I get an error when I use myRand::RandInt instead of something like default_random_engine. But I don't understand how am I supposed to implement the random_engine function. What I've done works well with std::random_shuffle, but I understand that this function was deprecated, and std::shuffle is preferred.
I am trying to get this to work:
int main()
{
std::vector<int> v = { 1, 2, 3, 4, 5, 6, 7, 8, 9 };
std::shuffle (v.begin(), v.end(), myRand::RandInt);
return 0;
}
I've defined a namespace to implement the functions:
namespace myRand {
bool simulatingRandom = false;
std::vector<int> secuenciaPseudoRandom = {1,0,1,0};
long unsigned int index = 0;
int Rand() {
//check
if (index > secuenciaPseudoRandom.size() - 1 ) {
index = 0;
std::cout << "Warning: myRand resetting secuence" << std::endl;
};
if (simulatingRandom) {
//std::cout << "myRand returning " << secuenciaPseudoRandom[i] << std::endl;
return secuenciaPseudoRandom[index++];
}
else {
return rand();
}
}
// works as rand() % i in the case of simulatingRandom == false
int RandInt(int i) {
return Rand() %i;
}
}
Basically I want to be able to change between simulating random and true random easily for testing purposes. So that in my main code I can do the testing with simulatingRandom set to true and then change it to false. Maybe there is a better way to do testing of functions that involves random. If so, I am open to any suggestions.
the last argument to std::shuffle must meet the requirements of UniformRandomBitGenerator. The generator should be an object not a function. For example a minimal implementation would be:
struct RandInt
{
using result_type = int;
static constexpr result_type min()
{
return 0;
}
static constexpr result_type max()
{
return RAND_MAX;
}
result_type operator()()
{
return Rand();
}
};
You can then call it as:
std::shuffle (v.begin(), v.end(), myRand::RandInt());
Note that you'l need to adjust the values of min and max if you set your simulatingRandom value to true to match the expected values. If they don't match the true values std::shuffle probably wont be as random as it should be.
Have to finish with the usual reminder not to use rand in modern code: Why is the use of rand() considered bad? especially without calling srand first. The use of rand is the main reason std::random_shuffle is deprecated.
Related
I am shifting from Python to C so bit rusty on the semantics as well as coding habit. In Python everything is treated as an object and objects are passed to functions. This is not the case in C so I want to increment an integer using pointers. What is the correct assignment to do so. I want to do it the following way but have the assignments wrong:
#include <stdio.h>
int i = 24;
int increment(*i){
*i++;
return i;
}
int main() {
increment(&i);
printf("i = %d, i);
return 0;
}
I fixed your program:
#include <stdio.h>
int i = 24;
// changed from i to j in order to avoid confusion.
// note you could declare the return type as void instead
int increment(int *j){
(*j)++;
return *j;
}
int main() {
increment(&i);
printf("i = %d", i);
return 0;
}
Your main error was the missing int in the function's argument (also a missing " in the printf).
Also I would prefer using parentheses in expressions as *j++ and specify exactly the precedence like I did in (*j)++, because I want to increment the content of the variable in the 'j' location not to increment the pointer - meaning to point it on the next memory cell - and then use its content.
I wrote the code below, but I get a notification saying No viable overloaded "=".
(Note that the list id contains some strings)
QList<QString>id;
QList<int>::iterator iter;
iter = std::find(logid.begin(), logid.end(), id);
The issue is that you are using the std::find function incorrectly. You are also trying to find inside a list another list.
Try this:
#include <QtDebug>
QList<int> logid = {1, 2, 3};
QList<QString> ids = {"2", "5"};
for (const auto &id : ids) {
auto it = std::find_if(logid.begin(), logid.end(), [&](const int x) {
return x == id.toInt();
});
if (it != logid.end()) {
// Valid item
qDebug() << "Address" << ⁢
qDebug() << "Value" << *it;
}
}
Note: since ids is a List of QString, you need to convert it to int.
