if __name__ == "__main__":
numpy.set_printoptions(threshold=numpy.inf)
parser = argparse.ArgumentParser()
parser.add_argument("datafile", type=str, help="data file for histrogram")
parser.add_argument("-o",
"--outdir",
type=str,
help="directory to save plots")
args = parser.parse_args()
if not os.path.isdir(args.outdir):
print("making directory: " + args.outdir)
os.mkdir(args.outdir)
header, data = albatrostools.get_data(args.datafile, 300000)
print(header)
print("finished reading file")
print(data["spectrum_number"])
pyplot.plot(data["spectrum_number"])
pyplot.savefig(args.outdir + "/spectrum_number.png")
pyplot.clf()
pols = albatrostools.correlate(data["pol0"], data["pol1"])
print("just after correlate")
pol00 = numpy.absolute(pols["pol00"])**2
pol11 = numpy.absolute(pols["pol11"])**2
pol01 = pols["pol01"]
del pols
fnames = sft.time2fnames(ctime_start, ctime_stop, opts.data_dir)
if len(fnames) == 0:
print 'No files found in time range'
exit(0)
pol00 = None
pol11 = None
pol01_mag = None
pol01_phase = None
tstamps = []
for fname in fnames:
print 'Reading', fname
fname_sub = fname.split('/')[-1]
tstamp = fname_sub.split('.')[0]
tstamps.append(tstamp)
header, data = albatrostools.get_data(fname, items=opts.readlen)
if header['bit_mode'] == 1:
plot_auto = False
else:
plot_auto = True
fmin = header['channels'][0] * 125.0 / 2048
fmax = header['channels'][-1] * 125.0 / 2048
# print 'Data dimensions are:', nm.shape(data['pol0']), 'and', nm.shape(data['pol1'])
ntime = nm.shape(data['pol0'])[0]
nchan = nm.shape(data['pol0'])[1]
freqs = nm.linspace(fmin, fmax, nchan)
# Calculate auto and cross correlations
corr = data['pol0'] * nm.conj(data['pol1'])
# Append averaged data
if opts.dsfac is True:
data_dir = "/data/cynthia/albatros/mars2019/baseband"
#fnames = sft.time2fnames(ctime_start, ctime_stop, data_dir)
fnames = ["data/15632/1563273072.raw"]
if len(fnames) == 0:
print('No files found in time range')
exit(0)
else:
print("we have", len(fnames), 'files')
audio = np.array([])
for fname in fnames:
print("working on", fname)
header, data = albatrostools.get_data(fname,
items=-1,
unpack_fast=False,
float=True)
print("unpacked")
# pool = Pool(processes=n_cores)
n_channels = header['channels'][-1]
s_channel = header['channels'][0]
#freq = np.linspace(0,(n_channels / 2048) * 128e6, n_channels)
fs = 2 * n_channels * 125e6 / 2048
time_stream = {'pol0': [], 'pol1': []}
with get_context("spawn").Pool(processes=n_cores) as pool:
time_stream['pol0'] = np.array(
pool.map(do_inverse, [
(data['pol0'][x:x + (5 * items_per_core), :], n_channels,
s_channel) for x in range(0,
t_start = np.fromfile(froot + 'time_gps_start.raw', dtype='double')
t_stop = np.fromfile(froot + 'time_gps_stop.raw', dtype='double')
dt = t_stop - t_start
#dt=np.diff(t_start) #this seems be more accurate than t_stop-t_start
t_per_spec = 2048 * 2 / 250e6
nspec_approx = np.median(dt) / t_per_spec
items = -1
bin_size = np.int(nspec_approx)
for file_name in fnames:
#print(file_name)
t1 = time.time()
header, stuff = albatrostools.get_data(file_name,
unpack_fast=True,
float=True,
byte_delta=-8)
t2 = time.time()
spec0 = albatrostools.bin_autos(stuff['pol0'], bin_size)
spec1 = albatrostools.bin_autos(stuff['pol1'], bin_size)
#pol1_rollx=np.empty(stuff['pol1'].shape,dtype=stuff['pol1'].dtype)
#pol1_rolly=np.empty(stuff['pol1'].shape,dtype=stuff['pol1'].dtype)
#pol1_rollx[:]=np.roll(stuff['pol1'],1,axis=1)
#pol1_rolly[:]=np.roll(stuff['pol1'],1,axis=0)
spec01 = albatrostools.bin_crosses(stuff['pol1'], stuff['pol0'], bin_size)
#spec01x=albatrostools.bin_crosses(stuff['pol0'],pol1_rollx,bin_size)
#spec01y=albatrostools.bin_crosses(stuff['pol0'],pol1_rolly,bin_size)
t3 = time.time()
try:
big_spec0 = np.append(big_spec0, spec0, axis=0)
big_spec1 = np.append(big_spec1, spec1, axis=0)
if len(fnames) == 0:
print 'No files found in time range'
exit(0)
pol00 = None
pol11 = None
pol01_mag = None
pol01_phase = None
tstamps = []
for fname in fnames:
print 'Reading', fname
fname_sub = fname.split('/')[-1]
tstamp = fname_sub.split('.')[0]
tstamps.append(tstamp)
header, data = albatrostools.get_data(fname, items=opts.readlen, unpack_fast=True, float=True)
##unpack using c code do not forget to compile that stuff first!
if header['bit_mode'] == 1:
plot_auto = False
else:
plot_auto = True
fmin = header['channels'][0]*125.0/2048
fmax = header['channels'][-1]*125.0/2048
# print 'Data dimensions are:', nm.shape(data['pol0']), 'and', nm.shape(data['pol1'])
ntime = nm.shape(data['pol0'])[0]
nchan = nm.shape(data['pol0'])[1]
freqs = nm.linspace(fmin, fmax, nchan)