// Factory method for SignatureLoadModel.
internal CategoricalImputerTransformer(IHostEnvironment host, ModelLoadContext ctx) :
base(host.Register(nameof(CategoricalImputerTransformer)))
{
host.Check(!CommonExtensions.OsIsCentOS7(), "CentOS7 is not supported");
host.CheckValue(ctx, nameof(ctx));
ctx.CheckAtModel(GetVersionInfo());
// *** Binary format ***
// int number of column pairs
// for each column pair:
// string output column name
// string input column name
// column type
// int length of c++ byte array
// byte array from c++
var columnCount = ctx.Reader.ReadInt32();
_columns = new TypedColumn[columnCount];
for (int i = 0; i < columnCount; i++)
{
_columns[i] = TypedColumn.CreateTypedColumn(ctx.Reader.ReadString(), ctx.Reader.ReadString(), ctx.Reader.ReadString());
// Load the C++ state and create the C++ transformer.
var dataLength = ctx.Reader.ReadInt32();
var data = ctx.Reader.ReadByteArray(dataLength);
_columns[i].CreateTransformerFromSavedData(data);
}
}
internal CategoricalImputerTransformer(IHostEnvironment host, IDataView input, CategoricalImputerEstimator.Column[] columns) :
base(host.Register(nameof(CategoricalImputerEstimator)))
{
var schema = input.Schema;
_columns = columns.Select(x => TypedColumn.CreateTypedColumn(x.Name, x.Source, schema[x.Source].Type.RawType.ToString())).ToArray();
foreach (var column in _columns)
{
column.CreateTransformerFromEstimator(input);
}
}
public void TestWrongName()
{
OLVColumn column = new OLVColumn();
column.AspectName = "Photo.Unknown";
TypedColumn <Person> tcolumn = new TypedColumn <Person>(column);
tcolumn.GenerateAspectGetter();
Assert.AreEqual("'Unknown' is not a parameter-less method, property or field of type 'System.String'", column.GetValue(this.person1));
}
public void TestPropertyReplacedByNew()
{
OLVColumn column = new OLVColumn();
column.AspectName = "CulinaryRating";
TypedColumn <Person2> tcolumn = new TypedColumn <Person2>(column);
Assert.IsNull(column.AspectGetter);
tcolumn.GenerateAspectGetter();
Assert.IsNotNull(column.AspectGetter);
Assert.AreEqual(200, column.GetValue(this.person2));
}
public void Execute <T>(string aspectName, object expectedResult, T person) where T : class
{
OLVColumn column = new OLVColumn();
column.AspectName = aspectName;
TypedColumn <T> tcolumn = new TypedColumn <T>(column);
Assert.IsNull(column.AspectGetter);
tcolumn.GenerateAspectGetter();
Assert.IsNotNull(column.AspectGetter);
Assert.AreEqual(expectedResult, column.GetValue(person));
}
public Form1()
{
InitializeComponent();
Shown += (sender, args) => new Form2().Show();
_tptvFilesystem = new TypedObjectListView <FileSystemItem>(tvFilesystem);
_tpcolName = _tptvFilesystem.GetColumn("Name");
SetupFsTreeView();
UpdateControlsState();
}
public void ExecuteAspect(string aspectName, object expectedResult, Person person)
{
OLVColumn column = new OLVColumn();
column.AspectName = aspectName;
Assert.AreEqual(expectedResult, column.GetValue(person));
TypedColumn <Person> tcolumn = new TypedColumn <Person>(column);
Assert.IsNull(column.AspectGetter);
tcolumn.GenerateAspectGetter();
Assert.IsNotNull(column.AspectGetter);
Assert.AreEqual(expectedResult, column.GetValue(person));
}
private unsafe TransformerEstimatorSafeHandle CreateTransformerFromEstimator(IDataView input)
{
IntPtr estimator;
IntPtr errorHandle;
bool success;
var allColumns = input.Schema.Where(x => _allColumnNames.Contains(x.Name)).Select(x => TypedColumn.CreateTypedColumn(x, _dataColumns)).ToDictionary(x => x.Column.Name);
// Create TypeId[] for types of grain and data columns;
