checkpoint

Author: montanalow

examples/basic/src/main.rs

@@ -12,9 +12,9 @@ fn main() {
 
     // load train and test matrices from text files (in LibSVM format).
     println!("Loading train and test matrices...");
-    let dtrain = DMatrix::load("../../xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
+    let dtrain = DMatrix::load(r#"{"uri": "../../xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
     println!("Train matrix: {}x{}", dtrain.num_rows(), dtrain.num_cols());
-    let dtest = DMatrix::load("../../xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+    let dtest = DMatrix::load(r#"{"uri": "../../xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
     println!("Test matrix: {}x{}", dtest.num_rows(), dtest.num_cols());
 
     // configure objectives, metrics, etc.

examples/custom_objective/src/main.rs

@@ -6,8 +6,8 @@ use xgboost::{parameters, DMatrix, Booster};
 fn main() {
     // load train and test matrices from text files (in LibSVM format)
     println!("Custom objective example...");
-    let dtrain = DMatrix::load("../../xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
-    let dtest = DMatrix::load("../../xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+    let dtrain = DMatrix::load(r#"{"uri": "../../xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
+    let dtest = DMatrix::load(r#"{"uri": "../../xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
 
     // specify datasets to evaluate against during training
     let evaluation_sets = [(&dtest, "test"), (&dtrain, "train")];

src/booster.rs

@@ -591,14 +591,14 @@ impl Booster {
         for part in eval.split('\t').skip(1) {
             for evname in evnames {
                 if part.starts_with(evname) {
-                    let metric_parts: Vec<&str> = part[evname.len() + 1..].split(':').into_iter().collect();
+                    let metric_parts: Vec<&str> = part[evname.len() + 1..].split(':').collect();
                     assert_eq!(metric_parts.len(), 2);
                     let metric = metric_parts[0];
                     let score = metric_parts[1]
                         .parse::<f32>()
                         .unwrap_or_else(|_| panic!("Unable to parse XGBoost metrics output: {}", eval));
 
-                    let metric_map = result.entry(evname.to_string()).or_insert_with(IndexMap::new);
+                    let metric_map = result.entry(evname.to_string()).or_default();
                     metric_map.insert(metric.to_owned(), score);
                 }
             }
@@ -669,7 +669,7 @@ impl FeatureMap {
             };
 
             let feature_name = &parts[1];
-            let feature_type = match FeatureType::from_str(&parts[2]) {
+            let feature_type = match FeatureType::from_str(parts[2]) {
                 Ok(feature_type) => feature_type,
                 Err(msg) => {
                     let msg = format!("Unable to parse features from line {}: {}", i + 1, msg);
@@ -727,7 +727,7 @@ mod tests {
     use parameters::{self, learning, tree};
 
     fn read_train_matrix() -> XGBResult<DMatrix> {
-        DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train")
+        DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#)
     }
 
     fn load_test_booster() -> Booster {
@@ -761,7 +761,7 @@ mod tests {
 
     #[test]
     fn save_and_load_from_buffer() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
         let mut booster = Booster::new_with_cached_dmats(&BoosterParameters::default(), &[&dmat_train]).unwrap();
         let attr = booster.get_attribute("foo").expect("Getting attribute failed");
         assert_eq!(attr, None);
@@ -804,8 +804,8 @@ mod tests {
 
     #[test]
     fn predict() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
-        let dmat_test = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
+        let dmat_test =DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
 
         let tree_params = tree::TreeBoosterParametersBuilder::default()
             .max_depth(2)
@@ -835,11 +835,11 @@ mod tests {
 
         let train_metrics = booster.evaluate(&dmat_train).unwrap();
         assert_eq!(*train_metrics.get("logloss").unwrap(), 0.006634271);
-        assert_eq!(*train_metrics.get("map@4-").unwrap(), 0.0012738854);
+        assert_eq!(*train_metrics.get("map@4-").unwrap(), 1.0);
 
         let test_metrics = booster.evaluate(&dmat_test).unwrap();
         assert_eq!(*test_metrics.get("logloss").unwrap(), 0.006919953);
-        assert_eq!(*test_metrics.get("map@4-").unwrap(), 0.005154639);
+        assert_eq!(*test_metrics.get("map@4-").unwrap(), 1.0);
 
         let v = booster.predict(&dmat_test).unwrap();
         assert_eq!(v.len(), dmat_test.num_rows());
@@ -886,8 +886,8 @@ mod tests {
 
