Searched refs:histograms (Results 1 - 14 of 14) sorted by relevance

/external/libchrome/base/metrics/
H A Dhistogram_snapshot_manager_unittest.cc83 // kNoFlags filter should record all histograms.
91 const std::vector<std::string>& histograms = local
93 EXPECT_EQ(2U, histograms.size());
94 EXPECT_EQ("UmaHistogram", histograms[0]);
95 EXPECT_EQ("UmaStabilityHistogram", histograms[1]);
107 const std::vector<std::string>& histograms = local
109 EXPECT_EQ(2U, histograms.size());
110 EXPECT_EQ("UmaHistogram", histograms[0]);
111 EXPECT_EQ("UmaStabilityHistogram", histograms[1]);
123 const std::vector<std::string>& histograms local
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H A Dsparse_histogram_unittest.cc24 // for histogram allocation. False will allocate histograms from the process
157 StatisticsRecorder::Histograms histograms; local
158 StatisticsRecorder::GetHistograms(&histograms);
160 ASSERT_EQ(1U, histograms.size());
161 HistogramBase* sparse_histogram = histograms[0];
186 StatisticsRecorder::Histograms histograms; local
187 StatisticsRecorder::GetHistograms(&histograms);
188 ASSERT_EQ(2U, histograms.size());
190 std::string name1 = histograms[0]->histogram_name();
191 std::string name2 = histograms[
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/external/webp/src/enc/
H A Dhistogram_enc.c31 // Maximum number of histograms allowed in greedy combining algorithm.
116 sizeof(*set) + size * (sizeof(*set->histograms) +
123 set->histograms = (VP8LHistogram**)memory;
124 memory += size * sizeof(*set->histograms);
129 set->histograms[i] = (VP8LHistogram*)memory;
131 set->histograms[i]->literal_ = (uint32_t*)(memory + sizeof(VP8LHistogram));
132 VP8LHistogramInit(set->histograms[i], cache_bits);
257 // trivial_at_end is 1 if the two histograms only have one element that is
266 // BitsEntropyRefine is 0 for histograms with only one non-zero value.
472 // Construct the histograms fro
478 VP8LHistogram** const histograms = image_histo->histograms; local
500 VP8LHistogram** const histograms = image_histo->histograms; local
515 VP8LHistogram** const histograms = image_histo->histograms; local
540 VP8LHistogram** const histograms = image_histo->histograms; local
685 HistoQueuePush(HistoQueue* const histo_queue, VP8LHistogram** const histograms, int idx1, int idx2, double threshold) argument
727 VP8LHistogram** const histograms = image_histo->histograms; local
807 VP8LHistogram** const histograms = image_histo->histograms; local
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H A Dhistogram_enc.h12 // Models the histograms of literal and distance codes.
30 // A simple container for histograms of data.
41 uint32_t trivial_symbol_; // True, if histograms for Red, Blue & Alpha
49 // Collection of histograms with fixed capacity, allocated as one
54 VP8LHistogram** histograms; member in struct:__anon30431
82 // Allocate an array of pointer to histograms, allocated and initialized
H A Dvp8l_enc.c251 // Let's add one zero to the predicted histograms. The zeros are removed
464 // Iterate over all histograms and get the aggregate number of codes used.
466 const VP8LHistogram* const histo = histogram_image->histograms[i];
507 VP8LHistogram* const histo = histogram_image->histograms[i];
529 // and more spiking histograms.
818 VP8LHistogramStoreRefs(refs, histogram_image->histograms[0]);
959 // Free combined histograms.
963 // Free scratch histograms.
