In [1]:
fnames = io.l1a_filenames("dark", iterator=False, stage=False)
In [3]:
len(fnames)
Out[3]:
6307
In [5]:
from IPython.parallel import Client
c = Client()
In [6]:
dview = c.direct_view()
lview = c.load_balanced_view()
In [7]:
l1a = io.L1AReader(fnames[0])
In [8]:
io.get_header_df(l1a.hdulist[0]).T.convert_objects()
Out[8]:
SIMPLE
BITPIX
NAXIS
NAXIS1
NAXIS2
NAXIS3
EXTEND
BLANK
FILENAME
CAPTURE
...
OBS_ID
INT_TIME
MCP_VOLT
MIR_DEG
N_FILL
BIN_TBL
SPA_OFS
SPA_SIZE
SPE_OFS
SPE_SIZE
0
True
32
3
256
10
21
True
-1
mvn_iuv_l1a_apoapse-orbit00626-fuvdark_2015012...
2015/025 Jan 25 15:33:02.76293UTC
...
8198
14.4
-1.83
32.901
0
LINEAR 15,16 linear_0006
89
80
0
4
1 rows × 23 columns
In [13]:
integration_df = l1a.Integration.T.set_index('ET')
In [17]:
integration_df['mean'] = l1a.img.mean(axis=(1,2))
In [18]:
integration_df['std'] = l1a.img.std(axis=(1,2))
In [33]:
for col in l1a.Observation.columns:
print(col.name)
PRODUCT_ID
COLLECTION_ID
BUNDLE_ID
CODE_SVN_REVISION
ANC_SVN_REVISION
PRODUCT_CREATION_DATE
OBSERVATION_TYPE
MISSION_PHASE
TARGET_NAME
ORBIT_SEGMENT
ORBIT_NUMBER
SOLAR_LONGITUDE
GRATING_SELECT
KEYHOLE_SELECT
BIN_PATTERN_INDEX
CADENCE
INT_TIME
DUTY_CYCLE
CHANNEL
WAVELENGTH
WAVELENGTH_WIDTH
KERNELS
In [6]:
def process_fname(fname):
import numpy as np
l1a = io.L1AReader(fname)
header_df = io.get_header_df(l1a.hdulist[0]).T.convert_objects()
if header_df['NAXIS'] == 2:
header_df['NAXIS3'] = np.nan
header_df.drop(['XUV', 'OBS_ID', 'INT_TIME'], axis=1, inplace=True)
df = pd.concat([header_df,
l1a.Engineering.T.convert_objects(),],
axis=1)
df['primary_mean'] = l1a.img.mean()
df['primary_std'] = l1a.img.std()
if df.size != 61:
return df, False
else:
savepath = io.save_to_hdf(df, fname, 'l1a_dark_scans')
return df, True
In [7]:
results = lview.map_async(process_fname, fnames)
In [36]:
size_not_61 = []
dfs = []
for res in results:
if not res[1]:
size_not_61.append(res[0].FILENAME)
dfs.append(res[0])
In [38]:
pd.concat(dfs, axis=0)
Out[38]:
AVERAGE
BIN_SHIFT
BIN_SHIFT_DIR
BIN_TBL
BIN_TYPE
BIN_X_ROW
BIN_Y_ROW
BITPIX
BLANK
BSCALE
...
START_TIME
START_TIME__SUB
STEP_INT
STEP_NUM
STEP_SIZE
SW_VER
TEST_PATTERN
TIME_FLAG
XUV
primary_mean
0
1922
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
480692579
27611
3
315
14
915
12
Synced
FUV
2663.203505
0
61733
4
1
NON LINEAR 13,13 nonlin_0001
NON LINEAR
13
13
32
-1
NaN
...
471877268
49002
3
60
14
-1
12
Synced
MUV
42290.504348
0
20721
0
0
NON LINEAR 12,12 nonlin_0001
NON LINEAR
12
12
32
-1
NaN
...
471616886
64371
3
315
14
-1
12
Synced
FUV
53130.544629
0
2413
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
478823096
65025
3
315
14
-1
12
Synced
MUV
3223.514683
0
1328
0
0
LINEAR 5,6 linear_0011
LINEAR
5
6
32
-1
NaN
...
