John's Vademecum - public:miscellany:watches

COSC

anonymous@undisclosed.example.com (Anonymous) — Tue, 30 Dec 2025 09:55:07 +0000

COSC

History

COSC

Test definitions

15 day test regime

Day	Temp/°C	Pos	Daily rate	Variance
1	23	6H	M1
2	23		M2	V1
3	23	3H	M3
4	23		M4	V2
5	23	9H	M5
6	23		M6	V3
7	23	Dd	M7
8	23		M8	V4
9	23	Du	M9
10	23		M10	V5
11	8	Du	M11
12	23	Du	M12
13	38	Du	M13
14	23	6H	M14
15	23	6H	M15

Test	ID	Description	Limit
Mean Daily Rate M(1→10)	M	average of M1 → M10	-4/+6
Mean Variation	V	average of V1 → V5	2
Greatest Variation	V_max	Largest of V1 → V5	5
Difference V → H	D	Average(M1→M2) - Average(M9→M10)	-6 / +8
Largest Variation from mean	P	Largest Value difference between any individual M and average of M(1→10)	10
Thermal Variation	C	(M13 - M11) / (38 - 8)	±0.6
Rate Resumption	R	M15 - Ave(M1→M2)	±5

pseudo Tests with Timegrapher

Ignoring Temperature Variations.

Make 2 measurements on Timegrapher in each position, separated by 24 hours and record them in table:

Day	Pos	Daily rate	Variance
1	6H	M1
2		M2	V1
3	3H	M3
4		M4	V2
5	9H	M5
6		M6	V3
7	Ddn	M7
8		M8	V4
9	Dup	M9
14	6H	M14
15	6H	M15

Some results

Archimede Deck watch (a 10 day test, not a timegrapher pseudo-test)

Day	Pos		Daily rate		Variance
1	6H	M1	+0.3
2		M2	+1.3	V1	1.0
3	3H	M3	-0.7
4		M4	-1.7	V2	1.0
5	9H	M5	+8.2
6		M6	+6.1	V3	2.1
7	Dd	M7	+11.0
8		M8	+10.9	V4	0.1
9	Du	M9	+9.9
10		M10	+9.5	V5	0.4
14	6H	M14	+2.5
15	6H	M15	+2.7

Test	Desc	Result	Pass/Fail	Limit
M	Mean Daily Rate	+5.5	Pass	-4 / +6
V	Mean Variation	0.9	Pass	2
V_max	Greatest Variation	2.1	Pass	5
D	Difference Vert → Horiz	-8.9	Fail	-6 / +8
P	Largest Difference from Mean	7.2	Pass	10
R	Rate resumption	1.9	Pass	-5 / +5

Page created Sun May 22 00:23:48 2022 by John Pumford-Green

Page last updated: 30/12/25 09:55 GMT

watch, cosc

Rolex Info

anonymous@undisclosed.example.com (Anonymous) — Tue, 30 Dec 2025 09:55:07 +0000

←Watches

Rolex Info

History

Interesting Current Models

Milgauss

Date	Model Reference	Calibre	List Price
Dec 2017	116400GV		£6050
Oct 2018	116400GV		£6300
May 2019			£6300
Jan 2020			£6650
Sep 2021	116400GV		£6650
May 2022	116400GV	3131	£7350
Oct 2023	Has been discontinued

Explorer I

Date	Model Reference	Calibre	List Price
Oct 2018	214270 39mm		£5000
May 2019			£5000
Jan 2020			£5200
Sep 2021	124270 36mm		£5150
May 2022	124270 36mm	3230	£5700
Oct 2023	124270 36mm	3230	£6100
Feb 2025	124270 36mm	3230	£6400

GMT Master II

Date	Model Reference	Calibre	List Price
Oct 2018	126710BLRO		£7150
Jan 2020			£7750
Sep 2021	126710BLNR		£7750
May 2022	126710BLNR	3285	£8400
Oct 2023	126710BLNR	3285	£9150
Feb 2025	126710BLNR	3285	£9450

