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-// Copyright 2017 The Abseil Authors.
-//
-// 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
-//
-//      https://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.
-
-#ifndef ABSL_RANDOM_INTERNAL_CHI_SQUARE_H_
-#define ABSL_RANDOM_INTERNAL_CHI_SQUARE_H_
-
-// The chi-square statistic.
-//
-// Useful for evaluating if `D` independent random variables are behaving as
-// expected, or if two distributions are similar.  (`D` is the degrees of
-// freedom).
-//
-// Each bucket should have an expected count of 10 or more for the chi square to
-// be meaningful.
-
-#include <cassert>
-
-#include "absl/base/config.h"
-
-namespace absl {
-ABSL_NAMESPACE_BEGIN
-namespace random_internal {
-
-constexpr const char kChiSquared[] = "chi-squared";
-
-// Returns the measured chi square value, using a single expected value.  This
-// assumes that the values in [begin, end) are uniformly distributed.
-template <typename Iterator>
-double ChiSquareWithExpected(Iterator begin, Iterator end, double expected) {
-  // Compute the sum and the number of buckets.
-  assert(expected >= 10);  // require at least 10 samples per bucket.
-  double chi_square = 0;
-  for (auto it = begin; it != end; it++) {
-    double d = static_cast<double>(*it) - expected;
-    chi_square += d * d;
-  }
-  chi_square = chi_square / expected;
-  return chi_square;
-}
-
-// Returns the measured chi square value, taking the actual value of each bucket
-// from the first set of iterators, and the expected value of each bucket from
-// the second set of iterators.
-template <typename Iterator, typename Expected>
-double ChiSquare(Iterator it, Iterator end, Expected eit, Expected eend) {
-  double chi_square = 0;
-  for (; it != end && eit != eend; ++it, ++eit) {
-    if (*it > 0) {
-      assert(*eit > 0);
-    }
-    double e = static_cast<double>(*eit);
-    double d = static_cast<double>(*it - *eit);
-    if (d != 0) {
-      assert(e > 0);
-      chi_square += (d * d) / e;
-    }
-  }
-  assert(it == end && eit == eend);
-  return chi_square;
-}
-
-// ======================================================================
-// The following methods can be used for an arbitrary significance level.
-//
-
-// Calculates critical chi-square values to produce the given p-value using a
-// bisection search for a value within epsilon, relying on the monotonicity of
-// ChiSquarePValue().
-double ChiSquareValue(int dof, double p);
-
-// Calculates the p-value (probability) of a given chi-square value.
-double ChiSquarePValue(double chi_square, int dof);
-
-}  // namespace random_internal
-ABSL_NAMESPACE_END
-}  // namespace absl
-
-#endif  // ABSL_RANDOM_INTERNAL_CHI_SQUARE_H_