1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
|
WEBVTT captioned by sachac
NOTE Introduction
00:00:00.000 --> 00:00:03.999
Hi, this is Dave O'Toole, and today
00:00:04.000 --> 00:00:07.799
I'll be giving a presentation on tracking health data
00:00:07.800 --> 00:00:12.759
with Emacs, Org Mode, and Gnuplot.
00:00:12.760 --> 00:00:16.079
So Gnuplot is the well-known scientific
00:00:16.080 --> 00:00:19.039
and mathematical plotting application.
00:00:19.040 --> 00:00:24.639
You feed it text files full of names, dates, numbers,
00:00:24.640 --> 00:00:27.199
data points, and you get out a nice graph.
00:00:27.200 --> 00:00:31.119
You can spit out SVG. You can spit out PNG graphics.
00:00:31.120 --> 00:00:33.639
In this case, we're using an SVG.
NOTE How to take daily health journal items
00:00:33.640 --> 00:00:36.839
What I'm going to show you today
00:00:36.840 --> 00:00:39.839
is how to take daily health journal items:
00:00:39.840 --> 00:00:42.119
in other words, things like I exercised
00:00:42.120 --> 00:00:44.319
such and such number of minutes today,
00:00:44.320 --> 00:00:47.399
I got X hours of sleep last night,
00:00:47.400 --> 00:00:51.479
I used such and such number of pieces of nicotine gum,
00:00:51.480 --> 00:00:54.559
say five pieces. So let's see,
00:00:54.560 --> 00:00:58.439
we've got this whole picture here, all right,
00:00:58.440 --> 00:00:59.359
and I've tracked here...
00:00:59.360 --> 00:01:02.319
This is a month of data from my life.
00:01:02.320 --> 00:01:05.159
This is... I'm not showing all the variables,
00:01:05.160 --> 00:01:08.519
but this is what I felt comfortable sharing
00:01:08.520 --> 00:01:14.239
in order to help people who might have a need to track,
00:01:14.240 --> 00:01:15.919
either because of a chronic condition,
00:01:15.920 --> 00:01:18.599
or just because of a health improvement goal
00:01:18.600 --> 00:01:20.959
or what have you, people who might need to
00:01:20.960 --> 00:01:23.319
track health data in a way
00:01:23.320 --> 00:01:24.959
that's a little bit more robust
00:01:24.960 --> 00:01:26.599
than just one or two variables
00:01:26.600 --> 00:01:29.839
and just weight or just blood pressure.
00:01:29.840 --> 00:01:33.079
So in this case, I've got exercise,
00:01:33.080 --> 00:01:36.399
I've got the number of hours of sleep,
00:01:36.400 --> 00:01:38.559
the number of doses of nicotine,
00:01:38.560 --> 00:01:40.799
(that's the yellow line here),
00:01:40.800 --> 00:01:44.199
and this is referring to nicotine gum.
00:01:44.240 --> 00:01:45.559
What we're going to be talking about
00:01:45.560 --> 00:01:47.839
is looking at connections, the idea
00:01:47.840 --> 00:01:49.879
that plotting your data can actually
00:01:49.880 --> 00:01:52.119
help you figure out what's going on.
00:01:52.120 --> 00:01:53.079
This is just one month.
00:01:53.080 --> 00:01:55.439
I've been doing this for a couple of months now,
00:01:55.440 --> 00:01:57.559
but I felt comfortable showing one month
00:01:57.560 --> 00:01:59.439
with a limited subset of the variables.
NOTE How to set up your org templates
00:01:59.440 --> 00:02:02.239
What I'm going to be doing in this presentation
00:02:02.240 --> 00:02:05.279
is showing you how to set up your org templates
00:02:05.280 --> 00:02:08.799
so that you can, you know, hit a hotkey
00:02:08.800 --> 00:02:11.839
to capture today's data with an org template--
00:02:11.840 --> 00:02:14.199
or in this case yesterday's. Usually I'm saying, okay,
00:02:14.200 --> 00:02:15.639
yesterday this happened,
00:02:15.640 --> 00:02:17.479
because you don't know until the day's over
00:02:17.480 --> 00:02:19.719
how many pieces of nicotine gum you ate
00:02:19.720 --> 00:02:21.439
or how many hours you slept.
