import jalview.datamodel.AlignmentAnnotation;
import jalview.datamodel.AlignmentI;
import jalview.datamodel.Annotation;
+import jalview.datamodel.Profile;
+import jalview.datamodel.ProfileI;
+import jalview.datamodel.Profiles;
+import jalview.datamodel.ProfilesI;
+import jalview.datamodel.ResidueCount;
+import jalview.datamodel.ResidueCount.SymbolCounts;
import jalview.datamodel.SequenceI;
+import jalview.ext.android.SparseIntArray;
+import jalview.util.Comparison;
import jalview.util.Format;
import jalview.util.MappingUtils;
import jalview.util.QuickSort;
+import java.awt.Color;
import java.util.Arrays;
import java.util.Hashtable;
import java.util.List;
*/
public class AAFrequency
{
- private static final int TO_UPPER_CASE = 'A' - 'a'; // -32
-
- public static final String MAXCOUNT = "C";
-
- public static final String MAXRESIDUE = "R";
-
- public static final String PID_GAPS = "G";
-
- public static final String PID_NOGAPS = "N";
-
public static final String PROFILE = "P";
- public static final String ENCODED_CHARS = "E";
-
/*
* Quick look-up of String value of char 'A' to 'Z'
*/
}
}
- public static final Hashtable[] calculate(List<SequenceI> list,
- int start, int end)
+ public static final ProfilesI calculate(List<SequenceI> list, int start,
+ int end)
{
return calculate(list, start, end, false);
}
- public static final Hashtable[] calculate(List<SequenceI> sequences,
+ public static final ProfilesI calculate(List<SequenceI> sequences,
int start, int end, boolean profile)
{
SequenceI[] seqs = new SequenceI[sequences.size()];
for (int i = 0; i < sequences.size(); i++)
{
seqs[i] = sequences.get(i);
- if (seqs[i].getLength() > width)
+ int length = seqs[i].getLength();
+ if (length > width)
{
- width = seqs[i].getLength();
+ width = length;
}
}
- Hashtable[] reply = new Hashtable[width];
-
if (end >= width)
{
end = width;
}
- calculate(seqs, start, end, reply, profile);
+ ProfilesI reply = calculate(seqs, width, start, end, profile);
return reply;
}
}
- public static final void calculate(SequenceI[] sequences, int start,
- int end, Hashtable[] result, boolean profile)
+ /**
+ * Calculate the consensus symbol(s) for each column in the given range.
+ *
+ * @param sequences
+ * @param width
+ * the full width of the alignment
+ * @param start
+ * start column (inclusive, base zero)
+ * @param end
+ * end column (exclusive)
+ * @param saveFullProfile
+ * if true, store all symbol counts
+ */
+ public static final ProfilesI calculate(final SequenceI[] sequences,
+ int width, int start, int end, boolean saveFullProfile)
{
- Hashtable residueHash;
- int maxCount, nongap, i, j, v;
- int jSize = sequences.length;
- String maxResidue;
- char c = '-';
- float percentage;
-
- int[] values = new int[255];
+ // long now = System.currentTimeMillis();
+ int seqCount = sequences.length;
+ boolean nucleotide = false;
+ int nucleotideCount = 0;
+ int peptideCount = 0;
- char[] seq;
+ ProfileI[] result = new ProfileI[width];
- for (i = start; i < end; i++)
+ for (int column = start; column < end; column++)
{
- residueHash = new Hashtable();
- maxCount = 0;
- maxResidue = "";
- nongap = 0;
- values = new int[255];
+ /*
+ * Apply a heuristic to detect nucleotide data (which can
+ * be counted in more compact arrays); here we test for
+ * more than 90% nucleotide; recheck every 10 columns in case
+ * of misleading data e.g. highly conserved Alanine in peptide!
+ * Mistakenly guessing nucleotide has a small performance cost,
+ * as it will result in counting in sparse arrays.
+ * Mistakenly guessing peptide has a small space cost,
+ * as it will use a larger than necessary array to hold counts.
