RxJava different output between Flowable and Observable with Window and Groupby - kotlin

I'm using RxJava2 with code that boils down to something like this:
val whitespaceRegex = Regex("\\s+")
val queryRegex = Regex("query=([^&]+)", RegexOption.IGNORE_CASE)
val dateTimeFormatter = DateTimeFormatter.ISO_OFFSET_DATE_TIME
#JvmStatic
fun main(args: Array<String>) {
val cnt = AtomicLong()
val templateStr = "|date| /ignored/ query=|query|"
val random = ThreadLocalRandom.current()
var curDate = ZonedDateTime.of(LocalDate.of(2016, Month.JANUARY, 1), LocalTime.MIDNIGHT, ZoneId.of("UTC"))
val generator = Flowable.generate<String> { emitter ->
// normally these are read from a file, this is for the example
val next = cnt.incrementAndGet()
if (next % 3000 == 0L) {
curDate = curDate.plusDays(1)
}
if (next < 100000) {
val curStr = templateStr
.replace("|date|", dateTimeFormatter.format(curDate))
.replace("|query|", random.nextInt(1, 1000).toString())
emitter.onNext(curStr)
} else {
emitter.onComplete()
}
}
val source = generator
.map { line ->
val cols = line.split(whitespaceRegex)
val queryRaw = queryRegex.find(cols[2])?.groupValues?.get(1) ?: ""
val query = URLDecoder.decode(queryRaw, Charsets.UTF_8.name()).toLowerCase().replace(whitespaceRegex, " ").trim()
val date = dateTimeFormatter.parse(cols[0])
Pair(LocalDate.from(date), query)
}
.share()
source
.window(source.map { it.first }.distinctUntilChanged())
.flatMap { window ->
window
.groupBy { pair -> pair }
.flatMap({ grouping ->
grouping
.count()
.map {
Pair(grouping.key, it)
}.toFlowable()
})
}
.subscribe({ println("Result: $it}") }, { it.printStackTrace() }, { println("Done") })
}
When I use Observable.generate it works fine, but with Flowable.generate there is no output. This is counting how many queries occurred on a given day. The day increase sequentially so I form a window of each day, then count the queries with a groupBy. Do I need to do this differently with Flowable?

As akarnokd mentioned, this was due to flatMap having a default maxConcurrency of 128. I found this issue, https://github.com/ReactiveX/RxJava/issues/5126, which describes the reason in more detail. This fixes the problem:
val cnt = AtomicLong()
val templateStr = "|date| /ignored/ query=|query|"
val random = ThreadLocalRandom.current()
var curDate = ZonedDateTime.of(LocalDate.of(2016, Month.JANUARY, 1), LocalTime.MIDNIGHT, ZoneId.of("UTC"))
val generator = Flowable.generate<String> { emitter ->
val next = cnt.incrementAndGet()
if (next % 3000 == 0L) {
curDate = curDate.plusDays(1)
}
if (next < 1000000) {
val curStr = templateStr
.replace("|date|", dateTimeFormatter.format(curDate))
.replace("|query|", random.nextInt(1, 1000).toString())
emitter.onNext(curStr)
} else {
emitter.onComplete()
}
}
val source = generator
.map { line ->
val cols = line.split(whitespaceRegex)
val queryRaw = queryRegex.find(cols[2])?.groupValues?.get(1) ?: ""
val query = URLDecoder.decode(queryRaw, Charsets.UTF_8.name()).toLowerCase().replace(whitespaceRegex, " ").trim()
val date = dateTimeFormatter.parse(cols[0])
Pair(LocalDate.from(date), query)
}
.share()
source
.window(source.map { it.first }.distinctUntilChanged().doOnEach({println("Win: $it")}))
.flatMap( { window ->
window
.groupBy { pair -> pair }
.flatMap({ grouping ->
grouping
.count()
.map {
Pair(grouping.key, it)
}.toFlowable()
// fix is here
}, Int.MAX_VALUE)
// and here
}, Int.MAX_VALUE)
.subscribe({ println("Result: $it}") }, { it.printStackTrace() }, { println("Done") })

Related

Problem saving data into room db from paging library api response

I have an application built using Jetpack Compose , where i also use paging library 3 to fetch data from db , i have multiple remote mediator where i fetch data and save it directly into database , the issue is that sometimes data gets saved , sometimes not , it goes to the point that sometimes one of the two only gets data stored.
