def test_variance(self): from test_utils import elementwiseVar series = self.generateTestSeries() varVal = series.variance() arys = series.values().collect() expected = elementwiseVar([ary.astype('float16') for ary in arys]) assert_true(allclose(expected, varVal)) assert_equals('float64', str(varVal.dtype))
def test_variance(self): from test_utils import elementwiseVar arys, shape, size = _generateTestArrays(2, 'uint8') imageData = ImagesLoader(self.sc).fromArrays(arys) varVal = imageData.variance() expected = elementwiseVar([ary.astype('float16') for ary in arys]) assert_true(allclose(expected, varVal)) assert_equals('float64', str(varVal.dtype))
def test_stats(self): from test_utils import elementwiseMean, elementwiseVar series = self.generateTestSeries() statsVal = series.stats() arys = series.values().collect() floatArys = [ary.astype('float16') for ary in arys] expectedMean = elementwiseMean(floatArys) expectedVar = elementwiseVar(floatArys) assert_true(allclose(expectedMean, statsVal.mean())) assert_true(allclose(expectedVar, statsVal.variance()))
def test_stats(self): from test_utils import elementwiseMean, elementwiseVar arys, shape, size = _generateTestArrays(2, 'uint8') imageData = ImagesLoader(self.sc).fromArrays(arys) statsval = imageData.stats() floatarys = [ary.astype('float16') for ary in arys] # StatsCounter contains a few different measures, only test a couple: expectedMean = elementwiseMean(floatarys) expectedVar = elementwiseVar(floatarys) assert_true(allclose(expectedMean, statsval.mean())) assert_true(allclose(expectedVar, statsval.variance()))