def test_ant_index(self):
# Only testing rpoco8, rpoco16, and snap
bof = "rpoco8"
for i in range(8):
self.assertEqual(pc.get_ant_index(bof, i), i)
self.assertEqual(pc.get_ant_index(bof, str(i)), i)
self.assertEqual(pc.get_ant_index(bof, chr(ord("a") + i)), i)
self.assertEqual(pc.get_ant_index(bof, chr(ord("a") + i) + "1"), i)
for i in range(32):
chan = chr(ord("a") + i / 4) + str(1 + i % 4)
if i % 4:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chan)
if i >= 8:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, i)
with self.assertRaises(ValueError):
pc.get_ant_index(bof, str(i))
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chr(ord("a") + i))
bof = "rpoco16"
for i in range(16):
chan = chr(ord("a") + i / 2) + str(1 + i % 2)
self.assertEqual(pc.get_ant_index(bof, chan), i)
for i in range(32):
chan = chr(ord("a") + i / 4) + str(1 + i % 4)
if i % 4 > 1:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chan)
bof = "spoco12"
parser.add_argument('-q',
'--quiet',
action='store_true',
help='Suppress messages to stdout.')
parser.add_argument('-s',
'--scale',
action='store_true',
help=' '.join([
'Scale the output by number of spectra',
'per integration.'
]))
args = parser.parse_args()
# Get the antenna numbers
model = pc.get_model_uv(args.infiles)
ant_i = pc.get_ant_index(model, args.ant_i)
ant_j = pc.get_ant_index(model, args.ant_j)
ant_i, ant_j = min(ant_i, ant_j), max(ant_i, ant_j)
# Initialize arrays to store the spectra
spectra_r, spectra_i = pc.spec_list(args.infiles, ant_i, ant_j,
not args.quiet)
# Get the frequency bins of the data
uv = aipy.miriad.UV(args.infiles[0])
frequency = 1e3 * aipy.cal.get_freqs(uv['sdf'], uv['sfreq'], uv['nchan'])
# Compute the means
mean_spec_r = np.mean(spectra_r, axis=0)
mean_spec_i = np.mean(spectra_i, axis=0)
if args.scale:
help='Plot on a log scale.')
parser.add_argument('-p', '--plot-all',
action='store_true',
help='Plot real/imag + abs of correlation.')
parser.add_argument('-q', '--quiet',
action='store_true',
help='Suppress messages to stdout.')
parser.add_argument('-s', '--scale',
action='store_true',
help=' '.join(['Scale the output by number of spectra',
'per integration.']))
args = parser.parse_args()
# Get the antenna numbers
model = pc.get_model_uv(args.infiles)
ant_i = pc.get_ant_index(model, args.ant_i)
ant_j = pc.get_ant_index(model, args.ant_j)
ant_i, ant_j = min(ant_i, ant_j), max(ant_i, ant_j)
# Initialize arrays to store the spectra
spectra_r, spectra_i = pc.spec_list(args.infiles, ant_i, ant_j, not args.quiet)
# Get the frequency bins of the data
uv = aipy.miriad.UV(args.infiles[0])
frequency = 1e3 * aipy.cal.get_freqs(uv['sdf'], uv['sfreq'], uv['nchan'])
# Compute the means
mean_spec_r = np.mean(spectra_r, axis=0)
mean_spec_i = np.mean(spectra_i, axis=0)
if args.scale:
fft_size = 2*uv['nchan']
def test_ant_index(self):
# Only testing rpoco8, rpoco16, and snap
bof = 'rpoco8'
for i in range(8):
self.assertEqual(pc.get_ant_index(bof, i), i)
self.assertEqual(pc.get_ant_index(bof, str(i)), i)
self.assertEqual(pc.get_ant_index(bof, chr(ord('a')+i)), i)
self.assertEqual(pc.get_ant_index(bof, chr(ord('a')+i)+'1'), i)
for i in range(32):
chan = chr(ord('a')+i/4) + str(1+i%4)
if i % 4:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chan)
if i >= 8:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, i)
with self.assertRaises(ValueError):
pc.get_ant_index(bof, str(i))
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chr(ord('a')+i))
bof = 'rpoco16'
for i in range(16):
chan = chr(ord('a')+i/2) + str(1+i%2)
self.assertEqual(pc.get_ant_index(bof, chan), i)
for i in range(32):
chan = chr(ord('a')+i/4) + str(1+i%4)
if i % 4 > 1:
with self.assertRaises(ValueError):
pc.get_ant_index(bof, chan)
bof = 'spoco12'
