[Met_help] [rt.rap.ucar.edu #66066] History for tc_stat and tc_pair columns
John Halley Gotway via RT
met_help at ucar.edu
Fri Jan 22 13:18:05 MST 2016
----------------------------------------------------------------
Initial Request
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Hi John-
Would it be possible for tc_stat to dump rows with fixed column widths?
In this example, the columns are misaligned after the INITIALS column.
VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT LEAD
VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR X_ERR
Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP AMAX_WIND
BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34 ASE_WIND_34
BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34 AAL_WIND_50
BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50 ASW_WIND_50
BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64 ANE_WIND_64
BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64 ANW_WIND_64
BNW_WIND_64
V4.1 MPS2 BEST WP122013 WP 12 TRAMI 20130811_000000
2280000 20130820_120000 NA NA TCMPR 1 1 TS
NA NA 32.30000 134.60000 23.90000 126.80000 651.49763
412.83554 503.99998 92.52541 644.77546 60.58750 270.63910 NA 978 NA
60 NA NA 0.00000 90.00000 0.00000
85.00000 0.00000 75.00000 0.00000 100.00000 NA NA
NA 35.00000 NA 30.00000 NA 30.00000 NA
35.00000 NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130817_000000
2280000 20130826_120000 NA NA TCMPR 1 1 TS
NA NA 17.80000 124.20000 17.30000 124.10000 30.54056
5.72064 30.00000 21.73292 21.44925 104.25230 91.06346 NA 996
NA 35 NA NA 0.00000 NA 0.00000
NA 0.00000 NA 0.00000 NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130818_000000
2280000 20130827_120000 NA NA TCMPR 1 1 TS
NA NA 20.70000 115.90000 20.10000 123.50000 428.91396
-427.40050 36.00002 176.20573 -390.96353 119.01410 118.94980 NA 985
NA 50 NA NA 0.00000 40.00000 0.00000
30.00000 0.00000 30.00000 0.00000 35.00000 NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP152013 WP 15 TORAJI 20130825_000000
2280000 20130903_120000 NA NA TCMPR 1 1 TS
NA NA 41.60000 127.10000 30.30000 129.00000 684.25195
-92.28646 677.99995 451.89724 -513.63513 -100.96810 84.68660 NA 985
NA 50 NA NA 0.00000 45.00000 0.00000
50.00000 0.00000 35.00000 0.00000 40.00000 NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130904_000000
2280000 20130913_120000 NA NA TCMPR 1 1 TS
NA NA 18.10000 144.30000 23.20000 139.70000 400.42270
258.26793 -306.00002 -383.28971 -115.62710 1028.66101 648.70898 NA
996 NA 35 NA NA 0.00000 NA
0.00000 NA 0.00000 NA 0.00000 NA NA
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130905_000000
2280000 20130914_120000 NA NA TCMPR 1 1 TS
NA NA 23.40000 138.60000 26.10000 135.60000 230.14142
163.46577 -162.00005 -229.75389 -12.61574 614.51782 387.20541 NA
989 NA 45 NA NA 0.00000 135.00000
0.00000 120.00000 0.00000 120.00000 0.00000 135.00000 NA
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130906_000000
2280000 20130915_120000 NA NA TCMPR 1 1 TS
NA NA 18.10000 142.60000 31.60000 135.10000 907.10389
408.33499 -810.00000 -619.18017 662.68927 991.41199 109.24570 NA
978 NA 60 NA NA 0.00000 130.00000
0.00000 120.00000 0.00000 120.00000 0.00000 130.00000 NA
NA NA 55.00000 NA 55.00000 NA
55.00000 NA 55.00000 NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130907_000000
2280000 20130916_120000 NA NA TCMPR 1 1 EX
NA NA 22.20000 135.20000 40.50000 144.00000 1186.98278
-450.91487 -1097.99995 -1132.64047 354.32543 581.21613 92.07251 NA
985 NA 50 NA NA 0.00000 130.00000
0.00000 120.00000 0.00000 120.00000 0.00000 130.00000 NA
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130910_000000
2280000 20130919_120000 NA NA TCMPR 1 1 ST
NA NA 14.40000 151.30000 18.20000 127.30000 1400.79930
1382.11963 -228.00007 -1179.32775 755.45896 1018.58600 280.86429 NA
918 NA 140 NA NA 0.00000 120.00000
0.00000 110.00000 0.00000 110.00000 0.00000 120.00000 NA
NA NA 80.00000 NA 80.00000 NA
80.00000 NA 80.00000 NA NA NA 50.00000
NA 50.00000 NA 50.00000 NA 50.00000
V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130911_000000
2280000 20130920_120000 NA NA TCMPR 1 1 ST
NA NA 18.70000 127.30000 20.10000 123.70000 220.37362
203.73644 -83.99998 -220.05336 11.11562 283.60529 126.11950 NA 926
NA 130 NA NA 0.00000 175.00000 0.00000
155.00000 0.00000 180.00000 0.00000 185.00000 NA NA
NA 110.00000 NA 100.00000 NA 105.00000 NA
100.00000 NA NA NA 60.00000 NA
60.00000 NA 60.00000 NA 60.00000
V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130913_000000
2280000 20130922_120000 NA NA TCMPR 1 1 TY
NA NA 28.20000 112.10000 22.90000 115.20000 359.56157
-167.81084 318.00007 260.88710 247.33765 -313.14011 -3.89150 NA 963
NA 80 NA NA 0.00000 155.00000 0.00000
140.00000 0.00000 160.00000 0.00000 165.00000 NA NA
NA 80.00000 NA 80.00000 NA 85.00000 NA
90.00000 NA NA NA 45.00000 NA
45.00000 NA 55.00000 NA 55.00000
V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130912_000000
2280000 20130921_120000 NA NA TCMPR 1 1 TS
NA NA 8.80000 143.40000 20.30000 144.30000 691.97683
-52.26869 -689.99994 -238.94929 -649.27874 694.88080 906.01562 NA
989 NA 45 NA NA 0.00000 45.00000
0.00000 45.00000 0.00000 45.00000 0.00000 45.00000
NA NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130913_000000
2280000 20130922_120000 NA NA TCMPR 1 1 TS
NA NA 17.70000 138.30000 22.70000 142.10000 368.49149
-213.97658 -300.00000 -75.00525 -360.70947 811.64050 726.07819 NA
985 NA 50 NA NA 0.00000 75.00000
0.00000 70.00000 0.00000 45.00000 0.00000 55.00000 NA
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130914_000000
2280000 20130923_120000 NA NA TCMPR 1 1 TY
NA NA 23.80000 129.70000 25.20000 140.40000 590.20317
-584.19497 -84.00009 330.11474 -489.12025 427.15900 550.46490 NA
974 NA 65 NA NA 0.00000 70.00000
0.00000 65.00000 0.00000 55.00000 0.00000 60.00000 NA
NA NA 30.00000 NA 30.00000 NA
30.00000 NA 30.00000 NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130915_000000
2280000 20130924_120000 NA NA TCMPR 1 1 TY
NA NA 16.60000 150.20000 26.80000 138.90000 878.28441
629.95205 -611.99993 -848.18204 227.36123 1150.77100 430.30380 NA
967 NA 75 NA NA 0.00000 110.00000
0.00000 100.00000 0.00000 100.00000 0.00000 110.00000 NA
NA NA 50.00000 NA 50.00000 NA
50.00000 NA 50.00000 NA NA NA 20.00000
NA 20.00000 NA 20.00000 NA 20.00000
V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130917_000000
2280000 20130926_120000 NA NA TCMPR 1 1 TS
NA NA 47.10000 159.90000 35.20000 147.70000 902.00008
551.18812 713.99986 863.91157 -258.78148 259.14221 335.57449 NA 982
NA 55 NA NA 0.00000 120.00000 0.00000
115.00000 0.00000 110.00000 0.00000 110.00000 NA NA
NA 20.00000 NA 20.00000 NA 20.00000 NA
20.00000 NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP202013 WP 20 WUTIP 20130918_000000
2280000 20130927_120000 NA NA TCMPR 1 1 TS
NA NA 10.90000 124.40000 16.90000 115.20000 645.53851
535.83577 -360.00000 -535.73486 -359.94175 0.96633 265.55920 NA 993
NA 40 NA NA 0.00000 NA 0.00000
NA 0.00000 NA 0.00000 NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP202013 WP 20 WUTIP 20130919_000000
2280000 20130928_120000 NA NA TCMPR 1 1 TY
NA NA 14.70000 120.30000 16.80000 113.70000 401.42007
381.13263 -125.99997 -401.29847 6.29368 -2.54905 216.48489 NA 974
NA 65 NA NA 0.00000 75.00000 0.00000
60.00000 0.00000 60.00000 0.00000 75.00000 NA NA
NA 35.00000 NA 35.00000 NA 35.00000 NA
35.00000 NA NA NA 20.00000 NA
20.00000 NA 20.00000 NA 20.00000
V4.1 MPS2 BEST WP212013 WP 21 SEPAT 20130922_000000
2280000 20131001_120000 NA NA TCMPR 1 1 TS
NA NA 30.90000 150.10000 31.20000 141.30000 452.70500
452.34701 -18.00007 -94.38948 442.67220 545.13910 233.12720 NA 996
NA 35 NA NA 0.00000 NA 0.00000
NA 0.00000 NA 0.00000 NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130922_000000
2280000 20131001_120000 NA NA TCMPR 1 1 TS
NA NA 14.80000 136.70000 16.00000 131.40000 314.92354
306.58252 -71.99999 -101.06048 298.20785 671.46130 411.86899 NA 985
NA 50 NA NA 0.00000 80.00000 0.00000
80.00000 0.00000 80.00000 0.00000 80.00000 NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130923_000000
2280000 20131002_120000 NA NA TCMPR 1 1 TS
NA NA 19.70000 122.90000 19.00000 129.80000 392.86562
-390.61412 42.00005 157.63196 -359.77769 80.28793 426.59109 NA 978
NA 60 NA NA 0.00000 105.00000 0.00000
95.00000 0.00000 95.00000 0.00000 100.00000 NA NA
NA 40.00000 NA 40.00000 NA 40.00000 NA
40.00000 NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130925_000000
2280000 20131004_120000 NA NA TCMPR 1 1 TY
NA NA 26.80000 136.40000 23.30000 129.00000 453.75560
402.23643 210.00000 -157.15414 425.58503 381.13260 396.91461 NA 959
NA 85 NA NA 0.00000 185.00000 0.00000
180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
NA 115.00000 NA 115.00000 NA 115.00000 NA
115.00000 NA NA NA 65.00000 NA
60.00000 NA 50.00000 NA 65.00000
V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130926_000000
2280000 20131005_120000 NA NA TCMPR 1 1 TY
NA NA 25.90000 136.20000 25.00000 125.90000 560.63609
558.02942 53.99998 -497.84683 257.58144 415.80469 212.22690 NA 956
NA 90 NA NA 0.00000 185.00000 0.00000
180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
NA 115.00000 NA 115.00000 NA 115.00000 NA
115.00000 NA NA NA 65.00000 NA
60.00000 NA 50.00000 NA 65.00000
V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130927_000000
2280000 20131006_120000 NA NA TCMPR 1 1 TY
NA NA 40.20000 155.40000 27.00000 121.70000 1861.09680
1684.16663 792.00005 -781.61516 1688.64187 469.29181 60.47377 NA
974 NA 65 NA NA 0.00000 160.00000
0.00000 160.00000 0.00000 145.00000 0.00000 165.00000 NA
NA NA 85.00000 NA 85.00000 NA
95.00000 NA 95.00000 NA NA NA NA
NA NA NA NA NA NA
V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130926_000000
2280000 20131005_120000 NA NA TCMPR 1 1 TY
NA NA 28.90000 147.40000 19.50000 139.50000 710.64606
432.34460 563.99998 -160.60386 692.12892 519.29248 837.58588 NA 974
NA 65 NA NA 0.00000 65.00000 0.00000
55.00000 0.00000 55.00000 0.00000 65.00000 NA NA
NA 20.00000 NA 20.00000 NA 20.00000 NA
20.00000 NA NA NA NA NA
NA NA NA NA NA
V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130928_000000
2280000 20131007_120000 NA NA TCMPR 1 1 TY
NA NA 17.20000 139.30000 28.00000 127.70000 912.56803
642.55465 -647.99995 -891.27852 195.20035 854.80731 235.05280 NA
933 NA 120 NA NA 0.00000 90.00000
0.00000 90.00000 0.00000 95.00000 0.00000 100.00000 NA
NA NA 50.00000 NA 50.00000 NA
55.00000 NA 60.00000 NA NA NA 30.00000
NA 30.00000 NA 35.00000 NA 35.00000
V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130929_000000
2280000 20131008_120000 NA NA TCMPR 1 1 EX
NA NA 38.30000 137.20000 34.50000 129.60000 432.08312
367.03112 227.99995 413.65747 124.56344 46.20382 41.50455 NA 982 NA
55 NA NA 0.00000 90.00000 0.00000
90.00000 0.00000 75.00000 0.00000 75.00000 NA NA
NA 50.00000 NA 50.00000 NA 50.00000 NA
50.00000 NA NA NA NA NA
NA NA NA NA NA
And could lead time be right-aligned in tc_pair output? It would be nice
to have the hhmmss columns line up.
