Change all float to double. Delete unnecessary String format.

src/main/java/proteomics/ECL2.java

@@ -81,7 +81,7 @@ private ECL2(String parameter_path, String spectra_path) throws IOException, MzX
             cal_evalue = false;
         }
 
-        float delta_c_t = Float.valueOf(parameter_map.get("delta_c_t"));
+        double delta_c_t = Double.valueOf(parameter_map.get("delta_c_t"));
 
         boolean flankingPeaks = true;
         if (parameter_map.get("flanking_peaks").contentEquals("0")) {

src/main/java/proteomics/Search/CalEValue.java

@@ -15,14 +15,13 @@
 public class CalEValue {
 
     private static final Logger logger = LoggerFactory.getLogger(CalEValue.class);
-    private static final float maxTolerance = 20;
-    private static final float toleranceStep = 1;
+    private static final double maxTolerance = 20;
+    private static final double toleranceStep = 1;
 
     static void calEValue(int scan_num, ResultEntry result_entry, BuildIndex buildIndexObj, TreeMap<Integer, List<Double>> binScoresMap, float linker_mass, float originalTolerance, SparseVector xcorrPL, double singleChainT) throws IOException {
         int gap_num = ECL2.score_point_t - result_entry.getScoreCount();
-        float tolerance = originalTolerance;
-        float massWithoutLinker = result_entry.spectrum_mass - linker_mass;
-        int maxBinIdx = buildIndexObj.massToBin(massWithoutLinker * 0.5f);
+        double tolerance = originalTolerance;
+        int maxBinIdx = buildIndexObj.massToBin(massWithoutLinker * 0.5);
         while (gap_num > 0 && tolerance <= maxTolerance) {
             gap_num = generateRandomRandomScores(gap_num, tolerance, toleranceStep, binScoresMap, result_entry.spectrum_mass, massWithoutLinker, result_entry.charge, xcorrPL, buildIndexObj, buildIndexObj.getMassBinSeqMap(), buildIndexObj.getSeqEntryMap(), buildIndexObj.returnMassTool(), result_entry, maxBinIdx, singleChainT);
             tolerance += toleranceStep;
@@ -172,15 +171,15 @@ static void calEValue(int scan_num, ResultEntry result_entry, BuildIndex buildIn
             logger.debug("Estimating E-value failed. Scan: {}, mass: {}, slope: {}, intercept: {}, R square: {}, point num: {}.",scan_num, result_entry.spectrum_mass, optimal_slope, optimal_intercept, max_r_square, result_entry.getScoreCount());
         } else {
             result_entry.setEValue(Math.exp((optimal_slope * Math.round(result_entry.getScore() * inverseHistogramBinSize) + optimal_intercept) + Math.log((double) result_entry.getCandidateNum() / (double) result_entry.getScoreCount()))); // double point precision limitation.
-            result_entry.setEValueDetails((float) max_r_square, (float) optimal_slope, (float) optimal_intercept, optimal_start_idx, null_end_idx);
+            result_entry.setEValueDetails(max_r_square, optimal_slope, optimal_intercept, optimal_start_idx, null_end_idx);
         }
 
         if (ECL2.debug) {
             BufferedWriter writer = new BufferedWriter(new FileWriter(scan_num + ".evalue.csv"));
-            writer.write(String.format(Locale.US, "histogram,survival,ln(survival),slope=%.4f,intercept=%.4f,rsquare=%.4f,start=%d,end=%d\n", optimal_slope, optimal_intercept, max_r_square, optimal_start_idx, null_end_idx));
+            writer.write(String.format(Locale.US, "histogram,survival,ln(survival),slope=%f,intercept=%f,rsquare=%f,start=%d,end=%d\n", optimal_slope, optimal_intercept, max_r_square, optimal_start_idx, null_end_idx));
             for (int i = 0; i <= max_nonzero_idx; ++i) {
                 if (i < ln_survival_count_array.length) {
-                    writer.write(String.format(Locale.US, "%d,%d,%.4f\n", score_histogram[i], survival_count_array[i], ln_survival_count_array[i]));
+                    writer.write(String.format(Locale.US, "%d,%d,%f\n", score_histogram[i], survival_count_array[i], ln_survival_count_array[i]));
                 } else {
                     writer.write(String.format(Locale.US, "%d,%d\n", score_histogram[i], survival_count_array[i]));
                 }
@@ -189,7 +188,7 @@ static void calEValue(int scan_num, ResultEntry result_entry, BuildIndex buildIn
         }
     }
 