Remote Mediator 1:
#ExperimentalPagingApi
class PopularClothingRemoteMediator #Inject constructor(
private val clothingApi: ClothingApi,
private val clothingDatabase: ClothingDatabase
) : RemoteMediator<Int, Clothing>(){
private val clothingDao = clothingDatabase.clothingDao()
private val clothingRemoteKeysDao = clothingDatabase.clothingRemoteKeysDao()
override suspend fun initialize(): InitializeAction {
val currentTime = System.currentTimeMillis()
val lastUpdated = clothingRemoteKeysDao.getRemoteKeys(clothingId = 1)?.lastUpdated ?: 0L
val cacheTimeout = 1440
val diffInMinutes = (currentTime - lastUpdated) / 1000 / 60
return if (diffInMinutes.toInt() <= cacheTimeout) {
// Log.d("RemoteMediator", "UP TO DATE")
InitializeAction.SKIP_INITIAL_REFRESH
} else {
// Log.d("RemoteMediator", "REFRESH")
InitializeAction.LAUNCH_INITIAL_REFRESH
}
}
override suspend fun load(loadType: LoadType, state: PagingState<Int, Clothing>): MediatorResult {
return try {
val page = when (loadType) {
LoadType.REFRESH -> {
val remoteKeys = getRemoteKeyClosestToCurrentPosition(state)
remoteKeys?.nextPage?.minus(1) ?: 1
}
LoadType.PREPEND -> {
val remoteKeys = getRemoteKeyForFirstItem(state)
val prevPage = remoteKeys?.prevPage
?: return MediatorResult.Success(
endOfPaginationReached = remoteKeys != null
)
prevPage
}
LoadType.APPEND -> {
val remoteKeys = getRemoteKeyForLastItem(state)
val nextPage = remoteKeys?.nextPage
?: return MediatorResult.Success(
endOfPaginationReached = remoteKeys != null
)
nextPage
}
}
val response = clothingApi.getPopularClothing(page = page)
if (response.popularClothing.isNotEmpty()) {
clothingDatabase.withTransaction {
if (loadType == LoadType.REFRESH) {
clothingDao.deleteAllClothing()
clothingRemoteKeysDao.deleteAllRemoteKeys()
}
val prevPage = response.prevPage
val nextPage = response.nextPage
val keys = response.popularClothing.map { clothing ->
ClothingRemoteKeys(
clothingId = clothing.clothingId,
prevPage = prevPage,
nextPage = nextPage,
lastUpdated = response.lastUpdated
)
}
// When i debug this code , it works fine and the last line is executed
// the issue data sometimes gets saved , sometimes not
clothingRemoteKeysDao.addAllRemoteKeys(clothingRemoteKeys = keys)
clothingDao.addClothing(clothing = response.popularClothing)
}
}
MediatorResult.Success(endOfPaginationReached = response.nextPage == null)
} catch (e: Exception) {
return MediatorResult.Error(e)
}
}
private suspend fun getRemoteKeyClosestToCurrentPosition(
state: PagingState<Int, Clothing>
): ClothingRemoteKeys? {
return state.anchorPosition?.let { position ->
state.closestItemToPosition(position)?.clothingId?.let { clothingId ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothingId)
}
}
}
private suspend fun getRemoteKeyForFirstItem(
state: PagingState<Int, Clothing>
): ClothingRemoteKeys? {
return state.pages.firstOrNull { it.data.isNotEmpty() }?.data?.firstOrNull()
?.let { clothing ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothing.clothingId)
}
}
private suspend fun getRemoteKeyForLastItem(
state: PagingState<Int, Clothing>
): ClothingRemoteKeys? {
return state.pages.lastOrNull { it.data.isNotEmpty() }?.data?.lastOrNull()
?.let { clothing ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothing.clothingId)
}
}
}
Remote Mediator 2:
class OuterwearRemoteMediator #Inject constructor(
private val clothingApi: ClothingApi,
private val clothingDatabase: ClothingDatabase
) : RemoteMediator<Int, Clothing>() {
private val clothingDao = clothingDatabase.clothingDao()
private val clothingRemoteKeysDao = clothingDatabase.clothingRemoteKeysDao()
override suspend fun initialize(): InitializeAction {
val currentTime = System.currentTimeMillis()
val lastUpdated = clothingRemoteKeysDao.getRemoteKeys(clothingId = 1)?.lastUpdated ?: 0L