+ */
+ if (nucleotideCount > 100 && column % 10 == 0)
+ {
+ nucleotide = (9 * peptideCount < nucleotideCount);
+ }
+ ResidueCount residueCounts = new ResidueCount(nucleotide);
- for (j = 0; j < jSize; j++)
+ for (int row = 0; row < seqCount; row++)
{
- if (sequences[j] == null)
+ if (sequences[row] == null)
{
- System.err
- .println("WARNING: Consensus skipping null sequence - possible race condition.");
+ System.err.println(
+ "WARNING: Consensus skipping null sequence - possible race condition.");
continue;
}
- seq = sequences[j].getSequence();
- if (seq.length > i)
+ if (sequences[row].getLength() > column)
{
- c = seq[i];
-
- if (c == '.' || c == ' ')
- {
- c = '-';
- }
-
- if (c == '-')
+ char c = sequences[row].getCharAt(column);
+ residueCounts.add(c);
+ if (Comparison.isNucleotide(c))
{
- values['-']++;
- continue;
+ nucleotideCount++;
}
- else if ('a' <= c && c <= 'z')
+ else if (!Comparison.isGap(c))
{
- c += TO_UPPER_CASE;
+ peptideCount++;
}
-
- nongap++;
- values[c]++;
-
}
else
{
- values['-']++;
- }
- }
- if (jSize == 1)
- {
- maxResidue = String.valueOf(c);
- maxCount = 1;
- }
- else
- {
- for (v = 'A'; v <= 'Z'; v++)
- {
- // TODO why ignore values[v] == 1?
- if (values[v] < 1 /* 2 */|| values[v] < maxCount)
- {
- continue;
- }
-
- if (values[v] > maxCount)
- {
- maxResidue = CHARS[v - 'A'];
- }
- else if (values[v] == maxCount)
- {
- maxResidue += CHARS[v - 'A'];
- }
- maxCount = values[v];
+ /*
+ * count a gap if the sequence doesn't reach this column
+ */
+ residueCounts.addGap();
}
}
- if (maxResidue.length() == 0)
- {
- maxResidue = "-";
- }
- if (profile)
- {
- // TODO use a 1-dimensional array with jSize, nongap in [0] and [1]
- residueHash.put(PROFILE, new int[][] { values,
- new int[] { jSize, nongap } });
- }
- residueHash.put(MAXCOUNT, new Integer(maxCount));
- residueHash.put(MAXRESIDUE, maxResidue);
- percentage = ((float) maxCount * 100) / jSize;
- residueHash.put(PID_GAPS, new Float(percentage));
+ int maxCount = residueCounts.getModalCount();
+ String maxResidue = residueCounts.getResiduesForCount(maxCount);
+ int gapCount = residueCounts.getGapCount();
+ ProfileI profile = new Profile(seqCount, gapCount, maxCount,
+ maxResidue);
- if (nongap > 0)
+ if (saveFullProfile)
{
- // calculate for non-gapped too
- percentage = ((float) maxCount * 100) / nongap;
+ profile.setCounts(residueCounts);
}
- residueHash.put(PID_NOGAPS, new Float(percentage));
- result[i] = residueHash;
+ result[column] = profile;
}
+ return new Profiles(result);
+ // long elapsed = System.currentTimeMillis() - now;
+ // System.out.println(elapsed);
}
/**
- * Compute all or part of the annotation row from the given consensus
- * hashtable
+ * Make an estimate of the profile size we are going to compute i.e. how many
+ * different characters may be present in it. Overestimating has a cost of
+ * using more memory than necessary. Underestimating has a cost of needing to
+ * extend the SparseIntArray holding the profile counts.
*
- * @param consensus
- * - pre-allocated annotation row
- * @param hconsensus
- * @param iStart
- * @param width
- * @param ignoreGapsInConsensusCalculation
- * @param includeAllConsSymbols
- * @param nseq
+ * @param profileSizes
+ * counts of sizes of profiles so far encountered
+ * @return
*/
- public static void completeConsensus(AlignmentAnnotation consensus,
- Hashtable[] hconsensus, int iStart, int width,
- boolean ignoreGapsInConsensusCalculation,
- boolean includeAllConsSymbols, long nseq)
+ static int estimateProfileSize(SparseIntArray profileSizes)
{
- completeConsensus(consensus, hconsensus, iStart, width,
- ignoreGapsInConsensusCalculation, includeAllConsSymbols, null,
- nseq);
+ if (profileSizes.size() == 0)
+ {
+ return 4;
+ }
+
+ /*
+ * could do a statistical heuristic here e.g. 75%ile
+ * for now just return the largest value
+ */
+ return profileSizes.keyAt(profileSizes.size() - 1);
}
/**
* Derive the consensus annotations to be added to the alignment for display.
* This does not recompute the raw data, but may be called on a change in
- * display options, such as 'show logo', which may in turn result in a change
- * in the derived values.
+ * display options, such as 'ignore gaps', which may in turn result in a
+ * change in the derived values.
