Merge pull request #7 from mrmaxent/predict-noclamp

Predict noclamp

density/CachedFeature.java

@@ -24,16 +24,16 @@ a copy of this software and associated documentation files (the
 package density;
 
 class CachedFeature extends Feature {
-    float[] vals=null;
+    double[] vals=null;
     Feature f;
 
     public CachedFeature(Feature f) {
 	this.f = f;
 	name = f.name;
 	n = f.n;
-	vals = new float[n];
+	vals = new double[n];
 	for (int p=0; p<n; p++)
-	    vals[p] = (float) f.eval(p);
+	    vals[p] = f.eval(p);
     }
 
     public double eval(int p) { return vals[p]; }

density/Project.java

@@ -291,6 +291,7 @@ boolean wouldExtrapolate(int r, int c) {
 		}
 
 		public float eval(int r, int c) {
+		    doClamp = is("doClamp");
 		    double pred = predclamp = pred(r, c, true);
 		    if (doClamp) {
 			doClamp = false;

density/Runner.java

@@ -1238,14 +1238,14 @@ Feature[] featuresWithSamples(Feature[] f, Sample[] ss) {
 	double[] backgroundHash = new double[f[0].n];
 	for (int i=0; i<f[0].n; i++)
 	    for (int j=0; j<f.length; j++) 
-		backgroundHash[i] += rnd[j] * (float) f[j].eval(i);
+		backgroundHash[i] += rnd[j] * f[j].eval(i);
 	Arrays.sort(backgroundHash);
 	ArrayList samplesToAdda = new ArrayList();
 	for (int i=0; i<ss.length; i++) {
 	    double r = 0.0;
 	    for (int j=0; j<f.length; j++)
 		if (f[j].hasData(ss[i]))
-		    r += rnd[j] * (float) f[j].eval(ss[i]);
+		    r += rnd[j] * f[j].eval(ss[i]);
 	    if (is("addAllSamplesToBackground") || Arrays.binarySearch(backgroundHash, r) < 0)  // not found
 		samplesToAdda.add(ss[i]);
 	}

density/SampleSet2.java

@@ -162,12 +162,12 @@ public void process() {
 		    Sample s = new Sample(-1, r, c, y, x, spid, null);
 
 		    int goodvals = 0;
-		    float[] data = new float[n];
+		    double[] data = new double[n];
 		    for (int j=0; j<n; j++) {
 			int idx = layerToColumn[j];
 			data[j] = NODATA_value;
 			if (idx!=-1 && idx<fields.length && !fields[SampleSet.firstEnvVar+idx].trim().equals("")) 
-			    data[j] = Float.parseFloat(fields[SampleSet.firstEnvVar+idx]);
+			    data[j] = Double.parseDouble(fields[SampleSet.firstEnvVar+idx]);
 			if (data[j] == NODATA_value && idx!=-1) {
 			    warnPartialData(x,y,sampleFileName,layers[j].name);
                             if (!params.allowpartialdata())
@@ -204,7 +204,7 @@ static void warnPartialData(double x, double y, String sampleFileName, String fi
     public void createMaps() {
 	Sample[] s = getSamples();
 	for (int i=0; i<s.length; i++) {
-	    float[] data = (float[]) datamap.get(s[i]);
+	    double[] data = (double[]) datamap.get(s[i]);
 	    HashMap map = new HashMap();
 	    for (int j=0; j<n; j++)
 		map.put(layers[j].getName(), (data[j]==SampleSet.NODATA_value) ? null : new Double(data[j]));

density/Utils.java

@@ -32,7 +32,7 @@ a copy of this software and associated documentation files (the
 
 public class Utils {
 
-    static String version = "3.4.1";
+    static String version = "3.4.3";
     static boolean interrupt=false, warnings=true;
     public static boolean verbose=false, visible=true;
     static JFrame topLevelFrame = null;

readme.txt

@@ -7,7 +7,7 @@ Miro Dudik          ([email protected])
 Steven Phillips     ([email protected])
 Rob Schapire        ([email protected])
 
-Version 3.4.1, April 2017
+Version 3.4.3, November 2020
 
 This file outlines the steps you should take to begin using maxent to
 model species geographic distributions.  To download the program, or
@@ -118,6 +118,16 @@ click on the maxent.bat file instead.  If this is not the problem,
 click on the "help" button for more advice.
 
 
+Main Changes in Version 3.4.3:
+-----------------------------
+   Fixed a bug that was causing abrupt changes in response curves for some floating -point predictor variables,
+     due to the "add samples to background" option not adding all samples for floating-point predictors.
+
+Main Changes in Version 3.4.2:
+-----------------------------
+   Fixed bug that causes nodoclamp flag not to work for dismo's predict method for MaxEnt objects
+
+
 Main Changes in Version 3.4.1:
 -----------------------------
    Fixed bug that caused regularization multiplier to be have increasing effect over multiple runs