Submariner

Date	Model Reference	Calibre	List Price
Oct 2018	116610LN		£6650
May 2019			£6650
Jan 2020			£7150
Nov 2020	126610LV		£7650
Sep 2021			£7300
May 2022	126610LN	3235	£8050
Oct 2023	126610LN	3235	£8650
Feb 2025	126610LN	3235	£9100

Air King

Date	Model Reference	Calibre	List Price
May 2022	126900	3230	£5900
Oct 2023	126900	3230	£6250
Feb 2025	126900	3230	£6600

Vintage Model Prices

Rolex Website

https://www.rolex.com/watches.html

Page created Sun May 22 00:24:48 2022 by John Pumford-Green

Page last updated: 30/12/25 09:55 GMT

watch, rolex

Watches

anonymous@undisclosed.example.com (Anonymous) — Tue, 30 Dec 2025 09:55:07 +0000

←Miscellany

Watches

Mechanical watches, mainly. I can't afford to get involved in the Watch Hobby by collecting them, but I do enjoy learning about them.

I wear a Damasko DA36 as my main watch but also have a Seiko SKX007 and a couple of recent G-Shocks as well as a Casio F91W, a Suunto Vector, a couple of older G-shocks and a CWC G10 Military…. and a couple more….

UPDATE : Feb 2024

Now I'm wearing my varifocals full-time I'm able to wear a digital watch I'm enjoying wearing my G-Shock Casio GW-M5610 occasionally, and still swapping back to the Damasko DA36 too.

UPDATE : Feb 2025

I wore the G-Shock and CWC G10 for most of 2024 and into 2025. I've now gone back to my Damasko Damasko DA36 and plan to wear it for the rest of 2025, and possibly longer.

My Watch Notes

External Links

Page Updated : 30/12/25 09:55 GMT

watch

Watchcheck Python code

anonymous@undisclosed.example.com (Anonymous) — Fri, 23 Jan 2026 14:13:10 +0000

Watchcheck Python code

I wrote a small python2 application to keep track of a watch/clock's daily rate error. It's a console-only mimic of an Android app that I use on my phone to track my watch timekeeping.

I wrote it mainly as a thought-experiment rather than as a fully functional piece of code.

You put the application in a directory specific to the watch and execute it from that directory. the data from each measurement is stored in a json file in the same directory.

update 23/01/26 I've modified the code to run under Python 3 - using the tool 2to3 and a minor manual tweak.

watchcheck.py in Python 3

watchcheck.py

# a text-terminal version of the WatchCheck app
## to track error, daily error rate of timepieces.
# auto update?
#
import time
import datetime
import json
 
 
 
 
def write_file(text):
    filename = "logfile.txt"
    f = open(filename, 'a+')
    timenow = time.strftime("%d/%m/%Y %H:%M:%S", time.gmtime(time.time()))
    log = " ".join((timenow, text, "\r\n"))
    f.write(log)
    f.close()
 
 
 
def get_delta():
 
    print(time.strftime("Current Time = %H:%M"))
 
    h = time.strftime("%H")
    w = input("Watch time %s:" % (h))
    print(w)
 
    date = time.strftime("%Y/%m/%d")
    s = date + " " + h +":"+ w +":00"
 
    input("Press enter when seconds = 0 ")
 
    watchtime = time.mktime(datetime.datetime.strptime(s, "%Y/%m/%d %H:%M:%S").timetuple())
    record_time = time.strftime("%Y/%m/%d %H:%M:%S")
    timenow = time.time()
    delta = watchtime - timenow
 
    return record_time,delta
 
 
def watch_stat():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
    if len(error_list) > 1:
        first_record = error_list[0]
        latest_record = error_list[-1]
        previous_record = error_list[-2]
 
        first_time = first_record[0]
 
        first_delta = first_record[1]
 
        latest_time = latest_record[0] 
        latest_delta = latest_record[1]
 
        previous_time = previous_record[0]
        previous_delta = previous_record[1]
 
