Merge pull request #286 from JalenEvans/TrailingDigitsTest

countOfTrailingDigits() Bug Fix

TripoliCore/src/main/java/org/cirdles/tripoli/utilities/mathUtilities/FormatterForSigFigN.java

@@ -18,17 +18,43 @@ public class FormatterForSigFigN {
      */
     public static int countOfTrailingDigitsForSigFig(double standardError, int sigFig) {
         int countOfTrailingDigitsForSigFig = 0;
-        if (Math.abs(standardError) < 10.0) {
+        if (Math.abs(standardError) < 10.0 && Math.abs(standardError) > 0.0) {
             double rounded = MathUtilities.roundedToSize(standardError, sigFig);
-            DecimalFormat df = new DecimalFormat("#");
+            String pattern = generatePattern(rounded, sigFig);
+            DecimalFormat df = new DecimalFormat(pattern);
             df.setMaximumFractionDigits(8);
             String roundedString = df.format(rounded);
-            int dotIndex = roundedString.indexOf(".");
-            countOfTrailingDigitsForSigFig = Math.max(roundedString.length() - dotIndex - 1, sigFig);
+            int scale = roundedString.split("\\.")[1].length();
+            countOfTrailingDigitsForSigFig = scale;
         }
         return countOfTrailingDigitsForSigFig;
     }
 
+    /**
+     * Generates a DecimalFormat pattern that allows for a certain amount of trailing zeros specified by
+     * the amount of significant figures
+     * @param rounded
+     * @return String pattern to be used in DecimalFormat
+     */
+    public static String generatePattern(double rounded, int sigFig) {
+        String pattern = "#.";
+        if (Double.isFinite(rounded)) {
+            // Converts the decimal value to a BigDecimal to find the scale
+            BigDecimal valueBD = new BigDecimal(String.valueOf(rounded));
+            int scale = sigFig - (valueBD.precision() - valueBD.scale());
+
+            // Allows for a trailing zero in each decimal place within the scale
+            for (int i = 0; i < scale; i++) {
+                pattern += "0";
+            }
+
+            return pattern;
+        }
+
+        // Returns default pattern if rounded number is infinite
+        return "#";
+    }
+
     /**
      * see https://docs.google.com/document/d/14PPEDEJPylNMavpJDpYSuemNb0gF5dz_To3Ek1Y_Agw/edit#bookmark=id.bf8wjg6paqcw
      *

TripoliCore/src/main/java/org/cirdles/tripoli/utilities/mathUtilities/MathUtilities.java

@@ -64,7 +64,7 @@ public static int nChooseR(int n, int r) {
 
     /**
      * see https://docs.google.com/document/d/14PPEDEJPylNMavpJDpYSuemNb0gF5dz_To3Ek1Y_Agw/edit#bookmark=id.k016qg1ghequ
-     * seehttps://www.lexjansen.com/wuss/2007/DatabaseMgtWarehousing/DMW_Lin_CleaningData.pdf
+     * see https://www.lexjansen.com/wuss/2007/DatabaseMgtWarehousing/DMW_Lin_CleaningData.pdf
      *
      * @param dataIn
      * @return
@@ -76,12 +76,14 @@ public static boolean[] applyChauvenetsCriterion(double[] dataIn, boolean[] incl
 
         For now, assume a default value of ChauvenetRejectionProbability = 0.5.  In the future, we can ask the user to input
         this constant (must be on [0,1]), but I’ve never heard of anyone using a different value than 0.5.
+        ***
         Assemble the data to evaluate into a vector called data. Do not include cycles and blocks previously rejected by the user in the data vector.
         The number of elements in data is n
         Calculate the mean and standard deviation of data, xbar and stddev.
         For each element of data, calculate absZ_i = abs(data_i - xbar) / stddev where abs() is the absolute value
         Calculate Chauvenet’s criterion, C_i = n * erfc(absZ_i) for each absZ_i
         Identify all data with C_i > ChauvenetRejectionProbability as an outlier by Chauvenet’s Criterion
+        ***
         Plot Chauvenet-identified outliers in red and recalculate all statistics after rejecting the identified outliers.
         Gray out the Chauvenet button so that it can’t be re-applied.
          */

TripoliCore/src/test/java/org/cirdles/tripoli/utilities/mathUtilities/MathUtilitiesTest.java

@@ -1,11 +1,43 @@
 package org.cirdles.tripoli.utilities.mathUtilities;
 
