What do you mean by the term web optimization?

What do you mean by the term web optimization?

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Mathematical Optimization – How to Get ReplaceAll Before the Function Call

I have a problem that I am trying to solve with NMinimize.

I have a scoring function, which will give me a final score. The problem has many variables, so instead of having them as parameters, they are assembled by variable name. Here is a simple example:

scoreResults = Function[
Module[{temp, i},
 temp = 0;
 Print["Checkpoint 0: " <> ToString[temp]];
 For[i = 0, i < 2, i++,
  temp = temp + ToExpression["aaa" <> ToString[i]];
  If[ToExpression["aaa" <> ToString[i]] > 300,
   temp = temp + 100000;
   ];
  Print["Checkpoint 1: " <> ToString[Evaluate[temp]]];
  ];
 Return[temp, Module];
 ]
];

Notice the If condition. Now, when I evaluate with ReplaceAll, I get the following:

scoreResults[] /. {aaa0 -> 123, aaa1 -> 456}
Checkpoint 0: 0
Checkpoint 1: aaa0
Checkpoint 1: aaa0 + aaa1
579

This is not correct! I think what happens is that the function is evaluated before replacing everything. Is it possible to get around this without having input parameters? My problem has a lot of variables and the scoring function will have a lot of nested for loops, so it's essential to assemble variable names on the fly in the scoring function. Even though I use input parameters for the function, I find that my ToExpression ["aaa" <> ToString [i]] is not effective.

In the end, I would like to use this notation function with NMinimize like this:

NMinimize[{scoreResults[], {aaa0 > 222, aaa1 > 333}}, {aaa0, aaa1}]

Currently, the answer that this gives me is false:

{555., {aaa0 -> 222., aaa1 -> 333.}}

Thank you in advance for your help, I have been trying to understand this for a while now. I understand that when I arrive in the NMinimize part, I will probably have to use NumericQ, but for the moment, I just have to overcome the initial problem, the function to produce the correct value, including If statement.

Optimization – Group the tuple list in the dictionary optimally in Python

I have a list of tuples with the following structure:

lista = (('A', 25.5), ('B', 0.14), ('C', 0.0),('A', 28), ('C', 0.3), ('B', 0.18), ('A', 23))

I just put A, B and C But it can contain more types.

From this structure, I wish to group them in a dictionary in order to obtain the following result:

salida = {'A': (25.5, 28, 23), 'B': (0.14, 0.18), 'C': (0.0, 0.3)}

I managed to do it with the code transformation function that I put next, but I will have to do it with millions of disks, so it would have to be optimized, because it is likely there are better ways, but I have already struggled a lot with that.

To test, I created a list of 40 million tuples with the function listaPrueba and with the transformation function I took 19.63 seconds.
If someone finds a more effective way, I would appreciate it.

import itertools
import time

numero = 10000000

def listaPrueba(num):
    return (('A', 1), ('B', 2), ('C', 3), ('D', 4)) * num
lst_Pruebas = listaPrueba(numero)


def transformar(lista, diccionario={}):
    for clave, grupo in itertools.groupby(lista, lambda x: x(0)):
        for elemento in grupo:
            diccionario.setdefault(clave, ()).append(elemento(1))
    return diccionario


inicio = time.perf_counter()
salida = transformar(lst_Pruebas)

print(f'Tiempo: {time.perf_counter()-inicio}')


assert sum(salida('A')) == numero * 1
assert sum(salida('B')) == numero * 2
assert sum(salida('C')) == numero * 3
assert sum(salida('D')) == numero * 4

I've used itertools because I imagine it will be optimized for iterations, but I'm not sure, so I do not care how to fix it.

selenium – Python script for parsing links optimization?

I wrote a test that parses links from a web page and a loop clicks on each of them, and then returns to the main page. But, it is accompanied by the whole web page again and again and overwriting the links array, although only one link is needed per iteration. I understand that this is inefficient. How can I optimize this?