00:02:21.440 --> 00:02:25.959
So usually we're recording data for the previous day.
00:02:25.960 --> 00:02:28.079
We can set up a capture template
00:02:28.080 --> 00:02:30.919
so that it fills a little org entry. One for exercise,
00:02:30.920 --> 00:02:34.279
one for sleep, one for nicotine, one for distress.
00:02:34.280 --> 00:02:36.919
Here distress is just 1 to 10:
00:02:36.920 --> 00:02:38.559
how bad do you feel today?
00:02:38.560 --> 00:02:41.639
It's not a scientific measure, but you know,
00:02:41.640 --> 00:02:43.359
many, many things ask you to rate
00:02:43.360 --> 00:02:47.119
on a scale of 1 to 10, how bad is the anxiety,
00:02:47.120 --> 00:02:49.639
how bad is the general level of stress,
00:02:49.640 --> 00:02:51.679
and so without a lot of complication,
00:02:51.680 --> 00:02:53.159
I just rate that one to ten.
00:02:53.160 --> 00:02:58.799
Pain, okay, we won't have to get into any details,
00:02:58.800 --> 00:03:00.959
but if there is a level of chronic pain, well,
00:03:00.960 --> 00:03:04.239
I put that between 1 and 10. As we can see here,
00:03:04.240 --> 00:03:07.319
during the period that I've shown you, it's pretty low.
00:03:07.320 --> 00:03:11.919
There's some. If you miss a dose of medication,
00:03:11.920 --> 00:03:13.599
you can track that, in this case
00:03:13.600 --> 00:03:17.639
with a big ugly red triangle, you know.
00:03:17.640 --> 00:03:24.279
You can see, I can see here that in mid-, in late September,
00:03:24.280 --> 00:03:29.199
sorry, in early to mid-October,
00:03:29.200 --> 00:03:30.999
I stopped using the nicotine gum
00:03:31.000 --> 00:03:32.959
and probably should have cut down more gradually
00:03:32.960 --> 00:03:34.759
because my sleep suffered. Look at this.
00:03:34.760 --> 00:03:37.199
The sleep line is down here, okay?
NOTE How to do it in GNU Emacs
00:03:38.320 --> 00:03:39.519
What I'm going to do now,
00:03:39.520 --> 00:03:40.879
now that I've shown you the graph
00:03:40.880 --> 00:03:44.799
and some of the things that are useful about it,
00:03:44.800 --> 00:03:46.639
I'm going to actually take a step back
00:03:46.640 --> 00:03:50.319
and show you from start to finish how you can do this
00:03:50.320 --> 00:03:53.319
in GNU Emacs, and I have a little template generator
00:03:53.320 --> 00:03:56.279
that you can use if you'd like.
00:03:56.280 --> 00:03:59.919
All right, so let's go back.
00:03:59.920 --> 00:04:01.479
Let's step back from this file.
00:04:01.480 --> 00:04:07.599
We're going to split the screen, and on the left side,
00:04:07.600 --> 00:04:09.839
I'm going to put the underlying Org file
00:04:09.840 --> 00:04:10.919
that generates this graph.
00:04:10.920 --> 00:04:16.839
Let me shrink that a little bit.
NOTE Overview of the presentation
00:04:16.840 --> 00:04:22.759
All right, I'm going to work my way backwards
00:04:22.760 --> 00:04:26.519
from the template to the template generator,
00:04:26.520 --> 00:04:28.439
meaning that you'll be able to spit out,
00:04:28.440 --> 00:04:31.839
given your own specification of health variables,
00:04:31.840 --> 00:04:33.519
you'll be able to have it spit out
00:04:33.520 --> 00:04:38.159
a custom Gnuplot script like this
00:04:38.160 --> 00:04:41.319
that's preset up with the definitions
00:04:41.320 --> 00:04:43.159
for the column view in Org mode.
00:04:43.160 --> 00:04:45.399
I'm assuming a little bit of familiarity
00:04:45.400 --> 00:04:47.199
with Org mode and Gnuplotting,
00:04:47.200 --> 00:04:51.959
but I'll try to explain as much as I can as I go along.
NOTE The journal
00:04:51.960 --> 00:04:59.039
The journal here is where... okay, okay, one moment.
