Add License information, Fix formatting

src/main/scala/com/amazon/deequ/suggestions/rules/RetainCompletenessRule.scala

@@ -40,7 +40,10 @@ case class RetainCompletenessRule(
   }
 
   override def candidate(profile: ColumnProfile, numRecords: Long): ConstraintSuggestion = {
-    val targetCompleteness = intervalStrategy.calculateTargetConfidenceInterval(profile.completeness, numRecords).lowerBound
+    val targetCompleteness = intervalStrategy.calculateTargetConfidenceInterval(
+      profile.completeness,
+      numRecords
+    ).lowerBound
 
     val constraint = completenessConstraint(profile.column, _ >= targetCompleteness)
 

src/main/scala/com/amazon/deequ/suggestions/rules/interval/ConfidenceIntervalStrategy.scala

@@ -1,3 +1,19 @@
+/**
+ * Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not
+ * use this file except in compliance with the License. A copy of the License
+ * is located at
+ *
+ *     http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file 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 com.amazon.deequ.suggestions.rules.interval
 
 import breeze.stats.distributions.{Gaussian, Rand}
@@ -15,7 +31,11 @@ trait ConfidenceIntervalStrategy {
     * @param confidence confidence level of method used to estimate the interval.
     * @return
     */
-  def calculateTargetConfidenceInterval(pHat: Double, numRecords: Long, confidence: Double = defaultConfidence): ConfidenceInterval
+  def calculateTargetConfidenceInterval(
+    pHat: Double,
+    numRecords: Long,
+    confidence: Double = defaultConfidence
+  ): ConfidenceInterval
 
   def validateInput(pHat: Double, confidence: Double): Unit = {
     require(0.0 <= pHat && pHat <= 1.0, "pHat must be between 0.0 and 1.0")

src/main/scala/com/amazon/deequ/suggestions/rules/interval/WaldIntervalStrategy.scala

@@ -1,3 +1,19 @@
+/**
+ * Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not
+ * use this file except in compliance with the License. A copy of the License
+ * is located at
+ *
+ *     http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file 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 com.amazon.deequ.suggestions.rules.interval
 
 import com.amazon.deequ.suggestions.rules.interval.ConfidenceIntervalStrategy.{ConfidenceInterval, defaultConfidence}
@@ -12,7 +28,11 @@ import scala.math.BigDecimal.RoundingMode
  *      Normal approximation interval (Wikipedia)</a>
  */
 case class WaldIntervalStrategy() extends ConfidenceIntervalStrategy {
-  def calculateTargetConfidenceInterval(pHat: Double, numRecords: Long, confidence: Double = defaultConfidence): ConfidenceInterval = {
+  def calculateTargetConfidenceInterval(
+    pHat: Double,
+    numRecords: Long,
+    confidence: Double = defaultConfidence
+  ): ConfidenceInterval = {
     validateInput(pHat, confidence)
     val successRatio = BigDecimal(pHat)
     val marginOfError = BigDecimal(calculateZScore(confidence) * math.sqrt(pHat * (1 - pHat) / numRecords))

src/main/scala/com/amazon/deequ/suggestions/rules/interval/WilsonScoreIntervalStrategy.scala

@@ -1,3 +1,19 @@
+/**
+ * Copyright 2018 Amazon.com, Inc. or its affiliates. All Rights Reserved.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License"). You may not
+ * use this file except in compliance with the License. A copy of the License
+ * is located at
+ *
+ *     http://aws.amazon.com/apache2.0/
+ *
+ * or in the "license" file accompanying this file. This file 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 com.amazon.deequ.suggestions.rules.interval
 
 import com.amazon.deequ.suggestions.rules.interval.ConfidenceIntervalStrategy.{ConfidenceInterval, defaultConfidence}
@@ -13,7 +29,10 @@ import scala.math.BigDecimal.RoundingMode
  */
 case class WilsonScoreIntervalStrategy() extends ConfidenceIntervalStrategy {
 
-  def calculateTargetConfidenceInterval(pHat: Double, numRecords: Long, confidence: Double = defaultConfidence): ConfidenceInterval = {
+  def calculateTargetConfidenceInterval(
+    pHat: Double, numRecords: Long,
+    confidence: Double = defaultConfidence
+  ): ConfidenceInterval = {
     validateInput(pHat, confidence)
     val zScore = calculateZScore(confidence)
     val zSquareOverN = math.pow(zScore, 2) / numRecords

src/test/scala/com/amazon/deequ/suggestions/rules/ConstraintRulesTest.scala

@@ -157,7 +157,9 @@ class ConstraintRulesTest extends WordSpec with FixtureSupport with SparkContext
           val fakeColumnProfile = getFakeColumnProfileWithNameAndCompleteness("att1", 0.5)
 
           val check = Check(CheckLevel.Warning, "some")
-            .addConstraint(RetainCompletenessRule(intervalStrategy = strategy).candidate(fakeColumnProfile, 100).constraint)
+            .addConstraint(
+              RetainCompletenessRule(intervalStrategy = strategy).candidate(fakeColumnProfile, 100).constraint
+            )
 
           val verificationResult = VerificationSuite()
             .onData(dfWithColumnCandidate)