V4.1 GFSO BEST WP122013 WP 12 TRAMI 20130815_000000
960000 20130819_000000 NA NA TCMPR 34 17 TS
NA DAA 25.00000 128.00000 19.50000 127.90000 330.04672
5.55316 330.00000 -276.47785 -180.14330 326.47580 323.94629 997
989 29 45 NA NA 0.00000 25.00000 0.00000
50.00000 0.00000 50.00000 0.00000 25.00000 NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA
V4.1 GFSO BEST WP122013 WP 12 TRAMI 20130815_000000
1020000 20130819_060000 NA NA TCMPR 34 18 TS
NA DAA 25.00000 128.50000 19.70000 128.10000 318.77369
22.19674 317.99995 246.64050 -201.86271 353.67529 337.48401 994
985 29 50 NA NA 0.00000 60.00000
0.00000 60.00000 0.00000 60.00000 0.00000 60.00000
NA NA NA NA NA NA
NA NA NA NA NA NA NA
NA NA NA NA NA NA NA
Not a show-stopper but it would make things a little easier to read. :)
dave
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Complete Ticket History
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Subject: Re: [rt.rap.ucar.edu #66066] tc_stat and tc_pair columns
From: John Halley Gotway
Time: Fri Apr 04 10:51:34 2014
Dave,
In the tc_pairs tool (and the other MET statistics tools, like Point-
Stat, Grid-Stat, Wavelet-Stat, and MODE), we use a class called
AsciiTable to store the output statistics, format the output
columns, and write the data to the output files. We chose not to
write out fixed-widths columns because there are a few columns that
could have arbitrary length (like AMODEL, BMODEL, and STORM_NAME
in the tc_pairs output). By formatting the output with the AsciiTable
class, we ensure that there is at least one space between the columns
and all the columns line up in a single output file.
However, the tc_stat tool reads the output from many runs of tc_pairs
- much like the stat_analysis and mode_analysis tools read the output
from many runs of the MET statistics tools. Since the
lengths of the strings may vary from run to run (e.g. STORM_NAME =
TOMAS vs GABRIELLE), the output column widths can vary from run to
run. In tc_stat, we read each line, decide whether or not it
meets the filtering criteria, and if it does, write it to the dump
file immediately. We don't buffer the data. So we can end up with
output files that don't exactly line up.
I see the advantage of having the column widths automatically adjust
to the data as far preferable to the rigidity of a fixed-width format.
However, I understand that having the output from tc_stat
(stat_analysis and mode_analysis as well) misaligned is a nuisance.
The lengths of the name for each output column do impose a minimum
column width. Can you tell me which columns are misaligned in your
output? I'm not sure what the culprit would be in the tc_pairs
output.
To address this issue, I see some options as...
(1) We could buffer the data using the AsciiTable class. That'd fix
the problem, but would be much slower and consume too much memory,
especially if we're reading a lot of data. So that isn't really
feasible here.
(2) We could write the data to a temp file, keeping track of the
maximum column widths. Then we could read the data back in and write
it out using those maximum widths. That'd just take a little
extra time to run.
Any thoughts?
Thanks,
John
On 04/02/2014 11:31 AM, David Ahijevych via RT wrote:
>
> Wed Apr 02 11:31:15 2014: Request 66066 was acted upon.
> Transaction: Ticket created by ahijevyc
> Queue: met_help
> Subject: tc_stat and tc_pair columns
> Owner: Nobody
> Requestors: ahijevyc at ucar.edu
> Status: new
> Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>
>
> Hi John-
> Would it be possible for tc_stat to dump rows with fixed column
widths?
> In this example, the columns are misaligned after the INITIALS
column.
> VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT LEAD
> VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
> WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR X_ERR
> Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP AMAX_WIND
> BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34
ASE_WIND_34
> BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34
AAL_WIND_50
> BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50
ASW_WIND_50
> BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64
ANE_WIND_64
> BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64
ANW_WIND_64
> BNW_WIND_64
> V4.1 MPS2 BEST WP122013 WP 12 TRAMI 20130811_000000
> 2280000 20130820_120000 NA NA TCMPR 1 1
TS
> NA NA 32.30000 134.60000 23.90000 126.80000 651.49763
> 412.83554 503.99998 92.52541 644.77546 60.58750 270.63910 NA 978
NA
> 60 NA NA 0.00000 90.00000 0.00000
> 85.00000 0.00000 75.00000 0.00000 100.00000 NA NA
> NA 35.00000 NA 30.00000 NA 30.00000 NA
> 35.00000 NA NA NA NA NA
> NA NA NA NA NA
> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130817_000000
> 2280000 20130826_120000 NA NA TCMPR 1 1
TS
> NA NA 17.80000 124.20000 17.30000 124.10000 30.54056
> 5.72064 30.00000 21.73292 21.44925 104.25230 91.06346 NA 996
> NA 35 NA NA 0.00000 NA 0.00000
> NA 0.00000 NA 0.00000 NA NA NA
> NA NA NA NA NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA
> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130818_000000
> 2280000 20130827_120000 NA NA TCMPR 1 1
TS
> NA NA 20.70000 115.90000 20.10000 123.50000 428.91396
> -427.40050 36.00002 176.20573 -390.96353 119.01410 118.94980 NA
985
> NA 50 NA NA 0.00000 40.00000 0.00000
> 30.00000 0.00000 30.00000 0.00000 35.00000 NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA NA
> NA NA NA NA NA
> V4.1 MPS2 BEST WP152013 WP 15 TORAJI 20130825_000000
> 2280000 20130903_120000 NA NA TCMPR 1 1
TS
> NA NA 41.60000 127.10000 30.30000 129.00000 684.25195
> -92.28646 677.99995 451.89724 -513.63513 -100.96810 84.68660 NA
985
> NA 50 NA NA 0.00000 45.00000 0.00000
> 50.00000 0.00000 35.00000 0.00000 40.00000 NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA NA
> NA NA NA NA NA
> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130904_000000
> 2280000 20130913_120000 NA NA TCMPR 1 1
TS
> NA NA 18.10000 144.30000 23.20000 139.70000 400.42270
> 258.26793 -306.00002 -383.28971 -115.62710 1028.66101 648.70898 NA
> 996 NA 35 NA NA 0.00000 NA
> 0.00000 NA 0.00000 NA 0.00000 NA
NA
> NA NA NA NA NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA NA
> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130905_000000
> 2280000 20130914_120000 NA NA TCMPR 1 1
TS
> NA NA 23.40000 138.60000 26.10000 135.60000 230.14142
> 163.46577 -162.00005 -229.75389 -12.61574 614.51782 387.20541 NA
> 989 NA 45 NA NA 0.00000 135.00000
> 0.00000 120.00000 0.00000 120.00000 0.00000 135.00000
NA
> NA NA NA NA NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA NA
> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130906_000000
> 2280000 20130915_120000 NA NA TCMPR 1 1
TS
> NA NA 18.10000 142.60000 31.60000 135.10000 907.10389
> 408.33499 -810.00000 -619.18017 662.68927 991.41199 109.24570 NA
> 978 NA 60 NA NA 0.00000 130.00000
> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
NA
> NA NA 55.00000 NA 55.00000 NA
> 55.00000 NA 55.00000 NA NA NA NA
> NA NA NA NA NA NA
> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130907_000000
> 2280000 20130916_120000 NA NA TCMPR 1 1
EX
> NA NA 22.20000 135.20000 40.50000 144.00000 1186.98278
> -450.91487 -1097.99995 -1132.64047 354.32543 581.21613 92.07251 NA
> 985 NA 50 NA NA 0.00000 130.00000
> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
NA
> NA NA NA NA NA NA
> NA NA NA NA NA NA NA
> NA NA NA NA NA NA
> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130910_000000
> 2280000 20130919_120000 NA NA TCMPR 1 1
ST
> NA NA 14.40000 151.30000 18.20000 127.30000 1400.79930
> 1382.11963 -228.00007 -1179.32775 755.45896 1018.58600 280.86429 NA
> 918 NA 140 NA NA 0.00000 120.00000
> 0.00000 110.00000 0.00000 110.00000 0.00000 120.00000
NA
> NA NA 80.00000 NA 80.00000 NA
> 80.00000 NA 80.00000 NA NA NA 50.00000
> NA 50.00000 NA 50.00000 NA 50.00000
> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130911_000000
> 2280000 20130920_120000 NA NA TCMPR 1 1
ST
> NA NA 18.70000 127.30000 20.10000 123.70000 220.37362
> 203.73644 -83.99998 -220.05336 11.11562 283.60529 126.11950 NA
926
> NA 130 NA NA 0.00000 175.00000 0.00000
> 155.00000 0.00000 180.00000 0.00000 185.00000 NA NA
> NA 110.00000 NA 100.00000 NA 105.00000 NA
> 100.00000 NA NA NA 60.00000 NA
> 60.00000 NA 60.00000 NA 60.00000
> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130913_000000
> 2280000 20130922_120000 NA NA TCMPR 1 1
TY
> NA NA 28.20000 112.10000 22.90000 115.20000 359.56157
> -167.81084 318.00007 260.88710 247.33765 -313.14011 -3.89150 NA
963
> NA 80 NA NA 0.00000 155.00000 0.00000
> 140.00000 0.00000 160.00000 0.00000 165.00000 NA NA
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>
> And could lead time be right-aligned in tc_pair output? It would be
nice
> to have the hhmmss columns line up.
> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
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0.00000
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318.77369
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> Not a show-stopper but it would make things a little easier to read.
:)
>
> dave
>
------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #66066] tc_stat and tc_pair columns
From: David Ahijevych
Time: Fri Apr 04 11:11:27 2014
Hi John
I knew there was some stuff I hadn't considered!
I can see the dilemma with different storm name lengths and different
runs of tc_pairs. But those issues aren't causing the problem in this
example; the storm name column is fine and tc_stat is reading one
input
file.
It is just that once it gets to ALAT, ALON, BLAT, BLON, TK_ERR, X_ERR,
Y_ERR, ALTK_ERR the number of characters to the left of the decimal
point starts changing. For example, 1.000 has one character and
100.000
has three. That means the column width of 1.000 is 5 and the column
width of 100.000 is 7. It would nice to space-pad or zero pad so the
hundreds column would always be first, then the tens, then the ones,
then the decimal, and so on. Is that doable with the confines of
AsciiTable?
Dave
Dave, In the tc_pairs tool (and the other MET statistics tools, like
Point-Stat, Grid-Stat, Wavelet-Stat, and MODE), we use a class called
AsciiTable to store the output statistics, format the output columns,
and write the data to the output files. We chose not to write out
fixed-widths columns because there are a few columns that could have
arbitrary length (like AMODEL, BMODEL, and STORM_NAME in the tc_pairs
output). By formatting the output with the AsciiTable class, we ensure
that there is at least one space between the columns and all the
columns
line up in a single output file. However, the tc_stat tool reads the
output from many runs of tc_pairs - much like the stat_analysis and
mode_analysis tools read the output from many runs of the MET
statistics
tools. Since the lengths of the strings may vary from run to run (e.g.
STORM_NAME = TOMAS vs GABRIELLE), the output column widths can vary
from
run to run. In tc_stat, we read each line, decide whether or not it
meets the filtering criteria, and if it does, write it to the dump
file
immediately. We don't buffer the data. So we can end up with output
files that don't exactly line up. I see the advantage of having the
column widths automatically adjust to the data as far preferable to
the
rigidity of a fixed-width format. However, I understand that having
the
output from tc_stat (stat_analysis and mode_analysis as well)
misaligned
is a nuisance. The lengths of the name for each output column do
impose
a minimum column width. Can you tell me which columns are misaligned
in
your output? I'm not sure what the culprit would be in the tc_pairs
output. To address this issue, I see some options as... (1) We could
buffer the data using the AsciiTable class. That'd fix the problem,
but
would be much slower and consume too much memory, especially if we're
reading a lot of data. So that isn't really feasible here. (2) We
could
write the data to a temp file, keeping track of the maximum column
widths. Then we could read the data back in and write it out using
those
maximum widths. That'd just take a little extra time to run. Any
thoughts? Thanks, John On 04/02/2014 11:31 AM, David Ahijevych via RT
wrote:
>> Wed Apr 02 11:31:15 2014: Request 66066 was acted upon.
>> Transaction: Ticket created by ahijevyc
>> Queue: met_help
>> Subject: tc_stat and tc_pair columns
>> Owner: Nobody
>> Requestors: ahijevyc at ucar.edu
>> Status: new
>> Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>
>>
>> Hi John-
>> Would it be possible for tc_stat to dump rows with fixed column
widths?
>> In this example, the columns are misaligned after the INITIALS
column.
>> VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT LEAD
>> VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
>> WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR
X_ERR
>> Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP AMAX_WIND
>> BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34
ASE_WIND_34
>> BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34
AAL_WIND_50
>> BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50
ASW_WIND_50
>> BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64
ANE_WIND_64
>> BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64
ANW_WIND_64
>> BNW_WIND_64
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>> NA NA NA NA NA NA
>> NA NA NA NA NA
>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130923_000000
>> 2280000 20131002_120000 NA NA TCMPR 1 1
TS
>> NA NA 19.70000 122.90000 19.00000 129.80000 392.86562
>> -390.61412 42.00005 157.63196 -359.77769 80.28793 426.59109 NA
978
>> NA 60 NA NA 0.00000 105.00000 0.00000
>> 95.00000 0.00000 95.00000 0.00000 100.00000 NA NA
>> NA 40.00000 NA 40.00000 NA 40.00000 NA
>> 40.00000 NA NA NA NA NA
>> NA NA NA NA NA
>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130925_000000
>> 2280000 20131004_120000 NA NA TCMPR 1 1
TY
>> NA NA 26.80000 136.40000 23.30000 129.00000 453.75560
>> 402.23643 210.00000 -157.15414 425.58503 381.13260 396.91461 NA
959
>> NA 85 NA NA 0.00000 185.00000 0.00000
>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>> 115.00000 NA NA NA 65.00000 NA
>> 60.00000 NA 50.00000 NA 65.00000
>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130926_000000
>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>> NA NA 25.90000 136.20000 25.00000 125.90000 560.63609
>> 558.02942 53.99998 -497.84683 257.58144 415.80469 212.22690 NA
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>> NA 90 NA NA 0.00000 185.00000 0.00000
>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>> 115.00000 NA NA NA 65.00000 NA
>> 60.00000 NA 50.00000 NA 65.00000
>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130927_000000
>> 2280000 20131006_120000 NA NA TCMPR 1 1
TY
>> NA NA 40.20000 155.40000 27.00000 121.70000
1861.09680
>> 1684.16663 792.00005 -781.61516 1688.64187 469.29181 60.47377 NA
>> 974 NA 65 NA NA 0.00000 160.00000
>> 0.00000 160.00000 0.00000 145.00000 0.00000 165.00000
NA
>> NA NA 85.00000 NA 85.00000 NA
>> 95.00000 NA 95.00000 NA NA NA NA
>> NA NA NA NA NA NA
>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130926_000000
>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>> NA NA 28.90000 147.40000 19.50000 139.50000 710.64606
>> 432.34460 563.99998 -160.60386 692.12892 519.29248 837.58588 NA
974
>> NA 65 NA NA 0.00000 65.00000 0.00000
>> 55.00000 0.00000 55.00000 0.00000 65.00000 NA NA
>> NA 20.00000 NA 20.00000 NA 20.00000 NA
>> 20.00000 NA NA NA NA NA
>> NA NA NA NA NA
>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130928_000000
>> 2280000 20131007_120000 NA NA TCMPR 1 1
TY
>> NA NA 17.20000 139.30000 28.00000 127.70000 912.56803
>> 642.55465 -647.99995 -891.27852 195.20035 854.80731 235.05280 NA
>> 933 NA 120 NA NA 0.00000 90.00000
>> 0.00000 90.00000 0.00000 95.00000 0.00000 100.00000
NA
>> NA NA 50.00000 NA 50.00000 NA
>> 55.00000 NA 60.00000 NA NA NA 30.00000
>> NA 30.00000 NA 35.00000 NA 35.00000
>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130929_000000
>> 2280000 20131008_120000 NA NA TCMPR 1 1
EX
>> NA NA 38.30000 137.20000 34.50000 129.60000 432.08312
>> 367.03112 227.99995 413.65747 124.56344 46.20382 41.50455 NA 982
NA
>> 55 NA NA 0.00000 90.00000 0.00000
>> 90.00000 0.00000 75.00000 0.00000 75.00000 NA NA
>> NA 50.00000 NA 50.00000 NA 50.00000 NA
>> 50.00000 NA NA NA NA NA
>> NA NA NA NA NA
>>
>> And could lead time be right-aligned in tc_pair output? It would be
nice
>> to have the hhmmss columns line up.
>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
>> 960000 20130819_000000 NA NA TCMPR 34 17 TS
>> NA DAA 25.00000 128.00000 19.50000 127.90000
330.04672
>> 5.55316 330.00000 -276.47785 -180.14330 326.47580 323.94629
997
>> 989 29 45 NA NA 0.00000 25.00000
0.00000
>> 50.00000 0.00000 50.00000 0.00000 25.00000 NA
>> NA NA NA NA NA NA NA
>> NA NA NA NA NA NA NA
>> NA NA NA NA NA
>> V4.1 GFSO BEST WP122013 WP 12 TRAMI 20130815_000000
>> 1020000 20130819_060000 NA NA TCMPR 34 18
TS
>> NA DAA 25.00000 128.50000 19.70000 128.10000
318.77369
>> 22.19674 317.99995 246.64050 -201.86271 353.67529 337.48401
994
>> 985 29 50 NA NA 0.00000 60.00000
>> 0.00000 60.00000 0.00000 60.00000 0.00000 60.00000
>> NA NA NA NA NA NA
>> NA NA NA NA NA NA NA
>> NA NA NA NA NA NA NA
>>
>> Not a show-stopper but it would make things a little easier to
read. :)
>>
>> dave
>>
------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #66066] tc_stat and tc_pair columns
From: John Halley Gotway
Time: Fri Apr 04 11:26:43 2014
Dave,
Ah, I understand now. Yes, I agree, it would be nice to line up the
decimal points in all the output files. I'm going to reassign this
ticket to Randy - who originally developed the AsciiTable
class. Let's see what he says.
Thanks,
John
On 04/04/2014 11:11 AM, David Ahijevych via RT wrote:
>
> <URL: https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>
> Hi John
>
> I knew there was some stuff I hadn't considered!
>
> I can see the dilemma with different storm name lengths and
different
> runs of tc_pairs. But those issues aren't causing the problem in
this
> example; the storm name column is fine and tc_stat is reading one
input
> file.
>
> It is just that once it gets to ALAT, ALON, BLAT, BLON, TK_ERR,
X_ERR,
> Y_ERR, ALTK_ERR the number of characters to the left of the decimal
> point starts changing. For example, 1.000 has one character and
100.000
> has three. That means the column width of 1.000 is 5 and the column
> width of 100.000 is 7. It would nice to space-pad or zero pad so
the
> hundreds column would always be first, then the tens, then the ones,
> then the decimal, and so on. Is that doable with the confines of
AsciiTable?
>
> Dave
>
>
>
>
> Dave, In the tc_pairs tool (and the other MET statistics tools, like
> Point-Stat, Grid-Stat, Wavelet-Stat, and MODE), we use a class
called
> AsciiTable to store the output statistics, format the output
columns,
> and write the data to the output files. We chose not to write out
> fixed-widths columns because there are a few columns that could have
> arbitrary length (like AMODEL, BMODEL, and STORM_NAME in the
tc_pairs
> output). By formatting the output with the AsciiTable class, we
ensure
> that there is at least one space between the columns and all the
columns
> line up in a single output file. However, the tc_stat tool reads the
> output from many runs of tc_pairs - much like the stat_analysis and
> mode_analysis tools read the output from many runs of the MET
statistics
> tools. Since the lengths of the strings may vary from run to run
(e.g.