00:04:59.040 --> 00:05:03.519
So as you can see, there's a sub-entry here
00:05:03.520 --> 00:05:06.279
for each day that I've included from my data set
00:05:06.280 --> 00:05:08.559
starting on September 13th of this year
00:05:08.560 --> 00:05:10.399
and ending on October 17th.
00:05:10.400 --> 00:05:16.959
And there's an Org property drawer with
00:05:16.960 --> 00:05:22.999
the corresponding names of each field and the value.
00:05:29.800 --> 00:05:36.759
Now the idea here is that the columns specify...
00:05:36.760 --> 00:05:40.639
if you know a little bit about Org mode,
00:05:40.640 --> 00:05:43.479
what happens is that you...
00:05:43.480 --> 00:05:50.919
let's say that I hit the key for my journal template,
00:05:50.920 --> 00:05:52.799
which... Mine is very similar.
NOTE The capture buffer
00:05:52.800 --> 00:06:00.879
This is the capture buffer for today's date,
00:06:00.880 --> 00:06:02.679
and if you're recording yesterday's date,
00:06:02.680 --> 00:06:04.519
you can just flip it like that if you need to.
00:06:04.520 --> 00:06:08.639
Then I say, yesterday, I remember
00:06:08.640 --> 00:06:11.159
I went for about a one-mile walk,
00:06:11.160 --> 00:06:14.119
so that's probably about 20 minutes,
00:06:14.120 --> 00:06:16.519
and that I had such and such,
00:06:16.520 --> 00:06:19.079
I had eight and a half hours of sleep, let's say.
00:06:19.080 --> 00:06:22.479
I estimate how many pieces of nicotine gum I have.
00:06:22.480 --> 00:06:25.799
I try to count as closely as I can, how much distress,
00:06:25.800 --> 00:06:26.359
you know what I mean,
00:06:26.360 --> 00:06:28.279
whether or not I missed a dose of medication.
00:06:28.280 --> 00:06:32.399
Then when you hit C-c C-c,
00:06:32.400 --> 00:06:39.799
it captures that to the end of your Org file.
00:06:39.800 --> 00:06:46.679
Now what this shows is that... I cut and paste it in.
00:06:46.680 --> 00:06:48.159
I've been keeping these entries every day for months,
00:06:48.160 --> 00:06:51.319
and that I cut and pasted in a month of data.
NOTE The columnview table
00:06:51.320 --> 00:07:00.799
Now I'm going to dig in a little bit to the Gnuplot script.
00:07:00.800 --> 00:07:07.759
This here, all this stuff, is one component of the graph,
00:07:07.760 --> 00:07:11.359
and I'll go over how it works.
00:07:11.360 --> 00:07:19.319
First, the items through this column declaration here,
00:07:19.320 --> 00:07:30.199
and the id:myid, this columnview table here,
00:07:30.200 --> 00:07:34.919
#+BEGIN: columnview, this whole bit here,
00:07:34.920 --> 00:07:39.879
is going to get filled in with the corresponding columns,
00:07:39.880 --> 00:07:43.039
exercise minutes, sleep hours, nicotine doses.
00:07:43.040 --> 00:07:53.559
And then it gets pumped out by Org mode into a file
00:07:53.560 --> 00:07:59.840
that looks like this: tab-separated values
00:07:59.841 --> 00:08:03.479
with an ISO-style date at the beginning.
NOTE Gnuplot
00:08:03.480 --> 00:08:10.359
So what we're going to do is we're going to go through
00:08:10.360 --> 00:08:14.479
the Gnuplot portion of this,
00:08:14.480 --> 00:08:16.359
and I'm going to enlarge the font a little.
00:08:21.280 --> 00:08:23.719
I'm going to go line by line through the Gnuplot portion.
00:08:23.720 --> 00:08:30.639
Now, my template generator will give you one like this.
00:08:30.640 --> 00:08:33.119
You don't have to write this from scratch.
00:08:33.120 --> 00:08:35.679
But I'm going to go through it line by line
00:08:35.680 --> 00:08:37.479
because if you do use the template,
00:08:37.480 --> 00:08:42.199
then it'll help to have gone through it line by line,
00:08:42.200 --> 00:08:46.679
because you're probably going to have to modify it.