*
* @param consensus
* the annotation row to add annotations to
- * @param hconsensus
+ * @param profiles
* the source consensus data
- * @param iStart
- * start column
- * @param width
- * end column
- * @param ignoreGapsInConsensusCalculation
- * if true, use the consensus calculated ignoring gaps
- * @param includeAllConsSymbols
+ * @param startCol
+ * start column (inclusive)
+ * @param endCol
+ * end column (exclusive)
+ * @param ignoreGaps
+ * if true, normalise residue percentages ignoring gaps
+ * @param showSequenceLogo
* if true include all consensus symbols, else just show modal
* residue
- * @param alphabet
* @param nseq
* number of sequences
*/
public static void completeConsensus(AlignmentAnnotation consensus,
- Hashtable[] hconsensus, int iStart, int width,
- boolean ignoreGapsInConsensusCalculation,
- boolean includeAllConsSymbols, char[] alphabet, long nseq)
+ ProfilesI profiles, int startCol, int endCol, boolean ignoreGaps,
+ boolean showSequenceLogo, long nseq)
{
+ // long now = System.currentTimeMillis();
if (consensus == null || consensus.annotations == null
- || consensus.annotations.length < width)
+ || consensus.annotations.length < endCol)
{
- // called with a bad alignment annotation row - wait for it to be
- // initialised properly
+ /*
+ * called with a bad alignment annotation row
+ * wait for it to be initialised properly
+ */
return;
}
- final Format fmt = getPercentageFormat(nseq);
-
- for (int i = iStart; i < width; i++)
+ for (int i = startCol; i < endCol; i++)
{
- Hashtable hci;
- if (i >= hconsensus.length || ((hci = hconsensus[i]) == null))
+ ProfileI profile = profiles.get(i);
+ if (profile == null)
{
- // happens if sequences calculated over were shorter than alignment
- // width
+ /*
+ * happens if sequences calculated over were
+ * shorter than alignment width
+ */
consensus.annotations[i] = null;
- continue;
+ return;
}
- Float fv = (Float) hci
- .get(ignoreGapsInConsensusCalculation ? PID_NOGAPS : PID_GAPS);
- if (fv == null)
- {
- consensus.annotations[i] = null;
- // data has changed below us .. give up and
- continue;
- }
- float value = fv.floatValue();
- String maxRes = hci.get(AAFrequency.MAXRESIDUE).toString();
- StringBuilder mouseOver = new StringBuilder(64);
- if (maxRes.length() > 1)
- {
- mouseOver.append("[").append(maxRes).append("] ");
- maxRes = "+";
- }
- else
+
+ final int dp = getPercentageDp(nseq);
+
+ float value = profile.getPercentageIdentity(ignoreGaps);
+
+ String description = getTooltip(profile, value, showSequenceLogo,
+ ignoreGaps, dp);
+
+ String modalResidue = profile.getModalResidue();
+ if ("".equals(modalResidue))
{
- mouseOver.append(hci.get(AAFrequency.MAXRESIDUE) + " ");
+ modalResidue = "-";
}
- int[][] profile = (int[][]) hci.get(AAFrequency.PROFILE);
- if (profile != null && includeAllConsSymbols)
+ else if (modalResidue.length() > 1)
{
- int sequenceCount = profile[1][0];
- int nonGappedCount = profile[1][1];
- int normalisedBy = ignoreGapsInConsensusCalculation ? nonGappedCount
- : sequenceCount;
- mouseOver.setLength(0);
- if (alphabet != null)
- {
- for (int c = 0; c < alphabet.length; c++)
- {
- float tval = profile[0][alphabet[c]] * 100f / normalisedBy;
- mouseOver
- .append(((c == 0) ? "" : "; "))
- .append(alphabet[c])
- .append(" ")
- .append(((fmt != null) ? fmt.form(tval) : ((int) tval)))
- .append("%");
- }
- }
- else
- {
- // TODO do this sort once only in calculate()?
- // char[][] ca = new char[profile[0].length][];
- char[] ca = new char[profile[0].length];
- float[] vl = new float[profile[0].length];
- for (int c = 0; c < ca.length; c++)
- {
- ca[c] = (char) c;
- // ca[c] = new char[]
- // { (char) c };
- vl[c] = profile[0][c];
- }
- QuickSort.sort(vl, ca);
- for (int p = 0, c = ca.length - 1; profile[0][ca[c]] > 0; c--)
- {
- final char residue = ca[c];
- if (residue != '-')
- {
- float tval = profile[0][residue] * 100f / normalisedBy;
- mouseOver
- .append((((p == 0) ? "" : "; ")))
- .append(residue)
- .append(" ")
- .append(((fmt != null) ? fmt.form(tval)
- : ((int) tval))).append("%");
- p++;
- }
- }
- }
+ modalResidue = "+";
}
- else
+ consensus.annotations[i] = new Annotation(modalResidue, description,
+ ' ', value);
+ }
+ // long elapsed = System.currentTimeMillis() - now;
+ // System.out.println(-elapsed);
+ }
+
+ /**
+ * Derive the gap count annotation row.
