Regardless of whether it’s a median filter, a Kalman filter or anything
else, integrating it into weewx doesn’t seem trivial to me. This is something
Tom and the other developers would need to consider and decide the best way to
proceed. Also, how many users would take advantage of it. There’s a time
series based on the loop intervals, etc., to think of as well.
I agree it probably would be best as an optional add-on, but again, I am
not one of the coders. Personally, I would only use such a feature to de-spike
the signal strength. I don’t have a need for an alarm, but others might.
Lastly, I wonder if there’s already a way to trigger an alarm. That’s a
feature that I haven’t researched, if it does exist. I threw my two cents in
only because of the simplicity and robustness of a small median filter.
Getting one working with weewx and/or an alarm is out of my league.
For what it’s worth, I too am growing tomatoes, but we’ve harvested the
lot this week, escaping the frost due to an unusually mild autumn. But
gardening is off topic! :-)
- Paul VE1DX
> On Oct 12, 2021, at 8:02 PM, Stephen Hocking <[email protected]>
> wrote:
>
>
> It does seem like an ideal use-case for a Kalman filter.
>
> https://medium.com/@jaems33/understanding-kalman-filters-with-python-2310e87b8f48
>
>> On Wed, 13 Oct 2021 at 09:54, Richard Horobin <[email protected]> wrote:
>> I accept that you want to remove spikes.
>>
>> Do you think this process could be used to detect "warning" levels? eg
>> tomato plants are not frost-hardy at all, so we need a warning when the
>> temperature goes to 5C.
>>
>> Many other processes require warnings at plus or minus 2.5 standard
>> deviations, as used in Shewhart Statistical Process Control charts. I
>> imagine this would be an optional add-on function, as it's non-core to weewx.
>>
>>> On Tuesday, 12 October 2021 at 00:14:07 UTC+11 WindnFog wrote:
>>> FWIW, here's how I'm doing it in C on an Arduino to de-spike/smooth
>>> temperature and humidity:
>>>
>>> #define buff_size 7 // Must be an odd number. Should be greater than 5.
>>> 7 works well.
>>>
>>>
>>> >snip<
>>>
>>> void bubble_sort(float sort_array[], int n)
>>> {
>>> int i, j;
>>> float temp;
>>>
>>> for (i = 0 ; i < n - 1; i++)
>>> {
>>> for (j = 0 ; j < n - i - 1; j++)
>>> {
>>> if (sort_array[j] > sort_array[j+1])
>>> {
>>> // Swap values
>>> temp = sort_array[j];
>>> sort_array[j] = sort_array[j+1];
>>> sort_array[j+1] = temp;
>>> }
>>> }
>>> }
>>> }
>>>
>>>
>>> >snip<
>>>
>>>
>>> // Sort them. Use quick and dirty bubble sort because it's a small number
>>> of data points
>>> bubble_sort(h_array_sort, buff_size);
>>> bubble_sort(t_array_sort, buff_size);
>>>
>>> // Use the median of the last "buff_size" readings for the display
>>> median_index = buff_size / 2;
>>>
>>> h = h_array_sort[median_index];
>>> t = t_array_sort[median_index];
>>>
>>>
>>> - Paul VE1DX
>>>
>>>
>>> On 2021-10-11 9:55 a.m., WindnFog wrote:
>>>> This would be out of my league to develop in Python. In my Fortran and
>>>> Pascal programming days of data acquisition, we routinely used 5,7, or 9
>>>> point median filters to smooth and de-spike oceanographic data. I would
>>>> think this might be a valuable addition to weewx.
>>>>
>>>> It's not a lot of code (bubble sort a small array of input data with the
>>>> median value being the output). Still, where the weewx developers would
>>>> put it and how users would configure which channels to filter, the width
>>>> of the filter, etc., might be a bridge too far. Just a thought.
>>>>
>>>> - Paul VE1DX
>>>>
>>>>> On Tuesday, October 5, 2021 at 10:56:53 AM UTC-3 [email protected]
>>>>> wrote:
>>>>>> Here is a description of my adventures cleaning up the database
>>>>>> http://www.adelieresources.com//2019/01/conversion-from-wview-to-weewx-weather-station-software/
>>>>>>
>>>>>> On Monday, October 4, 2021 at 6:30:16 AM UTC-7 [email protected] wrote:
>>>>>>> Thanks Tom! I love Weewx and get a kick out of playing with the data.
>>>>>>> My biggest variance here in Springfield Illinois was 4.4 degrees.
>>>>>>> On 4/21/21 at 12:15pm i went from 49.1 to 56.3 then fell back to 54.7.
>>>>>>> No rain that day, just clouds and sun I guess. Breezy.
>>>>>>>
>>>>>>> Walt
>>>>>>>
>>>>>>> On Sunday, October 3, 2021 at 8:39:09 PM UTC-5 [email protected] wrote:
>>>>>>>> Wow! Some serious SQL fu!
>>>>>>>>
>>>>>>>> Very nice.
>>>>>>>>
>>>>>>>> On Sun, Oct 3, 2021 at 12:20 PM [email protected] <[email protected]>
>>>>>>>> wrote:
>>>>>>>>> Here's an updated query that does better checking and it can delete
>>>>>>>>> the rows or update the temperatures. Test it out on a copy of your
>>>>>>>>> database first. This works for sqlite. Don't know about others.
>>>>>>>>>
>>>>>>>>> Walt
>>>>>>>>>
>>>>>>>>> On Sunday, October 3, 2021 at 6:48:23 AM UTC-5 [email protected] wrote:
>>>>>>>>>> Exactly. Is there a way to consider only cases such as +0, -10, +0
>>>>>>>>>> (i.e. spikes) and not those like +0, -6. -8 ?
