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some style nits #1278

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some style nits #1278

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58c688e
clean up some imports
ryan-williams Nov 17, 2016
5dee5d5
misc style nits
ryan-williams Nov 17, 2016
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7 changes: 3 additions & 4 deletions adam-core/src/main/scala/org/bdgenomics/adam/models/SequenceDictionary.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -17,11 +17,10 @@
*/
package org.bdgenomics.adam.models

import htsjdk.samtools.{ SAMFileHeader, SAMSequenceRecord, SAMSequenceDictionary }
import htsjdk.samtools.{ SAMFileHeader, SAMSequenceDictionary, SAMSequenceRecord }
import htsjdk.variant.vcf.VCFHeader
import org.apache.avro.generic.IndexedRecord
import org.bdgenomics.formats.avro.{ AlignmentRecord, NucleotideContigFragment, Contig }
import scala.collection._
import org.bdgenomics.formats.avro.{ Contig, NucleotideContigFragment }

import scala.collection.JavaConversions._

/**
Expand Down
100 changes: 62 additions & 38 deletions adam-core/src/main/scala/org/bdgenomics/adam/rdd/ADAMContext.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -18,9 +18,9 @@
package org.bdgenomics.adam.rdd

import java.io.{ File, FileNotFoundException, InputStream }
import java.util.regex.Pattern

import htsjdk.samtools.util.Locatable
import htsjdk.samtools.{ SAMFileHeader, ValidationStringency }
import htsjdk.samtools.util.{ Interval, Locatable }
import htsjdk.variant.vcf.VCFHeader
import org.apache.avro.Schema
import org.apache.avro.file.DataFileStream
Expand All @@ -40,12 +40,7 @@ import org.bdgenomics.adam.converters._
import org.bdgenomics.adam.instrumentation.Timers._
import org.bdgenomics.adam.io._
import org.bdgenomics.adam.models._
import org.bdgenomics.adam.projections.{
AlignmentRecordField,
FeatureField,
NucleotideContigFragmentField,
Projection
}
import org.bdgenomics.adam.projections.{ FeatureField, Projection }
import org.bdgenomics.adam.rdd.contig.NucleotideContigFragmentRDD
import org.bdgenomics.adam.rdd.feature._
import org.bdgenomics.adam.rdd.fragment.FragmentRDD
Expand All @@ -59,9 +54,8 @@ import org.bdgenomics.utils.io.LocalFileByteAccess
import org.bdgenomics.utils.misc.{ HadoopUtil, Logging }
import org.seqdoop.hadoop_bam._
import org.seqdoop.hadoop_bam.util._

import scala.collection.JavaConversions._
import scala.collection.JavaConverters._
import scala.collection.Map
import scala.reflect.ClassTag

/**
Expand Down Expand Up @@ -97,7 +91,7 @@ object ADAMContext {
implicit def sameTypeConversionFn[T, U <: GenomicRDD[T, U]](gRdd: U,
rdd: RDD[T]): U = {
// hijack the transform function to discard the old RDD
gRdd.transform(oldRdd => rdd)
gRdd.transform(_ => rdd)
}

implicit def readsToVCConversionFn(arRdd: AlignmentRecordRDD,
Expand Down Expand Up @@ -143,8 +137,6 @@ private class FileFilter(private val name: String) extends PathFilter {
}
}

import org.bdgenomics.adam.rdd.ADAMContext._

/**
* The ADAMContext provides functions on top of a SparkContext for loading genomic data.
*
Expand Down Expand Up @@ -193,12 +185,13 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
private def loadSingleVcfMetadata(filePath: String): (SequenceDictionary, Seq[Sample]) = {
def headerToMetadata(vcfHeader: VCFHeader): (SequenceDictionary, Seq[Sample]) = {
val sd = SequenceDictionary.fromVCFHeader(vcfHeader)
val samples = asScalaBuffer(vcfHeader.getGenotypeSamples)
.map(s => {
Sample.newBuilder()
.setSampleId(s)
.build()
}).toSeq
val samples =
asScalaBuffer(vcfHeader.getGenotypeSamples)
.map(s =>
Sample.newBuilder()
.setSampleId(s)
.build()
)
(sd, samples)
}