        FMT = '%Y/%m/%d %H:%M:%S'
 
        t_latest = datetime.datetime.strptime(latest_time, FMT)
        t_previous = datetime.datetime.strptime(previous_time, FMT)
        t_first = datetime.datetime.strptime(first_time, FMT)
 
        tdelta = t_latest - t_previous
        full_delta = t_latest - t_first
 
        elapsed_time = tdelta.total_seconds()
 
        full_time = full_delta.total_seconds()
 
        print("First record time ", first_time)
        print("First record delta ", first_delta)
        print("")
 
        print("Previous record time ", previous_time)
        print("Previous record delta ", previous_delta)
        print("")
 
        print("Latest record time " , latest_time)
        print("Latest record delta ", latest_delta)
        print("")
 
        print("Overall elapsed time ", full_delta)
        print("Latest elapsed time ", tdelta)
        print("")
 
        # Current Error rate
        time_error = latest_delta - previous_delta
        error_rate = time_error / elapsed_time
        daily_rate = error_rate * (60*60*24)
        ppm_daily = error_rate * 1000000
 
        # Overall Error rate
        total_error = latest_delta - first_delta
        average_error_rate = total_error / full_time
 
        average_rate = average_error_rate * (60*60*24)
        ppm_overall = average_error_rate * 1000000
 
 
        print("Latest delta change ", time_error)
 
        print("Latest elapsed time %d seconds " % (elapsed_time))
 
        print("")
        print("Daily PPM : %0.3f" % ppm_daily)
        print("Daily rate error: %0.1f s/d " % (daily_rate))
 
        print("")
        print("Total Time %d seconds" % (full_time))
        print("Total error ", total_error)
        print("Total PPM : %0.3f" % ppm_overall)
        print("Total rate error: %0.1f s/d" % (average_rate))
        print("")
        print("========================================================")
        print(" Delta : %+0.1f s | Rate : %+0.1f s/d | Average : %+0.1f s/d" % (latest_delta, daily_rate, average_rate))
        print("========================================================")
        print("")
        text = "\t%+0.1f\t\t%+0.1f\t\t%+0.1f" % (latest_delta, daily_rate, average_rate)
        write_file(text)
    else:
        print("No rate yet")
 
 
def new_record():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
    s,delta = get_delta()
 
    print("")
    print("%s \n\nDelta %0.1f seconds" % (s, delta))
    last_data=[s,delta]
    error_list.append(last_data)
    #print error_list
 
    with open('error_list.json', 'w') as outfile:
        json.dump(error_list, outfile)
 
    return
 
def delete_last():
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
    error_list.pop()
 
    with open('error_list.json', 'w') as outfile:
        json.dump(error_list, outfile)
 
    return
 
 
def menu():
    print("Wire2waves WatchCheck.....")
    print("=========================\n")
    print("N : New Record\nD : Delete Last\nS : Stats\nQ : Quit\n")
    choice = input("Command > : ").upper()
    if choice == "N":
        print("New")
        new_record()
        watch_stat()
        menu()
    elif choice == "S":
        print("Stat")
        watch_stat()
        menu()
    elif choice == "D":
        delete_last()
        watch_stat()
        menu()
    elif choice == "Q":
        return
    else:
        print("?")
        menu()
 
 
menu()

original watchcheck.py in python 2

watchcheck.py

#! /usr/bin/env python
 
## a text-terminal version of the WatchCheck app
## to track error, daily error rate of timepieces.
# auto update?
#
import time
import datetime
import json
 
 
 
 
def write_file(text):
    filename = "logfile.txt"
    f = open(filename, 'a+')
    timenow = time.strftime("%d/%m/%Y %H:%M:%S", time.gmtime(time.time()))
    log = " ".join((timenow, text, "\r\n"))
    f.write(log)
    f.close()
 
