-
Notifications
You must be signed in to change notification settings - Fork 461
/
ParameterizedBuiltinFunctionExpression.java
877 lines (748 loc) · 34.4 KB
/
ParameterizedBuiltinFunctionExpression.java
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysds.parser;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.HashMap;
import java.util.HashSet;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Set;
import java.util.stream.Collectors;
import org.antlr.v4.runtime.ParserRuleContext;
import org.apache.wink.json4j.JSONObject;
import org.apache.sysds.common.Builtins;
import org.apache.sysds.common.Types.DataType;
import org.apache.sysds.common.Types.ParamBuiltinOp;
import org.apache.sysds.common.Types.ValueType;
import org.apache.sysds.parser.LanguageException.LanguageErrorCodes;
import org.apache.sysds.runtime.util.CollectionUtils;
public class ParameterizedBuiltinFunctionExpression extends DataIdentifier
{
//note: we use a linked hashmap to preserve the order of
//parameters if needed, such as for named lists
private Builtins _opcode;
private LinkedHashMap<String,Expression> _varParams;
public static final String TF_FN_PARAM_DATA = "target";
public static final String TF_FN_PARAM_MTD2 = "meta";
public static final String TF_FN_PARAM_SPEC = "spec";
public static final String TF_FN_PARAM_MTD = "transformPath"; //NOTE MB: for backwards compatibility
public static HashMap<Builtins, ParamBuiltinOp> pbHopMap;
static {
pbHopMap = new HashMap<>();
pbHopMap.put(Builtins.GROUPEDAGG, ParamBuiltinOp.GROUPEDAGG);
pbHopMap.put(Builtins.RMEMPTY, ParamBuiltinOp.RMEMPTY);
pbHopMap.put(Builtins.REPLACE, ParamBuiltinOp.REPLACE);
pbHopMap.put(Builtins.LOWER_TRI, ParamBuiltinOp.LOWER_TRI);
pbHopMap.put(Builtins.UPPER_TRI, ParamBuiltinOp.UPPER_TRI);
// For order, a ReorgOp is constructed with ReorgOp.SORT type
pbHopMap.put(Builtins.ORDER, ParamBuiltinOp.INVALID);
// Distribution Functions
pbHopMap.put(Builtins.CDF, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.PNORM, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.PT, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.PF, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.PCHISQ, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.PEXP, ParamBuiltinOp.CDF);
pbHopMap.put(Builtins.INVCDF, ParamBuiltinOp.INVCDF);
pbHopMap.put(Builtins.QNORM, ParamBuiltinOp.INVCDF);
pbHopMap.put(Builtins.QT, ParamBuiltinOp.INVCDF);
pbHopMap.put(Builtins.QF, ParamBuiltinOp.INVCDF);
pbHopMap.put(Builtins.QCHISQ, ParamBuiltinOp.INVCDF);
pbHopMap.put(Builtins.QEXP, ParamBuiltinOp.INVCDF);
// toString
pbHopMap.put(Builtins.TOSTRING, ParamBuiltinOp.TOSTRING);
}
public static ParameterizedBuiltinFunctionExpression getParamBuiltinFunctionExpression(ParserRuleContext ctx,
String functionName, ArrayList<ParameterExpression> paramExprsPassed, String fileName) {
if (functionName == null || paramExprsPassed == null)
return null;
Builtins pbifop = Builtins.get(functionName, true);
if ( pbifop == null )
return null;
LinkedHashMap<String,Expression> varParams = new LinkedHashMap<>();
for (ParameterExpression pexpr : paramExprsPassed)
varParams.put(pexpr.getName(), pexpr.getExpr());
ParameterizedBuiltinFunctionExpression retVal =
new ParameterizedBuiltinFunctionExpression(ctx, pbifop,varParams, fileName);
return retVal;
}
public ParameterizedBuiltinFunctionExpression(ParserRuleContext ctx, Builtins op, LinkedHashMap<String,Expression> varParams,
String filename) {
_opcode = op;
_varParams = varParams;
setCtxValuesAndFilename(ctx, filename);
}
public ParameterizedBuiltinFunctionExpression(Builtins op,
LinkedHashMap<String, Expression> varParams, ParseInfo parseInfo) {
_opcode = op;
_varParams = varParams;
setParseInfo(parseInfo);
}
@Override
public Expression rewriteExpression(String prefix) {