-    private static int generateRandomRandomScores(int gap_num, float tolerance, float toleranceStep, TreeMap<Integer, List<Double>> binScoresMap, float precursorMass, float massWithoutLinker, int precursorCharge, SparseVector xcorrPL, BuildIndex buildIndex, TreeMap<Integer, Set<String>> binSequencesMap, Map<String, ChainEntry> seqEntryMap, MassTool massTool, ResultEntry resultEntry, int maxBinIdx, double singleChainT) {
+    private static int generateRandomRandomScores(int gap_num, double tolerance, double toleranceStep, TreeMap<Integer, List<Double>> binScoresMap, double precursorMass, double massWithoutLinker, int precursorCharge, SparseVector xcorrPL, BuildIndex buildIndex, TreeMap<Integer, Set<String>> binSequencesMap, Map<String, ChainEntry> seqEntryMap, MassTool massTool, ResultEntry resultEntry, int maxBinIdx, double singleChainT) {
         for (int binIdx1 : binSequencesMap.keySet()) {
             if (binIdx1 < maxBinIdx) {
                 int leftBinIdx1 = buildIndex.massToBin(massWithoutLinker - tolerance - toleranceStep) - binIdx1;
@@ -217,7 +216,7 @@ private static int generateRandomRandomScores(int gap_num, float tolerance, floa
         return gap_num;
     }
 
-    private static List<Double> subFunction(int binIdx, TreeMap<Integer, List<Double>> binScoresMap, TreeMap<Integer, Set<String>> binSequencesMap, Map<String, ChainEntry> seqEntryMap, MassTool massTool, float precursorMass, int precursorCharge, SparseVector xcorrPL, double singleChainT) {
+    private static List<Double> subFunction(int binIdx, TreeMap<Integer, List<Double>> binScoresMap, TreeMap<Integer, Set<String>> binSequencesMap, Map<String, ChainEntry> seqEntryMap, MassTool massTool, double precursorMass, int precursorCharge, SparseVector xcorrPL, double singleChainT) {
         List<Double> scoreList = new ArrayList<>();
         if (binScoresMap.containsKey(binIdx)) {
             scoreList = binScoresMap.get(binIdx);

src/main/java/proteomics/Search/Search.java

@@ -12,15 +12,15 @@
 
 public class Search {
 
-    public final float ms1_tolerance;
+    public final double ms1_tolerance;
     public final int ms1_tolerance_unit;
     private final Map<String, ChainEntry> chain_entry_map;
     private final Map<Character, Float> fix_mod_map;
     private final MassTool mass_tool_obj;
     private final TreeMap<Integer, Set<String>> bin_seq_map;
     private final BuildIndex build_index_obj;
     private final int[] C13_correction_range;
-    final float single_chain_t;
+    final double single_chain_t;
     private final boolean cal_evalue;
 
     /////////////////////////////////////////public methods////////////////////////////////////////////////////////////
@@ -30,9 +30,9 @@ public Search(BuildIndex build_index_obj, Map<String, String> parameter_map) {
         fix_mod_map = build_index_obj.getFixModMap();
         mass_tool_obj = build_index_obj.returnMassTool();
         ms1_tolerance_unit = Integer.valueOf(parameter_map.get("ms1_tolerance_unit"));
-        ms1_tolerance = Float.valueOf(parameter_map.get("ms1_tolerance"));
+        ms1_tolerance = Double.valueOf(parameter_map.get("ms1_tolerance"));
         bin_seq_map = build_index_obj.getMassBinSeqMap();
-        single_chain_t = Float.valueOf(parameter_map.get("single_chain_t"));
+        single_chain_t = Double.valueOf(parameter_map.get("single_chain_t"));
         if (parameter_map.get("cal_evalue").contentEquals("0")) {
             cal_evalue = false;
         } else {
@@ -56,8 +56,8 @@ ResultEntry doSearch(SpectrumEntry spectrumEntry, SparseVector xcorrPL, TreeMap<
         }
 
         // set MS1 tolerance for further usage.
-        float leftMs1Tol = ms1_tolerance;
-        float rightMs1Tol = ms1_tolerance;
+        double leftMs1Tol = ms1_tolerance;
+        double rightMs1Tol = ms1_tolerance;
         if (ms1_tolerance_unit == 1) {
             leftMs1Tol = spectrumEntry.precursor_mass - (spectrumEntry.precursor_mass / (1 + ms1_tolerance * 1e-6f));
             rightMs1Tol = (spectrumEntry.precursor_mass / (1 - ms1_tolerance * 1e-6f)) - spectrumEntry.precursor_mass;
@@ -78,8 +78,8 @@ ResultEntry doSearch(SpectrumEntry spectrumEntry, SparseVector xcorrPL, TreeMap<
                 break;
             }
 
