def test_weightstats_2(self): x1, x2 = self.x1, self.x2 w1, w2 = self.w1, self.w2 d1 = DescrStatsW(x1) d1w = DescrStatsW(x1, weights=w1) d2w = DescrStatsW(x2, weights=w2) x1r = d1w.asrepeats() x2r = d2w.asrepeats() # print 'random weights' # print ttest_ind(x1, x2, weights=(w1, w2)) # print stats.ttest_ind(x1r, x2r) assert_almost_equal( ttest_ind(x1, x2, weights=(w1, w2))[:2], stats.ttest_ind(x1r, x2r), 14) #not the same as new version with random weights/replication # assert x1r.shape[0] == d1w.sum_weights # assert x2r.shape[0] == d2w.sum_weights assert_almost_equal(x2r.var(), d2w.var, 14) assert_almost_equal(x2r.std(), d2w.std, 14) #one-sample tests # print d1.ttest_mean(3) # print stats.ttest_1samp(x1, 3) # print d1w.ttest_mean(3) # print stats.ttest_1samp(x1r, 3) assert_almost_equal(d1.ttest_mean(3)[:2], stats.ttest_1samp(x1, 3), 11) assert_almost_equal( d1w.ttest_mean(3)[:2], stats.ttest_1samp(x1r, 3), 11)
def test_weightstats_2(self): x1, x2 = self.x1, self.x2 w1, w2 = self.w1, self.w2 d1 = DescrStatsW(x1) d1w = DescrStatsW(x1, weights=w1) d2w = DescrStatsW(x2, weights=w2) x1r = d1w.asrepeats() x2r = d2w.asrepeats() # print 'random weights' # print ttest_ind(x1, x2, weights=(w1, w2)) # print stats.ttest_ind(x1r, x2r) assert_almost_equal(ttest_ind(x1, x2, weights=(w1, w2))[:2], stats.ttest_ind(x1r, x2r), 14) #not the same as new version with random weights/replication # assert x1r.shape[0] == d1w.sum_weights # assert x2r.shape[0] == d2w.sum_weights assert_almost_equal(x2r.var(), d2w.var, 14) assert_almost_equal(x2r.std(), d2w.std, 14) #one-sample tests # print d1.ttest_mean(3) # print stats.ttest_1samp(x1, 3) # print d1w.ttest_mean(3) # print stats.ttest_1samp(x1r, 3) assert_almost_equal(d1.ttest_mean(3)[:2], stats.ttest_1samp(x1, 3), 11) assert_almost_equal(d1w.ttest_mean(3)[:2], stats.ttest_1samp(x1r, 3), 11)
def test_weightstats_1(self): x1, x2 = self.x1, self.x2 w1, w2 = self.w1, self.w2 w1_ = 2. * np.ones(len(x1)) w2_ = 2. * np.ones(len(x2)) d1 = DescrStatsW(x1) # print ttest_ind(x1, x2) # print ttest_ind(x1, x2, usevar='separate') # #print ttest_ind(x1, x2, usevar='separate') # print stats.ttest_ind(x1, x2) # print ttest_ind(x1, x2, usevar='separate', alternative='larger') # print ttest_ind(x1, x2, usevar='separate', alternative='smaller') # print ttest_ind(x1, x2, usevar='separate', weights=(w1_, w2_)) # print stats.ttest_ind(np.r_[x1, x1], np.r_[x2,x2]) assert_almost_equal(ttest_ind(x1, x2, weights=(w1_, w2_))[:2], stats.ttest_ind(np.r_[x1, x1], np.r_[x2,x2]))
def test_weightstats_1(self): x1, x2 = self.x1, self.x2 w1, w2 = self.w1, self.w2 w1_ = 2. * np.ones(len(x1)) w2_ = 2. * np.ones(len(x2)) d1 = DescrStatsW(x1) # print ttest_ind(x1, x2) # print ttest_ind(x1, x2, usevar='separate') # #print ttest_ind(x1, x2, usevar='separate') # print stats.ttest_ind(x1, x2) # print ttest_ind(x1, x2, usevar='separate', alternative='larger') # print ttest_ind(x1, x2, usevar='separate', alternative='smaller') # print ttest_ind(x1, x2, usevar='separate', weights=(w1_, w2_)) # print stats.ttest_ind(np.r_[x1, x1], np.r_[x2,x2]) assert_almost_equal( ttest_ind(x1, x2, weights=(w1_, w2_))[:2], stats.ttest_ind(np.r_[x1, x1], np.r_[x2, x2]))