I want to check how much darks vary inside a dark observation, whenever there's more than one dark in an observation.
In [1]:
fname = meta.stagel1bsummary
In [2]:
fname
Out[2]:
'/maven_iuvs/stage/products/level1b/IUVS_L1B_index_summary.txt'
In [ ]:
widths = [(0,8),
(8, 89),
(89,97),
(97,102),
(102,112),
(112,118),
(118,
In [7]:
pd.read_fwf(fname, skiprows=26, index=0).head()
Out[7]:
filenum filename
OBS_ID
XUV
INT_TIME
NX
NY
NZ
X1
X2
Y1
...
SHUT_STATE
PHASE
MODE
CYCLE
DET_TEMP
CASE_TEMP
FOV_DEG
STIM_STATE
FILL_BINS TARGET
PURPOSE
0
0 mvn_iuv_l1b_ISON1-cycle01-mode01-...
1
FUV
60000
225
255
36
2
451
2
...
open
NaN
1
1
3.0833
20.215
7.49
NaN
387720Siding Spr
Spectral
1
1 mvn_iuv_l1b_ISON1-cycle01-mode01-...
1
FUV
60000
225
255
36
2
451
2
...
open
NaN
1
1
4.8060
23.774
7.49
NaN
387720Siding Spr
Spectral
2
2 mvn_iuv_l1b_ISON1-cycle01-mode01-...
1
FUV
60000
225
255
36
2
451
2
...
open
NaN
1
1
6.1542
25.596
7.49
NaN
387720Siding Spr
Spectral
3
3 mvn_iuv_l1b_ISON1-cycle01-mode02-...
2
FUV
60000
370
70
36
132
871
126
...
open
NaN
2
1
7.4275
25.916
11.46
NaN
0Siding Spr
Spectral
4
4 mvn_iuv_l1b_ISON1-cycle01-mode02-...
2
MUV
60000
510
70
36
2
1021
126
...
open
NaN
2
1
5.1056
25.916
11.46
NaN
0Siding Spr
Spectral
5 rows × 24 columns
In [3]:
weird = (l1ameta.applymap(type) != l1ameta.iloc[0].apply(type)).any(axis=1)
In [4]:
l1ameta[weird]
Out[4]:
filename
OBS_ID
XUV
INT_TIME
NX
NY
NZ
X1
X2
Y1
...
PHASE
MODE
CYCLE
DET_TEMP
CASE_TEMP
FOV_DEG
STIM_STATE
FILL_BINS
TARGET
PURPOSE
filenum
18274mvn_iuv_l1a_outbound-orbit00107-mode1001-fuvdark_20141018T073619_v01_r01.fits.gz
1001
FUV
14400
1024
24
1
0
1023
319
582
...
-1
-13.99
5.183
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18275mvn_iuv_l1a_outbound-orbit00107-mode1001-muvdark_20141018T073619_v01_r01.fits.gz
1001
MUV
14400
1024
24
1
0
1023
441
704
...
-1
-16.31
5.183
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18278mvn_iuv_l1a_outbound-orbit00107-mode1001-fuvdark_20141018T073659_v01_r01.fits.gz
1001
FUV
14400
165
7
1
52
711
89
893
...
-1
-14.06
5.189
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18279mvn_iuv_l1a_outbound-orbit00107-mode1001-muvdark_20141018T073659_v01_r01.fits.gz
1001
MUV
14400
30
7
1
2
1021
96
900
...
-1
-16.31
5.189
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18282mvn_iuv_l1a_outbound-orbit00107-mode1001-fuvdark_20141018T075527_v01_r01.fits.gz
1001
FUV
1400
165
7
1
52
711
89
893
...
-1
-15.11
5.114
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18283mvn_iuv_l1a_outbound-orbit00107-mode1001-muvdark_20141018T075527_v01_r01.fits.gz
1001
MUV
1400
30
7
1
2
1021
96
900
...
-1
-17.51
5.114
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18290mvn_iuv_l1a_outbound-orbit00107-mode1001-fuvdark_20141018T082537_v01_r01.fits.gz
1001
FUV
14400
165
7
1
52
711
89
893
...
