--- a/testing1/alcohol.scala Wed Nov 29 21:22:29 2017 +0000
+++ b/testing1/alcohol.scala Sun Dec 03 21:11:49 2017 +0000
@@ -6,66 +6,93 @@
import io.Source
import scala.util._
-def get_csv_page(url: String) : List[String] =
- Source.fromURL(url)("ISO-8859-1").getLines.toList
-
-def get_csv_file(file: String) : List[String] =
- Source.fromFile(file)("ISO-8859-1").getLines.toList
-
-
-val url_alcohol =
+val url_alcohol =
"https://raw.githubusercontent.com/fivethirtyeight/data/master/alcohol-consumption/drinks.csv"
-val file_population =
+val file_population =
"population.csv"
-get_csv_page(url_alcohol)
-get_csv_file(file_population)
-get_csv_page(url_alcohol).size
-get_csv_file(file_population).size
-
-val alcs = get_csv_page(url_alcohol)
-val pops = get_csv_file(file_population)
+//(1) Complete the get_csv_page function below. It takes a URL-string
+// as argument and generates a list of strings corresponding to each
+// line in the downloaded csv-list. The URL url_alcohol above is one
+// possible argument.
-def process_alcs(lines: List[String]) : List[(String, Double)] =
- for (l <- lines) yield {
- val entries = l.split(",").toList
- (entries(0), entries(4).toDouble)
- }
-
-def process_pops(lines: List[String]) : Map[String, Long] =
- (for (l <- lines) yield {
- val entries = l.split(",").toList
- (entries(0), entries(1).toLong)
- }).toMap
-
+//def get_csv_page(url: String) : List[String] = ...
+def get_csv_page(url: String) : List[String] = {
+ val csv = Source.fromURL(url)
+ val contents = csv.mkString.split("\n")
+ contents.toList
+}
+// Complete the get_csv_file function below. It takes a file name
+// as argument and reads the content of the given file. Like above,
+// it should generate a list of strings corresponding to each
+// line in the csv-list. The filename file_population is one possible
+// argument.
-process_alcs(alcs.drop(1))(1)
-process_pops(pops.drop(1))("Albania")
-
-def sorted_country_consumption() : List[(String, Long)] = {
- val alcs2 = process_alcs(alcs.drop(1))
- val pops2 = process_pops(pops.drop(1))
- val cons_list =
- for ((cname, cons) <- alcs2;
- if pops2.isDefinedAt(cname)) yield (cname, (cons * pops2(cname)).toLong)
- cons_list.sortBy(_._2).reverse
+//def get_csv_file(file: String) : List[String] = ...
+def get_csv_file(file: String) : List[String] = {
+ val csv = Source.fromFile(file)
+ val contents = csv.mkString.split("\n")
+ contents.toList
}
-
-sorted_country_consumption().take(10)
-sorted_country_consumption().size
+//(2) Complete the functions that process the csv-lists. For
+// process_alcs extract the country name (as String) and the
+// pure alcohol consumption (as Double). For process_pops
+// generate a Map of Strings (country names) to Long numbers
+// (population sizes).
-def percentage(n: Int) : (Long, Long, Double) = {
- val cons_list = sorted_country_consumption()
- val sum_n = cons_list.take(n).map(_._2).sum
- val sum_all = cons_list.map(_._2).sum
- val perc = (sum_n.toDouble / sum_all.toDouble) * 100.0
- (sum_all, sum_n, perc)
+//def process_alcs(lines: List[String]) : List[(String, Double)] = ...
+def process_alcs(lines: List[String]) : List[(String, Double)] = {
+ val beheaded = lines.drop(1)
+ val splitEntries = for (n <- beheaded) yield n.split(",").toList
+ for (n <- splitEntries) yield (n.take(1).mkString, n.drop(4).mkString.toDouble)
+}
+//def process_pops(lines: List[String]) : Map[String, Long] = ...
