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With such a huge number of choices it may be hard to find the right designer for your specific needs. Toogit is always there to help you make the right choice when choosing a logo designer. These points could also be useful when hiring a web designer, graphic designer, or any designer for that matter.

I don’t want this post to come across as self promotional, however, I’ve linked to my own examples to show you how I personally communicate to potential clients the value of my design work. For other designers, I hope this in turn, gives you an idea of how you too can communicate the value of your work.

In no particular order:

  1. Experience : Previous identity projects will give you a good idea of what skill level your designer is at and what you can expect though this is not to say that a new designer can not produce top quality results – this point has to be considered with all of the other points mentioned below, in which case a strong portfolio is probably the best indicator.
  2. Positive Testimonials : Have they got positive testimonials from past clients and colleagues? Ensure you check the testimonials validity which can be done by looking for a web address or even by emailing the company. It’s a good idea to check if the company even exists.
  3. A Thorough Design Process : Do they have a logo design process in which they follow or are they simply producing logos like fast food? A typical process does not take under 24 hours to complete.
  4. Awards Won / Published Work : Have they won any awards for their work? Is their work published in any books or magazines? How recognised are they in the industry?
  5. A Strong Portfolio : How strong is their portfolio?   What is the make up of real to ‘fake’ logo designs? When I say ‘fake logos’ I refer to the logos made for fictional companies, rather than for real clients.
  6. Price : The price of the service is usually quite evident of what he is going to deliver. In most cases, freelancer should deliver what you pay for but don’t take price as the only indication. How much does a logo design actually cost? In my experience, this is the most frequently asked question and the hardest to answer. This is because every company has different requirements the best approach is to draw up a customised quote for each individual client.
  7. Design Affiliations : Are they affiliated with any design associations or publications? This is a good indication of how dedicated they are to their craft though is not at all essential.
  8. Great Customer Service : Do they respond to your emails quickly? How do they communicate & present themselves? A designer should provide great customer service throughout the whole process, from the initial email right through to after sales support.
  9. Business Professionalism : Attention to detail, trustworthiness, strong communication skills and time management are all vital and go hand in hand with great customer service.
  10. Appropriate Questions : A designer should ask a no of questions to find out your needs in relation to your business goals. Questions should revolve around the companies history, target market, competitors, company goals, etc.

Optimization deals with selecting the simplest option among a number of possible choices that are feasible or do not violate constraints. Python is used to optimize parameters in a model to best fit data, increase profitability of a possible engineering style, or meet another form of objective which will be described mathematically with variables and equations.

 

pyOpt is a Python-based package for formulating and solving nonlinear constrained optimization problems in an efficient, reusable and portable manner. Python programming uses object-oriented concepts, such as class inheritance and operator overloading, to maintain a distinct separation between the problem formulation and the optimization approach used to solve the problem.

 

All optimisation downside solvers inherit from the Optimizer abstract category. The category attributes include the solver name (name), an optimizer kind symbol (category), and dictionaries that contain the solver setup parameters (options) and message output settings (informs). The class provides ways to check and alter default solver parameters (getOption, setOption), as well as a method that runs the solver for a given optimisation problem (solve).

 

Optimization solver

A number of constrained optimization solvers are designed to solve the general nonlinear optimization problem.

