they are created, I know that 0 < x < y <= U. Obviously: x/y < 1.
In my LP objective, how do I…
Adi Shavit
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CVXPY library to optimise utility function
I am trying to maximise the utility function with two constraints. But I am not sure where I need to fix the Code.
I have tried making the dimensions of the matrices same and specified in the code
I have defined the global parameters
I have…
Prachi
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Unable to install PyPortfolioOpt
When trying to install PyPortfolioOpt using pip it errors out with the following message,
ERROR: Failed building wheel for cvxpy
ERROR: Could not build wheels for cvxpy which use PEP 517 and cannot be installed directly
However, i do have cvxpy…
sarvotham
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1 answer
Solving KKT equations in SymPy
I am trying to solve KKT equations using sympy. All of the equations are symbolic and contain constants that are not given as numbers but as symbols. Alongside with the equations, there are also inequality constraints.
Is it possible to do this in…
Light
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Is there a way to implement a constraint: Rank(X) == 1 in CVXPY
I got some code from a friend which reads like this:
import numpy as np
import cvxpy as cp
def tomoSolve(m, P,prin=True):
# get d from projector length
d = int(np.sqrt(P.shape[1]))
# n.b. due to cvxpy's implementation of variable…
Markus
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Is there a GLPK parameter that affects convergence?
I'm using GLPK_MI to solve a Mixed Integer Linear Program via cvxpy.
Whenever my problem grows beyond about 2000 constraints, the solver does not converge and just keeps on running.
When I removed some redundant constraints to stay below 2000…
Adi Shavit
- 16,743
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- 137
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1 answer
Write Dirichlet Log Likelihood with DCP ruleset
I would like to write the log likelihood of the Dirichlet density as a disciplined convex programming (DCP) optimization problem with respect to the parameters of the Dirichlet distribution alpha. However, the log likelihood
def…
Jon Deaton
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No strict inequalities in cvxpy problem but still get the error "Strict inequalities are not allowed"
I was using the CVXPY library in Python, trying to solve a particular optimization problem.
import cvxpy as cp
import numpy as np
from scipy.stats import norm
(...)
a = cp.Variable([10, 1])
obj = cp.Maximize(sum(norm.logcdf(A @ a,…
JackAu
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Segmentation fault (core dumped) while using CVXPY library
I am trying to solve an optimization problem using CVXPY library. My code runs properly on a dummy dataset but crashes when I key in the actual dataset. The error I got is
Segmentation fault (core dumped)
I tried to search for the solution on…
Upendra01
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2 answers
Automatic unwanted terminal outputs while solving cvxpy optimization problem
While trying to solve a logistic regression problem using cvxpy I got a bunch of terminal outputs when calling the solve() function even though no print-outs were programmed. Furthermore, no information about the problem was printed to the terminal…
Manumerous
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Euclidean distance in convex constraint & optimization
Beginner style, general question regarding convex optimization. As part of the learning cvxpy specifically, and convex optimization in general, was trying a basic (imaginary) geometry (hopefully convex) optimization problem. Given two points in 2D…
StevieG_001
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1 answer
CVXPY to minimize difference between 2 arrays
I have 2 arrays of n elements each. The first is a percentage (ranging from 0% to 100%) where the sum of all elements yields 100%. The second is constituted of integers ranging from -3 to 3 (inclusive).
The objective of my script is to vary the…
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1 answer
Python non convex optimization
I use the package cvxpy form Python to solve a non convex optimization problem which is given as follows:
import numpy as np
import cvxpy as cp
def kl(a,b):
if a==b:
return 0.000001
if b==0:
return 1000000
if a==0:
…
Maurice Rolvien
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Is there an alternative to scipy.optimize.lsq_linear for solving a non-square matrix equation by minimizing the L1 norm instead?
I wrote a python code that imports some data which I then manipulate to get a nonsquare matrix A. I then used the following code to solve the matrix equation.
from scipy.optimize import lsq_linear
X = lsq_linear(A_normalized, Y, bounds=(0, np.inf),…
YKZ
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1 answer
Is there a way to get the final system of equations sent by cvxpy to the solver?
If I understand correctly, cvxpy converts our high-level problem description to the standard canonical form before it is sent to a solver.
By the standard form I mean the form that can be used for the descent algorithms, so, for instance, it would…
t-arsin
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