Renaming openecomp to onap

Issue-ID: AAI-208
Change-Id: I2bd02287bed376111156aca0100e2b7b74e368e3
Signed-off-by: Arul.Nambi <arul.nambi@amdocs.com>

1 files changed, 0 insertions, 284 deletions

diff --git a/src/main/java/org/openecomp/sparky/analytics/HistogramSampler.java b/src/main/java/org/openecomp/sparky/analytics/HistogramSampler.java
deleted file mode 100644
index 029ed95..0000000
--- a/src/main/java/org/openecomp/sparky/analytics/HistogramSampler.java
+++ /dev/null
@@ -1,284 +0,0 @@
-/**
- * ============LICENSE_START=======================================================
- * org.onap.aai
- * ================================================================================
- * Copyright © 2017 AT&T Intellectual Property. All rights reserved.
- * Copyright © 2017 Amdocs
- * ================================================================================
- * Licensed under the Apache License, Version 2.0 (the "License");
- * you may not use this file except in compliance with the License.
- * You may obtain a copy of the License at
- *
- *       http://www.apache.org/licenses/LICENSE-2.0
- *
- * Unless required by applicable law or agreed to in writing, software
- * distributed under the License is distributed on an "AS IS" BASIS,
- * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- * See the License for the specific language governing permissions and
- * limitations under the License.
- * ============LICENSE_END=========================================================
- *
- * ECOMP is a trademark and service mark of AT&T Intellectual Property.
- */
-package org.openecomp.sparky.analytics;
-
-/**
- * A class that models a histogram for reporting and tracking long values with variable steps, bins,
- * and floating point accuracy.
- * 
- * @author davea.
- */
-public final class HistogramSampler {
-
-  private String label;
-
-  private long binMaxValue;
-
-  private int numBins;
-
-  private double stepSize;
-
-  private long sampleValueTotal;
-
-  private long minValue = -1;
-
-  private long maxValue = 0;
-
-  private long numSamples = 0;
-
-  private long decimalPointAccuracy = 0;
-
-  private static String FORMAT_FLOAT_TEMPLATE = "%%.%df";
-
-  private String floatFormatStr;
-
-  private long[] histogramBins;
-
-  /**
-   * Instantiates a new histogram sampler.
-   *
-   * @param label the label
-   * @param maxValue the max value
-   * @param numBins the num bins
-   * @param decimalPointAccuracy the decimal point accuracy
-   */
-  public HistogramSampler(String label, long maxValue, int numBins, int decimalPointAccuracy) {
-    this.label = label;
-    this.binMaxValue = maxValue;
-    this.numBins = numBins;
-    this.stepSize = ((double) binMaxValue / (double) numBins);
-    this.decimalPointAccuracy = decimalPointAccuracy;
-    this.floatFormatStr = String.format(FORMAT_FLOAT_TEMPLATE, this.decimalPointAccuracy);
-
-    /*
-     * [numBins + 1] => last bin is catch-all for outliers
-     */
-
-    initializeHistogramBins(numBins + 1);
-
-  }
-
-  /**
-   * Initialize histogram bins.
-   *
-   * @param numBins the num bins
-   */
-  private void initializeHistogramBins(int numBins) {
-
-    histogramBins = new long[numBins];
-    int counter = 0;
-    while (counter < numBins) {
-      histogramBins[counter] = 0;
-      counter++;
-    }
-
-  }
-
-  /*
-   * Is it really necessary to synchronize the collection, or should we simply switch the underlying
-   * data type to an AtomicLong
-   */
-
-  /**
-   * Track.
-   *
-   * @param value the value
-   */
-  public synchronized void track(long value) {
-
-    if (value < 0) {
-      return;
-    }
-
-    sampleValueTotal += value;
-    numSamples++;
-
-    if (minValue == -1) {
-      minValue = value;
-    }
-
-    if (value < minValue) {
-      minValue = value;
-    }
-
-    if (value > maxValue) {
-      maxValue = value;
-    }
-
-    /*
-     * One step bin determination
-     */
-
-    if (value < (numBins * stepSize)) {
-
-      int index = (int) (value / stepSize);
