| 227 | param_names = ["method"] |
| 228 | |
| 229 | def setup(self, method): |
| 230 | win = 100 |
| 231 | arr = np.random.rand(100000) |
| 232 | if hasattr(DataFrame, "rolling"): |
| 233 | df = DataFrame(arr).rolling(win) |
| 234 | |
| 235 | @run_parallel(num_threads=2) |
| 236 | def parallel_rolling(): |
| 237 | getattr(df, method)() |
| 238 | |
| 239 | self.parallel_rolling = parallel_rolling |
| 240 | elif have_rolling_methods: |
| 241 | rolling = { |
| 242 | "median": rolling_median, |
| 243 | "mean": rolling_mean, |
| 244 | "min": rolling_min, |
| 245 | "max": rolling_max, |
| 246 | "var": rolling_var, |
| 247 | "skew": rolling_skew, |
| 248 | "kurt": rolling_kurt, |
| 249 | "std": rolling_std, |
| 250 | } |
| 251 | |
| 252 | @run_parallel(num_threads=2) |
| 253 | def parallel_rolling(): |
| 254 | rolling[method](arr, win) |
| 255 | |
| 256 | self.parallel_rolling = parallel_rolling |
| 257 | else: |
| 258 | raise NotImplementedError |
| 259 | |
| 260 | def time_rolling(self, method): |
| 261 | self.parallel_rolling() |