I want to parallelize a function and have the problem that after a few hours my memory is overloaded.
The test program calculates something simple, and works so far. Only the memory usage is constantly increasing.
QT Project file:
QT -= gui
QT += concurrent widgets
CONFIG += c++11 console
CONFIG -= app_bundle
DEFINES += QT_DEPRECATED_WARNINGS
SOURCES += main.cpp
QT program file:
#include <QCoreApplication>
#include <qdebug.h>
#include <qtconcurrentrun.h>
double parallel_function(int instance){
return (double)(instance)*10.0;
}
int main(int argc, char *argv[])
{
QCoreApplication a(argc, argv);
int nr_of_threads = 8;
double result_sum,temp_var;
for(qint32 i = 0; i<100000000; i++){
QFuture<double> * future = new QFuture<double>[nr_of_threads];
for(int thread = 0; thread < nr_of_threads; thread++){
future[thread] = QtConcurrent::run(parallel_function,thread);
}
for(int thread = 0; thread < nr_of_threads; thread++){
future[thread].waitForFinished();
temp_var = future[thread].result();
qDebug()<<"result: " << temp_var;
result_sum += temp_var;
}
}
qDebug()<<"total: "<<result_sum;
return a.exec();
}
As I have observed, QtConcurrent::run(parallel_function,thread) allocates memory, but does not release memory after future[thread].waitForFinished().
What's wrong here?
You have memory leak because future array is not deleted. Add delete[] future at the end of outer for loop.
for(qint32 i = 0; i<100000000; i++)
{
QFuture<double> * future = new QFuture<double>[nr_of_threads];
for(int thread = 0; thread < nr_of_threads; thread++){
future[thread] = QtConcurrent::run(parallel_function,thread);
}
for(int thread = 0; thread < nr_of_threads; thread++){
future[thread].waitForFinished();
temp_var = future[thread].result();
qDebug()<<"result: " << temp_var;
result_sum += temp_var;
}
delete[] future; // <--
}
Here's how this might look - note how much simpler everything can be! You're dead set on doing manual memory management: why? First of all, QFuture is a value. You can store it very efficiently in any vector container that will manage the memory for you. You can iterate such a container using range-for. Etc.
QT = concurrent # dependencies are automatic, you don't use widgets
CONFIG += c++14 console
CONFIG -= app_bundle
SOURCES = main.cpp
Even though the example is synthetic and the map_function is very simple, it's worth considering how to do things most efficiently and expressively. Your algorithm is a typical map-reduce operation, and blockingMappedReduce has half the overhead of manually doing all of the work.
First of all, let's recast the original problem in C++, instead of some C-with-pluses Frankenstein.
// https://github.com/KubaO/stackoverflown/tree/master/questions/future-ranges-49107082
/* QtConcurrent will include QtCore as well */
#include <QtConcurrent>
#include <algorithm>
#include <iterator>
using result_type = double;
static result_type map_function(int instance){
return instance * result_type(10);
}
static void sum_modifier(result_type &result, result_type value) {
result += value;
}
static result_type sum_function(result_type result, result_type value) {
return result + value;
}
result_type sum_approach1(int const N) {
QVector<QFuture<result_type>> futures(N);
int id = 0;
for (auto &future : futures)
future = QtConcurrent::run(map_function, id++);
return std::accumulate(futures.cbegin(), futures.cend(), result_type{}, sum_function);
}
There is no manual memory management, and no explicit splitting into "threads" - that was pointless, since the concurrent execution platform is aware of how many threads there are. So this is already better!
But this seems quite wasteful: each future internally allocates at least once (!).
Instead of using futures explicitly for each result, we can use the map-reduce framework. To generate the sequence, we can define an iterator that provides the integers we wish to work on. The iterator can be a forward or a bidirectional one, and its implementation is the bare minimum needed by QtConcurrent framework.