480734258
40827
255
0
-1
917
12
Synced
FUV
971.874286
0
7683
4
0
LINEAR 7,8 linear_0011
LINEAR
7
8
32
-1
NaN
...
480326751
11588
3
101
13
911:913
12
Synced
MUV
53573.423197
0
9966
6
1
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
478940579
22379
3
315
14
911
12
Synced
MUV
61692.067361
0
9440
1
1
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479731313
143
3
315
14
911
12
Synced
FUV
15389.216402
0
17650
0
0
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
478630201
7337
3
315
14
-1
12
Synced
FUV
32192.207490
0
32111
0
0
LINEAR 0,19 linear_0011
LINEAR
0
19
32
-1
NaN
...
479222776
1124
255
0
-1
911
12
Synced
MUV
23181.817627
0
3821
0
0
LINEAR 5,6 linear_0011
LINEAR
5
6
32
-1
NaN
...
479190975
33497
255
0
-1
911
12
Synced
FUV
2794.985000
0
3360
0
0
LINEAR 17,18 linear_0009
LINEAR
17
18
32
-1
NaN
...
478614286
31208
3
315
14
-1
12
Synced
MUV
17964.374603
0
1928
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
480694505
26957
3
315
14
917
12
Synced
FUV
2678.315807
0
5421
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
478843182
5702
3
315
14
-1
12
Synced
MUV
57163.442758
0
2536
1
1
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
479602728
64044
3
315
14
911
12
Synced
MUV
5439.402083
0
3383
0
0
LINEAR 17,18 linear_0009
LINEAR
17
18
32
-1
NaN
...
477933423
470
3
315
14
-1
12
Synced
MUV
110870.110159
0
14467
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479767037
64044
3
315
14
911
12
Synced
FUV
38898.092725
0
3623
0
0
LINEAR 17,18 linear_0009
LINEAR
17
18
32
-1
NaN
...
478093770
60120
3
315
14
-1
12
Synced
MUV
12729.946032
0
5143
0
0
NON LINEAR 13,13 nonlin_0001
NON LINEAR
13
13
32
-1
NaN
...
470907305
62736
3
315
14
-1
12
Synced
MUV
11332.875983
0
2242
0
0
LINEAR 7,8 linear_0009
LINEAR
7
8
32
-1
NaN
...
478281964
6029
3
101
-11
-1
12
Synced
MUV
1372.002551
0
31456
0
0
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
476310944
43770
3
315
14
-1
12
Synced
FUV
36074.099107
0
2197
0
0
LINEAR 11,12 linear_0006
LINEAR
11
12
32
-1
NaN
...
476234113
4067
255
0
-1
-1
12
Synced
FUV
2014.989177
0
1871
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479929291
5375
3
315
14
911:913
12
Synced
FUV
2691.514286
0
7832
1
1
LINEAR 5,6 linear_0011
LINEAR
5
6
32
-1
NaN
...
479855767
19109
3
101
25
911:913
12
Synced
FUV
6816.452075
0
3616
0
0
LINEAR 17,18 linear_0009
LINEAR
17
18
32
-1
NaN
...
478158677
13223
3
315
14
-1
12
Synced
MUV
12632.639365
0
17555
0
0
LINEAR 7,8 linear_0009
LINEAR
7
8
32
-1
NaN
...
478119049
32189
3
101
25
-1
12
Synced
MUV
32868.954932
0
12086
1
1
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479539418
26957
3
315
14
911
12
Synced
FUV
15807.014087
0
60617
0
0
NON LINEAR 13,13 nonlin_0001
NON LINEAR
13
13
32
-1
NaN
...
471794791
36767
3
60
14
-1
12
Synced
MUV
41484.841304
0
16958
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
478777923
5375
3
315
14
-1
12
Synced
FUV
35438.433333
0
2407
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
480888932
42135
3
315
14
917
12
Synced
MUV
2505.559028
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
...
0
61
0
0
LINEAR 1,2 linear_0006
LINEAR
1
2
32
-1
NaN
...
477247772
17474
255
0
-1
-1
12
Synced
FUV
260.983333
0
16164
3
1
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479328811
2105
3
315
14
911
12
Synced
FUV
40920.806283
0
4992
4
1
NON LINEAR 13,13 nonlin_0001
NON LINEAR
13
13
32
-1
NaN
...