LinkedHashMap<String,Expression> newVarParams = new LinkedHashMap<>();
for (String key : _varParams.keySet()){
Expression newExpr = _varParams.get(key).rewriteExpression(prefix);
newVarParams.put(key, newExpr);
}
ParameterizedBuiltinFunctionExpression retVal =
new ParameterizedBuiltinFunctionExpression(_opcode, newVarParams, this);
return retVal;
}
public void setOpcode(Builtins op) {
_opcode = op;
}
public Builtins getOpCode() {
return _opcode;
}
public HashMap<String,Expression> getVarParams() {
return _varParams;
}
public Expression getVarParam(String name) {
return _varParams.get(name);
}
public void addVarParam(String name, Expression value){
_varParams.put(name, value);
}
/**
* Validate parse tree : Process BuiltinFunction Expression in an assignment
* statement
*/
@Override
public void validateExpression(HashMap<String, DataIdentifier> ids, HashMap<String, ConstIdentifier> constVars, boolean conditional)
{
// validate all input parameters
for ( String s : getVarParams().keySet() ) {
Expression paramExpr = getVarParam(s);
if (paramExpr instanceof FunctionCallIdentifier)
raiseValidateError("UDF function call not supported as parameter to built-in function call", false);
paramExpr.validateExpression(ids, constVars, conditional);
}
String outputName = getTempName();
DataIdentifier output = new DataIdentifier(outputName);
//output.setProperties(this.getFirstExpr().getOutput());
this.setOutput(output);
// IMPORTANT: for each operation, one must handle unnamed parameters
switch (this.getOpCode()) {
case GROUPEDAGG:
validateGroupedAgg(output, conditional);
break;
case CDF:
case INVCDF:
case PNORM:
case QNORM:
case PT:
case QT:
case PF:
case QF:
case PCHISQ:
case QCHISQ:
case PEXP:
case QEXP:
validateDistributionFunctions(output, conditional);
break;
case RMEMPTY:
validateRemoveEmpty(output, conditional);
break;
case REPLACE:
validateReplace(output, conditional);
break;
case ORDER:
validateOrder(output, conditional);
break;
case TRANSFORMAPPLY:
validateTransformApply(output, conditional);
break;
case TRANSFORMDECODE:
validateTransformDecode(output, conditional);
break;
case TRANSFORMCOLMAP:
validateTransformColmap(output, conditional);
break;
case TRANSFORMMETA:
validateTransformMeta(output, conditional);
break;
case LOWER_TRI:
case UPPER_TRI:
validateExtractTriangular(output, getOpCode(), conditional);
break;
case TOSTRING:
validateCastAsString(output, conditional);
break;
case LISTNV:
validateNamedList(output, conditional);
break;
case PARAMSERV:
validateParamserv(output, conditional);
break;
default: //always unconditional (because unsupported operation)
//handle common issue of transformencode
if( getOpCode()==Builtins.TRANSFORMENCODE )
raiseValidateError("Parameterized function "+ getOpCode() +" requires a multi-assignment statement "
+ "for data and metadata.", false, LanguageErrorCodes.UNSUPPORTED_EXPRESSION);
else
raiseValidateError("Unsupported parameterized function "+ getOpCode(),
false, LanguageErrorCodes.UNSUPPORTED_EXPRESSION);
}
}
@Override
public void validateExpression(MultiAssignmentStatement stmt, HashMap<String, DataIdentifier> ids, HashMap<String, ConstIdentifier> constVars, boolean conditional)
{
// validate all input parameters
for ( String s : getVarParams().keySet() ) {
Expression paramExpr = getVarParam(s);
if (paramExpr instanceof FunctionCallIdentifier)
raiseValidateError("UDF function call not supported as parameter to built-in function call", false);
paramExpr.validateExpression(ids, constVars, conditional);
}
_outputs = new Identifier[stmt.getTargetList().size()];
int count = 0;
for (DataIdentifier outParam: stmt.getTargetList()){
DataIdentifier tmp = new DataIdentifier(outParam);
tmp.setParseInfo(this);
_outputs[count++] = tmp;
}
switch (this.getOpCode()) {
case TRANSFORMENCODE:
DataIdentifier out1 = (DataIdentifier) getOutputs()[0];