  1. PSQP: This optimizer is a preconditioned sequential quadratic programming algorithm. This optimizer implements a sequential quadratic programming method with a BFGS variable metric update.
  2. SLSQP: This optimizer is a sequential least squares programming algorithm. SLSQP uses the Han–Powell quasi-Newton method with a BFGS update of the B-matrix and an L1-test function in the step-length algorithm. The optimizer uses a slightly modified version of Lawson and Hanson’s NNLS nonlinear least-squares solver.
  3. CONMIN: This optimizer implements the method of feasible directions. CONMIN solves the nonlinear programming problem by moving from one feasible point to an improved one by choosing at each iteration a feasible direction and step size that improves the objective function.
  4. COBYLA: It is an implementation of Powell’s nonlinear derivative–free constrained optimization that uses a linear approximation approach. The algorithm is a sequential trust–region algorithm that employs linear approximations to the objective and constraint functions.
  5. SOLVOPT: SOLVOPT is a modified version of Shor’s r–algorithm with space dilation to find a local minimum of nonlinear and non–smooth problems.
  6. KSOPT: This code reformulates the constrained problem into an unconstrained one using a composite Kreisselmeier–Steinhauser objective function to create an envelope of the objective function and set of constraints. The envelope function is then optimized using a sequential unconstrained minimization technique.
  7. NSGA2: This optimizer is a non-dominating sorting genetic algorithm that solves non-convex and non-smooth single and multiobjective optimization problems.
  8. ALGENCAN: It solves the general non-linear constrained optimization problem without resorting to the use of matrix manipulations. It uses instead an Augmented Lagrangian approach which is able to solve extremely large problems with moderate computer time.
  9. FILTERSD: It use of a Ritz values approach Linear Constraint Problem solver. Second derivatives and storage of an approximate reduced Hessian matrix is avoided using a limited memory spectral gradient approach based on Ritz values.

 

To solve an optimization problem with pyOpt an optimizer must be initialized. The initialization of one or more optimizers is independent of the initialization of any number of optimization problems. To initialize SLSQP, which is an open-source, sequential least squares programming algorithm that comes as part of the pyOpt package, use:

>>> slsqp = pyOpt.SLSQP()

This initializes an instance of SLSQP with the default options. The setOption method can be used to change any optimizer specific option, for example the internal output flag of SLSQP:

>>> slsqp.setOption('IPRINT', -1)

Now Schittkowski’s constrained problem can be solved using SLSQP and for example, pyOpt’s automatic finite difference for the gradients:

>>> [fstr, xstr, inform] = slsqp(opt_prob,sens_type='FD')

By default, the solution information of an optimizer is also stored in the specific optimization problem. To output solution to the screen one can use:

>>> print opt_prob.solution(0)

 

Example:

The problem is taken from the set of nonlinear programming examples by Hock and Schittkowski and it is defined as

=======================================================================

      min            − x1x2x3

     x1,x2,x3

 

subjected to     x1 + 2x2 + 2x3 − 72 ≤ 0

                        − x1 − 2x2 − 2x3 ≤ 0

 

                        0 ≤ x1 ≤ 42

                        0 ≤ x2 ≤ 42

                        0 ≤ x3 ≤ 42

 

The optimum of this problem is at (x1∗ , x2∗ , x3* ) = (24, 12, 12), with an objective function value of f ∗ = −3456, and constraint values g (x∗ ) = (0, −72).

 

#======================================================================

# Standard Python modules

#======================================================================

import os, sys, time

import pdb

#======================================================================

# Extension modules

#======================================================================

#from pyOpt import *

from pyOpt import Optimization

from pyOpt import PSQP

from pyOpt import SLSQP

from pyOpt import CONMIN

from pyOpt import COBYLA

from pyOpt import SOLVOPT

from pyOpt import KSOPT

from pyOpt import NSGA2

from pyOpt import ALGENCAN

from pyOpt import FILTERSD

 

#======================================================================

def objfunc(x):

   

    f = -x[0]*x[1]*x[2]

    g = [0.0]*2

    g[0] = x[0] + 2.*x[1] + 2.*x[2] - 72.0

    g[1] = -x[0] - 2.*x[1] - 2.*x[2]

   

    fail = 0

    return f,g, fail  

 

#======================================================================

# Instantiate Optimization Problem

opt_prob = Optimization('Hock and Schittkowski Constrained Problem',objfunc)

opt_prob.addVar('x1','c',lower=0.0,upper=42.0,value=10.0)

opt_prob.addVar('x2','c',lower=0.0,upper=42.0,value=10.0)

opt_prob.addVar('x3','c',lower=0.0,upper=42.0,value=10.0)

opt_prob.addObj('f')

opt_prob.addCon('g1','i')

opt_prob.addCon('g2','i')

print opt_prob

 

