DEV: Update VSContext to support covariates (#237)

FEAT: Add functions for importing std and transposed CSVs

FEAT: Add function for unioning features and covariates

Author: NickEdwards7502

src/main/scala/au/csiro/variantspark/api/VSContext.scala

@@ -1,15 +1,23 @@
 package au.csiro.variantspark.api
 
-import au.csiro.variantspark.input.{CsvLabelSource, FeatureSource, VCFFeatureSource, VCFSource}
+import au.csiro.variantspark.input.{
+  CsvLabelSource,
+  FeatureSource,
+  VCFFeatureSource,
+  VCFSource,
+  CsvFeatureSource,
+  CsvStdFeatureSource,
+  UnionedFeatureSource
+}
 import org.apache.hadoop.fs.FileSystem
 import org.apache.spark.sql.SparkSession
 import org.apache.spark.sql.SQLContext
-import au.csiro.variantspark.input.CsvFeatureSource
-import au.csiro.variantspark.input.CsvFeatureSource._
 import com.github.tototoshi.csv.CSVFormat
 import au.csiro.variantspark.input.DefaultCSVFormatSpec
 import org.apache.hadoop.conf.Configuration
 import org.apache.spark.SparkContext
+import org.apache.spark.rdd.RDD
+import scala.collection.JavaConverters._
 
 trait SqlContextHolder {
   def sqlContext: SQLContext
@@ -28,7 +36,7 @@ class VSContext(val spark: SparkSession) extends SqlContextHolder {
 
   /** Import features from a VCF file
     * @param inputFile path to file or directory with VCF files to load
-    * @return FeatureSource loaded from the VCF file or files
+    * @return FeatureSource loaded from the VCF file
     */
   def importVCF(inputFile: String, sparkPar: Int = 0): FeatureSource = {
     val vcfSource =
@@ -37,12 +45,62 @@ class VSContext(val spark: SparkSession) extends SqlContextHolder {
   }
 
   /** Import features from a CSV file
-    * @param inputFile: path to file or directory with VCF files to load
+    * @param inputFile: path to CSV file
+    * @param optVariableTypes: optional type specifications
+    * @param csvFormat: [[com.github.tototoshi.csv.CSVFormat]] row format
+    * @return FeatureSource loaded from the CSV file
+    */
+  def importTransposedCSV(inputFile: String,
+      optVariableTypes: Option[RDD[String]], csvFormat: CSVFormat): FeatureSource = {
+    CsvFeatureSource(sc.textFile(inputFile), csvFormat = csvFormat,
+      optVariableTypes = optVariableTypes)
+  }
+  def importTransposedCSV(inputFile: String,
+      variableTypes: java.util.ArrayList[String] = null): FeatureSource = {
+    val csvFormat: CSVFormat = DefaultCSVFormatSpec
+    val optVariableTypes: Option[RDD[String]] = Option(variableTypes).map { types =>
+      sc.parallelize(types.asScala.toSeq)
+    }
+    importTransposedCSV(inputFile, optVariableTypes, csvFormat)
+  }
+  def importTransposedCSV(inputFile: String): FeatureSource = {
+    val csvFormat: CSVFormat = DefaultCSVFormatSpec
+    val optVariableTypes: Option[RDD[String]] = None
+    importTransposedCSV(inputFile, optVariableTypes, csvFormat)
+  }
+
+  /** Import features from a transposed CSV file
+    * @param inputFile: path to CSV file
+    * @param optVariableTypes: optional type specifications
     * @param csvFormat: [[com.github.tototoshi.csv.CSVFormat]] row format
-    * @return FeatureSource loaded from the VCF file or files
+    * @return FeatureSource loaded from CSV file
+    */
+  def importStdCSV(inputFile: String,
+      optVariableTypes: Option[RDD[String]], csvFormat: CSVFormat): FeatureSource = {
+    CsvStdFeatureSource(sc.textFile(inputFile), csvFormat = csvFormat,
+      optVariableTypes = optVariableTypes)
+  }
+  def importStdCSV(inputFile: String,
+      variableTypes: java.util.ArrayList[String] = null): FeatureSource = {
+    val csvFormat: CSVFormat = DefaultCSVFormatSpec
+    val optVariableTypes: Option[RDD[String]] = Option(variableTypes).map { types =>
+      sc.parallelize(types.asScala.toSeq)
+    }
+    importStdCSV(inputFile, optVariableTypes, csvFormat)
+  }
+  def importStdCSV(inputFile: String): FeatureSource = {
+    val csvFormat: CSVFormat = DefaultCSVFormatSpec
+    val optVariableTypes: Option[RDD[String]] = None
+    importStdCSV(inputFile, optVariableTypes, csvFormat)
+  }
+
+  /** Combine FeatureSource objects (typically a genotype source and a covariate source)
+    * @param featureSource: FeatureSource object containing genotype information
+    * @param covariateSource: FeatureSource object containing covariate information
     */
-  def importCSV(inputFile: String, csvFormat: CSVFormat = DefaultCSVFormatSpec): FeatureSource = {
-    CsvFeatureSource(sc.textFile(inputFile), csvFormat = csvFormat)
+  def unionFeaturesAndCovariates(featureSource: FeatureSource,
+      covariateSource: FeatureSource): FeatureSource = {
+    UnionedFeatureSource(featureSource, covariateSource)
   }
 
   /** Loads a labels form a column in a CSV file