 
 
 
def get_delta():
 
    print time.strftime("Current Time = %H:%M")
 
    h = time.strftime("%H")
    w = raw_input("Watch time %s:" % (h))
    print w
 
    date = time.strftime("%Y/%m/%d")
    s = date + " " + h +":"+ w +":00"
 
    raw_input("Press enter when seconds = 0 ")
 
    watchtime = time.mktime(datetime.datetime.strptime(s, "%Y/%m/%d %H:%M:%S").timetuple())
    record_time = time.strftime("%Y/%m/%d %H:%M:%S")
    timenow = time.time()
    delta = watchtime - timenow
 
    return record_time,delta
 
 
def watch_stat():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
    if len(error_list) > 1:
        first_record = error_list[0]
        latest_record = error_list[-1]
        previous_record = error_list[-2]
 
        first_time = first_record[0]
 
        first_delta = first_record[1]
 
        latest_time = latest_record[0] 
        latest_delta = latest_record[1]
 
        previous_time = previous_record[0]
        previous_delta = previous_record[1]
 
        FMT = '%Y/%m/%d %H:%M:%S'
 
        t_latest = datetime.datetime.strptime(latest_time, FMT)
        t_previous = datetime.datetime.strptime(previous_time, FMT)
        t_first = datetime.datetime.strptime(first_time, FMT)
 
        tdelta = t_latest - t_previous
        full_delta = t_latest - t_first
 
        elapsed_time = tdelta.total_seconds()
 
        full_time = full_delta.total_seconds()
 
        print "First record time ", first_time
        print "First record delta ", first_delta
        print ""
 
        print "Previous record time ", previous_time
        print "Previous record delta ", previous_delta
        print ""
 
        print "Latest record time " , latest_time
        print "Latest record delta ", latest_delta
        print ""
 
        print "Overall elapsed time ", full_delta
        print "Latest elapsed time ", tdelta
        print ""
 
        # Current Error rate
        time_error = latest_delta - previous_delta
        error_rate = time_error / elapsed_time
        daily_rate = error_rate * (60*60*24)
        ppm_daily = error_rate * 1000000
 
        # Overall Error rate
        total_error = latest_delta - first_delta
        average_error_rate = total_error / full_time
 
        average_rate = average_error_rate * (60*60*24)
        ppm_overall = average_error_rate * 1000000
 
 
        print "Latest delta change ", time_error
 
        print "Latest elapsed time %d seconds " % (elapsed_time)
 
        print ""
        print "Daily PPM : %0.3f" % ppm_daily
        print "Daily rate error: %0.1f s/d " % (daily_rate)
 
        print ""
        print "Total Time %d seconds" % (full_time)
        print "Total error ", total_error
        print "Total PPM : %0.3f" % ppm_overall
        print "Total rate error: %0.1f s/d" % (average_rate)
        print ""
        print "========================================================"
        print " Delta : %+0.1f s | Rate : %+0.1f s/d | Average : %+0.1f s/d" % (latest_delta, daily_rate, average_rate)
        print "========================================================"
        print ""
        text = "\t%+0.1f\t\t%+0.1f\t\t%+0.1f" % (latest_delta, daily_rate, average_rate)
        write_file(text)
    else:
        print "No rate yet"
 
 
def new_record():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
    s,delta = get_delta()
 
    print ""
    print "%s \n\nDelta %0.1f seconds" % (s, delta)
    last_data=[s,delta]
    error_list.append(last_data)
    #print error_list
 
    with open('error_list.json', 'wb') as outfile:
        json.dump(error_list, outfile)
 
    return
 
def delete_last():
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
    error_list.pop()
 
    with open('error_list.json', 'wb') as outfile:
        json.dump(error_list, outfile)
 
    return
 
 
def menu():
    print "Wire2waves WatchCheck....."
    print "=========================\n"
    print "N : New Record\nD : Delete Last\nS : Stats\nQ : Quit\n"
    choice = raw_input("Command > : ").upper()
    if choice == "N":
        print "New"
        new_record()
        watch_stat()
        menu()
    elif choice == "S":
        print "Stat"
        watch_stat()
        menu()
    elif choice == "D":
        delete_last()
        watch_stat()
        menu()
    elif choice == "Q":
        return
    else:
        print "?"
        menu()
 
 
menu()