471913787
56523
3
315
14
-1
12
Synced
MUV
11234.824845
0
22201
1
1
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
476628472
36440
3
315
14
-1
12
Synced
FUV
34976.648165
0
1920
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
480674402
3740
3
315
14
915
12
Synced
FUV
2730.076058
0
21764
0
0
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
476792734
1124
3
315
14
-1
12
Synced
FUV
38581.768204
0
14944
0
0
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
478126226
45078
3
315
14
-1
12
Synced
FUV
15213.472470
0
2297
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
480985245
29900
3
315
14
917
12
Synced
MUV
2496.904663
0
4071
0
0
LINEAR 9,10 linear_0010
LINEAR
9
10
32
-1
NaN
...
477894538
2105
255
0
-1
-1
12
Synced
FUV
161.524748
0
2076
0
0
LINEAR 7,8 linear_0009
LINEAR
7
8
32
-1
NaN
...
476354099
42789
3
101
30
-1
12
Synced
MUV
2107.544962
0
48346
4
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
480401647
23033
3
315
14
911:913
12
Synced
MUV
163177.213790
0
9898
1
1
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479716662
7010
3
315
14
911
12
Synced
FUV
13145.500198
0
2408
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
479180836
55215
3
315
14
911
12
Synced
MUV
8378.715774
0
2109
1
1
LINEAR 7,8 linear_0009
LINEAR
7
8
32
-1
NaN
...
476783655
5048
3
101
-11
-1
12
Synced
MUV
1357.574511
0
2807
0
0
LINEAR 5,6 linear_0009
LINEAR
5
6
32
-1
NaN
...
477794616
64371
3
101
-25
-1
12
Synced
FUV
3907.151077
0
2357
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
480690654
45078
3
315
14
915
12
Synced
MUV
2513.807341
0
15881
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
479476446
58812
3
315
14
911
12
Synced
FUV
33883.674405
0
59435
0
0
LINEAR 5,5 linear_0008
LINEAR
5
5
32
-1
NaN
...
477659010
34805
255
0
-1
-1
12
Synced
MUV
14857.743164
0
44351
0
0
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
476281165
55542
3
315
14
-1
12
Synced
FUV
51213.313046
0
2659
0
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
479456049
52599
3
315
14
911
12
Synced
MUV
3117.794345
0
5589
4
0
LINEAR 5,6 linear_0011
LINEAR
5
6
32
-1
NaN
...
480392965
10934
255
0
-1
911:913
12
Synced
FUV
4087.895000
0
19374
1
1
LINEAR 15,16 linear_0009
LINEAR
15
16
32
-1
NaN
...
478340352
10934
3
315
14
-1
12
Synced
FUV
31529.082639
0
19172
0
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
480222854
14858
3
315
14
911:913
12
Synced
FUV
49619.280886
0
3934
0
0
LINEAR 5,6 linear_0009
LINEAR
5
6
32
-1
NaN
...
477924105
21071
3
101
23
-1
12
Synced
FUV
6988.576531
0
3505
0
0
LINEAR 5,6 linear_0009
LINEAR
5
6
32
-1
NaN
...
478606052
51945
3
101
-30
-1
12
Synced
FUV
5176.238450
0
2681
3
0
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
480235257
57504
3
315
14
911:913
12
Synced
MUV
2887.264385
0
2222
0
0
LINEAR 0,19 linear_0009
LINEAR
0
19
32
-1
NaN
...
477797758
29900
255
0
-1
-1
12
Synced
FUV
92.616130
0
52
0
0
LINEAR 1,2 linear_0006
LINEAR
1
2
32
-1
NaN
...
478870848
47694
255
0
-1
-1
12
Synced
FUV
225.762500
0
10901
1
1
LINEAR 17,18 linear_0011
LINEAR
17
18
32
-1
NaN
...
479588427
38402
3
315
14
911
12
Synced
MUV
103847.657341
0
13621
4
0
LINEAR 15,16 linear_0011
LINEAR
15
16
32
-1
NaN
...
480449123
15512
3
315
14
915
12
Synced
FUV
20075.114881
16102 rows × 63 columns
In [ ]:
In [8]:
from iuvs import multitools
In [9]:
multitools.progress_display(results, fnames, sleep=20)
2.3 % done.