> STORM_NAME = TOMAS vs GABRIELLE), the output column widths can vary
from
> run to run. In tc_stat, we read each line, decide whether or not it
> meets the filtering criteria, and if it does, write it to the dump
file
> immediately. We don't buffer the data. So we can end up with output
> files that don't exactly line up. I see the advantage of having the
> column widths automatically adjust to the data as far preferable to
the
> rigidity of a fixed-width format. However, I understand that having
the
> output from tc_stat (stat_analysis and mode_analysis as well)
misaligned
> is a nuisance. The lengths of the name for each output column do
impose
> a minimum column width. Can you tell me which columns are misaligned
in
> your output? I'm not sure what the culprit would be in the tc_pairs
> output. To address this issue, I see some options as... (1) We could
> buffer the data using the AsciiTable class. That'd fix the problem,
but
> would be much slower and consume too much memory, especially if
we're
> reading a lot of data. So that isn't really feasible here. (2) We
could
> write the data to a temp file, keeping track of the maximum column
> widths. Then we could read the data back in and write it out using
those
> maximum widths. That'd just take a little extra time to run. Any
> thoughts? Thanks, John On 04/02/2014 11:31 AM, David Ahijevych via
RT
> wrote:
>>> Wed Apr 02 11:31:15 2014: Request 66066 was acted upon.
>>> Transaction: Ticket created by ahijevyc
>>> Queue: met_help
>>> Subject: tc_stat and tc_pair columns
>>> Owner: Nobody
>>> Requestors: ahijevyc at ucar.edu
>>> Status: new
>>> Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>>
>>>
>>> Hi John-
>>> Would it be possible for tc_stat to dump rows with fixed column
widths?
>>> In this example, the columns are misaligned after the INITIALS
column.
>>> VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT LEAD
>>> VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
>>> WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR
X_ERR
>>> Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP AMAX_WIND
>>> BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34
ASE_WIND_34
>>> BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34
AAL_WIND_50
>>> BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50
ASW_WIND_50
>>> BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64
ANE_WIND_64
>>> BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64
ANW_WIND_64
>>> BNW_WIND_64
>>> V4.1 MPS2 BEST WP122013 WP 12 TRAMI 20130811_000000
>>> 2280000 20130820_120000 NA NA TCMPR 1 1
TS
>>> NA NA 32.30000 134.60000 23.90000 126.80000
651.49763
>>> 412.83554 503.99998 92.52541 644.77546 60.58750 270.63910 NA
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>>> 60 NA NA 0.00000 90.00000 0.00000
>>> 85.00000 0.00000 75.00000 0.00000 100.00000 NA NA
>>> NA 35.00000 NA 30.00000 NA 30.00000 NA
>>> 35.00000 NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130817_000000
>>> 2280000 20130826_120000 NA NA TCMPR 1 1
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>>> NA NA 17.80000 124.20000 17.30000 124.10000 30.54056
>>> 5.72064 30.00000 21.73292 21.44925 104.25230 91.06346 NA 996
>>> NA 35 NA NA 0.00000 NA 0.00000
>>> NA 0.00000 NA 0.00000 NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY 20130818_000000
>>> 2280000 20130827_120000 NA NA TCMPR 1 1
TS
>>> NA NA 20.70000 115.90000 20.10000 123.50000
428.91396
>>> -427.40050 36.00002 176.20573 -390.96353 119.01410 118.94980 NA
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>>> NA 50 NA NA 0.00000 40.00000 0.00000
>>> 30.00000 0.00000 30.00000 0.00000 35.00000 NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP152013 WP 15 TORAJI 20130825_000000
>>> 2280000 20130903_120000 NA NA TCMPR 1 1
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>>> NA NA 41.60000 127.10000 30.30000 129.00000
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>>> -92.28646 677.99995 451.89724 -513.63513 -100.96810 84.68660 NA
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>>> NA 50 NA NA 0.00000 45.00000 0.00000
>>> 50.00000 0.00000 35.00000 0.00000 40.00000 NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130904_000000
>>> 2280000 20130913_120000 NA NA TCMPR 1 1
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>>> NA NA 18.10000 144.30000 23.20000 139.70000
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>>> 258.26793 -306.00002 -383.28971 -115.62710 1028.66101 648.70898 NA
>>> 996 NA 35 NA NA 0.00000 NA
>>> 0.00000 NA 0.00000 NA 0.00000 NA
NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130905_000000
>>> 2280000 20130914_120000 NA NA TCMPR 1 1
TS
>>> NA NA 23.40000 138.60000 26.10000 135.60000
230.14142
>>> 163.46577 -162.00005 -229.75389 -12.61574 614.51782 387.20541 NA
>>> 989 NA 45 NA NA 0.00000 135.00000
>>> 0.00000 120.00000 0.00000 120.00000 0.00000 135.00000
NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130906_000000
>>> 2280000 20130915_120000 NA NA TCMPR 1 1
TS
>>> NA NA 18.10000 142.60000 31.60000 135.10000
907.10389
>>> 408.33499 -810.00000 -619.18017 662.68927 991.41199 109.24570 NA
>>> 978 NA 60 NA NA 0.00000 130.00000
>>> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
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>>> NA NA 55.00000 NA 55.00000 NA
>>> 55.00000 NA 55.00000 NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI 20130907_000000
>>> 2280000 20130916_120000 NA NA TCMPR 1 1
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>>> NA NA 22.20000 135.20000 40.50000 144.00000
1186.98278
>>> -450.91487 -1097.99995 -1132.64047 354.32543 581.21613 92.07251 NA
>>> 985 NA 50 NA NA 0.00000 130.00000
>>> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130910_000000
>>> 2280000 20130919_120000 NA NA TCMPR 1 1
ST
>>> NA NA 14.40000 151.30000 18.20000 127.30000
1400.79930
>>> 1382.11963 -228.00007 -1179.32775 755.45896 1018.58600 280.86429
NA
>>> 918 NA 140 NA NA 0.00000 120.00000
>>> 0.00000 110.00000 0.00000 110.00000 0.00000 120.00000
NA
>>> NA NA 80.00000 NA 80.00000 NA
>>> 80.00000 NA 80.00000 NA NA NA 50.00000
>>> NA 50.00000 NA 50.00000 NA 50.00000
>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130911_000000
>>> 2280000 20130920_120000 NA NA TCMPR 1 1
ST
>>> NA NA 18.70000 127.30000 20.10000 123.70000
220.37362
>>> 203.73644 -83.99998 -220.05336 11.11562 283.60529 126.11950 NA
926
>>> NA 130 NA NA 0.00000 175.00000 0.00000
>>> 155.00000 0.00000 180.00000 0.00000 185.00000 NA NA
>>> NA 110.00000 NA 100.00000 NA 105.00000 NA
>>> 100.00000 NA NA NA 60.00000 NA
>>> 60.00000 NA 60.00000 NA 60.00000
>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI 20130913_000000
>>> 2280000 20130922_120000 NA NA TCMPR 1 1
TY
>>> NA NA 28.20000 112.10000 22.90000 115.20000
359.56157
>>> -167.81084 318.00007 260.88710 247.33765 -313.14011 -3.89150 NA
963
>>> NA 80 NA NA 0.00000 155.00000 0.00000
>>> 140.00000 0.00000 160.00000 0.00000 165.00000 NA NA
>>> NA 80.00000 NA 80.00000 NA 85.00000 NA
>>> 90.00000 NA NA NA 45.00000 NA
>>> 45.00000 NA 55.00000 NA 55.00000
>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130912_000000
>>> 2280000 20130921_120000 NA NA TCMPR 1 1
TS
>>> NA NA 8.80000 143.40000 20.30000 144.30000 691.97683
>>> -52.26869 -689.99994 -238.94929 -649.27874 694.88080 906.01562 NA
>>> 989 NA 45 NA NA 0.00000 45.00000
>>> 0.00000 45.00000 0.00000 45.00000 0.00000 45.00000
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130913_000000
>>> 2280000 20130922_120000 NA NA TCMPR 1 1
TS
>>> NA NA 17.70000 138.30000 22.70000 142.10000
368.49149
>>> -213.97658 -300.00000 -75.00525 -360.70947 811.64050 726.07819 NA
>>> 985 NA 50 NA NA 0.00000 75.00000
>>> 0.00000 70.00000 0.00000 45.00000 0.00000 55.00000
NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130914_000000
>>> 2280000 20130923_120000 NA NA TCMPR 1 1
TY
>>> NA NA 23.80000 129.70000 25.20000 140.40000
590.20317
>>> -584.19497 -84.00009 330.11474 -489.12025 427.15900 550.46490 NA
>>> 974 NA 65 NA NA 0.00000 70.00000
>>> 0.00000 65.00000 0.00000 55.00000 0.00000 60.00000
NA
>>> NA NA 30.00000 NA 30.00000 NA
>>> 30.00000 NA 30.00000 NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130915_000000
>>> 2280000 20130924_120000 NA NA TCMPR 1 1
TY
>>> NA NA 16.60000 150.20000 26.80000 138.90000
878.28441
>>> 629.95205 -611.99993 -848.18204 227.36123 1150.77100 430.30380 NA
>>> 967 NA 75 NA NA 0.00000 110.00000
>>> 0.00000 100.00000 0.00000 100.00000 0.00000 110.00000
NA
>>> NA NA 50.00000 NA 50.00000 NA
>>> 50.00000 NA 50.00000 NA NA NA 20.00000
>>> NA 20.00000 NA 20.00000 NA 20.00000
>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK 20130917_000000
>>> 2280000 20130926_120000 NA NA TCMPR 1 1
TS
>>> NA NA 47.10000 159.90000 35.20000 147.70000
902.00008
>>> 551.18812 713.99986 863.91157 -258.78148 259.14221 335.57449 NA
982
>>> NA 55 NA NA 0.00000 120.00000 0.00000
>>> 115.00000 0.00000 110.00000 0.00000 110.00000 NA NA
>>> NA 20.00000 NA 20.00000 NA 20.00000 NA
>>> 20.00000 NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP 20130918_000000
>>> 2280000 20130927_120000 NA NA TCMPR 1 1
TS
>>> NA NA 10.90000 124.40000 16.90000 115.20000
645.53851
>>> 535.83577 -360.00000 -535.73486 -359.94175 0.96633 265.55920 NA
993
>>> NA 40 NA NA 0.00000 NA 0.00000
>>> NA 0.00000 NA 0.00000 NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP 20130919_000000
>>> 2280000 20130928_120000 NA NA TCMPR 1 1
TY
>>> NA NA 14.70000 120.30000 16.80000 113.70000
401.42007
>>> 381.13263 -125.99997 -401.29847 6.29368 -2.54905 216.48489 NA
974
>>> NA 65 NA NA 0.00000 75.00000 0.00000
>>> 60.00000 0.00000 60.00000 0.00000 75.00000 NA NA
>>> NA 35.00000 NA 35.00000 NA 35.00000 NA
