1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
|
import aoflagger as aof
import numpy
print("Flagging with AOFlagger version " + aof.AOFlagger.get_version_string())
nch = 256
ntimes = 1000
aoflagger = aof.AOFlagger()
# Load strategy from disk (alternatively use 'make_strategy' to use a default one)
path = aoflagger.find_strategy_file(aof.TelescopeId.Generic)
strategy = aoflagger.load_strategy_file(path)
data = aoflagger.make_image_set(ntimes, nch, 8)
print("Number of times: " + str(data.width()))
print("Number of channels: " + str(data.height()))
# When flagging multiple baselines, iterate over the baselines and
# call the following code for each baseline
# (to use multithreading, make sure to create an imageset for each
# thread)
# Make eight images: real and imaginary for 4 pol
for imgindex in range(8):
# Initialize data
values = numpy.zeros([nch, ntimes])
data.set_image_buffer(imgindex, values)
flags = strategy.run(data)
flagvalues = flags.get_buffer()
flagcount = sum(sum(flagvalues))
print(
"Percentage flags on zero data: "
+ str(flagcount * 100.0 / (nch * ntimes))
+ "%"
)
# Collect statistics
# We create some unrealistic time and frequency arrays to be able
# to run these functions. Normally, these should hold the time
# and frequency values.
timeArray = numpy.linspace(0.0, ntimes, num=ntimes, endpoint=False)
freqArray = numpy.linspace(0.0, nch, num=nch, endpoint=False)
qs = aoflagger.make_quality_statistics(timeArray, freqArray, 4, False)
qs.collect_statistics(
data, flags, aoflagger.make_flag_mask(ntimes, nch, False), 0, 1
)
try:
qs.write_statistics("test.qs")
except:
print("write_statistics() failed")
|
