Merge pull request #4 from nno/nf/user_duration

Nf/user duration

doc/source/about.rst

@@ -3,6 +3,7 @@
 About the authors
 =================
 
+
 + Nikolaas N. Oosterhof (nikolaas `dot` oosterhof `at` unitn `dot` it) is a postdoctoral fellow at the Center for Mind/Brain Sciences, Trento University, Italy.
 + Chris A. Oosterhof (chris `dot` oosterhof `at` theroyal `dot` ca) is a PhD student at the Institute of Mental Health Research, University of Ottowa, Canada.
 

doc/source/conf.py

@@ -54,9 +54,9 @@
 # built documents.
 #
 # The short X.Y version.
-version = '0.40'
+version = '1,0'
 # The full version, including alpha/beta/rc tags.
-release = '0.40'
+release = '1.0'
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.

doc/source/manual.rst

@@ -60,6 +60,7 @@ Burstidator analysis
   + usually this involves double-clicking the ``burstiDAtor.jar`` file.
 
 * Optionally: to switch between burst detection for DA (dopamine), 5HT (serotonin), RTN (reticular thalamic nucleus) or GLU (glutamate) neuron burst detection, click ``type: DA`` / ``type: 5HT`` / ``type: RTN`` / ``type: GLU``.
+* Optionally: to set your own burst detection parameters, select ``User type`` and set three parameters: maximum inter-spike interval to start a burst, maximum inter-spike. and mininum number of spikes to form a burst.
 * Click *Wizard*.
 * Browse to the folder containing the ``*.txt`` output files from Spike2 (see above).
 * Click *open*. BurstiDAtor will display the number of ``*.txt`` files in that folder.

java/burstiDAtor/AutoCorr.java

@@ -7,76 +7,82 @@
 
 public class AutoCorr extends Histogram {
     public AutoCorr(Spikes spikes) {
-	super();
-	int n_spikes = spikes.length();
-
-	Settings settings = Settings.getInstance();
-	SpikeDelta min_isi = SpikeDelta.fromString(settings.getS("autocorr_min"));
-	SpikeDelta max_isi = SpikeDelta.fromString(settings.getS("autocorr_max"));
-	SpikeDelta binwidth = SpikeDelta.fromString(settings.getS("autocorr_binwidth"));
-
-	int n_bins = max_isi.subtract(min_isi).divideCeil(binwidth);
-
-	for (int i = 0; i <= n_bins; i++) {
-	    bins.add((double) i);
-	    if (i<n_bins) {
-	    	counts.add(0);
-	    }
-	}
-
-	if (n_spikes<2) {
-	    return;
-	}
-
-	for (int i = 0; i < n_spikes; i++) {
-	    for (int j = i + 1; j < spikes.length(); j++) {
-		SpikeDelta delta = new SpikeDelta(spikes.get(i), spikes.get(j));
-		int bin = getBin(min_isi, binwidth, delta);
-		boolean too_small = bin < 0;
-		boolean too_large = bin >= n_bins;
-		boolean keep = !(too_small || too_large);
-		if (keep) {
-		    counts.set(bin, 1 + counts.get(bin));
-		}
-		if (too_large) {
-		    break;
-		}
-	    }
-	}
+        super();
+        int n_spikes = spikes.length();
+
+        Settings settings = Settings.getInstance();
+        SpikeDelta min_isi = SpikeDelta
+                .fromString(settings.getS("autocorr_min"));
+        SpikeDelta max_isi = SpikeDelta
+                .fromString(settings.getS("autocorr_max"));
+        SpikeDelta binwidth = SpikeDelta
+                .fromString(settings.getS("autocorr_binwidth"));
+
+        int n_bins = max_isi.subtract(min_isi).divideCeil(binwidth);
+
+        for (int i = 0; i <= n_bins; i++) {
+            bins.add((double) i);
+            if (i < n_bins) {
+                counts.add(0);
+            }
+        }
+
+        if (n_spikes < 2) {
+            return;
+        }
+
+        for (int i = 0; i < n_spikes; i++) {
+            for (int j = i + 1; j < spikes.length(); j++) {
+                SpikeDelta delta = new SpikeDelta(spikes.get(i),
+                        spikes.get(j));
+                int bin = getBin(min_isi, binwidth, delta);
+                boolean too_small = bin < 0;
+                boolean too_large = bin >= n_bins;
+                boolean keep = !(too_small || too_large);
+                if (keep) {
+                    counts.set(bin, 1 + counts.get(bin));
+                }
+                if (too_large) {
+                    break;
+                }
+            }
+        }
     }
 