-1
-15.94
4.994
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18291mvn_iuv_l1a_outbound-orbit00107-mode1001-muvdark_20141018T082537_v01_r01.fits.gz
1001
MUV
14400
30
7
1
2
1021
96
900
...
-1
-18.41
4.994
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18292mvn_iuv_l1a_outbound-orbit00107-mode1001-fuvdark_20141018T082559_v01_r01.fits.gz
1001
FUV
1400
165
7
1
52
711
89
893
...
-1
-16.01
4.994
12.670
0Siding
Spr
Spectral
NaN
NaN
NaN
18293mvn_iuv_l1a_outbound-orbit00107-mode1001-muvdark_20141018T082559_v01_r01.fits.gz
1001
MUV
1400
30
7
1
2
1021
96
900
...
-1
-18.26
4.994
12.670
0Siding
Spr
Spectral
NaN
NaN
NaN
18347mvn_iuv_l1a_periapse-orbit00108-mode0001-fuvdark_20141018T112844_v01_r01.fits.gz
1
FUV
4200
256
7
1
0
1023
89
893
...
-1
-16.31
4.930
17.290
0Siding
Spr
Spectral
NaN
NaN
NaN
18348mvn_iuv_l1a_periapse-orbit00108-mode0001-muvdark_20141018T112844_v01_r01.fits.gz
1
MUV
4200
256
7
1
0
1023
96
900
...
-1
-18.86
4.930
17.290
0Siding
Spr
Spectral
NaN
NaN
NaN
18375mvn_iuv_l1a_periapse-orbit00108-mode0001-fuvdark_20141018T115024_v01_r01.fits.gz
1
FUV
4200
256
7
1
0
1023
89
893
...
-1
-15.86
5.063
23.370
0Siding
Spr
Spectral
NaN
NaN
NaN
18376mvn_iuv_l1a_periapse-orbit00108-mode0001-muvdark_20141018T115024_v01_r01.fits.gz
1
MUV
4200
256
7
1
0
1023
96
900
...
-1
-18.41
5.063
23.370
0Siding
Spr
Spectral
NaN
NaN
NaN
18379mvn_iuv_l1a_outbound-orbit00108-mode1001-fuvdark_20141018T121322_v01_r01.fits.gz
1001
FUV
14400
1024
24
1
0
1023
319
582
...
-1
-16.01
5.114
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18380mvn_iuv_l1a_outbound-orbit00108-mode1001-muvdark_20141018T121322_v01_r01.fits.gz
1001
MUV
14400
1024
24
1
0
1023
441
704
...
-1
-18.56
5.114
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18383mvn_iuv_l1a_outbound-orbit00108-mode1001-fuvdark_20141018T121402_v01_r01.fits.gz
1001
FUV
14400
165
7
1
52
711
89
893
...
-1
-16.01
5.107
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18384mvn_iuv_l1a_outbound-orbit00108-mode1001-muvdark_20141018T121402_v01_r01.fits.gz
1001
MUV
14400
30
7
1
2
1021
96
900
...
-1
-18.56
5.107
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18387mvn_iuv_l1a_outbound-orbit00108-mode1001-fuvdark_20141018T123229_v01_r01.fits.gz
1001
FUV
1400
165
7
1
52
711
89
893
...
-1
-15.86
5.069
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18388mvn_iuv_l1a_outbound-orbit00108-mode1001-muvdark_20141018T123229_v01_r01.fits.gz
1001
MUV
1400
30
7
1
2
1021
96
900
...
-1
-18.71
5.069
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18395mvn_iuv_l1a_outbound-orbit00108-mode1001-fuvdark_20141018T130240_v01_r01.fits.gz
1001
FUV
14400
165
7
1
52
711
89
893
...
-1
-16.24
4.962
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18396mvn_iuv_l1a_outbound-orbit00108-mode1001-muvdark_20141018T130240_v01_r01.fits.gz
1001
MUV
14400
30
7
1
2
1021
96
900
...
-1
-18.56
4.962
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18397mvn_iuv_l1a_outbound-orbit00108-mode1001-fuvdark_20141018T130302_v01_r01.fits.gz
1001
FUV
1400
165
7
1
52
711
89
893
...