var dataColumnTypes = new TypeId[_dataColumns.Length];
var grainColumnTypes = new TypeId[_grainColumns.Length];
foreach (var column in _grainColumns.Select((value, index) => new { index, value }))
{
grainColumnTypes[column.index] = allColumns[column.value].GetTypeId();
}
foreach (var column in _dataColumns.Select((value, index) => new { index, value }))
{
dataColumnTypes[column.index] = allColumns[column.value].GetTypeId();
fixed(bool *suppressErrors = &_suppressTypeErrors)
fixed(TypeId * rawDataColumnTypes = dataColumnTypes)
fixed(TypeId * rawGrainColumnTypes = grainColumnTypes)
{
success = CreateEstimatorNative(rawGrainColumnTypes, new IntPtr(grainColumnTypes.Length), rawDataColumnTypes, new IntPtr(dataColumnTypes.Length), _imputeMode, suppressErrors, out estimator, out errorHandle);
}
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
using (var estimatorHandle = new TransformerEstimatorSafeHandle(estimator, DestroyEstimatorNative))
{
TrainingState trainingState;
FitResult fitResult;
// Create buffer to hold binary data
var memoryStream = new MemoryStream(4096);
var binaryWriter = new BinaryWriter(memoryStream, Encoding.UTF8);
// Can't use a using with this because it potentially needs to be reset. Manually disposing as needed.
var cursor = input.GetRowCursorForAllColumns();
// Initialize getters
foreach (var column in allColumns.Values)
{
column.InitializeGetter(cursor);
}
// Start the loop with the cursor in a valid state already.
var valid = cursor.MoveNext();
// Make sure its not an empty data frame
Debug.Assert(valid);
while (true)
{
// Get the state of the native estimator.
success = GetStateNative(estimatorHandle, out trainingState, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
// If we are no longer training then exit loop.
if (trainingState != TrainingState.Training)
{
break;
}
// Build byte array to send column data to native featurizer
BuildColumnByteArray(allColumns, ref binaryWriter);
// Fit the estimator
fixed(byte *bufferPointer = memoryStream.GetBuffer())
{
var binaryArchiveData = new NativeBinaryArchiveData()
{
Data = bufferPointer, DataSize = new IntPtr(memoryStream.Position)
};
success = FitNative(estimatorHandle, binaryArchiveData, out fitResult, out errorHandle);
}
// Reset memory stream to 0
memoryStream.Position = 0;
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
// If we need to reset the data to the beginning.
if (fitResult == FitResult.ResetAndContinue)
{
ResetCursor(input, ref cursor, allColumns);
}
// If we are at the end of the data.
if (!cursor.MoveNext())
{
// If we get here fitResult should never be ResetAndContinue
Debug.Assert(fitResult != FitResult.ResetAndContinue);
OnDataCompletedNative(estimatorHandle, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
ResetCursor(input, ref cursor, allColumns);
}
}
// When done training complete the estimator.
success = CompleteTrainingNative(estimatorHandle, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
// Create the native transformer from the estimator;
success = CreateTransformerFromEstimatorNative(estimatorHandle, out IntPtr transformer, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
// Manually dispose of the IEnumerator since we don't have a using statement;
cursor.Dispose();
return(new TransformerEstimatorSafeHandle(transformer, DestroyTransformerNative));
}
}
private unsafe TransformerEstimatorSafeHandle CreateTransformerFromEstimator(IDataView input)
{
IntPtr estimator;
IntPtr errorHandle;
bool success;
