// Adapt a trained model to a test dataset with different enums
/*@Test*/ public void testModelAdapt() {
File file1 = TestUtil.find_test_file("./smalldata/kaggle/KDDTrain.arff.gz");
Key fkey1 = NFSFileVec.make(file1);
Key dest1 = Key.make("KDDTrain.hex");
File file2 = TestUtil.find_test_file("./smalldata/kaggle/KDDTest.arff.gz");
Key fkey2 = NFSFileVec.make(file2);
Key dest2 = Key.make("KDDTest.hex");
GBM gbm = null;
Frame fr = null;
try {
gbm = new GBM();
gbm.source = ParseDataset2.parse(dest1, new Key[] {fkey1});
UKV.remove(fkey1);
gbm.response = gbm.source.remove(41); // Response is col 41
gbm.ntrees = 2;
gbm.max_depth = 8;
gbm.learn_rate = 0.2f;
gbm.min_rows = 10;
gbm.nbins = 50;
gbm.invoke();
// The test data set has a few more enums than the train
Frame ftest = ParseDataset2.parse(dest2, new Key[] {fkey2});
Frame preds = gbm.score(ftest);
} finally {
UKV.remove(dest1); // Remove original hex frame key
if (gbm != null) {
UKV.remove(gbm.dest()); // Remove the model
UKV.remove(gbm.response._key);
gbm.remove(); // Remove GBM Job
if (fr != null) fr.remove();
}
}
}
/**
* Find & parse a folder of CSV files. NPE if file not found.
*
* @param fname Test filename
* @return Frame or NPE
*/
protected Frame parse_test_folder(String fname) {
File folder = find_test_file(fname);
assert folder.isDirectory();
File[] files = folder.listFiles();
Arrays.sort(files);
ArrayList<Key> keys = new ArrayList<Key>();
for (File f : files) if (f.isFile()) keys.add(NFSFileVec.make(f)._key);
Key[] res = new Key[keys.size()];
keys.toArray(res);
return ParseDataset.parse(Key.make(), res);
}
// ==========================================================================
public void basicGBM(String fname, String hexname, PrepData prep) {
File file = TestUtil.find_test_file(fname);
if (file == null) return; // Silently abort test if the file is missing
Key fkey = NFSFileVec.make(file);
Key dest = Key.make(hexname);
GBM gbm = null;
Frame fr = null;
try {
gbm = new GBM();
gbm.source = fr = ParseDataset2.parse(dest, new Key[] {fkey});
UKV.remove(fkey);
int idx = prep.prep(fr);
if (idx < 0) {
gbm.classification = false;
idx = ~idx;
}
String rname = fr._names[idx];
gbm.response = fr.vecs()[idx];
fr.remove(idx); // Move response to the end
fr.add(rname, gbm.response);
gbm.ntrees = 4;
gbm.max_depth = 4;
gbm.min_rows = 1;
gbm.nbins = 50;
gbm.cols = new int[fr.numCols()];
for (int i = 0; i < gbm.cols.length; i++) gbm.cols[i] = i;
gbm.learn_rate = .2f;
gbm.invoke();
fr = gbm.score(gbm.source);
GBM.GBMModel gbmmodel = UKV.get(gbm.dest());
// System.out.println(gbmmodel.toJava());
} finally {
UKV.remove(dest); // Remove original hex frame key
if (gbm != null) {
UKV.remove(gbm.dest()); // Remove the model
UKV.remove(gbm.response._key);
gbm.remove(); // Remove GBM Job
if (fr != null) fr.remove();
}
}
}
@Test
public void testBasicExpr1() {
Key dest = Key.make("h.hex");
try {
File file = TestUtil.find_test_file("smalldata/tnc3_10.csv");
// File file = TestUtil.find_test_file("smalldata/iris/iris_wheader.csv");
// File file = TestUtil.find_test_file("smalldata/cars.csv");
Key fkey = NFSFileVec.make(file);
ParseDataset2.parse(dest, new Key[] {fkey});
// Simple numbers & simple expressions
checkStr("1.23", 1.23);
checkStr(" 1.23 + 2.34", 3.57);
checkStr(" 1.23 + 2.34 * 3", 8.25); // op precedence of * over +
checkStr(
" 1.23 2.34", "Junk at end of line\n" + " 1.23 2.34\n" + " ^--^\n"); // Syntax error