>>> 35.00000 NA NA NA 20.00000 NA
>>> 20.00000 NA 20.00000 NA 20.00000
>>> V4.1 MPS2 BEST WP212013 WP 21 SEPAT 20130922_000000
>>> 2280000 20131001_120000 NA NA TCMPR 1 1
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>>> NA NA 30.90000 150.10000 31.20000 141.30000
452.70500
>>> 452.34701 -18.00007 -94.38948 442.67220 545.13910 233.12720 NA
996
>>> NA 35 NA NA 0.00000 NA 0.00000
>>> NA 0.00000 NA 0.00000 NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130922_000000
>>> 2280000 20131001_120000 NA NA TCMPR 1 1
TS
>>> NA NA 14.80000 136.70000 16.00000 131.40000
314.92354
>>> 306.58252 -71.99999 -101.06048 298.20785 671.46130 411.86899 NA
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>>> NA 50 NA NA 0.00000 80.00000 0.00000
>>> 80.00000 0.00000 80.00000 0.00000 80.00000 NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130923_000000
>>> 2280000 20131002_120000 NA NA TCMPR 1 1
TS
>>> NA NA 19.70000 122.90000 19.00000 129.80000
392.86562
>>> -390.61412 42.00005 157.63196 -359.77769 80.28793 426.59109 NA
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>>> NA 60 NA NA 0.00000 105.00000 0.00000
>>> 95.00000 0.00000 95.00000 0.00000 100.00000 NA NA
>>> NA 40.00000 NA 40.00000 NA 40.00000 NA
>>> 40.00000 NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130925_000000
>>> 2280000 20131004_120000 NA NA TCMPR 1 1
TY
>>> NA NA 26.80000 136.40000 23.30000 129.00000
453.75560
>>> 402.23643 210.00000 -157.15414 425.58503 381.13260 396.91461 NA
959
>>> NA 85 NA NA 0.00000 185.00000 0.00000
>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>>> 115.00000 NA NA NA 65.00000 NA
>>> 60.00000 NA 50.00000 NA 65.00000
>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130926_000000
>>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>>> NA NA 25.90000 136.20000 25.00000 125.90000
560.63609
>>> 558.02942 53.99998 -497.84683 257.58144 415.80469 212.22690 NA
956
>>> NA 90 NA NA 0.00000 185.00000 0.00000
>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>>> 115.00000 NA NA NA 65.00000 NA
>>> 60.00000 NA 50.00000 NA 65.00000
>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW 20130927_000000
>>> 2280000 20131006_120000 NA NA TCMPR 1 1
TY
>>> NA NA 40.20000 155.40000 27.00000 121.70000
1861.09680
>>> 1684.16663 792.00005 -781.61516 1688.64187 469.29181 60.47377 NA
>>> 974 NA 65 NA NA 0.00000 160.00000
>>> 0.00000 160.00000 0.00000 145.00000 0.00000 165.00000
NA
>>> NA NA 85.00000 NA 85.00000 NA
>>> 95.00000 NA 95.00000 NA NA NA NA
>>> NA NA NA NA NA NA
>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130926_000000
>>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>>> NA NA 28.90000 147.40000 19.50000 139.50000
710.64606
>>> 432.34460 563.99998 -160.60386 692.12892 519.29248 837.58588 NA
974
>>> NA 65 NA NA 0.00000 65.00000 0.00000
>>> 55.00000 0.00000 55.00000 0.00000 65.00000 NA NA
>>> NA 20.00000 NA 20.00000 NA 20.00000 NA
>>> 20.00000 NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130928_000000
>>> 2280000 20131007_120000 NA NA TCMPR 1 1
TY
>>> NA NA 17.20000 139.30000 28.00000 127.70000
912.56803
>>> 642.55465 -647.99995 -891.27852 195.20035 854.80731 235.05280 NA
>>> 933 NA 120 NA NA 0.00000 90.00000
>>> 0.00000 90.00000 0.00000 95.00000 0.00000 100.00000
NA
>>> NA NA 50.00000 NA 50.00000 NA
>>> 55.00000 NA 60.00000 NA NA NA 30.00000
>>> NA 30.00000 NA 35.00000 NA 35.00000
>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS 20130929_000000
>>> 2280000 20131008_120000 NA NA TCMPR 1 1
EX
>>> NA NA 38.30000 137.20000 34.50000 129.60000
432.08312
>>> 367.03112 227.99995 413.65747 124.56344 46.20382 41.50455 NA
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>>> 55 NA NA 0.00000 90.00000 0.00000
>>> 90.00000 0.00000 75.00000 0.00000 75.00000 NA NA
>>> NA 50.00000 NA 50.00000 NA 50.00000 NA
>>> 50.00000 NA NA NA NA NA
>>> NA NA NA NA NA
>>>
>>> And could lead time be right-aligned in tc_pair output? It would
be nice
>>> to have the hhmmss columns line up.
>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
>>> 960000 20130819_000000 NA NA TCMPR 34 17 TS
>>> NA DAA 25.00000 128.00000 19.50000 127.90000
330.04672
>>> 5.55316 330.00000 -276.47785 -180.14330 326.47580 323.94629
997
>>> 989 29 45 NA NA 0.00000 25.00000
0.00000
>>> 50.00000 0.00000 50.00000 0.00000 25.00000 NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA
>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI 20130815_000000
>>> 1020000 20130819_060000 NA NA TCMPR 34 18
TS
>>> NA DAA 25.00000 128.50000 19.70000 128.10000
318.77369
>>> 22.19674 317.99995 246.64050 -201.86271 353.67529
337.48401 994
>>> 985 29 50 NA NA 0.00000 60.00000
>>> 0.00000 60.00000 0.00000 60.00000 0.00000 60.00000
>>> NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>> NA NA NA NA NA NA NA
>>>
>>> Not a show-stopper but it would make things a little easier to
read. :)
>>>
>>> dave
>>>
>
------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #66066] tc_stat and tc_pair columns
From: John Halley Gotway
Time: Fri Apr 04 14:09:23 2014
Dave,
I talked to Randy about it, and we suggest right-justifying all the
numeric output columns. That should have the effect of lining up the
decimal points. That still won't resolve the misaligned
output columns from tc_stat, stat_analysis, and mode_analysis in all
cases, but it should help make the output more readable.
To get that output to line up in all cases, we'd need to write it to a
temp file first, and then rewrite it using the maximum column widths.
But we're just not convinced it's worth that extra step.
What's your opinion?
I'll define the right-justification of numeric columns as a
development task for the next release.
Thanks,
John
On 04/04/2014 11:26 AM, John Halley Gotway wrote:
> Dave,
>
> Ah, I understand now. Yes, I agree, it would be nice to line up the
decimal points in all the output files. I'm going to reassign this
ticket to Randy - who originally developed the AsciiTable
> class. Let's see what he says.
>
> Thanks,
> John
>
> On 04/04/2014 11:11 AM, David Ahijevych via RT wrote:
>>
>> <URL: https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>
>> Hi John
>>
>> I knew there was some stuff I hadn't considered!
>>
>> I can see the dilemma with different storm name lengths and
different
>> runs of tc_pairs. But those issues aren't causing the problem in
this
>> example; the storm name column is fine and tc_stat is reading one
input
>> file.
>>
>> It is just that once it gets to ALAT, ALON, BLAT, BLON, TK_ERR,
X_ERR,
>> Y_ERR, ALTK_ERR the number of characters to the left of the decimal
>> point starts changing. For example, 1.000 has one character and
100.000
>> has three. That means the column width of 1.000 is 5 and the column
>> width of 100.000 is 7. It would nice to space-pad or zero pad so
the
>> hundreds column would always be first, then the tens, then the
ones,
>> then the decimal, and so on. Is that doable with the confines of
AsciiTable?
>>
>> Dave
>>
>>
>>
>>
>> Dave, In the tc_pairs tool (and the other MET statistics tools,
like
>> Point-Stat, Grid-Stat, Wavelet-Stat, and MODE), we use a class
called
>> AsciiTable to store the output statistics, format the output
columns,
>> and write the data to the output files. We chose not to write out
>> fixed-widths columns because there are a few columns that could
have
>> arbitrary length (like AMODEL, BMODEL, and STORM_NAME in the
tc_pairs
>> output). By formatting the output with the AsciiTable class, we
ensure
>> that there is at least one space between the columns and all the
columns
>> line up in a single output file. However, the tc_stat tool reads
the
>> output from many runs of tc_pairs - much like the stat_analysis and
>> mode_analysis tools read the output from many runs of the MET
statistics
>> tools. Since the lengths of the strings may vary from run to run
(e.g.
>> STORM_NAME = TOMAS vs GABRIELLE), the output column widths can vary
from
>> run to run. In tc_stat, we read each line, decide whether or not it
>> meets the filtering criteria, and if it does, write it to the dump
file
>> immediately. We don't buffer the data. So we can end up with output
>> files that don't exactly line up. I see the advantage of having the
>> column widths automatically adjust to the data as far preferable to
the
>> rigidity of a fixed-width format. However, I understand that having
the
>> output from tc_stat (stat_analysis and mode_analysis as well)
misaligned
>> is a nuisance. The lengths of the name for each output column do
impose
>> a minimum column width. Can you tell me which columns are
misaligned in
>> your output? I'm not sure what the culprit would be in the tc_pairs
>> output. To address this issue, I see some options as... (1) We
could
>> buffer the data using the AsciiTable class. That'd fix the problem,
but
>> would be much slower and consume too much memory, especially if
we're
>> reading a lot of data. So that isn't really feasible here. (2) We
could
>> write the data to a temp file, keeping track of the maximum column
>> widths. Then we could read the data back in and write it out using
those
>> maximum widths. That'd just take a little extra time to run. Any
>> thoughts? Thanks, John On 04/02/2014 11:31 AM, David Ahijevych via
RT
>> wrote:
>>>> Wed Apr 02 11:31:15 2014: Request 66066 was acted upon.
>>>> Transaction: Ticket created by ahijevyc
>>>> Queue: met_help
>>>> Subject: tc_stat and tc_pair columns
>>>> Owner: Nobody
>>>> Requestors: ahijevyc at ucar.edu
>>>> Status: new
>>>> Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>>>
>>>>
>>>> Hi John-
>>>> Would it be possible for tc_stat to dump rows with fixed column
widths?
>>>> In this example, the columns are misaligned after the INITIALS
column.