Running it for the first time, with no previous records stored, looks like this:

Wire2waves WatchCheck.....
=========================

N : New Record
D : Delete Last
S : Stats
Q : Quit

Command > : n
New
Current Time = 10:18
Watch time 10:19
19
Press enter when seconds = 0

2022/05/04 10:19:30

Delta -30.2 seconds

and the first time-delta is stored in the error_list.json file like this:

[["2022/05/04 10:19:30", -30.179980039596558]]

Running it again, after only 10 minutes looks like this:

Command > : n
New
Current Time = 10:30
Watch time 10:30
30
Press enter when seconds = 0

2022/05/04 10:30:30

Delta -30.2 seconds
First record time  2022/05/04 10:19:30
First record delta  -30.1799800396

Previous record time  2022/05/04 10:19:30
Previous record delta  -30.1799800396

Latest record time  2022/05/04 10:30:30
Latest record delta  -30.1998269558

Overall elapsed time  0:11:00
Latest elapsed time  0:11:00

Latest delta change  -0.0198469161987
Latest elapsed time 660 seconds

Daily PPM : -30.071
Daily rate error: -2.6 s/d

Total Time 660 seconds
Total error  -0.0198469161987
Total PPM : -30.071
Total rate error: -2.6 s/d

========================================================
 Delta : -30.2 s | Rate : -2.6 s/d | Average : -2.6 s/d
========================================================

The error_list.json file now looks like:

[["2022/05/04 10:19:30", -30.179980039596558], ["2022/05/04 10:30:30", -30.199826955795288]]

There's also a small utility called watchstat.py that reads the error_list.json file to calculate and display the data

original watchstat.py in python 2

watchstat.py

#! /usr/bin/env python
 
## a text-terminal version of the WatchCheck app
## to track error, daily error rate of timepieces.
 
#
import time
import datetime
import json
 
 
 
def watch_stat():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
 
 
 
    if len(error_list) > 1:
        first_record = error_list[0]
        latest_record = error_list[-1]
        previous_record = error_list[-2]
 
        first_time = first_record[0]
 
        first_delta = first_record[1]
 
        latest_time = latest_record[0] 
        latest_delta = latest_record[1]
 
        previous_time = previous_record[0]
        previous_delta = previous_record[1]
 
        FMT = '%Y/%m/%d %H:%M:%S'
 
        t_latest = datetime.datetime.strptime(latest_time, FMT)
        t_previous = datetime.datetime.strptime(previous_time, FMT)
        t_first = datetime.datetime.strptime(first_time, FMT)
 
        tdelta = t_latest - t_previous
        full_delta = t_latest - t_first
 
        elapsed_time = tdelta.total_seconds()
 
        full_time = full_delta.total_seconds()
 
        print "First record time ", first_time
        print "First record delta ", first_delta
        print ""
 
        print "Previous record time ", previous_time
        print "Previous record delta ", previous_delta
        print ""
 
        print "Latest record time " , latest_time
        print "Latest record delta ", latest_delta
        print ""
 
        print "Overall elapsed time ", full_delta
        print "Latest elapsed time ", tdelta
        print ""
 
        # Current Error rate
        time_error = latest_delta - previous_delta
        error_rate = time_error / elapsed_time
        daily_rate = error_rate * (60*60*24)
        ppm_daily = error_rate * 1000000
 