-    public static int getBin(SpikeDelta t_onset, SpikeDelta binwidth, SpikeDelta t) {
-	int bin = t.subtract(t_onset).divideFloor(binwidth);
-	return bin;
+    public static int getBin(SpikeDelta t_onset, SpikeDelta binwidth,
+            SpikeDelta t) {
+        int bin = t.subtract(t_onset).divideFloor(binwidth);
+        return bin;
     }
 
     public BufferedImage getPlot() {
-	return super.getPlot("time (ms)");
+        return super.getPlot("time (ms)");
     }
 
-
     public static void main(String... unused) throws Exception {
-	String d = "/Users/nick/tmp/";
+        String d = "/Users/nick/tmp/";
 
-	String[] fns = { "neuron 1 651542.txt", "neuron 2 653286.txt", "Neuron 3 653284.txt" };
+        String[] fns = { "neuron 1 651542.txt", "neuron 2 653286.txt",
+                    "Neuron 3 653284.txt" };
 
-	for (int i = 0; i < fns.length; i++) {
+        for (int i = 0; i < fns.length; i++) {
 
-	    String fn = "/Users/nick/tmp/" + fns[i];
-	    File f = new File(fn);
-	    Spikes spikes = new Spikes(f);
-	    AutoCorr ac = new AutoCorr(spikes);
+            String fn = "/Users/nick/tmp/" + fns[i];
+            File f = new File(fn);
+            Spikes spikes = new Spikes(f);
+            AutoCorr ac = new AutoCorr(spikes);
 
-	    BufferedImage img = ac.getPlot();
+            BufferedImage img = ac.getPlot();
 
-	    try {
-		// Save as PNG
-		File file = new File("/Users/nick/tmp/neuron" + (i + 1) + ".png");
-		ImageIO.write(img, "png", file);
+            try {
+                // Save as PNG
+                File file = new File(
+                        "/Users/nick/tmp/neuron" + (i + 1) + ".png");
+                ImageIO.write(img, "png", file);
 
-	    } catch (IOException e) {
-	    }
+            } catch (IOException e) {
+            }
 
-	}
+        }
     }
 }

java/burstiDAtor/Burst.java

@@ -21,8 +21,7 @@ public Burst() {
     /**
      * add a spike to the burst
      *
-     * @param onset
-     *            time of the spike
+     * @param onset time of the spike
      */
     public void add(double onset) {
         onsets.add(onset);
@@ -31,16 +30,14 @@ public void add(double onset) {
     /**
      * Compute statistics for this burst
      *
-     * @param fs
-     *            Optional list of property keys to return. If null or empty
-     *            then all keys are returned.
-     * @return Props instance containing properties of this burst, with a subset
-     *         of the following keys (or all if fs is null or empty): "nSp"
-     *         (number of spikes), "firstSp" (onset of first spike), "lastSp"
-     *         (onset of last spike), "center" (average of first and last
-     *         spike), "BuDur" (duration of the burst), "SpFreq" (spike
-     *         frequency in the burst), and "interSp" (interspike interval in
-     *         the burst).
+     * @param fs Optional list of property keys to return. If null or empty then all
+     *           keys are returned.
+     * @return Props instance containing properties of this burst, with a subset of
+     *         the following keys (or all if fs is null or empty): "nSp" (number of
+     *         spikes), "firstSp" (onset of first spike), "lastSp" (onset of last
+     *         spike), "center" (average of first and last spike), "BuDur" (duration
+     *         of the burst), "SpFreq" (spike frequency in the burst), and "interSp"
+     *         (interspike interval in the burst).
      */
     public Props getStats(String... fs) {
         Props s = new Props();
@@ -61,8 +58,9 @@ public Props getStats(String... fs) {
         s.put("SpFreq", freq);
         s.put("interSp", dur / (double) (n - 1));
 
-        Props r = (fs == null || fs.length == 0 || (fs.length == 1 && fs[0] == null)) ? s
-                : s.filter(fs);
+        Props r = (fs == null || fs.length == 0
+                || (fs.length == 1 && fs[0] == null)) ? s
+                        : s.filter(fs);
         return r;
     }