-            float left_mass_2;
-            float right_mass_2;
+            double left_mass_2;
+            double right_mass_2;
             int left_idx_2;
             int right_idx_2;
             NavigableMap<Integer, Set<String>> sub_map = new TreeMap<>();

src/main/java/proteomics/Search/SearchWrap.java

@@ -23,7 +23,7 @@ public class SearchWrap implements Callable<FinalResultEntry> {
     private final PreSpectrum preSpectrumObj;
     private final Map<String, Set<String>> seqProMap;
     private final boolean cal_evalue;
-    private final float delta_c_t;
+    private final double delta_c_t;
 
     public SearchWrap(Search search_obj, SpectrumEntry spectrumEntry, BuildIndex build_index_obj, MassTool mass_tool_obj, Map<String, Set<String>> seqProMap, boolean cal_evalue, float delta_c_t, boolean flankingPeaks) {
         this.search_obj = search_obj;
@@ -51,7 +51,7 @@ public FinalResultEntry call() throws IOException {
         if (resultEntry != null) {
             if (1 - (resultEntry.getSecondScore() / resultEntry.getScore()) >= delta_c_t) {
                 if (cal_evalue) {
-                    float originalTolerance;
+                    double originalTolerance;
                     if (search_obj.ms1_tolerance_unit == 1) {
                         originalTolerance = resultEntry.spectrum_mass * search_obj.ms1_tolerance * 1e-6f;
                     } else {

src/main/java/proteomics/Spectrum/PreSpectra.java

@@ -57,7 +57,7 @@ public PreSpectra(JMzReader spectra_parser, BuildIndex build_index_obj, Map<Stri
             }
             int precursor_charge = spectrum.getPrecursorCharge();
             double precursor_mz = spectrum.getPrecursorMZ();
-            float precursor_mass = (float) (precursor_mz * precursor_charge - precursor_charge * 1.00727646688);
+            double precursor_mass = (precursor_mz * precursor_charge - precursor_charge * 1.00727646688);
 
             Map<Double, Double> raw_mz_intensity_map = spectrum.getPeakList();
 

src/main/java/proteomics/Spectrum/PreSpectrum.java

@@ -78,7 +78,7 @@ private SparseVector prepareXcorr(double[] pl_array) {
                 }
             }
             if (Math.abs(temp) > 1e-6) {
-                xcorr_pl.put(i, (float) temp);
+                xcorr_pl.put(i, temp);
             }
         }
 
@@ -109,7 +109,7 @@ private double[] normalizeSpec(double[] plArray) {
 
             if (maxWindowIntensity > 0) {
                 double temp1 = 50 / maxWindowIntensity;
-                double temp2 = 0.05f * maxIntensity;
+                double temp2 = 0.05 * maxIntensity;
                 for (int j = 0; j < windowSize; ++j) {
                     int idx = i * windowSize + j;
                     if (idx < plArray.length) {

src/main/java/proteomics/TheoSeq/MassTool.java

@@ -14,41 +14,41 @@ public class MassTool {
 
     public static final double H2O = 18.010564684;
 
-    private final Map<Character, Float> mass_table = new HashMap<>(25, 1);
+    private final Map<Character, Double> mass_table = new HashMap<>(25, 1);
     private final int missed_cleavage;
     private final String cut_site;
     private final String protect_site;
     private final double inverseMzBinSize;
     private final double one_minus_bin_offset;
 
