Merge pull request 'A lot' (#1) from feature/current_conditions into master
Reviewed-on: #1
This commit is contained in:
@@ -67,9 +67,23 @@ public class CanadaDatamartProvider extends ForecastProvider {
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String code = data[0].trim();
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String town = data[1].trim();
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String province = data[2].trim();
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String supportedDisplaysString = propertyManager.getStringNoSet("displays-enabled.code."+code, "");
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if(supportedDisplaysString.trim().length() <= 0)
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supportedDisplaysString = propertyManager.getString("displays-enabled.town."+town.toLowerCase().replaceAll("\\s", "_")+"."+province.toLowerCase().replace("\\s", "_"), "");
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float latitude = Float.parseFloat(data[3].trim().substring(0, data[3].length()-1));
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float longitude = Float.parseFloat(data[4].trim().substring(0, data[4].length()-1));
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towns.add(new TownInfo(code, town, province, latitude, longitude, priority));
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TownInfo townInfo = new TownInfo(code, town, province, latitude, longitude, priority);
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if(supportedDisplaysString.trim().length() > 0)
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{
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String[] displays = supportedDisplaysString.split(",");
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for(int i = 0; i < displays.length; i++)
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{
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displays[i] = displays[i].trim();
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}
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townInfo.setSupportedDisplays(displays);
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}
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towns.add(townInfo);
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}
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}
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}
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@@ -4,6 +4,7 @@ import java.io.BufferedReader;
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import java.io.IOException;
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import java.io.InputStreamReader;
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import java.util.HashMap;
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import java.util.Map;
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import com.flaremicro.util.Util;
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import com.flaremicro.visualforecast.icons.IconProvider;
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@@ -12,6 +13,7 @@ public class DatamartTranslation {
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private HashMap<Integer, Byte> iconTranslation = new HashMap<Integer, Byte>();
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private HashMap<String, WeatherLines> stringTranslation = new HashMap<String, WeatherLines>();
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private HashMap<String, WeatherLines> fallBacks = new HashMap<String, WeatherLines>();
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public DatamartTranslation() {
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iconTranslation.put(0, IconProvider.SUN.id);
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@@ -65,16 +67,18 @@ public class DatamartTranslation {
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{
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reader = new BufferedReader(new InputStreamReader(this.getClass().getResourceAsStream("/translation.csv")));
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String line;
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while((line = reader.readLine()) != null)
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while ((line = reader.readLine()) != null)
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{
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String[] info = line.split(",");
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if(info.length == 2)
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if (info.length == 2)
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{
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stringTranslation.put(info[0].toLowerCase(), new WeatherLines(info[1], ""));
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fallBacks.put(info[1], new WeatherLines(info[1], ""));
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}
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else if(info.length == 3)
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else if (info.length == 3)
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{
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stringTranslation.put(info[0].toLowerCase(), new WeatherLines(info[1], info[2]));
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fallBacks.put(info[1] + " " + info[2], new WeatherLines(info[1], info[2]));
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}
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}
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}
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@@ -90,20 +94,164 @@ public class DatamartTranslation {
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}
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public byte icon(int icon) {
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if(!iconTranslation.containsKey(icon))
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if (!iconTranslation.containsKey(icon))
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return IconProvider.INVALID.id;
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return iconTranslation.get(icon);
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}
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public WeatherLines weatherName(String desc) {
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WeatherLines lines = stringTranslation.get(desc.toLowerCase());
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if(lines == null)
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if (lines == null)
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{
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System.out.println("FAILED:"+desc.toLowerCase());
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return new WeatherLines("TRANSLAT.", "FAILURE");
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System.out.println("FAILED:" + desc.toLowerCase());
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return getClosestMatching(desc);
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}
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else return lines;
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}
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public WeatherLines getClosestMatching(String desc) {
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WeatherLines bestMatch = new WeatherLines("TRANSLAT.", "FAILURE");
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desc = desc.toLowerCase();
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double bestRatio = Integer.MAX_VALUE;
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for (Map.Entry<String, WeatherLines> set : fallBacks.entrySet())
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{
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double ratio2 = getLevenshteinDistance(desc, set.getKey());
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if (ratio2 < bestRatio)
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{
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bestRatio = ratio2;
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bestMatch = set.getValue();
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}
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}
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System.out.println("Got " + bestMatch.line1 + " " + bestMatch.line2 + " for desc " + desc);
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return bestMatch;
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}
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public static int getLevenshteinDistance(CharSequence s, CharSequence t) {
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if (s == null || t == null)
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{
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throw new IllegalArgumentException("Strings must not be null");
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}
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int n = s.length();
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int m = t.length();
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if (n == 0)
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{
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return m;
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}
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else if (m == 0)
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{
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return n;
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}
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if (n > m)
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{
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// swap the input strings to consume less memory
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final CharSequence tmp = s;
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s = t;
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t = tmp;
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n = m;
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m = t.length();
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}
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final int[] p = new int[n + 1];
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// indexes into strings s and t
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int i; // iterates through s
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int j; // iterates through t
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int upper_left;
