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/**
 * Copyright (C) 2016 Hurence ([email protected])
 *
 * 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.
 */
package com.caseystella.analytics.distribution.scaling;

import com.caseystella.analytics.distribution.GlobalStatistics;

public class DefaultScalingFunctions {
    public static class ShiftToPositive implements ScalingFunction {

        @Override
        public double scale(double val, GlobalStatistics globalStatistics) {
            if(globalStatistics.getMin() != null) {
                return val + Math.abs(globalStatistics.getMin());
            }
            else {
                throw new RuntimeException("Unable to shift to positive because min is not set.");
            }
        }
    }
    public static class SqueezeToUnit implements ScalingFunction {
        @Override
        public double scale(double val, GlobalStatistics globalStatistics) {
            if(globalStatistics.getMin() != null && globalStatistics.getMax() != null) {
                return (val - globalStatistics.getMin())/(globalStatistics.getMax() - globalStatistics.getMin());
            }
            throw new RuntimeException("Unable to squeeze to [0,1] because either min or max isn't specified");
        }
    }
    public static class FixedMeanUnitVariance implements ScalingFunction {

        @Override
        public double scale(double val, GlobalStatistics stats) {
            if(stats.getMin() != null && stats.getMax() != null && stats.getMean() != null && stats.getStddev() != null) {
                double projectedValue = (val - stats.getMean()) / stats.getStddev();
                double projectedMin = (stats.getMin() - stats.getMean())/stats.getStddev();
                //I KNOW that this isn't really E[X] = 0, sqrt(V[X]) = 1, but I have to scale to positive.
                return projectedValue + Math.abs(projectedMin);
            }
            throw new RuntimeException("Unable to scale to 0 mean, unit variance and then shift positive because we require min, max, mean and stddev to be globally known");
        }
    }
    public static class ZeroMeanUnitVariance implements ScalingFunction {

        @Override
        public double scale(double val, GlobalStatistics stats) {
            if(stats.getMin() != null && stats.getMax() != null && stats.getMean() != null && stats.getStddev() != null) {
                return (val - stats.getMean()) / stats.getStddev();
            }
            throw new RuntimeException("Unable to scale to 0 mean, unit variance and then shift positive because we require min, max, mean and stddev to be globally known");
        }
    }
}