-1
-16.24
4.968
12.670
0Siding
Spr
Spectral
NaN
NaN
NaN
18398mvn_iuv_l1a_outbound-orbit00108-mode1001-muvdark_20141018T130302_v01_r01.fits.gz
1001
MUV
1400
30
7
1
2
1021
96
900
...
-1
-18.71
4.968
12.670
0Siding
Spr
Spectral
NaN
NaN
NaN
18452mvn_iuv_l1a_periapse-orbit00109-mode0001-fuvdark_20141018T160546_v01_r01.fits.gz
1
FUV
4200
256
7
1
0
1023
89
893
...
-1
-16.39
4.930
17.290
0Siding
Spr
Spectral
NaN
NaN
NaN
18453mvn_iuv_l1a_periapse-orbit00109-mode0001-muvdark_20141018T160546_v01_r01.fits.gz
1
MUV
4200
256
7
1
0
1023
96
900
...
-1
-18.86
4.930
17.290
0Siding
Spr
Spectral
NaN
NaN
NaN
18480mvn_iuv_l1a_periapse-orbit00109-mode0001-fuvdark_20141018T162726_v01_r01.fits.gz
1
FUV
4200
256
7
1
0
1023
89
893
...
-1
-15.94
5.101
23.370
0Siding
Spr
Spectral
NaN
NaN
NaN
18481mvn_iuv_l1a_periapse-orbit00109-mode0001-muvdark_20141018T162726_v01_r01.fits.gz
1
MUV
4200
256
7
1
0
1023
96
900
...
-1
-18.41
5.101
23.370
0Siding
Spr
Spectral
NaN
NaN
NaN
18484mvn_iuv_l1a_outbound-orbit00109-mode1001-fuvdark_20141018T165023_v01_r01.fits.gz
1001
FUV
14400
1024
24
1
0
1023
319
582
...
-1
-15.94
5.202
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
18485mvn_iuv_l1a_outbound-orbit00109-mode1001-muvdark_20141018T165023_v01_r01.fits.gz
1001
MUV
14400
1024
24
1
0
1023
441
704
...
-1
-18.56
5.202
89.990
0Siding
Spr
Spectral
NaN
NaN
NaN
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
49421
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49422
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49423
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49424
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49425
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49426
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49427
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49428
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49429
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49430
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49431
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49432
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49433
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49434
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49435
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49436
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49437
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T19...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49438
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T19...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49439
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49440
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49441
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49442
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49443
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49444
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49445
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49446
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49447
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49448
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
65.88
0Siding
Spr
Spectral
NaN
NaN
49449
mvn_iuv_l1a_apoapse-orbit00950-fuv_20150327T20...
8203
FUV
14400
72
10
21
52
627
89
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
49450
mvn_iuv_l1a_apoapse-orbit00950-muv_20150327T20...
8203
MUV
14400
96
10
21
140
907
101
...
-1
-1.00
174.000
1.819
90.1
0Siding
Spr
Spectral
NaN
NaN
16963 rows × 25 columns
In [24]:
l1ameta.columns
Out[24]:
Index(['filename', 'OBS_ID', 'XUV', 'INT_TIME', 'NX', 'NY', 'NZ', 'X1', 'X2', 'Y1', 'Y2', 'BINX', 'BINY', 'MCP_HV', 'SHUT_STATE', 'PHASE', 'MODE', 'CYCLE', 'DET_TEMP', 'CASE_TEMP', 'FOV_DEG', 'STIM_STATE', 'FILL_BINS', 'TARGET', 'PURPOSE'], dtype='object')
In [2]:
dark_multis = l1ameta[(l1ameta.NZ==2) & l1ameta.filename.str.contains('dark')]
Writing function knowing that I picked only dark files with 2 dark obs per file.
