Remove stale, commented code

src/toast/tests/_helpers.py

@@ -968,143 +968,6 @@ def create_fake_wcs_scanned_tod(
                 del ob[buf]
 
 
-# def create_fake_sky(data, dist_key, map_key, hpix_out=None):
-#     np.random.seed(987654321)
-#     dist = data[dist_key]
-#     pix_data = PixelData(dist, np.float64, n_value=3, units=defaults.det_data_units)
-#     # Just replicate the fake data across all local submaps
-#     off = 0
-#     for submap in range(dist.n_submap):
-#         I_data = 0.3 * np.random.normal(size=dist.n_pix_submap)
-#         Q_data = 0.03 * np.random.normal(size=dist.n_pix_submap)
-#         U_data = 0.03 * np.random.normal(size=dist.n_pix_submap)
-#         if submap in dist.local_submaps:
-#             pix_data.data[off, :, 0] = I_data
-#             pix_data.data[off, :, 1] = Q_data
-#             pix_data.data[off, :, 2] = U_data
-#             off += 1
-#     data[map_key] = pix_data
-#     if hpix_out is not None:
-#         write_healpix_fits(
-#             pix_data,
-#             hpix_out,
-#             nest=True,
-#             comm_bytes=10000000,
-#             report_memory=False,
-#             single_precision=False,
-#         )
-
-
-# def create_fake_healpix_sky(
-#     data,
-#     dist_key,
-#     map_key,
-#     fwhm=10.0 * u.arcmin,
-#     lmax=256,
-#     hpix_out=None,
-# ):
-#     npix = data[dist_key].npix
-#     map_vals = np.array(
-#         rng.random(
-#             npix,
-#             key=(12345, 6789),
-#             counter=(0, 0),
-#             sampler="gaussian",
-#         ),
-#         dtype=np.float64,
-#     )
-#     map_vals = hp.smoothing(
-#         map_vals, fwhm=self.fwhm.to_value(u.radian), lmax=self.lmax
-#     ).astype(dtype)
-#     sss_map /= np.std(sss_map)
-
-#     dist = data[dist_key]
-#     pix_data = PixelData(dist, np.float64, n_value=3, units=defaults.det_data_units)
-#     # Just replicate the fake data across all local submaps
-#     off = 0
-#     for submap in range(dist.n_submap):
-#         I_data = 0.3 * np.random.normal(size=dist.n_pix_submap)
-#         Q_data = 0.03 * np.random.normal(size=dist.n_pix_submap)
-#         U_data = 0.03 * np.random.normal(size=dist.n_pix_submap)
-#         if submap in dist.local_submaps:
-#             pix_data.data[off, :, 0] = I_data
-#             pix_data.data[off, :, 1] = Q_data
-#             pix_data.data[off, :, 2] = U_data
-#             off += 1
-#     data[map_key] = pix_data
-#     if hpix_out is not None:
-#         write_healpix_fits(
-#             pix_data,
-#             hpix_out,
-#             nest=True,
-#             comm_bytes=10000000,
-#             report_memory=False,
-#             single_precision=False,
-#         )
-
-
-# def create_fake_sky_tod(
-#     data,
-#     pixel_pointing,
-#     stokes_weights,
-#     map_vals=(1.0, 1.0, 1.0),
-#     det_data=defaults.det_data,
-#     randomize=False,
-# ):
-#     """Fake sky signal with constant I/Q/U"""
-#     np.random.seed(987654321)
-
-#     # Build the pixel distribution
-#     build_dist = ops.BuildPixelDistribution(
-#         pixel_dist="fake_map_dist",
-#         pixel_pointing=pixel_pointing,
-#     )
-#     build_dist.apply(data)
-
-#     # Create a fake sky
-#     map_key = "fake_map"
-#     dist_key = build_dist.pixel_dist
-#     dist = data[dist_key]
-#     pix_data = PixelData(dist, np.float64, n_value=3, units=u.K)
-#     off = 0
-#     for submap in range(dist.n_submap):
-#         if submap in dist.local_submaps:
-#             if randomize:
-#                 pix_data.data[off, :, 0] = map_vals[0] * np.random.normal(
-#                     size=dist.n_pix_submap
-#                 )
-#                 pix_data.data[off, :, 1] = map_vals[1] * np.random.normal(
-#                     size=dist.n_pix_submap
-#                 )
-#                 pix_data.data[off, :, 2] = map_vals[2] * np.random.normal(
-#                     size=dist.n_pix_submap
-#                 )
-#             else:
-#                 pix_data.data[off, :, 0] = map_vals[0]
-#                 pix_data.data[off, :, 1] = map_vals[1]
-#                 pix_data.data[off, :, 2] = map_vals[2]
-#             off += 1
-#     data[map_key] = pix_data
-
-#     # Scan map into timestreams
-#     scanner = ops.ScanMap(
-#         det_data=defaults.det_data,
-#         pixels=pixel_pointing.pixels,
-#         weights=stokes_weights.weights,
-#         map_key=map_key,
-#     )
-#     scan_pipe = ops.Pipeline(
-#         detector_sets=["SINGLE"],
-#         operators=[
-#             pixel_pointing,
-#             stokes_weights,
-#             scanner,
-#         ],
-#     )
-#     scan_pipe.apply(data)
-#     return map_key
-
-
 def create_fake_mask(data, dist_key, mask_key):
     np.random.seed(987654321)
     dist = data[dist_key]