/// <summary> /// Wrong data length /// </summary> //JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes: //ORIGINAL LINE: @Test(expectedExceptions = IllegalArgumentException.class) public void dataDifferentLengthWithSenseTest() public virtual void dataDifferentLengthWithSenseTest() { double[] xValues = new double[] { -5.0, -1.4, 3.2, 3.5 }; double[] yValues = new double[] { -2.2, 1.1, 1.9, 2.3, 1.2 }; ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP_SENSE[1]); interp.interpolateWithSensitivity(xValues, yValues); }
/// <summary> /// Test linear extrapolation without clamped points /// </summary> //JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes: //ORIGINAL LINE: @Test public void linearExtrapolationNoClampedTest() public virtual void linearExtrapolationNoClampedTest() { double[] xValues = new double[] { -5.0, -1.4, 3.2, 3.5, 7.6 }; double[] yValues = new double[] { -2.2, 1.1, 1.9, 2.3, -0.1 }; int nData = xValues.Length; int nKeys = 20; double interval = (3.0 * xValues[nData - 1] - xValues[nData - 1]) / (nKeys - 1); double[] keys = new double[nKeys]; int n = INTERP.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP[i]); PiecewisePolynomialResult result = interp.interpolate(xValues, yValues); for (int j = 0; j < nKeys; ++j) { keys[j] = xValues[nData - 1] + j * interval; } double[] values = FUNC.evaluate(result, keys).row(0).toArray(); for (int j = 2; j < nKeys; ++j) { InterpolatorTestUtil.assertRelative("linearExtrapolationTest", values[j - 1] - values[j - 2], values[j - 1] - values[j - 2], EPS); } } n = INTERP_SENSE.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP_SENSE[i]); PiecewisePolynomialResultsWithSensitivity result = interp.interpolateWithSensitivity(xValues, yValues); for (int j = 0; j < nKeys; ++j) { keys[j] = xValues[nData - 1] + j * interval; } double[] values = FUNC.evaluate(result, keys).row(0).toArray(); for (int j = 2; j < nKeys; ++j) { InterpolatorTestUtil.assertRelative("linearExtrapolationTest", values[j - 1] - values[j - 2], values[j - 1] - values[j - 2], EPS); } DoubleArray[] sense = FUNC.nodeSensitivity(result, keys); for (int k = 0; k < nData; ++k) { double[] yValuesUp = Arrays.copyOf(yValues, nData); double[] yValuesDw = Arrays.copyOf(yValues, nData); yValuesUp[k] += DELTA / xValues[k]; yValuesDw[k] -= DELTA / xValues[k]; PiecewisePolynomialResultsWithSensitivity resultUp = interp.interpolateWithSensitivity(xValues, yValuesUp); PiecewisePolynomialResultsWithSensitivity resultDw = interp.interpolateWithSensitivity(xValues, yValuesDw); double[] tmpUp = FUNC.evaluate(resultUp, keys).rowArray(0); double[] tmpDw = FUNC.evaluate(resultDw, keys).rowArray(0); for (int l = 0; l < nKeys; ++l) { double res = 0.5 * (tmpUp[l] - tmpDw[l]) / DELTA; // lk InterpolatorTestUtil.assertRelative("linearExtrapolationTest", sense[l].get(k), res, DELTA); } } } }
/// <summary> /// No clamped points added /// </summary> //JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes: //ORIGINAL LINE: @Test public void notClampedTest() public virtual void notClampedTest() { double[][] xValuesSet = new double[][] { new double[] { -5.0, -1.4, 3.2, 3.5, 7.6 }, new double[] { 1.0, 2.0, 4.5, 12.1, 14.2 }, new double[] { -5.2, -3.4, -3.2, -0.9, -0.2 } }; double[][] yValuesSet = new double[][] { new double[] { -2.2, 1.1, 1.9, 2.3, -0.1 }, new double[] { 3.4, 5.2, 4.3, 1.1, 0.2 }, new double[] { 1.4, 2.2, 4.1, 1.9, 0.99 } }; for (int k = 0; k < xValuesSet.Length; ++k) { double[] xValues = Arrays.copyOf(xValuesSet[k], xValuesSet[k].Length); double[] yValues = Arrays.copyOf(yValuesSet[k], yValuesSet[k].Length); int nData = xValues.Length; double[] xyValues = new double[nData]; for (int j = 0; j < nData; ++j) { xyValues[j] = xValues[j] * yValues[j]; } int nKeys = 100; double interval = (xValues[nData - 1] - xValues[0]) / (nKeys - 1.0); int n = INTERP.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP[i]); for (int j = 0; j < nKeys; ++j) { double key = xValues[0] + interval * j; InterpolatorTestUtil.assertRelative("notClampedTest", INTERP[i].interpolate(xValues, xyValues, key), interp.interpolate(xValues, yValues, key), EPS); } } n = INTERP_SENSE.