[CPP] Template classes and functors

Template classes

In the last blog, we introduce template functions:
enter image description here
Also, we can make a template class, which is similar to generic class in Java.
enter image description here

  • Here is a simple version of linked list to store integer value
  • Let’s now using template to make it to store all kinds of data
  • Add prior to each member function definition: template < typename T>
  • Add the < T >to the end of the class name in the member function implementation/definition(if we have separate .h and .cpp file)
  • enter image description here
  • Still remember we use it in STL containers: vector<int> vector1;

Functors

Simple functors

functors are classes which overload () operator
enter image description here

Functors with member data

enter image description here

Functors taking variables by reference

enter image description here

Functors vs Functions

enter image description here
Here, what we did is to use a function pointer and apply function using this function pointer.
But now i want to make the function pointer to functors or make it to use both, what should i do?

  • Use Template!
    enter image description here

What we do here?!
Because function pointer and functor both use () operator, so it will work on both. Also, template is really nice and brilliant on this!
Also, functors are object, they behave like function but it is not a function! The most important thing about them is that they can store things in themselves

Another advanced way

  • < functional> header file
  • std::function< return type (param types) > function name
  • Template class, type specifies return type and parameters
  • Store, copy or invoke any callable of correct type, for example function pointer and functors
  • Useful if you need to store these things for calling later
  • enter image description here

评论

发表评论

此博客中的热门博文

[MLE] W2 Multivariate linear regression

图片
Multivariate linear regression What we have talked about in week 1 is linear regression with single feature. For example, in the house pricing predicting problem, we only use the size of house (x) to predict the price (y) . But what if there are other features like age, bedroom numbers and so on? Linear regression with multiple variables is also known as “multivariate linear regression” According to the graph above, we now have new representation symbols: n = number of features m = number of training examples \(x^{(i)}\) = \(i^{th}\) training example \(x^{(i)}_j\) = feature j in \(i^{th}\) training example 1416 is \(x_{1}^{(2)}\) in this case, m is 47 for example, n is 4. Hypothesis function The multivariable form of the hypothesis function accommodating these multiple features is as follows: if we make \(x_0\) to 1, the \(h_{\theta}(x)\) will be \(\theta^Tx\), which is \(\theta\) transpose matrix multiply by x, where \(\theta\) is a vector of 1 by(n+1) dimension an
阅读全文

[MLE] W1 Introduction

图片
Before get started The blog is based on the machine learning course on Coursera, taught by Andrew Ng . From today, i will begin my study trip on Machine learning, which will be labelled as MLE. This course will last 11 weeks and today is week 1. The application of machine learning is everywhere: Database mining Applications can’t program by hand Self-customizing program Understanding human learning(brain, real AI) Introduction What is Machine Learning Two definitions of machine learning are offered: Arthur Samuel described it as: “the field of study that gives computers the ability to learn without being explicitly programmed.” This is an older, informal definition. Tom Mitchell provides a more modern definition: “A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E.” If we raise a example of what is machine learning: If
阅读全文

[AIM] MetaHeuristics

图片
Day2 Outline Metaheuristics -definition Single point based search method(simple stochastic local search) Iterated local search Scheduling Tabu Search Metaheuristic what is a metaheuristic? A metaheuristic is a high-level problem independent algorithmic framework that provides a set of guidelines or strategies to develop heuristic optimization algorithms. what is the difference between heuristic and metaheuristic? Heuristic : Heuristics are problem-dependent techniques. As such, they usually are adapted to the problem at hand and they try to take full advantage of the particularities of this problem. However, because they are often too greedy, they usually get trapped in a local optimum and thus fail, in general, to obtain the global optimum solution. Metaheuristic : Meta-heuristics, on the other hand, are problem-independent techniques . As such, they do not take advantage of any specificity of the problem and, therefore, can be used as black boxes . In general, t
阅读全文