optimization

问题 This code works correctly. def m(model, i): return model.fd_amt[i] <= getattr(model, 'br_sa_ind')[i] * global_m setattr(model, ind+"_m",Constraint(model.br_standalone_I, rule=m)) But this def m(model, i, ind_name): return model.fd_amt[i] <= getattr(model, ind_name)[i] * global_m setattr(model, ind+"_m",Constraint(rule=m(model,model.model.br_standalone_I, 'br_sa_ind') )) results in this error: ERROR: evaluating expression: No value for uninitialized NumericValue object fd_amt[br_standalone_I]

问题 Can I measure the code size with the help of an fseek() function and store it to a shell variable? Is it possible to extract the code size, compilation time and execution time using milepost gcc or a GNU Profiler tool ? If yes, how to store them into shell variables? Since my aim is to find the best set of optimization technique upon the basis of the compilation time, execution time and code size, I will be expecting some function that can return these parameters. MyPgm=/root/Project/Programs

问题 I want to calibrate the Heston SV model (http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.139.3204&rep=rep1&type=pdf) using the function callHestoncf from the package NMOF . For that I need to estimate four structural parameters (vT, rho, k & sigma) using a loss function. The loss function is a weighted sum of squared errors of the form 1/N * sum(w_i * (market_price - model_price)^2) where the weight is 1/market_price. The code is structured as follows: Random sample data from whole

问题 I am trying to run the following code, but there is an error in dvar float+ using CP; int rows=3; int columns=3; range para=1..rows*columns; float model1[para]=...; dvar float+ model0[para]; maximize sum(p in para) model0[p]*(lg(model0[p]/model1[p])); subject to{ c1: sum(p in para) model0[p]==3.0; } 回答1: Decision variables with CPOptimizer cannot be float. As can be seen in the example floatexpr.mod you can use a float dexpr in order to use decimal values computed out of a integer decision

问题 I am trying to minimize the following function using Linear programming. I am unable to include the image of my objective function. Click this Objective Function to view what I am trying to optimize. My question is there any library or function in python which can do this optimization for me or should I be writing the code? 回答1: import cvxpy as cp import numpy as np N=10 M=100 U = np.random.random((M,N)) m = np.random.random(M) t = cp.Variable(M) x = cp.Variable(N) prob = cp.Problem(cp

问题 I am attempting to load all js files using approach explained in this video @3:30 Optimize your code: load code at the right time I have implemented this approach in index.js as <script> var scripts = '<script src="./js/jquery-3.5.1.min.js"/>'+ '<script src="./js/jquery-ui.min.js"/>'+ '<script src="./js/bootstrap.min.js"/>'+ '<script src="./js/index.js"/>'; $(window).on("load",function(){ $("body").append(scripts) }); </script> also tried as in html head tag <script> var scripts = '<script

问题 I tested the following codes: void f1() { int x = 1; cout << "f1 : " << &x << endl; } void f2() { int x = 2; cout << "f2 : " << &x << endl; } void f3() { { int x = 3; cout << "f3_1: " << &x << endl; } { int x = 4; cout << "f3_2: " << &x << endl; } } int main() { f1(); f2(); f3(); } in release build, the output is... f1 : 00FAF780 f2 : 00FAF780 f3_1: 00FAF780 f3_2: 00FAF780 <-- I expected but in debug build, f1 : 012FF908 f2 : 012FF908 f3_1: 012FF908 f3_2: 012FF8FC <-- what?? I thought the

问题 I have the below VBA to extract data from the database: Sub Get_Data_from_DWH () Dim conn As New ADODB.Connection Dim rs As New ADODB.Recordset Dim dateVar As Date Set conn = New ADODB.Connection conn.ConnectionString = "DRIVER={MySQL ODBC 5.1 Driver}; SERVER=XX.XXX.XXX.XX; DATABASE=bi; UID=testuser; PWD=test; OPTION=3" conn.Open strSQL = " SELECT" & _ " product, brand, sales_channel," & _ " country, sales_manager, sales_date, return_date, " & _ " process_type, sale_quantity, return_quantity

问题 I am trying to use scipy.optimize.fsolve() to solve for x that makes the function equal to zero, but keep getting the error above. My code is: import scipy.optimize as optimize from scipy.stats import genextreme as gev gevcombined = [(-0.139, 3.035, 0.871),(-0.0863, 3.103, 0.818),(-0.198, 3.13, 0.982)] ratio = [0.225, 0.139, 0.294] P = [0.5,0.8,0.9,0.96,0.98,0.99] def mixedpop(x): for j in range(len(ratio)): F = (ratio[j]*gev.cdf(x,gevcombined[j][0],gevcombined[j][1],gevcombined[j][2]))+((1

问题 I am trying to use scipy.optimize.fsolve() to solve for x that makes the function equal to zero, but keep getting the error above. My code is: import scipy.optimize as optimize from scipy.stats import genextreme as gev gevcombined = [(-0.139, 3.035, 0.871),(-0.0863, 3.103, 0.818),(-0.198, 3.13, 0.982)] ratio = [0.225, 0.139, 0.294] P = [0.5,0.8,0.9,0.96,0.98,0.99] def mixedpop(x): for j in range(len(ratio)): F = (ratio[j]*gev.cdf(x,gevcombined[j][0],gevcombined[j][1],gevcombined[j][2]))+((1