esmitt

#include <iostream.h> //example of operator overloading

template<class T>
class Stack {
public:
   Stack(int n); 
   Stack(Stack<T>& s); //copy constructor
   ~Stack() {delete [] stackPtr;}   // destructor
   Stack<T> operator +  (const Stack<T>& s2) const; //overloading +
   Stack<T>& operator = (const Stack<T>& s); //overloading assignment     

esmitt

# Numpy is needed because OpenCV images in python are actually numpy arrays.
import numpy
import cv2

class iris_detection():
    def __init__(self, image_path):
        '''
        initialize the class and set the class attributes
        '''
        self._img = None

esmitt

#include <windows.h>
#include <GLFW/glfw3.h>
#include <iostream>

// change this to int main() to allow the console
int WINAPI WinMain(HINSTANCE hInstance, HINSTANCE hPrevInstance, char*, int nShowCmd)
{
  GLFWwindow* window;
  int windowSizeW = 640, windowSizeH = 480;
  // initialize the library

esmitt

    import scipy.io as scio
    from typing import Any, Dict
    import numpy as np
    
    
    def load_matfile(filename: str) -> Dict:
        def parse_mat(element: Any):
            # lists (1D cell arrays usually) or numpy arrays as well
            if element.__class__ == np.ndarray and element.dtype == np.object_ and len(element.shape) > 0:
                return [parse_mat(entry) for entry in element]

esmitt

@echo off

REM Remove files generated by compiler in this directory and all subdirectories.
REM Essential release files are kept.

echo Removing "*.csproj.user" files...
for /f "delims==" %%i in ('dir /b /on /s "%~p0*.csproj.user"') do del "%%i" /f /q
echo.

echo Removing "*.exe.config" files...

esmitt

import sys
import pandas as pd

filename = sys.argv[1]
filename = filename[:-4]
read_file = pd.read_csv (filename + ".csv")
read_file.to_excel (filename + ".xlsx", index = None, header=True)

# run as 
# python csv_to_xlsx.py %1

esmitt

from tensorflow.keras import Model
from tensorflow.keras.layers import Convolution2D
from tensorflow.keras.layers import MaxPool2D
from tensorflow.keras.layers import BatchNormalization
from tensorflow.keras.layers import Input
from tensorflow.keras.layers import Flatten
from tensorflow.keras.layers import Dropout
from tensorflow.keras.layers import Dense
from tensorflow.keras.layers import concatenate
from tensorflow.keras.optimizers import Adam

esmitt

vtkNew<vtkCallbackCommand> keypressCallback;
  
auto KeypressCallbackFunction = [](vtkObject* caller, long unsigned int vtkNotUsed(eventId), void* clientData, void* vtkNotUsed(callData)) {
    vtkRenderWindowInteractor* iren = static_cast<vtkRenderWindowInteractor*>(caller);
    std::cout << "Pressed: " << iren->GetKeySym() << std::endl;
  };
keypressCallback->SetCallback(KeypressCallbackFunction);
renderWindowInteractor->AddObserver(vtkCommand::KeyPressEvent, keypressCallback);

esmitt

#include <iostream>
#include <string>
#include <sstream>

template <typename T>
std::string to_string_with_precision(const T a_value, const int n = 4)
{
  std::ostringstream out;
  out.precision(n);
  out << std::fixed << a_value;

esmitt

#include <iostream>
#include <chrono>

int main()
{
  std::cout << "Starting computation ..." << std::endl;
  auto start = std::chrono::steady_clock::now();
  // insert code to measure here
  auto end = std::chrono::steady_clock::now();
  auto diff = end - start;