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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.
// @formatter:off
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*
* This file is part of tensorics.
*
* 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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package org.tensorics.core.resolve.engine;
import org.tensorics.core.commons.options.OptionRegistry;
import org.tensorics.core.resolve.options.ResolvingOption;
import org.tensorics.core.tree.domain.Node;
import org.tensorics.core.tree.domain.ResolvingContext;
/**
* An implementation of this interface is responsible for processing a tree of instruction nodes and resolving as many
* nodes as possible within one resolver.
*
* The actual algorithm to accomplish this task depends on the implementation.
*
* @author kfuchsbe
*/
public interface Dispatcher {
/**
* process the tree, starting from the given node and resolve as many nodes as possible.
*
* @param rootNode the node which shall be considered as root node of the tree to process
* @param actualContext the current state of the context, which can be used by resolvers to look up some values.
* @param processingOptions
* @return a context which shall contain the resolved values.
*/
ResolvingContext processTree(Node rootNode, ResolvingContext actualContext,
OptionRegistry processingOptions);
}