checkStr("1.23 < 2.34", 1);
checkStr("1.23 <=2.34", 1);
checkStr("1.23 > 2.34", 0);
checkStr("1.23 >=2.34", 0);
checkStr("1.23 ==2.34", 0);
checkStr("1.23 !=2.34", 1);
checkStr("1 & 2", 1);
checkStr("NA&0", 0); // R-spec: 0 not NA
checkStr("0&NA", 0); // R-spec: 0 not NA
checkStr("NA&1", Double.NaN); // R-spec: NA not 1
checkStr("1&NA", Double.NaN);
checkStr("1|NA", 1);
checkStr("1&&2", 1);
checkStr("1||0", 1);
checkStr("NA||1", 1);
checkStr("NA||0", Double.NaN);
checkStr("0||NA", Double.NaN);
checkStr("!1", 0);
checkStr("(!)(1)", 0);
checkStr(
"(!!)(1)",
"Arg 'x' typed as dblary but passed dblary(dblary)\n" + "(!!)(1)\n" + " ^-^\n");
checkStr("-1", -1);
checkStr("-(1)", -1);
checkStr("(-)(1)", "Passed 1 args but expected 2\n" + "(-)(1)\n" + " ^--^\n");
checkStr("-T", -1);
checkStr(
"* + 1",
"Arg 'x' typed as dblary but passed anyary{dblary,dblary,}(dblary,dblary)\n"
+ "* + 1\n"
+ "^----^\n");
// Simple op as prefix calls
checkStr(
"+(1.23,2.34)",
"Missing ')'\n"
+ "+(1.23,2.34)\n"
+ " ^---^\n"); // Syntax error: looks like unary op application
checkStr("+(1.23)", 1.23); // Unary operator
// Simple scalar assignment
checkStr("1=2", "Junk at end of line\n" + "1=2\n" + " ^^\n");
checkStr("x", "Unknown var x\n" + "x\n" + "^^\n");
checkStr("x+2", "Unknown var x\n" + "x+2\n" + "^^\n");
checkStr("2+x", "Missing expr or unknown ID\n" + "2+x\n" + " ^\n");
checkStr("x=1", 1);
checkStr("x<-1", 1); // Alternative R assignment syntax
checkStr("x=3;y=4", 4); // Return value is last expr
// Ambiguity & Language
checkStr("x=mean"); // Assign x to the built-in fcn mean
checkStr(
"x=mean=3",
3); // Assign x & id mean with 3; "mean" here is not related to any built-in fcn
checkStr("x=mean(c(3))", 3); // Assign x to the result of running fcn mean(3)
checkStr("x=mean(c(\n3))", 3); // Assign x to the result of running fcn mean(3)
checkStr(
"x=mean+3",
"Arg 'x' typed as dblary but passed dbl(ary)\n"
+ "x=mean+3\n"
+ " ^-----^\n"); // Error: "mean" is a function; cannot add a function and a number
checkStr(
"apply(c(1,2,3),,nrow)", "Missing argument\napply(c(1,2,3),,nrow)\n ^\n");
checkStr(
"foo==bar",
"Unknown var foo\nfoo==bar\n^--^\n"); // Error msg is about "foo==" and not new assignment
// "foo="
// Simple array handling; broadcast operators
checkStr("h.hex"); // Simple ref
checkStr("h.hex[2,3]", 1); // Scalar selection
checkStr(
"h.hex[2,+]",
"Must be scalar or array\n" + "h.hex[2,+]\n" + " ^-^\n"); // Function not allowed
checkStr("h.hex[2+4,-4]"); // Select row 6, all-cols but 4
checkStr("h.hex[1,-1]; h.hex[2,-2]; h.hex[3,-3]"); // Partial results are freed
checkStr(
"h.hex[2+3,h.hex]",
"Selector must be a single column: [pclass, name, sex, age, sibsp, parch, ticket, fare, cabin, embarked, boat, body, home.dest, survived]"); // Error: col selector has too many columns
checkStr("h.hex[2,]"); // Row 2 all cols
checkStr("h.hex[,3]"); // Col 3 all rows
checkStr("h.hex+1"); // Broadcast scalar over ary
checkStr("h.hex-h.hex");
checkStr("1.23+(h.hex-h.hex)");
checkStr("(1.23+h.hex)-h.hex");
checkStr("min(h.hex,1+2)", 0);
checkStr("max(h.hex,1+2)", 211.3375);
checkStr("min.na.rm(h.hex,NA)", 0); // 0
checkStr("max.na.rm(h.hex,NA)", 211.3375); // 211.3375
checkStr("min.na.rm(c(NA, 1), -1)", -1); // -1
checkStr("max.na.rm(c(NA, 1), -1)", 1); // 1
checkStr("max(c(Inf,1), 2 )", Double.POSITIVE_INFINITY); // Infinity
