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authorGravatar Abseil Team <absl-team@google.com>2022-09-12 16:04:42 -0700
committerGravatar Copybara-Service <copybara-worker@google.com>2022-09-12 16:05:39 -0700
commit5a547f8bbd310850bb8123446110730abafdad56 (patch)
tree3407227cb7ea1bac60e341c42cf5da32a3ed6ff1 /absl/profiling
parent0a066f31d981d69f7bde961055691906dabd4a3c (diff)
Fix "unsafe narrowing" warnings in absl, 8/n.
Addresses failures with the following, in some files: -Wshorten-64-to-32 -Wimplicit-int-conversion -Wsign-compare -Wsign-conversion -Wtautological-unsigned-zero-compare (This specific CL focuses on .cc files in */internal/.) Bug: chromium:1292951 PiperOrigin-RevId: 473868797 Change-Id: Ibe0b76e33f9e001d59862beaac54fb47bacd39b2
Diffstat (limited to 'absl/profiling')
-rw-r--r--absl/profiling/internal/exponential_biased_test.cc20
1 files changed, 11 insertions, 9 deletions
diff --git a/absl/profiling/internal/exponential_biased_test.cc b/absl/profiling/internal/exponential_biased_test.cc
index 6a6c317e..ebfbcad4 100644
--- a/absl/profiling/internal/exponential_biased_test.cc
+++ b/absl/profiling/internal/exponential_biased_test.cc
@@ -94,13 +94,14 @@ double AndersonDarlingPValue(int n, double z) {
}
double AndersonDarlingStatistic(const std::vector<double>& random_sample) {
- int n = random_sample.size();
+ size_t n = random_sample.size();
double ad_sum = 0;
- for (int i = 0; i < n; i++) {
+ for (size_t i = 0; i < n; i++) {
ad_sum += (2 * i + 1) *
std::log(random_sample[i] * (1 - random_sample[n - 1 - i]));
}
- double ad_statistic = -n - 1 / static_cast<double>(n) * ad_sum;
+ const auto n_as_double = static_cast<double>(n);
+ double ad_statistic = -n_as_double - 1 / n_as_double * ad_sum;
return ad_statistic;
}
@@ -111,14 +112,15 @@ double AndersonDarlingStatistic(const std::vector<double>& random_sample) {
// Marsaglia and Marsaglia for details.
double AndersonDarlingTest(const std::vector<double>& random_sample) {
double ad_statistic = AndersonDarlingStatistic(random_sample);
- double p = AndersonDarlingPValue(random_sample.size(), ad_statistic);
+ double p = AndersonDarlingPValue(static_cast<int>(random_sample.size()),
+ ad_statistic);
return p;
}
TEST(ExponentialBiasedTest, CoinTossDemoWithGetSkipCount) {
ExponentialBiased eb;
for (int runs = 0; runs < 10; ++runs) {
- for (int flips = eb.GetSkipCount(1); flips > 0; --flips) {
+ for (int64_t flips = eb.GetSkipCount(1); flips > 0; --flips) {
printf("head...");
}
printf("tail\n");
@@ -132,7 +134,7 @@ TEST(ExponentialBiasedTest, CoinTossDemoWithGetSkipCount) {
TEST(ExponentialBiasedTest, SampleDemoWithStride) {
ExponentialBiased eb;
- int stride = eb.GetStride(10);
+ int64_t stride = eb.GetStride(10);
int samples = 0;
for (int i = 0; i < 10000000; ++i) {
if (--stride == 0) {
@@ -147,7 +149,7 @@ TEST(ExponentialBiasedTest, SampleDemoWithStride) {
// Testing that NextRandom generates uniform random numbers. Applies the
// Anderson-Darling test for uniformity
TEST(ExponentialBiasedTest, TestNextRandom) {
- for (auto n : std::vector<int>({
+ for (auto n : std::vector<size_t>({
10, // Check short-range correlation
100, 1000,
10000 // Make sure there's no systemic error
@@ -161,7 +163,7 @@ TEST(ExponentialBiasedTest, TestNextRandom) {
}
std::vector<uint64_t> int_random_sample(n);
// Collect samples
- for (int i = 0; i < n; i++) {
+ for (size_t i = 0; i < n; i++) {
int_random_sample[i] = x;
x = ExponentialBiased::NextRandom(x);
}
@@ -169,7 +171,7 @@ TEST(ExponentialBiasedTest, TestNextRandom) {
std::sort(int_random_sample.begin(), int_random_sample.end());
std::vector<double> random_sample(n);
// Convert them to uniform randoms (in the range [0,1])
- for (int i = 0; i < n; i++) {
+ for (size_t i = 0; i < n; i++) {
random_sample[i] =
static_cast<double>(int_random_sample[i]) / max_prng_value;
}