From eb1b185d700d130f8ba4aaba7ca7a6070687822d Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Tue, 8 Sep 2015 09:47:48 -0400
Subject: [PATCH 1/3] TST: Added glm test for Python

---
 tests/python/test_models.py | 15 +++++++++++++++
 1 file changed, 15 insertions(+)
 create mode 100644 tests/python/test_models.py

diff --git a/tests/python/test_models.py b/tests/python/test_models.py
new file mode 100644
index 000000000..a12198f59
--- /dev/null
+++ b/tests/python/test_models.py
@@ -0,0 +1,15 @@
+import numpy as np
+import xgboost as xgb
+
+dpath = 'demo/data/'
+
+def test_glm():
+	dtrain = xgb.DMatrix('../data/agaricus.txt.train')
+	dtest = xgb.DMatrix('../data/agaricus.txt.test')
+	param = {'silent':1, 'objective':'binary:logistic', 'booster':'gblinear',
+         'alpha': 0.0001, 'lambda': 1 }
+    watchlist  = [(dtest,'eval'), (dtrain,'train')]
+	num_round = 4
+	bst = xgb.train(param, dtrain, num_round, watchlist)
+	preds = bst.predict(dtest)
+	labels = dtest.get_label()
\ No newline at end of file

From 82a43f448eb5466e3a47b52d619dc01e0ac87f5f Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Tue, 8 Sep 2015 09:54:38 -0400
Subject: [PATCH 2/3] TST: Added Python test for custom objective functions

---
 tests/python/test_models.py | 23 ++++++++++++++++++++---
 1 file changed, 20 insertions(+), 3 deletions(-)

diff --git a/tests/python/test_models.py b/tests/python/test_models.py
index a12198f59..b0eb7482d 100644
--- a/tests/python/test_models.py
+++ b/tests/python/test_models.py
@@ -2,14 +2,31 @@ import numpy as np
 import xgboost as xgb
 
 dpath = 'demo/data/'
+dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
+dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
 
 def test_glm():
-	dtrain = xgb.DMatrix('../data/agaricus.txt.train')
-	dtest = xgb.DMatrix('../data/agaricus.txt.test')
 	param = {'silent':1, 'objective':'binary:logistic', 'booster':'gblinear',
          'alpha': 0.0001, 'lambda': 1 }
     watchlist  = [(dtest,'eval'), (dtrain,'train')]
 	num_round = 4
 	bst = xgb.train(param, dtrain, num_round, watchlist)
 	preds = bst.predict(dtest)
-	labels = dtest.get_label()
\ No newline at end of file
+	labels = dtest.get_label()
+
+def test_custom_objective():
+	param = {'max_depth':2, 'eta':1, 'silent':1 }
+	watchlist  = [(dtest,'eval'), (dtrain,'train')]
+	num_round = 2
+	def logregobj(preds, dtrain):
+    	labels = dtrain.get_label()
+    	preds = 1.0 / (1.0 + np.exp(-preds))
+    	grad = preds - labels
+    	hess = preds * (1.0-preds)
+    	return grad, hess
+    def evalerror(preds, dtrain):
+    	labels = dtrain.get_label()
+    	return 'error', float(sum(labels != (preds > 0.0))) / len(labels)
+    bst = xgb.train(param, dtrain, num_round, watchlist, logregobj, evalerror)
+
+

From 8196d5d680f0beeaf390d5fbbaa8d8f32207669b Mon Sep 17 00:00:00 2001
From: terrytangyuan <terrytangyuan@gmail.com>
Date: Tue, 8 Sep 2015 10:14:28 -0400
Subject: [PATCH 3/3] TST: More thorough checks for Python tests

---
 tests/python/test_models.py | 31 +++++++++++++++++++------------
 1 file changed, 19 insertions(+), 12 deletions(-)

diff --git a/tests/python/test_models.py b/tests/python/test_models.py
index b0eb7482d..8c06d9de9 100644
--- a/tests/python/test_models.py
+++ b/tests/python/test_models.py
@@ -6,27 +6,34 @@ dtrain = xgb.DMatrix(dpath + 'agaricus.txt.train')
 dtest = xgb.DMatrix(dpath + 'agaricus.txt.test')
 
 def test_glm():
-	param = {'silent':1, 'objective':'binary:logistic', 'booster':'gblinear',
-         'alpha': 0.0001, 'lambda': 1 }
-    watchlist  = [(dtest,'eval'), (dtrain,'train')]
+	param = {'silent':1, 'objective':'binary:logistic', 'booster':'gblinear', 'alpha': 0.0001, 'lambda': 1 }
+	watchlist  = [(dtest,'eval'), (dtrain,'train')]
 	num_round = 4
 	bst = xgb.train(param, dtrain, num_round, watchlist)
+	assert isinstance(bst, xgb.core.Booster)
 	preds = bst.predict(dtest)
 	labels = dtest.get_label()
+	err = sum(1 for i in range(len(preds)) if int(preds[i]>0.5)!=labels[i]) / float(len(preds))
+	assert err < 0.1
 
 def test_custom_objective():
 	param = {'max_depth':2, 'eta':1, 'silent':1 }
 	watchlist  = [(dtest,'eval'), (dtrain,'train')]
 	num_round = 2
 	def logregobj(preds, dtrain):
-    	labels = dtrain.get_label()
-    	preds = 1.0 / (1.0 + np.exp(-preds))
-    	grad = preds - labels
-    	hess = preds * (1.0-preds)
-    	return grad, hess
-    def evalerror(preds, dtrain):
-    	labels = dtrain.get_label()
-    	return 'error', float(sum(labels != (preds > 0.0))) / len(labels)
-    bst = xgb.train(param, dtrain, num_round, watchlist, logregobj, evalerror)
+		labels = dtrain.get_label()
+		preds = 1.0 / (1.0 + np.exp(-preds))
+		grad = preds - labels
+		hess = preds * (1.0-preds)
+		return grad, hess
+	def evalerror(preds, dtrain):
+		labels = dtrain.get_label()
+		return 'error', float(sum(labels != (preds > 0.0))) / len(labels)
+	bst = xgb.train(param, dtrain, num_round, watchlist, logregobj, evalerror)
+	assert isinstance(bst, xgb.core.Booster)
+	preds = bst.predict(dtest)
+	labels = dtest.get_label()
+	err = sum(1 for i in range(len(preds)) if int(preds[i]>0.5)!=labels[i]) / float(len(preds))
+	assert err < 0.1