val cacheTimeout = 1440
val diffInMinutes = (currentTime - lastUpdated) / 1000 / 60
return if (diffInMinutes.toInt() <= cacheTimeout) {
// Log.d("RemoteMediator", "UP TO DATE")
InitializeAction.SKIP_INITIAL_REFRESH
} else {
// Log.d("RemoteMediator", "REFRESH")
InitializeAction.LAUNCH_INITIAL_REFRESH
}
}
override suspend fun load(loadType: LoadType, state: PagingState<Int, Clothing>): MediatorResult {
return try {
val page = when (loadType) {
LoadType.REFRESH -> {
val remoteKeys = getRemoteKeyClosestToCurrentPosition(state)
remoteKeys?.nextPage?.minus(1) ?: 1
}
LoadType.PREPEND -> {
val remoteKeys = getRemoteKeyForFirstItem(state)
val prevPage = remoteKeys?.prevPage
?: return MediatorResult.Success(
endOfPaginationReached = remoteKeys != null
)
prevPage
}
LoadType.APPEND -> {
val remoteKeys = getRemoteKeyForLastItem(state)
val nextPage = remoteKeys?.nextPage
?: return MediatorResult.Success(endOfPaginationReached = remoteKeys != null)
nextPage
}
}
val response = clothingApi.getOuterwear(page = page)
if (response.outerwear.isNotEmpty()) {
clothingDatabase.withTransaction {
if (loadType == LoadType.REFRESH) {
clothingDao.deleteAllClothing()
clothingRemoteKeysDao.deleteAllRemoteKeys()
}
val prevPage = response.prevPage
val nextPage = response.nextPage
val keys = response.outerwear.map { clothing ->
ClothingRemoteKeys(
clothingId = clothing.clothingId,
prevPage = prevPage,
nextPage = nextPage,
lastUpdated = response.lastUpdated
)
}
// the same thing here
// When i debug this code , it works fine and the last line is executed
// the issue data sometimes gets saved , sometimes not
clothingRemoteKeysDao.addAllRemoteKeys(clothingRemoteKeys = keys)
clothingDao.addClothing(clothing = response.outerwear)
}
}
MediatorResult.Success(endOfPaginationReached = response.nextPage == null)
} catch (e: Exception) {
return MediatorResult.Error(e)
}
}
private suspend fun getRemoteKeyClosestToCurrentPosition(
state: PagingState<Int, Clothing>): ClothingRemoteKeys? {
return state.anchorPosition?.let { position ->
state.closestItemToPosition(position)?.clothingId?.let { clothingId ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothingId)
}
}
}
private suspend fun getRemoteKeyForFirstItem(
state: PagingState<Int, Clothing>): ClothingRemoteKeys? {
return state.pages.firstOrNull { it.data.isNotEmpty() }?.data?.firstOrNull()
?.let { clothing ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothing.clothingId)
}
}
private suspend fun getRemoteKeyForLastItem(
state: PagingState<Int, Clothing>
): ClothingRemoteKeys? {
return state.pages.lastOrNull { it.data.isNotEmpty() }?.data?.lastOrNull()
?.let { clothing ->
clothingRemoteKeysDao.getRemoteKeys(clothingId = clothing.clothingId)
}
}

Kotlin - The method returns how many elements meet the condition

I'm struggling to get this working:
Implement the method countWhere (condition: (T) -> Boolean): Int. The method returns how many elements meet the condition (state).
Here is an example of how it can be used:
NOTE: I can't change the fun main stuff.
fun main () {
val list = LinkedList <String> ()
list . addFirst ("Apple")
list . addFirst ("Banana")
list . addFirst ("Bear")
val fruitStartsWithB = list. countWhere {element ->
element. starts with ("B")
}
println (fruitStartsWithB) // fruitsStartsWithB is 2 because there are two items in the list that go into "B".
}
this is what causing me troubles:
fun countWhere(condition: (T) -> Boolean): Int {
var count: Int = 0
forEach { if (this == condition) count++ }
return count
}
my return is 0. My return has to be 2. Where is my mistake and how do I fix it?
This is all the code I have:
class LinkedList <T>: Iterable<T> {
data class Node <T>( val data : T, var next : Node <T>?)
