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What the efficient way to create a vector of point clouds used as a buffer in order to store multi-scanning point clouds
Starting C++11, you can use std::vector as an RAII buffer.
Instead of allocating the space yourself using new and then having to delete the pointer to avoid memory leaks, you can simply create an std::vector and pre-allocate it so that it can be used a a buffer:
(some of this is some pseudo code since I'm not familiar with point clouds)
#include <vector>
constexpr unsigned int numberOfPoints = 100;
std::vector<point_clouds> buffer(numberOfPoints);
scan_point_clound_func(buffer.data(), buffer.size());
point_cloud p = buffer[0];
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I'm trying to open a .bin file in Matlab. The file is a xcat phantom of human body.
dims: 320,128,666
vxsize: 2.5,2.5,2.5
data type: 32-bit float, littleendian
And what I want is to open/see image of a specific slice of this file.
The XCAT phantom comes in raw format. Just use fopen, fread (with the precision flag set to the correct type) and fclose. Then you will likely need to reshape what fread returns.
Once you have the 3D image in MATLAB, then just slice it with indexes img(:,100,:)
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I am not able to figure out difference between vector<set <int >> v(26) and vector<set < int > > v[26]. Please if possible explain how they work and how are they different with example.
Both are invalid declarations. One is an illegal declaration of one vector with 26 elements and the other is an illegal declaration of an array of 26 vectors.
set is a class template and needs a type to be used.
Example:
vector<set<int>> v(26); // a vector with 26 sets of int
vector<set<int>> v[26]; // an array of 26 vectors of set of ints
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I want to align a pair of long texts with ~20M chars each.
I've used in the past Smith-Waterman algorithm but (from my limited understanding) it requires creating a 2-dimensional array with the size of the texts (20M by 20M array) - which is not practical.
So I'm looking for an algorithm to align a pair of long texts that will keep a practical memory size and execution time.
UPDATE
I've also tried Myers and Miller using this implementation: https://www.codeproject.com/Articles/42279/Investigating-Myers-diff-algorithm-Part-of
But I still got out of memory exception on "not so large" texts (1MB).
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The following is an interview question which shows up here and here:
Given a timer time() with nanosecond accuracy and given the interface
interface RealTimeCounter:
void increment()
int getCountInLastSecond()
int getCountInLastMinute()
int getCountInLastHour()
int getCountInLastDay()
The getCountInLastX functions should return the number of times increment was called in the last X
Here's one suggested solution (paraphrased from the above blog entry):
Maintain an ArrayList of timestamps. When asked for a given counter, let's say, the count for the last second, perform a binary search for (timer.time() - ONE_SECOND_IN_NANOSECONDS), and return the list.length() - list_index. Then, as a background process at regular intervals we trim our data. Since we only need to maintain data for the last day, we can delete all entries prior to the last day.
Please critique this solution or offer a better performing one.
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I am working on some sample program and trying to use matrix functionalities offered by Eigen3 library.
I want to store high precision integer variable(mpz_t) in a (100,100) matrix. For storing integer, there is already inbuilt data type MatrixXd. Similarly, just wanted it for high precision variables. Please share some advices.
Thanks.
Basically, all you need to do is declare a Matrix<mpz_class,Dynamic,Dynamic> matrix. The mpz_class type is a c++ wrapper around mpz_t such that it behaves like any scalar type.
Here is an example:
#include <Eigen/Core>
#include <gmpxx.h>
using namespace Eigen;
typedef Matrix<mpz_class,Dynamic,Dynamic> MatrixXz;
int main() {
MatrixXz A(10,10), B(10,10), C(10,10);
A.fill(111);
B.fill(222);
C = 2*A + B;
}