public virtual void testAddObject()
{
DataFrame frame = new DataFrame();
Assert.NotNull(frame);
Assert.True(frame.Size == 0);
DataFrame child = new DataFrame();
frame.Add(child);
Assert.True(frame.Size == 1);
}
public void Run()
{
DataField datefield = new DataField("DATE", DateTime.UtcNow);
byte[] data = datefield.Bytes;
Console.WriteLine(ByteUtil.Dump(data));
Console.WriteLine("\r\n*************************************************************\r\n");
MemoryStream stream = new MemoryStream(data);
BinaryReader reader = new BinaryReader(stream);
DataField newfield = new DataField(reader);
byte[] otherdata = newfield.Bytes;
Console.WriteLine(ByteUtil.Dump(otherdata));
Console.WriteLine("\r\n*************************************************************\r\n");
DateTime time = (DateTime)newfield.ObjectValue;
Console.WriteLine(time.ToShortDateString() + " " + time.ToShortTimeString());
Console.WriteLine(ByteUtil.Dump(datefield.Value));
long millis = ByteUtil.RetrieveLong(datefield.Value, 0);
Console.WriteLine("Millis: " + millis);
Console.WriteLine("\r\n*************************************************************\r\n");
DataFrame frame = new DataFrame();
frame.Add(datefield);
DataFrame newframe = new DataFrame();
newframe.Add("NewDate", newfield);
frame.Add("newframe", newframe);
Console.WriteLine(frame.ToString());
}
public static void LoadData()
{
featureShape = new Shape(2);
labelShape = new Shape(1);
DataFrame frameX = new DataFrame(featureShape);
DataFrame frameY = new DataFrame(labelShape);
/*
* //One approach of building dataset
* trainData.Add(new List<float>() { 0, 0 }, 0);
* trainData.Add(new List<float>() { 0, 1 }, 1);
* trainData.Add(new List<float>() { 1, 0 }, 1);
* trainData.Add(new List<float>() { 1, 1 }, 0);
* trainData.YFrame.OneHotEncode();
*/
//Second approach
frameX.Add(0, 0); frameY.Add(0);
frameX.Add(0, 1); frameY.Add(1);
frameX.Add(1, 0); frameY.Add(1);
frameX.Add(1, 1); frameY.Add(0);
trainData = new DataFrameList(frameX, frameY);
}
public void TestAddNewIndexGetIndex()
{
Pair col = new Pair("Column1", new Series(new NDArray(1, 2, 3)));
Pair col1 = new Pair("Column2", new Series(new NDArray(4, 5, 6)));
DataFrame df = new DataFrame(col, col1);
NDArray i = new NDArray(new NDArray(7, 8), new NDArray(9, 10));
NDArray index = new NDArray("Hat", "Cat");
df.Add(i, index, null);
NDArray t = df.GetIndex();
Assert.True(t.Equals(new NDArray(0, 1, 2, "Hat", "Cat")), "Arrays are not equal.");
}
private static void RunTest()
{
Random Rnd = new Random();
DataFrame trnX_fin = new DataFrame();
DataFrame trnY_fin = new DataFrame();
for (int cc = 0; (cc < 100); cc++)
{
float[] sngLst = new float[100];
for (int indx = 0; (indx < 100); indx++)
{
sngLst[indx] = (float)Rnd.NextDouble();
}
trnX_fin.Add(sngLst);
}
for (int cc = 0; (cc < 100); cc++)
{
float[] sngLst = new float[3];
// fake one hot just for check
sngLst[0] = 0;
sngLst[1] = 1;
sngLst[2] = 0;
trnY_fin.Add(sngLst);
}
XYFrame XYfrm = new XYFrame();
XYfrm.XFrame = trnX_fin;
XYfrm.YFrame = trnY_fin;
// Split
TrainTestFrame trainTestFrame = XYfrm.SplitTrainTest(0.3);
// init some values
int shape_of_input = XYfrm.XFrame.Shape[1];
int embval = 100;
int seed = 2;
Sequential model = new Sequential();
model.Add(new Reshape(Shape.Create(1, embval), Shape.Create(shape_of_input)));
model.Add(new LSTM(64, returnSequence: false, cellDim: 4, weightInitializer: new SiaNet.Model.Initializers.GlorotUniform(0.05, seed), recurrentInitializer: new SiaNet.Model.Initializers.GlorotUniform(0.05, seed), biasInitializer: new SiaNet.Model.Initializers.GlorotUniform(0.05, seed)));
model.Add(new Dense(3, act: "sigmoid", useBias: true, weightInitializer: new SiaNet.Model.Initializers.GlorotUniform(0.05, seed)));
model.Compile(OptOptimizers.Adam, OptLosses.MeanSquaredError, OptMetrics.Accuracy);
model.Train(trainTestFrame.Train, 200, 8, trainTestFrame.Test);
}
public void TestAddSingle()
{