private var first : Node <T>? = null
var isSorted = true
fun isEmpty() = first == null
fun addFirst(data: T) {
first = Node(data, first)
isSorted = false
}
fun getFirst(): T = get(0)
fun get(n: Int): T {
if (n < 0 ) throw IndexOutOfBoundsException ()
var run = first
var count = 0
while (count < n && run != null) {
run = run.next
count++
}
return run?.data ?: throw IndexOutOfBoundsException ()
}
fun clear () {
first = null // Clear
isSorted = true // Clear
}
// fun size (): Int{
// var run = first
// var count = 0
// while (run != null) {
// count++
// run = run.next
// }
// return count
// }
fun getOrNull(index: Int): T? {
if (index < 0 ) return null
var run = first
var count = 0
while (count < index && run != null) {
run = run.next
count++
}
return run?.data ?: null
}
fun addLast (data: T){
if (isEmpty()) addFirst(data) else {
var runPointer = first
while (runPointer?.next != null) {
runPointer = runPointer.next
}
runPointer?.next = Node(data, null)
}
isSorted = false
}
fun forEach(action: (T) -> Unit) {
for (i in this ) action(i)
}
fun size (): Int{
var count = 0
forEach { count ++ }
return count
}
override fun iterator(): Iterator<T> = object: Iterator <T> {
private var run = first
override fun hasNext(): Boolean = run!= null
override fun next(): T {
val res = run?.data ?: throw NoSuchElementException()
run = run?.next
return res
}
}
fun countWhere(condition: (T) -> Boolean): Int {
var count: Int = 0
forEach { if (condition(it)) count++ }
return count
}
}
you have to invoke your lambda:
fun countWhere(condition: (T) -> Boolean): Int {
var count: Int = 0
forEach { if (condition(it)) count++ }
return count
}

Cut pairs with empty values from map

I'd like to filter out all the pairs with empty values
val mapOfNotEmptyPairs: Map<String, String> = mapOf("key" to Some("value"), "secondKey" to None)
expected:
print(mapOfNotEmptyPairs)
// {key=value}
Vanilla Kotlin
val rawMap = mapOf<String, String?>(
"key" to "value", "secondKey" to null)
// Note that this doesn't adjust the type. If needed, use
// a cast (as Map<String,String>) or mapValues{ it.value!! }
val filteredMap = rawMap.filterValues { it != null }
System.out.println(filteredMap)
p.s When using Arrow Option
val rawMap = mapOf<String, Option<String>>(
mapOf("key" to Some("value"), "secondKey" to None)
val transformedMap = rawMap
.filterValues { it.isDefined() }
.mapValues { it.value.orNull()!! }
p.p.s When using Arrow Option and their filterMap extension function;
val rawMap = mapOf<String, Option<String>>(
mapOf("key" to Some("value"), "secondKey" to None)
val transformedMap = rawMap
.filterMap { it.value.orNull() }
val mapOfNotEmptyPairs =
mapOf("key" to Some("value"), "secondKey" to None)
.filterValues { it is Some<String> } // or { it !is None } or { it.isDefined() }
.mapValues { (_, v) -> (v as Some<String>).t }

Kotlin - replace item in a map

I'm write a function that should replace an item in map. I have reach it using HashMap but is possible to write something similar in a "kotlinmatic way"?
fun HashMap<Int, String>.ignoreFields(path: String, fieldsToIgnore: FieldsToIgnore) = {
val filtered: List<Field> = fieldsToIgnore.ignoreBodyFields.filter { it.tagFile == path }
filtered.forEach {
val updatedJson = JsonPath.parse(JsonPath.parse(this[it.order])
.read<String>(whatevervariable))
.delete(it.field)
.apply { set("equalJson", this) }
.jsonString()
this.replace(it.order, updatedJson)
}
return this
}
update using map based on answers:
fun Map<Int, String>.ignoreFields(path: String, fieldsToIgnore: FieldsToIgnore): Map<Int, String> {
val filtered = fieldsToIgnore.ignoreBodyFields.filter { it.tagFile == path }
return this.mapValues {m ->
val field = filtered.find { it.order == m.key }
if (field != null) {
JsonPath.parse(JsonPath.parse(this[field.order])
.read<String>(whatevervariable))
.delete(field.field)
.apply { set(pathBodyEqualToJson, this) }
.jsonString()
} else {
m.value
}
}
}
You can use mapValues to conditionally use different value for same key. This will return a new immutable map
Update: filtered will now be a map of order to updatedJson
fun HashMap<Int, String>.ignoreFields(path: String,
fieldsToIgnore: FieldsToIgnore): Map<Int, String> {
val filtered: Map<Int, String> = fieldsToIgnore.ignoreBodyFields
.filter { it.tagFile == path }
.map {
val updatedJson = JsonPath.parse(JsonPath.parse(this[it.order])
.read<String>(whatevervariable))
.delete(it.field)
.apply { set("equalJson", this) }
.jsonString()
it.order to updatedJson
}
return this.mapValues {
filtered.getOrElse(it.key) { it.value }
}
}
A possible solution is to use mapValues() operator, e.g.:
fun Map<Int, String>.ignoreFields(ignoredFields: List<Int>): Map<Int, String> {
return this.mapValues {
if (ignoredFields.contains(it.key)) {
"whatever"
} else {
it.value
}
}
}
// Example
val ignoredFields = listOf<Int>(1,3)
val input = mapOf<Int, String>(1 to "a", 2 to "b", 3 to "c")
val output = input.ignoreFields(ignoredFields)
print(output)
// prints {1=whatever, 2=b, 3=whatever}

ojAlgo - Optimization issue with contiguous block logic?