+def process_pops(lines: List[String]) : Map[String, Long] = {
+ val beheaded = lines.drop(1);
+ def toOnePair(line: String) : (String, Long) = {
+ val splitAsList = line.split(",").toList
+ (splitAsList.take(1).mkString, splitAsList.drop(1).mkString.toLong)
+ }
+ val splitEntries = for (n <- beheaded) yield toOnePair(n)
+ splitEntries.toMap
}
-percentage(10)
-percentage(164)
+//(3) Calculate for each country the overall alcohol_consumption using
+// the data from the alcohol list and the population sizes list. You
+// should only include countries on the alcohol list that are also
+// on the population sizes list with the exact same name. Note that
+// the spelling of some names in the alcohol list differs from the
+// population sizes list. You can ignore entries where the names differ.
+// Sort the resulting list according to the country with the highest alcohol
+// consumption to the country with the lowest alcohol consumption.
+//def sorted_country_consumption() : List[(String, Long)] = ...
+def sorted_country_consumption() : List[(String, Long)] = {
+ val countryToPop = process_pops(get_csv_file(file_population))
+ val countryAndAlc = process_alcs(get_csv_page(url_alcohol))
+ val countryAndConsumption = countryAndAlc.collect {
+ case oneCountryAndAlc
+ if countryToPop.isDefinedAt(oneCountryAndAlc._1) =>
+ (oneCountryAndAlc._1, (oneCountryAndAlc._2*countryToPop.get(oneCountryAndAlc._1).get).toLong)
+ }
+ countryAndConsumption.sortWith(_._2 > _._2)
}
+
+// Calculate the world consumption of pure alcohol of all countries, which
+// should be the first element in the tuple below. The second element is
+// the overall consumption of the first n countries in the sorted list
+// from above; and finally the double should be the percentage of the
+// first n countries drinking from the the world consumption of alcohol.
+
+//def percentage(n: Int) : (Long, Long, Double) = ...
+def percentage(n: Int) : (Long, Long, Double) = {
+ val ctryConsump = sorted_country_consumption()
+ val totalAlc = ctryConsump.map(_._2).sum
+ val firstNAlc = ctryConsump.take(n).map(_._2).sum
+ val pcntage = (firstNAlc*1.0/totalAlc)*100;
+ (ctryConsump.map(_._2).sum, ctryConsump.take(n).map(_._2).sum, pcntage)
+}
+}
--- a/testing1/drumb.scala Wed Nov 29 21:22:29 2017 +0000
+++ b/testing1/drumb.scala Sun Dec 03 21:11:49 2017 +0000
@@ -1,4 +1,4 @@
-// Advanvced Part 3 about a really dumb investment strategy
+// Advanced Part 3 about a really dumb investment strategy
//==========================================================
object CW6c {
@@ -7,131 +7,110 @@
//two test portfolios
val blchip_portfolio = List("GOOG", "AAPL", "MSFT", "IBM", "FB", "AMZN", "BIDU")
-val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI",
- "DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "GGP", "HCP")
+val rstate_portfolio = List("PLD", "PSA", "AMT", "AIV", "AVB", "BXP", "CCI","DLR", "EQIX", "EQR", "ESS", "EXR", "FRT", "GGP", "HCP")
-// (1) The function below should obtain the first trading price
-// for a stock symbol by using the query
-//
-// http://ichart.yahoo.com/table.csv?s=<<symbol>>&a=0&b=1&c=<<year>>&d=1&e=1&f=<<year>>
-//
-// and extracting the first January Adjusted Close price in a year.
-
+// (1.a) The function below takes a stock symbol and a year as arguments.
+// It should read the corresponding CSV-file and read the January
+// data from the given year. The data should be collected in a list of
+// strings for each line in the CSV-file.
