DataOperationsCatalog.CreateEnumerable<TRow> 方法
定義
重要
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IDataView將 轉換成強型別 IEnumerable<T> 。
public System.Collections.Generic.IEnumerable<TRow> CreateEnumerable<TRow> (Microsoft.ML.IDataView data, bool reuseRowObject, bool ignoreMissingColumns = false, Microsoft.ML.Data.SchemaDefinition schemaDefinition = default) where TRow : class, new();member this.CreateEnumerable : Microsoft.ML.IDataView * bool * bool * Microsoft.ML.Data.SchemaDefinition -> seq<'Row (requires 'Row : null and 'Row : (new : unit -> 'Row))> (requires 'Row : null and 'Row : (new : unit -> 'Row))Public Function CreateEnumerable(Of TRow As {Class, New}) (data As IDataView, reuseRowObject As Boolean, Optional ignoreMissingColumns As Boolean = false, Optional schemaDefinition As SchemaDefinition = Nothing) As IEnumerable(Of TRow)類型參數
- TRow
使用者定義專案類型。
參數
- data
- IDataView
基礎資料檢視。
- reuseRowObject
- Boolean
是否要在每個資料列上傳回相同的物件，或為每個資料列配置一個新的物件。
- ignoreMissingColumns
- Boolean
當要求的資料行不存在於資料檢視中時，是否要忽略案例。
- schemaDefinition
- SchemaDefinition
選擇性使用者提供的架構定義。 如果不存在，則會從 T 的定義推斷架構。
傳回
IEnumerable<TRow>
， IEnumerable<T> 保存 中的資料。 data 它可以列舉多次。
範例
using System;
using System.Collections.Generic;
using Microsoft.ML;
namespace Samples.Dynamic
{
public static class DataViewEnumerable
{
// A simple case of creating IDataView from
//IEnumerable.
public static void Example()
{
// Create a new context for ML.NET operations. It can be used for
// exception tracking and logging,
// as a catalog of available operations and as the source of randomness.
var mlContext = new MLContext();
// Get a small dataset as an IEnumerable.
IEnumerable<SampleTemperatureData> enumerableOfData =
GetSampleTemperatureData(5);
// Load dataset into an IDataView.
IDataView data = mlContext.Data.LoadFromEnumerable(enumerableOfData);
// We can now examine the records in the IDataView. We first create an
// enumerable of rows in the IDataView.
var rowEnumerable = mlContext.Data
.CreateEnumerable<SampleTemperatureData>(data,
reuseRowObject: true);
// SampleTemperatureDataWithLatitude has the definition of a Latitude
// column of type float. We can use the parameter ignoreMissingColumns
// to true to ignore any missing columns in the IDataView. The produced
// enumerable will have the Latitude field set to the default for the
// data type, in this case 0.
var rowEnumerableIgnoreMissing = mlContext.Data
.CreateEnumerable<SampleTemperatureDataWithLatitude>(data,
reuseRowObject: true, ignoreMissingColumns: true);
Console.WriteLine($"Date\tTemperature");
foreach (var row in rowEnumerable)
Console.WriteLine(
$"{row.Date.ToString("d")}\t{row.Temperature}");
// Expected output:
// Date Temperature
// 1/2/2012 36
// 1/3/2012 36
// 1/4/2012 34
// 1/5/2012 35
// 1/6/2012 35
Console.WriteLine($"Date\tTemperature\tLatitude");
foreach (var row in rowEnumerableIgnoreMissing)
Console.WriteLine($"{row.Date.ToString("d")}\t{row.Temperature}"
+ $"\t{row.Latitude}");
// Expected output:
// Date Temperature Latitude
// 1/2/2012 36 0
// 1/3/2012 36 0
// 1/4/2012 34 0
// 1/5/2012 35 0
// 1/6/2012 35 0
}
private class SampleTemperatureData
{
public DateTime Date { get; set; }
public float Temperature { get; set; }
}
private class SampleTemperatureDataWithLatitude
{
public float Latitude { get; set; }
public DateTime Date { get; set; }
public float Temperature { get; set; }
}
/// <summary>
/// Get a fake temperature dataset.
/// </summary>
/// <param name="exampleCount">The number of examples to return.</param>
/// <returns>An enumerable of <see cref="SampleTemperatureData"/>.</returns>
private static IEnumerable<SampleTemperatureData> GetSampleTemperatureData(
int exampleCount)
{
var rng = new Random(1234321);
var date = new DateTime(2012, 1, 1);
float temperature = 39.0f;
for (int i = 0; i < exampleCount; i++)
{
date = date.AddDays(1);
temperature += rng.Next(-5, 5);
yield return new SampleTemperatureData
{
Date = date,
Temperature =
temperature
};
}
}
}
}