water.fvec.Frame.<init>()方法的使用及代码示例

x33g5p2x  于2022-01-19 转载在 其他  
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本文整理了Java中water.fvec.Frame.<init>()方法的一些代码示例，展示了Frame.<init>()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Frame.<init>()方法的具体详情如下：
包路径：water.fvec.Frame
类名称：Frame
方法名：<init>

Frame.<init>介绍

暂无

代码示例

代码示例来源：origin: h2oai/h2o-2

/**
 * Create a new frame based on given column data.
 * @param names  name of frame columns
 * @param vecs  columns data represented by individual data
 * @return a new frame composed of given vectors.
 */
public static Frame frame(String[] names, Vec[] vecs) { return new Frame(names, vecs); }
/**

代码示例来源：origin: h2oai/h2o-2

/** Create a subframe from given interval of columns.
 *
 * @param startIdx index of first column (inclusive)
 * @param endIdx index of the last column (exclusive)
 * @return a new frame containing specified interval of columns
 */
public Frame subframe(int startIdx, int endIdx) {
 Frame result = new Frame(Arrays.copyOfRange(_names,startIdx,endIdx),Arrays.copyOfRange(vecs(),startIdx,endIdx));
 return result;
}

代码示例来源：origin: h2oai/h2o-3

@Override public Frame scoreReconstruction(Frame frame, Key<Frame> destination_key, boolean reverse_transform) {
 Frame adaptedFr = new Frame(frame);
 adaptTestForTrain(adaptedFr, true, false);
 return reconstruct(frame, adaptedFr, destination_key, true, reverse_transform);
}

代码示例来源：origin: h2oai/h2o-3

private Frame generateFrameOfZeros(int rowCount, int colCount) {
 Vec tempVec = Vec.makeZero(rowCount);
 return(new Frame(tempVec.makeZeros(colCount)));  // return a frame of zeros with size rowCount by colCount
}

代码示例来源：origin: h2oai/h2o-2

protected final Frame selectFrame(Frame frame) {
  Vec[] vecs = new Vec[cols.length];
  String[] names = new String[cols.length];
  for( int i = 0; i < cols.length; i++ ) {
   vecs[i] = frame.vecs()[cols[i]];
   names[i] = frame.names()[cols[i]];
  }
  return new Frame(names, vecs);
 }
}

代码示例来源：origin: h2oai/h2o-3

@Override
public Frame scoreLeafNodeAssignment(Frame frame, LeafNodeAssignmentType type, Key<Frame> destination_key) {
 Frame adaptFrm = new Frame(frame);
 adaptTestForTrain(adaptFrm, true, false);
 final String[] names = makeAllTreeColumnNames();
 AssignLeafNodeTaskBase task = AssignLeafNodeTaskBase.make(_output, type);
 return task.execute(adaptFrm, names, destination_key);
}

代码示例来源：origin: h2oai/h2o-3

@Override
protected Frame makeValidWorkspace() {
 // FIXME: this is not efficient, we need a sparse volatile chunks
 Vec[] tmp = _valid.anyVec().makeVolatileDoubles(numClassTrees());
 String[] tmpNames = new String[tmp.length];
 for (int i = 0; i < tmpNames.length; i++)
  tmpNames[i] = "__P_" + i;
 return new Frame(tmpNames, tmp);
}

代码示例来源：origin: h2oai/h2o-3

ModelMetrics scoreAndMakeModelMetrics(SharedTreeModel model, Frame fr, Frame adaptedFr, boolean buildTreeOneNode) {
 Frame input = _preds != null ? new Frame(adaptedFr).add(_preds) : adaptedFr;
 return doAll(input, buildTreeOneNode)
     .makeModelMetrics(model, fr, adaptedFr, _preds);
}

代码示例来源：origin: h2oai/h2o-3

public ModelMetrics doScoreMetricsOneFrame(Frame frame, Job job) {
  Frame pred = this.predictScoreImpl(frame, new Frame(frame), null, job, true, CFuncRef.from(_parms._custom_metric_func));
  pred.remove();
  return ModelMetrics.getFromDKV(this, frame);
}

代码示例来源：origin: h2oai/h2o-3

@Override public Frame outputFrame(Key<Frame> key, String [] names, String [][] domains){
 _predFrame = new Frame(key, names, _predFrame.vecs());
 if (domains!=null)
  _predFrame.vec(0).setDomain(domains[0]); //only the label is ever categorical
 if (_predFrame._key!=null)
  DKV.put(_predFrame);
 return _predFrame;
}
@Override public void map(Chunk[] chks, NewChunk[] cpreds) { }

代码示例来源：origin: h2oai/h2o-3

@Override
public Frame scoreStagedPredictions(Frame frame, Key<Frame> destination_key) {
 Frame adaptFrm = new Frame(frame);
 adaptTestForTrain(adaptFrm, true, false);
 final String[] names = makeAllTreeColumnNames();
 final int outputcols = names.length;
 return new StagedPredictionsTask(this)
     .doAll(outputcols, Vec.T_NUM, adaptFrm)
     .outputFrame(destination_key, names, null);
}

