src/com/flaremicro/visualforecast/datamart/CanadaDatamartProvider.java

@@ -67,9 +67,23 @@ public class CanadaDatamartProvider extends ForecastProvider {
 					String code = data[0].trim();
 					String town = data[1].trim();
 					String province = data[2].trim();
+					String supportedDisplaysString = propertyManager.getStringNoSet("displays-enabled.code."+code, "");
+					if(supportedDisplaysString.trim().length() <= 0)
+						supportedDisplaysString = propertyManager.getString("displays-enabled.town."+town.toLowerCase().replaceAll("\\s", "_")+"."+province.toLowerCase().replace("\\s", "_"), "");
+					
 					float latitude = Float.parseFloat(data[3].trim().substring(0, data[3].length()-1));
 					float longitude = Float.parseFloat(data[4].trim().substring(0, data[4].length()-1));
-					towns.add(new TownInfo(code, town, province, latitude, longitude, priority));
+					TownInfo townInfo = new TownInfo(code, town, province, latitude, longitude, priority);
+					if(supportedDisplaysString.trim().length() > 0)
+					{
+						String[] displays = supportedDisplaysString.split(",");
+						for(int i = 0; i < displays.length; i++)
+						{
+							displays[i] = displays[i].trim();
+						}
+						townInfo.setSupportedDisplays(displays);
+					}
+					towns.add(townInfo);
 				}
 			}
 		}

src/com/flaremicro/visualforecast/datamart/DatamartTranslation.java

@@ -4,6 +4,7 @@ import java.io.BufferedReader;
 import java.io.IOException;
 import java.io.InputStreamReader;
 import java.util.HashMap;
+import java.util.Map;
 
 import com.flaremicro.util.Util;
 import com.flaremicro.visualforecast.icons.IconProvider;
@@ -12,6 +13,7 @@ public class DatamartTranslation {
 
 	private HashMap<Integer, Byte> iconTranslation = new HashMap<Integer, Byte>();
 	private HashMap<String, WeatherLines> stringTranslation = new HashMap<String, WeatherLines>();
+	private HashMap<String, WeatherLines> fallBacks = new HashMap<String, WeatherLines>();
 
 	public DatamartTranslation() {
 		iconTranslation.put(0, IconProvider.SUN.id);
@@ -71,10 +73,12 @@ public class DatamartTranslation {
 				if (info.length == 2)
 				{
 					stringTranslation.put(info[0].toLowerCase(), new WeatherLines(info[1], ""));
+					fallBacks.put(info[1], new WeatherLines(info[1], ""));
 				}
 				else if (info.length == 3)
 				{
 					stringTranslation.put(info[0].toLowerCase(), new WeatherLines(info[1], info[2]));
+					fallBacks.put(info[1] + " " + info[2], new WeatherLines(info[1], info[2]));
 				}
 			}
 		}
@@ -100,10 +104,154 @@ public class DatamartTranslation {
 		if (lines == null)
 		{
 			System.out.println("FAILED:" + desc.toLowerCase());
-			return new WeatherLines("TRANSLAT.", "FAILURE");
+			return getClosestMatching(desc);
 		}
 		else return lines;
 	}
+
+	public WeatherLines getClosestMatching(String desc) {
+		WeatherLines bestMatch = new WeatherLines("TRANSLAT.", "FAILURE");
+		desc = desc.toLowerCase();
+		double bestRatio = Integer.MAX_VALUE;
+		for (Map.Entry<String, WeatherLines> set : fallBacks.entrySet())
+		{
+			double ratio2 = getLevenshteinDistance(desc, set.getKey());
+			if (ratio2 < bestRatio)
+			{
+				bestRatio = ratio2;
+				bestMatch = set.getValue();
+			}
+		}
+		System.out.println("Got " + bestMatch.line1 + " " + bestMatch.line2 + " for desc " + desc);
+		return bestMatch;
+	}
+
+	public static int getLevenshteinDistance(CharSequence s, CharSequence t) {
+		if (s == null || t == null)
+		{
+			throw new IllegalArgumentException("Strings must not be null");
+		}
+		int n = s.length();
+		int m = t.length();
+
+		if (n == 0)
+		{
+			return m;
+		}
+		else if (m == 0)
+		{
+			return n;
+		}
+
+		if (n > m)
+		{
+			// swap the input strings to consume less memory
+			final CharSequence tmp = s;
+			s = t;
+			t = tmp;
+			n = m;
+			m = t.length();
+		}
+
+		final int[] p = new int[n + 1];
+		// indexes into strings s and t
+		int i; // iterates through s
+		int j; // iterates through t
+		int upper_left;
+		int upper;
+
+		char t_j; // jth character of t
+		int cost;
+
+		for (i = 0; i <= n; i++)
+		{
+			p[i] = i;
+		}
+
+		for (j = 1; j <= m; j++)
+		{
+			upper_left = p[0];
+			t_j = t.charAt(j - 1);
+			p[0] = j;
+
+			for (i = 1; i <= n; i++)
+			{
+				upper = p[i];
+				cost = s.charAt(i - 1) == t_j ? 0 : 1;
+				// minimum of cell to the left+1, to the top+1, diagonally left and up +cost
+				p[i] = Math.min(Math.min(p[i - 1] + 1, p[i] + 1), upper_left + cost);
+				upper_left = upper;
+			}
+		}
+
+		return p[n];
+	}
+
+	double findSimilarityRatio(String sentence1, String sentence2) {
+
+		HashMap<String, Integer> firstSentenceMap = new HashMap<String, Integer>();
+		HashMap<String, Integer> secondSentenceMap = new HashMap<String, Integer>();
+
+		String[] firstSentenceWords = sentence1.split(" ");
+		String[] secondSentenceWords = sentence2.split(" ");
+
+		for (String word : firstSentenceWords)
+		{
+			if (firstSentenceMap.containsKey(word))
+			{
+				firstSentenceMap.put(word, firstSentenceMap.get(word) + 1);
+			}
+			else
+			{
+				firstSentenceMap.put(word, 1);
+			}
+		}
+
+		for (String word : secondSentenceWords)
+		{
+			if (secondSentenceMap.containsKey(word))
+			{
+				secondSentenceMap.put(word, secondSentenceMap.get(word) + 1);
+			}
+			else
+			{
+				secondSentenceMap.put(word, 1);
+			}
+		}
+
+		double totalWords = 0;
+		double totalHits = 0;
+
+		if (firstSentenceWords.length >= secondSentenceWords.length)
+		{
+			totalWords = firstSentenceWords.length;
+			for (Map.Entry<String, Integer> entry : firstSentenceMap.entrySet())
+			{
+				String key = entry.getKey();
+
+				if (secondSentenceMap.containsKey(key))
+				{
+					totalHits = totalHits + Math.min(secondSentenceMap.get(key), firstSentenceMap.get(key));
+				}
+			}
+		}
+		else
+		{
+			totalWords = secondSentenceWords.length;
+			for (Map.Entry<String, Integer> entry : secondSentenceMap.entrySet())
+			{
+				String key = entry.getKey();
+
+				if (firstSentenceMap.containsKey(key))
+				{
+					totalHits = totalHits + Math.min(secondSentenceMap.get(key), firstSentenceMap.get(key));
+				}
+			}
+
+		}
+
+		return totalHits / totalWords;
+	}
 }
 