-    public MassTool(int missed_cleavage, Map<Character, Float> fix_mod_map, String cut_site, String protect_site, float mz_bin_size, float one_minus_bin_offset) {
+    public MassTool(int missed_cleavage, Map<Character, Double> fix_mod_map, String cut_site, String protect_site, double mz_bin_size, double one_minus_bin_offset) {
         inverseMzBinSize = 1 / mz_bin_size;
         this.missed_cleavage = missed_cleavage;
         this.cut_site = cut_site;
         this.protect_site = protect_site;
         this.one_minus_bin_offset = one_minus_bin_offset;
-        mass_table.put('G', 57.021464f + fix_mod_map.get('G'));
-        mass_table.put('A', 71.037114f + fix_mod_map.get('A'));
-        mass_table.put('S', 87.032028f + fix_mod_map.get('S'));
-        mass_table.put('P', 97.052764f + fix_mod_map.get('P'));
-        mass_table.put('V', 99.068414f + fix_mod_map.get('V'));
-        mass_table.put('T', 101.047678f + fix_mod_map.get('I'));
-        mass_table.put('C', 103.009184f + fix_mod_map.get('C'));
-        mass_table.put('I', 113.084064f + fix_mod_map.get('I'));
-        mass_table.put('L', 113.084064f + fix_mod_map.get('L'));
-        mass_table.put('N', 114.042927f + fix_mod_map.get('N'));
-        mass_table.put('D', 115.026943f + fix_mod_map.get('D'));
-        mass_table.put('Q', 128.058578f + fix_mod_map.get('Q'));
-        mass_table.put('K', 128.094963f + fix_mod_map.get('K'));
-        mass_table.put('E', 129.042593f + fix_mod_map.get('E'));
-        mass_table.put('M', 131.040485f + fix_mod_map.get('M'));
-        mass_table.put('H', 137.058912f + fix_mod_map.get('H'));
-        mass_table.put('F', 147.068414f + fix_mod_map.get('F'));
-        mass_table.put('R', 156.101111f + fix_mod_map.get('R'));
-        mass_table.put('Y', 163.063329f + fix_mod_map.get('Y'));
-        mass_table.put('W', 186.079313f + fix_mod_map.get('W'));
-        mass_table.put('U', 150.953636f + fix_mod_map.get('U'));
-        mass_table.put('O', 132.08988f + fix_mod_map.get('O'));
+        mass_table.put('G', 57.021464 + fix_mod_map.get('G'));
+        mass_table.put('A', 71.037114 + fix_mod_map.get('A'));
+        mass_table.put('S', 87.032028 + fix_mod_map.get('S'));
+        mass_table.put('P', 97.052764 + fix_mod_map.get('P'));
+        mass_table.put('V', 99.068414 + fix_mod_map.get('V'));
+        mass_table.put('T', 101.047678 + fix_mod_map.get('I'));
+        mass_table.put('C', 103.009184 + fix_mod_map.get('C'));
+        mass_table.put('I', 113.084064 + fix_mod_map.get('I'));
+        mass_table.put('L', 113.084064 + fix_mod_map.get('L'));
+        mass_table.put('N', 114.042927 + fix_mod_map.get('N'));
+        mass_table.put('D', 115.026943 + fix_mod_map.get('D'));
+        mass_table.put('Q', 128.058578 + fix_mod_map.get('Q'));
+        mass_table.put('K', 128.094963 + fix_mod_map.get('K'));
+        mass_table.put('E', 129.042593 + fix_mod_map.get('E'));
+        mass_table.put('M', 131.040485 + fix_mod_map.get('M'));
+        mass_table.put('H', 137.058912 + fix_mod_map.get('H'));
+        mass_table.put('F', 147.068414 + fix_mod_map.get('F'));
+        mass_table.put('R', 156.101111 + fix_mod_map.get('R'));
+        mass_table.put('Y', 163.063329 + fix_mod_map.get('Y'));
+        mass_table.put('W', 186.079313 + fix_mod_map.get('W'));
+        mass_table.put('U', 150.953636 + fix_mod_map.get('U'));
+        mass_table.put('O', 132.08988 + fix_mod_map.get('O'));
         mass_table.put('n', fix_mod_map.get('n'));
         mass_table.put('c', fix_mod_map.get('c'));
     }
@@ -57,19 +57,19 @@ public int mzToBin(double mz) {
         return (int) (mz * inverseMzBinSize + one_minus_bin_offset);
     }
 
-    public float calResidueMass(String seq) { // n and c are also AA.
+    public double calResidueMass(String seq) { // n and c are also AA.
         double total_mass = 0;
         Matcher matcher = mod_aa_pattern.matcher(seq);
         while (matcher.find()) {
             char aa = matcher.group(1).charAt(0);
-            float delta_mass = 0;
+            double delta_mass = 0;
             if (matcher.group(3) != null) {
-                delta_mass = Float.valueOf(matcher.group(3));
+                delta_mass = Double.valueOf(matcher.group(3));
             }
             total_mass += mass_table.get(aa) + delta_mass;
         }
 
-        return (float) total_mass;
+        return total_mass;
     }
 
     public Set<String> buildChainSet(String pro_seq, short linker_type) {
@@ -106,11 +106,11 @@ public Set<String> buildChainSet(String pro_seq, short linker_type) {
         return chain_seq_set;
     }
 