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP_SENSE[i]); PiecewisePolynomialResultsWithSensitivity result = interp.interpolateWithSensitivity(xValues, yValues); PiecewisePolynomialResultsWithSensitivity resultBase = INTERP_SENSE[i].interpolateWithSensitivity(xValues, xyValues); for (int j = 0; j < nKeys; ++j) { double key = xValues[0] + interval * j; InterpolatorTestUtil.assertRelative("notClampedTest", FUNC.evaluate(resultBase, key).get(0), FUNC.evaluate(result, key).get(0), EPS); InterpolatorTestUtil.assertArrayRelative("notClampedTest", FUNC.nodeSensitivity(resultBase, key).toArray(), FUNC.nodeSensitivity(result, key).toArray(), EPS); } } } }
/// <summary> /// 2D method is not implemented /// </summary> //JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes: //ORIGINAL LINE: @Test(expectedExceptions = UnsupportedOperationException.class) public void notImplementedTest() public virtual void notImplementedTest() { double[] xValues = new double[] { -5.0, -1.4, 3.2, 3.5, 7.6 }; double[][] yValues = new double[][] { new double[] { -2.2, 1.1, 1.9, 2.3, 1.2 }, new double[] { -2.2, 1.1, 1.9, 2.3, 1.2 } }; ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP_SENSE[1]); interp.interpolate(xValues, yValues); }
/// <summary> /// Clamped points /// </summary> //JAVA TO C# CONVERTER TODO TASK: Most Java annotations will not have direct .NET equivalent attributes: //ORIGINAL LINE: @Test public void clampedTest() public virtual void clampedTest() { double[] xValues = new double[] { -5.0, -1.4, 3.2, 3.5, 7.6 }; double[] yValues = new double[] { -2.2, 1.1, 1.9, 2.3, -0.1 }; double[][] xValuesClampedSet = new double[][] { new double[] { 0.0 }, new double[] { -7.2, -2.5, 8.45 }, new double[] {} }; double[][] yValuesClampedSet = new double[][] { new double[] { 0.0 }, new double[] { -1.2, -1.4, 2.2 }, new double[] {} }; for (int k = 0; k < xValuesClampedSet.Length; ++k) { double[] xValuesClamped = Arrays.copyOf(xValuesClampedSet[k], xValuesClampedSet[k].Length); double[] yValuesClamped = Arrays.copyOf(yValuesClampedSet[k], yValuesClampedSet[k].Length); int nData = xValues.Length; int nClamped = xValuesClamped.Length; int nTotal = nData + nClamped; double[] xValuesForBase = new double[nTotal]; double[] yValuesForBase = new double[nTotal]; Array.Copy(xValues, 0, xValuesForBase, 0, nData); Array.Copy(yValues, 0, yValuesForBase, 0, nData); Array.Copy(xValuesClamped, 0, xValuesForBase, nData, nClamped); Array.Copy(yValuesClamped, 0, yValuesForBase, nData, nClamped); DoubleArrayMath.sortPairs(xValuesForBase, yValuesForBase); double[] xyValuesBase = new double[nTotal]; for (int j = 0; j < nTotal; ++j) { xyValuesBase[j] = xValuesForBase[j] * yValuesForBase[j]; } int nKeys = 100; double interval = (xValues[nData - 1] - xValues[0]) / (nKeys - 1.0); int n = INTERP.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP[i], xValuesClamped, yValuesClamped); for (int j = 0; j < nKeys; ++j) { double key = xValues[0] + interval * j; InterpolatorTestUtil.assertRelative("clampedTest", INTERP[i].interpolate(xValuesForBase, xyValuesBase, key), interp.interpolate(xValues, yValues, key), EPS); } } n = INTERP_SENSE.Length; for (int i = 0; i < n; ++i) { ProductPiecewisePolynomialInterpolator interp = new ProductPiecewisePolynomialInterpolator(INTERP_SENSE[i], xValuesClamped, yValuesClamped); PiecewisePolynomialResultsWithSensitivity result = interp.interpolateWithSensitivity(xValues, yValues); PiecewisePolynomialResultsWithSensitivity resultBase = INTERP_SENSE[i].interpolateWithSensitivity(xValuesForBase, xyValuesBase); for (int j = 0; j < nKeys; ++j) { double key = xValues[0] + interval * j; InterpolatorTestUtil.assertRelative("clampedTest", FUNC.evaluate(resultBase, key).get(0), FUNC.evaluate(result, key).get(0), EPS); InterpolatorTestUtil.assertArrayRelative("clampedTest", FUNC.nodeSensitivity(resultBase, key).toArray(), FUNC.nodeSensitivity(result, key).toArray(), EPS); } } } }