00:08:46.680 --> 00:08:49.119
So first, we're going to clear the graphics
00:08:49.120 --> 00:08:50.199
from any previous runs
00:08:50.200 --> 00:08:53.799
so that if we reuse the same Gnuplot process,
00:08:53.800 --> 00:08:57.759
we're not overwriting the old--
00:08:57.760 --> 00:09:00.719
that we are completely overwriting the old image.
00:09:00.720 --> 00:09:03.319
So that's the purpose of this line here.
NOTE Output parameters
00:09:03.320 --> 00:09:08.559
The output parameters: we want to put out an SVG file.
00:09:08.560 --> 00:09:13.639
Font Arial, that's funny,
00:09:13.640 --> 00:09:16.119
but I don't know what font it's actually ending up choosing,
00:09:16.120 --> 00:09:16.879
but it looks fine.
00:09:16.880 --> 00:09:19.639
Then we want it to be square,
00:09:19.640 --> 00:09:21.919
so I'm giving it 900 by 900 pixels,
00:09:21.920 --> 00:09:23.719
even though it is a scalable vector graphic.
00:09:23.720 --> 00:09:29.159
We're putting it in the same folder as the org file,
00:09:29.160 --> 00:09:30.799
example.svg.
00:09:30.800 --> 00:09:39.519
These lines here set it up to use the Org mode format
00:09:39.520 --> 00:09:42.679
that we showed in the other file over here.
00:09:42.680 --> 00:09:48.359
The time format is four-digit year, two-digit month,
00:09:48.360 --> 00:09:50.359
two-digit day.
00:09:50.360 --> 00:09:56.479
The time format doesn't specify here the time,
00:09:56.480 --> 00:09:59.599
but that doesn't seem to mess it up.
00:09:59.600 --> 00:10:02.439
This line "set datafile separator" means that
00:10:02.440 --> 00:10:04.239
the separators between that
00:10:04.240 --> 00:10:06.959
and between all the other fields are tabs,
00:10:06.960 --> 00:10:08.919
which is what Org mode does
00:10:08.920 --> 00:10:10.999
when it spits out a table by default.
00:10:11.000 --> 00:10:15.479
Okay, along to the next lines.
NOTE Time series data
00:10:15.480 --> 00:10:18.119
We're going to set up for time series data,
00:10:18.120 --> 00:10:22.807
meaning that the x-axis is going to be time,
00:10:22.808 --> 00:10:26.119
x2tics 1 format.
00:10:26.120 --> 00:10:30.399
I believe this means that every day has one tick
00:10:30.400 --> 00:10:32.879
and that this tells it that the first--
00:10:32.880 --> 00:10:39.359
unfortunately, I forget the exact meaning of this one line.
00:10:39.360 --> 00:10:44.959
I'm just going to move on. We want one X tick per day,
00:10:44.960 --> 00:10:46.519
and because X is in seconds,
00:10:46.520 --> 00:10:50.319
it's 24 hours times 60 minutes times 60 seconds.
00:10:50.320 --> 00:10:55.639
This line "set grid xtics" gives us
00:10:55.640 --> 00:10:57.279
a vertical line on each day of the graph.
00:10:57.280 --> 00:10:58.319
I'll pull up the graph
00:10:58.320 --> 00:11:00.039
just so that it's a little easier to see.
00:11:00.040 --> 00:11:03.919
All these vertical lines, one on each day,
00:11:03.920 --> 00:11:06.199
that's given to you by "set grid xtics".
00:11:06.200 --> 00:11:10.159
One Y tick every five points.
00:11:10.160 --> 00:11:13.719
So here at five pieces of nicotine,
00:11:13.720 --> 00:11:15.959
we've got a five, at ten pieces – well,
00:11:15.960 --> 00:11:19.679
we don't want to eat ten pieces, but ten, fifteen, twenty.
00:11:19.680 --> 00:11:25.479
Rotating the labels to make them fit a little bit better,
00:11:25.480 --> 00:11:28.039
that's this part here where the labels are sideways,
00:11:28.040 --> 00:11:30.639
and even with just one month of data,
00:11:30.640 --> 00:11:35.159
they're getting a little crowded.
