Pfthb

I'm doing linear optimization using interior point method.
My optimization code looks like

z=scipy.optimize.linprog(c, A_ub, b_ub, bounds=bounds,method='interior-point',
 options = "maxiter":10000)

I have 34K of data. Checked the shape of A_ub using below code

A_ub.shape
Out[7]: (37439, 74878)

Initially same code ran for 8K data but now it's throwing error

TypeError: Invalid input for linprog: A_ub must be a numerical 2D array with each row representing an upper bound inequality constraint

Can you help me to resolve this issue?

I found this example from old code

from scipy import optimize
 optimize.linprog(
... c = [1, 3], 
... A_ub=[[1, 1]], 
... b_ub=[4],
... bounds=(1, 6),
... method='interior-point'
... )
 con: array(, dtype=float64)
 fun: 4.00000000831602
 message: 'Optimization terminated successfully.'
 nit: 4
 slack: array([2.])
 status: 0
 success: True
 x: array([1., 1.])

Of course you can use simple or any other method. May be you should check memory,you are dealing with large arrays.