     #[test]
     fn predict_leaf() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
-        let dmat_test = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
+        let dmat_test = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
 
         let tree_params = tree::TreeBoosterParametersBuilder::default()
             .max_depth(2)
@@ -919,8 +919,8 @@ mod tests {
 
     #[test]
     fn predict_contributions() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
-        let dmat_test = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
+        let dmat_test = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
 
         let tree_params = tree::TreeBoosterParametersBuilder::default()
             .max_depth(2)
@@ -953,8 +953,8 @@ mod tests {
 
     #[test]
     fn predict_interactions() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
-        let dmat_test = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.test").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
+        let dmat_test = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.test?format=libsvm"}"#).unwrap();
 
         let tree_params = tree::TreeBoosterParametersBuilder::default()
             .max_depth(2)
@@ -1005,7 +1005,7 @@ mod tests {
 
     #[test]
     fn dump_model() {
-        let dmat_train = DMatrix::load("xgboost-sys/xgboost/demo/data/agaricus.txt.train").unwrap();
+        let dmat_train = DMatrix::load(r#"{"uri": "xgboost-sys/xgboost/demo/data/agaricus.txt.train?format=libsvm"}"#).unwrap();
 
         println!("{:?}", dmat_train.shape());
 
@@ -1033,82 +1033,79 @@ mod tests {
             .unwrap();
         let booster = Booster::train(&training_params).unwrap();
 