00:11:35.160 --> 00:11:41.399
This "set key box lc" just makes the line around the key,
00:11:41.400 --> 00:11:44.039
the legend here, a little bit less severe.
00:11:44.040 --> 00:11:51.079
set xtics format: this makes it so that, for example,
00:11:51.080 --> 00:11:53.479
I've done a United-States-style date here
00:11:53.480 --> 00:11:55.279
with the month and then the day.
00:11:55.280 --> 00:11:58.839
You don't necessarily have to do that.
00:11:58.840 --> 00:12:01.959
You can have whatever you want.
00:12:01.960 --> 00:12:03.079
This xtics format,
00:12:03.080 --> 00:12:06.319
that relates to how the dates are printed.
00:12:06.320 --> 00:12:12.519
Remember that over here, this set timefmt,
00:12:12.520 --> 00:12:15.159
that relates to how the dates are formatted
00:12:15.160 --> 00:12:16.999
in the Org mode output.
00:12:17.000 --> 00:12:18.319
So remember, those are two...
00:12:18.320 --> 00:12:19.519
You don't want to mix those up.
00:12:19.520 --> 00:12:23.799
All right, "yrange [0:40]".
00:12:23.800 --> 00:12:28.719
Thus far, my exercise sessions have all been
00:12:28.720 --> 00:12:31.479
less than 30 minutes, and nothing's gone over 30.
00:12:31.480 --> 00:12:35.839
If you have a health variable
00:12:35.840 --> 00:12:38.119
that is in a significantly different range,
00:12:38.120 --> 00:12:41.639
you may need to get a slightly more complicated
00:12:41.640 --> 00:12:43.719
Gnuplot script because it is possible to plot
00:12:43.720 --> 00:12:46.479
multiple yranges in one plot
00:12:46.480 --> 00:12:48.719
if you have a variable that uses a different range.
00:12:48.720 --> 00:12:49.759
It's just a little trickier.
00:12:49.760 --> 00:12:55.919
These parts here, aside from the fact
00:12:55.920 --> 00:12:59.079
that you might make some changes that relate to
00:12:59.080 --> 00:13:01.319
the date and your country format,
00:13:01.320 --> 00:13:03.239
are going to be the same.
00:13:03.240 --> 00:13:05.919
This is like boilerplate for almost anything.
NOTE Health variables
00:13:05.920 --> 00:13:09.799
Now here are the parts that are going to vary
00:13:09.800 --> 00:13:13.399
depending on what health variables you want to store.
00:13:13.400 --> 00:13:18.039
There are three main sections here.
00:13:18.040 --> 00:13:28.719
One is setting the different line types that are used.
00:13:28.720 --> 00:13:32.479
Setting linetype 1 with line width 2, line color RGB.
00:13:32.480 --> 00:13:34.959
Unfortunately, Gnuplot is a little bit cryptic,
00:13:34.960 --> 00:13:36.879
which is why I've made this template generator
00:13:36.880 --> 00:13:37.999
that I'll show you in a moment.
00:13:38.000 --> 00:13:43.039
I pick a color. So this is exercise, forest green.
00:13:43.040 --> 00:13:49.279
Point size 1, meaning you get
00:13:49.280 --> 00:13:51.599
these little green triangles about that size.
00:13:51.600 --> 00:13:54.719
But the point type 9 is the pointing up triangle.
00:13:54.720 --> 00:13:59.519
Line type 2, purple. So that's the sleep line.
00:13:59.520 --> 00:14:02.999
So we're just establishing these different line types
00:14:03.000 --> 00:14:04.719
that we've given arbitrary numbers.
00:14:04.720 --> 00:14:08.959
Now onto the next section.
00:14:08.960 --> 00:14:12.919
Oh, before I move on here,
00:14:12.920 --> 00:14:16.119
you can see point type 11 for line 5, which is red.
00:14:16.120 --> 00:14:18.079
And that's the missed medications line,
00:14:18.080 --> 00:14:20.639
so you get a triangle that's upside down
00:14:20.640 --> 00:14:22.679
because that's point shape 11.
NOTE Goal lines
00:14:22.680 --> 00:14:27.879
All right. The next section here is the goal lines.