#include <iterator>
template <typename tag> class num_iterator : public std::iterator<tag, int, int, const int*, int> {
int num = 0;
using self = num_iterator;
using base = std::iterator<tag, int, int, const int*, int>;
public:
explicit num_iterator(int num = 0) : num(num) {}
self &operator++() { num ++; return *this; }
self &operator--() { num --; return *this; }
self &operator+=(typename base::difference_type d) { num += d; return *this; }
friend typename base::difference_type operator-(self lhs, self rhs) { return lhs.num - rhs.num; }
bool operator==(self o) const { return num == o.num; }
bool operator!=(self o) const { return !(*this == o); }
typename base::reference operator*() const { return num; }
};
using num_f_iterator = num_iterator<std::forward_iterator_tag>;
result_type sum_approach2(int const N) {
auto results = QtConcurrent::blockingMapped<QVector<result_type>>(num_f_iterator{0}, num_f_iterator{N}, map_function);
return std::accumulate(results.cbegin(), results.cend(), result_type{}, sum_function);
}
using num_b_iterator = num_iterator<std::bidirectional_iterator_tag>;
result_type sum_approach3(int const N) {
auto results = QtConcurrent::blockingMapped<QVector<result_type>>(num_b_iterator{0}, num_b_iterator{N}, map_function);
return std::accumulate(results.cbegin(), results.cend(), result_type{}, sum_function);
}
Could we drop the std::accumulate and use blockingMappedReduced instead? Sure:
result_type sum_approach4(int const N) {
return QtConcurrent::blockingMappedReduced(num_b_iterator{0}, num_b_iterator{N},
map_function, sum_modifier);
}
We can also try a random access iterator:
using num_r_iterator = num_iterator<std::random_access_iterator_tag>;
result_type sum_approach5(int const N) {
return QtConcurrent::blockingMappedReduced(num_r_iterator{0}, num_r_iterator{N},
map_function, sum_modifier);
}
Finally, we can switch from using range-generating iterators, to a precomputed range:
#include <numeric>
result_type sum_approach6(int const N) {
QVector<int> sequence(N);
std::iota(sequence.begin(), sequence.end(), 0);
return QtConcurrent::blockingMappedReduced(sequence, map_function, sum_modifier);
}
Of course, our point is to benchmark it all:
template <typename F> void benchmark(F fun, double const N) {
QElapsedTimer timer;
timer.start();
auto result = fun(N);
qDebug() << "sum:" << fixed << result << "took" << timer.elapsed()/N << "ms/item";
}
int main() {
const int N = 1000000;
benchmark(sum_approach1, N);
benchmark(sum_approach2, N);
benchmark(sum_approach3, N);
benchmark(sum_approach4, N);
benchmark(sum_approach5, N);
benchmark(sum_approach6, N);
}
On my system, in release build, the output is:
sum: 4999995000000.000000 took 0.015778 ms/item
sum: 4999995000000.000000 took 0.003631 ms/item
sum: 4999995000000.000000 took 0.003610 ms/item
sum: 4999995000000.000000 took 0.005414 ms/item
sum: 4999995000000.000000 took 0.000011 ms/item
sum: 4999995000000.000000 took 0.000008 ms/item
Note how using map-reduce on a random-iterable sequence has over 3 orders of magnitude lower overhead than using QtConcurrent::run, and is 2 orders of magnitude faster than non-random-iterable solutions.
I've started learning C for Arduino for about 2 weeks. I have the following code and I don't understand how data is retrieved from function ReadLine. Also I don't understand how variable BufferCount affects the program and why it is used. I do know that it holds the number of digits the year have but that's about all I know about this variable.
From what I've learned so far a function is composed of:
function type specifier
function name
function arguments.