/external/brotli/c/enc/
H A Dmetablock_inc.h19 /* We merge histograms A and B if
37 /* Offset of the histograms of the previous two block types. */
48 BlockSplit* split, HistogramType** histograms, size_t* histograms_size) {
70 assert(*histograms == 0);
72 *histograms = BROTLI_ALLOC(m, HistogramType, *histograms_size);
73 self->histograms_ = *histograms;
88 HistogramType* histograms = self->histograms_; variable
96 BitsEntropy(histograms[0].data_, self->alphabet_size_);
102 FN(HistogramClear)(&histograms[self->curr_histogram_ix_]);
105 double entropy = BitsEntropy(histograms[sel
45 InitBlockSplitter( MemoryManager* m, FN(BlockSplitter)* self, size_t alphabet_size, size_t min_block_size, double split_threshold, size_t num_symbols, BlockSplit* split, HistogramType** histograms, size_t* histograms_size) argument
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H A Dblock_encoder_inc.h15 const HistogramType* histograms, const size_t histograms_size,
27 BuildAndStoreHuffmanTree(&histograms[i].data_[0], alphabet_size, tree,
14 BuildAndStoreEntropyCodes(MemoryManager* m, BlockEncoder* self, const HistogramType* histograms, const size_t histograms_size, HuffmanTree* tree, size_t* storage_ix, uint8_t* storage) argument
H A Dblock_splitter_inc.h15 HistogramType* histograms) {
19 FN(ClearHistograms)(histograms, num_histograms);
28 FN(HistogramAddVector)(&histograms[i], data + pos, stride);
49 HistogramType* histograms) {
59 FN(HistogramAddHistogram)(&histograms[iter % num_histograms], &sample);
69 const HistogramType* histograms,
88 insert_cost[i] = FastLog2((uint32_t)histograms[i].total_count_);
94 insert_cost[j] - BitCost(histograms[j].data_[i]);
180 HistogramType* histograms) {
182 FN(ClearHistograms)(histograms, num_histogram
12 InitialEntropyCodes(const DataType* data, size_t length, size_t stride, size_t num_histograms, HistogramType* histograms) argument
46 RefineEntropyCodes(const DataType* data, size_t length, size_t stride, size_t num_histograms, HistogramType* histograms) argument
66 FindBlocks(const DataType* data, const size_t length, const double block_switch_bitcost, const size_t num_histograms, const HistogramType* histograms, double* insert_cost, double* cost, uint8_t* switch_signal, uint8_t *block_id) argument
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H A Dmetablock.c162 Gathers histograms for all context buckets. */
170 /* We merge histograms A and B if
188 /* Offset of the histograms of the previous two block types. */
199 size_t num_symbols, BlockSplit* split, HistogramLiteral** histograms,
229 assert(*histograms == 0);
231 *histograms = BROTLI_ALLOC(m, HistogramLiteral, *histograms_size);
232 self->histograms_ = *histograms;
248 HistogramLiteral* histograms = self->histograms_; local
261 BitsEntropy(histograms[i].data_, self->alphabet_size_);
273 /* Try merging the set of histograms fo
196 InitContextBlockSplitter( MemoryManager* m, ContextBlockSplitter* self, size_t alphabet_size, size_t num_contexts, size_t min_block_size, double split_threshold, size_t num_symbols, BlockSplit* split, HistogramLiteral** histograms, size_t* histograms_size) argument
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/external/tensorflow/tensorflow/python/kernel_tests/distributions/
H A Dcategorical_test.py123 histograms = [[0.2, 0.8], [0.6, 0.4]]
124 dist = categorical.Categorical(math_ops.log(histograms) - 50.)
129 histograms = [0.2, 0.8]
130 dist = categorical.Categorical(math_ops.log(histograms) - 50.)
137 histograms = array_ops.placeholder(dtype=dtypes.float32,
140 dist = categorical.Categorical(probs=histograms)
149 histograms: histograms_feed_one,
159 histograms: histograms_feed_two,
171 histograms = [[0.1, 0.2, 0.3, 0.25, 0.15],
175 dist = categorical.Categorical(probs=histograms)
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/external/pdfium/testing/image_diff/
H A Dimage_diff.cpp194 " RGBA value histograms (which is resistant to shifts in layout)\n"
302 bool histograms = false; local
314 histograms = true;
331 return CompareImages(filename1, filename2, histograms);
/external/ImageMagick/MagickCore/
H A Dpaint.c712 **histograms,
745 histograms=AcquireHistogramThreadSet(NumberPaintBins);
746 if (histograms == (size_t **) NULL)
790 histogram=histograms[GetOpenMPThreadId()];
866 histograms=DestroyHistogramThreadSet(histograms);
708 **histograms, local
/external/ImageMagick/www/api/
H A Dsegment.php59 <p>SegmentImage() segment an image by analyzing the histograms of the color components and identifying units that are homogeneous with the fuzzy C-means technique.</p>
H A Dmagick-image.php5310 <p>MagickSegmentImage() segments an image by analyzing the histograms of the color components and identifying units that are homogeneous with the fuzzy C-means technique.</p>

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