public void TestUtilSparseMatrix_Vecsum()
{
SparseBinaryMatrix matrix1 = new SparseBinaryMatrix(new[] { 1024, 1024 });
// fill half the matrix
for (int i = 0; i < 1024; i++)
{
for (int j = 0; j < 512; j += 2)
{
matrix1.Set(1, i, j);
}
}
int[] inputVec = new int[1024]; // all zero
int[] results = new int[1024];
matrix1.RightVecSumAtNZ(inputVec, results, 0);
inputVec = new int[1024]; // some zero
for (int j = 0; j < 512; j += 2)
{
inputVec[j] = 1;
}
results = new int[1024];
matrix1.RightVecSumAtNZ(inputVec, results, 0);
}
public void TestAll()
{
SparseBinaryMatrix sm = CreateDefaultMatrix();
int[] all = { 0, 5, 11, 16, 22, 27, 33, 38, 44, 49 };
Assert.IsTrue(sm.All(all));
}
public void TestOr()
{
SparseBinaryMatrix sm = CreateDefaultMatrix();
int[] orBits = { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 };
byte[] expected = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
sm.Or(orBits);
Assert.IsTrue(Arrays.AreEqual(expected, ((SparseByteArray)sm.GetSlice(0)).AsDense()), "Arrays are not equal");
}
public void CreateDistributedArrayTest()
{
int[] dims;
var arr = new InMemoryArray(1, typeof(int), dims = new int[] { 100, 100 });
SparseBinaryMatrix m = new SparseBinaryMatrix(dims, true, arr);
for (int i = 0; i < 100; i++)
{
for (int j = 0; j < 100; j++)
{
m.set(7, i, j);
}
}
}
public void TestSliceIndexes()
{
SparseBinaryMatrix sm = new SparseBinaryMatrix(this.dimensions);
int[][] expected =
{
new int[] { 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 },
new int[] { 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 },
new int[] { 20, 21, 22, 23, 24, 25, 26, 27, 28, 29 },
new int[] { 30, 31, 32, 33, 34, 35, 36, 37, 38, 39 },
new int[] { 40, 41, 42, 43, 44, 45, 46, 47, 48, 49 }
};
for (int i = 0; i < this.dimensions[0]; i++)
{
Assert.IsTrue(Arrays.AreEqual(expected[i], sm.GetSliceIndexes(new[] { i })));
}
}
private SparseBinaryMatrix CreateDefaultMatrix()
{
SparseBinaryMatrix sm = new SparseBinaryMatrix(this.dimensions);
int[][] values =
{
new int[] { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0 },
new int[] { 0, 1, 0, 0, 0, 0, 1, 0, 0, 0 },
new int[] { 0, 0, 1, 0, 0, 0, 0, 1, 0, 0 },
new int[] { 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 },
new int[] { 0, 0, 0, 0, 1, 0, 0, 0, 0, 1 }
};
for (int i = 0; i < 5; i++)
{
for (int j = 0; j < 10; j++)
{
sm.Set(values[i][j], new int[] { i, j });
}
}
return(sm);
}
private void DoTestRightVecSumAtNzFast(AbstractSparseBinaryMatrix sm)
{
int[] dimensions = new int[] { 5, 10 };
int[][] connectedSynapses = new int[][]
{
new int[] { 1, 0, 0, 0, 0, 1, 0, 0, 0, 0 },
new int[] { 0, 1, 0, 0, 0, 0, 1, 0, 0, 0 },
new int[] { 0, 0, 1, 0, 0, 0, 0, 1, 0, 0 },
new int[] { 0, 0, 0, 1, 0, 0, 0, 0, 1, 0 },
new int[] { 0, 0, 0, 0, 1, 0, 0, 0, 0, 1 }
};
for (int i = 0; i < sm.GetDimensions()[0]; i++)
{
for (int j = 0; j < sm.GetDimensions()[1]; j++)
{
sm.Set(connectedSynapses[i][j], i, j);
}
}
for (int i = 0; i < 5; i++)
{
for (int j = 0; j < 10; j++)
{
Assert.AreEqual(connectedSynapses[i][j], sm.GetIntValue(i, j));
}
}
int[] inputVector = new int[] { 1, 0, 1, 0, 1, 0, 1, 0, 1, 0 };
int[] results = new int[5];
int[] trueResults = new int[] { 1, 1, 1, 1, 1 };
sm.RightVecSumAtNZ(inputVector, results);
for (int i = 0; i < results.Length; i++)
{
Assert.AreEqual(trueResults[i], results[i]);
}
///////////////////////
connectedSynapses = new int[][]
{
new int[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 },
new int[] { 0, 0, 1, 1, 1, 1, 1, 1, 1, 1 },
new int[] { 0, 0, 0, 0, 1, 1, 1, 1, 1, 1 },
new int[] { 0, 0, 0, 0, 0, 0, 1, 1, 1, 1 },
new int[] { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 }
};
sm = new SparseBinaryMatrix(dimensions);
for (int i = 0; i < sm.GetDimensions()[0]; i++)
{
for (int j = 0; j < sm.GetDimensions()[1]; j++)
{
sm.Set(connectedSynapses[i][j], i, j);
}
}
for (int i = 0; i < 5; i++)
{
for (int j = 0; j < 10; j++)
{
Assert.AreEqual(connectedSynapses[i][j], sm.GetIntValue(i, j));
}
}
inputVector = new int[] { 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
results = new int[5];
trueResults = new int[] { 10, 8, 6, 4, 2 };
sm.RightVecSumAtNZ(inputVector, results);
for (int i = 0; i < results.Length; i++)
{
Assert.AreEqual(trueResults[i], results[i]);
}
}