In [68]:
def process_fname(fname):
l1a = io.L1AReader(fname)
first, second = l1a.img.mean(axis=(1,2))
diff = (first-second)/first
return fname, diff
In [3]:
from IPython.parallel import Client
In [4]:
c = Client()
lbview = c.load_balanced_view()
In [76]:
results = lbview.map_async(process_fname, dark_multis.filename)
In [7]:
import time
import sys
while not has_spa_size.ready():
print(100*has_spa_size.progress/ len(io.l1a_filenames(iterator=False)))
sys.stdout.flush()
time.sleep(10)
1.7744643211726268
2.2185316894416665
2.653573298193043
3.0669530841020274
3.527266819502861
3.9749444915789662
4.390129429391483
4.83239164575699
5.272848710218965
5.707890318970342
6.179034965792371
6.5978302074119535
6.978717259057349
7.343357943570951
7.792840767550589
8.227882376301967
8.64126216221095
9.121432568550643
9.520371139231367
9.96082820369334
10.368792533891726
10.762315648861852
11.163059371446106
11.545751574995036
12.034947740852393
12.332797804935286
12.80033214795025
13.246204668122823
13.672220517356536
14.072964239940791
14.547719190569886
14.90694441937289
15.278805711500622
15.706626712637869
16.09834467570446
16.48645233496399
16.926909399425963
17.37819737530913
17.764499882665127
18.132750870985795
18.52807913785945
18.96492589851436
19.38913659584454
19.744751520840477
20.076899471090492
20.457786522735887
20.831452966767152
21.190678195570158
21.573370399119085
21.941621387439753
22.37666299619113
22.699785186923478
23.04998465620882
23.50127263209199
23.858692708991462
24.284708558225173
24.620466812282253
24.96886112966406
25.39848728270484
25.7884000938679
26.176507753127424
26.564615412386953
26.96716428687474
27.400400743722585
27.763236276332652
28.21813455602289
28.617073126703612
28.981713811217215
29.39689874902973
29.78139610448219
30.164088308031122
30.604545372493096
31.00528909507735
31.44213585573226
31.842879578316516
32.22918208567251
32.57938155495785
32.94582739137498
33.308662923985054
33.725653013701105
34.15347401483835
34.55060743361554
34.94413054858566
35.39722367637237
35.7690849685001
36.18607505821615
36.60487029983573
37.000198566709386
37.46953806162789
37.890138455151
38.29990793725292
38.742170153618424
39.15554993952741
39.53102153546221
39.96245284040652
40.449843854360346
40.91918334927884
41.35061465422315
41.85966749101937
42.312760618806074
42.751412531364515
43.24060869722187
43.68467606549091
44.11249706662816
44.57100565012546
44.9988266512627
45.4789970576024
45.888766539704314
46.35449573081575
46.72635702294348
47.04947921367583
47.42675596151416
47.838330595519615
48.25532068523566
48.645233496398724
49.0748596494395
49.47740852392729
49.84926981605502
50.313193855262924
50.70130151452245
51.08038341426431
51.49737350398036
51.957687239381194
52.43605249381736
52.847627127822804
53.24837085040706
53.68160730725491
54.05888405509324
54.45060201815983
54.86578695597235
55.31165947614492
55.66185894543026
56.078849035146305
56.47778760582703
56.923660125999604
57.38036355759337
57.78832788779176
58.16740978753362
58.600646244381466
58.99416935935159
59.39491308193585
59.822734083073094
60.23250356517501
60.691012148672314
61.16035164359081
61.56109536617507
62.03043486109356
62.469086773652
62.90773868621044
63.24710724407459
63.694784916150695
64.12441106919147
64.59916601982057
65.05767460331786
65.49091106016571
65.92414751701355
66.38085094860733
66.81769770926223
67.31050417892666
67.74735093958157
68.1300431431305
68.5109301947759