I am using ojAlgo to work through a classroom scheduling problem I'm doing as an exercise. The source code can be found here on GitHub in the kotlin_solution folder:
https://github.com/thomasnield/optimized-scheduling-demo
Everything was going fine until I started to implement contiguous block logic which I've described over on Math Exchange. Bascially, if a class session requires 4 blocks then those 4 blocks need to be together.
For some reason, this modeling logic screeches to a halt when I implement the contiguous logic in this part of the code. It is churning infinitely.
Here is the Kotlin code in it's entirety:
import org.ojalgo.optimisation.ExpressionsBasedModel
import org.ojalgo.optimisation.Variable
import java.time.DayOfWeek
import java.time.LocalDate
import java.time.LocalDateTime
import java.time.LocalTime
import java.util.concurrent.atomic.AtomicInteger
// declare model
val model = ExpressionsBasedModel()
val funcId = AtomicInteger(0)
val variableId = AtomicInteger(0)
fun variable() = Variable(variableId.incrementAndGet().toString().let { "Variable$it" }).apply(model::addVariable)
fun addExpression() = funcId.incrementAndGet().let { "Func$it"}.let { model.addExpression(it) }
// Any Monday through Friday date range will work
val operatingDates = LocalDate.of(2017,10,16)..LocalDate.of(2017,10,20)
val operatingDay = LocalTime.of(8,0)..LocalTime.of(17,0)
val breaks = listOf<ClosedRange<LocalTime>>(
//LocalTime.of(11,30)..LocalTime.of(13,0)
)
// classes
val scheduledClasses = listOf(
ScheduledClass(id=1, name="Psych 101", hoursLength=1.0, repetitions=2),
ScheduledClass(id=2, name="English 101", hoursLength=1.5, repetitions=3),
ScheduledClass(id=3, name="Math 300", hoursLength=1.5, repetitions=2),
ScheduledClass(id=4, name="Psych 300", hoursLength=3.0, repetitions=1),
ScheduledClass(id=5, name="Calculus I", hoursLength=2.0, repetitions=2),
ScheduledClass(id=6, name="Linear Algebra I", hoursLength=2.0, repetitions=3),
ScheduledClass(id=7, name="Sociology 101", hoursLength=1.0, repetitions=2),
ScheduledClass(id=8, name="Biology 101", hoursLength=1.0, repetitions=2)
)
fun main(args: Array<String>) {
println("Job started at ${LocalTime.now()}")
applyConstraints()
println(model.minimise())
Session.all.forEach {
println("${it.name}-${it.repetitionIndex}: ${it.start.dayOfWeek} ${it.start.toLocalTime()}-${it.end.toLocalTime()}")
}
println("Job ended at ${LocalTime.now()}")
}
data class Block(val dateTimeRange: ClosedRange<LocalDateTime>) {
val timeRange = dateTimeRange.let { it.start.toLocalTime()..it.endInclusive.toLocalTime() }
fun addConstraints() {
val f = addExpression().upper(1)
OccupationState.all.filter { it.block == this }.forEach {
f.set(it.occupied, 1)
}
}
companion object {
// Operating blocks
val all by lazy {
generateSequence(operatingDates.start.atTime(operatingDay.start)) {
it.plusMinutes(15).takeIf { it.plusMinutes(15) <= operatingDates.endInclusive.atTime(operatingDay.endInclusive) }
}.filter { it.toLocalTime() in operatingDay }
.map { Block(it..it.plusMinutes(15)) }
.toList()
}
}
}
data class ScheduledClass(val id: Int,
val name: String,
val hoursLength: Double,
val repetitions: Int) {
val sessions by lazy {
Session.all.filter { it.parentClass == this }
}
fun addConstraints() {
//guide 3 repetitions to be fixed on MONDAY, WEDNESDAY, FRIDAY
if (repetitions == 3) {
sessions.forEach { session ->
val f = addExpression().level(session.blocksNeeded)
session.occupationStates.asSequence()
.filter {
it.block.dateTimeRange.start.dayOfWeek ==
when(session.repetitionIndex) {
1 -> DayOfWeek.MONDAY
2 -> DayOfWeek.WEDNESDAY
3 -> DayOfWeek.FRIDAY
else -> throw Exception("Must be 1/2/3")
}
}
.forEach {
f.set(it.occupied,1)
}
}
}
//guide two repetitions to be 48 hours apart (in development)
if (repetitions == 2) {
val first = sessions.find { it.repetitionIndex == 1 }!!
val second = sessions.find { it.repetitionIndex == 2 }!!