        # Overall Error rate
        total_error = latest_delta - first_delta
        average_error_rate = total_error / full_time
 
        average_rate = average_error_rate * (60*60*24)
        ppm_overall = average_error_rate * 1000000
 
 
        print "Latest delta change ", time_error
 
        print "Latest elapsed time %d seconds " % (elapsed_time)
 
        print ""
        print "Daily PPM : %0.3f" % ppm_daily
        print "Daily rate error: %0.1f s/d " % (daily_rate)
 
        print ""
        print "Total Time %d seconds" % (full_time)
        print "Total error ", total_error
        print "Total PPM : %0.3f" % ppm_overall
        print "Total rate error: %0.1f s/d" % (average_rate)
        print ""
        print "========================================================"
        print " Delta : %0.1f s | Rate : %0.1f s/d | Average : %0.1f s/d" % (latest_delta, daily_rate, average_rate)
        print "========================================================"
        print ""
    else:
        print "No rate yet"
 
 
watch_stat()

watchstat.py in python 3

watchstat.py

## a text-terminal version of the WatchCheck app
## to track error, daily error rate of timepieces.
 
#
import time
import datetime
import json
 
 
 
def watch_stat():
 
    try:
        saved_error = open('error_list.json')
        error_list = json.load(saved_error)
    except:
        error_list = []
 
 
 
 
    if len(error_list) > 1:
        first_record = error_list[0]
        latest_record = error_list[-1]
        previous_record = error_list[-2]
 
        first_time = first_record[0]
 
        first_delta = first_record[1]
 
        latest_time = latest_record[0] 
        latest_delta = latest_record[1]
 
        previous_time = previous_record[0]
        previous_delta = previous_record[1]
 
        FMT = '%Y/%m/%d %H:%M:%S'
 
        t_latest = datetime.datetime.strptime(latest_time, FMT)
        t_previous = datetime.datetime.strptime(previous_time, FMT)
        t_first = datetime.datetime.strptime(first_time, FMT)
 
        tdelta = t_latest - t_previous
        full_delta = t_latest - t_first
 
        elapsed_time = tdelta.total_seconds()
 
        full_time = full_delta.total_seconds()
 
        print("First record time ", first_time)
        print("First record delta ", first_delta)
        print("")
 
        print("Previous record time ", previous_time)
        print("Previous record delta ", previous_delta)
        print("")
 
        print("Latest record time " , latest_time)
        print("Latest record delta ", latest_delta)
        print("")
 
        print("Overall elapsed time ", full_delta)
        print("Latest elapsed time ", tdelta)
        print("")
 
        # Current Error rate
        time_error = latest_delta - previous_delta
        error_rate = time_error / elapsed_time
        daily_rate = error_rate * (60*60*24)
        ppm_daily = error_rate * 1000000
 
        # Overall Error rate
        total_error = latest_delta - first_delta
        average_error_rate = total_error / full_time
 
        average_rate = average_error_rate * (60*60*24)
        ppm_overall = average_error_rate * 1000000
 
 
        print("Latest delta change ", time_error)
 
        print("Latest elapsed time %d seconds " % (elapsed_time))
 
        print("")
        print("Daily PPM : %0.3f" % ppm_daily)
        print("Daily rate error: %0.1f s/d " % (daily_rate))
 
        print("")
        print("Total Time %d seconds" % (full_time))
        print("Total error ", total_error)
        print("Total PPM : %0.3f" % ppm_overall)
        print("Total rate error: %0.1f s/d" % (average_rate))
        print("")
        print("========================================================")
        print(" Delta : %0.1f s | Rate : %0.1f s/d | Average : %0.1f s/d" % (latest_delta, daily_rate, average_rate))
        print("========================================================")
        print("")
    else:
        print("No rate yet")
 
 
watch_stat()

Running watchstat.py on the newly updated error_list.json

gm4slv@laptop:~/watchcheck_damasko $ python watchstat.py
First record time  2022/05/04 10:19:30
First record delta  -30.1799800396

Previous record time  2022/05/04 10:19:30
Previous record delta  -30.1799800396

Latest record time  2022/05/04 10:30:30
Latest record delta  -30.1998269558

Overall elapsed time  0:11:00
Latest elapsed time  0:11:00

Latest delta change  -0.0198469161987
Latest elapsed time 660 seconds

Daily PPM : -30.071
Daily rate error: -2.6 s/d

Total Time 660 seconds
Total error  -0.0198469161987
Total PPM : -30.071
Total rate error: -2.6 s/d

========================================================
 Delta : -30.2 s | Rate : -2.6 s/d | Average : -2.6 s/d
========================================================

watchcheck.py also creates a log file on each run.