+ *
+ * @param gaprow
+ * the annotation row to add annotations to
+ * @param profiles
+ * the source consensus data
+ * @param startCol
+ * start column (inclusive)
+ * @param endCol
+ * end column (exclusive)
+ */
+ public static void completeGapAnnot(AlignmentAnnotation gaprow,
+ ProfilesI profiles, int startCol, int endCol, long nseq)
+ {
+ if (gaprow == null || gaprow.annotations == null
+ || gaprow.annotations.length < endCol)
+ {
+ /*
+ * called with a bad alignment annotation row
+ * wait for it to be initialised properly
+ */
+ return;
+ }
+ // always set ranges again
+ gaprow.graphMax = nseq;
+ gaprow.graphMin = 0;
+ double scale = 0.8 / nseq;
+ for (int i = startCol; i < endCol; i++)
+ {
+ ProfileI profile = profiles.get(i);
+ if (profile == null)
{
- mouseOver.append(
- (((fmt != null) ? fmt.form(value) : ((int) value))))
- .append("%");
+ /*
+ * happens if sequences calculated over were
+ * shorter than alignment width
+ */
+ gaprow.annotations[i] = null;
+ return;
}
- consensus.annotations[i] = new Annotation(maxRes,
- mouseOver.toString(), ' ', value);
+
+ final int gapped = profile.getNonGapped();
+
+ String description = "" + gapped;
+
+ gaprow.annotations[i] = new Annotation("", description, '\0', gapped,
+ jalview.util.ColorUtils.bleachColour(Color.DARK_GRAY,
+ (float) scale * gapped));
}
}
/**
- * Returns a Format designed to show all significant figures for profile
- * percentages. For less than 100 sequences, returns null (the integer
- * percentage value will be displayed). For 100-999 sequences, returns "%3.1f"
+ * Returns a tooltip showing either
+ * <ul>
+ * <li>the full profile (percentages of all residues present), if
+ * showSequenceLogo is true, or</li>
+ * <li>just the modal (most common) residue(s), if showSequenceLogo is
+ * false</li>
+ * </ul>
+ * Percentages are as a fraction of all sequence, or only ungapped sequences
+ * if ignoreGaps is true.
*
- * @param nseq
+ * @param profile
+ * @param pid
+ * @param showSequenceLogo
+ * @param ignoreGaps
+ * @param dp
+ * the number of decimal places to format percentages to
* @return
*/
- protected static Format getPercentageFormat(long nseq)
+ static String getTooltip(ProfileI profile, float pid,
+ boolean showSequenceLogo, boolean ignoreGaps, int dp)
{
- int scale = 0;
- while (nseq >= 10)
+ ResidueCount counts = profile.getCounts();
+
+ String description = null;
+ if (counts != null && showSequenceLogo)
{
- scale++;
- nseq /= 10;
+ int normaliseBy = ignoreGaps ? profile.getNonGapped()
+ : profile.getHeight();
+ description = counts.getTooltip(normaliseBy, dp);
}
- return scale <= 1 ? null : new Format("%3." + (scale - 1) + "f");
+ else
+ {
+ StringBuilder sb = new StringBuilder(64);
+ String maxRes = profile.getModalResidue();
+ if (maxRes.length() > 1)
+ {
+ sb.append("[").append(maxRes).append("]");
+ }
+ else
+ {
+ sb.append(maxRes);
+ }
+ if (maxRes.length() > 0)
+ {
+ sb.append(" ");
+ Format.appendPercentage(sb, pid, dp);
+ sb.append("%");
+ }
+ description = sb.toString();
+ }
+ return description;
}
/**
* in descending order of percentage value
* </pre>
*
- * @param hconsensus
- * the data table from which to extract and sort values
+ * @param profile
+ * the data object from which to extract and sort values
* @param ignoreGaps
* if true, only non-gapped values are included in percentage
* calculations
* @return
*/
- public static int[] extractProfile(Hashtable hconsensus,
- boolean ignoreGaps)
+ public static int[] extractProfile(ProfileI profile, boolean ignoreGaps)
{
int[] rtnval = new int[64];
- int[][] profile = (int[][]) hconsensus.get(AAFrequency.PROFILE);
- if (profile == null)