>>>> VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT LEAD
>>>> VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
>>>> WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR
X_ERR
>>>> Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP AMAX_WIND
>>>> BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34
ASE_WIND_34
>>>> BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34
AAL_WIND_50
>>>> BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50
ASW_WIND_50
>>>> BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64
ANE_WIND_64
>>>> BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64
ANW_WIND_64
>>>> BNW_WIND_64
>>>> V4.1 MPS2 BEST WP122013 WP 12 TRAMI
20130811_000000
>>>> 2280000 20130820_120000 NA NA TCMPR 1 1
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>>>> NA NA 32.30000 134.60000 23.90000 126.80000
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>>>> 412.83554 503.99998 92.52541 644.77546 60.58750 270.63910 NA
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>>>> 60 NA NA 0.00000 90.00000 0.00000
>>>> 85.00000 0.00000 75.00000 0.00000 100.00000 NA NA
>>>> NA 35.00000 NA 30.00000 NA 30.00000 NA
>>>> 35.00000 NA NA NA NA NA
>>>> NA NA NA NA NA
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>>>> 5.72064 30.00000 21.73292 21.44925 104.25230 91.06346 NA 996
>>>> NA 35 NA NA 0.00000 NA 0.00000
>>>> NA 0.00000 NA 0.00000 NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY
20130818_000000
>>>> 2280000 20130827_120000 NA NA TCMPR 1 1
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>>>> NA NA 20.70000 115.90000 20.10000 123.50000
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>>>> -427.40050 36.00002 176.20573 -390.96353 119.01410 118.94980 NA
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>>>> NA 50 NA NA 0.00000 40.00000 0.00000
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>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA
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>>>> -92.28646 677.99995 451.89724 -513.63513 -100.96810 84.68660 NA
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>>>> NA 50 NA NA 0.00000 45.00000 0.00000
>>>> 50.00000 0.00000 35.00000 0.00000 40.00000 NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
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>>>> 258.26793 -306.00002 -383.28971 -115.62710 1028.66101 648.70898
NA
>>>> 996 NA 35 NA NA 0.00000 NA
>>>> 0.00000 NA 0.00000 NA 0.00000 NA
NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
20130905_000000
>>>> 2280000 20130914_120000 NA NA TCMPR 1 1
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>>>> NA NA 23.40000 138.60000 26.10000 135.60000
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>>>> 163.46577 -162.00005 -229.75389 -12.61574 614.51782 387.20541 NA
>>>> 989 NA 45 NA NA 0.00000 135.00000
>>>> 0.00000 120.00000 0.00000 120.00000 0.00000 135.00000
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>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
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>>>> NA NA 18.10000 142.60000 31.60000 135.10000
907.10389
>>>> 408.33499 -810.00000 -619.18017 662.68927 991.41199 109.24570 NA
>>>> 978 NA 60 NA NA 0.00000 130.00000
>>>> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
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>>>> NA NA 55.00000 NA 55.00000 NA
>>>> 55.00000 NA 55.00000 NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
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>>>> NA NA 22.20000 135.20000 40.50000 144.00000
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>>>> -450.91487 -1097.99995 -1132.64047 354.32543 581.21613 92.07251
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>>>> 985 NA 50 NA NA 0.00000 130.00000
>>>> 0.00000 120.00000 0.00000 120.00000 0.00000 130.00000
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>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
20130910_000000
>>>> 2280000 20130919_120000 NA NA TCMPR 1 1
ST
>>>> NA NA 14.40000 151.30000 18.20000 127.30000
1400.79930
>>>> 1382.11963 -228.00007 -1179.32775 755.45896 1018.58600 280.86429
NA
>>>> 918 NA 140 NA NA 0.00000 120.00000
>>>> 0.00000 110.00000 0.00000 110.00000 0.00000 120.00000
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>>>> NA NA 80.00000 NA 80.00000 NA
>>>> 80.00000 NA 80.00000 NA NA NA 50.00000
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>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
20130911_000000
>>>> 2280000 20130920_120000 NA NA TCMPR 1 1
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220.37362
>>>> 203.73644 -83.99998 -220.05336 11.11562 283.60529 126.11950 NA
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>>>> NA 130 NA NA 0.00000 175.00000 0.00000
>>>> 155.00000 0.00000 180.00000 0.00000 185.00000 NA NA
>>>> NA 110.00000 NA 100.00000 NA 105.00000 NA
>>>> 100.00000 NA NA NA 60.00000 NA
>>>> 60.00000 NA 60.00000 NA 60.00000
>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
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359.56157
>>>> -167.81084 318.00007 260.88710 247.33765 -313.14011 -3.89150 NA
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>>>> NA 80 NA NA 0.00000 155.00000 0.00000
>>>> 140.00000 0.00000 160.00000 0.00000 165.00000 NA NA
>>>> NA 80.00000 NA 80.00000 NA 85.00000 NA
>>>> 90.00000 NA NA NA 45.00000 NA
>>>> 45.00000 NA 55.00000 NA 55.00000
>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130912_000000
>>>> 2280000 20130921_120000 NA NA TCMPR 1 1
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>>>> NA NA 8.80000 143.40000 20.30000 144.30000
691.97683
>>>> -52.26869 -689.99994 -238.94929 -649.27874 694.88080 906.01562 NA
>>>> 989 NA 45 NA NA 0.00000 45.00000
>>>> 0.00000 45.00000 0.00000 45.00000 0.00000 45.00000
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130913_000000
>>>> 2280000 20130922_120000 NA NA TCMPR 1 1
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>>>> NA NA 17.70000 138.30000 22.70000 142.10000
368.49149
>>>> -213.97658 -300.00000 -75.00525 -360.70947 811.64050 726.07819 NA
>>>> 985 NA 50 NA NA 0.00000 75.00000
>>>> 0.00000 70.00000 0.00000 45.00000 0.00000 55.00000
NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130914_000000
>>>> 2280000 20130923_120000 NA NA TCMPR 1 1
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>>>> NA NA 23.80000 129.70000 25.20000 140.40000
590.20317
>>>> -584.19497 -84.00009 330.11474 -489.12025 427.15900 550.46490 NA
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>>>> 0.00000 65.00000 0.00000 55.00000 0.00000 60.00000
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>>>> NA NA 30.00000 NA 30.00000 NA
>>>> 30.00000 NA 30.00000 NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130915_000000
>>>> 2280000 20130924_120000 NA NA TCMPR 1 1
TY
>>>> NA NA 16.60000 150.20000 26.80000 138.90000
878.28441
>>>> 629.95205 -611.99993 -848.18204 227.36123 1150.77100 430.30380 NA
>>>> 967 NA 75 NA NA 0.00000 110.00000
>>>> 0.00000 100.00000 0.00000 100.00000 0.00000 110.00000
NA
>>>> NA NA 50.00000 NA 50.00000 NA
>>>> 50.00000 NA 50.00000 NA NA NA 20.00000
>>>> NA 20.00000 NA 20.00000 NA 20.00000
>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130917_000000
>>>> 2280000 20130926_120000 NA NA TCMPR 1 1
TS
>>>> NA NA 47.10000 159.90000 35.20000 147.70000
902.00008
>>>> 551.18812 713.99986 863.91157 -258.78148 259.14221 335.57449 NA
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>>>> NA 55 NA NA 0.00000 120.00000 0.00000
>>>> 115.00000 0.00000 110.00000 0.00000 110.00000 NA NA
>>>> NA 20.00000 NA 20.00000 NA 20.00000 NA
>>>> 20.00000 NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP
20130918_000000
>>>> 2280000 20130927_120000 NA NA TCMPR 1 1
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>>>> NA NA 10.90000 124.40000 16.90000 115.20000
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>>>> 535.83577 -360.00000 -535.73486 -359.94175 0.96633 265.55920 NA
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>>>> NA 40 NA NA 0.00000 NA 0.00000
>>>> NA 0.00000 NA 0.00000 NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP
20130919_000000
>>>> 2280000 20130928_120000 NA NA TCMPR 1 1
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>>>> NA NA 14.70000 120.30000 16.80000 113.70000
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>>>> 381.13263 -125.99997 -401.29847 6.29368 -2.54905 216.48489 NA
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>>>> NA 65 NA NA 0.00000 75.00000 0.00000
>>>> 60.00000 0.00000 60.00000 0.00000 75.00000 NA NA
>>>> NA 35.00000 NA 35.00000 NA 35.00000 NA
>>>> 35.00000 NA NA NA 20.00000 NA
>>>> 20.00000 NA 20.00000 NA 20.00000
>>>> V4.1 MPS2 BEST WP212013 WP 21 SEPAT
20130922_000000
>>>> 2280000 20131001_120000 NA NA TCMPR 1 1
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>>>> NA NA 30.90000 150.10000 31.20000 141.30000
452.70500
>>>> 452.34701 -18.00007 -94.38948 442.67220 545.13910 233.12720 NA
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>>>> NA 35 NA NA 0.00000 NA 0.00000
>>>> NA 0.00000 NA 0.00000 NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130922_000000
>>>> 2280000 20131001_120000 NA NA TCMPR 1 1
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>>>> NA NA 14.80000 136.70000 16.00000 131.40000
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>>>> 306.58252 -71.99999 -101.06048 298.20785 671.46130 411.86899 NA
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>>>> NA 50 NA NA 0.00000 80.00000 0.00000
>>>> 80.00000 0.00000 80.00000 0.00000 80.00000 NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130923_000000
>>>> 2280000 20131002_120000 NA NA TCMPR 1 1
TS
>>>> NA NA 19.70000 122.90000 19.00000 129.80000
392.86562
>>>> -390.61412 42.00005 157.63196 -359.77769 80.28793 426.59109 NA
978
>>>> NA 60 NA NA 0.00000 105.00000 0.00000
>>>> 95.00000 0.00000 95.00000 0.00000 100.00000 NA NA
>>>> NA 40.00000 NA 40.00000 NA 40.00000 NA
>>>> 40.00000 NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130925_000000
>>>> 2280000 20131004_120000 NA NA TCMPR 1 1
TY
>>>> NA NA 26.80000 136.40000 23.30000 129.00000
453.75560
>>>> 402.23643 210.00000 -157.15414 425.58503 381.13260 396.91461 NA
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>>>> NA 85 NA NA 0.00000 185.00000 0.00000
>>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>>>> 115.00000 NA NA NA 65.00000 NA
>>>> 60.00000 NA 50.00000 NA 65.00000
>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130926_000000
>>>> 2280000 20131005_120000 NA NA TCMPR 1 1
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>>>> NA NA 25.90000 136.20000 25.00000 125.90000
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>>>> 558.02942 53.99998 -497.84683 257.58144 415.80469 212.22690 NA
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>>>> NA 90 NA NA 0.00000 185.00000 0.00000
>>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>>> NA 115.00000 NA 115.00000 NA 115.00000 NA
>>>> 115.00000 NA NA NA 65.00000 NA
>>>> 60.00000 NA 50.00000 NA 65.00000
>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130927_000000
>>>> 2280000 20131006_120000 NA NA TCMPR 1 1
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>>>> NA NA 40.20000 155.40000 27.00000 121.70000
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>>>> 1684.16663 792.00005 -781.61516 1688.64187 469.29181 60.47377 NA
>>>> 974 NA 65 NA NA 0.00000 160.00000
>>>> 0.00000 160.00000 0.00000 145.00000 0.00000 165.00000
NA
>>>> NA NA 85.00000 NA 85.00000 NA
>>>> 95.00000 NA 95.00000 NA NA NA NA
>>>> NA NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130926_000000
>>>> 2280000 20131005_120000 NA NA TCMPR 1 1
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>>>> NA NA 28.90000 147.40000 19.50000 139.50000
710.64606
>>>> 432.34460 563.99998 -160.60386 692.12892 519.29248 837.58588 NA
974
>>>> NA 65 NA NA 0.00000 65.00000 0.00000
>>>> 55.00000 0.00000 55.00000 0.00000 65.00000 NA NA
>>>> NA 20.00000 NA 20.00000 NA 20.00000 NA
>>>> 20.00000 NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130928_000000
>>>> 2280000 20131007_120000 NA NA TCMPR 1 1
TY
>>>> NA NA 17.20000 139.30000 28.00000 127.70000
912.56803
>>>> 642.55465 -647.99995 -891.27852 195.20035 854.80731 235.05280 NA
>>>> 933 NA 120 NA NA 0.00000 90.00000
>>>> 0.00000 90.00000 0.00000 95.00000 0.00000 100.00000
NA
>>>> NA NA 50.00000 NA 50.00000 NA
>>>> 55.00000 NA 60.00000 NA NA NA 30.00000
>>>> NA 30.00000 NA 35.00000 NA 35.00000
>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130929_000000
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>>>> NA NA 38.30000 137.20000 34.50000 129.60000
432.08312
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982 NA
>>>> 55 NA NA 0.00000 90.00000 0.00000
>>>> 90.00000 0.00000 75.00000 0.00000 75.00000 NA NA
>>>> NA 50.00000 NA 50.00000 NA 50.00000 NA
>>>> 50.00000 NA NA NA NA NA
>>>> NA NA NA NA NA
>>>>
>>>> And could lead time be right-aligned in tc_pair output? It would
be nice
>>>> to have the hhmmss columns line up.