04/05/2022 09:30:30     -30.2           -2.6            -2.6

The fields are “date time”, current error, error in seconds per day since last record, average error in seconds per day since the start.

This mimics the behaviour of the Android Watchcheck app

John Pumford-Green Wed May 4 09:09:09 2022

Page Updated : 23/01/26 14:13 GMT

python, watch

Watchwinder

anonymous@undisclosed.example.com (Anonymous) — Tue, 30 Dec 2025 09:55:07 +0000

←Watches

Watchwinder

Home Brew Winder

I built a simple watch-winder to keep automatic watches fully wound when not being worn. Mainly as a small project to play with a pyBoard and a servo motor.

A short piece of microPython makes the servo turn, first one direction, then then other, then a pause, at a speed that makes sure a watch is fully wound overnight. The speed depends on the required number of turns to achieve full-wind, which depends on the watch movement, and whether the movement winds in one or other, or both, rotational directions.

The watch is placed in a plastic box attached to the servo motor and the motor is simple clamped in a panavise, with the axis of the servo at about 45°

Photos

pyBoard Quick Reference

[✓ John Pumford-Green, 2025-03-09]~~add some photos~~

Python Code

microPython code for Pyboard to control continuous rotation servo.

# main.py -- put your code here!
 
 
import pyb
 
servo1 = pyb.Servo(1)
 
# LED colours
# red flash = motor stopped
# green on = manual stop for 120 seconds
# yellow on/flash = motor running
# blue flash = 5 seconds before a change of state
 
ledr = pyb.LED(1) 
ledg = pyb.LED(2)
ledy = pyb.LED(3)
ledb = pyb.LED(4) 
 
# servo speeds to achieve approx 6 rpm in either direction.
ccw = 14
cw = -7
stop = 0
 
 
# 12 minute cycle :
# observed turns complete per stage:
# 2 min CW = ~11 turns
# 4 min stop
# 2 min CCW = ~ 12 turns
# 4 min stop
# 23 turns / 12 min = 115 turns / hour
# ETA 2836-2 requires 650 turns / day for full winding 
# this would take 5.6 hours on winder per day to guarantee full wind.
 
period = 120 # seconds
 
# turn LEDs off (unneccesary?)
ledr.off()
ledg.off() 
ledy.off()
ledb.off()
 
# interrupt function to allow changing/removing watch
def stop_servo():
 
	# red LED on at start of interruption
	ledr.on()
	ledy.off()
 
	# turn off any flashing LEDs during interruption
	tim4.callback(None)
 
	# flash blue LED to signal stop imminent
	flash_blue()
 
	# stop servo
	servo1.speed(0)
 
	# red LED off and green LED on to indicate "safe to proceed"
	ledr.off()
	ledg.on()
 
	# pause for 2 minute
	pyb.delay(120 * 1000)
 
	# flash blue LED to signal re-start imminent
	flash_blue()
 
	# green LED off to indicate end of interruption.
	ledg.off()
 
	pyb.hard_reset()
 
	# after resumption from interrupt the next stage will usually be a 
	# "stop" period, assuming the interrupt occurred during a "run" period
	# perhaps need to look at the best way of resuming? or even quit()
	# at the end of the stop_servo() interrupt and then manually reset via the 
	# RST button?
 
