#! /usr/bin/env python from __future__ import print_function from openturns import * TESTPREAMBLE() try: size = 10 dimension = 2 sample = Sample(size, dimension) # Fill-in the sample for i in range(size): p = Point(dimension) for j in range(dimension): p[j] = i + j * 1.0 / dimension sample[i] = p print("sample=", repr(sample)) # History using the Null strategy nullStrategy = Null() for i in range(size): nullStrategy.store(sample[i]) print("Null strategy sample=", repr(nullStrategy.getSample())) # History using the Full strategy fullStrategy = Full() fullStrategy.setDimension(dimension) for i in range(size): fullStrategy.store(sample[i]) print("Full strategy sample=", repr(fullStrategy.getSample())) # History using the Last strategy, large storage lastStrategy = Last(3 * size) lastStrategy.setDimension(dimension) for i in range(size): lastStrategy.store(sample[i]) print("Last strategy sample (large storage)=", repr(lastStrategy.getSample())) lastStrategy = Last(size // 3) lastStrategy.setDimension(dimension) # History using the Last strategy, small storage for i in range(size): lastStrategy.store(sample[i]) print("Last strategy sample (small storage)=", repr(lastStrategy.getSample())) # History using the Compact strategy, large storage compactStrategy = Compact(3 * size) compactStrategy.setDimension(dimension) for i in range(size): compactStrategy.store(sample[i]) print("Compact strategy sample (large storage)=", repr(compactStrategy.getSample())) compactStrategy = Compact(size // 3) compactStrategy.setDimension(dimension) # History using the Compact strategy, small storage for i in range(size): compactStrategy.store(sample[i]) print("Compact strategy sample (small storage)=", repr(compactStrategy.getSample())) except: import sys print("t_HistoryStrategy_std.py", sys.exc_info()[0], sys.exc_info()[1])