}
}
companion object {
val all by lazy { scheduledClasses }
}
}
data class Session(val id: Int,
val name: String,
val hoursLength: Double,
val repetitionIndex: Int,
val parentClass: ScheduledClass) {
val blocksNeeded = (hoursLength * 4).toInt()
val occupationStates by lazy {
OccupationState.all.asSequence().filter { it.session == this }.toList()
}
val start get() = occupationStates.asSequence().filter { it.occupied.value.toInt() == 1 }
.map { it.block.dateTimeRange.start }
.min()!!
val end get() = occupationStates.asSequence().filter { it.occupied.value.toInt() == 1 }
.map { it.block.dateTimeRange.endInclusive }
.max()!!
fun addConstraints() {
val f1 = addExpression().level(0)
//block out exceptions
occupationStates.asSequence()
.filter { os -> breaks.any { os.block.timeRange.start in it } || os.block.timeRange.start !in operatingDay }
.forEach {
// b = 0, where b is occupation state
// this means it should never be occupied
f1.set(it.occupied, 1)
}
//sum of all boolean states for this session must equal the # blocks needed
val f2 = addExpression().level(blocksNeeded)
occupationStates.forEach {
f2.set(it.occupied, 1)
}
//ensure all occupied blocks are consecutive
// PROBLEM, not finding a solution and stalling
/*
b1, b2, b3 .. bn = binary from each group
all binaries must sum to 1, indicating fully consecutive group exists
b1 + b2 + b3 + .. bn = 1
*/
val consecutiveStateConstraint = addExpression().level(1)
(0..occupationStates.size).asSequence().map { i ->
occupationStates.subList(i, (i + blocksNeeded).let { if (it > occupationStates.size) occupationStates.size else it })
}.filter { it.size == blocksNeeded }
.forEach { grp ->
/*
b = 1,0 binary for group
n = blocks needed
x1, x2, x3 .. xn = occupation states in group
x1 + x2 + x3 .. + xn - bn >= 0
*/
val binaryForGroup = variable().binary()
consecutiveStateConstraint.set(binaryForGroup, 1)
addExpression().lower(0).apply {
grp.forEach {
set(it.occupied,1)
}
set(binaryForGroup, -1 * blocksNeeded)
}
}
}
companion object {
val all by lazy {
ScheduledClass.all.asSequence().flatMap { sc ->
(1..sc.repetitions).asSequence()
.map { Session(sc.id, sc.name, sc.hoursLength, it, sc) }
}.toList()
}
}
}
data class OccupationState(val block: Block, val session: Session) {
val occupied = variable().binary()
companion object {
val all by lazy {
Block.all.asSequence().flatMap { b ->
Session.all.asSequence().map { OccupationState(b,it) }
}.toList()
}
}
}
fun applyConstraints() {
Session.all.forEach { it.addConstraints() }
ScheduledClass.all.forEach { it.addConstraints() }
Block.all.forEach { it.addConstraints() }
}
** UPDATE **
I created a self-contained example that simplifies what I'm trying to do above. It seems the contiguous logic is indeed the problem, and the more "slots" the problem has the slower it performs. At 48000 variables, the contiguous logic seems to churn forever.
import org.ojalgo.optimisation.ExpressionsBasedModel
import org.ojalgo.optimisation.Variable
import org.ojalgo.optimisation.integer.IntegerSolver
import java.util.concurrent.ThreadLocalRandom
import java.util.concurrent.atomic.AtomicInteger
// declare ojAlgo Model
val model = ExpressionsBasedModel()
// custom DSL for expression inputs, eliminate naming and adding
val funcId = AtomicInteger(0)
val variableId = AtomicInteger(0)
fun variable() = Variable(variableId.incrementAndGet().toString().let { "Variable$it" }).apply(model::addVariable)
fun addExpression() = funcId.incrementAndGet().let { "Func$it"}.let { model.addExpression(it) }
val letterCount = 9
val numberCount = 480
val minContiguousBlocks = 4
val maxContiguousBlocks = 4
fun main(args: Array<String>) {
Letter.all.forEach { it.addConstraints() }
Number.all.forEach { it.addConstraints() }
model.countVariables().run { println("$this variables") }
model.options.debug(IntegerSolver::class.java)
model.minimise().run(::println)
Letter.all.joinToString(prefix = "\t", separator = "\t").run(::println)
Letter.all.map { it.slotsNeeded }.joinToString(prefix = "\t", separator = "\t").run(::println)
Number.all.forEach { n ->