	# main programme resumes where it left off....
	return
 
def cycle_led():
 
	ledb.on()
	pyb.delay(500)
	ledy.on()
	pyb.delay(500)
	ledg.on()
	pyb.delay(500)
	ledr.on()
	pyb.delay(500)
	ledb.off()
	ledy.off()
	ledg.off()
	ledr.off()
 
	return
 
def flash_blue():
 
	t = 0
	while t < 10:
 
		ledb.toggle()
		pyb.delay(500)
		t += 1
	return
 
def rotate_cw(p):
 
	# solid yellow LED when going CW
	ledy.on()
	servo1.speed(cw, 1000)
	pyb.delay(p * 1000)
	flash_blue()
	ledy.off()
 
	return
 
 
def rotate_ccw(p):
 
	# flash yellow LED when going CCW
	tim4.callback(lambda t: ledy.toggle())
	servo1.speed(ccw, 1000)
	pyb.delay(p * 1000)
	flash_blue()
	tim4.callback(None)
	ledy.off()
 
 
	return
 
 
def pause(p):
 
	# flash red LED during motor pause period
	tim4.callback(lambda t: ledr.toggle())
	servo1.speed(stop, 1000)
	pyb.delay(p * 1000)
	flash_blue()
	tim4.callback(None)
	ledr.off()
 
	return
 
 
# USR on-board switch used to pause running to allow
# watch to be removed / changed
sw = pyb.Switch()
 
# callback to run the function that pauses the operation
sw.callback(stop_servo)
 
#timer to flash LEDs
tim4 = pyb.Timer(4, freq=2)
 
cycle_led()
 
# the main loop
while True:
 
		rotate_cw(period)
 
		pause(2 * period)
 
		rotate_ccw(period)
 
		pause(2 * period)

Page Info

Page created Sun May 22 00:52:45 2022 by John Pumford-Green

Page last updated: 30/12/25 09:55 GMT

watch, python

Day	Temp/°C	Pos	Daily rate	Variance
1	23	6H	M1
2	23		M2	V1
3	23	3H	M3
4	23		M4	V2
5	23	9H	M5
6	23		M6	V3
7	23	Dd	M7
8	23		M8	V4
9	23	Du	M9
10	23		M10	V5
11	8	Du	M11
12	23	Du	M12
13	38	Du	M13
14	23	6H	M14
15	23	6H	M15

Day	Pos	Daily rate	Variance
1	6H	M1
2		M2	V1
3	3H	M3
4		M4	V2
5	9H	M5
6		M6	V3
7	Ddn	M7
8		M8	V4
9	Dup	M9
14	6H	M14
15	6H	M15

Day	Temp/°C	Pos	Daily rate	Variance
1	23	6H	M1
2	23		M2	V1
3	23	3H	M3
4	23		M4	V2
5	23	9H	M5
6	23		M6	V3
7	23	Dd	M7
8	23		M8	V4
9	23	Du	M9
10	23		M10	V5
11	8	Du	M11
12	23	Du	M12
13	38	Du	M13
14	23	6H	M14
15	23	6H	M15

Day	Pos	Daily rate	Variance
1	6H	M1
2		M2	V1
3	3H	M3
4		M4	V2
5	9H	M5
6		M6	V3
7	Ddn	M7
8		M8	V4
9	Dup	M9
14	6H	M14
15	6H	M15

Day	Temp/°C	Pos	Daily rate	Variance
1	23	6H	M1
2	23		M2	V1
3	23	3H	M3
4	23		M4	V2
5	23	9H	M5
6	23		M6	V3
7	23	Dd	M7
8	23		M8	V4
9	23	Du	M9
10	23		M10	V5
11	8	Du	M11
12	23	Du	M12
13	38	Du	M13
14	23	6H	M14
15	23	6H	M15

Day	Pos	Daily rate	Variance
1	6H	M1
2		M2	V1
3	3H	M3
4		M4	V2
5	9H	M5
6		M6	V3
7	Ddn	M7
8		M8	V4
9	Dup	M9
14	6H	M14
15	6H	M15