# Instantiate Optimizer (PSQP) & Solve Problem

psqp = PSQP()

psqp.setOption('IPRINT',0)

psqp(opt_prob,sens_type='FD')

print opt_prob.solution(0)

 

# Instantiate Optimizer (SLSQP) & Solve Problem

slsqp = SLSQP()

slsqp.setOption('IPRINT',-1)

slsqp(opt_prob,sens_type='FD')

print opt_prob.solution(1)

 

# Instantiate Optimizer (CONMIN) & Solve Problem

conmin = CONMIN()

conmin.setOption('IPRINT',0)

conmin(opt_prob,sens_type='CS')

print opt_prob.solution(2)

 

# Instantiate Optimizer (COBYLA) & Solve Problem

cobyla = COBYLA()

cobyla.setOption('IPRINT',0)

cobyla(opt_prob)

print opt_prob.solution(3)

 

# Instantiate Optimizer (SOLVOPT) & Solve Problem

solvopt = SOLVOPT()

solvopt.setOption('iprint',-1)

solvopt(opt_prob,sens_type='FD')

print opt_prob.solution(4)

 

# Instantiate Optimizer (KSOPT) & Solve Problem

ksopt = KSOPT()

ksopt.setOption('IPRINT',0)

ksopt(opt_prob,sens_type='FD')

print opt_prob.solution(5)

 

# Instantiate Optimizer (NSGA2) & Solve Problem

nsga2 = NSGA2()

nsga2.setOption('PrintOut',0)

nsga2(opt_prob)

print opt_prob.solution(6)

 

# Instantiate Optimizer (ALGENCAN) & Solve Problem

algencan = ALGENCAN()

algencan.setOption('iprint',0)

algencan(opt_prob)

print opt_prob.solution(7)

 

# Instantiate Optimizer (FILTERSD) & Solve Problem

filtersd = FILTERSD()

filtersd.setOption('iprint',0)

filtersd(opt_prob)

print opt_prob.solution(8)

 

Solving non-linear global optimization problems could be tedious task sometimes. If the problem is not that complex then general purpose solvers could work. However, as the complexity of problem increases, general purpose global optimizers start to take time. That is when need to create your problem specific fast and direct global optimizer’s need arises.

 

We have an specialized team with PHD holders and coders to design and develop customized global optimizers. If you need help with one, please feel free to send your queries to us.

 

We first understand the problem and data by visualizing it. After that we create a solution to your needs.

 

Please do read to understand what a solver is and how it works - If you want to create your own simple solver. This is not exactly how every solver works, however, this will give you a pretty solid idea of what is a solver and how it is supposed to work.

As you know, JavaScript is the top programming language in the world, the language of the web, of mobile hybrid apps (like PhoneGap or Appcelerator), of the server side (like NodeJS or Wakanda) and has many other implementations. It’s also the starting point for many new developers to the world of programming, as it can be used to display a simple alert in the web browser but also to control a robot (using nodebot, or nodruino). The developers who master JavaScript and write organized and performant code have become the most sought after in the job market.

 

In this article, I’ll share a set of JavaScript tips, tricks and best practices that should be known by all JavaScript developers regardless of their browser/engine or the SSJS (Server Side JavaScript) interpreter.

 

Don’t forget var” keyword when assigning a variable’s value for the first time.

Assignment to an undeclared variable automatically results in a global variable being created. Avoid global variables.

Use “===” instead of “==”

The == (or !=) operator performs an automatic type conversion if needed. The === (or !==) operator will not perform any conversion. It compares the value and the type, which could be considered faster than ==

[10] === 10    // is false

[10]  == 10    // is true

'10' == 10     // is true

'10' === 10    // is false

 []   == 0     // is true

 [] ===  0     // is false

 '' == false   // is true but true == "a" is false

 '' ===   false // is false 

undefined, null, 0, false, NaN, '' (empty string) are all falsy.

