using Microsoft.ML.Data;

namespace CreditCardFraudDetection.DataModels
{
    public class ModelInput
    {
        [ColumnName("Time"), LoadColumn(0)]
        public float Time { get; set; }

        [ColumnName("V1"), LoadColumn(1)]
        public float V1 { get; set; }

        [ColumnName("V2"), LoadColumn(2)]
        public float V2 { get; set; }

        [ColumnName("V3"), LoadColumn(3)]
        public float V3 { get; set; }

        [ColumnName("V4"), LoadColumn(4)]
        public float V4 { get; set; }

        [ColumnName("V5"), LoadColumn(5)]
        public float V5 { get; set; }

        [ColumnName("V6"), LoadColumn(6)]
        public float V6 { get; set; }

        [ColumnName("V7"), LoadColumn(7)]
        public float V7 { get; set; }

        [ColumnName("V8"), LoadColumn(8)]
        public float V8 { get; set; }

        [ColumnName("V9"), LoadColumn(9)]
        public float V9 { get; set; }

        [ColumnName("V10"), LoadColumn(10)]
        public float V10 { get; set; }

        [ColumnName("V11"), LoadColumn(11)]
        public float V11 { get; set; }

        [ColumnName("V12"), LoadColumn(12)]
        public float V12 { get; set; }

        [ColumnName("V13"), LoadColumn(13)]
        public float V13 { get; set; }

        [ColumnName("V14"), LoadColumn(14)]
        public float V14 { get; set; }

        [ColumnName("V15"), LoadColumn(15)]
        public float V15 { get; set; }

        [ColumnName("V16"), LoadColumn(16)]
        public float V16 { get; set; }

        [ColumnName("V17"), LoadColumn(17)]
        public float V17 { get; set; }

        [ColumnName("V18"), LoadColumn(18)]
        public float V18 { get; set; }

        [ColumnName("V19"), LoadColumn(19)]
        public float V19 { get; set; }

        [ColumnName("V20"), LoadColumn(20)]
        public float V20 { get; set; }

        [ColumnName("V21"), LoadColumn(21)]
        public float V21 { get; set; }

        [ColumnName("V22"), LoadColumn(22)]
        public float V22 { get; set; }

        [ColumnName("V23"), LoadColumn(23)]
        public float V23 { get; set; }

        [ColumnName("V24"), LoadColumn(24)]
        public float V24 { get; set; }

        [ColumnName("V25"), LoadColumn(25)]
        public float V25 { get; set; }

        [ColumnName("V26"), LoadColumn(26)]
        public float V26 { get; set; }

        [ColumnName("V27"), LoadColumn(27)]
        public float V27 { get; set; }

        [ColumnName("V28"), LoadColumn(28)]
        public float V28 { get; set; }

        [ColumnName("Amount"), LoadColumn(29)]
        public float Amount { get; set; }

        [ColumnName("Class"), LoadColumn(30)]
        public bool Class { get; set; }
    }
} 

 using Microsoft.ML.Data;

namespace CreditCardFraudDetection.DataModels
{
    public class ModelOutput
    {
        [ColumnName("PredictedLabel")]
        public bool Prediction { get; set; }

        public float Score { get; set; }
    }
}  
  

IDataView trainingDataView = mlContext.Data.LoadFromTextFile<ModelInput>(
                                            path: dataFilePath,
                                            hasHeader: true,
                                            separatorChar: ',',
                                            allowQuoting: true,
                                            allowSparse: false);

var dataProcessPipeline = mlContext.Transforms.Concatenate("Features", new[] { "Time", "V1", "V2", "V3", "V4", "V5", "V6", "V7", "V8", "V9", "V10", "V11", "V12", "V13", "V14", "V15", "V16", "V17", "V18", "V19", "V20", "V21", "V22", "V23", "V24", "V25", "V26", "V27", "V28", "Amount" });

// Choosing algorithm
var trainer = mlContext.BinaryClassification.Trainers.LightGbm(labelColumnName: "Class", featureColumnName: "Features");

// Appending algorithm to pipeline
var trainingPipeline = dataProcessPipeline.Append(trainer);

ITransformer model = trainingPipeline.Fit(trainingDataView);
mlContext.Model.Save(model , trainingDataView.Schema, <path>);
 

var crossValidationResults = mlContext.BinaryClassification.CrossValidateNonCalibrated(trainingDataView, trainingPipeline, numberOfFolds: 5, labelColumnName: "Class");

var predEngine = mlContext.Model.CreatePredictionEngine<ModelInput, ModelOutput>(mlModel);

ModelInput sampleData = new ModelInput() {
    time = 0,
    V1 = -1.3598071336738,
    ...
};

ModelOutput predictionResult = predEngine.Predict(sampleData);

Console.WriteLine($"Actual value: {sampleData.Class} | Predicted value: {predictionResult.Prediction}"); 

private ITransformer SetupMlnetModel(string tensorFlowModelFilePath)
{
    var pipeline = _mlContext.<preprocess-data>
           .Append(_mlContext.Model.LoadTensorFlowModel(tensorFlowModelFilePath)
                                               .ScoreTensorFlowModel(
                                                      outputColumnNames: new[]{TensorFlowModelSettings.outputTensorName },
                                                      inputColumnNames: new[] { TensorFlowModelSettings.inputTensorName },
                                                      addBatchDimensionInput: false));
 