checkStr("min(c(Inf,1),-Inf)", Double.NEGATIVE_INFINITY); // -Infinity
checkStr("is.na(h.hex)");
checkStr("sum(is.na(h.hex))", 0);
checkStr("nrow(h.hex)*3", 30);
checkStr("h.hex[nrow(h.hex)-1,ncol(h.hex)-1]");
checkStr("x=1;x=h.hex"); // Allowed to change types via shadowing at REPL level
checkStr("a=h.hex"); // Top-level assignment back to H2O.STORE
checkStr(
"(h.hex+1)<-2",
"Junk at end of line\n" + "(h.hex+1)<-2\n" + " ^-^\n"); // No L-value
checkStr(
"h.hex[nrow(h.hex=1),]",
"Arg 'x' typed as ary but passed dbl\n"
+ "h.hex[nrow(h.hex=1),]\n"
+ " ^--------^\n"); // Passing a scalar 1.0 to nrow
checkStr(
"h.hex[{h.hex=10},]"); // ERROR BROKEN: SHOULD PARSE statement list here; then do evil
// side-effect killing h.hex but also using 10 to select last row
checkStr("h.hex[3,4]<-4;", 4);
checkStr("c(1,3,5)");
// Column row subselection
checkStr("h.hex[,c(1,3,5)]");
checkStr("h.hex[c(1,3,5),]");
checkStr("a=c(11,22,33,44,55,66); a[c(2,6,1),]");
// Named column selection
checkStr("h.hex$ 2", "Missing column name after $\nh.hex$ 2\n ^^\n");
checkStr(
"h.hex$crunk",
"Missing column crunk in frame [pclass, name, sex, age, sibsp, parch, ticket, fare, cabin, embarked, boat, body, home.dest, survived]");
checkStr("h.hex$pclass");
checkStr("mean(h.hex$pclass)", 1);
// More complicated operator precedence
checkStr("c(1,0)&c(2,3)"); // 1,0
checkStr("c(2,NA)&&T", 1); // 1
checkStr("-(x = 3)", -3);
checkStr("x<-+");
checkStr(
"x<-+;x(2)",
"Passed 1 args but expected 2\nx<-+;x(2)\n ^--^\n"); // Error, + is binary if used as
// prefix
checkStr("x<-+;x(1,2)", 3); // 3
checkStr("x<-*;x(2,3)", 6); // 6
checkStr("x=c(0,1);!x+1"); // ! has lower precedence
checkStr("x=c(1,-2);-+---x");
checkStr("x=c(1,-2);--!--x");
checkStr("!(y=c(3,4))");
checkStr("!x!=1");
checkStr("(!x)!=1");
checkStr("1+x^2");
checkStr("1+x**2");
checkStr("x + 2/y");
checkStr("x + (2/y)");
checkStr("-x + y");
checkStr("-(x + y)");
checkStr("-x % y");
checkStr("-(x % y)");
checkStr("T|F&F", 1); // Evals as T|(F&F)==1 not as (T|F)&F==0
checkStr("T||F&&F", 1); // Evals as T|(F&F)==1 not as (T|F)&F==0
// User functions
checkStr("function(=){x+1}(2)", "Invalid var\nfunction(=){x+1}(2)\n ^\n");
checkStr("function(x,=){x+1}(2)", "Invalid var\nfunction(x,=){x+1}(2)\n ^\n");
checkStr("function(x,<-){x+1}(2)", "Invalid var\nfunction(x,<-){x+1}(2)\n ^\n");
checkStr(
"function(x,x){x+1}(2)", "Repeated argument\nfunction(x,x){x+1}(2)\n ^^\n");
checkStr("function(x,y,z){x[]}(h.hex,1,2)");
checkStr(
"function(x){x[]}(2)",
"Arg 'x' typed as ary but passed dbl\nfunction(x){x[]}(2)\n ^--^\n");
checkStr("function(x){x+1}(2)", 3);
checkStr("function(x){y=x+y}(2)");
checkStr("function(x){}(2)");
checkStr("function(x){y=x*2; y+1}(2)", 5);
checkStr("function(x){y=1+2}(2)", 3);
checkStr("function(x){y=1+2;y=c(1,2)}"); // Not allowed to change types in inner scopes
checkStr("a=function(x) x+1; 7", 7); // Function def w/out curly-braces; return 7
checkStr("a=function(x) {x+1}; 7", 7); // Function def w/ curly-braces; return 7
checkStr("a=function(x) {x+1; 7}"); // Function def of 7
checkStr("c(1,c(2,3))");
checkStr("a=c(1,Inf);c(2,a)");
// Test sum flattening all args
checkStr("sum(1,2,3)", 6);
checkStr("sum(c(1,3,5))", 9);
checkStr("sum(4,c(1,3,5),2,6)", 21);
checkStr("sum(1,h.hex,3)"); // should report an error because h.hex has enums
checkStr("sum(c(NA,-1,1))", Double.NaN);
