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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
/*******************************************************************************
*
* 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
* limitations under the License.
*
******************************************************************************/
// @formatter:on
package org.tensorics.core.tensorbacked;
import static org.tensorics.core.util.InstantiatorType.CONSTRUCTOR;
import static org.tensorics.core.util.Instantiators.instantiatorFor;
import java.util.ArrayList;
import java.util.List;
import java.util.Set;
import org.tensorics.core.tensor.Tensor;
import org.tensorics.core.tensorbacked.annotation.Dimensions;
import com.google.common.collect.ImmutableSet;
/**
* This class gives an access to the methods for {@link Tensorbacked} object support.
*
* @author agorzaws, kfuchsbe
*/
public final class TensorbackedInternals {
private TensorbackedInternals() {
/* Only static methods */
}
/**
* Retrieves the dimensions from the given class inheriting from tensor backed. This is done by inspecting the
* {@link Dimensions} annotation.
*
* @param tensorBackedClass the class for which to determine the dimensions
* @return the set of dimentions (classses of coordinates) which are required to create an instance of the given
* class.
*/
public static Set> dimensionsOf(Class> tensorBackedClass) {
Dimensions dimensionAnnotation = tensorBackedClass.getAnnotation(Dimensions.class);
if (dimensionAnnotation == null) {
throw new IllegalArgumentException("No annotation of type '" + Dimensions.class
+ "' is present on the class '" + tensorBackedClass
+ "'. Therefore, the dimensions of this tensorbacked type cannot be determined.");
}
return ImmutableSet.copyOf(dimensionAnnotation.value());
}
/**
* Creates an instance of a class backed by a tensor.
*
* @param tensorBackedClass the type of the class for which to create an instance.
* @param tensor the tensor to back the instance
* @return a new instance of the given class, backed by the given tensor
*/
public static > T createBackedByTensor(Class tensorBackedClass, Tensor tensor) {
verifyDimensions(tensorBackedClass, tensor);
return instantiatorFor(tensorBackedClass).ofType(CONSTRUCTOR).withArgumentType(Tensor.class).create(tensor);
}
private static , V> void verifyDimensions(Class tensorBackedClass, Tensor tensor) {
Set> targetDimensions = dimensionsOf(tensorBackedClass);
Set> tensorDimensions = tensor.shape().dimensionSet();
if (!targetDimensions.equals(tensorDimensions)) {
throw new IllegalArgumentException("Dimensions of target class (" + targetDimensions
+ ") do not match dimensions of given tensor (" + tensorDimensions + "). Cannot create object.");
}
}
public static Iterable> tensorsOf(Iterable> tensorbackeds) {
List> tensors = new ArrayList<>();
for (Tensorbacked tensorbacked : tensorbackeds) {
tensors.add(tensorbacked.tensor());
}
return tensors;
}
}