Letter.all.asSequence().map { l -> l.slots.first { it.number == n }.occupied.value.toInt() }
.joinToString(prefix = "$n ", separator = "\t").run { println(this) }
}
}
class Letter(val value: String, val slotsNeeded: Int = 1) {
val slots by lazy {
Slot.all.filter { it.letter == this }.sortedBy { it.number.value }
}
fun addConstraints() {
// Letter must be assigned once
addExpression().level(1).apply {
slots.forEach { set(it.occupied, 1) }
}
//handle recurrences
if (slotsNeeded > 1) {
slots.rollingBatches(slotsNeeded).forEach { batch ->
val first = batch.first()
addExpression().upper(0).apply {
batch.asSequence().flatMap { it.number.slots.asSequence() }
.forEach {
set(it.occupied, 1)
}
set(first.number.cumulativeState, -1)
}
}
}
//prevent scheduling at end of window
// all slots must sum to 0 in region smaller than slots needed
addExpression().level(0).apply {
slots.takeLast(slotsNeeded - 1)
.forEach {
set(it.occupied, 1)
}
}
}
override fun toString() = value
companion object {
val all = ('A'..'Z').asSequence()
.take(letterCount)
.map { it.toString() }
.map { Letter(it, ThreadLocalRandom.current().nextInt(minContiguousBlocks, maxContiguousBlocks + 1)) }
.toList()
}
}
class Number(val value: Int) {
val slots by lazy {
Slot.all.filter { it.number == this }
}
// b_x
val cumulativeState = variable().lower(0).upper(1)
fun addConstraints() {
// Number can only be assigned once
addExpression().upper(1).apply {
slots.forEach { set(it.occupied, 1) }
}
}
companion object {
val all = (1..numberCount).asSequence()
.map { Number(it) }
.toList()
}
override fun toString() = value.toString().let { if (it.length == 1) "$it " else it }
}
data class Slot(val letter: Letter, val number: Number) {
val occupied = variable().binary()
companion object {
val all = Letter.all.asSequence().flatMap { letter ->
Number.all.asSequence().map { number -> Slot(letter, number) }
}.toList()
}
override fun toString() = "$letter$number: ${occupied?.value?.toInt()}"
}
fun <T> List<T>.rollingBatches(batchSize: Int) = (0..size).asSequence().map { i ->
subList(i, (i + batchSize).let { if (it > size) size else it })
}.filter { it.size == batchSize }
I figured it out. I'll update this answer later with the full mathematical modeling explanation. Essentially for each 15 minute block I queried for slot groups that include that block, and declared the sum of all of them must be no more than one. This ended up being acceptably efficient as it runs in 30-60 seconds.
The code is here on GitHub, as well as below:
https://github.com/thomasnield/optimized-scheduling-demo
import org.ojalgo.optimisation.integer.IntegerSolver
import java.time.LocalDate
import java.time.LocalTime
import org.ojalgo.optimisation.ExpressionsBasedModel
import org.ojalgo.optimisation.Variable
import java.time.DayOfWeek
import java.time.LocalDateTime
import java.util.concurrent.atomic.AtomicInteger
// Any Monday through Friday date range will work
val operatingDates = LocalDate.of(2017,10,16)..LocalDate.of(2017,10,20)
val operatingDay = LocalTime.of(8,0)..LocalTime.of(17,0)
val breaks = listOf<ClosedRange<LocalTime>>(
LocalTime.of(11,30)..LocalTime.of(13,0)
)
// classes
val scheduledClasses = listOf(
ScheduledClass(id=1, name="Psych 101",hoursLength=1.0, repetitions=2),
ScheduledClass(id=2, name="English 101", hoursLength=1.5, repetitions=3),
ScheduledClass(id=3, name="Math 300", hoursLength=1.5, repetitions=2),
ScheduledClass(id=4, name="Psych 300", hoursLength=3.0, repetitions=1),
ScheduledClass(id=5, name="Calculus I", hoursLength=2.0, repetitions=2),
ScheduledClass(id=6, name="Linear Algebra I", hoursLength=2.0, repetitions=3),
ScheduledClass(id=7, name="Sociology 101", hoursLength=1.0, repetitions=2),
ScheduledClass(id=8, name="Biology 101", hoursLength=1.0, repetitions=2)
)
fun main(args: Array<String>) {
println("Job started at ${LocalTime.now()}")
applyConstraints()
model.countVariables().run { println("$this variables") }
model.options.apply {
//debug(IntegerSolver::class.java)
iterations_suffice = 0
}
println(model.minimise())
ScheduledClass.all.forEach {