checkStr("sum.na.rm(c(NA,-1,1))", 0);
checkStr("function(a){a[];a=1}");
checkStr("a=1;a=2;function(x){x=a;a=3}");
checkStr("a=h.hex;function(x){x=a;a=3;nrow(x)*a}(a)", 30);
checkStr("a=h.hex;a[,1]=(a[,1]==8)");
// Higher-order function typing: fun is typed in the body of function(x)
checkStr("function(funy){function(x){funy(x)*funy(x)}}(sgn)(-2)", 1);
// Filter/selection
checkStr("h.hex[h.hex[,4]>30,]");
checkStr("a=c(1,2,3);a[a[,1]>10,1]");
checkStr("sapply(a,sum)[1,1]", 6);
checkStr("apply(h.hex,2,sum)"); // ERROR BROKEN: the ENUM cols should fold to NA
checkStr("y=5;apply(h.hex,2,function(x){x[]+y})");
checkStr(
"apply(h.hex,2,function(x){x=1;h.hex})",
"Arg 'fcn' typed as ary(ary) but passed ary(dbl)\napply(h.hex,2,function(x){x=1;h.hex})\n ^-------------------------------^\n");
checkStr(
"apply(h.hex,2,function(x){h.hex})",
"apply requires that ary fun(ary x) return 1 column");
checkStr("apply(h.hex,2,function(x){sum(x)/nrow(x)})");
checkStr("mean=function(x){apply(x,2,sum)/nrow(x)};mean(h.hex)");
checkStr("sum(apply(h.hex[,c(4,5)],1,mean))", 184.96); // Row-wise apply on mean
// Conditional selection;
checkStr("ifelse(0,1,2)", 2);
checkStr("ifelse(0,h.hex+1,h.hex+2)");
checkStr("ifelse(h.hex>3,99,h.hex)"); // Broadcast selection
checkStr("ifelse(0,+,*)(1,2)", 2); // Select functions
checkStr("(0 ? + : *)(1,2)", 2); // Trinary select
checkStr("(1? h.hex : (h.hex+1))[1,2]", 0); // True (vs false) test
// Impute the mean
checkStr(
"apply(h.hex,2,function(x){total=sum(ifelse(is.na(x),0,x)); rcnt=nrow(x)-sum(is.na(x)); mean=total / rcnt; ifelse(is.na(x),mean,x)})");
checkStr("factor(h.hex[,5])");
// Slice assignment & map
checkStr("h.hex[,2]");
checkStr("h.hex[,2]+1");
checkStr("h.hex[,3]=3.3;h.hex"); // Replace a col with a constant
checkStr("h.hex[,3]=h.hex[,2]+1"); // Replace a col
checkStr("h.hex[,ncol(h.hex)+1]=4"); // Extend a col
checkStr("a=ncol(h.hex);h.hex[,c(a+1,a+2)]=5"); // Extend two cols
checkStr("h.hex[,7]=x=3; !(x+2)");
checkStr("table(h.hex)");
checkStr("table(h.hex[,5])");
checkStr("table(h.hex[,c(2,7)])");
checkStr("table(h.hex[,c(2,9)])");
checkStr("a=cbind(c(1,2,3), c(4,5,6))");
checkStr("a[,1] = factor(a[,1])");
checkStr("is.factor(a[,1])", 1);
checkStr("isTRUE(c(1,3))", 0);
checkStr("a=1;isTRUE(1)", 1);
checkStr("a=c(1,2);isTRUE(a)", 0);
checkStr("isTRUE(min)", 0);
checkStr("seq_len(0)", "Error in seq_len(0): argument must be coercible to positive integer");
checkStr(
"seq_len(-1)", "Error in seq_len(-1): argument must be coercible to positive integer");
checkStr("seq_len(10)");
checkStr("3 < 4 | F & 3 > 4", 1); // Evals as (3<4) | (F & (3>4))
checkStr("3 < 4 || F && 3 > 4", 1);
checkStr("h.hex[,4] != 29 || h.hex[,2] < 305 && h.hex[,2] < 81", Double.NaN);
// checkStr("h.hex[h.hex[,4]>40,]=-99");
// checkStr("h.hex[2,]=h.hex[7,]");
// checkStr("h.hex[c(1,3,5),1] = h.hex[c(2,4,6),2]");
// checkStr("h.hex[c(1,3,5),1] = h.hex[c(2,4),2]");
// checkStr("map()");
// checkStr("map(1)");
// checkStr("map(+,h.hex,1)");
// checkStr("map(+,1,2)");
// checkStr("map(function(x){x[];1},h.hex)");
// checkStr("map(function(a,b,d){a+b+d},h.hex,h.hex,1)");
// checkStr("map(function(a,b){a+ncol(b)},h.hex,h.hex)");
// Quantile
checkStr("quantile(seq_len(10),seq_len(10)/10)");
checkStr("quantile(runif(seq_len(10000),-1),seq_len(10)/10)");
checkStr("quantile(h.hex[,4],c(0,.05,0.3,0.55,0.7,0.95,0.99))");
// ddply error checks