DataIdentifier out2 = (DataIdentifier) getOutputs()[1];
validateTransformEncode(out1, out2, conditional);
break;
default: //always unconditional (because unsupported operation)
raiseValidateError("Unsupported parameterized function "+ getOpCode(), false, LanguageErrorCodes.INVALID_PARAMETERS);
}
}
private void validateParamserv(DataIdentifier output, boolean conditional) {
String fname = getOpCode().name();
// validate the first five arguments
if (getVarParams().size() < 1) {
raiseValidateError("Should provide more arguments for function " + fname, false, LanguageErrorCodes.INVALID_PARAMETERS);
}
//check for invalid parameters
Set<String> valid = CollectionUtils.asSet(Statement.PS_MODEL, Statement.PS_FEATURES, Statement.PS_LABELS,
Statement.PS_VAL_FEATURES, Statement.PS_VAL_LABELS, Statement.PS_UPDATE_FUN, Statement.PS_AGGREGATION_FUN,
Statement.PS_MODE, Statement.PS_UPDATE_TYPE, Statement.PS_FREQUENCY, Statement.PS_EPOCHS,
Statement.PS_BATCH_SIZE, Statement.PS_PARALLELISM, Statement.PS_SCHEME, Statement.PS_FED_RUNTIME_BALANCING,
Statement.PS_FED_WEIGHING, Statement.PS_HYPER_PARAMS, Statement.PS_CHECKPOINTING, Statement.PS_SEED);
checkInvalidParameters(getOpCode(), getVarParams(), valid);
// check existence and correctness of parameters
checkDataType(fname, Statement.PS_MODEL, DataType.LIST, conditional); // check the model which is the only non-parameterized argument
checkDataType(fname, Statement.PS_FEATURES, DataType.MATRIX, conditional);
checkDataType(fname, Statement.PS_LABELS, DataType.MATRIX, conditional);
checkDataValueType(true, fname, Statement.PS_VAL_FEATURES, DataType.MATRIX, ValueType.FP64, conditional);
checkDataValueType(true, fname, Statement.PS_VAL_LABELS, DataType.MATRIX, ValueType.FP64, conditional);
checkDataValueType(false, fname, Statement.PS_UPDATE_FUN, DataType.SCALAR, ValueType.STRING, conditional);
checkDataValueType(false, fname, Statement.PS_AGGREGATION_FUN, DataType.SCALAR, ValueType.STRING, conditional);
checkStringParam(true, fname, Statement.PS_MODE, conditional);
checkStringParam(true, fname, Statement.PS_UPDATE_TYPE, conditional);
checkStringParam(true, fname, Statement.PS_FREQUENCY, conditional);
checkDataValueType(false, fname, Statement.PS_EPOCHS, DataType.SCALAR, ValueType.INT64, conditional);
checkDataValueType(true, fname, Statement.PS_BATCH_SIZE, DataType.SCALAR, ValueType.INT64, conditional);
checkDataValueType(true, fname, Statement.PS_PARALLELISM, DataType.SCALAR, ValueType.INT64, conditional);
checkStringParam(true, fname, Statement.PS_SCHEME, conditional);
checkStringParam(true, fname, Statement.PS_FED_RUNTIME_BALANCING, conditional);
checkStringParam(true, fname, Statement.PS_FED_WEIGHING, conditional);
checkDataValueType(true, fname, Statement.PS_HYPER_PARAMS, DataType.LIST, ValueType.UNKNOWN, conditional);
checkStringParam(true, fname, Statement.PS_CHECKPOINTING, conditional);
checkDataValueType(true, fname, Statement.PS_SEED, DataType.SCALAR, ValueType.INT64, conditional);
// set output characteristics
output.setDataType(DataType.LIST);
output.setValueType(ValueType.UNKNOWN);
output.setDimensions(getVarParam(Statement.PS_MODEL).getOutput().getDim1(), 1);
output.setBlocksize(-1);
}
private void checkStringParam(boolean optional, String fname, String pname, boolean conditional) {
Expression param = getVarParam(pname);
if (param == null) {
if (optional) {
return;
}
raiseValidateError(String.format("Function %s should provide parameter '%s'", fname, pname), conditional);
}
if (!(param.getOutput().getDataType().isScalar() && param.getOutput().getValueType().equals(ValueType.STRING))) {
raiseValidateError(
String.format("Function %s should provide a string value for %s parameter.", fname, pname),
conditional);
}
}
// example: A = transformapply(target=X, meta=M, spec=s)