+import org.junit.jupiter.api.AfterEach;
+import org.junit.jupiter.api.BeforeEach;
 import org.junit.jupiter.api.Test;
 
+import static org.junit.jupiter.api.Assertions.assertArrayEquals;
 import static org.junit.jupiter.api.Assertions.assertEquals;
 
+import org.apache.commons.math3.stat.descriptive.DescriptiveStatistics;
+import static org.apache.commons.math3.special.Erf.erfc;
+import com.google.common.math.Stats;
+
 class MathUtilitiesTest {
 
+    double[] arr;
+    boolean[] indices;
+
+    boolean[] solvedIndices;
+
+    @BeforeEach
+    /**
+     * Created a data set of double values
+     *
+     * Document the process of using the python script and mention the imports used
+     */
+    void setUp() {
+        //Create an array of doubles
+        arr = new double[] {47.3, 50.5, 53.7, 55.8, 55.0, 56.0001, 57.0012345678, 57.004999, 58.153, 58.852, 58.123, 58.543, 60.415, 60.794, 60.351,
+                61.751, 61.652, 61.325, 61.587, 61.126, 61.897, 62.543, 62.258, 62.689, 63.5473, 63.789, 64.369, 67.115, 68.142, 72.368};
+        indices = new boolean[] {true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true};
+
+
+        solvedIndices = new boolean[] {false, false, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, false};
+    }
+
+    @AfterEach
+    void tearDown() {
+    }
+
     @Test
     void roundedToSize() {
 
@@ -30,4 +62,64 @@ void nChooseR() {
         assertEquals(20, MathUtilities.nChooseR(6, 3)); // n=6, r=3
         assertEquals(252, MathUtilities.nChooseR(10, 5)); // n=10, r=5
     }
+
+    @Test
+    void applyChauvenetsCriterion() {
+        assertArrayEquals(solvedIndices, MathUtilities.applyChauvenetsCriterion(arr, indices));
+    }
+
+    @Test
+    void testDescriptiveStatistics() {
+        //Add all data points to Descriptive Statistics (descStats)
+        DescriptiveStatistics descStats = new DescriptiveStatistics();
+        for (int i = 0; i < arr.length; i++) {
+            descStats.addValue(arr[i]);
+        }
+
+        //Add all data points to Stats (stats)
+        Stats stats = Stats.of(arr);
+
+        //Compare their respective methods
+        assertEquals(descStats.getMean(), stats.mean(), 0.000000000001);
+        assertEquals(descStats.getStandardDeviation(), stats.sampleStandardDeviation(), 0.00000000001);
+    }
+
+    @Test
+    void testRoundedToSize() {
+        int sigFigs = 4;
+
+        double[] nums = {6.1542565, 2.36489, 8.9125, 0.025483, 10.5475, 103.2578, 0.00012563, 0.2000, 0.0000, 2.0, 3};
+
+        double[] actual = new double[nums.length];
+
+        double[] expected = {6.154,2.365,8.913,0.02548,10.55,103.3,0.0001256,0.2000,0.0000,2.000,3.000}; // Iff sigFigs is equal to 4
+
+        for (int i = 0; i < nums.length; i++) {
+            actual[i] = MathUtilities.roundedToSize(nums[i], sigFigs);
+        }
+
+        assertArrayEquals(expected, actual);
+    }
+
+
+    @Test
+    void testCountOfTrailingDigits() {
+        int sigFigs = 4;
+
+        /*
+        Conditions for a Good Set of Numbers: Include Whole Integers, Numbers with Trailing Zeros, Numbers with Leading Zeros,
+        Numbers greater than 10, Numbers less than 10, Numbers with Spurious Digits, Numbers with 0s in between Non-Zero digits,
+
+         */
+        double[] nums = {6.1542565, 2.30089, 8.9125, 0.025483, 10.5475, 103.2578, 0.00012563, 0.2000, 0.0000, 2.0, 3};
+        double[] actual = new double[nums.length];
+
+        double[] expected = {3,3,3,5,0,0,7,4,0,3,3}; // Iff sigFigs is equal to 4
+
+        for (int i = 0; i < nums.length; i++) {
+            actual[i] = FormatterForSigFigN.countOfTrailingDigitsForSigFig(nums[i], sigFigs);
+        }
+
+        assertArrayEquals(expected, actual);
+    }
 }