-      histogramBins[index]++;
-
-    } else {
-      // peg the metric in the outlier bin
-      histogramBins[numBins - 1]++;
-    }
-
-  }
-
-  /**
-   * Clear.
-   */
-  public void clear() {
-
-    int counter = 0;
-    while (counter < numBins) {
-      histogramBins[counter] = 0;
-      counter++;
-    }
-
-    minValue = -1;
-    maxValue = 0;
-    numSamples = 0;
-    sampleValueTotal = 0;
-
-  }
-
-  /**
-   * Re initialize bins.
-   *
-   * @param label the label
-   * @param numBins the num bins
-   * @param maxValue the max value
-   * @param decimalPointAccuracy the decimal point accuracy
-   */
-  public void reInitializeBins(String label, int numBins, long maxValue, int decimalPointAccuracy) {
-    this.label = label;
-    this.decimalPointAccuracy = decimalPointAccuracy;
-    this.floatFormatStr = String.format(FORMAT_FLOAT_TEMPLATE, this.decimalPointAccuracy);
-    this.numBins = numBins;
-    this.minValue = -1;
-    this.maxValue = 0;
-    initializeHistogramBins(numBins);
-    this.stepSize = (maxValue / numBins);
-    clear();
-  }
-
-  public long getNumberOfSamples() {
-    return numSamples;
-  }
-
-  public long getTotalValueSum() {
-    return sampleValueTotal;
-  }
-
-  /**
-   * Gets the stats.
-   *
-   * @param formatted the formatted
-   * @param indentPadding the indent padding
-   * @return the stats
-   */
-  public String getStats(boolean formatted, String indentPadding) {
-
-    StringBuilder sb = new StringBuilder(128);
-
-
-    if (!formatted) {
-      // generate CSV in the following format
-
-      /*
-       * label,minValue,maxValue,avgValue,numSamples,stepSize,numSteps,stepCounters
-       */
-      sb.append(indentPadding);
-      sb.append(label).append(",");
-      sb.append(minValue).append(",");
-      sb.append(maxValue).append(",");
-      if (numSamples == 0) {
-        sb.append(0).append(",");
-      } else {
-        sb.append((sampleValueTotal / numSamples)).append(",");
-      }
-      sb.append(numSamples).append(",");
-      sb.append(numBins).append(",");
-      sb.append(String.format(floatFormatStr, stepSize));
-
-      int counter = 0;
-      while (counter < numBins) {
-
-        if (counter != (numBins)) {
-          sb.append(",");
-        }
-
-        sb.append(histogramBins[counter]);
-
-        counter++;
-
-      }
-
-      return sb.toString();
-
-    }
-
-    sb.append("\n");
-    sb.append(indentPadding).append("Label = ").append(label).append("\n");
-    sb.append(indentPadding).append("Min = ").append(minValue).append("\n");
-    sb.append(indentPadding).append("Max = ").append(maxValue).append("\n");
-    sb.append(indentPadding).append("numSamples = ").append(numSamples).append("\n");
-
-    if (numSamples == 0) {
-      sb.append(indentPadding).append("Avg = ").append(0).append("\n");
-    } else {
-      sb.append(indentPadding).append("Avg = ").append((sampleValueTotal / numSamples))
-          .append("\n");
-    }
-
-    sb.append(indentPadding).append("StepSize = ").append(String.format(floatFormatStr, stepSize))
-        .append("\n");
-
-    sb.append(indentPadding).append("Sample Histogram:").append("\n");
-
-    int counter = 0;
-    while (counter < numBins) {
-
-      if (counter == (numBins - 1)) {
-        // outlier bin
-        double leftBound = (stepSize * counter);
-        sb.append(indentPadding).append("\t")
-            .append(" x >= " + String.format(floatFormatStr, leftBound) + " : " 
-                + histogramBins[counter])
-            .append("\n");
-
-      } else {
-        double leftBound = (stepSize * counter);
-        double rightBound = ((stepSize) * (counter + 1));
-        sb.append(indentPadding).append("\t")
-            .append((String.format(floatFormatStr, leftBound) + " < x < "
-                + String.format(floatFormatStr, rightBound) + " : " + histogramBins[counter]))
-            .append("\n");
-      }
-
-      counter++;
-
-    }
-
-    return sb.toString();
-
-  }
-
-}