private void validateTransformApply(DataIdentifier output, boolean conditional)
{
//validate data / metadata (recode maps)
checkDataType("transformapply", TF_FN_PARAM_DATA, DataType.FRAME, conditional);
checkDataType("transformapply", TF_FN_PARAM_MTD2, DataType.FRAME, conditional);
//validate specification
checkDataValueType(false, "transformapply", TF_FN_PARAM_SPEC, DataType.SCALAR, ValueType.STRING, conditional);
validateTransformSpec(TF_FN_PARAM_SPEC, conditional);
//set output dimensions
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(-1, -1);
}
private void validateTransformDecode(DataIdentifier output, boolean conditional)
{
//validate data / metadata (recode maps)
checkDataType("transformdecode", TF_FN_PARAM_DATA, DataType.MATRIX, conditional);
checkDataType("transformdecode", TF_FN_PARAM_MTD2, DataType.FRAME, conditional);
//validate specification
checkDataValueType(false, "transformdecode", TF_FN_PARAM_SPEC, DataType.SCALAR, ValueType.STRING, conditional);
validateTransformSpec(TF_FN_PARAM_SPEC, conditional);
//set output dimensions
output.setDataType(DataType.FRAME);
output.setValueType(ValueType.STRING);
output.setDimensions(-1, -1);
}
private void validateTransformColmap(DataIdentifier output, boolean conditional)
{
//validate data / metadata (recode maps)
Expression exprTarget = getVarParam(Statement.GAGG_TARGET);
checkDataType("transformcolmap", TF_FN_PARAM_DATA, DataType.FRAME, conditional);
//validate specification
checkDataValueType(false,"transformcolmap", TF_FN_PARAM_SPEC, DataType.SCALAR, ValueType.STRING, conditional);
validateTransformSpec(TF_FN_PARAM_SPEC, conditional);
//set output dimensions
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(exprTarget.getOutput().getDim2(), 3);
}
private void validateTransformMeta(DataIdentifier output, boolean conditional)
{
//validate specification
checkDataValueType(false,"transformmeta", TF_FN_PARAM_SPEC, DataType.SCALAR, ValueType.STRING, conditional);
validateTransformSpec(TF_FN_PARAM_SPEC, conditional);
//validate meta data path
checkDataValueType(false,"transformmeta", TF_FN_PARAM_MTD, DataType.SCALAR, ValueType.STRING, conditional);
//set output dimensions
output.setDataType(DataType.FRAME);
output.setValueType(ValueType.STRING);
output.setDimensions(-1, -1);
}
private void validateTransformEncode(DataIdentifier output1, DataIdentifier output2, boolean conditional)
{
//validate data / metadata (recode maps)
checkDataType("transformencode", TF_FN_PARAM_DATA, DataType.FRAME, conditional);
//validate specification
checkDataValueType(false, "transformencode", TF_FN_PARAM_SPEC, DataType.SCALAR, ValueType.STRING, conditional);
validateTransformSpec(TF_FN_PARAM_SPEC, conditional);
//set output dimensions
output1.setDataType(DataType.MATRIX);
output1.setValueType(ValueType.FP64);
output1.setDimensions(-1, -1);
output2.setDataType(DataType.FRAME);
output2.setValueType(ValueType.STRING);
output2.setDimensions(-1, -1);
}
@SuppressWarnings("unused")
private void validateTransformSpec(String pname, boolean conditional) {
Expression data = getVarParam(pname);
if( data instanceof StringIdentifier ) {
try {
StringIdentifier spec = (StringIdentifier)data;
new JSONObject(spec.getValue()); //for validate
}
catch(Exception ex) {
raiseValidateError("Transform specification parsing issue: ",
conditional, ex.getMessage());
}
}
}
private void validateExtractTriangular(DataIdentifier output, Builtins op, boolean conditional) {
//check for invalid parameters
Set<String> valid = CollectionUtils.asSet("target", "diag", "values");
checkInvalidParameters(op, getVarParams(), valid);
//check existence and correctness of arguments
checkTargetParam(getVarParam("target"), conditional);
checkOptionalBooleanParam(getVarParam("diag"), "diag", conditional);
checkOptionalBooleanParam(getVarParam("values"), "values", conditional);