 

Use Semicolons for line termination

The use of semi-colons for line termination is a good practice. You won’t be warned if you forget it, because in most cases it will be inserted by the JavaScript parser. For more details about why you should use semi-colons.

 

Create an object constructor

function Person(firstName, lastName){

    this.firstName =  firstName;

    this.lastName = lastName;        

}  

var Khalid = new Person("Khalid", "Ansari");

 

Be careful when using typeof, instanceof and constructor.

typeof: a JavaScript unary operator used to return a string that represents the primitive type of a variable, don’t forget that typeof null will return “object”, and for the majority of object types (Array, Date, and others) will return also “object”.

constructor: is a property of the internal prototype property, which could be overridden by code.

 

instanceof: is another JavaScript operator that check in all the prototypes chain the constructor it returns true if it’s found and false if not.

 

var arr = ["a", "b", "c"];

typeof arr;   // return "object" 

arr  instanceof Array // true

arr.constructor();  //[]

 

Define a Self-calling Function

This is often called a Self-Invoked Anonymous Function or Immediately Invoked Function Expression (IIFE). It is a function that executes automatically when you create it, If you want to use this function you can write in the following way: 

 

(function(){

    // some private code that will be executed automatically

})();  

(function(p,q){

    var r = p+q;

    return r;

})(40,50);

 

Get a random item from an array

var items_array = [12, 548 , 'a' , 2 , 5478 , 'toogit' , 8852, , 'freelance' , 2145 , 119];

var  randomItem = items[Math.floor(Math.random() * items.length)];

 

Get a random number in a specific range

This code snippet can be useful when trying to generate fake data for testing purposes, such as a salary between min and max.

var x = Math.floor(Math.random() * (max - min + 1)) + min;

 

Generate an array of numbers with numbers from 0 to max

var numbersArray = [] , max = 100;

for( var i=1; numbersArray.push(i++) < max;);  // numbers = [1,2,3 ... 100] 

 

Generate a random set of alphanumeric characters

function generateRandomAlphaNum(len) {

    var rdmString = "";

    for( ; rdmString.length < len; rdmString  += Math.random().toString(36).substr(2));

    return  rdmString.substr(0, len);

}

 

Shuffle an array of numbers

var numbers = [5, 458 , 120 , -215 , 228 , 400 , 122205, -85411];

numbers = numbers.sort(function(){ return Math.random() - 0.5});

 

A better option could be to implement a random sort order by code (e.g. : Fisher-Yates shuffle), than using the native sort JavaScript function

 

A string trim function

The classic trim function of Java, C#, PHP and many other language that remove whitespace from a string doesn’t exist in JavaScript, so we could add it to the String object.

String.prototype.trim = function(){return this.replace(/^s+|s+$/g, "");};  

A native implementation of the trim() function is available in the recent JavaScript engines.

 

Append an array to another array

var array1 = [12 , "foo" , {name "Joe"} , -2458];

var array2 = ["Doe" , 555 , 100];

Array.prototype.push.apply(array1, array2);

 

Transform the arguments object into an array

var argArray = Array.prototype.slice.call(arguments);

 

Verify that a given argument is a number

function isNumber(n){

    return !isNaN(parseFloat(n)) && isFinite(n);

}

 

Verify that a given argument is an array

function isArray(obj){

    return Object.prototype.toString.call(obj) === '[object Array]' ;

}

Note that if the toString() method is overridden, you will not get the expected result using this trick.

Or Use..