What I see in this program makes me think that the function can also return values using the argument part. I always thought that a function can only return a value that is the same type (int, boolean ...) as the type specifier.
void setup() {
Serial.begin(9600);
}
void loop() {
if (Serial.avaible() > 0) {
int bufferCount;
int year;
char myData[20];
bufferCount = ReadLine (myData);
year = atoi(myData); //convert string to int
Serial.print("Year: ");
Serial.print(year);
if (IsLeapYear(year)) {
Serial.print(" is ");
} else {
Serial.print(" is not ");
}
Serial.println("a leap year");
}
}
int IsLeapYear(int yr) {
if (yr % 4 == 0 && yr % 100 != 0 || yr % 400 == 0) {
return 1; //it's a leap year
} else {
return 0;
}
}
int ReadLine (char str[]) {
char c;
int index = 0;
while (true) {
if (Serial.available() > 0) {
c = Serial.read();
if (c != '\n') {
str[index++] = c;
} else {
str[index] = '\0'; //null termination character
break;
}
}
}
return index;
}
The fundamental concept you are missing is pointers. In the case of a function like isLeapYear there, you'd be right about that parameter. It is just a copy of the data from whatever variable was passed in when the function gets called.
But with ReadLine things are different. ReadLine is getting a pointer to a char array. A pointer is a special kind of variable that holds the memory address of another variable. And it is true that in this case you are getting a local copy of the pointer, but it still points to the same location in memory. And during the function, data is copied not into the variable str, but to the memory location it points to. Since that is a memory location that belongs to a variable in the scope of the calling function, that actual variable's value will be changed. You've written over it in memory.
For the quick sort algorithm(recursive), every time when it calls itself, it have the condition if(p < r). Please correct me if I am wrong: as far as I know, for every recursive algorithm, it has a condition as the time when it entered the routine, and this condition is used to get the base case. But I still cannot understand how to correctly set and test this condition ?
void quickSort(int* arr, int p, int r)
{
if(p < r)
{
int q = partition(arr,p,r);
quickSort(arr,p,q-1);
quickSort(arr,q+1,r);
}
}
For my entire code, please refer to the following:
/*
filename : main.c
description: quickSort algorithm
*/
#include<iostream>
using namespace std;
void exchange(int* val1, int* val2)
{
int temp = *val1;
*val1 = *val2;
*val2 = temp;
}
int partition(int* arr, int p, int r)
{
int x = arr[r];
int j = p;
int i = j-1;
while(j<=r-1)
{
if(arr[j] <= x)
{
i++;
// exchange arr[r] with arr[j]
exchange(&arr[i],&arr[j]);
}
j++;
}
exchange(&arr[i+1],&arr[r]);
return i+1;
}
void quickSort(int* arr, int p, int r)
{
if(p < r)
{
int q = partition(arr,p,r);
quickSort(arr,p,q-1);
quickSort(arr,q+1,r);
}
}
// driver program to test the quick sort algorithm
int main(int argc, const char* argv[])
{
int arr1[] = {13,19,9,5,12,8,7,4,21,2,6,11};
cout <<"The original array is: ";
for(int i=0; i<12; i++)
{
cout << arr1[i] << " ";
}
cout << "\n";
quickSort(arr1,0,11);
//print out the sorted array
cout <<"The sorted array is: ";
for(int i=0; i<12; i++)
{
cout << arr1[i] << " ";
}
cout << "\n";
cin.get();
return 0;
}
Your question is not quite clear, but I will try to answer.
Quicksort works by sorting smaller and smaller arrays. The base case is an array with less than 2 elements because no sorting would be required.
At each step it finds a partition value and makes it true that all the values to the left of the partition value are smaller and all values to the right of the partition value are larger. In other words, it puts the partition value in the correct place. Then it recursively sorts the array to the left of the partition and the array to right of the partition.
The base case of quicksort is an array with one element because a one element array requires no sorting. In your code, p is the index of the first element and r is the index of the last element. The predicate p < r is only true for an array of at least size 2. In other words, if p >= r then you have an array of size 1 (or zero, or nonsense) and there is no work to do.