    ITransformer mlModel = pipeline.Fit(CreateEmptyDataView());
 
    return mlModel;
}

<InputText @bind-Value="employee.FirstName" />

[Parameter] public string Value { set; get; }

[Parameter] public EventCallback<string> ValueChanged { get; set; }

[Parameter] public Action<string> ValueChanged { get; set; }

[Parameter] public Expression<Func<string>> ValueExpression { get; set; }

public object ProcessingBoundary(IList<SummaryCellData> columnCellsSummaryData)
        {
            if (columnCellsSummaryData == null || !columnCellsSummaryData.Any()) return 0;

            var list = columnCellsSummaryData;
            var lastItem = list.Last();

            return lastItem.CellData.PropertyValue;

        }

Method 'set_DisplayFormatFormula' in type 'Hezareh.Modules.Accounting.Reporting.ViewModels.MySampleAggregateFunction' from assembly 'Hezareh.Modules.Accounting, Version=1.0.0.0, Culture=neutral, PublicKeyToken=null' does not have an implementation.

CREATE PROCEDURE [dbo].[GetAllBlogsAndPosts]
AS
    SELECT * FROM dbo.Blogs
    SELECT * FROM dbo.Posts

public class Blog
    {
        public int BlogId { get; set; }
        public string Name { get; set; }

        public virtual List<Post> Posts { get; set; }
    }

    public class Post
    {
        public int PostId { get; set; }
        public string Title { get; set; }
        public string Content { get; set; }

        public int BlogId { get; set; }
        public virtual Blog Blog { get; set; }
    }

    public class BloggingContext : DbContext
    {
        public DbSet<Blog> Blogs { get; set; }
        public DbSet<Post> Posts { get; set; }
    }


 
using System;
using System.Collections.Generic;
using System.Data.Entity;
using System.Data.Entity.Infrastructure;
using System.Data.Objects;

namespace Sproc.Demo
{
    class Program
    {
        static void Main(string[] args)
        {
            using (var db = new BloggingContext())
            {
                 db.Database.Initialize(force: false);
               
                var cmd = db.Database.Connection.CreateCommand();
                cmd.CommandText = "[dbo].[GetAllBlogsAndPosts]";

                try
                {
                    // اجرای پروسیجر
                    db.Database.Connection.Open();
                    var reader = cmd.ExecuteReader();

                    // خواند رکوردهای blogs
                    var blogs = ((IObjectContextAdapter)db)
                        .ObjectContext
                        .Translate<Blog>(reader, "Blogs", MergeOption.AppendOnly);

                    foreach (var item in blogs)
                    {
                        Console.WriteLine(item.Name);
                    }

                    // پرش به نتایج بعدی (همان Posts)
                    reader.NextResult();
                    var posts = ((IObjectContextAdapter)db)
                        .ObjectContext
                        .Translate<Post>(reader, "Posts", MergeOption.AppendOnly);

                    foreach (var item in posts)
                    {
                        Console.WriteLine(item.Title);
                    }
                }
                finally
                {
                    db.Database.Connection.Close();
                }
            }
        }
    }

        static void Main( string[] args )
        {
            Book book = new Book() 
            {
                Code = 1,
                Title = "Book1",
                Category = "Default"
            };

            NoteBook noteBook = new NoteBook();

            noteBook = (NoteBook)book;//Compile error
            noteBook = book as NoteBook;//Compile error
        }

• DataContext: این شیء اتصالش را به منبع داده‌ها برقرار کرده و هر موقع داده‌ای را نیاز داریم، از طریق این شیء تامین می‌شود.
• DataBinding: یک واسطه بین DataContext و هر آن چیزی است که قرار است از داده‌ها تغذیه کند. در تعریفی رسمی‌تر می‌گوییم: روشی ساده و قدرتمند بوده و واسطی است بین مدل تجاری و رابط کاربری. هر زمانی که داده‌ای تغییر کند، ما را آگاه می‌سازد که می‌تواند یک ارتباط یک طرفه یا دو طرفه باشد.
  
• DataTemplate: نحوه‌ی فرمت بندی و نمایش داده‌ها را تعیین می‌کند.

   public enum FieldOfWork
    {
        Actor=0,
        Director=1,
        Producer=2
    }
    public class Person
    {
        public string Name { get; set; }

        public bool Gender { get; set; }

        public string ImageName { get; set; }

        public string Country { get; set; }

        public DateTime Date { get; set; }

        public IList<FieldOfWork> FieldOfWork { get; set; }
        public static Person GetPerson()
        {
            return new Person()
            {
                Name = "Leo",
                Gender = true,
                ImageName ="man.jpg",
                Country = "Italy",
                Date = DateTime.Now
            };
        }
    }

 DataContext = Person.GetPerson();

public partial class MainWindow : Window
    {
        public MainWindow()
        {
            InitializeComponent();
            DataContext = Person.GetPerson();
        }  
    }

Text="{Binding Name}"

Source="{Binding ImageName}"

 public interface IFeatureToggle {
   bool FeatureEnabled {get;}  
}

class ShowMessageToggle : IFeatureToggle  
 {   
    public bool FeatureEnabled {
     get{
           return  bool.Parse(ConfigurationManager.AppSettings["ShowMessageEnabled"]);      
        }
 }

class Program
 {
 static void Main(string[] args)
   {
     var toggle = new ShowMessageToggle();
     if (toggle.FeatureEnabled)
     {
        Console.WriteLine("This feature is enabled")
     }
     else
     {  
         Console.WriteLine("This feature is disabled");            
     }
   }  
 }