00:14:27.880 --> 00:14:33.440
There are horizontal dashed lines here
00:14:33.441 --> 00:14:37.359
at 8 purple hours of sleep, because 8 hours is the goal.
00:14:37.360 --> 00:14:41.519
So there's a horizontal line at Y = 8.
00:14:41.520 --> 00:14:43.879
For pieces of nicotine gum,
00:14:43.880 --> 00:14:46.959
I'm trying to keep it to around 5 right now.
00:14:46.960 --> 00:14:52.519
So my goal line is at 5. So these...
00:14:52.520 --> 00:14:56.759
Here, a goal of at least 20 minutes of exercise.
00:14:56.760 --> 00:14:59.079
Sometimes I get more, sometimes I get less.
00:14:59.080 --> 00:15:02.199
There's a green line and a 20, showing that that's the goal.
00:15:02.200 --> 00:15:06.479
These lines here are actually the goal lines.
00:15:06.480 --> 00:15:09.119
You can specify the goal for each one
00:15:09.120 --> 00:15:11.999
in the template generator that I'll show you.
NOTE The Gnuplot command
00:15:12.000 --> 00:15:28.079
The last part is the actual plot command.
00:15:28.080 --> 00:15:30.199
So the dependent... So okay,
00:15:30.200 --> 00:15:34.919
these all start with 1, "using 1" against this variable.
00:15:34.920 --> 00:15:41.599
So $2... This is a ternary operator here
00:15:41.600 --> 00:15:49.199
that says if the value of the second column is zero,
00:15:49.200 --> 00:15:52.359
then don't plot a point. In other words,
00:15:52.360 --> 00:15:56.079
not a number means it won't plot a point.
00:15:56.080 --> 00:15:58.919
The template generator lets you skip over
00:15:58.920 --> 00:16:02.119
the details of that. It sticks this in there.
00:16:02.120 --> 00:16:02.759
I'll show you.
00:16:02.760 --> 00:16:09.399
So we only want to plot a point when the value is non-zero.
00:16:09.400 --> 00:16:12.479
If there was no exercise, we're not plotting a point.
00:16:12.480 --> 00:16:15.759
The with construct means we'll plot data
00:16:15.760 --> 00:16:21.340
using date against exercise with points,
00:16:21.341 --> 00:16:25.519
the title is "exercise (minutes)", line type 1.
00:16:25.520 --> 00:16:29.839
Remember, we established line type 1 up here
00:16:29.840 --> 00:16:35.079
as being forest green, point style 1,
00:16:35.080 --> 00:16:37.599
point type 9, green triangles.
00:16:37.600 --> 00:16:42.399
Now I'm going to show 1 against column 3,
00:16:42.400 --> 00:16:43.919
which is "hours of sleep".
00:16:43.920 --> 00:16:46.039
This one is plotted with lines,
00:16:46.040 --> 00:16:48.599
so we don't specify a point type or point size,
00:16:48.600 --> 00:16:51.719
just a line type 2. And remember, you can see
00:16:51.720 --> 00:16:55.240
that line type 2 is defined as purple
00:16:55.241 --> 00:16:57.359
with point type 1, point size 1.
00:16:57.360 --> 00:16:59.959
Okay, so I did specify point size and point type,
00:16:59.960 --> 00:17:01.479
but because I'm not plotting with points,
00:17:01.480 --> 00:17:02.279
those are ignored.
00:17:02.280 --> 00:17:08.799
Here we come to the line with nicotine.
00:17:08.800 --> 00:17:11.559
The fourth column is the nicotine number,
00:17:11.560 --> 00:17:13.199
the fourth column from the Org mode file.
00:17:13.200 --> 00:17:16.007
So here you can see how we're telling Gnuplot
00:17:16.008 --> 00:17:19.799
to take each column of the tab-separated Org mode file
00:17:19.800 --> 00:17:21.119
and put it into the graph.
00:17:21.120 --> 00:17:25.959
The line types are set up here.
00:17:25.960 --> 00:17:30.799
The goal lines are set up here.
00:17:30.800 --> 00:17:35.559
And then the actual plot command is set up here.
NOTE The template generator
00:17:35.560 --> 00:17:41.319
So now we're going to work further backwards
00:17:41.320 --> 00:17:42.959
from this Gnuplot template
00:17:42.960 --> 00:17:46.559
to the template generator that I used to make it.