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In [10]:
import glob
h5fnames = glob.glob("/home/klay6683/output/l1a_dark_scans/*.h5")
In [11]:
len(h5fnames)
Out[11]:
40421
In [12]:
def chunker(seq, size):
return (seq[pos:pos + size] for pos in range(0, len(seq), size))
In [13]:
dfs = []
for i,chunk in enumerate(chunker(h5fnames, 200)):
print("Chunk {}".format(i))
frames = []
for fname in chunk:
frames.append(pd.read_hdf(fname, 'df'))
dfs.append(pd.concat(frames, ignore_index=True))
Chunk 0
Chunk 1
Chunk 2
Chunk 3
Chunk 4
Chunk 5
Chunk 6
Chunk 7
Chunk 8
Chunk 9
Chunk 10
Chunk 11
Chunk 12
Chunk 13
Chunk 14
Chunk 15
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In [14]:
superdf = pd.concat(dfs, ignore_index=True)
In [15]:
superdf.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 40421 entries, 0 to 40420
Data columns (total 63 columns):
AVERAGE 40421 non-null float64
BIN_SHIFT 40421 non-null int64
BIN_SHIFT_DIR 40421 non-null int64
BIN_TBL 40421 non-null object
BIN_TYPE 40421 non-null object
BIN_X_ROW 40421 non-null int64
BIN_Y_ROW 40421 non-null int64
BITPIX 40421 non-null int64
BLANK 40421 non-null int64
BSCALE 494 non-null float64
BZERO 494 non-null float64
CADENCE 40421 non-null float64
CAPTURE 40421 non-null object
CASE_TEMP 39927 non-null float64
CHECKSUM 40421 non-null float64
DATA_COMPRESSION 40421 non-null int64
DET_TEMP 39927 non-null float64
EXTEND 40421 non-null bool
FILENAME 40421 non-null object
FUV_BAD_PIXEL_MASK 40421 non-null int64
IMAGE_NUMBER 40421 non-null float64
INT_TIME 40421 non-null float64
LENGTH 40421 non-null float64
MCP_GAIN 40421 non-null float64
MCP_VOLT 40421 non-null float64
MIRROR_POS 40421 non-null float64
MIR_DEG 40421 non-null float64
MODE 40421 non-null object
MUV_BAD_PIXEL_MASK 40421 non-null int64
NAXIS 40421 non-null int64
NAXIS1 40421 non-null int64
NAXIS2 40421 non-null int64
NAXIS3 19545 non-null float64
NUMBER 40421 non-null float64
N_FILL 40421 non-null int64
OBS_ID 40421 non-null float64
ON_CHIP_WINDOWING 40421 non-null int64
PROCESS 40421 non-null object
SCAN_MODE 40421 non-null object
SCI_ERR_FLAGS 40421 non-null int64
SCI_PKT_CKSUM 40421 non-null int64
SCI_SEG_LENGTH 40421 non-null float64
SCI_SEG_NUM 40421 non-null float64
SCI_SEG_TOTAL 40421 non-null float64
SET_TOTAL 40421 non-null float64
SHUTTER_NUM 40421 non-null int64
SHUTTER_OFF 40421 non-null float64
SHUTTER_ON 40421 non-null float64
SIMPLE 40421 non-null bool
SPA_OFS 40421 non-null int64
SPA_SIZE 40421 non-null int64
SPE_OFS 40421 non-null int64
SPE_SIZE 40421 non-null int64
START_TIME 40421 non-null float64
START_TIME__SUB 40421 non-null float64
STEP_INT 40421 non-null int64
STEP_NUM 40421 non-null float64
STEP_SIZE 40421 non-null int64
SW_VER 40421 non-null object
TEST_PATTERN 40421 non-null int64
TIME_FLAG 40421 non-null object
XUV 40421 non-null object
primary_mean 40154 non-null float64
dtypes: bool(2), float64(27), int64(24), object(10)
memory usage: 19.2+ MB
In [18]:
from iuvs import calib
In [19]:
superdf.DET_TEMP = superdf.DET_TEMP.map(calib.convert_det_temp_to_C)
superdf.CASE_TEMP = superdf.CASE_TEMP.map(calib.convert_case_temp_to_C)
In [20]:
superdf.to_hdf('/home/klay6683/output/l1a_summary.h5','df')
In [21]:
meta.produce_summary_txt(superdf, 'l1a_summary.txt')
In [ ]:
Content source: michaelaye/iuvs
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