if( getVarParam("diag") == null ) //default handling
_varParams.put("diag", new BooleanIdentifier(false));
if( getVarParam("values") == null ) //default handling
_varParams.put("values", new BooleanIdentifier(false));
// Output is a matrix with unknown dims
Identifier in = getVarParam("target").getOutput();
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(in.getDim1(), in.getDim2());
}
private void validateReplace(DataIdentifier output, boolean conditional) {
//check existence and correctness of arguments
Expression target = getVarParam("target");
checkTargetParam(target, conditional);
Expression pattern = getVarParam("pattern");
if( pattern==null ) {
raiseValidateError("Named parameter 'pattern' missing. Please specify the replacement pattern.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
else if( pattern.getOutput().getDataType() != DataType.SCALAR ){
raiseValidateError("Replacement pattern 'pattern' is of type '"+pattern.getOutput().getDataType()+"'. Please, specify a scalar replacement pattern.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
Expression replacement = getVarParam("replacement");
if( replacement==null ) {
raiseValidateError("Named parameter 'replacement' missing. Please specify the replacement value.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
else if( replacement.getOutput().getDataType() != DataType.SCALAR ){
raiseValidateError("Replacement value 'replacement' is of type '"+replacement.getOutput().getDataType()+"'. Please, specify a scalar replacement value.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
// Output is a matrix with same dims as input
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(target.getOutput().getDim1(), target.getOutput().getDim2());
}
private void validateOrder(DataIdentifier output, boolean conditional) {
//check existence and correctness of arguments
Expression target = getVarParam("target");
checkTargetParam(target, conditional);
//check for unsupported parameters
for(String param : getVarParams().keySet())
if( !(param.equals("target") || param.equals("by") || param.equals("decreasing") || param.equals("index.return")) )
raiseValidateError("Unsupported order parameter: '"+param+"'", false);
Expression orderby = getVarParam("by"); //[OPTIONAL] BY
if( orderby == null ) { //default first column, good fit for vectors
orderby = new IntIdentifier(1);
addVarParam("by", orderby);
}
else if( !(orderby.getOutput().getDataType().isScalar()
|| orderby.getOutput().getDataType().isMatrix()) ) {
raiseValidateError("Orderby column 'by' is of type '"+orderby.getOutput().getDataType()+"'. Please, use a scalar or row vector to specify column indexes.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
Expression decreasing = getVarParam("decreasing"); //[OPTIONAL] DECREASING
if( decreasing == null ) { //default: ascending
addVarParam("decreasing", new BooleanIdentifier(false));
}
else if( decreasing.getOutput().getDataType() != DataType.SCALAR ){
raiseValidateError("Ordering 'decreasing' is of type '"+decreasing.getOutput().getDataType()+"', '"+decreasing.getOutput().getValueType()+"'. Please, specify 'decreasing' as a scalar boolean.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
Expression indexreturn = getVarParam("index.return"); //[OPTIONAL] DECREASING
if( indexreturn == null ) { //default: sorted data
indexreturn = new BooleanIdentifier(false);
addVarParam("index.return", indexreturn);
}
else if( indexreturn.getOutput().getDataType() != DataType.SCALAR ){
raiseValidateError("Return type 'index.return' is of type '"+indexreturn.getOutput().getDataType()+"', '"+indexreturn.getOutput().getValueType()+"'. Please, specify 'indexreturn' as a scalar boolean.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
long dim2 = ( indexreturn instanceof BooleanIdentifier ) ?