var allColumns = input.Schema.Where(x => _allColumnNames.Contains(x.Name)).Select(x => TypedColumn.CreateTypedColumn(x, _dataColumns)).ToDictionary(x => x.Column.Name);
// Create buffer to hold binary data
var columnBuffer = new byte[4096];
// Create TypeId[] for types of grain and data columns;
var dataColumnTypes = new TypeId[_dataColumns.Length];
var grainColumnTypes = new TypeId[_grainColumns.Length];
foreach (var column in _grainColumns.Select((value, index) => new { index, value }))
{
grainColumnTypes[column.index] = allColumns[column.value].GetTypeId();
}
foreach (var column in _dataColumns.Select((value, index) => new { index, value }))
{
dataColumnTypes[column.index] = allColumns[column.value].GetTypeId();
fixed(bool *suppressErrors = &_suppressTypeErrors)
fixed(TypeId * rawDataColumnTypes = dataColumnTypes)
fixed(TypeId * rawGrainColumnTypes = grainColumnTypes)
{
success = CreateEstimatorNative(rawGrainColumnTypes, new IntPtr(grainColumnTypes.Length), rawDataColumnTypes, new IntPtr(dataColumnTypes.Length), _imputeMode, suppressErrors, out estimator, out errorHandle);
}
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
using (var estimatorHandler = new TransformerEstimatorSafeHandle(estimator, DestroyEstimatorNative))
{
var fitResult = FitResult.Continue;
while (fitResult != FitResult.Complete)
{
using (var cursor = input.GetRowCursorForAllColumns())
{
// Initialize getters for start of loop
foreach (var column in allColumns.Values)
{
column.InitializeGetter(cursor);
}
while ((fitResult == FitResult.Continue || fitResult == FitResult.ResetAndContinue) && cursor.MoveNext())
{
BuildColumnByteArray(allColumns, ref columnBuffer, out int serializedDataLength);
fixed(byte *bufferPointer = columnBuffer)
{
var binaryArchiveData = new NativeBinaryArchiveData()
{
Data = bufferPointer, DataSize = new IntPtr(serializedDataLength)
};
success = FitNative(estimatorHandler, binaryArchiveData, out fitResult, out errorHandle);
}
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
}
success = CompleteTrainingNative(estimatorHandler, out fitResult, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
}
}
success = CreateTransformerFromEstimatorNative(estimatorHandler, out IntPtr transformer, out errorHandle);
if (!success)
{
throw new Exception(GetErrorDetailsAndFreeNativeMemory(errorHandle));
}
return(new TransformerEstimatorSafeHandle(transformer, DestroyTransformerNative));
}
}
// Initalize the Format of the ObjectListView
private void InitModel()
{
if (ObjectListView.IsVistaOrLater)
{
this.Font = new Font("msyh", 8);
}
this.folvAnime.AddDecoration(new EditingCellBorderDecoration(true));
TypedObjectListView <Anime> tolv = new TypedObjectListView <Anime>(this.folvAnime);
tolv.GenerateAspectGetters();
// Name of Anime
TypedColumn <Anime> tc = new TypedColumn <Anime>(this.olvColName);
tc.AspectPutter = (Anime a, object opn) => { a.Name = opn.ToString(); };
// Schedule of Anime
tc = new TypedColumn <Anime>(this.olvColSchedule);
tc.GroupKeyGetter = (Anime a) => a.Year;
// Type of Anime
tc = new TypedColumn <Anime>(this.olvColType);
tc.AspectPutter = (Anime a, object opt) => { a.Type = (MediaType)opt; };
tc.ImageGetter = (Anime a) => {
switch (a.Format)
{
case MergeFormat.MKV:
return(Properties.Resources.MKV);
case MergeFormat.MP4:
return(Properties.Resources.MP4);
case MergeFormat.AVI:
return(Properties.Resources.AVI);
case MergeFormat.WMV:
return(Properties.Resources.WMV);
case MergeFormat.M2TS:
return(Properties.Resources.M2TS);
default:
return(-1);
}
};
// Format of Anime
#region