println("${it.name}- ${it.daysOfWeek.joinToString("/")} ${it.start.toLocalTime()}-${it.end.toLocalTime()}")
}
println("Job ended at ${LocalTime.now()}")
}
// declare model
val model = ExpressionsBasedModel()
val funcId = AtomicInteger(0)
val variableId = AtomicInteger(0)
fun variable() = Variable(variableId.incrementAndGet().toString().let { "Variable$it" }).apply(model::addVariable)
fun addExpression() = funcId.incrementAndGet().let { "Func$it"}.let { model.addExpression(it) }
data class Block(val dateTimeRange: ClosedRange<LocalDateTime>) {
val timeRange = dateTimeRange.let { it.start.toLocalTime()..it.endInclusive.toLocalTime() }
val available get() = (breaks.all { timeRange.start !in it } && timeRange.start in operatingDay)
//val cumulativeState = variable().apply { if (available) lower(0).upper(1) else level(0) }
val slots by lazy {
Slot.all.filter { it.block == this }
}
fun addConstraints() {
if (available) {
addExpression().lower(0).upper(1).apply {
ScheduledClass.all.asSequence().flatMap { it.anchorOverlapFor(this#Block) }
.filter { it.block.available }
.forEach {
set(it.occupied, 1)
}
}
} else {
ScheduledClass.all.asSequence().flatMap { it.anchorOverlapFor(this#Block) }
.forEach {
it.occupied.level(0)
}
}
}
companion object {
// Operating blocks
val all by lazy {
generateSequence(operatingDates.start.atStartOfDay()) {
it.plusMinutes(15).takeIf { it.plusMinutes(15) <= operatingDates.endInclusive.atTime(23,59) }
}.map { Block(it..it.plusMinutes(15)) }
.toList()
}
fun applyConstraints() {
all.forEach { it.addConstraints() }
}
}
}
data class ScheduledClass(val id: Int,
val name: String,
val hoursLength: Double,
val repetitions: Int,
val repetitionGapDays: Int = 2) {
val repetitionGapSlots = repetitionGapDays * 24 * 4
val slotsNeeded = (hoursLength * 4).toInt()
val slots by lazy {
Slot.all.asSequence().filter { it.session == this }.toList()
}
val batches by lazy {
slots.rollingRecurrences(slotsNeeded = slotsNeeded, gapSize = repetitionGapSlots, recurrencesNeeded = repetitions)
}
fun anchorOverlapFor(block: Block) = batches.asSequence()
.filter { it.flatMap { it }.any { it.block == block } }
.map { it.first().first() }
val start get() = slots.asSequence().filter { it.occupied.value.toInt() == 1 }.map { it.block.dateTimeRange.start }.min()!!
val end get() = start.plusMinutes((hoursLength * 60.0).toLong())
val daysOfWeek get() = (0..(repetitions-1)).asSequence().map { start.dayOfWeek.plus(it.toLong() * repetitionGapDays) }.sorted()
fun addConstraints() {
//sum of all boolean states for this session must be 1
addExpression().level(1).apply {
slots.forEach {
set(it.occupied, 1)
}
}
//guide Mon/Wed/Fri for three repetitions
if (repetitions == 3) {
addExpression().level(1).apply {
slots.filter { it.block.dateTimeRange.start.dayOfWeek == DayOfWeek.MONDAY }
.forEach {
set(it.occupied, 1)
}
}
}
//guide two repetitions to start on Mon, Tues, or Wed
if (repetitions == 2) {
addExpression().level(1).apply {
slots.filter { it.block.dateTimeRange.start.dayOfWeek in DayOfWeek.MONDAY..DayOfWeek.WEDNESDAY }.forEach {
set(it.occupied, 1)
}
}
}
}
companion object {
val all by lazy { scheduledClasses }
}
}
data class Slot(val block: Block, val session: ScheduledClass) {
val occupied = variable().apply { if (block.available) binary() else level(0) }
companion object {
val all by lazy {
Block.all.asSequence().flatMap { b ->
ScheduledClass.all.asSequence().map { Slot(b,it) }
}.toList()
}
}
}
fun applyConstraints() {
Block.applyConstraints()
ScheduledClass.all.forEach { it.addConstraints() }
}
fun <T> List<T>.rollingBatches(batchSize: Int) = (0..size).asSequence().map { i ->
subList(i, (i + batchSize).let { if (it > size) size else it })
}.filter { it.size == batchSize }
fun <T> List<T>.rollingRecurrences(slotsNeeded: Int, gapSize: Int, recurrencesNeeded: Int) =
(0..size).asSequence().map { i ->
(1..recurrencesNeeded).asSequence().map { (it - 1) * gapSize }
.filter { it + i < size}
.map { r ->
subList(i + r, (i + r + slotsNeeded).let { if (it > size) size else it })
}.filter { it.size == slotsNeeded }
.toList()
}.filter { it.size == recurrencesNeeded }