import io.Source
import scala.util._
-def get_january_data(symbol: String, year: Int) : List[String] =
- Source.fromFile(symbol ++ ".csv")("ISO-8859-1").getLines.toList.filter(_.startsWith(year.toString))
+def get_january_data(symbol: String, year: Int) : List[String] = {
+ val file = symbol + ".csv"
+ val list = scala.io.Source.fromFile(file).mkString.split("\n").toList
+ val rx = (year.toString + ".*")
+ (for(n <- 1 to list.length -1 if(list(n) matches rx)) yield list(n)).toList
+}
+
+
+// (1.b) From the output of the get_january_data function, the next function
+// should extract the first line (if it exists) and the corresponding
+// first trading price in that year as Option[Double]. If no line is
+// generated by get_january_data then the result is None
def get_first_price(symbol: String, year: Int) : Option[Double] = {
- val data = Try(Some(get_january_data(symbol, year).head)) getOrElse None
- data.map(_.split(",").toList(1).toDouble)
+ val first_line = get_january_data(symbol, year)
+
+ if(first_line.length == 0 ){
+ None
+ } else {
+ Option((first_line(0).split(",")(1)).toDouble)
+ }
}
-get_first_price("GOOG", 1980)
-get_first_price("GOOG", 2010)
-get_first_price("FB", 2014)
-
-// Complete the function below that obtains all first prices
-// for the stock symbols from a portfolio for the given
-// range of years
-
-def get_prices(portfolio: List[String], years: Range): List[List[Option[Double]]] =
- for (year <- years.toList) yield
- for (symbol <- portfolio) yield get_first_price(symbol, year)
+// (1.c) Complete the function below that obtains all first prices
+// for the stock symbols from a portfolio (list of strings) and
+// for the given range of years. The inner lists are for the
+// stock symbols and the outer list for the years.
-// test case
-val p_fb = get_prices(List("FB"), 2012 to 2014)
-val p = get_prices(List("GOOG", "AAPL"), 2010 to 2012)
+def get_prices(portfolio: List[String], years: Range) : List[List[Option[Double]]] ={
+ (for(y <- years) yield (for(n <- 0 to portfolio.length-1) yield get_first_price(portfolio(n), y)).toList).toList
+}
+
-val tt = get_prices(List("BIDU"), 2004 to 2008)
-// (2) The first function below calculates the change factor (delta) between
-// a price in year n and a price in year n+1. The second function calculates
-// all change factors for all prices (from a portfolio).
+// (2) The first function below calculates the change factor (dta) between
+// a price in year n and a price in year n + 1. The second function calculates
+// all change factors for all prices (from a portfolio). The input to this
+// function are the nested lists created by get_prices above.
def get_delta(price_old: Option[Double], price_new: Option[Double]) : Option[Double] = {
- (price_old, price_new) match {
- case (Some(x), Some(y)) => Some((y - x) / x)
- case _ => None
- }
+ for( x <- price_old; y <- price_new) yield (y-x)/x
}
-def get_deltas(data: List[List[Option[Double]]]): List[List[Option[Double]]] =
- for (i <- (0 until (data.length - 1)).toList) yield
- for (j <- (0 until (data(0).length)).toList) yield get_delta(data(i)(j), data(i + 1)(j))
+def get_deltas(data: List[List[Option[Double]]]) : List[List[Option[Double]]] = {
+ (for( n <- 1 to data.length-1) yield (for(i <- 0 to data(n).length-1) yield get_delta(data(n-1)(i), data(n)(i))).toList).toList
+}
-// test case using the prices calculated above
-val d = get_deltas(p)
-val ttd = get_deltas(tt)
// (3) Write a function that given change factors, a starting balance and a year
-// calculates the yearly yield, i.e. new balanace, according to our dump investment
-// strategy. Another function calculates given the same data calculates the
-// compound yield up to a given year. Finally a function combines all
-// calculations by taking a portfolio, a range of years and a start balance
-// as arguments.
+// calculates the yearly yield, i.e. new balance, according to our dump investment
+// strategy. Another function calculates given the same data calculates the
+// compound yield up to a given year. Finally a function combines all
+// calculations by taking a portfolio, a range of years and a start balance
+// as arguments.
