List of usage examples for java.io DataOutput writeDouble
void writeDouble(double v) throws IOException;
double value, which is comprised of eight bytes, to the output stream. From source file:ml.shifu.shifu.core.correlation.CorrelationWritable.java
@Override public void write(DataOutput out) throws IOException { out.writeInt(this.columnIndex); out.writeDouble(this.sum); out.writeDouble(this.sumSquare); out.writeDouble(this.count); if (this.xySum == null) { out.writeInt(0);//from w ww. j a va 2 s . co m } else { out.writeInt(this.xySum.length); for (double doub : this.xySum) { out.writeDouble(doub); } } if (this.xxSum == null) { out.writeInt(0); } else { out.writeInt(this.xxSum.length); for (double doub : this.xxSum) { out.writeDouble(doub); } } if (this.yySum == null) { out.writeInt(0); } else { out.writeInt(this.yySum.length); for (double doub : this.yySum) { out.writeDouble(doub); } } if (this.adjustCount == null) { out.writeInt(0); } else { out.writeInt(this.adjustCount.length); for (double doub : this.adjustCount) { out.writeDouble(doub); } } if (this.adjustSumX == null) { out.writeInt(0); } else { out.writeInt(this.adjustSumX.length); for (double doub : this.adjustSumX) { out.writeDouble(doub); } } if (this.adjustSumY == null) { out.writeInt(0); } else { out.writeInt(this.adjustSumY.length); for (double doub : this.adjustSumY) { out.writeDouble(doub); } } }
From source file:ml.shifu.shifu.core.dtrain.dataset.PersistBasicFloatNetwork.java
private void writeDoubleArray(DataOutput out, double[] array) throws IOException { if (array == null) { out.writeInt(0);/*from w ww .ja v a 2s.c o m*/ } else { out.writeInt(array.length); for (double d : array) { out.writeDouble(d); } } }
From source file:ml.shifu.shifu.core.dtrain.dataset.PersistBasicFloatNetwork.java
public void saveNetwork(DataOutput out, final BasicFloatNetwork network) throws IOException { final FlatNetwork flat = network.getStructure().getFlat(); // write general properties Map<String, String> properties = network.getProperties(); if (properties == null) { out.writeInt(0);/*from w w w .j a va 2 s.c o m*/ } else { out.writeInt(properties.size()); for (Entry<String, String> entry : properties.entrySet()) { ml.shifu.shifu.core.dtrain.StringUtils.writeString(out, entry.getKey()); ml.shifu.shifu.core.dtrain.StringUtils.writeString(out, entry.getValue()); } } // write fields values in BasicFloatNetwork out.writeInt(flat.getBeginTraining()); out.writeDouble(flat.getConnectionLimit()); writeIntArray(out, flat.getContextTargetOffset()); writeIntArray(out, flat.getContextTargetSize()); out.writeInt(flat.getEndTraining()); out.writeBoolean(flat.getHasContext()); out.writeInt(flat.getInputCount()); writeIntArray(out, flat.getLayerCounts()); writeIntArray(out, flat.getLayerFeedCounts()); writeIntArray(out, flat.getLayerContextCount()); writeIntArray(out, flat.getLayerIndex()); writeDoubleArray(out, flat.getLayerOutput()); out.writeInt(flat.getOutputCount()); writeIntArray(out, flat.getWeightIndex()); writeDoubleArray(out, flat.getWeights()); writeDoubleArray(out, flat.getBiasActivation()); // write activation list out.writeInt(flat.getActivationFunctions().length); for (final ActivationFunction af : flat.getActivationFunctions()) { ml.shifu.shifu.core.dtrain.StringUtils.writeString(out, af.getClass().getSimpleName()); writeDoubleArray(out, af.getParams()); } // write sub sets Set<Integer> featureList = network.getFeatureSet(); if (featureList == null || featureList.size() == 0) { out.writeInt(0); } else { out.writeInt(featureList.size()); for (Integer integer : featureList) { out.writeInt(integer); } } }
From source file:com.marklogic.tree.ExpandedTree.java