//this.olvColFormat.Renderer = new MappedImageRenderer(new object[] {
// MergeFormat.MKV, Properties.Resources.MKV,
// MergeFormat.MP4, Properties.Resources.MP4,
// MergeFormat.AVI, Properties.Resources.AVI,
// MergeFormat.WMV, Properties.Resources.WMV,
// MergeFormat.M2TS, Properties.Resources.M2TS
//});
//tc = new TypedColumn<Anime>(this.olvColFormat);
//tc.AspectPutter = delegate(Anime a, object opf) { a.Format = (MergeFormat)opf; };
#endregion
// SubTeam of Anime
tc = new TypedColumn <Anime>(this.olvColSubTeam);
tc.AspectPutter = (Anime a, object opp) => { a.SubTeam = opp.ToString(); };
tc.ImageGetter = (Anime a) => {
switch (a.SubStyle)
{
case SubStyles.External:
return(Properties.Resources.External);
case SubStyles.Sealed:
return(Properties.Resources.Sealed);
case SubStyles.Embedded:
return(Properties.Resources.Embedded);
default:
return(-1);
}
};
// SubStyle of Anime
#region
//this.olvColSubStyle.Renderer = new MappedImageRenderer(new object[] {
// SubStyles.External, Properties.Resources.External,
// SubStyles.Sealed, Properties.Resources.Sealed,
// SubStyles.Embedded, Properties.Resources.Embedded
//});
//tc = new TypedColumn<Anime>(this.olvColSubStyle);
//tc.AspectPutter = delegate(Anime a, object ops) { a.SubStyle = (SubStyles)ops; };
#endregion
// Size of Anime
this.olvColSize.AspectToStringConverter = ots => {
long ls = (long)ots;
if (ls == 0L)
{
return("-");
}
else if (ls >= 1000000000L)
{
return(String.Format("{0:#,##0.#0} G", ls / 1073741824D));
}
else
{
return(String.Format("{0:#,##0.#0} M", ls / 1048576D));
}
};
this.olvColSize.MakeGroupies(
new long[] { 5368709120L, 10737418240L },
new string[] { "0~5 GB", "5~10 GB", ">10 GB" }
);
// Store of Anime
tc = new TypedColumn <Anime>(this.olvColStore);
tc.AspectPutter = (Anime a, object opg) => { a.Store = (bool)opg; };
this.olvColStore.Renderer = new MappedImageRenderer(true, Properties.Resources.Accept, false, Properties.Resources.Alert);
// Enjoy of Anime
tc = new TypedColumn <Anime>(this.olvColEnjoy);
tc.AspectPutter = (Anime a, object opv) => { a.Enjoy = (bool)opv; };
this.olvColEnjoy.Renderer = new MappedImageRenderer(true, Properties.Resources.Smile, false, Properties.Resources.Sad);
// Grade of Anime
tc = new TypedColumn <Anime>(this.olvColGrade);
tc.AspectPutter = (Anime a, object opr) => {
int onr = (int)opr;
a.Grade = onr; //onr < 1 ? 1 : onr;
};
this.olvColGrade.Renderer = new MultiImageRenderer(Properties.Resources.Diamond, 3, 0, 4);
this.olvColGrade.MakeGroupies(
new int[] { 1, 2 },
new string[] { "Normal", "Nice", "Good" }
);
// Note of Anime
this.olvColNote.AspectToStringConverter = otn => otn.ToString().Replace('\u0002', '\u0020');
//RowBorderDecoration rbd = new RowBorderDecoration();
//rbd.BorderPen = new Pen(Color.Orchid, 1);
//rbd.FillBrush = null;
//rbd.CornerRounding = 4.0f;
//HotItemStyle hotItemStyle = new HotItemStyle();
//hotItemStyle.Decoration = rbd;
//hotItemStyle.Overlay = new AnimeViewOverlay();
//this.folvAnime.HotItemStyle = hotItemStyle;
this.folvAnime.UseTranslucentHotItem = true;
this.folvAnime.UseTranslucentSelection = true;
this.folvAnime.HotItemStyle.Overlay = new AnimeViewOverlay();
this.folvAnime.HotItemStyle = this.folvAnime.HotItemStyle;
this.folvAnime.PrimarySortColumn = this.olvColTitle;
this.folvAnime.PrimarySortOrder = SortOrder.Ascending;
}
// Initalize the Format of the ObjectListView
private void InitModel()
{
this.olvAnime.AddDecoration(new EditingCellBorderDecoration(true));
TypedObjectListView <Anime> tolv = new TypedObjectListView <Anime>(this.olvAnime);
tolv.GenerateAspectGetters();