checkStr("ddply(h.hex,h.hex,sum)", "Only one column-of-columns for column selection");
checkStr("ddply(h.hex,seq_len(10000),sum)", "Too many columns selected");
checkStr("ddply(h.hex,NA,sum)", "NA not a valid column");
checkStr("ddply(h.hex,c(1,NA,3),sum)", "NA not a valid column");
checkStr("ddply(h.hex,c(1,99,3),sum)", "Column 99 out of range for frame columns 17");
checkStr("nrow(unique(h.hex[,5]))", 3);
checkStr("nrow(unique(h.hex[,6]))", 2);
checkStr("nrow(unique(h.hex[,c(5,6)]))", 4); // multi-column unique
// Newlines as statement-ends
checkStr("3*4+5*6", 42);
checkStr("(h.hex[1,1]=2)", 2);
checkStr("(h.hex[1,1]=2\n)", 2);
checkStr("(h.hex[1,1]\n=2)", 2);
checkStr("(h.hex\n[1,1]=2)", 2);
checkStr("function(){x=1.23;(x=4.5)\n}()", 4.5);
checkStr("function(){x=1.23;x=\n4.5\n}()", 4.5);
checkStr("x=3\nfunction()x=1.23\nx", 3);
checkStr("x=3\nfunction(){(x=1.23)}\nx", 3);
checkStr("x=function(df)\n{\nmin(df$age)\n}\n;x(h.hex)", 0.92);
checkStr("1.23\n-4", -4);
checkStr("1.23 +\n-4", -2.77);
checkStr("x=3;3*-x", -9); // *- is not a token
checkStr(
"x=3;3\n*\n-\nx", 3); // Each of '3' and '*' and '-' and 'x' is a standalone statement
// No strings, yet
checkStr(
"function(df) { min(df[,\"age\"]) }",
"The current Exec does not handle strings\nfunction(df) { min(df[,\"age\"]) }\n ^\n");
// Cleanup testing temps
checkStr("a=0;x=0;y=0", 0); // Delete keys from global scope
} finally {
Lockable.delete(dest); // Remove original hex frame key
}
}
@Test
public void testBasicExpr1() {
Key dest = Key.make("h.hex");
try {
File file = TestUtil.find_test_file("smalldata/tnc3_10.csv");
// File file = TestUtil.find_test_file("smalldata/iris/iris_wheader.csv");
// File file = TestUtil.find_test_file("smalldata/cars.csv");
Key fkey = NFSFileVec.make(file);
ParseDataset2.parse(dest, new Key[] {fkey});
UKV.remove(fkey);
checkStr("1.23"); // 1.23
checkStr(" 1.23 + 2.34"); // 3.57
checkStr(" 1.23 + 2.34 * 3"); // 10.71, L2R eval order
checkStr(" 1.23 2.34"); // Syntax error
checkStr("1.23 < 2.34"); // 1
checkStr("1.23 <=2.34"); // 1
checkStr("1.23 > 2.34"); // 0
checkStr("1.23 >=2.34"); // 0
checkStr("1.23 ==2.34"); // 0
checkStr("1.23 !=2.34"); // 1
checkStr("h.hex"); // Simple ref
checkStr("+(1.23,2.34)"); // prefix 3.57
checkStr("+(1.23)"); // Syntax error, not enuf args
checkStr("+(1.23,2,3)"); // Syntax error, too many args
checkStr("h.hex[2,3]"); // Scalar selection
checkStr("h.hex[2,+]"); // Function not allowed
checkStr("h.hex[2+4,-4]"); // Select row 6, all-cols but 4
checkStr("h.hex[1,-1]; h.hex[2,-2]; h.hex[3,-3]"); // Partial results are freed
checkStr("h.hex[2+3,h.hex]"); // Error: col selector has too many columns
checkStr("h.hex[2,]"); // Row 2 all cols
checkStr("h.hex[,3]"); // Col 3 all rows
checkStr("h.hex+1"); // Broadcast scalar over ary
checkStr("h.hex-h.hex");
checkStr("1.23+(h.hex-h.hex)");
checkStr("(1.23+h.hex)-h.hex");
checkStr("min(h.hex,1+2)");
checkStr("max(h.hex,1+2)");
checkStr("is.na(h.hex)");
checkStr("nrow(h.hex)*3");
checkStr("h.hex[nrow(h.hex)-1,ncol(h.hex)-1]");
checkStr("1=2");
checkStr("x");
checkStr("x+2");
checkStr("2+x");
checkStr("x=1");
checkStr("x<-1"); // Alternative R assignment syntax
checkStr("x=1;x=h.hex"); // Allowed to change types via shadowing at REPL level
checkStr("a=h.hex"); // Top-level assignment back to H2O.STORE
checkStr("x<-+");
checkStr("(h.hex+1)<-2");
checkStr("h.hex[nrow(h.hex=1),]");