@Override public void write(DataOutput out) throws IOException { out.writeLong(uriKey);/* w w w .j av a2s . c om*/ out.writeLong(uniqKey); out.writeLong(linkKey); out.writeInt(numKeys); if (numKeys > 0) { for (long key : keys) { out.writeLong(key); } } if (atomData != null && atomData.length > 0) { out.writeInt(atomData.length); for (int i = 0; i < atomData.length; i++) { out.writeByte(atomData[i]); } } else { out.writeInt(0); } out.writeInt(atomLimit); if (atomIndex != null && atomIndex.length > 0) { for (int i = 0; i < atomIndex.length; i++) { out.writeInt(atomIndex[i]); } } if (nodeNameNameAtom != null && nodeNameNameAtom.length > 0) { out.writeInt(nodeNameNameAtom.length); for (int i = 0; i < nodeNameNameAtom.length; i++) { out.writeInt(nodeNameNameAtom[i]); out.writeInt(nodeNameNamespaceAtom[i]); } } else { out.writeInt(0); } out.writeInt(numNodeReps); if (numNodeReps > 0) { for (int i = 0; i < numNodeReps; i++) { out.writeLong(nodeOrdinal[i]); out.writeByte(nodeKind[i]); out.writeInt(nodeRepID[i]); out.writeInt(nodeParentNodeRepID[i]); } } if (elemNodeNodeNameRepID != null && elemNodeNodeNameRepID.length > 0) { out.writeInt(elemNodeNodeNameRepID.length); for (int i = 0; i < elemNodeNodeNameRepID.length; i++) { out.writeInt(elemNodeNodeNameRepID[i]); out.writeInt(elemNodeAttrNodeRepID[i]); out.writeInt(elemNodeChildNodeRepID[i]); out.writeInt(elemNodeElemDeclRepID[i]); out.writeInt(elemNodeNumAttributes[i]); out.writeInt(elemNodeNumDefaultAttrs[i]); out.writeInt(elemNodeNumChildren[i]); out.writeInt(elemNodeFlags[i]); } } else { out.writeInt(0); } if (attrNodeNodeNameRepID != null && attrNodeNodeNameRepID.length > 0) { out.writeInt(attrNodeNodeNameRepID.length); for (int i = 0; i < attrNodeNodeNameRepID.length; i++) { out.writeInt(attrNodeNodeNameRepID[i]); out.writeInt(attrNodeTextRepID[i]); out.writeInt(attrNodeAttrDeclRepID[i]); } } else { out.writeInt(0); } out.writeInt(numLinkNodeReps); if (numLinkNodeReps > 0) { for (int i = 0; i < numLinkNodeReps; i++) { out.writeLong(linkNodeKey[i]); out.writeLong(linkNodeNodeCount[i]); out.writeInt(linkNodeNodeNameRepID[i]); out.writeInt(linkNodeNodeRepID[i]); } } if (docNodeTextRepID != null && docNodeTextRepID.length > 0) { out.writeInt(docNodeTextRepID.length); for (int i = 0; i < docNodeTextRepID.length; i++) { out.writeInt(docNodeTextRepID[i]); out.writeInt(docNodeChildNodeRepID[i]); out.writeInt(docNodeNumChildren[i]); } } else { out.writeInt(0); } if (piNodeTargetAtom != null && piNodeTargetAtom.length > 0) { out.writeInt(piNodeTargetAtom.length); for (int i = 0; i < piNodeTargetAtom.length; i++) { out.writeInt(piNodeTargetAtom[i]); out.writeInt(piNodeTextRepID[i]); } } else { out.writeInt(0); } out.writeInt(numNSNodeReps); if (numNSNodeReps > 0) { for (int i = 0; i < numNSNodeReps; i++) { out.writeLong(nsNodeOrdinal[i]); out.writeInt(nsNodePrevNSNodeRepID[i]); out.writeInt(nsNodePrefixAtom[i]); out.writeInt(nsNodeUriAtom[i]); } } // skip permission node since it's not exposed to the API out.writeInt(uriTextRepID); out.writeInt(colsTextRepID); out.writeInt(numTextReps); if (numTextReps > 0) { for (int i = 0; i < numTextReps; i++) { out.writeInt(textReps[i]); } } if (arrayNodeTextRepID != null && arrayNodeTextRepID.length > 0) { out.writeInt(arrayNodeTextRepID.length); for (int i = 0; i < arrayNodeTextRepID.length; i++) { out.writeInt(arrayNodeTextRepID[i]); out.writeInt(arrayNodeChildNodeRepID[i]); out.writeInt(arrayNodeNumChildren[i]); } } else { out.writeInt(0); } if (doubles != null && doubles.length > 0) { out.writeInt(doubles.length); for (int i = 0; i < doubles.length; i++) { out.writeDouble(doubles[i]); } } else { out.writeInt(0); } }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * //from www .j a v a2s.c o m * @param out * @throws IOException */ private void writeSparseToDense(DataOutput out) throws IOException { //write block type 'dense' out.writeByte(BlockType.DENSE_BLOCK.ordinal()); //write data (from sparse to dense) if (sparseRows == null) //empty block for (int i = 0; i < rlen * clen; i++) out.writeDouble(0); else //existing sparse block { for (int i = 0; i < rlen; i++) { if (i < sparseRows.length && sparseRows[i] != null && !sparseRows[i].isEmpty()) { SparseRow arow = sparseRows[i]; int alen = arow.size(); int[] aix = arow.getIndexContainer(); double[] avals = arow.getValueContainer(); //foreach non-zero value, fill with 0s if required for (int j = 0, j2 = 0; j2 < alen; j++, j2++) { for (; j < aix[j2]; j++) out.writeDouble(0); out.writeDouble(avals[j2]); } //remaining 0 values in row for (int j = aix[alen - 1] + 1; j < clen; j++) out.writeDouble(0); } else //empty row for (int j = 0; j < clen; j++) out.writeDouble(0); } } }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * /*from w w w . j ava2s. c om*/ * @param out * @throws IOException */ private void writeDenseBlock(DataOutput out) throws IOException { out.writeByte(BlockType.DENSE_BLOCK.ordinal()); int limit = rlen * clen; if (out instanceof MatrixBlockDataOutput) //fast serialize ((MatrixBlockDataOutput) out).writeDoubleArray(limit, denseBlock); else //general case (if fast serialize not supported) for (int i = 0; i < limit; i++) out.writeDouble(denseBlock[i]); }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * /*from www.j a v a 2 s. c om*/ * @param out * @throws IOException */ private void writeDenseToUltraSparse(DataOutput out) throws IOException { out.writeByte(BlockType.ULTRA_SPARSE_BLOCK.ordinal()); writeNnzInfo(out, true); long wnnz = 0; if (clen > 1) //ULTRA-SPARSE BLOCK { //block: write ijv-triples for (int r = 0, ix = 0; r < rlen; r++) for (int c = 0; c < clen; c++, ix++) if (denseBlock[ix] != 0) { out.writeInt(r); out.writeInt(c); out.writeDouble(denseBlock[ix]); wnnz++; } } else //ULTRA-SPARSE COL { //col: write iv-pairs for (int r = 0; r < rlen; r++) if (denseBlock[r] != 0) { out.writeInt(r); out.writeDouble(denseBlock[r]); wnnz++; } } //validity check (nnz must exactly match written nnz) if (nonZeros != wnnz) { throw new IOException( "Invalid number of serialized non-zeros: " + wnnz + " (expected: " + nonZeros + ")"); } }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * /*from w w w . j a v a 2 s . co m*/ * @param out * @throws IOException */ private void writeDenseToSparse(DataOutput out) throws IOException { out.writeByte(BlockType.SPARSE_BLOCK.ordinal()); //block type writeNnzInfo(out, false); int start = 0; for (int r = 0; r < rlen; r++) { //count nonzeros int nr = 0; for (int i = start; i < start + clen; i++) if (denseBlock[i] != 0.0) nr++; out.writeInt(nr); for (int c = 0; c < clen; c++) { if (denseBlock[start] != 0.0) { out.writeInt(c); out.writeDouble(denseBlock[start]); } start++; } } }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * /*from w w w . j a v a 2s . c om*/ * @param out * @throws IOException */ private void writeSparseToUltraSparse(DataOutput out) throws IOException { out.writeByte(BlockType.ULTRA_SPARSE_BLOCK.ordinal()); writeNnzInfo(out, true); long wnnz = 0; if (clen > 1) //ULTRA-SPARSE BLOCK { //block: write ijv-triples for (int r = 0; r < Math.min(rlen, sparseRows.length); r++) if (sparseRows[r] != null && !sparseRows[r].isEmpty()) { int alen = sparseRows[r].size(); int[] aix = sparseRows[r].getIndexContainer(); double[] avals = sparseRows[r].getValueContainer(); for (int j = 0; j < alen; j++) { //ultra-sparse block: write ijv-triples out.writeInt(r); out.writeInt(aix[j]); out.writeDouble(avals[j]); wnnz++; } } } else //ULTRA-SPARSE COL { //block: write iv-pairs (should never happen since always dense) for (int r = 0; r < Math.min(rlen, sparseRows.length); r++) if (sparseRows[r] != null && !sparseRows[r].isEmpty()) { out.writeInt(r); out.writeDouble(sparseRows[r].getValueContainer()[0]); wnnz++; } } //validity check (nnz must exactly match written nnz) if (nonZeros != wnnz) { throw new IOException( "Invalid number of serialized non-zeros: " + wnnz + " (expected: " + nonZeros + ")"); } }
From source file:com.ibm.bi.dml.runtime.matrix.data.MatrixBlock.java
/** * //from w w w . j av a 2 s.c om * @param out * @throws IOException */ private void writeSparseBlock(DataOutput out) throws IOException { out.writeByte(BlockType.SPARSE_BLOCK.ordinal()); writeNnzInfo(out, false); if (out instanceof MatrixBlockDataOutput) //fast serialize ((MatrixBlockDataOutput) out).writeSparseRows(rlen, sparseRows); else //general case (if fast serialize not supported) { int r = 0; for (; r < Math.min(rlen, sparseRows.length); r++) { if (sparseRows[r] == null) out.writeInt(0); else { int nr = sparseRows[r].size(); out.writeInt(nr); int[] cols = sparseRows[r].getIndexContainer(); double[] values = sparseRows[r].getValueContainer(); for (int j = 0; j < nr; j++) { out.writeInt(cols[j]); out.writeDouble(values[j]); } } } for (; r < rlen; r++) out.writeInt(0); } }