Array.isArray(obj); // its a new Array method

You could also use instanceofif you are not working with multiple frames. However, if you have many contexts, you will get a wrong result.

var myFrame = document.createElement('iframe');

document.body.appendChild(myFrame);

var myArray = window.frames[window.frames.length-1].Array;

var arr = new myArray(a,b,10); // [a,b,10]  

// instanceof will not work correctly, myArray loses his constructor 

// constructor is not shared between frames

arr instanceof Array; // false

 

Get the max or the min in an array of numbers

var  numbers = [5, 458 , 120 , -215 , 228 , 400 , 122205, -85411]; 

var maxInNumbers = Math.max.apply(Math, numbers); 

var minInNumbers = Math.min.apply(Math, numbers);

 

Empty an array

var myArray = [12 , 222 , 1000 ];  

myArray.length = 0; // myArray will be equal to [].

 

Don’t use delete to remove an item from array

Use splice instead of using delete to delete an item from an array. Using delete replaces the item with undefined instead of the removing it from the array.

Instead of…

var items = [12, 548 ,'a' , 2 , 5478 , 'foo' , 8852, , 'Doe' ,2154 , 119 ]; 

items.length; // return 11 

delete items[3]; // return true 

items.length; // return 11 

Use

var items = [12, 548 ,'a' , 2 , 5478 , 'foo' , 8852, , 'Doe' ,2154 , 119 ]; 

items.length; // return 11 

items.splice(3,1) ; 

items.length; // return 10 

 

Clearing or truncating an array

An easy way of clearing or truncating an array without reassigning it is by changing its length property value:

const arr = [11,22,33,44,55,66];

// truncanting

arr.length = 3;

console.log(arr); //=> [11, 22, 33]

// clearing

arr.length = 0;

console.log(arr); //=> []

console.log(arr[2]); //=> undefined

 

Simulating named parameters with object destructuring

Chances are high that you’re already using configuration objects when you need to pass a variable set of options to some function, like this:

doSomething({ foo: 'Hello', bar: 'Toogit!', baz: 42 });

function doSomething(config) {  

const foo = config.foo !== undefined ? config.foo : 'Hi';  const bar = config.bar !== undefined ? config.bar : 'Me!';  const baz = config.baz !== undefined ? config.baz : 13;  // ...

}

This is an old but effective pattern, which tries to simulate named parameters in JavaScript. The function calling looks fine. On the other hand, the config object handling logic is unnecessarily verbose. With ES2015 object destructuring, you can circumvent this downside:

function doSomething({ foo = 'Hello', bar = 'Toogit!', baz = 13 }) {  // ...}

And if you need to make the config object optional, it’s very simple, too:

function doSomething({ foo = 'Hello', bar = 'Toogit!', baz = 13 } = {}) {  // ...}

 

Object destructuring for array items

Assign array items to individual variables with object destructuring:

const csvFileLine = '1997,John Doe,US,john@doe.com,New York';const { 2: country, 4: state } = csvFileLine.split(',');

 

 

What is the difference between Java and JavaScript?

 

These are two different programming languages.

 

Javascript is a language that has gained tremendous popularity as a language on the web browsers to create dynamic and interactive web pages.

 

Java is a language that has got a similar popularity when you build a “backend” system, which is a fancy word for “almost anything”.

 

Despite the common prefix, they are not related; there creators are different and so are their origin stories (as highlighted by other answers). 

- JavaScript is a genius marketing scam that polluted the world of browsers exceptionally well. The browser reads JavaScript’s code line by line and executes it.

 

- Java is a general purpose language that is used almost everywhere, from Android mobile apps and cryptography to OS and cloud computing. Java’s code is stored in bytecoded format and then gets JIT compiled before the actual execution. In other words, it translates the bytecode to machine code.

 

- Java is class based. JS is prototype based. All objects, like Array or Function inherit from the Object.prototype which remains on top of the chain.

 

- JavaScript uses dynamic type checking (checks the variables while the code executes), unlike Java’s static checking system (variables are verified at compile time), which is more bug free.

 

- The word “Script.” It’s a joke, in case you didn’t get it.

 

 

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