Math.NET C#（開發者的工作原理）

using MathNet.Numerics;

public class BasicMathOperations
{
    public void PerformCalculations()
    {
        // Example of basic arithmetic operation
        // Using basic trigonometric function from Math.NET
        double result = 2 * MathNet.Numerics.Trig.Cos(45);
        Console.WriteLine($"The result is: {result}");
    }
}

Imports MathNet.Numerics

Public Class BasicMathOperations
	Public Sub PerformCalculations()
		' Example of basic arithmetic operation
		' Using basic trigonometric function from Math.NET
		Dim result As Double = 2 * MathNet.Numerics.Trig.Cos(45)
		Console.WriteLine($"The result is: {result}")
	End Sub
End Class

using MathNet.Numerics.Statistics;
using System;

public class CrimeDataAnalysis
{
    public void AnalyzeCrimeData()
    {
        // Hypothetical crime rate data for a series of districts
        var crimeRates = new double[] { 5.2, 3.8, 4.6, 2.9, 3.5 };

        // Calculating statistical metrics to understand crime trends
        double meanCrimeRate = Statistics.Mean(crimeRates);
        double varianceCrimeRate = Statistics.Variance(crimeRates);

        // Outputting the analysis results
        Console.WriteLine($"Average Crime Rate: {meanCrimeRate}, Variance in Crime Rate: {varianceCrimeRate}");

        // Additional analysis can be added here to further assist in the crime-solving process
        // For instance, correlating crime rates with different variables (like time, location, etc.)
    }
}

class Program
{
    static void Main(string[] args)
    {
        // Simulating a scenario where LAPD and New York City start collaborating using statistical analysis
        Console.WriteLine("Los Angeles Police Department and New York City Precinct Collaboration:");
        CrimeDataAnalysis crimeDataAnalysis = new CrimeDataAnalysis();
        crimeDataAnalysis.AnalyzeCrimeData();
    }
}

Imports MathNet.Numerics.Statistics
Imports System

Public Class CrimeDataAnalysis
	Public Sub AnalyzeCrimeData()
		' Hypothetical crime rate data for a series of districts
		Dim crimeRates = New Double() { 5.2, 3.8, 4.6, 2.9, 3.5 }

		' Calculating statistical metrics to understand crime trends
		Dim meanCrimeRate As Double = Statistics.Mean(crimeRates)
		Dim varianceCrimeRate As Double = Statistics.Variance(crimeRates)

		' Outputting the analysis results
		Console.WriteLine($"Average Crime Rate: {meanCrimeRate}, Variance in Crime Rate: {varianceCrimeRate}")

		' Additional analysis can be added here to further assist in the crime-solving process
		' For instance, correlating crime rates with different variables (like time, location, etc.)
	End Sub
End Class

Friend Class Program
	Shared Sub Main(ByVal args() As String)
		' Simulating a scenario where LAPD and New York City start collaborating using statistical analysis
		Console.WriteLine("Los Angeles Police Department and New York City Precinct Collaboration:")
		Dim crimeDataAnalysis As New CrimeDataAnalysis()
		crimeDataAnalysis.AnalyzeCrimeData()
	End Sub
End Class

using IronPdf;

public class PdfGenerator
{
    public void CreatePdf()
    {
        // Create an instance of ChromePdfRenderer for PDF generation
        var Renderer = new ChromePdfRenderer();
        // Render a simple HTML string as a PDF
        var PDF = Renderer.RenderHtmlAsPdf("<h1>Hello, IronPDF!</h1>");
        // Save the generated PDF to a file
        PDF.SaveAs("HelloIronPDF.pdf");
    }
}

Imports IronPdf

Public Class PdfGenerator
	Public Sub CreatePdf()
		' Create an instance of ChromePdfRenderer for PDF generation
		Dim Renderer = New ChromePdfRenderer()
		' Render a simple HTML string as a PDF
		Dim PDF = Renderer.RenderHtmlAsPdf("<h1>Hello, IronPDF!</h1>")
		' Save the generated PDF to a file
		PDF.SaveAs("HelloIronPDF.pdf")
	End Sub
End Class

using MathNet.Numerics.Statistics;
using IronPdf;

public class StatisticalReport
{
    public void CreateReport(double[] data)
    {
        // Calculate statistical metrics from data
        double mean = Statistics.Mean(data);
        double variance = Statistics.Variance(data);

        // Create a PDF renderer
        var Renderer = new ChromePdfRenderer();
        // Render statistical metrics as HTML and convert it to a PDF
        var PDF = Renderer.RenderHtmlAsPdf($"<h1>Statistical Report</h1><p>Mean: {mean}</p><p>Variance: {variance}</p>");
        // Save the generated PDF
        PDF.SaveAs("StatisticalReport.pdf");
    }
}

Imports MathNet.Numerics.Statistics
Imports IronPdf

Public Class StatisticalReport
	Public Sub CreateReport(ByVal data() As Double)
		' Calculate statistical metrics from data
		Dim mean As Double = Statistics.Mean(data)
		Dim variance As Double = Statistics.Variance(data)

		' Create a PDF renderer
		Dim Renderer = New ChromePdfRenderer()
		' Render statistical metrics as HTML and convert it to a PDF
		Dim PDF = Renderer.RenderHtmlAsPdf($"<h1>Statistical Report</h1><p>Mean: {mean}</p><p>Variance: {variance}</p>")
		' Save the generated PDF
		PDF.SaveAs("StatisticalReport.pdf")
	End Sub
End Class