-        let features = FeatureMap::from_file("xgboost-sys/xgboost/demo/data/featmap.txt")
-            .expect("failed to parse feature map file");
-
         assert_eq!(
-            booster.dump_model(true, Some(&features)).unwrap(),
-            "0:[odor=none] yes=2,no=1,gain=4000.53101,cover=1628.25
-1:[stalk-root=club] yes=4,no=3,gain=1158.21204,cover=924.5
-		3:leaf=1.71217716,cover=812
-		4:leaf=-1.70044053,cover=112.5
-2:[spore-print-color=green] yes=6,no=5,gain=198.173828,cover=703.75
-		5:leaf=-1.94070864,cover=690.5
-		6:leaf=1.85964918,cover=13.25
-
-0:[stalk-root=rooted] yes=2,no=1,gain=832.545044,cover=788.852051
-1:[odor=none] yes=4,no=3,gain=569.725098,cover=768.389709
-		3:leaf=0.78471756,cover=458.936859
-		4:leaf=-0.968530357,cover=309.45282
-	2:leaf=-6.23624468,cover=20.462389
-
-0:[ring-type=pendant] yes=2,no=1,gain=368.744568,cover=457.069458
-1:[stalk-surface-below-ring=scaly] yes=4,no=3,gain=226.33696,cover=221.051468
-		3:leaf=0.658725023,cover=212.999451
-		4:leaf=5.77228642,cover=8.05200672
-2:[spore-print-color=purple] yes=6,no=5,gain=258.184265,cover=236.018005
-		5:leaf=-0.791407049,cover=233.487625
-		6:leaf=-9.421422,cover=2.53038669
-
-0:[odor=foul] yes=2,no=1,gain=140.486069,cover=364.119354
-1:[gill-size=broad] yes=4,no=3,gain=139.860504,cover=274.101959
-		3:leaf=0.614153326,cover=95.8599854
-		4:leaf=-0.877905607,cover=178.241974
-	2:leaf=1.07747853,cover=90.0174103
-
-0:[spore-print-color=green] yes=2,no=1,gain=112.605011,cover=189.202194
-1:[gill-spacing=close] yes=4,no=3,gain=66.4029999,cover=177.771835
-		3:leaf=-1.26934469,cover=42.277401
-		4:leaf=0.152607277,cover=135.494431
-	2:leaf=2.92190909,cover=11.4303684
-
-0:[odor=almond] yes=2,no=1,gain=52.5610275,cover=170.612762
-1:[odor=anise] yes=4,no=3,gain=67.3869553,cover=150.881165
-		3:leaf=0.431742132,cover=131.902222
-		4:leaf=-1.53846073,cover=18.9789505
-2:[gill-spacing=close] yes=6,no=5,gain=12.4420624,cover=19.731596
-		5:leaf=-3.02413678,cover=3.65769386
-		6:leaf=-1.02315068,cover=16.0739021
-
-0:[odor=none] yes=2,no=1,gain=66.2389145,cover=142.360611
-1:[odor=anise] yes=4,no=3,gain=31.2294312,cover=72.7557373
-		3:leaf=0.777142286,cover=64.5309982
-		4:leaf=-1.19710124,cover=8.22473907
-2:[spore-print-color=green] yes=6,no=5,gain=12.1987419,cover=69.6048737
-		5:leaf=-0.912605286,cover=66.1211166
-		6:leaf=0.836115122,cover=3.48375821
-
-0:[gill-size=broad] yes=2,no=1,gain=20.6531773,cover=79.4027634
-1:[spore-print-color=white] yes=4,no=3,gain=16.0703697,cover=34.9289207
-		3:leaf=-0.0180106498,cover=25.0319824
-		4:leaf=1.4361918,cover=9.89693928
-2:[odor=foul] yes=6,no=5,gain=22.1144333,cover=44.4738464
-		5:leaf=-0.908311546,cover=36.982872
-		6:leaf=0.890622675,cover=7.49097395
-
-0:[odor=almond] yes=2,no=1,gain=11.7128553,cover=53.3251991
-1:[ring-type=pendant] yes=4,no=3,gain=12.546154,cover=44.299942
-		3:leaf=-0.515293062,cover=15.7899179
-		4:leaf=0.56883812,cover=28.5100231
-	2:leaf=-1.01502442,cover=9.02525806
-
-0:[population=clustered] yes=2,no=1,gain=14.8892794,cover=45.9312019
-1:[odor=none] yes=4,no=3,gain=10.1308851,cover=43.0564575
-		3:leaf=0.217203051,cover=22.3283749
-		4:leaf=-0.734555721,cover=20.7280827
-2:[stalk-root=missing] yes=6,no=5,gain=19.3462334,cover=2.87474418
-		5:leaf=3.63442755,cover=1.34154534
-		6:leaf=-0.609474957,cover=1.53319895
+            booster.dump_model(true, None).unwrap(),