Pair col = new Pair("Column1", new Series(new NDArray(1, 2, 3)));
Pair col1 = new Pair("Column2", new Series(new NDArray(4, 5, 6)));
DataFrame df = new DataFrame(col, col1);
NDArray i = new NDArray(7, 8);
df.Add(i);
Pair col3 = new Pair("Column1", new Series(new NDArray(1, 2, 3, 7)));
Pair col4 = new Pair("Column2", new Series(new NDArray(4, 5, 6, 8)));
DataFrame df1 = new DataFrame(col3, col4);
Assert.True(df.Equals(df1), "Arrays are not equal.");
}
public void TestAddGetIndex()
{
Pair col = new Pair("Column1", new Series(new NDArray(1, 2, 3)));
Pair col1 = new Pair("Column2", new Series(new NDArray(4, 5, 6)));
DataFrame df = new DataFrame(col, col1);
NDArray i = new NDArray(new NDArray(7, 8), new NDArray(9, 10));
df.Add(i);
Pair col3 = new Pair("Column1", new Series(new NDArray(1, 2, 3, 7, 8)));
Pair col4 = new Pair("Column2", new Series(new NDArray(4, 5, 6, 9, 10)));
NDArray index = df.GetIndex();
Assert.True(index.Equals(new NDArray(0, 1, 2, 3, 4)), "Arrays are not equal.");
}
public void TestAddColumn()
{
Pair col = new Pair("Column1", new Series(new NDArray(1, 2, 3)));
Pair col1 = new Pair("Column2", new Series(new NDArray(4, 5, 6)));
DataFrame df = new DataFrame(col, col1);
NDArray i = new NDArray(new NDArray(7, 8), new NDArray(9, 10));
NDArray columns = new NDArray("Column1", "Column2");
df.Add(i, null, columns);
Pair col3 = new Pair("Column1", new Series(new NDArray(1, 2, 3, 7, 8)));
Pair col4 = new Pair("Column2", new Series(new NDArray(4, 5, 6, 9, 10)));
DataFrame df1 = new DataFrame(col3, col4);
Assert.True(df.Equals(df1), "Arrays are not equal.");
}
public void TestBinaryOperationsOnBoolColumn()
{
var df = new DataFrame();
var dataFrameColumn1 = new PrimitiveColumn <bool>("Bool1", Enumerable.Range(0, 10).Select(x => true));
var dataFrameColumn2 = new PrimitiveColumn <bool>("Bool2", Enumerable.Range(0, 10).Select(x => true));
df.InsertColumn(0, dataFrameColumn1);
df.InsertColumn(1, dataFrameColumn2);
// bool + int should throw
Assert.Throws <NotSupportedException>(() => df.Add(5));
// Left shift should throw
Assert.Throws <NotSupportedException>(() => df.LeftShift(5));
IReadOnlyList <bool> listOfBools = new List <bool>()
{
true, false
};
// bool equals and And should work
var newdf = df.Equals(true);
Assert.Equal(true, newdf[4, 0]);
var newdf1 = df.Equals(listOfBools);
Assert.Equal(false, newdf1[4, 1]);
newdf = df.And(true);
Assert.Equal(true, newdf[4, 0]);
newdf1 = df.And(listOfBools);
Assert.Equal(false, newdf1[4, 1]);
newdf = df.Or(true);
Assert.Equal(true, newdf[4, 0]);
newdf1 = df.Or(listOfBools);
Assert.Equal(true, newdf1[4, 1]);
newdf = df.Xor(true);
Assert.Equal(false, newdf[4, 0]);
newdf1 = df.Xor(listOfBools);
Assert.Equal(true, newdf1[4, 1]);
}
public void GetRow()
{
NDArray index = new NDArray(DateTime.Parse("2018-03-12"), DateTime.Parse("2018-03-13"), DateTime.Parse("2018-03-14"));
Pair col1 = new Pair("Open", new Series(new NDArray(1592.599976, 1615.959961, 1597.000000), index));
Pair col2 = new Pair("High", new Series(new NDArray(1605.329956, 1617.540039, 1606.439941), index));
Pair col3 = new Pair("Low", new Series(new NDArray(1586.699951, 1578.010010, 1590.890015), index));
Pair col4 = new Pair("Close", new Series(new NDArray(1598.390015, 1588.180054, 1591.000000), index));
Pair col5 = new Pair("Adj Close", new Series(new NDArray(1598.390015, 1588.180054, 1591.000000), index));
Pair col6 = new Pair("Volume", new Series(new NDArray(5174200, 6531900, 4175400), index));
DataFrame df1 = new DataFrame(col1, col2, col3, col4, col5, col6);
DataFrame t = df1.GetRow(DateTime.Parse("2018-03-13"));
DataFrame t2 = new DataFrame();
NDArray cols = new NDArray("Open", "High", "Low", "Close", "Adj Close", "Volume");
t2.Add(new NDArray(1615.959961, 1617.540039, 1578.010010, 1588.180054, 1588.180054, 6531900), new NDArray(DateTime.Parse("2018-03-13")), cols);
Assert.True(t.Equals(t2), "Arrays are not equal.");
}
