From f6381ea62cc28ebed1eb5f68cf74ec123a1eb649 Mon Sep 17 00:00:00 2001 From: Matt Roeschke Date: Sat, 25 Nov 2017 11:57:11 -0800 Subject: [PATCH] CLN: ASV eval benchmark --- asv_bench/benchmarks/eval.py | 57 +++++++++++++++++------------------- 1 file changed, 27 insertions(+), 30 deletions(-) diff --git a/asv_bench/benchmarks/eval.py b/asv_bench/benchmarks/eval.py index 6f33590ee9e33..fd18b3f21cf45 100644 --- a/asv_bench/benchmarks/eval.py +++ b/asv_bench/benchmarks/eval.py @@ -1,4 +1,4 @@ -from .pandas_vb_common import * +import numpy as np import pandas as pd try: import pandas.core.computation.expressions as expr @@ -7,64 +7,61 @@ class Eval(object): + goal_time = 0.2 params = [['numexpr', 'python'], [1, 'all']] param_names = ['engine', 'threads'] def setup(self, engine, threads): - self.df = DataFrame(np.random.randn(20000, 100)) - self.df2 = DataFrame(np.random.randn(20000, 100)) - self.df3 = DataFrame(np.random.randn(20000, 100)) - self.df4 = DataFrame(np.random.randn(20000, 100)) + np.random.seed(1234) + self.df = pd.DataFrame(np.random.randn(20000, 100)) + self.df2 = pd.DataFrame(np.random.randn(20000, 100)) + self.df3 = pd.DataFrame(np.random.randn(20000, 100)) + self.df4 = pd.DataFrame(np.random.randn(20000, 100)) if threads == 1: expr.set_numexpr_threads(1) def time_add(self, engine, threads): - df, df2, df3, df4 = self.df, self.df2, self.df3, self.df4 - pd.eval('df + df2 + df3 + df4', engine=engine) + pd.eval('self.df + self.df2 + self.df3 + self.df4', engine=engine) def time_and(self, engine, threads): - df, df2, df3, df4 = self.df, self.df2, self.df3, self.df4 - pd.eval('(df > 0) & (df2 > 0) & (df3 > 0) & (df4 > 0)', engine=engine) + pd.eval('(self.df > 0) & (self.df2 > 0) & ' + '(self.df3 > 0) & (self.df4 > 0)', engine=engine) def time_chained_cmp(self, engine, threads): - df, df2, df3, df4 = self.df, self.df2, self.df3, self.df4 - pd.eval('df < df2 < df3 < df4', engine=engine) + pd.eval('self.df < self.df2 < self.df3 < self.df4', engine=engine) def time_mult(self, engine, threads): - df, df2, df3, df4 = self.df, self.df2, self.df3, self.df4 - pd.eval('df * df2 * df3 * df4', engine=engine) + pd.eval('self.df * self.df2 * self.df3 * self.df4', engine=engine) def teardown(self, engine, threads): expr.set_numexpr_threads() class Query(object): + goal_time = 0.2 def setup(self): - self.N = 1000000 - self.halfway = ((self.N // 2) - 1) - self.index = date_range('20010101', periods=self.N, freq='T') - self.s = Series(self.index) + np.random.seed(1234) + self.N = 10**6 + self.halfway = (self.N // 2) - 1 + self.index = pd.date_range('20010101', periods=self.N, freq='T') + self.s = pd.Series(self.index) self.ts = self.s.iloc[self.halfway] - self.df = DataFrame({'a': np.random.randn(self.N), }, index=self.index) - self.df2 = DataFrame({'dates': self.s.values,}) - - self.df3 = DataFrame({'a': np.random.randn(self.N),}) - self.min_val = self.df3['a'].min() - self.max_val = self.df3['a'].max() + self.df = pd.DataFrame({'a': np.random.randn(self.N), 'dates': self.s}, + index=self.index) + self.data = np.random.randn(self.N) + self.min_val = self.data.min() + self.max_val = self.data.max() def time_query_datetime_index(self): - ts = self.ts - self.df.query('index < @ts') + self.df.query('index < @self.ts') - def time_query_datetime_series(self): - ts = self.ts - self.df2.query('dates < @ts') + def time_query_datetime_column(self): + self.df.query('dates < @self.ts') def time_query_with_boolean_selection(self): - min_val, max_val = self.min_val, self.max_val - self.df.query('(a >= @min_val) & (a <= @max_val)') + self.df.query('(a >= @self.min_val) & (a <= @self.max_val)')