eliminated uvpspec.generate_noise pstokes correction

and added noise_validation test to test_noise

hera_pspec/testing.py

@@ -201,8 +201,8 @@ def uvpspec_from_data(data, bl_grps, data_std=None, spw_ranges=None, beam=None,
     return uvp
 
 
-def noise_sim(data, Tsys, beam, Nextend=0, seed=None, inplace=False, whiten=False,
-              run_check=True):
+def noise_sim(data, Tsys, beam, Nextend=0, seed=None, inplace=False,
+              whiten=False, run_check=True):
     """
     Generate a simulated Gaussian noise realization.
 

hera_pspec/tests/test_noise.py

@@ -4,7 +4,7 @@
 import os
 import sys
 from hera_pspec.data import DATA_PATH
-from hera_pspec import uvpspec, conversions, parameter, pspecbeam, noise
+from hera_pspec import uvpspec, conversions, pspecdata, pspecbeam, noise, testing, utils
 import copy
 import h5py
 from collections import OrderedDict as odict
@@ -64,4 +64,50 @@ def test_calc_P_N(self):
         nt.assert_true(Dsq[1] < P_N)
 
 
+def test_noise_validation():
+    """
+    make sure that the noise.py code produces
+    correct noise 1-sigma amplitude using a
+    noise simulation.
+    """
+    # get simulated noise in Jy
+    bfile = os.path.join(DATA_PATH, 'HERA_NF_dipole_power.beamfits')
+    beam = pspecbeam.PSpecBeamUV(bfile)
+    uvfile = os.path.join(DATA_PATH, "zen.even.xx.LST.1.28828.uvOCRSA")
+    Tsys = 300.0  # Kelvin
+
+    # generate noise
+    seed = 0
+    uvd = testing.noise_sim(uvfile, Tsys, beam, seed=seed, whiten=True, inplace=False, Nextend=9)
+
+    # get redundant baseline group
+    reds, lens, angs = utils.get_reds(uvd, pick_data_ants=True, bl_len_range=(10, 20),
+                                      bl_deg_range=(0, 1))
+    bls1, bls2, blps = utils.construct_blpairs(reds[0], exclude_auto_bls=True, exclude_permutations=True)
+
+    # setup PSpecData
+    ds = pspecdata.PSpecData(dsets=[copy.deepcopy(uvd), copy.deepcopy(uvd)], wgts=[None, None], beam=beam)
+    ds.Jy_to_mK()
+
+    # get pspec
+    uvp = ds.pspec(bls1, bls2, (0, 1), [('xx', 'xx')], input_data_weight='identity', norm='I',
+                   taper='none', sampling=False, little_h=True, spw_ranges=[(0, 50)], verbose=False)
+
+    # get noise spectra from one of the blpairs
+    P_N = uvp.generate_noise_spectra(0, 'xx', Tsys, blpairs=uvp.get_blpairs()[:1], num_steps=2000).values()[0][0, 0]
+
+    # get P_std of real spectra for each baseline across time axis
+    P_stds = np.array([np.std(uvp.get_data((0, bl, 'xx')).real, axis=1) for bl in uvp.get_blpairs()])
+
+    # get average P_std_avg and its standard error
+    P_std_avg = np.mean(P_stds)
+
+    # assert close to P_N: 2%
+    # This should be updated to be within standard error on P_std_avg
+    # when the spw_range-variable pspec amplitude bug is resolved
+    nt.assert_true(np.abs(P_std_avg - P_N) / P_N < 0.02)
+
+
+
+
 

hera_pspec/uvpspec.py

@@ -1570,13 +1570,8 @@ def generate_noise_spectra(self, spw, pol, Tsys, blpairs=None, little_h=True,
                 if form == 'Pk':
                     pn = np.ones(len(dlys), np.float) * pn
 
-                # If pseudo stokes pol (as opposed to linear or circular pol),
-                # divide by extra factor of 2
-                if isinstance(pol, (np.str, str)):
-                    pol = uvutils.polstr2num(pol)
-
-                if pol in (1, 2, 3, 4): pn /= 2.0 # pseudo stokes pol
-                if real: pn /= np.sqrt(2) # if real divide by sqrt(2)
+                if real:
+                    pn /= np.sqrt(2) # if real divide by sqrt(2)
 
                 # append to P_blp
                 P_blp.append(pn)