>>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
>>>> 960000 20130819_000000 NA NA TCMPR 34 17 TS
>>>> NA DAA 25.00000 128.00000 19.50000 127.90000
330.04672
>>>> 5.55316 330.00000 -276.47785 -180.14330 326.47580 323.94629
997
>>>> 989 29 45 NA NA 0.00000 25.00000
0.00000
>>>> 50.00000 0.00000 50.00000 0.00000 25.00000 NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA
>>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
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TS
>>>> NA DAA 25.00000 128.50000 19.70000 128.10000
318.77369
>>>> 22.19674 317.99995 246.64050 -201.86271 353.67529
337.48401 994
>>>> 985 29 50 NA NA 0.00000 60.00000
>>>> 0.00000 60.00000 0.00000 60.00000 0.00000 60.00000
>>>> NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>> NA NA NA NA NA NA NA
>>>>
>>>> Not a show-stopper but it would make things a little easier to
read. :)
>>>>
>>>> dave
>>>>
>>
------------------------------------------------
Subject: Re: [rt.rap.ucar.edu #66066] tc_stat and tc_pair columns
From: David Ahijevych
Time: Fri Apr 04 14:51:17 2014
HI John,
That first suggestion sounds great. It won't solve everything, but it
would fix everything that I found.
For the times it doesn't solve everything, it will still probably be
readable. There are only a few columns with the potential to change;
even the cumulative effect will be small.
Thanks,
Dave
4/4/14 2:09 PM, John Halley Gotway via RT wrote:
> Dave,
>
> I talked to Randy about it, and we suggest right-justifying all the
numeric output columns. That should have the effect of lining up the
decimal points. That still won't resolve the misaligned
> output columns from tc_stat, stat_analysis, and mode_analysis in all
cases, but it should help make the output more readable.
>
> To get that output to line up in all cases, we'd need to write it to
a temp file first, and then rewrite it using the maximum column
widths. But we're just not convinced it's worth that extra step.
> What's your opinion?
>
> I'll define the right-justification of numeric columns as a
development task for the next release.
>
> Thanks,
> John
>
> On 04/04/2014 11:26 AM, John Halley Gotway wrote:
>> Dave,
>>
>> Ah, I understand now. Yes, I agree, it would be nice to line up
the decimal points in all the output files. I'm going to reassign
this ticket to Randy - who originally developed the AsciiTable
>> class. Let's see what he says.
>>
>> Thanks,
>> John
>>
>> On 04/04/2014 11:11 AM, David Ahijevych via RT wrote:
>>> <URL: https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>>
>>> Hi John
>>>
>>> I knew there was some stuff I hadn't considered!
>>>
>>> I can see the dilemma with different storm name lengths and
different
>>> runs of tc_pairs. But those issues aren't causing the problem in
this
>>> example; the storm name column is fine and tc_stat is reading one
input
>>> file.
>>>
>>> It is just that once it gets to ALAT, ALON, BLAT, BLON, TK_ERR,
X_ERR,
>>> Y_ERR, ALTK_ERR the number of characters to the left of the
decimal
>>> point starts changing. For example, 1.000 has one character and
100.000
>>> has three. That means the column width of 1.000 is 5 and the
column
>>> width of 100.000 is 7. It would nice to space-pad or zero pad so
the
>>> hundreds column would always be first, then the tens, then the
ones,
>>> then the decimal, and so on. Is that doable with the confines of
AsciiTable?
>>>
>>> Dave
>>>
>>>
>>>
>>>
>>> Dave, In the tc_pairs tool (and the other MET statistics tools,
like
>>> Point-Stat, Grid-Stat, Wavelet-Stat, and MODE), we use a class
called
>>> AsciiTable to store the output statistics, format the output
columns,
>>> and write the data to the output files. We chose not to write out
>>> fixed-widths columns because there are a few columns that could
have
>>> arbitrary length (like AMODEL, BMODEL, and STORM_NAME in the
tc_pairs
>>> output). By formatting the output with the AsciiTable class, we
ensure
>>> that there is at least one space between the columns and all the
columns
>>> line up in a single output file. However, the tc_stat tool reads
the
>>> output from many runs of tc_pairs - much like the stat_analysis
and
>>> mode_analysis tools read the output from many runs of the MET
statistics
>>> tools. Since the lengths of the strings may vary from run to run
(e.g.
>>> STORM_NAME = TOMAS vs GABRIELLE), the output column widths can
vary from
>>> run to run. In tc_stat, we read each line, decide whether or not
it
>>> meets the filtering criteria, and if it does, write it to the dump
file
>>> immediately. We don't buffer the data. So we can end up with
output
>>> files that don't exactly line up. I see the advantage of having
the
>>> column widths automatically adjust to the data as far preferable
to the
>>> rigidity of a fixed-width format. However, I understand that
having the
>>> output from tc_stat (stat_analysis and mode_analysis as well)
misaligned
>>> is a nuisance. The lengths of the name for each output column do
impose
>>> a minimum column width. Can you tell me which columns are
misaligned in
>>> your output? I'm not sure what the culprit would be in the
tc_pairs
>>> output. To address this issue, I see some options as... (1) We
could
>>> buffer the data using the AsciiTable class. That'd fix the
problem, but
>>> would be much slower and consume too much memory, especially if
we're
>>> reading a lot of data. So that isn't really feasible here. (2) We
could
>>> write the data to a temp file, keeping track of the maximum column
>>> widths. Then we could read the data back in and write it out using
those
>>> maximum widths. That'd just take a little extra time to run. Any
>>> thoughts? Thanks, John On 04/02/2014 11:31 AM, David Ahijevych via
RT
>>> wrote:
>>>>> Wed Apr 02 11:31:15 2014: Request 66066 was acted upon.
>>>>> Transaction: Ticket created by ahijevyc
>>>>> Queue: met_help
>>>>> Subject: tc_stat and tc_pair columns
>>>>> Owner: Nobody
>>>>> Requestors: ahijevyc at ucar.edu
>>>>> Status: new
>>>>> Ticket <URL:
https://rt.rap.ucar.edu/rt/Ticket/Display.html?id=66066 >
>>>>>
>>>>>
>>>>> Hi John-
>>>>> Would it be possible for tc_stat to dump rows with fixed column
widths?
>>>>> In this example, the columns are misaligned after the INITIALS
column.
>>>>> VERSION AMODEL BMODEL STORM_ID BASIN CYCLONE STORM_NAME INIT
LEAD
>>>>> VALID INIT_MASK VALID_MASK LINE_TYPE TOTAL INDEX LEVEL
>>>>> WATCH_WARN INITIALS ALAT ALON BLAT BLON TK_ERR
X_ERR
>>>>> Y_ERR ALTK_ERR CRTK_ERR ADLAND BDLAND AMSLP BMSLP
AMAX_WIND
>>>>> BMAX_WIND AAL_WIND_34 BAL_WIND_34 ANE_WIND_34 BNE_WIND_34
ASE_WIND_34
>>>>> BSE_WIND_34 ASW_WIND_34 BSW_WIND_34 ANW_WIND_34 BNW_WIND_34
AAL_WIND_50
>>>>> BAL_WIND_50 ANE_WIND_50 BNE_WIND_50 ASE_WIND_50 BSE_WIND_50
ASW_WIND_50
>>>>> BSW_WIND_50 ANW_WIND_50 BNW_WIND_50 AAL_WIND_64 BAL_WIND_64
ANE_WIND_64
>>>>> BNE_WIND_64 ASE_WIND_64 BSE_WIND_64 ASW_WIND_64 BSW_WIND_64
ANW_WIND_64
>>>>> BNW_WIND_64
>>>>> V4.1 MPS2 BEST WP122013 WP 12 TRAMI
20130811_000000
>>>>> 2280000 20130820_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 32.30000 134.60000 23.90000 126.80000
651.49763
>>>>> 412.83554 503.99998 92.52541 644.77546 60.58750 270.63910 NA
978 NA
>>>>> 60 NA NA 0.00000 90.00000 0.00000
>>>>> 85.00000 0.00000 75.00000 0.00000 100.00000 NA NA
>>>>> NA 35.00000 NA 30.00000 NA 30.00000
NA
>>>>> 35.00000 NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY
20130817_000000
>>>>> 2280000 20130826_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 17.80000 124.20000 17.30000 124.10000
30.54056
>>>>> 5.72064 30.00000 21.73292 21.44925 104.25230 91.06346 NA 996
>>>>> NA 35 NA NA 0.00000 NA 0.00000
>>>>> NA 0.00000 NA 0.00000 NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP142013 WP 14 KONG-REY
20130818_000000
>>>>> 2280000 20130827_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 20.70000 115.90000 20.10000 123.50000
428.91396
>>>>> -427.40050 36.00002 176.20573 -390.96353 119.01410 118.94980 NA
985
>>>>> NA 50 NA NA 0.00000 40.00000 0.00000
>>>>> 30.00000 0.00000 30.00000 0.00000 35.00000 NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP152013 WP 15 TORAJI
20130825_000000
>>>>> 2280000 20130903_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 41.60000 127.10000 30.30000 129.00000
684.25195
>>>>> -92.28646 677.99995 451.89724 -513.63513 -100.96810 84.68660 NA
985
>>>>> NA 50 NA NA 0.00000 45.00000 0.00000
>>>>> 50.00000 0.00000 35.00000 0.00000 40.00000 NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
20130904_000000
>>>>> 2280000 20130913_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 18.10000 144.30000 23.20000 139.70000
400.42270
>>>>> 258.26793 -306.00002 -383.28971 -115.62710 1028.66101 648.70898
NA
>>>>> 996 NA 35 NA NA 0.00000 NA
>>>>> 0.00000 NA 0.00000 NA 0.00000 NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
20130905_000000
>>>>> 2280000 20130914_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 23.40000 138.60000 26.10000 135.60000
230.14142
>>>>> 163.46577 -162.00005 -229.75389 -12.61574 614.51782 387.20541 NA
>>>>> 989 NA 45 NA NA 0.00000 135.00000
>>>>> 0.00000 120.00000 0.00000 120.00000 0.00000
135.00000 NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
20130906_000000
>>>>> 2280000 20130915_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 18.10000 142.60000 31.60000 135.10000
907.10389
>>>>> 408.33499 -810.00000 -619.18017 662.68927 991.41199 109.24570 NA
>>>>> 978 NA 60 NA NA 0.00000 130.00000
>>>>> 0.00000 120.00000 0.00000 120.00000 0.00000
130.00000 NA
>>>>> NA NA 55.00000 NA 55.00000 NA
>>>>> 55.00000 NA 55.00000 NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP162013 WP 16 MAN-YI