代码示例来源：origin: h2oai/h2o-3

static Frame discretizeTime(double[] time, Vec startVec, Vec stopVec) {
 final boolean hasStartColumn = startVec != null;
 final Frame f = new Frame();
 if (hasStartColumn)
  f.add("__startCol", startVec);
 f.add("__stopCol", stopVec);
 return new DiscretizeTimeTask(time, startVec != null).doAll(hasStartColumn ? 2 : 1, Vec.T_NUM, f).outputFrame();
}

代码示例来源：origin: h2oai/h2o-3

private static Frame fullFrame(CoxPH coxPH, Frame adaptFr, Frame train) {
 if (! coxPH._parms.isStratified())
  return adaptFr;
 Frame ff = new Frame();
 for (String col : coxPH._parms._stratify_by)
  if (adaptFr.vec(col) == null)
   ff.add(col, train.vec(col));
 ff.add(adaptFr);
 return ff;
}

代码示例来源：origin: h2oai/h2o-3

/**
 * @return frame without rows with NAs in `columnIndex` column
 */
static Frame filterOutNAsInColumn(Frame fr, int columnIndex) {
 Frame noNaPredicateFrame = new IsNotNaTask().doAll(1, Vec.T_NUM, new Frame(fr.vec(columnIndex))).outputFrame();
 return selectByPredicate(fr, noNaPredicateFrame);
}

代码示例来源：origin: h2oai/h2o-3

private static Frame filterByValueBase(Frame fr, int columnIndex, double value, boolean isInverted) {
 Frame predicateFrame = new FilterByValueTask(value, isInverted).doAll(1, Vec.T_NUM, new Frame(fr.vec(columnIndex))).outputFrame();
 return selectByPredicate(fr, predicateFrame);
}

代码示例来源：origin: h2oai/h2o-3

public DataInfo validDinfo(Frame valid) {
 DataInfo res = new DataInfo(_adaptedFrame,null,1,_useAllFactorLevels,TransformType.NONE,TransformType.NONE,_skipMissing,_imputeMissing,!(_skipMissing || _imputeMissing),_weights,_offset,_fold);
 res._interactions = _interactions;
 res._interactionSpec = _interactionSpec;
 if (_interactionSpec != null) {
  valid = Model.makeInteractions(valid, true, _interactions, _useAllFactorLevels, _skipMissing, false).add(valid);
 }
 res._adaptedFrame = new Frame(_adaptedFrame.names(),valid.vecs(_adaptedFrame.names()));
 res._valid = true;
 return res;
}

代码示例来源：origin: h2oai/h2o-2

void tos_into_slot( int idx, String id ) {
 subRef(_ary[idx], _key[idx]);
 subRef(_fcn[idx]);
 Frame fr =                   _ary[_sp-1];
 _ary[idx] = fr==null ? null : addRef(new Frame(fr));
 _d  [idx] =                  _d  [_sp-1] ;
 _fcn[idx] =           addRef(_fcn[_sp-1]);
 _str[idx] =                  _str[_sp-1] ;
 _key[idx] = fr!=null ? id : null;
 assert _ary[0]== null || check_refcnt(_ary[0].anyVec());
}

代码示例来源：origin: h2oai/h2o-3

public static void runBigScore(GLMModel model,
                Frame fr, boolean computeMetrics,
                boolean makePrediction, Job j) {
 String[] names = model.makeScoringNames();
 String[][] domains = model.makeScoringDomains(fr, computeMetrics, names);
 Frame adaptedFrame = new Frame(fr);
 model.adaptTestForTrain(adaptedFrame, true, computeMetrics);
 Scope.track(adaptedFrame);
 model
     .makeBigScoreTask(domains, names, adaptedFrame, computeMetrics, makePrediction, j, null)
     .doAll(adaptedFrame);
}

代码示例来源：origin: h2oai/h2o-3

private GLMScore makeScoringTask(Frame adaptFrm, boolean generatePredictions, Job j){
 int responseId = adaptFrm.find(_output.responseName());
 if(responseId > -1 && adaptFrm.vec(responseId).isBad()) { // remove inserted invalid response
  adaptFrm = new Frame(adaptFrm.names(),adaptFrm.vecs());
  adaptFrm.remove(responseId);
 }
 // Build up the names & domains.
 final boolean computeMetrics = adaptFrm.vec(_output.responseName()) != null && !adaptFrm.vec(_output.responseName()).isBad();
 String [] domain = _output.nclasses()<=1 ? null : !computeMetrics ? _output._domains[_output._domains.length-1] : adaptFrm.lastVec().domain();
 // Score the dataset, building the class distribution & predictions
 return new GLMScore(j, this, _output._dinfo.scoringInfo(_output._names,adaptFrm),domain,computeMetrics, generatePredictions);
}
/** Score an already adapted frame.  Returns a new Frame with new result

代码示例来源：origin: h2oai/h2o-3

@Test
public void test_toTwoDimTable_with_empty_models_and_without_sort_metric() {
 Leaderboard lb = null;
 UserFeedback ufb = new UserFeedback(new AutoML());
 try {
  lb = Leaderboard.getOrMakeLeaderboard("dummy_lb_no_sort_metric", ufb, new Frame(), null);
  TwoDimTable table = lb.toTwoDimTable();
  Assert.assertNotNull("empty leaderboard should also produce a TwoDimTable", table);
  Assert.assertEquals("no models in this leaderboard", table.getTableDescription());
 } finally {
  if (lb != null) lb.deleteWithChildren();
  ufb.delete();
 }
}

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