 class WeatherLines {

src/com/flaremicro/visualforecast/datamart/ForecastProcessor.java

@@ -11,7 +11,6 @@ import java.util.Calendar;
 import java.util.Date;
 import java.util.Locale;
 import java.util.TimeZone;
-import java.util.concurrent.TimeUnit;
 
 import javax.xml.XMLConstants;
 import javax.xml.parsers.DocumentBuilder;
@@ -26,6 +25,7 @@ import org.xml.sax.SAXException;
 
 import com.flaremicro.util.Util;
 import com.flaremicro.visualforecast.forecast.DayForecast;
+import com.flaremicro.visualforecast.forecast.DetailedForecast;
 import com.flaremicro.visualforecast.forecast.ForecastDetails;
 import com.flaremicro.visualforecast.forecast.HourlyForecast;
 import com.flaremicro.visualforecast.forecast.TownForecast;
@@ -77,7 +77,7 @@ public class ForecastProcessor implements Runnable {
 		return -1;
 	}
 
-	public void processHourlyForecast(TownForecast forecast, Document doc) {
+	public HourlyForecast[] processHourlyForecast(Document doc) {
 		DateFormat dateFormat = new SimpleDateFormat("yyyyMMddHHmm");
 		dateFormat.setTimeZone(TimeZone.getTimeZone("UTC"));
 		NodeList hourlyForecast = doc.getElementsByTagName("hourlyForecast");
@@ -106,7 +106,7 @@ public class ForecastProcessor implements Runnable {
 				}
 			}
 		}
-		forecast.setHourlyForecast(hourlyForecastArray.toArray(new HourlyForecast[0]));
+		return hourlyForecastArray.toArray(new HourlyForecast[0]);
 	}
 
 	public void processForecasts() {
@@ -115,7 +115,6 @@ public class ForecastProcessor implements Runnable {
 		ArrayList<TownForecast> townForecasts = new ArrayList<TownForecast>();
 		for (TownInfo townInfo : towns)
 		{
-			DayForecast[] dayForecasts = new DayForecast[8];
 			InputStream is = null;
 			Document doc = null;
 			try
@@ -145,6 +144,41 @@ public class ForecastProcessor implements Runnable {
 