checkStr("h.hex[2,3]<-4;");
checkStr("c(1,3,5)");
checkStr("function(=){x+1}(2)");
checkStr("function(x,=){x+1}(2)");
checkStr("function(x,<-){x+1}(2)");
checkStr("function(x,x){x+1}(2)");
checkStr("function(x,y,z){x[]}(h.hex,1,2)");
checkStr("function(x){x[]}(2)");
checkStr("function(x){x+1}(2)");
checkStr("function(x){y=x+y}(2)");
checkStr("function(x){}(2)");
checkStr("function(x){y=x*2; y+1}(2)");
checkStr("function(x){y=1+2}(2)");
checkStr("function(x){y=1+2;y=c(1,2)}"); // Not allowed to change types in inner scopes
checkStr("sum(1,2,3)");
checkStr("sum(c(1,3,5))");
checkStr("sum(4,c(1,3,5),2,6)");
checkStr("sum(1,h.hex,3)");
checkStr("h.hex[,c(1,3,5)]");
checkStr("h.hex[c(1,3,5),]");
checkStr("a=c(11,22,33,44,55,66); a[c(2,6,1),]");
checkStr("function(a){a[];a=1}");
checkStr("a=1;a=2;function(x){x=a;a=3}");
checkStr("a=h.hex;function(x){x=a;a=3;nrow(x)*a}(a)");
checkStr("a=h.hex;a[,1]=(a[,1]==8)");
// Higher-order function typing: fun is typed in the body of function(x)
checkStr("function(funy){function(x){funy(x)*funy(x)}}(sgn)(-2)");
// Filter/selection
checkStr("h.hex[h.hex[,2]>4,]");
checkStr("a=c(1,2,3);a[a[,1]>10,1]");
checkStr("apply(h.hex,2,sum)");
checkStr("y=5;apply(h.hex,2,function(x){x[]+y})");
checkStr("apply(h.hex,2,function(x){x=1;h.hex})");
checkStr("apply(h.hex,2,function(x){h.hex})");
checkStr("mean=function(x){apply(x,2,sum)/nrow(x)};mean(h.hex)");
// Conditional selection;
checkStr("ifelse(0,1,2)");
checkStr("ifelse(0,h.hex+1,h.hex+2)");
checkStr("ifelse(h.hex>3,99,h.hex)"); // Broadcast selection
checkStr("ifelse(0,+,*)(1,2)"); // Select functions
checkStr("(0 ? + : *)(1,2)"); // Trinary select
checkStr("(1? h.hex : (h.hex+1))[1,2]"); // True (vs false) test
// Impute the mean
checkStr(
"apply(h.hex,2,function(x){total=sum(ifelse(is.na(x),0,x)); rcnt=nrow(x)-sum(is.na(x)); mean=total / rcnt; ifelse(is.na(x),mean,x)})");
checkStr("factor(h.hex[,5])");
// Slice assignment & map
checkStr("h.hex[,2]");
checkStr("h.hex[,2]+1");
checkStr("h.hex[,3]=3.3;h.hex"); // Replace a col with a constant
checkStr("h.hex[,3]=h.hex[,2]+1"); // Replace a col
checkStr("h.hex[,ncol(h.hex)+1]=4"); // Extend a col
checkStr("a=ncol(h.hex);h.hex[,c(a+1,a+2)]=5"); // Extend two cols
checkStr("table(h.hex)");
checkStr("table(h.hex[,3])");
checkStr("h.hex[,4] != 29 || h.hex[,2] < 305 && h.hex[,2] < 81");
checkStr("a=cbind(c(1,2,3), c(4,5,6))");
// checkStr("h.hex[h.hex[,2]>4,]=-99");
// checkStr("h.hex[2,]=h.hex[7,]");
// checkStr("h.hex[c(1,3,5),1] = h.hex[c(2,4,6),2]");
// checkStr("h.hex[c(1,3,5),1] = h.hex[c(2,4),2]");
// checkStr("map()");
// checkStr("map(1)");
// checkStr("map(+,h.hex,1)");
// checkStr("map(+,1,2)");
// checkStr("map(function(x){x[];1},h.hex)");
// checkStr("map(function(a,b,d){a+b+d},h.hex,h.hex,1)");
// checkStr("map(function(a,b){a+ncol(b)},h.hex,h.hex)");
checkStr("a=0;x=0"); // Delete keys from global scope
} finally {
UKV.remove(dest); // Remove original hex frame key
}
}
/**
* Find & parse a CSV file. NPE if file not found.
*
* @param fname Test filename
* @return Frame or NPE
*/
public static Frame parse_test_file(String fname) {
return parse_test_file(Key.make(), fname);
}
/**
* The train/valid Frame instances are sorted by categorical (themselves sorted by cardinality
* greatest to least) with all numerical columns following. The response column(s) are placed at
* the end.