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int upper;
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char t_j; // jth character of t
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int cost;
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for (i = 0; i <= n; i++)
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{
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p[i] = i;
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}
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for (j = 1; j <= m; j++)
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{
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upper_left = p[0];
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t_j = t.charAt(j - 1);
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p[0] = j;
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for (i = 1; i <= n; i++)
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{
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upper = p[i];
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cost = s.charAt(i - 1) == t_j ? 0 : 1;
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// minimum of cell to the left+1, to the top+1, diagonally left and up +cost
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p[i] = Math.min(Math.min(p[i - 1] + 1, p[i] + 1), upper_left + cost);
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upper_left = upper;
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}
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}
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return p[n];
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}
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double findSimilarityRatio(String sentence1, String sentence2) {
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HashMap<String, Integer> firstSentenceMap = new HashMap<String, Integer>();
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HashMap<String, Integer> secondSentenceMap = new HashMap<String, Integer>();
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String[] firstSentenceWords = sentence1.split(" ");
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String[] secondSentenceWords = sentence2.split(" ");
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for (String word : firstSentenceWords)
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{
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if (firstSentenceMap.containsKey(word))
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{
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firstSentenceMap.put(word, firstSentenceMap.get(word) + 1);
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}
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else
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{
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firstSentenceMap.put(word, 1);
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}
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}
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for (String word : secondSentenceWords)
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{
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if (secondSentenceMap.containsKey(word))
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{
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secondSentenceMap.put(word, secondSentenceMap.get(word) + 1);
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}
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else
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{
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secondSentenceMap.put(word, 1);
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}
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}
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double totalWords = 0;
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double totalHits = 0;
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if (firstSentenceWords.length >= secondSentenceWords.length)
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{
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totalWords = firstSentenceWords.length;
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for (Map.Entry<String, Integer> entry : firstSentenceMap.entrySet())
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{
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String key = entry.getKey();
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if (secondSentenceMap.containsKey(key))
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{
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totalHits = totalHits + Math.min(secondSentenceMap.get(key), firstSentenceMap.get(key));
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}
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}
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}
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else
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{
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totalWords = secondSentenceWords.length;
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for (Map.Entry<String, Integer> entry : secondSentenceMap.entrySet())
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{
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String key = entry.getKey();
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if (firstSentenceMap.containsKey(key))
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{
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totalHits = totalHits + Math.min(secondSentenceMap.get(key), firstSentenceMap.get(key));
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}
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}
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}
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return totalHits / totalWords;
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}
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}
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class WeatherLines {
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@@ -11,7 +11,6 @@ import java.util.Calendar;
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import java.util.Date;
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import java.util.Locale;
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import java.util.TimeZone;
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import java.util.concurrent.TimeUnit;
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import javax.xml.XMLConstants;
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import javax.xml.parsers.DocumentBuilder;
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@@ -26,6 +25,7 @@ import org.xml.sax.SAXException;
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import com.flaremicro.util.Util;
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import com.flaremicro.visualforecast.forecast.DayForecast;
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import com.flaremicro.visualforecast.forecast.DetailedForecast;
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import com.flaremicro.visualforecast.forecast.ForecastDetails;
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import com.flaremicro.visualforecast.forecast.HourlyForecast;
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import com.flaremicro.visualforecast.forecast.TownForecast;
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@@ -77,7 +77,7 @@ public class ForecastProcessor implements Runnable {
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return -1;
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}
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public void processHourlyForecast(TownForecast forecast, Document doc) {
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public HourlyForecast[] processHourlyForecast(Document doc) {
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DateFormat dateFormat = new SimpleDateFormat("yyyyMMddHHmm");
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dateFormat.setTimeZone(TimeZone.getTimeZone("UTC"));
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NodeList hourlyForecast = doc.getElementsByTagName("hourlyForecast");
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@@ -106,7 +106,7 @@ public class ForecastProcessor implements Runnable {
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}
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}
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}
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forecast.setHourlyForecast(hourlyForecastArray.toArray(new HourlyForecast[0]));
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return hourlyForecastArray.toArray(new HourlyForecast[0]);
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}
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public void processForecasts() {
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@@ -115,7 +115,6 @@ public class ForecastProcessor implements Runnable {
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ArrayList<TownForecast> townForecasts = new ArrayList<TownForecast>();
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for (TownInfo townInfo : towns)
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{
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DayForecast[] dayForecasts = new DayForecast[8];
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InputStream is = null;
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Document doc = null;
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try
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@@ -145,6 +144,41 @@ public class ForecastProcessor implements Runnable {
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if (doc != null)
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{
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TownForecast tf = new TownForecast(townInfo.townName + ", " + townInfo.province, process7DayForecast(doc));
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townForecasts.add(tf);
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tf.setHourlyForecast(this.processHourlyForecast(doc));
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tf.setDetailedForecast(process36HourForecast(doc));
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tf.setSupportedDisplays(townInfo.getSupportedDisplays());
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}
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}