-def yearly_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = {
- val somes = data(year).flatten
- val somes_length = somes.length
- if (somes_length == 0) balance
- else {
- val portion: Double = balance.toDouble / somes_length.toDouble
- balance + (for (x <- somes) yield (x * portion)).sum.toLong
- }
-}
-
-def compound_yield(data: List[List[Option[Double]]], balance: Long, year: Int): Long = {
- if (year >= data.length) balance else {
- val new_balance = yearly_yield(data, balance, year)
- compound_yield(data, new_balance, year + 1)
- }
+def yearly_yield(data: List[List[Option[Double]]], balance: Long, year: Int) : Long = {
+ val increments = (for(n <- 0 to data(year).length-1 if(!(data(year)(n) == None))) yield (data(year)(n).getOrElse(0.0))).toList
+ val sumi = (increments.sum).toDouble
+ if(increments.length == 0){
+ balance
+ }else{
+ val il = (increments.length).toDouble
+ val averag = sumi/il
+ val i = (balance + (balance*averag))
+ i.toLong
+ }
}
-//yearly_yield(d, 100, 0)
-//compound_yield(d.take(6), 100, 0)
-
-//test case
-//yearly_yield(d, 100, 0)
-//yearly_yield(d, 225, 1)
-//yearly_yield(d, 246, 2)
-//yearly_yield(d, 466, 3)
-//yearly_yield(d, 218, 4)
-
-//yearly_yield(d, 100, 0)
-//yearly_yield(d, 125, 1)
-
-def investment(portfolio: List[String], years: Range, start_balance: Long): Long = {
- compound_yield(get_deltas(get_prices(portfolio, years)), start_balance, 0)
+def compound_yield(data: List[List[Option[Double]]], balance: Long, ye: Int) : Long = {//if(year == 0) yearly_yield(data, balance, 0) else compound_yield(data, yearly_yield(data, balance, year), year-1)
+ val increments_py = (for(year <- 0 to ye) yield {
+ val increments = (for(n <- 0 to data(year).length-1 if(!(data(year)(n) == None))) yield (data(year)(n).getOrElse(0.0))).toList
+ val sum_of = (increments.sum).toDouble
+ val number_of = (increments.length).toDouble
+ sum_of/number_of + 1.0
+ }).toList
+ val mul_factor = increments_py.reduceLeft(_*_)
+ (balance*mul_factor).toLong
+}
+def investment(portfolio: List[String], years: Range, start_balance: Long) : Long = {
+ val p = get_prices(portfolio, years)
+ val d = get_deltas(p)
+ compound_yield(d, start_balance, d.length-1)
}
-val one = get_deltas(get_prices(rstate_portfolio, 1978 to 1984))
-val two = get_deltas(get_prices(blchip_portfolio, 1978 to 1984))
-val one_full = get_deltas(get_prices(rstate_portfolio, 1978 to 2017))
-val two_full = get_deltas(get_prices(blchip_portfolio, 1978 to 2017))
-
-one_full.map(_.flatten).map(_.sum).sum
-two_full.map(_.flatten).map(_.sum).sum
//test cases for the two portfolios given above
-//println("Real data: " + investment(rstate_portfolio, 1978 to 1981, 100))
-//println("Blue data: " + investment(blchip_portfolio, 1978 to 1981, 100))
+investment(rstate_portfolio, 1978 to 2017, 100)
+investment(blchip_portfolio, 1978 to 2017, 100)
-//for (i <- 1978 to 2017) {
-// println("Year " + i)
-// println("Real data: " + investment(rstate_portfolio, 1978 to i, 100))
-// println("Blue data: " + investment(blchip_portfolio, 1978 to i, 100))
-//}
-
-//1984
-//1992
}
--- a/testing2/knight3.scala Wed Nov 29 21:22:29 2017 +0000
+++ b/testing2/knight3.scala Sun Dec 03 21:11:49 2017 +0000
@@ -1,45 +1,96 @@
-import scala.annotation.tailrec
+// Part 3 about finding a single tour using the Warnsdorf Rule
+//=============================================================
+
object CW7c {
-type Pos = (Int, Int) // a position on a chessboard
-type Path = List[Pos] // a path...a list of positions
+
+type Pos = (Int, Int)
+type Path = List[Pos]
-def is_legal(dim: Int, path: Path)(x: Pos) : Boolean = {