*
* <p>Interactions: 1. Num-Num (Note: N(0,1) * N(0,1) ~ N(0,1) ) 2. Num-Enum 3. Enum-Enum
*
* <p>Interactions are produced on the fly and are dense (in all 3 cases). Consumers of DataInfo
* should not have to care how these interactions are generated. Any heuristic using the fullN
* value should continue functioning the same.
*
* <p>Interactions are specified in two ways: A. As a list of pairs of column indices. B. As a
* list of pairs of column indices with limited enums.
*/
public DataInfo(
Frame train,
Frame valid,
int nResponses,
boolean useAllFactorLevels,
TransformType predictor_transform,
TransformType response_transform,
boolean skipMissing,
boolean imputeMissing,
boolean missingBucket,
boolean weight,
boolean offset,
boolean fold,
Model.InteractionPair[] interactions) {
super(Key.<DataInfo>make());
_valid = valid != null;
assert predictor_transform != null;
assert response_transform != null;
_offset = offset;
_weights = weight;
_fold = fold;
assert !(skipMissing && imputeMissing) : "skipMissing and imputeMissing cannot both be true";
_skipMissing = skipMissing;
_imputeMissing = imputeMissing;
_predictor_transform = predictor_transform;
_response_transform = response_transform;
_responses = nResponses;
_useAllFactorLevels = useAllFactorLevels;
_interactions = interactions;
// create dummy InteractionWrappedVecs and shove them onto the front
if (_interactions != null) {
_interactionVecs = new int[_interactions.length];
train =
Model.makeInteractions(
train,
false,
_interactions,
_useAllFactorLevels,
_skipMissing,
predictor_transform == TransformType.STANDARDIZE)
.add(train);
if (valid != null)
valid =
Model.makeInteractions(
valid,
true,
_interactions,
_useAllFactorLevels,
_skipMissing,
predictor_transform == TransformType.STANDARDIZE)
.add(valid); // FIXME: should be using the training subs/muls!
}
_permutation = new int[train.numCols()];
final Vec[] tvecs = train.vecs();
// Count categorical-vs-numerical
final int n = tvecs.length - _responses - (offset ? 1 : 0) - (weight ? 1 : 0) - (fold ? 1 : 0);
int[] nums = MemoryManager.malloc4(n);
int[] cats = MemoryManager.malloc4(n);
int nnums = 0, ncats = 0;
for (int i = 0; i < n; ++i)
if (tvecs[i].isCategorical()) cats[ncats++] = i;
else nums[nnums++] = i;
_nums = nnums;
_cats = ncats;
_catLvls = new int[ncats][];
// sort the cats in the decreasing order according to their size
for (int i = 0; i < ncats; ++i)
for (int j = i + 1; j < ncats; ++j)
if (tvecs[cats[i]].domain().length < tvecs[cats[j]].domain().length) {
int x = cats[i];
cats[i] = cats[j];
cats[j] = x;
}
String[] names = new String[train.numCols()];
Vec[] tvecs2 = new Vec[train.numCols()];
// Compute the cardinality of each cat
_catModes = new int[ncats];
_catOffsets = MemoryManager.malloc4(ncats + 1);
_catMissing = new boolean[ncats];
int len = _catOffsets[0] = 0;
int interactionIdx = 0; // simple index into the _interactionVecs array
ArrayList<Integer> interactionIds;
if (_interactions == null) {
interactionIds = new ArrayList<>();
for (int i = 0; i < tvecs.length; ++i)
if (tvecs[i] instanceof InteractionWrappedVec) {
interactionIds.add(i);
}
_interactionVecs = new int[interactionIds.size()];
for (int i = 0; i < _interactionVecs.length; ++i) _interactionVecs[i] = interactionIds.get(i);
}
for (int i = 0; i < ncats; ++i) {
names[i] = train._names[cats[i]];
Vec v = (tvecs2[i] = tvecs[cats[i]]);
_catMissing[i] = missingBucket; // needed for test time
if (v instanceof InteractionWrappedVec) {
if (_interactions != null) _interactions[interactionIdx].vecIdx = i;
_interactionVecs[interactionIdx++] =
i; // i (and not cats[i]) because this is the index in _adaptedFrame
_catOffsets[i + 1] = (len += v.domain().length + (missingBucket ? 1 : 0));
} else
_catOffsets[i + 1] =
(len +=
v.domain().length
- (useAllFactorLevels ? 0 : 1)
+ (missingBucket ? 1 : 0)); // missing values turn into a new factor level
_catModes[i] =
imputeMissing ? imputeCat(train.vec(cats[i])) : _catMissing[i] ? v.domain().length : -100;
_permutation[i] = cats[i];
}
_numMeans = new double[nnums];
_numOffsets = MemoryManager.malloc4(nnums + 1);
_numOffsets[0] = len;
boolean isIWV; // is InteractionWrappedVec?