((BooleanIdentifier)indexreturn).getValue() ? 1: target.getOutput().getDim2() : -1;
// Output is a matrix with same dims as input
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(target.getOutput().getDim1(), dim2 );
}
private void validateRemoveEmpty(DataIdentifier output, boolean conditional) {
//check for invalid parameters
Set<String> valid = CollectionUtils.asSet("target", "margin", "select", "empty.return");
Set<String> invalid = _varParams.keySet().stream()
.filter(k -> !valid.contains(k)).collect(Collectors.toSet());
if( !invalid.isEmpty() )
raiseValidateError("Invalid parameters for removeEmpty: "
+ Arrays.toString(invalid.toArray(new String[0])), false);
//check existence and correctness of arguments
checkTargetParam(getVarParam("target"), conditional);
Expression margin = getVarParam("margin");
if( margin==null ){
raiseValidateError("Named parameter 'margin' missing. Please specify 'rows' or 'cols'.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
else if( !(margin instanceof DataIdentifier) && !margin.toString().equals("rows") && !margin.toString().equals("cols") ){
raiseValidateError("Named parameter 'margin' has an invalid value '"+margin.toString()+"'. Please specify 'rows' or 'cols'.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
Expression select = getVarParam("select");
if( select!=null && select.getOutput().getDataType() != DataType.MATRIX ){
raiseValidateError("Index matrix 'select' is of type '"+select.getOutput().getDataType()+"'. Please specify the select matrix.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
Expression empty = getVarParam("empty.return");
if( empty!=null && (!empty.getOutput().getDataType().isScalar() || empty.getOutput().getValueType() != ValueType.BOOLEAN) ){
raiseValidateError("Boolean parameter 'empty.return' is of type "+empty.getOutput().getDataType()
+"["+empty.getOutput().getValueType()+"].", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
if( empty == null ) //default handling
_varParams.put("empty.return", new BooleanIdentifier(true));
// Output is a matrix with unknown dims
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(-1, -1);
}
private void validateGroupedAgg(DataIdentifier output, boolean conditional)
{
//check existing target and groups
if (getVarParam(Statement.GAGG_TARGET) == null || getVarParam(Statement.GAGG_GROUPS) == null){
raiseValidateError("Must define both target and groups.", conditional);
}
Expression exprTarget = getVarParam(Statement.GAGG_TARGET);
Expression exprGroups = getVarParam(Statement.GAGG_GROUPS);
Expression exprNGroups = getVarParam(Statement.GAGG_NUM_GROUPS);
//check valid input dimensions
boolean colwise = true;
boolean matrix = false;
if( exprGroups.getOutput().dimsKnown() && exprTarget.getOutput().dimsKnown() )
{
//check for valid matrix input
if( exprGroups.getOutput().getDim2()==1 && exprTarget.getOutput().getDim2()>1 )
{
if( getVarParam(Statement.GAGG_WEIGHTS) != null ) {
raiseValidateError("Matrix input not supported with weights.", conditional);
}
if( getVarParam(Statement.GAGG_NUM_GROUPS) == null ) {
raiseValidateError("Matrix input not supported without specified numgroups.", conditional);
}
if( exprGroups.getOutput().getDim1() != exprTarget.getOutput().getDim1() ) {
raiseValidateError("Target and groups must have same dimensions -- " + " target dims: " +
exprTarget.getOutput().getDim1() +" x "+exprTarget.getOutput().getDim2()+", groups dims: " + exprGroups.getOutput().getDim1() + " x 1.", conditional);
}
matrix = true;
}
//check for valid col vector input
else if( exprGroups.getOutput().getDim2()==1 && exprTarget.getOutput().getDim2()==1 )
{
if( exprGroups.getOutput().getDim1() != exprTarget.getOutput().getDim1() ) {
raiseValidateError("Target and groups must have same dimensions -- " + " target dims: " +
exprTarget.getOutput().getDim1() +" x 1, groups dims: " + exprGroups.getOutput().getDim1() + " x 1.", conditional);
}
}
//check for valid row vector input
else if( exprGroups.getOutput().getDim1()==1 && exprTarget.getOutput().getDim1()==1 )
{
if( exprGroups.getOutput().getDim2() != exprTarget.getOutput().getDim2() ) {
raiseValidateError("Target and groups must have same dimensions -- " + " target dims: " +
"1 x " + exprTarget.getOutput().getDim2() +", groups dims: 1 x " + exprGroups.getOutput().getDim2() + ".", conditional);
}
colwise = true;
}
else {
raiseValidateError("Invalid target and groups inputs - dimension mismatch.", conditional);