+ ResidueCount counts = profile.getCounts();
+ if (counts == null)
{
return null;
}
- char[] ca = new char[profile[0].length];
- float[] vl = new float[profile[0].length];
- for (int c = 0; c < ca.length; c++)
- {
- ca[c] = (char) c;
- vl[c] = profile[0][c];
- }
- QuickSort.sort(vl, ca);
+
+ SymbolCounts symbolCounts = counts.getSymbolCounts();
+ char[] symbols = symbolCounts.symbols;
+ int[] values = symbolCounts.values;
+ QuickSort.sort(values, symbols);
int nextArrayPos = 2;
int totalPercentage = 0;
- int distinctValuesCount = 0;
- final int divisor = profile[1][ignoreGaps ? 1 : 0];
- for (int c = ca.length - 1; profile[0][ca[c]] > 0; c--)
+ final int divisor = ignoreGaps ? profile.getNonGapped()
+ : profile.getHeight();
+
+ /*
+ * traverse the arrays in reverse order (highest counts first)
+ */
+ for (int i = symbols.length - 1; i >= 0; i--)
{
- if (ca[c] != '-')
- {
- rtnval[nextArrayPos++] = ca[c];
- final int percentage = (int) (profile[0][ca[c]] * 100f / divisor);
- rtnval[nextArrayPos++] = percentage;
- totalPercentage += percentage;
- distinctValuesCount++;
- }
+ int theChar = symbols[i];
+ int charCount = values[i];
+
+ rtnval[nextArrayPos++] = theChar;
+ final int percentage = (charCount * 100) / divisor;
+ rtnval[nextArrayPos++] = percentage;
+ totalPercentage += percentage;
}
- rtnval[0] = distinctValuesCount;
+ rtnval[0] = symbols.length;
rtnval[1] = totalPercentage;
int[] result = new int[rtnval.length + 1];
result[0] = AlignmentAnnotation.SEQUENCE_PROFILE;
{
continue;
}
- List<char[]> codons = MappingUtils
- .findCodonsFor(seq, col, mappings);
+ List<char[]> codons = MappingUtils.findCodonsFor(seq, col,
+ mappings);
for (char[] codon : codons)
{
int codonEncoded = CodingUtils.encodeCodon(codon);
int modalCodonEncoded = codons[codons.length - 1];
int modalCodonCount = sortedCodonCounts[codons.length - 1];
- String modalCodon = String.valueOf(CodingUtils
- .decodeCodon(modalCodonEncoded));
- if (sortedCodonCounts.length > 1
- && sortedCodonCounts[codons.length - 2] == sortedCodonCounts[codons.length - 1])
+ String modalCodon = String
+ .valueOf(CodingUtils.decodeCodon(modalCodonEncoded));
+ if (sortedCodonCounts.length > 1 && sortedCodonCounts[codons.length
+ - 2] == sortedCodonCounts[codons.length - 1])
{
/*
* two or more codons share the modal count
StringBuilder samePercent = new StringBuilder();
String percent = null;
String lastPercent = null;
- Format fmt = getPercentageFormat(nseqs);
+ int percentDecPl = getPercentageDp(nseqs);
for (int j = codons.length - 1; j >= 0; j--)
{
final int pct = codonCount * 100 / totalCount;
String codon = String
.valueOf(CodingUtils.decodeCodon(codonEncoded));
- percent = fmt == null ? Integer.toString(pct) : fmt.form(pct);
+ StringBuilder sb = new StringBuilder();
+ Format.appendPercentage(sb, pct, percentDecPl);
+ percent = sb.toString();
if (showProfileLogo || codonCount == modalCodonCount)
{
if (percent.equals(lastPercent) && j > 0)
{
if (samePercent.length() > 0)
{
- mouseOver.append(samePercent).append(": ")
- .append(lastPercent).append("% ");
+ mouseOver.append(samePercent).append(": ").append(lastPercent)
+ .append("% ");
}
samePercent.setLength(0);
samePercent.append(codon);
mouseOver.toString(), ' ', pid);
}
}
+
+ /**
+ * Returns the number of decimal places to show for profile percentages. For
+ * less than 100 sequences, returns zero (the integer percentage value will be
+ * displayed). For 100-999 sequences, returns 1, for 1000-9999 returns 2, etc.
+ *
+ * @param nseq
+ * @return
+ */
+ protected static int getPercentageDp(long nseq)
+ {
+ int scale = 0;
+ while (nseq >= 100)
+ {
+ scale++;
+ nseq /= 10;
+ }
+ return scale;
+ }
}