I tried the links only once and then iterating through them in a loop. After the first iteration, it goes back to the second page, but it is not interactive (I think it is because of the web elements that are stored in the links page).

def setUp(self):
    self.driver = webdriver.Chrome()
    self.driver.get('https://yandex.ru')

def test_01(self): 
    driver = self.driver
    links = ()
    time.sleep(3)
    links = driver.find_elements_by_css_selector("a")
    for i in range(len(links)):
        links = driver.find_elements_by_css_selector("a")
        links(i).click()
        driver.get('https://yandex.ru')
        time.sleep(3)

Is it more efficient possible solution?

optimization – Can we reduce the maximization of this integral to maximizing the integrator?

I would like to know if we are able to reduce the following optimization problem to the ad hoc optimization of integrand: Maximize $$ sum_ {i in I} sum_ {j in I} int lambda ({ rm d} x) int lambda ({ rm}} y) left (w_i (x) p (x) q_j (y) wedge w_j (y) p (y) q_i (x) right) sigma_ {ij} (x, y) | g (x) -g (y) | ^ 2 $$ (as usual, $ a corner b: = min (a, b) = frac {a + b- | a-b |} $ 2 for $ a, b in mathbb R $) regarding the family $ (w_i) _ {i in I} $ and subject to the constraints begin {equation}
{q_i = 0 } subseteq {w_ip = 0 } ; ; ; text {for all} i in I
end {equation}
and begin {equation}
{p ne0 subseteq left { sum_ {i in I} w_i = 1 right },
end {equation}

or

  • $ (E, mathcal E, lambda) $ is a measurement space;
  • $ I $ is a non-empty finite set;
  • $ p, q_i: E to (0, infty) $ are $ mathcal E $-measurable with $$ int p : { rm}} lambda = int q_i : { rm d} lambda = 1 $$ for $ i in I $;
  • $ g in L ^ 2 (p lambda) $;
  • $ w_i: E to (0,1) $ is $ mathcal E $-measurable for $ i in I $;
  • $ sigma_ {ij}: E ^ 2 to (0, infty) $ is $ mathcal E ^ { otimes2} $-measurable for $ i, j in I $ with $$ sigma_ {ij} (x, y) = sigma_ {ji} (y, x) ; ; ; text {for all} x, y in E text {and} i, j in I $$ and $$ sum_ {j in I} int lambda { rd} y) q_j (y) sigma_ {ij} (x, y) = 1. $$

It is clear that the increase in the integral will increase the integral, but my problem is the integral product shape.

optimization – How to use domains without cookies with the Microsoft Azure portal?

My website is installed on the Microsoft Azure portal. My website using asp.net and framework (sitecore cms). That's C #.

I have checked my website with gtmetrix. He recommends using domains without cookies.

I want to try it, but I'm confused as to how to configure this under the Azure portal. I'm afraid this will bring down the server. How can I do this?

Optimization – How to use fields without cookies in the Azure portal?

My website installed in the azure portal (http://portal.azure.com). My website using asp.net and framework (sitecore cms). That's C #

When I visit my website with gtmetrix (https://gtmetrix.com/). There is a recommendation to use domains without cookies

I'm trying to search for a reference and its recommendation to create separate domains and subdomains to serve cookies

I want to try it. But I am confused to set up in the portal azure

I fear that this will cause the server. So I ask the & # 39; help here. How can I do this?

optimization – Query products count in the category using knuckles and indexes, but are too slow, can they be optimized?

I have selected (used to give me a number of products activated in the category with a price> 0):

SELECT COUNT(DISTINCT p.id) as ccount
FROM product p
 JOIN product_php_display_price ppdp ON ppdp.shop_id = 1 AND p.id = ppdp.product_id AND
ppdp.currency_id = 1
 JOIN shop_product_tree spt ON p.id = spt.product_id AND spt.shop_id = 1
 AND (state = "enabled" OR state = "disabled_for_buy")
 AND ppdp.php_display_price > 0

There are multicolumn indexes for each table used (also several different multicolumn indexes).

The product_php_display_price table has a multicolumn index (shop_id, product_id, currency_id, php_display_price).

The table product uses index (product_id, state).

Each table has 208,000 rows. Is there a way, how to speed that up? On my local machine, it takes about 2 seconds. Thank you.

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optimization – Perpendicular vectors of a set

I came across this problem and I want to know if there is a better solution.
There are n 3d vectors with the x, y and z components and I want to find all the perpendicular vector pairs in this set. Is there a better way than to check all possible pairs of 3 vectors, a kind of optimization (not the most obvious ones)?