 			if (doc != null)
 			{
+				TownForecast tf = new TownForecast(townInfo.townName + ", " + townInfo.province, process7DayForecast(doc));
+				townForecasts.add(tf);
+				tf.setHourlyForecast(this.processHourlyForecast(doc));
+				tf.setDetailedForecast(process36HourForecast(doc));
+				tf.setSupportedDisplays(townInfo.getSupportedDisplays());
+			}
+		}
+		
+		forecastDetails.setTownForecast(townForecasts.toArray(new TownForecast[0]));
+		setMostRecentForecast(forecastDetails);
+	}
+	
+	private DetailedForecast[] process36HourForecast(Document doc)
+	{
+		DetailedForecast[] detailedForecast = new DetailedForecast[3];
+		NodeList nodeList = doc.getElementsByTagName("forecast");
+		for (int i = 0; i < Math.min(detailedForecast.length, nodeList.getLength()); i++)
+		{
+			if (nodeList.item(1).getNodeType() == Node.ELEMENT_NODE)
+			{
+				if (nodeList.item(1).getNodeType() == Node.ELEMENT_NODE)
+				{
+					Element node = (Element) nodeList.item(i);
+					String title = XMLUtils.getStringFromTagAttribute(node, "period", "textForecastName");
+					String textForecast = XMLUtils.getStringFromTag(node, "textSummary");
+					detailedForecast[i] = new DetailedForecast(title, textForecast);
+				}
+			}
+		}
+		return detailedForecast;
+	}
+	
+	private DayForecast[] process7DayForecast(Document doc)
+	{
+		DayForecast[] dayForecasts = new DayForecast[8];
 		NodeList nodeList = doc.getElementsByTagName("forecast");
 		for (int i = 0; i < nodeList.getLength(); i++)
 		{
@@ -224,25 +258,21 @@ public class ForecastProcessor implements Runnable {
 				dayForecasts[i] = new DayForecast();
 			}
 		}
-				TownForecast tf = new TownForecast(townInfo.townName + ", " + townInfo.province, dayForecasts);
-				townForecasts.add(tf);
-				this.processHourlyForecast(tf, doc);
-			}
-		}
-		forecastDetails.setTownForecast(townForecasts.toArray(new TownForecast[0]));
-		setMostRecentForecast(forecastDetails);
+		return dayForecasts;
 	}
 
 	public void begin() {
 		if (!running)
 		{
 			running = true;
-			new Thread(this).start();
+			self = new Thread(this);
+			self.start();
 		}
 	}
 
 	public void end() {
 		running = false;
+		if(self != null)
 			self.interrupt();
 	}
 
@@ -262,7 +292,6 @@ public class ForecastProcessor implements Runnable {
 
 	@Override
 	public void run() {
-		self = Thread.currentThread();
 		while (running)
 		{
 			try

src/com/flaremicro/visualforecast/datamart/TownInfo.java

@@ -1,5 +1,11 @@
 package com.flaremicro.visualforecast.datamart;
 
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.Collections;
+import java.util.HashSet;
+import java.util.Set;
+
 public class TownInfo implements Comparable<TownInfo> {
 	public final String code;
 	public final String townName;
@@ -7,6 +13,7 @@ public class TownInfo implements Comparable<TownInfo> {
 	public final float northLat;
 	public final float westLong;
 	public final int priority;
+	private Set<String> displays = new HashSet<String>();
 	
 	public TownInfo(String code, String townName, String province, float northLat, float westLong, int priority) {
 		this.code = code;
@@ -21,4 +28,24 @@ public class TownInfo implements Comparable<TownInfo> {
 	public int compareTo(TownInfo o) {
 		return priority - o.priority;
 	}
+	
+	public void addSupportedDisplay(String display)
+	{
+		this.displays.add(display);
+	}
+	
+	public void setSupportedDisplays(String ... displays){
+		setSupportedDisplays(Arrays.asList(displays));
+	}
+	
+	public void setSupportedDisplays(Collection<String> displays){
+		this.displays.clear();
+		this.displays.addAll(displays);
+	}
+	
+	public Set<String> getSupportedDisplays()
+	{
+		return Collections.unmodifiableSet(displays);
+	}
+
 }

src/translation.csv

@@ -14,10 +14,11 @@ partly cloudy,Partly,Cloudy,
 showers or drizzle,Showers/,Drizzle
 Chance of showers,Chance,Showers
 A few showers,Few,Showers
+chance of drizzle,Chance,Drizzle
 Chance of drizzle or rain,Chance,Drizzle
 A few flurries or rain showers,Flurries/,Showers
 Chance of flurries or rain showers,Flurries/,Showers
-Chance of rain showers or flurries,Showers/Flurries
+Chance of rain showers or flurries,Showers/,Flurries
 chance of rain showers or wet flurries,Showers/,Flurries
 A few flurries,Flurries,
 Chance of flurries,Chance,Flurries
@@ -34,6 +35,7 @@ Overcast,Overcast,
 Showers,Showers,
 Chance of showers,Chance,Showers
 Periods of rain,Scattered,Rain
+Periods of drizzle,Scattered,Rain
 Mostly Cloudy,Mostly,Cloudy
 Rain at times heavy,Heavy,Rain
 A few showers or drizzle,Drizzle
@@ -102,3 +104,4 @@ Snow and blowing snow,Blowing,Snow
 Windy,Windy
 Smoke,Smoke
 rain showers or flurries,Showers/,Flurries
+chance of wet flurries,Wet,Flurries