}
}
//check function parameter
Expression functParam = getVarParam(Statement.GAGG_FN);
if( functParam == null ) {
raiseValidateError("must define function name (fn=<function name>) for aggregate()", conditional);
}
else if (functParam instanceof Identifier)
{
// standardize to lowercase and dequote fname
String fnameStr = functParam.toString();
// check that IF fname="centralmoment" THEN order=m is defined, where m=2,3,4
// check ELSE IF fname is allowed
if(fnameStr.equals(Statement.GAGG_FN_CM)){
String orderStr = getVarParam(Statement.GAGG_FN_CM_ORDER) == null ? null : getVarParam(Statement.GAGG_FN_CM_ORDER).toString();
if (orderStr == null || !(orderStr.equals("2") || orderStr.equals("3") || orderStr.equals("4"))){
raiseValidateError("for centralmoment, must define order. Order must be equal to 2,3, or 4", conditional);
}
}
else if (fnameStr.equals(Statement.GAGG_FN_COUNT)
|| fnameStr.equals(Statement.GAGG_FN_SUM)
|| fnameStr.equals(Statement.GAGG_FN_MEAN)
|| fnameStr.equals(Statement.GAGG_FN_VARIANCE)){}
else {
raiseValidateError("fname is " + fnameStr + " but must be either centeralmoment, count, sum, mean, variance", conditional);
}
}
//determine output dimensions
long outputDim1 = -1, outputDim2 = -1;
if( exprNGroups != null && exprNGroups instanceof Identifier )
{
Identifier numGroups = (Identifier) exprNGroups;
if ( numGroups instanceof ConstIdentifier) {
long ngroups = ((ConstIdentifier)numGroups).getLongValue();
if ( colwise ) {
outputDim1 = ngroups;
outputDim2 = matrix ? exprTarget.getOutput().getDim2() : 1;
}
else {
outputDim1 = 1; //no support for matrix
outputDim2 = ngroups;
}
}
}
//set output meta data
output.setDataType(DataType.MATRIX);
output.setValueType(ValueType.FP64);
output.setDimensions(outputDim1, outputDim2);
}
private void checkTargetParam(Expression target, boolean conditional) {
if( target==null )
raiseValidateError("Named parameter 'target' missing. Please specify the input matrix.",
conditional, LanguageErrorCodes.INVALID_PARAMETERS);
else if( target.getOutput().getDataType() != DataType.MATRIX )
raiseValidateError("Input matrix 'target' is of type '"+target.getOutput().getDataType()
+"'. Please specify the input matrix.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
private void checkOptionalBooleanParam(Expression param, String name, boolean conditional) {
if( param!=null && (!param.getOutput().getDataType().isScalar() || param.getOutput().getValueType() != ValueType.BOOLEAN) ){
raiseValidateError("Boolean parameter '"+name+"' is of type "+param.getOutput().getDataType()
+"["+param.getOutput().getValueType()+"].", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
}
private void checkInvalidParameters(Builtins op, HashMap<String, Expression> params,
Set<String> valid) {
Set<String> invalid = params.keySet().stream().filter(k -> !valid.contains(k)).collect(Collectors.toSet());
if (!invalid.isEmpty()) {
List<String> invalidMsg = invalid.stream().map(k -> {
String val = params.get(k).getText();
return k == null ? val : k + "=" + val;
}).collect(Collectors.toList());
raiseValidateError(String.format("Invalid parameters for %s: %s", op.name(), invalidMsg), false);
}
}
private void validateDistributionFunctions(DataIdentifier output, boolean conditional) {
// CDF and INVCDF expects one unnamed parameter, it must be renamed as "quantile"
// (i.e., we must compute P(X <= x) where x is called as "quantile" )
Builtins op = this.getOpCode();
// check if quantile is of type SCALAR
if ( getVarParam("target") == null || getVarParam("target").getOutput().getDataType() != DataType.SCALAR ) {
raiseValidateError("target must be provided for distribution functions, and it must be a scalar value.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
// Distribution specific checks
switch(op) {
case CDF:
case INVCDF:
if(getVarParam("dist") == null) {
raiseValidateError("For cdf() and icdf(), a distribution function must be specified (as a string).", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
break;
case QF:
case PF:
if(getVarParam("df1") == null || getVarParam("df2") == null ) {
raiseValidateError("Two degrees of freedom df1 and df2 must be provided for F-distribution.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
break;
case QT:
case PT:
if(getVarParam("df") == null ) {
raiseValidateError("Degrees of freedom df must be provided for t-distribution.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