20130907_000000
>>>>> 2280000 20130916_120000 NA NA TCMPR 1 1
EX
>>>>> NA NA 22.20000 135.20000 40.50000 144.00000
1186.98278
>>>>> -450.91487 -1097.99995 -1132.64047 354.32543 581.21613 92.07251
NA
>>>>> 985 NA 50 NA NA 0.00000 130.00000
>>>>> 0.00000 120.00000 0.00000 120.00000 0.00000
130.00000 NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
20130910_000000
>>>>> 2280000 20130919_120000 NA NA TCMPR 1 1
ST
>>>>> NA NA 14.40000 151.30000 18.20000 127.30000
1400.79930
>>>>> 1382.11963 -228.00007 -1179.32775 755.45896 1018.58600 280.86429
NA
>>>>> 918 NA 140 NA NA 0.00000 120.00000
>>>>> 0.00000 110.00000 0.00000 110.00000 0.00000
120.00000 NA
>>>>> NA NA 80.00000 NA 80.00000 NA
>>>>> 80.00000 NA 80.00000 NA NA NA 50.00000
>>>>> NA 50.00000 NA 50.00000 NA 50.00000
>>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
20130911_000000
>>>>> 2280000 20130920_120000 NA NA TCMPR 1 1
ST
>>>>> NA NA 18.70000 127.30000 20.10000 123.70000
220.37362
>>>>> 203.73644 -83.99998 -220.05336 11.11562 283.60529 126.11950 NA
926
>>>>> NA 130 NA NA 0.00000 175.00000 0.00000
>>>>> 155.00000 0.00000 180.00000 0.00000 185.00000 NA NA
>>>>> NA 110.00000 NA 100.00000 NA 105.00000
NA
>>>>> 100.00000 NA NA NA 60.00000 NA
>>>>> 60.00000 NA 60.00000 NA 60.00000
>>>>> V4.1 MPS2 BEST WP172013 WP 17 USAGI
20130913_000000
>>>>> 2280000 20130922_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 28.20000 112.10000 22.90000 115.20000
359.56157
>>>>> -167.81084 318.00007 260.88710 247.33765 -313.14011 -3.89150 NA
963
>>>>> NA 80 NA NA 0.00000 155.00000 0.00000
>>>>> 140.00000 0.00000 160.00000 0.00000 165.00000 NA NA
>>>>> NA 80.00000 NA 80.00000 NA 85.00000
NA
>>>>> 90.00000 NA NA NA 45.00000 NA
>>>>> 45.00000 NA 55.00000 NA 55.00000
>>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130912_000000
>>>>> 2280000 20130921_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 8.80000 143.40000 20.30000 144.30000
691.97683
>>>>> -52.26869 -689.99994 -238.94929 -649.27874 694.88080 906.01562
NA
>>>>> 989 NA 45 NA NA 0.00000 45.00000
>>>>> 0.00000 45.00000 0.00000 45.00000 0.00000
45.00000
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130913_000000
>>>>> 2280000 20130922_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 17.70000 138.30000 22.70000 142.10000
368.49149
>>>>> -213.97658 -300.00000 -75.00525 -360.70947 811.64050 726.07819
NA
>>>>> 985 NA 50 NA NA 0.00000 75.00000
>>>>> 0.00000 70.00000 0.00000 45.00000 0.00000 55.00000
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130914_000000
>>>>> 2280000 20130923_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 23.80000 129.70000 25.20000 140.40000
590.20317
>>>>> -584.19497 -84.00009 330.11474 -489.12025 427.15900 550.46490 NA
>>>>> 974 NA 65 NA NA 0.00000 70.00000
>>>>> 0.00000 65.00000 0.00000 55.00000 0.00000 60.00000
NA
>>>>> NA NA 30.00000 NA 30.00000 NA
>>>>> 30.00000 NA 30.00000 NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130915_000000
>>>>> 2280000 20130924_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 16.60000 150.20000 26.80000 138.90000
878.28441
>>>>> 629.95205 -611.99993 -848.18204 227.36123 1150.77100 430.30380
NA
>>>>> 967 NA 75 NA NA 0.00000 110.00000
>>>>> 0.00000 100.00000 0.00000 100.00000 0.00000
110.00000 NA
>>>>> NA NA 50.00000 NA 50.00000 NA
>>>>> 50.00000 NA 50.00000 NA NA NA 20.00000
>>>>> NA 20.00000 NA 20.00000 NA 20.00000
>>>>> V4.1 MPS2 BEST WP192013 WP 19 PABUK
20130917_000000
>>>>> 2280000 20130926_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 47.10000 159.90000 35.20000 147.70000
902.00008
>>>>> 551.18812 713.99986 863.91157 -258.78148 259.14221 335.57449 NA
982
>>>>> NA 55 NA NA 0.00000 120.00000 0.00000
>>>>> 115.00000 0.00000 110.00000 0.00000 110.00000 NA NA
>>>>> NA 20.00000 NA 20.00000 NA 20.00000
NA
>>>>> 20.00000 NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP
20130918_000000
>>>>> 2280000 20130927_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 10.90000 124.40000 16.90000 115.20000
645.53851
>>>>> 535.83577 -360.00000 -535.73486 -359.94175 0.96633 265.55920 NA
993
>>>>> NA 40 NA NA 0.00000 NA 0.00000
>>>>> NA 0.00000 NA 0.00000 NA NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP202013 WP 20 WUTIP
20130919_000000
>>>>> 2280000 20130928_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 14.70000 120.30000 16.80000 113.70000
401.42007
>>>>> 381.13263 -125.99997 -401.29847 6.29368 -2.54905 216.48489 NA
974
>>>>> NA 65 NA NA 0.00000 75.00000 0.00000
>>>>> 60.00000 0.00000 60.00000 0.00000 75.00000 NA NA
>>>>> NA 35.00000 NA 35.00000 NA 35.00000
NA
>>>>> 35.00000 NA NA NA 20.00000 NA
>>>>> 20.00000 NA 20.00000 NA 20.00000
>>>>> V4.1 MPS2 BEST WP212013 WP 21 SEPAT
20130922_000000
>>>>> 2280000 20131001_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 30.90000 150.10000 31.20000 141.30000
452.70500
>>>>> 452.34701 -18.00007 -94.38948 442.67220 545.13910 233.12720 NA
996
>>>>> NA 35 NA NA 0.00000 NA 0.00000
>>>>> NA 0.00000 NA 0.00000 NA NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130922_000000
>>>>> 2280000 20131001_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 14.80000 136.70000 16.00000 131.40000
314.92354
>>>>> 306.58252 -71.99999 -101.06048 298.20785 671.46130 411.86899 NA
985
>>>>> NA 50 NA NA 0.00000 80.00000 0.00000
>>>>> 80.00000 0.00000 80.00000 0.00000 80.00000 NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130923_000000
>>>>> 2280000 20131002_120000 NA NA TCMPR 1 1
TS
>>>>> NA NA 19.70000 122.90000 19.00000 129.80000
392.86562
>>>>> -390.61412 42.00005 157.63196 -359.77769 80.28793 426.59109 NA
978
>>>>> NA 60 NA NA 0.00000 105.00000 0.00000
>>>>> 95.00000 0.00000 95.00000 0.00000 100.00000 NA NA
>>>>> NA 40.00000 NA 40.00000 NA 40.00000
NA
>>>>> 40.00000 NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130925_000000
>>>>> 2280000 20131004_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 26.80000 136.40000 23.30000 129.00000
453.75560
>>>>> 402.23643 210.00000 -157.15414 425.58503 381.13260 396.91461 NA
959
>>>>> NA 85 NA NA 0.00000 185.00000 0.00000
>>>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>>>> NA 115.00000 NA 115.00000 NA 115.00000
NA
>>>>> 115.00000 NA NA NA 65.00000 NA
>>>>> 60.00000 NA 50.00000 NA 65.00000
>>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130926_000000
>>>>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 25.90000 136.20000 25.00000 125.90000
560.63609
>>>>> 558.02942 53.99998 -497.84683 257.58144 415.80469 212.22690 NA
956
>>>>> NA 90 NA NA 0.00000 185.00000 0.00000
>>>>> 180.00000 0.00000 165.00000 0.00000 170.00000 NA NA
>>>>> NA 115.00000 NA 115.00000 NA 115.00000
NA
>>>>> 115.00000 NA NA NA 65.00000 NA
>>>>> 60.00000 NA 50.00000 NA 65.00000
>>>>> V4.1 MPS2 BEST WP222013 WP 22 FITOW
20130927_000000
>>>>> 2280000 20131006_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 40.20000 155.40000 27.00000 121.70000
1861.09680
>>>>> 1684.16663 792.00005 -781.61516 1688.64187 469.29181 60.47377 NA
>>>>> 974 NA 65 NA NA 0.00000 160.00000
>>>>> 0.00000 160.00000 0.00000 145.00000 0.00000
165.00000 NA
>>>>> NA NA 85.00000 NA 85.00000 NA
>>>>> 95.00000 NA 95.00000 NA NA NA NA
>>>>> NA NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130926_000000
>>>>> 2280000 20131005_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 28.90000 147.40000 19.50000 139.50000
710.64606
>>>>> 432.34460 563.99998 -160.60386 692.12892 519.29248 837.58588 NA
974
>>>>> NA 65 NA NA 0.00000 65.00000 0.00000
>>>>> 55.00000 0.00000 55.00000 0.00000 65.00000 NA NA
>>>>> NA 20.00000 NA 20.00000 NA 20.00000
NA
>>>>> 20.00000 NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130928_000000
>>>>> 2280000 20131007_120000 NA NA TCMPR 1 1
TY
>>>>> NA NA 17.20000 139.30000 28.00000 127.70000
912.56803
>>>>> 642.55465 -647.99995 -891.27852 195.20035 854.80731 235.05280 NA
>>>>> 933 NA 120 NA NA 0.00000 90.00000
>>>>> 0.00000 90.00000 0.00000 95.00000 0.00000
100.00000 NA
>>>>> NA NA 50.00000 NA 50.00000 NA
>>>>> 55.00000 NA 60.00000 NA NA NA 30.00000
>>>>> NA 30.00000 NA 35.00000 NA 35.00000
>>>>> V4.1 MPS2 BEST WP232013 WP 23 DANAS
20130929_000000
>>>>> 2280000 20131008_120000 NA NA TCMPR 1 1
EX
>>>>> NA NA 38.30000 137.20000 34.50000 129.60000
432.08312
>>>>> 367.03112 227.99995 413.65747 124.56344 46.20382 41.50455 NA
982 NA
>>>>> 55 NA NA 0.00000 90.00000 0.00000
>>>>> 90.00000 0.00000 75.00000 0.00000 75.00000 NA NA
>>>>> NA 50.00000 NA 50.00000 NA 50.00000
NA
>>>>> 50.00000 NA NA NA NA NA
>>>>> NA NA NA NA NA
>>>>>
>>>>> And could lead time be right-aligned in tc_pair output? It would
be nice
>>>>> to have the hhmmss columns line up.
>>>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
>>>>> 960000 20130819_000000 NA NA TCMPR 34 17
TS
>>>>> NA DAA 25.00000 128.00000 19.50000 127.90000
330.04672
>>>>> 5.55316 330.00000 -276.47785 -180.14330 326.47580 323.94629
997
>>>>> 989 29 45 NA NA 0.00000 25.00000
0.00000
>>>>> 50.00000 0.00000 50.00000 0.00000 25.00000 NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>> NA NA NA NA NA
>>>>> V4.1 GFSO BEST WP122013 WP 12 TRAMI
20130815_000000
>>>>> 1020000 20130819_060000 NA NA TCMPR 34 18
TS
>>>>> NA DAA 25.00000 128.50000 19.70000 128.10000
318.77369
>>>>> 22.19674 317.99995 246.64050 -201.86271 353.67529
337.48401 994
>>>>> 985 29 50 NA NA 0.00000 60.00000
>>>>> 0.00000 60.00000 0.00000 60.00000 0.00000
60.00000
>>>>> NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA NA
>>>>> NA NA NA NA NA NA
NA
>>>>>
>>>>> Not a show-stopper but it would make things a little easier to
read. :)
>>>>>
>>>>> dave
>>>>>
------------------------------------------------
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