optimization

Java script optimization for a google apps script

南楼画角 提交于 2021-01-29 02:26:37
问题 I have the working code below that compares two sets of data from two different sheets. One is a list of 395 phone numbers, the second is a list of around 135,000 rows of data. The following code compares the two for similarities and copies the similar row to a third sheet. While the code does work for small scale tests, (1000 rows and 395 phone numbers) in around 10 minutes. However doing 135,000 rows makes the script time out. Here is the script below. `function copyRowtoSheet3() { var s1 =

ValueError: The array returned by a function changed size between calls scipy.fsolve()

谁都会走 提交于 2021-01-29 02:25:58
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

Database tables optimized for both read and write

ぃ、小莉子 提交于 2021-01-28 22:58:38
问题 We have a web service that pumps data into 3 database tables and a web application that reads that data in aggregated format in a SQL Server + ASP.Net environment. There is so much data arriving to the database tables and so much data read from them and at such high velocity, that the system started to fail. The tables have indexes on them, one of them is unique. One of the tables has billions of records and occupies a few hundred gigabytes of disk space; the other table is a smaller one,

Efficient use of boolean true and false in C++?

对着背影说爱祢 提交于 2021-01-28 21:43:53
问题 Would any compiler experts be able to comment on the efficient use of boolean values? Specifically, is the compiler able to optimize a std::vector<boolean> to use minimal memory? Is there an equivalent data structure that would? Back in the day, there were languages that had compilers that could compress an array of booleans to a representation of just one bit per boolean value. Perhaps the best that could be done for C++ is to use std::vector<char> to store the boolean values for minimal

Efficient use of boolean true and false in C++?

廉价感情. 提交于 2021-01-28 21:06:39
问题 Would any compiler experts be able to comment on the efficient use of boolean values? Specifically, is the compiler able to optimize a std::vector<boolean> to use minimal memory? Is there an equivalent data structure that would? Back in the day, there were languages that had compilers that could compress an array of booleans to a representation of just one bit per boolean value. Perhaps the best that could be done for C++ is to use std::vector<char> to store the boolean values for minimal

How can I find k minimum bounding rectangles to enclose all the given points?

丶灬走出姿态 提交于 2021-01-28 20:27:48
问题 Given a parameter k for the number of boxes and n data points, is there anyway I can find or approximate k axis-aligned bounding rectangles that enclose all the points while keeping the sum of the area of the rectangles minimum? 回答1: One way is to directly write this as a mathematical optimization problem. A high-level optimization model can look like as follows: We first define the decision variables: r(k,c) = coordinates for k-th box (e.g. c={x,y,w,h}) continuous variable with appropriate

Is there a better way to get the gcd than using the Euclidean algorithm

半世苍凉 提交于 2021-01-28 19:35:17
问题 I am trying to find a faster lcm function than I currently have. I tried to look up some better gcd but couldn't find anything that solves the problem. #include <bits/stdc++.h> const int MOD = 1000000007; using namespace std; long gcd (long a, long b) { if (a == 0) return b; return gcd (b % a, a); } long lcm (long a, long b) { if (a == 0 || b == 0) return 0; return a * b / gcd (a, b); } 回答1: The mothed you showed is probably the fastest one, but if you want to avoid recursion, try this, it

Is there a better way to get the gcd than using the Euclidean algorithm

醉酒当歌 提交于 2021-01-28 19:20:54
问题 I am trying to find a faster lcm function than I currently have. I tried to look up some better gcd but couldn't find anything that solves the problem. #include <bits/stdc++.h> const int MOD = 1000000007; using namespace std; long gcd (long a, long b) { if (a == 0) return b; return gcd (b % a, a); } long lcm (long a, long b) { if (a == 0 || b == 0) return 0; return a * b / gcd (a, b); } 回答1: The mothed you showed is probably the fastest one, but if you want to avoid recursion, try this, it

Why there exist error Uncaught ReferenceError: $ is not defined if add async?

十年热恋 提交于 2021-01-28 18:31:43
问题 My index like this : ... <html > <head> ... <script src="/scripts/myapp.min.js"></script> <script src="/scripts/myapp-themming.min.js"></script> </head> <body class="header-static"> <div class="page-container"> <!-- this is call header, navigaton, content, footer --> </div> <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="/Content/assets/script/jquery-ui.min.js"></script> ... <script type="text/javascript"> ... <

How to obtain the objective function value and values of variables during each iteration of the algorithm using pymoo?

随声附和 提交于 2021-01-28 18:12:36
问题 I would like to get the values of objective and decision variables during each iteration of the algorithm. Is there any way of doing that? I tried to use history, but it doesn't contain the values. I'm trying to solve a single objective optimization problem using pymoo. This objective function is like a black box function, which is not in a nice closed form. f = objective(x, fitted_model, lam) g1 = x[:, 0] - 3.5 g2 = 1.14 - x[:, 0] g3 = x[:, 1] - 103 g4 = 44.4 - x[:, 1] g5 = x[:, 2] - 107 g6