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Tensorics is a java framework which uses a tensor as a central object. A tensor represents a set of values placed in an N-dimensional space. Wherever you are tempted to use maps of maps, a tensor might be a good choice ;-) Tensorics provides methods to create, transform and performing calculations with those tensors.

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 * This file is part of tensorics.
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 * Copyright (c) 2008-2011, CERN. All rights reserved.
 *
 * 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
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// @formatter:on

package org.tensorics.core.tensor.lang;

import java.util.Set;

import org.tensorics.core.lang.Tensorics;
import org.tensorics.core.tensor.Position;
import org.tensorics.core.tensor.Positions;
import org.tensorics.core.tensor.Positions.DimensionStripper;
import org.tensorics.core.tensor.Tensor;

import com.google.common.collect.ImmutableSetMultimap;
import com.google.common.collect.Multimaps;
import com.google.common.collect.SetMultimap;
import com.google.common.collect.Sets;
import com.google.common.collect.Sets.SetView;

public class OngoingDimensionFlattening {

    private final Tensor tensor;
    private final Set> dimensionsToFlatten;

    public OngoingDimensionFlattening(Tensor tensor, Set> dimensions) {
        super();
        this.tensor = tensor;
        this.dimensionsToFlatten = dimensions;
    }

    public Tensor> intoTensorOfSets() {
        return Tensorics.fromMap(remainingDimensions(), Multimaps.asMap(intoSetMultimap()));
    }

    private SetMultimap intoSetMultimap() {
        ImmutableSetMultimap.Builder builder = ImmutableSetMultimap.builder();
        DimensionStripper dimensionStripper = Positions.stripping(dimensionsToFlatten);
        for (java.util.Map.Entry entry : tensor.asMap().entrySet()) {
            Position newPosition = dimensionStripper.apply(entry.getKey());
            builder.put(newPosition, entry.getValue());
        }
        return builder.build();
    }

    private SetView> remainingDimensions() {
        return Sets.difference(tensor.shape().dimensionSet(), dimensionsToFlatten);
    }

}