class_docstr: Test Annualized Volatility
class_docstr_tok: ["Test","Annualized","Volatility"]
docstr: Simple test for uniform returns should generate 0 volatility
docstr_tok: ["Simple","test","for","uniform","returns","should","generate","0","volatility"]
code: def test_simple_volatility(self):
      """
      Simple test for uniform returns should generate 0 volatility
      """
      nassets = 3
      ann_vol = AnnualizedVolatility()
      today = pd.Timestamp("2016", tz="utc")
      assets = np.arange(nassets, dtype=np.float64)
      returns = np.full(
          (ann_vol.window_length, nassets), 0.004, dtype=np.float64
      )
      out = np.empty(shape=(nassets,), dtype=np.float64)
  
      ann_vol.compute(today, assets, out, returns, 252)
  
      expected_vol = np.zeros(nassets)
      np.testing.assert_almost_equal(out, expected_vol, decimal=8)
  
imports: from __future__ import division
  from nose_parameterized import parameterized
  from six.moves import range
  import numpy
  import pandas
  import talib
  from numpy.random import RandomState
  from zipline.lib.adjusted_array import AdjustedArray
  from zipline.pipeline.data import USEquityPricing
  from zipline.pipeline.factors import BollingerBands, Aroon, FastStochasticOscillator, IchimokuKinkoHyo, LinearWeightedMovingAverage, RateOfChangePercentage, TrueRange, MovingAverageConvergenceDivergenceSignal, AnnualizedVolatility, RSI
  from zipline.testing import check_allclose, parameter_space
  from zipline.testing.fixtures import ZiplineTestCase
  from zipline.testing.predicates import assert_equal
  from .base import BaseUSEquityPipelineTestCase
label_desc: Use image node_id 1 for calling the AnnualizedVolatilityTestCase obj's underlying member method code with example usage: obj.test_simple_volatility() without return types