00:17:46.560 --> 00:18:01.959
Now I'm not going to go into
00:18:01.960 --> 00:18:03.759
all of the details of the code,
00:18:03.760 --> 00:18:06.159
but what I am going to show you is that
00:18:06.160 --> 00:18:10.679
there's a variable called `health-factors'.
00:18:10.680 --> 00:18:15.839
And what this does, this `health-factors-from-list'
00:18:15.840 --> 00:18:20.919
lets you specify, with a property list
00:18:20.920 --> 00:18:22.679
of keyword and value pairs
00:18:22.680 --> 00:18:24.799
(here's the keyword name and the value is exercise),
00:18:24.800 --> 00:18:28.199
the goal that I want 20 minutes of exercise,
00:18:28.200 --> 00:18:30.199
that the unit is minutes,
00:18:30.200 --> 00:18:36.159
that the color is forest green, and so on.
00:18:36.160 --> 00:18:39.439
The aspects of the Gnuplot setup
00:18:39.440 --> 00:18:43.559
have been abstracted here.
00:18:43.560 --> 00:18:49.279
Eight hours of sleep is the goal here.
00:18:49.280 --> 00:18:54.039
The hours are units. What color,
00:18:54.040 --> 00:18:55.119
what thickness of the line.
00:18:55.120 --> 00:19:00.079
Here we specify the number of points.
00:19:00.080 --> 00:19:01.279
There's references online
00:19:01.280 --> 00:19:05.199
that show you what point types are what shapes in Gnuplot,
00:19:05.200 --> 00:19:11.479
and so on and so forth.
NOTE The code that creates a template
00:19:11.480 --> 00:19:17.399
I'll walk through the code a little bit that does this,
00:19:17.400 --> 00:19:20.439
that actually takes these pieces,
00:19:20.440 --> 00:19:24.399
that takes this specification of what your variables are
00:19:24.400 --> 00:19:30.439
and turns it into a template.
00:19:30.440 --> 00:19:37.959
First, I'm using EIEIO,
00:19:37.960 --> 00:19:41.719
the object system that's included with GNU Emacs.
00:19:41.720 --> 00:19:45.119
It's a reasonable facsimile
00:19:45.120 --> 00:19:47.319
of the Common Lisp Object System.
00:19:47.320 --> 00:19:51.239
What I'm going to be doing here
00:19:51.240 --> 00:19:56.199
is defining a class with each of those items,
00:19:56.200 --> 00:19:58.479
those properties that we talked about in that list
00:19:58.480 --> 00:20:01.319
that lets you specify name, what the goal is,
00:20:01.320 --> 00:20:04.239
what the units are, and the Gnuplot things
00:20:04.240 --> 00:20:06.559
(the Gnuplot parameters like thickness,
00:20:06.560 --> 00:20:13.239
plot type, and all that) into a class that will then
00:20:13.240 --> 00:20:16.519
spit out the template once you feed it
00:20:16.520 --> 00:20:27.759
some of these health factor objects. So just a moment.
00:20:27.760 --> 00:20:34.479
For example, you can see that this template
00:20:34.480 --> 00:20:46.319
originally came from being generated by this code here.
00:20:46.320 --> 00:20:52.959
To use the template,
00:20:52.960 --> 00:20:55.399
to use this little template generator...
00:20:55.400 --> 00:21:06.279
See, here's where it spits out the line type
00:21:06.280 --> 00:21:07.439
given the pieces.
00:21:07.440 --> 00:21:09.679
This is all just text formatting.
00:21:09.680 --> 00:21:11.319
This is one of the things that Emacs Lisp
00:21:11.320 --> 00:21:13.159
just really excels at.
00:21:13.160 --> 00:21:19.519
I need to take a piece of data
00:21:19.520 --> 00:21:22.639
like a list of health information,
00:21:22.640 --> 00:21:25.679
a list of health variables, what their units are,
00:21:25.680 --> 00:21:28.119
and how they're supposed to be formatted in Gnuplot,
00:21:28.120 --> 00:21:30.199
and go from that to the nice template.
00:21:30.200 --> 00:21:31.719
So that's pretty much the whole thing.