+            "0:[f29<2.00001001] yes=1,no=2,missing=2,gain=4000.53101,cover=1628.25
+	1:[f109<2.00001001] yes=3,no=4,missing=4,gain=198.173828,cover=703.75
+		3:leaf=1.85964918,cover=13.25
+		4:leaf=-1.94070864,cover=690.5
+	2:[f56<2.00001001] yes=5,no=6,missing=6,gain=1158.21204,cover=924.5
+		5:leaf=-1.70044053,cover=112.5
+		6:leaf=1.71217716,cover=812
+
+0:[f60<2.00001001] yes=1,no=2,missing=2,gain=832.544983,cover=788.852051
+	1:leaf=-6.23624468,cover=20.462389
+	2:[f29<2.00001001] yes=3,no=4,missing=4,gain=569.725098,cover=768.389709
+		3:leaf=-0.968530357,cover=309.45282
+		4:leaf=0.78471756,cover=458.936859
+
+0:[f102<2.00001001] yes=1,no=2,missing=2,gain=368.744568,cover=457.069458
+	1:[f111<2.00001001] yes=3,no=4,missing=4,gain=258.184326,cover=236.018005
+		3:leaf=-9.421422,cover=2.53038669
+		4:leaf=-0.791407049,cover=233.487625
+	2:[f67<2.00001001] yes=5,no=6,missing=6,gain=226.336975,cover=221.051468
+		5:leaf=5.77228642,cover=8.05200672
+		6:leaf=0.658725023,cover=212.999451
+
+0:[f27<2.00001001] yes=1,no=2,missing=2,gain=140.486053,cover=364.119354
+	1:leaf=1.07747853,cover=90.0174103
+	2:[f39<2.00001001] yes=3,no=4,missing=4,gain=139.860519,cover=274.101959
+		3:leaf=-0.877905607,cover=178.241974
+		4:leaf=0.614153326,cover=95.8599854
+
+0:[f109<2.00001001] yes=1,no=2,missing=2,gain=112.605019,cover=189.202194
+	1:leaf=2.92190909,cover=11.4303684
+	2:[f36<2.00001001] yes=3,no=4,missing=4,gain=66.4029999,cover=177.771835
+		3:leaf=0.152607277,cover=135.494431
+		4:leaf=-1.26934469,cover=42.277401
+
+0:[f23<2.00001001] yes=1,no=2,missing=2,gain=52.5610313,cover=170.612762
+	1:[f36<2.00001001] yes=3,no=4,missing=4,gain=12.4420547,cover=19.731596
+		3:leaf=-1.02315068,cover=16.0739021
+		4:leaf=-3.02413678,cover=3.65769386
+	2:[f24<2.00001001] yes=5,no=6,missing=6,gain=67.3869553,cover=150.881165
+		5:leaf=-1.53846073,cover=18.9789505
+		6:leaf=0.431742132,cover=131.902222
+
+0:[f29<2.00001001] yes=1,no=2,missing=2,gain=66.2389145,cover=142.360611
+	1:[f109<2.00001001] yes=3,no=4,missing=4,gain=12.1987419,cover=69.6048737
+		3:leaf=0.836115122,cover=3.48375821
+		4:leaf=-0.912605286,cover=66.1211166
+	2:[f24<2.00001001] yes=5,no=6,missing=6,gain=31.229435,cover=72.7557373
+		5:leaf=-1.19710124,cover=8.22473907
+		6:leaf=0.777142286,cover=64.5309982
+
+0:[f39<2.00001001] yes=1,no=2,missing=2,gain=20.6531773,cover=79.4027634
+	1:[f27<2.00001001] yes=3,no=4,missing=4,gain=22.1144371,cover=44.4738464
+		3:leaf=0.890622675,cover=7.49097395
+		4:leaf=-0.908311546,cover=36.982872
+	2:[f112<2.00001001] yes=5,no=6,missing=6,gain=16.0703697,cover=34.9289207
+		5:leaf=1.4361918,cover=9.89693928
+		6:leaf=-0.0180106498,cover=25.0319824
+
+0:[f23<2.00001001] yes=1,no=2,missing=2,gain=11.7128553,cover=53.3251991
+	1:leaf=-1.01502442,cover=9.02525806
+	2:[f102<2.00001001] yes=3,no=4,missing=4,gain=12.5461531,cover=44.299942
+		3:leaf=0.56883812,cover=28.5100231
+		4:leaf=-0.515293062,cover=15.7899179
+
+0:[f115<2.00001001] yes=1,no=2,missing=2,gain=14.8892794,cover=45.9312019
+	1:[f61<2.00001001] yes=3,no=4,missing=4,gain=19.3462334,cover=2.87474418
+		3:leaf=-0.609474957,cover=1.53319895
+		4:leaf=3.63442755,cover=1.34154534
+	2:[f29<2.00001001] yes=5,no=6,missing=6,gain=10.1308861,cover=43.0564575
+		5:leaf=-0.734555721,cover=20.7280827
+		6:leaf=0.217203051,cover=22.3283749
 "
         );
     }