diff options
Diffstat (limited to 'benchmarks')
| -rw-r--r-- | benchmarks/benchmarks/bench_function_base.py | 169 |
1 files changed, 83 insertions, 86 deletions
diff --git a/benchmarks/benchmarks/bench_function_base.py b/benchmarks/benchmarks/bench_function_base.py index fa02cd82d..a82d424e7 100644 --- a/benchmarks/benchmarks/bench_function_base.py +++ b/benchmarks/benchmarks/bench_function_base.py @@ -95,6 +95,84 @@ class Select(Benchmark): np.select(self.cond_large, ([self.d, self.e] * 10)) +class SortGenerator(object): + # The size of the unsorted area in the "random unsorted area" + # benchmarks + AREA_SIZE = 10 + # The size of the "partially ordered" sub-arrays + BUBBLE_SIZE = 10 + + @staticmethod + def random(size, dtype): + arr = np.arange(size, dtype=dtype) + np.random.shuffle(arr) + return arr + + @staticmethod + def ordered(size, dtype): + return np.arange(size, dtype=dtype) + + @staticmethod + def reversed(size, dtype): + return np.arange(size-1, -1, -1, dtype=dtype) + + @staticmethod + def uniform(size, dtype): + return np.ones(size, dtype=dtype) + + @staticmethod + def _type_swapped_pair(size, dtype, swap_frac): + a = np.arange(size, dtype=dtype) + for _ in range(int(size * swap_frac)): + x, y = np.random.randint(0, size, 2) + a[x], a[y] = a[y], a[x] + return a + + @staticmethod + def _type_sorted_block(size, dtype, block_size): + a = np.arange(size, dtype=dtype) + b = [] + if size < block_size: + return a + block_num = size // block_size + for i in range(block_num): + b.extend(a[i::block_num]) + return np.array(b) + + @staticmethod + def _type_random_unsorted_area(size, dtype, frac, area_num): + area_num = int(area_num) + a = np.arange(size, dtype=dtype) + unsorted_len = int(size * frac / area_num) + for _ in range(area_num): + start = np.random.randint(size-unsorted_len) + end = start + unsorted_len + np.random.shuffle(a[start:end]) + return a + + def __getattr__(self, name): + import re + import functools + token_specification = [ + (r'sorted\_block\_([0-9]+)', + lambda size, dtype, x: self._type_sorted_block(size, dtype, x)), + (r'swapped\_pair\_([0-9]+)\_percent', + lambda size, dtype, x: self._type_swapped_pair(size, dtype, x / 100.0)), + (r'random\_unsorted\_area\_([0-9]+)\_percent', + lambda size, dtype, x: self._type_random_unsorted_area(size, dtype, x / 100.0, self.AREA_SIZE)), + (r'random_bubble\_([0-9]+)\_fold', + lambda size, dtype, x: self._type_random_unsorted_area(size, dtype, x * self.BUBBLE_SIZE / size, self.BUBBLE_SIZE)), + ] + + for pattern, function in token_specification: + match = re.fullmatch(pattern, name) + + if match is not None: + return functools.partial(function, x=int(match.group(1))) + + raise AttributeError + + class Sort(Benchmark): """ This benchmark tests sorting performance with several @@ -116,13 +194,14 @@ class Sort(Benchmark): random_unsorted_area_X_percent This kind of array has random unsorted areas which take up X% of the original array, the size of one - area is AREA_SIZE + area is SortGenerator.AREA_SIZE random_bubble_X_fold - ? + Same as random_unsorted_area, except that it has + X areas of size SortGenerator.BUBBLE_SIZE """ params = [ # In NumPy 1.17 and newer, 'merge' can be one of several - # stable sorts + # stable sorts, it isn't necessarily merge sort. ['quick', 'merge', 'heap'], ['float64', 'int64', 'uint64'], [ @@ -147,15 +226,10 @@ class Sort(Benchmark): # The size of the benchmarked arrays. ARRAY_SIZE = 10000 - # The size of the unsorted area in the "random unsorted area" - # benchmarks - AREA_SIZE = 10 - # ? - BUBBLE_SIZE = 10 def setup(self, kind, dtype, array_type): np.random.seed(1234) - self.arr = getattr(self, 'array_' + array_type)(self.ARRAY_SIZE, dtype) + self.arr = getattr(SortGenerator(), array_type)(self.ARRAY_SIZE, dtype) def time_sort_inplace(self, kind, dtype, array_type): self.arr.sort(kind=kind) @@ -166,83 +240,6 @@ class Sort(Benchmark): def time_argsort(self, kind, dtype, array_type): np.argsort(self.arr, kind=kind) - def array_random(self, size, dtype): - arr = np.arange(size, dtype=dtype) - np.random.shuffle(arr) - return arr - - def array_ordered(self, size, dtype): - return np.arange(size, dtype=dtype) - - def array_reversed(self, size, dtype): - return np.arange(size-1, -1, -1, dtype=dtype) - - def array_uniform(self, size, dtype): - return np.ones(size, dtype=dtype) - - def array_sorted_block_10(self, size, dtype): - return self.sorted_block(size, dtype, 10) - - def array_sorted_block_100(self, size, dtype): - return self.sorted_block(size, dtype, 100) - - def array_sorted_block_1000(self, size, dtype): - return self.sorted_block(size, dtype, 1000) - - def array_swapped_pair_1_percent(self, size, dtype): - return self.swapped_pair(size, dtype, 0.01) - - def array_swapped_pair_10_percent(self, size, dtype): - return self.swapped_pair(size, dtype, 0.1) - - def array_swapped_pair_50_percent(self, size, dtype): - return self.swapped_pair(size, dtype, 0.5) - - def array_random_unsorted_area_50_percent(self, size, dtype): - return self.random_unsorted_area(size, dtype, 0.5, self.AREA_SIZE) - - def array_random_unsorted_area_10_percent(self, size, dtype): - return self.random_unsorted_area(size, dtype, 0.1, self.AREA_SIZE) - - def array_random_unsorted_area_1_percent(self, size, dtype): - return self.random_unsorted_area(size, dtype, 0.01, self.AREA_SIZE) - - def array_random_bubble_1_fold(self, size, dtype): - return self.random_unsorted_area(size, dtype, 1, size / self.BUBBLE_SIZE) - - def array_random_bubble_5_fold(self, size, dtype): - return self.random_unsorted_area(size, dtype, 5, size / self.BUBBLE_SIZE) - - def array_random_bubble_10_fold(self, size, dtype): - return self.random_unsorted_area(size, dtype, 10, size / self.BUBBLE_SIZE) - - def swapped_pair(self, size, dtype, swap_frac): - a = np.arange(size, dtype=dtype) - for _ in range(int(size * swap_frac)): - x, y = np.random.randint(0, size, 2) - a[x], a[y] = a[y], a[x] - return a - - def sorted_block(self, size, dtype, block_size): - a = np.arange(size, dtype=dtype) - b = [] - if size < block_size: - return a - block_num = size // block_size - for i in range(block_num): - b.extend(a[i::block_num]) - return np.array(b) - - def random_unsorted_area(self, size, dtype, frac, area_num): - area_num = int(area_num) - a = np.arange(size, dtype=dtype) - unsorted_len = int(size * frac / area_num) - for _ in range(area_num): - start = np.random.randint(size-unsorted_len) - end = start + unsorted_len - np.random.shuffle(a[start:end]) - return a - class SortWorst(Benchmark): def setup(self): |