00:21:31.720 --> 00:21:40.999
I want to see if there's anything I missed.
NOTE The power of the chart
00:21:41.000 --> 00:21:51.519
Bring up the chart.
00:21:51.520 --> 00:21:54.279
This has been really useful
00:21:54.280 --> 00:21:59.599
for communicating with healthcare professionals
00:21:59.600 --> 00:22:04.399
because you are both on the same page
00:22:04.400 --> 00:22:05.879
about exactly what is happening,
00:22:05.880 --> 00:22:10.679
what's been happening because if... Let's say
00:22:10.680 --> 00:22:15.239
that you're tired when you talk to your care provider.
00:22:15.240 --> 00:22:17.559
Well, if you have objective information
00:22:17.560 --> 00:22:18.839
that you've been recording every day,
00:22:18.840 --> 00:22:22.399
that you're ahead of the game, really,
00:22:22.400 --> 00:22:25.119
because you don't need, necessarily, the presence of mind
00:22:25.120 --> 00:22:27.679
to be able to give your care provider
00:22:27.680 --> 00:22:30.039
a complete picture of what's going on in your world.
00:22:30.040 --> 00:22:33.039
If you can find those few minutes a day to enter--
00:22:33.040 --> 00:22:34.399
not even a few minutes,
00:22:34.400 --> 00:22:37.759
really just a minute to enter the data
00:22:37.760 --> 00:22:39.839
and say what happened yesterday...
00:22:39.840 --> 00:22:42.759
I'm finding over these months
00:22:42.760 --> 00:22:45.039
that I've been more in touch with my health when I can--
00:22:45.040 --> 00:22:49.919
not forced, but when I have the habit,
00:22:49.920 --> 00:22:52.159
the consistent habit every single day
00:22:52.160 --> 00:22:55.839
of recording that data--I'm accountable to myself.
00:22:55.840 --> 00:22:57.359
It's interesting.
00:22:57.360 --> 00:23:01.039
I guess it gets into a little bit of ideas
00:23:01.040 --> 00:23:02.439
about the Quantified Self
00:23:02.440 --> 00:23:05.239
and how holding yourself accountable
00:23:05.240 --> 00:23:09.919
can change what you do and what the outcomes are.
00:23:09.920 --> 00:23:14.159
Just look at this here.
00:23:14.160 --> 00:23:17.279
Without getting into too much detail,
00:23:17.280 --> 00:23:19.679
one of the reasons I track my sleep is because,
00:23:19.680 --> 00:23:22.039
as you can see, my sleep
00:23:22.040 --> 00:23:26.759
is not as well-regulated as most people,
00:23:26.760 --> 00:23:31.439
and that's why I need to do that.
00:23:31.440 --> 00:23:34.440
This was a time... 10, 12,
00:23:34.441 --> 00:23:36.639
here's 14 hours of sleep, that's depression.
00:23:36.640 --> 00:23:43.519
It oscillates a little bit. But then below the goal line,
00:23:43.520 --> 00:23:45.639
the things are a little more normal here.
00:23:45.640 --> 00:23:46.919
This is a little more normal.
00:23:46.920 --> 00:23:52.079
But then, really, without thinking about it too much,
00:23:52.080 --> 00:23:56.239
I cut out the nicotine, and my sleep suffered.
00:23:56.240 --> 00:24:00.199
Just the fact that I'm able to look and see that connection
00:24:00.200 --> 00:24:01.359
is really amazing to me.
00:24:01.360 --> 00:24:02.759
Maybe I would have anyway,
00:24:02.760 --> 00:24:05.239
but looking at the whole months of data,
00:24:05.240 --> 00:24:07.399
there have been many things to discuss
00:24:07.400 --> 00:24:09.919
and many things to think about.
NOTE Thanks
00:24:09.920 --> 00:24:12.159
Because this is a short presentation,
00:24:12.160 --> 00:24:13.839
I probably should wrap up.
00:24:13.840 --> 00:24:18.239
I just want to thank the whole Emacs community
00:24:18.240 --> 00:24:23.319
for being there and for including me in the conference
00:24:23.320 --> 00:24:27.079
and I hope to participate next year as well.
00:24:27.080 --> 00:24:29.240
Thank you so much.
|