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forecastDetails.setTownForecast(townForecasts.toArray(new TownForecast[0]));
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setMostRecentForecast(forecastDetails);
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}
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private DetailedForecast[] process36HourForecast(Document doc)
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{
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DetailedForecast[] detailedForecast = new DetailedForecast[3];
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NodeList nodeList = doc.getElementsByTagName("forecast");
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for (int i = 0; i < Math.min(detailedForecast.length, nodeList.getLength()); i++)
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{
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if (nodeList.item(1).getNodeType() == Node.ELEMENT_NODE)
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{
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if (nodeList.item(1).getNodeType() == Node.ELEMENT_NODE)
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{
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Element node = (Element) nodeList.item(i);
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String title = XMLUtils.getStringFromTagAttribute(node, "period", "textForecastName");
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String textForecast = XMLUtils.getStringFromTag(node, "textSummary");
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detailedForecast[i] = new DetailedForecast(title, textForecast);
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}
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}
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}
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return detailedForecast;
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}
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private DayForecast[] process7DayForecast(Document doc)
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{
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DayForecast[] dayForecasts = new DayForecast[8];
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NodeList nodeList = doc.getElementsByTagName("forecast");
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for (int i = 0; i < nodeList.getLength(); i++)
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{
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@@ -224,25 +258,21 @@ public class ForecastProcessor implements Runnable {
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dayForecasts[i] = new DayForecast();
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}
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}
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TownForecast tf = new TownForecast(townInfo.townName + ", " + townInfo.province, dayForecasts);
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townForecasts.add(tf);
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this.processHourlyForecast(tf, doc);
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}
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}
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forecastDetails.setTownForecast(townForecasts.toArray(new TownForecast[0]));
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setMostRecentForecast(forecastDetails);
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return dayForecasts;
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}
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public void begin() {
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if (!running)
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{
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running = true;
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new Thread(this).start();
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self = new Thread(this);
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self.start();
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}
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}
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public void end() {
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running = false;
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if(self != null)
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self.interrupt();
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}
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@@ -262,7 +292,6 @@ public class ForecastProcessor implements Runnable {
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@Override
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public void run() {
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self = Thread.currentThread();
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while (running)
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{
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try
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@@ -1,5 +1,11 @@
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package com.flaremicro.visualforecast.datamart;
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import java.util.Arrays;
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import java.util.Collection;
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import java.util.Collections;
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import java.util.HashSet;
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import java.util.Set;
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public class TownInfo implements Comparable<TownInfo> {
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public final String code;
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public final String townName;
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@@ -7,6 +13,7 @@ public class TownInfo implements Comparable<TownInfo> {
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public final float northLat;
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public final float westLong;
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public final int priority;
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private Set<String> displays = new HashSet<String>();
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public TownInfo(String code, String townName, String province, float northLat, float westLong, int priority) {
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this.code = code;
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@@ -21,4 +28,24 @@ public class TownInfo implements Comparable<TownInfo> {
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public int compareTo(TownInfo o) {
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return priority - o.priority;
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}
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public void addSupportedDisplay(String display)
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{
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this.displays.add(display);
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}
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public void setSupportedDisplays(String ... displays){
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setSupportedDisplays(Arrays.asList(displays));
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}
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public void setSupportedDisplays(Collection<String> displays){
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this.displays.clear();
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this.displays.addAll(displays);
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}
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public Set<String> getSupportedDisplays()
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{
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return Collections.unmodifiableSet(displays);
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}
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}
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@@ -14,10 +14,11 @@ partly cloudy,Partly,Cloudy,
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showers or drizzle,Showers/,Drizzle
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Chance of showers,Chance,Showers
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A few showers,Few,Showers
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chance of drizzle,Chance,Drizzle
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Chance of drizzle or rain,Chance,Drizzle
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A few flurries or rain showers,Flurries/,Showers
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Chance of flurries or rain showers,Flurries/,Showers
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Chance of rain showers or flurries,Showers/Flurries
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Chance of rain showers or flurries,Showers/,Flurries
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chance of rain showers or wet flurries,Showers/,Flurries
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A few flurries,Flurries,
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Chance of flurries,Chance,Flurries
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@@ -34,6 +35,7 @@ Overcast,Overcast,
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Showers,Showers,
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Chance of showers,Chance,Showers
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Periods of rain,Scattered,Rain
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Periods of drizzle,Scattered,Rain
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Mostly Cloudy,Mostly,Cloudy
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Rain at times heavy,Heavy,Rain
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A few showers or drizzle,Drizzle
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@@ -102,3 +104,4 @@ Snow and blowing snow,Blowing,Snow
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Windy,Windy
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Smoke,Smoke
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rain showers or flurries,Showers/,Flurries
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chance of wet flurries,Wet,Flurries
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Can't render this file because it has a wrong number of fields in line 13.
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