- if((x._1 >= 0) && (x._2 >= 0) && (x._1 < dim) && (x._2 < dim)){
- !(path.contains(x))
- } else false
- }
-
-def legal_moves(dim: Int, path: Path, x: Pos) : List[Pos] = {
- val lst = List( (1,2),(2,1),(2,-1),(1,-2), (-1,-2),(-2,-1),(-2,1),(-1,2) )
- val mapping = lst.map(s => ( s._1 + x._1, s._2 + x._2) )
- for( i <- mapping if ( is_legal(dim,path)(i) )) yield i
- }
-
-def ordered_moves(dim: Int, path: Path, x: Pos) : List[Pos] = {
-legal_moves(dim,path,x).sortBy(legal_moves(dim,path,_).length )
+def print_board(dim: Int, path: Path): Unit = {
+ println
+ for (i <- 0 until dim) {
+ for (j <- 0 until dim) {
+ print(f"${path.reverse.indexOf((i, j))}%3.0f ")
+ }
+ println
+ }
}
-def first(xs: List[Pos], f: Pos => Option[Path]) : Option[Path] ={
- if(xs.isEmpty)
- None
- else {
- val b = f(xs.head)
- if (b!=None)
- b
- else
- first(xs.tail,f)
- }
+def add_pair(x: Pos)(y: Pos): Pos =
+ (x._1 + y._1, x._2 + y._2)
+
+def is_legal(dim: Int, path: Path)(x: Pos): Boolean =
+ 0 <= x._1 && 0 <= x._2 && x._1 < dim && x._2 < dim && !path.contains(x)
+
+def moves(x: Pos): List[Pos] =
+ List(( 1, 2),( 2, 1),( 2, -1),( 1, -2),
+ (-1, -2),(-2, -1),(-2, 1),(-1, 2)).map(add_pair(x))
+
+def legal_moves(dim: Int, path: Path, x: Pos): List[Pos] =
+ moves(x).filter(is_legal(dim, path))
+
+def ordered_moves(dim: Int, path: Path, x: Pos): List[Pos] =
+ legal_moves(dim, path, x).sortBy((x) => legal_moves(dim, path, x).length)
+
+
+import scala.annotation.tailrec
+
+@tailrec
+def first(xs: List[Pos], f: Pos => Option[Path]): Option[Path] = xs match {
+ case Nil => None
+ case x::xs => {
+ val result = f(x)
+ if (result.isDefined) result else first(xs, f)
}
-
-def first_closed_tour_heuristic(dim: Int, path: Path) : Option[Path] = {
- if (dim < 5) None
- else
- if(path.length==dim*dim) Some(path)
- else
- first(ordered_moves(dim,path,path.head),y => first_closed_tour_heuristic(dim, y::path))
- }
-
}
-first_closed_tour_heuristic(6, List((3, 3)))
+def first_closed_tour_heuristic(dim: Int, path: Path): Option[Path] = {
+ if (path.length == dim * dim && moves(path.head).contains(path.last)) Some(path)
+ else
+ first(ordered_moves(dim, path, path.head), (x: Pos) => first_closed_tour_heuristic(dim, x::path))
+}
+
+/*
+for (dim <- 1 to 6) {
+ val t = first_closed_tour_heuristic(dim, List((dim / 2, dim / 2)))
+ println(s"${dim} x ${dim} closed: " + (if (t == None) "" else { print_board(dim, t.get) ; "" }))
+}*/
+
+
+def first_tour_heuristic(dim: Int, path: Path): Option[Path] = {
+
+ @tailrec
+ def aux(dim: Int, path: Path, moves: List[Pos]): Option[Path] =
+ if (path.length == dim * dim) Some(path)
+ else
+ moves match {
+ case Nil => None
+ case x::xs => {
+ val r = first_tour_heuristic(dim, x::path)
+ if (r.isDefined) r else aux(dim, path, xs)
+ }
+ }
+
+ aux(dim, path, ordered_moves(dim, path, path.head))
+}
+
+/*
+def first_tour_heuristic(dim: Int, path: Path): Option[Path] = {
+ if (path.length == dim * dim) Some(path)
+ else
+ first(ordered_moves(dim, path, path.head), (x: Pos) => first_tour_heuristic(dim, x::path))
+}
+*/
+
+/*
+for (dim <- 1 to 50) {
+ val t = first_tour_heuristic(dim, List((dim / 2, dim / 2)))
+ println(s"${dim} x ${dim}: " + (if (t == None) "" else { print_board(dim, t.get) ; "" }))
+}
+*/
+
+}
+
+
+//CW7c.first_tour_heuristic(50, List((0,0))).get
--- a/testing3/bf.scala Wed Nov 29 21:22:29 2017 +0000
+++ b/testing3/bf.scala Sun Dec 03 21:11:49 2017 +0000
@@ -49,6 +49,7 @@
}
+
// (2c) Complete the run function that interpretes (runs) a brainf***
// program: the arguments are a program, a program counter,
// a memory counter and a brainf*** memory. It Returns the