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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.
 * 
 * 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.
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// @formatter:on

package org.tensorics.core.testing.hamcrest;

import static com.google.common.base.Preconditions.checkArgument;
import static com.google.common.base.Preconditions.checkNotNull;

import java.util.HashMap;
import java.util.Map;
import java.util.Map.Entry;

import org.hamcrest.Description;
import org.hamcrest.TypeSafeDiagnosingMatcher;
import org.tensorics.core.tensor.Position;
import org.tensorics.core.tensor.Tensor;
import org.tensorics.core.tensor.lang.TensorSupport;

/**
 * A hamcrest matcher for unit tests, that matches a values of a tensor to be within a certain tolerance compared to the
 * values of a reference (expected) tensor. Further, the shapes of the two tensors have to be equal (conform with the
 * {@link org.tensorics.core.tensor.Shape#equals(Object)} method).
 * 
 * @author kfuchsbe
 * @param  the s
 * @see import org.tensorics.core.tensor.Shape
 * @see org.tensorics.core.math.structures.ringlike.Field
 */
public class TensorIsCloseTo extends TypeSafeDiagnosingMatcher> {

    private final TensorSupport support;
    private final Tensor expected;
    private final S tolerance;

    public TensorIsCloseTo(TensorSupport tensoricSupport, Tensor value, S tolerance) {
        super();
        this.support = checkNotNull(tensoricSupport, "tensoricSupport must not be null");
        this.expected = checkNotNull(value, "expected must not be null");
        this.tolerance = checkNotNull(tolerance, "tolerance must not be null");
        checkArgument(support.testIf(tolerance).isGreaterOrEqualTo(support.zero()), "Tolerance must be positive.");
    }

    @Override
    public void describeTo(Description description) {
        description.appendText("within " + tolerance + " close to other tensor.");
    }

    @Override
    protected boolean matchesSafely(Tensor valueToAssert, Description mismatchDescription) {
        if (!valueToAssert.shape().equals(expected.shape())) {
            mismatchDescription.appendText("Shapes are not equal!");
            return false;
        }

        Map> mismatches = mismatches(valueToAssert);
        if (!mismatches.isEmpty()) {
            mismatchDescription.appendText("the following mismatches were detected (position -> value):\n");
            for (Entry> entry : mismatches.entrySet()) {
                Mismatch mismatch = entry.getValue();
                mismatchDescription.appendText(entry.getKey() + " -> " + mismatch.value + " | expected = "
                        + mismatch.expected + ";\n");
            }
            return false;
        }
        return true;

    }

    private Map> mismatches(Tensor valueToAssert) {
        Map> mismatches = new HashMap<>();
        Tensor diff = support.calculate(valueToAssert).minus(expected);
        for (Position position : diff.shape().positionSet()) {
            S absoluteDiff = support.absoluteValueOf(diff.get(position));
            if (!support.testIf(absoluteDiff).isLessOrEqualTo(tolerance)) {
                mismatches.put(position, new Mismatch(expected.get(position), valueToAssert.get(position)));
            }
        }
        return mismatches;
    }

    private static class Mismatch {
        private final S expected;
        private final S value;

        public Mismatch(S expected, S actual) {
            super();
            this.expected = expected;
            this.value = actual;
        }

    }

}