-    public Map<Character, Float> getMassTable() {
+    public Map<Character, Double> getMassTable() {
         return mass_table;
     }
 
-    public double generateTheoFragmentAndCalXCorr(String seq, short linkSite, float additional_mass, int precursor_charge, SparseVector xcorrPL) {
+    public double generateTheoFragmentAndCalXCorr(String seq, short linkSite, double additional_mass, int precursor_charge, SparseVector xcorrPL) {
         linkSite = (short) Math.max(1, linkSite);
 
         int localMaxCharge = Math.min(max_charge, Math.max(precursor_charge - 1, 1));
@@ -182,9 +182,9 @@ public static AA[] seqToAAList(String seq) {
         List<AA> temp = new LinkedList<>();
         while (matcher.find()) {
             char aa = matcher.group(1).charAt(0);
-            float delta_mass = 0;
+            double delta_mass = 0;
             if (matcher.group(3) != null) {
-                delta_mass = Float.valueOf(matcher.group(3));
+                delta_mass = Double.valueOf(matcher.group(3));
             }
             temp.add(new AA(aa, delta_mass));
         }

src/main/java/proteomics/Types/AA.java

@@ -5,10 +5,10 @@
 public class AA {
 
     public final char aa;
-    public final float delta_mass;
+    public final double delta_mass;
     private final int hashCode;
 
-    public AA(char aa, float delta_mass) {
+    public AA(char aa, double delta_mass) {
         this.aa = aa;
         this.delta_mass = delta_mass;
         String toString;

src/main/java/proteomics/Types/BinaryModParam.java

@@ -2,12 +2,12 @@
 
 
 public class BinaryModParam {
-    public final float modMass;
+    public final double modMass;
     public final String aas;
 
     private final int hashCode;
 
-    public BinaryModParam(float modMass, String aas) {
+    public BinaryModParam(double modMass, String aas) {
         this.modMass = modMass;
         this.aas = aas;
         String toString = modMass + "@" + aas + "(binary)";

src/main/java/proteomics/Types/ChainEntry.java

@@ -5,13 +5,13 @@
 public class ChainEntry {
 
     public final String seq;
-    public final float chain_mass;
+    public final double chain_mass;
     public final Set<Short> link_site_set;
     public final boolean n_term;
     public final boolean c_term;
     public final int binaryModType;
 
-    public ChainEntry(String seq, float chain_mass, Set<Short> link_site_set, boolean n_term, boolean c_term, int binaryModType) {
+    public ChainEntry(String seq, double chain_mass, Set<Short> link_site_set, boolean n_term, boolean c_term, int binaryModType) {
         this.seq = seq;
         this.chain_mass = chain_mass;
         this.link_site_set = link_site_set;

src/main/java/proteomics/Types/DebugEntry.java

@@ -4,10 +4,10 @@ public class DebugEntry implements Comparable<DebugEntry> {
 
     public final String chain;
     public final int link_site;
-    public final float mass;
+    public final double mass;
     public final double score;
 
-    public DebugEntry(String chain, int link_site, float mass, double score) {
+    public DebugEntry(String chain, int link_site, double mass, double score) {
         this.chain = chain;
         this.link_site = link_site;
         this.mass = mass;

src/main/java/proteomics/Types/ResultEntry.java

@@ -31,9 +31,9 @@ public class ResultEntry{
     private long candidate_num;
     private int score_count = 0;
     private double e_value = 9999;
-    private float r_square;
-    private float slope;
-    private float intercept;
+    private double r_square;
+    private double slope;
+    private double intercept;
     private int start_idx;
     private int end_idx;
 
@@ -97,7 +97,7 @@ public void addToScoreHistogram(double score) {
         }
     }
 
-    public void setEValueDetails(float r_square, float slope, float intercept, int start_idx, int end_idx) {
+    public void setEValueDetails(double r_square, double slope, double intercept, int start_idx, int end_idx) {
         this.r_square = r_square;
         this.slope = slope;
         this.intercept = intercept;
@@ -152,15 +152,15 @@ public int getScoreCount() {
         return score_count;
     }
 
-    public float getRSquare() {
+    public double getRSquare() {
         return r_square;
     }
 
-    public float getSlope() {
+    public double getSlope() {
         return slope;
     }
 
-    public float getIntercept() {
+    public double getIntercept() {
         return intercept;
     }