68.98749029730853
69.38642886798924
69.83049623625828
70.3287181616333
70.78542159322707
71.20241168294312
71.67897178547575
72.1844143184649
72.6645847248046
73.04547177644999
73.50037005614023
73.82890770258317
74.31268841272993
74.76578154051663
75.11778616170551
75.55282777045689
75.94454573352347
76.35792551943246
76.74422802678845
77.15399750889037
77.52946910482517
77.97714677690128
78.42662960088091
78.80029604491217
79.2931025145766
79.69384623716086
80.15957542827229
80.6180840117696
80.99897106341498
81.44845388739462
81.90696247089193
82.37088651009982
82.79690235933354
83.19584093001426
83.64893405780096
84.0767550589382
84.49013484484719
84.89268371933498
85.31508926476162
85.71041753163529
86.1472642922902
86.57869559723451
86.98846507933642
87.39281910572775
87.84410708161091
88.2520714118093
88.69252847627128
89.09327219885553
89.51206744047512
89.87851327689225
90.3117497337401
90.75762225391267
91.19266386266405
91.60243334476596
92.01581313067494
92.4165568532592
92.7811975377728
93.19818762748885
93.6422549957579
94.04299871834215
94.49428669422532
94.8968355687131
95.25245049370905
95.61889633012618
95.98895247035038
96.43482499052296
96.82293264978247
97.22006606855967
97.67857465205697
98.06487715941296
98.40785602108417
98.83387187031789
99.21114861815622
99.6191129483546
In [88]:
df = pd.DataFrame(results.result, columns=['filename','diff']).merge(dark_multis, on='filename')
In [90]:
df['diff'].describe()
Out[90]:
count 3168.000000
mean -0.827809
std 10.020196
min -124.531195
25% -0.008314
50% 0.021521
75% 0.061263
max 0.400849
Name: diff, dtype: float64
In [92]:
df['time'] = df.filename.map(lambda x: io.Filename(x).time)
In [93]:
df.set_index('time', inplace=True)
In [95]:
df.sort_index(inplace=True)
In [101]:
%matplotlib inline
In [107]:
df[df['diff']<-5]['diff'].plot(style='*')
Out[107]:
<matplotlib.axes._subplots.AxesSubplot at 0x7f6c49a26518>
In [108]:
messedup = df[df['diff']<-5]
In [110]:
messedup.filename
Out[110]:
time
2015-02-13 06:47:25 mvn_iuv_l1a_outbound-orbit00724-echdark_201502...
2015-02-14 19:06:50 mvn_iuv_l1a_outbound-orbit00732-echdark_201502...
2015-02-15 04:11:49 mvn_iuv_l1a_outbound-orbit00734-echdark_201502...
2015-02-17 10:23:39 mvn_iuv_l1a_outbound-orbit00746-echdark_201502...
2015-02-20 01:27:44 mvn_iuv_l1a_outbound-orbit00760-echdark_201502...
2015-02-20 19:29:46 mvn_iuv_l1a_outbound-orbit00764-echdark_201502...
2015-02-21 04:30:34 mvn_iuv_l1a_outbound-orbit00766-echdark_201502...
2015-02-21 22:32:33 mvn_iuv_l1a_outbound-orbit00770-echdark_201502...
2015-02-22 16:34:26 mvn_iuv_l1a_outbound-orbit00774-echdark_201502...
2015-02-23 10:36:18 mvn_iuv_l1a_outbound-orbit00778-echdark_201502...
2015-02-24 04:38:09 mvn_iuv_l1a_outbound-orbit00782-echdark_201502...
2015-02-25 07:40:51 mvn_iuv_l1a_outbound-orbit00788-echdark_201502...
2015-02-26 01:42:33 mvn_iuv_l1a_outbound-orbit00792-echdark_201502...
2015-02-26 19:44:10 mvn_iuv_l1a_outbound-orbit00796-echdark_201502...
2015-02-27 13:45:45 mvn_iuv_l1a_outbound-orbit00800-echdark_201502...
2015-02-28 16:47:47 mvn_iuv_l1a_outbound-orbit00806-echdark_201502...
2015-03-01 10:49:09 mvn_iuv_l1a_outbound-orbit00810-echdark_201503...
2015-03-02 04:51:26 mvn_iuv_l1a_outbound-orbit00814-echdark_201503...
2015-03-02 22:53:48 mvn_iuv_l1a_outbound-orbit00818-echdark_201503...
2015-03-04 10:58:32 mvn_iuv_l1a_outbound-orbit00826-echdark_201503...
2015-03-05 05:00:50 mvn_iuv_l1a_outbound-orbit00830-echdark_201503...