Expand Down Expand Up @@ -451,12 +444,11 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
val rg = loadBamReadGroups(samHeader)
Some((sd, rg))
} catch {
case e: Throwable => {
case e: Throwable =>
log.error(
s"Loading failed for $fp:n${e.getMessage}\n\t${e.getStackTrace.take(25).map(_.toString).mkString("\n\t")}"
)
None
}
}
}).reduce((kv1, kv2) => {
(kv1._1 ++ kv2._1, kv1._2 ++ kv2._2)
Expand All @@ -471,7 +463,7 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
// contains bams, hadoop-bam is a-ok! i believe that it is better (perf) to
// just load from a single newAPIHadoopFile call instead of a union across
// files, so we do that whenever possible
val records = if (filteredFiles.size != bamFiles.size) {
val records = if (filteredFiles.length != bamFiles.length) {
sc.union(filteredFiles.map(p => {
sc.newAPIHadoopFile(p.toString, classOf[AnySAMInputFormat], classOf[LongWritable],
classOf[SAMRecordWritable], ContextUtil.getConfiguration(job))
Expand All @@ -480,7 +472,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
sc.newAPIHadoopFile(filePath, classOf[AnySAMInputFormat], classOf[LongWritable],
classOf[SAMRecordWritable], ContextUtil.getConfiguration(job))
}
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
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Though I'll probably get downvoted, I prefer to always have curly braces

if (Metrics.isRecording) {
  records.instrument()
}

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I'm also an "always braces" type.

records.instrument()

val samRecordConverter = new SAMRecordConverter

AlignedReadRDD(records.map(p => samRecordConverter.convert(p._2.get)),
Expand Down Expand Up @@ -538,7 +533,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
sc.newAPIHadoopFile(p.toString, classOf[BAMInputFormat], classOf[LongWritable],
classOf[SAMRecordWritable], conf)
}))
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

val samRecordConverter = new SAMRecordConverter
AlignedReadRDD(records.map(p => samRecordConverter.convert(p._2.get)),
seqDict,
Expand Down Expand Up @@ -618,7 +616,6 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable

// reverse list and return as seq
list.reverse
.toSeq
}

/**
Expand Down Expand Up @@ -675,7 +672,9 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
classOf[Text],
ContextUtil.getConfiguration(job)
)
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

// convert records
val fastqRecordConverter = new FastqRecordConverter
Expand Down Expand Up @@ -786,7 +785,9 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
classOf[Text],
ContextUtil.getConfiguration(job)
)
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

// convert records
val fastqRecordConverter = new FastqRecordConverter
Expand Down Expand Up @@ -845,7 +846,8 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
val records = readVcfRecords(filePath, None)

// attach instrumentation
if (Metrics.isRecording) records.instrument() else records
if (Metrics.isRecording)
records.instrument()

// load vcf metadata
val (sd, samples) = loadVcfMetadata(filePath)
Expand Down Expand Up @@ -882,7 +884,8 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
val records = readVcfRecords(filePath, Some(viewRegions))

// attach instrumentation
if (Metrics.isRecording) records.instrument() else records
if (Metrics.isRecording)
records.instrument()

// load vcf metadata
val (sd, samples) = loadVcfMetadata(filePath)
Expand Down Expand Up @@ -952,7 +955,9 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
classOf[LongWritable],
classOf[Text]
)
if (Metrics.isRecording) fastaData.instrument() else fastaData

if (Metrics.isRecording)
fastaData.instrument()

val remapData = fastaData.map(kv => (kv._1.get, kv._2.toString))

Expand Down Expand Up @@ -984,7 +989,9 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
classOf[Text],
ContextUtil.getConfiguration(job)
)
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

// convert records
val fastqRecordConverter = new FastqRecordConverter
Expand Down Expand Up @@ -1030,7 +1037,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD = {
val records = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism))
.flatMap(new GFF3Parser().parse(_, stringency))
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

FeatureRDD(records)
}

Expand All @@ -1050,7 +1060,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD = {
val records = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism))
.flatMap(new GTFParser().parse(_, stringency))
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

FeatureRDD(records)
}

Expand All @@ -1070,7 +1083,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD = {
val records = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism))
.flatMap(new BEDParser().parse(_, stringency))
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

FeatureRDD(records)
}

Expand All @@ -1090,7 +1106,10 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable
stringency: ValidationStringency = ValidationStringency.LENIENT): FeatureRDD = {
val records = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism))
.flatMap(new NarrowPeakParser().parse(_, stringency))
if (Metrics.isRecording) records.instrument() else records

if (Metrics.isRecording)
records.instrument()

FeatureRDD(records)
}

Expand All @@ -1111,11 +1130,16 @@ class ADAMContext private (@transient val sc: SparkContext) extends Serializable

val parsedLines = sc.textFile(filePath, minPartitions.getOrElse(sc.defaultParallelism))
.map(new IntervalListParser().parseWithHeader(_, stringency))
val (seqDict, records) = (SequenceDictionary(parsedLines.flatMap(_._1).collect(): _*),
parsedLines.flatMap(_._2))

val seqDict = SequenceDictionary(parsedLines.flatMap(_._1).collect(): _*)

val records = parsedLines.flatMap(_._2)

val seqDictMap = seqDict.records.map(sr => sr.name -> sr).toMap

if (Metrics.isRecording) records.instrument() else records
if (Metrics.isRecording)
records.instrument()

FeatureRDD(records, seqDict)
}

Expand Down