e2fd0b5699c69be501f52c54e0454b610e8110bd,src/main/java/rapaio/core/tests/ZTestTwoSamples.java,ZTestTwoSamples,ZTestTwoSamples,#Var#Var#number#number#number#number#HTTools.Alternative#,65

Before Change


        this.sl = sl;
        this.alt = alt;

        xComplete = x.stream().complete().toMappedVar();
        yComplete = y.stream().complete().toMappedVar();

        if (xComplete.rowCount() < 1 || yComplete.rowCount() < 1) {
            // nothing to do
            xSampleMean = Double.NaN;
            ySampleMean = Double.NaN;
            sampleMean = Double.NaN;

            zScore = Double.NaN;
            pValue = Double.NaN;
            ciLow = Double.NaN;
            ciHigh = Double.NaN;

            return;
        }

        xSampleMean = mean(xComplete).value();
        ySampleMean = mean(yComplete).value();
        sampleMean = xSampleMean - ySampleMean;

        double xv = xSd * xSd / xComplete.rowCount();
        double yv = ySd * ySd / yComplete.rowCount();

        double sv = Math.sqrt(xv + yv);

        zScore = (sampleMean - mu) / sv;

        Normal normal = new Normal(0, 1);
        switch (alt) {
            case GREATER_THAN:
                pValue = 1 - normal.cdf(zScore);
                break;
            case LESS_THAN:
                pValue = normal.cdf(zScore);
                break;
            default:
                pValue = normal.cdf(-Math.abs(zScore)) * 2;
        }

        ciLow = new Normal(sampleMean, sv).quantile(sl / 2);
        ciHigh = new Normal(sampleMean, sv).quantile(1 - sl / 2);
    }

    @Override

After Change


        this.sl = sl;
        this.alt = alt;

        Var xComplete = x.stream().complete().toMappedVar();
        Var yComplete = y.stream().complete().toMappedVar();

        if (xComplete.rowCount() < 1 || yComplete.rowCount() < 1) {
            // nothing to do
            sampleMean = Double.NaN;
            xSampleMean = Double.NaN;
            ySampleMean = Double.NaN;
            xSampleSize = -1;
            ySampleSize = -1;

            zScore = Double.NaN;
            pValue = Double.NaN;
            ciLow = Double.NaN;
            ciHigh = Double.NaN;

            return;
        }

        xSampleMean = mean(xComplete).value();
        xSampleSize = xComplete.rowCount();
        ySampleMean = mean(yComplete).value();
        ySampleSize = yComplete.rowCount();
        sampleMean = xSampleMean - ySampleMean;