break;
case QCHISQ:
case PCHISQ:
if(getVarParam("df") == null ) {
raiseValidateError("Degrees of freedom df must be provided for chi-squared-distribution.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
break;
default:
break;
// Not checking for QNORM, PNORM: distribution parameters mean and sd are optional with default values 0.0 and 1.0, respectively
// Not checking for QEXP, PEXP: distribution parameter rate is optional with a default values 1.0
// For all cdf functions, additional parameter lower.tail is optional with a default value TRUE
}
// CDF and INVCDF specific checks:
switch(op) {
case INVCDF:
case QNORM:
case QF:
case QT:
case QCHISQ:
case QEXP:
if(getVarParam("lower.tail") != null ) {
raiseValidateError("Lower tail argument is invalid while computing inverse cumulative probabilities.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
break;
case CDF:
case PNORM:
case PF:
case PT:
case PCHISQ:
case PEXP:
// no checks yet
break;
default:
break;
}
// Output is a scalar
output.setDataType(DataType.SCALAR);
output.setValueType(ValueType.FP64);
output.setDimensions(0, 0);
}
private void validateCastAsString(DataIdentifier output, boolean conditional) {
HashMap<String, Expression> varParams = getVarParams();
// replace parameter name for matrix argument
if( varParams.containsKey(null) )
varParams.put("target", varParams.remove(null));
// check validate parameter names
String[] validArgsArr = {"target", "rows", "cols", "decimal", "sparse", "sep", "linesep"};
HashSet<String> validArgs = new HashSet<>(Arrays.asList(validArgsArr));
for( String k : varParams.keySet() ) {
if( !validArgs.contains(k) ) {
raiseValidateError("Invalid parameter " + k + " for toString, valid parameters are " +
Arrays.toString(validArgsArr), conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
}
// set output characteristics
output.setDataType(DataType.SCALAR);
output.setValueType(ValueType.STRING);
output.setDimensions(0, 0);
}
private void validateNamedList(DataIdentifier output, boolean conditional) {
HashMap<String, Expression> varParams = getVarParams();
// set output characteristics
output.setDataType(DataType.LIST);
output.setValueType(ValueType.UNKNOWN);
output.setDimensions(varParams.size(), 1);
output.setBlocksize(-1);
}
private void checkDataType( String fname, String pname, DataType dt, boolean conditional ) {
Expression data = getVarParam(pname);
if( data==null )
raiseValidateError("Named parameter '" + pname + "' missing. Please specify the input.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
else if( data.getOutput().getDataType() != dt )
raiseValidateError("Input to "+fname+"::"+pname+" must be of type '"+dt.toString()+"'. It should not be of type '"+data.getOutput().getDataType()+"'.", conditional, LanguageErrorCodes.INVALID_PARAMETERS);
}
private void checkDataValueType(boolean optional, String fname, String pname, DataType dt, ValueType vt,
boolean conditional) {
Expression data = getVarParam(pname);
if (data == null) {
if (optional) {
return;
}
raiseValidateError(String.format("Named parameter '%s' is missing. Please specify the input.", pname),
conditional, LanguageErrorCodes.INVALID_PARAMETERS);
} else if (data.getOutput().getDataType() != dt || data.getOutput().getValueType() != vt)
raiseValidateError(String.format("Input to %s::%s must be of type '%s', '%s'.It should not be of type '%s', '%s'.",
fname, pname, dt.toString(), vt.toString(), data.getOutput().getDataType().toString(),
data.getOutput().getValueType().toString()), conditional,
LanguageErrorCodes.INVALID_PARAMETERS);
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder(_opcode.toString() + "(");
for (String key : _varParams.keySet()){
sb.append("," + key + "=" + _varParams.get(key));
}
sb.append(" )");
return sb.toString();
}
@Override
public VariableSet variablesRead() {
VariableSet result = new VariableSet();
for (String s : _varParams.keySet()) {
result.addVariables ( _varParams.get(s).variablesRead() );
}
return result;
}
@Override
public VariableSet variablesUpdated() {
VariableSet result = new VariableSet();
for (String s : _varParams.keySet()) {
result.addVariables ( _varParams.get(s).variablesUpdated() );
}
result.addVariable(((DataIdentifier)this.getOutput()).getName(), (DataIdentifier)this.getOutput());
return result;
}
@Override
public boolean multipleReturns() {
return (_opcode == Builtins.TRANSFORMENCODE);
}
}