// Name of Anime
TypedColumn <Anime> tc = new TypedColumn <Anime>(this.olvColName);
tc.AspectPutter = (Anime a, object opn) => { a.Name = opn.ToString(); };
// Schedule of Anime
tc = new TypedColumn <Anime>(this.olvColAirdate);
tc.GroupKeyGetter = (Anime a) => a.Year;
// Type of Anime
tc = new TypedColumn <Anime>(this.olvColType);
tc.AspectPutter = (Anime a, object opt) => { a.Type = (MediaType)opt; };
tc.ImageGetter = (Anime a) =>
{
switch (a.Format)
{
case MergeFormat.MKV:
return(Properties.Resources.MKV);
case MergeFormat.MP4:
return(Properties.Resources.MP4);
case MergeFormat.AVI:
return(Properties.Resources.AVI);
case MergeFormat.WMV:
return(Properties.Resources.WMV);
case MergeFormat.M2TS:
return(Properties.Resources.M2TS);
default:
return(-1);
}
};
// SubTeam of Anime
tc = new TypedColumn <Anime>(this.olvColSubTeam);
tc.AspectPutter = (Anime a, object opp) => { a.SubTeam = opp.ToString(); };
tc.ImageGetter = (Anime a) =>
{
switch (a.SubStyle)
{
case SubStyle.External:
return(Properties.Resources.External);
case SubStyle.Sealed:
return(Properties.Resources.Sealed);
case SubStyle.Embedded:
return(Properties.Resources.Embedded);
default:
return(-1);
}
};
// Size of Anime
this.olvColSize.AspectToStringConverter = ots =>
{
long ls = (long)ots;
if (ls == 0L)
{
return("-");
}
else if (ls >= 1000L * 1024L * 1024L) // 1000M -> 0.9765625G
{
return(String.Format("{0:#,##0.#0} G", (double)ls / (1024 * 1024 * 1024)));
}
else
{
return(String.Format("{0:#,##0.#0} M", (double)ls / (1024 * 1024)));
}
};
this.olvColSize.MakeGroupies(
new long[] { 1024L * 1024L * 1024L * 5L, 1024L * 1024L * 1024L * 10L },
new string[] { "0~5 GB", "5~10 GB", ">10 GB" }
);
// Store of Anime
tc = new TypedColumn <Anime>(this.olvColStore);
//tc.AspectPutter = (Anime a, object opg) => { a.Store = (bool)opg; };
//this.olvColStore.Renderer = new MappedImageRenderer(true, Properties.Resources.Accept, false, Properties.Resources.Alert);
tc.AspectPutter = (Anime a, object ops) => { a.Store = (StoreState)ops; };
this.olvColStore.Renderer = new MappedImageRenderer(new object[] {
StoreState.Ignore, null,
StoreState.Cont, Properties.Resources.Alert,
StoreState.Fin, Properties.Resources.Accept
});
// Enjoy of Anime
tc = new TypedColumn <Anime>(this.olvColEnjoy);
//tc.AspectPutter = (Anime a, object opv) => { a.Enjoy = (bool)opv; };
//this.olvColEnjoy.Renderer = new MappedImageRenderer(true, Properties.Resources.Smile, false, Properties.Resources.Sad);
tc.AspectPutter = (Anime a, object ope) => { a.Enjoy = (EnjoyState)ope; };
this.olvColEnjoy.Renderer = new MappedImageRenderer(new object[] {
EnjoyState.Ignore, null,
EnjoyState.NotYet, Properties.Resources.Sad,
EnjoyState.Done, Properties.Resources.Smile
});
// Grade of Anime
tc = new TypedColumn <Anime>(this.olvColGrade);
tc.AspectPutter = (Anime a, object opr) =>
{
int onr = (int)opr;
a.Grade = onr; //onr < 1 ? 1 : onr;
};
this.olvColGrade.Renderer = new MultiImageRenderer(Properties.Resources.Diamond, 3, 0, 4);
this.olvColGrade.MakeGroupies(
new int[] { 1, 2 },
new string[] { "Normal", "Nice", "Good" }
);
// Note of Anime
this.olvColNote.AspectToStringConverter = otn => otn.ToString().Replace('\u0002', '\u0020');
// this.olvAnime.UseHotItem auto true
this.olvAnime.UseTranslucentHotItem = true;
this.olvAnime.UseTranslucentSelection = true;
this.olvAnime.HotItemStyle.Overlay = new AnimeViewOverlay();
this.olvAnime.HotItemStyle = this.olvAnime.HotItemStyle;
this.olvAnime.PrimarySortColumn = this.olvColTitle;
this.olvAnime.PrimarySortOrder = SortOrder.Ascending;
}