2015-03-05 23:03:05 mvn_iuv_l1a_outbound-orbit00834-echdark_201503...
2015-03-06 17:05:16 mvn_iuv_l1a_outbound-orbit00838-echdark_201503...
Name: filename, dtype: object
In [139]:
l1a = io.L1AReader(messedup.filename[0])
In [5]:
def check_for_spa_size(fname):
l1a = io.L1AReader(fname)
try:
a = l1a.img_header['SPA_SIZE']
except KeyError:
return (fname, False)
else:
return (fname, True)
In [6]:
has_spa_size = lbview.map_async(check_for_spa_size, io.l1a_filenames())
In [157]:
_, axes = plt.subplots(nrows=2, figsize=(10,10))
l1a.plot_img_profile(0, ax=axes[0], log=False)
l1a.plot_img_profile(1, ax=axes[1], log=False)
plt.savefig('example_echdark_profile.png', dpi=100)
In [173]:
df.plot?
In [174]:
fig, ax = plt.subplots(nrows=3, figsize=(10,10))
df[df['diff']>-5]['diff'].plot(style='*', ax=ax[0], sharex=False)
df[df['diff']<-5]['diff'].plot(style='*', ax=ax[1], sharex=False)
df['diff'].plot(style='*', ax=ax[2], sharex=False)
plt.savefig('all_previous_echdark_plots_in_one.png',dpi=100)
In [167]:
df[df['diff']>-5]['diff'].plot(style='*', figsize=(10,10))
plt.savefig('echdark_usual_dark_ratios.png', dpi=100)
In [168]:
df[df['diff']>-5]['diff'].plot(style='*', figsize=(10,10))
plt.savefig('unusual_echdark_ratios.png', dpi=100)
In [169]:
df['diff'].plot(style='*', figsize=(10,10))
plt.savefig('all_ndim2_dark_ratios.png',dpi=100)
In [171]:
df[df['diff']<-5].filename.values
Out[171]:
array(['mvn_iuv_l1a_outbound-orbit00724-echdark_20150213T064725_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00732-echdark_20150214T190650_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00734-echdark_20150215T041149_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00746-echdark_20150217T102339_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00760-echdark_20150220T012744_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00764-echdark_20150220T192946_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00766-echdark_20150221T043034_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00770-echdark_20150221T223233_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00774-echdark_20150222T163426_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00778-echdark_20150223T103618_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00782-echdark_20150224T043809_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00788-echdark_20150225T074051_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00792-echdark_20150226T014233_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00796-echdark_20150226T194410_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00800-echdark_20150227T134545_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00806-echdark_20150228T164747_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00810-echdark_20150301T104909_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00814-echdark_20150302T045126_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00818-echdark_20150302T225348_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00826-echdark_20150304T105832_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00830-echdark_20150305T050050_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00834-echdark_20150305T230305_v01_s01.fits.gz',
'mvn_iuv_l1a_outbound-orbit00838-echdark_20150306T170516_v01_s01.fits.gz'], dtype=object)
In [8]:
dfhas_spa_size= pd.DataFrame(has_spa_size.result, columns=['filename','has_spa_size'])
In [10]:
dfhas_spa_size.has_spa_size.value_counts()
Out[10]:
True 53291
False 2106
dtype: int64
In [16]:
badfiles = dfhas_spa_size[~dfhas_spa_size.has_spa_size].filename
In [18]:
badfiles.to_csv('files_with_no_SPA_SIZE.csv', index=False)
In [19]:
!head files_with_no_SPA_SIZE.csv
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00408-muv_20141215T010127_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00392-fuv_20141212T004146_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00349-muv_20141203T193524_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00403-muv_20141214T020650_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00414-muv_20141216T044137_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00410-muv_20141215T103331_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00386-muv_20141210T200224_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00395-fuv_20141212T134909_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00350-muvdark_20141203T225847_v01_r01.fits.gz
/maven_iuvs/stage/products/level1a/mvn_iuv_l1a_apoapse-orbit00344-fuvdark_20141202T201151_v01_r01.fits.gz
In [ ]:
Content source: michaelaye/iuvs
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