for (int i = 0; i < nnums; ++i) {
names[i + ncats] = train._names[nums[i]];
Vec v = train.vec(nums[i]);
tvecs2[i + ncats] = v;
isIWV = v instanceof InteractionWrappedVec;
if (isIWV) {
if (null != _interactions) _interactions[interactionIdx].vecIdx = i + ncats;
_interactionVecs[interactionIdx++] = i + ncats;
}
_numOffsets[i + 1] = (len += (isIWV ? ((InteractionWrappedVec) v).expandedLength() : 1));
_numMeans[i] = train.vec(nums[i]).mean();
_permutation[i + ncats] = nums[i];
}
for (int i = names.length - nResponses - (weight ? 1 : 0) - (offset ? 1 : 0) - (fold ? 1 : 0);
i < names.length;
++i) {
names[i] = train._names[i];
tvecs2[i] = train.vec(i);
}
_adaptedFrame = new Frame(names, tvecs2);
train.restructure(names, tvecs2);
if (valid != null) valid.restructure(names, valid.vecs(names));
// _adaptedFrame = train;
setPredictorTransform(predictor_transform);
if (_responses > 0) setResponseTransform(response_transform);
}
// Test-on-Train. Slow test, needed to build a good model.
@Test
public void testGBMTrainTest() {
File file1 = TestUtil.find_test_file("..//classifcation1Train.txt");
if (file1 == null) return; // Silently ignore if file not found
Key fkey1 = NFSFileVec.make(file1);
Key dest1 = Key.make("train.hex");
File file2 = TestUtil.find_test_file("..//classification1Test.txt");
Key fkey2 = NFSFileVec.make(file2);
Key dest2 = Key.make("test.hex");
GBM gbm = null;
Frame fr = null, fpreds = null;
try {
gbm = new GBM();
fr = ParseDataset2.parse(dest1, new Key[] {fkey1});
UKV.remove(fkey1);
UKV.remove(fr.remove("agentId")._key); // Remove unique ID; too predictive
gbm.response = fr.remove("outcome"); // Train on the outcome
gbm.source = fr;
gbm.ntrees = 5;
gbm.max_depth = 10;
gbm.learn_rate = 0.2f;
gbm.min_rows = 10;
gbm.nbins = 100;
gbm.invoke();
// Test on the train data
Frame ftest = ParseDataset2.parse(dest2, new Key[] {fkey2});
UKV.remove(fkey2);
fpreds = gbm.score(ftest);
// Build a confusion matrix
ConfusionMatrix CM = new ConfusionMatrix();
CM.actual = ftest;
CM.vactual = ftest.vecs()[ftest.find("outcome")];
CM.predict = fpreds;
CM.vpredict = fpreds.vecs()[fpreds.find("predict")];
CM.serve(); // Start it, do it
// Really crappy cut-n-paste of what should be in the ConfusionMatrix class itself
long cm[][] = CM.cm;
long acts[] = new long[cm.length];
long preds[] = new long[cm[0].length];
for (int a = 0; a < cm.length; a++) {
long sum = 0;
for (int p = 0; p < cm[a].length; p++) {
sum += cm[a][p];
preds[p] += cm[a][p];
}
acts[a] = sum;
}
String adomain[] = ConfusionMatrix.show(acts, CM.vactual.domain());
String pdomain[] = ConfusionMatrix.show(preds, CM.vpredict.domain());
StringBuilder sb = new StringBuilder();
sb.append("Act/Prd\t");
for (String s : pdomain) if (s != null) sb.append(s).append('\t');
sb.append("Error\n");
long terr = 0;
for (int a = 0; a < cm.length; a++) {
if (adomain[a] == null) continue;
sb.append(adomain[a]).append('\t');
long correct = 0;
for (int p = 0; p < pdomain.length; p++) {
if (pdomain[p] == null) continue;
if (adomain[a].equals(pdomain[p])) correct = cm[a][p];
sb.append(cm[a][p]).append('\t');
}
long err = acts[a] - correct;
terr += err; // Bump totals
sb.append(String.format("%5.3f = %d / %d\n", (double) err / acts[a], err, acts[a]));
}
sb.append("Totals\t");
for (int p = 0; p < pdomain.length; p++)
if (pdomain[p] != null) sb.append(preds[p]).append("\t");
sb.append(
String.format(
"%5.3f = %d / %d\n", (double) terr / CM.vactual.length(), terr, CM.vactual.length()));
System.out.println(sb);
} finally {
UKV.remove(dest1); // Remove original hex frame key
UKV.remove(fkey2);
UKV.remove(dest2);
if (gbm != null) {
UKV.remove(gbm.dest()); // Remove the model
UKV.remove(gbm.response._key);
gbm.remove(); // Remove GBM Job
}
if (fr != null) fr.remove();
if (fpreds != null) fpreds.remove();
}
}