>>>>>>>>>> Meanwhile I thank you for your precious help.
>>>>>>>>>> Andrea
>>>>>>>>>>
>>>>>>>>>> Il giorno giovedì 30 settembre 2021 alle 23:03:35 UTC+2
>>>>>>>>>> [email protected] ha scritto:
>>>>>>>>>>> Just a reminder, this delete query will delete all situations where
>>>>>>>>>>> the criteria is met. Some of these situations are legit, temps can
>>>>>>>>>>> change rapidly. You want to make sure it's going to delete only
>>>>>>>>>>> the records you want before running it. There are probably some
>>>>>>>>>>> enhancements that can be made to the query to find more obvious
>>>>>>>>>>> spikes. Something like +0, -10, +0 might be a spike, whereas +0,
>>>>>>>>>>> -6. -8 is not, the temp is just falling fast.
>>>>>>>>>>>
>>>>>>>>>>> On Thursday, September 30, 2021 at 1:11:05 PM UTC-5
>>>>>>>>>>> [email protected] wrote:
>>>>>>>>>>>> Well, make sure you back up your database before you try to delete
>>>>>>>>>>>> anything in case this goes wrong. I would
>>>>>>>>>>>>
>>>>>>>>>>>> 1. Stop weewx
>>>>>>>>>>>> 2. Make a copy of the database
>>>>>>>>>>>> 3. Execute the delete SQL
>>>>>>>>>>>> 4. Run the original query again to see if things are OK
>>>>>>>>>>>> 5. Rebuild weewx dailies
>>>>>>>>>>>> 6. Start weewx
>>>>>>>>>>>>
>>>>>>>>>>>> Hopefully I'm not forgetting anything.
>>>>>>>>>>>>
>>>>>>>>>>>> I'm attaching SQL to delete the spiked records. You will have to
>>>>>>>>>>>> change the database name in the .open statement to the db you want
>>>>>>>>>>>> to change. You may need to run sqlite3 with sudo in order to
>>>>>>>>>>>> delete records.
>>>>>>>>>>>>
>>>>>>>>>>>> I thought a better solution would be to update the spiked temp
>>>>>>>>>>>> with an average of the readings surrounding the spike, but I'm
>>>>>>>>>>>> having trouble coming up with the SQL to do that.
>>>>>>>>>>>>
>>>>>>>>>>>> Walt
>>>>>>>>>>>> On Thursday, September 30, 2021 at 9:41:17 AM UTC-5
>>>>>>>>>>>> [email protected] wrote:
>>>>>>>>>>>>> Thank you Walt, this script works fine! in fact it highlighted
>>>>>>>>>>>>> that spike in my graph:
>>>>>>>>>>>>>
>>>>>>>>>>>>> DT datetime temp temp_prior
>>>>>>>>>>>>> temp_next variance d_back d_forw
>>>>>>>>>>>>> ------------------- ---------- ----------------
>>>>>>>>>>>>> ---------------- ---------------- ----------
>>>>>>>>>>>>> ------------------ ----------------
>>>>>>>>>>>>> 2021-09-30 04:15:00 1632968100 19.2970370370371
>>>>>>>>>>>>> 19.3363567649282 14.5003779289494 2.38
>>>>>>>>>>>>> 0.0393197278911508 4.79665910808766
>>>>>>>>>>>>>
>>>>>>>>>>>>> (I added two columns d_back = |t1-t2| and t_forw = |t1-t3|)
>>>>>>>>>>>>> Now, I need to delete the wrong record: in this case, it is t3
>>>>>>>>>>>>> (d_forw = 4.8). How can I automatically find it and then remove?
>>>>>>>>>>>>> Unfortunately I don't know the sql language and I can't complete
>>>>>>>>>>>>> the script myself.
>>>>>>>>>>>>>
>>>>>>>>>>>>> Thank you very much,
>>>>>>>>>>>>> Andrea
>>>>>>>>>>>>> Il giorno giovedì 30 settembre 2021 alle 15:27:37 UTC+2
>>>>>>>>>>>>> [email protected] ha scritto:
>>>>>>>>>>>>>> Here's a query using the "join a table to itself" method if you
>>>>>>>>>>>>>> don't have the LAG function. It prints observations that are
>>>>>>>>>>>>>> outside the average of the surrounding observations by 2+
>>>>>>>>>>>>>> degrees. I get about 30 observations this year and I think it's
>>>>>>>>>>>>>> legit. Although I don't get spikes in my data, I do use a 15
>>>>>>>>>>>>>> minute interval and my station is closer to the ground than it
>>>>>>>>>>>>>> should be. A lot can happen in 15 minutes and my temp graph is
>>>>>>>>>>>>>> always kinda wiggly.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Caveat Emptor on the attached query. You could modify it to
>>>>>>>>>>>>>> delete or update the offending rows instead of printing them out.
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> Walt
>>>>>>>>>>>>>>
>>>>>>>>>>>>>>
>>>>>>>>>>>>>> On Thursday, September 30, 2021 at 7:52:41 AM UTC-5
>>>>>>>>>>>>>> [email protected] wrote:
>>>>>>>>>>>>>>> Yes, it's possible, but it's not a simple SELECT statement. For
>>>>>>>>>>>>>>> example, this query will return all rows where the temperature
>>>>>>>>>>>>>>> difference between adjacent rows is greater than 1 degree:
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> SELECT g.* FROM (SELECT dateTime,
>>>>>>>>>>>>>>> datetime(dateTime,'unixepoch','localtime'), LAG(outTemp) OVER
>>>>>>>>>>>>>>> (ORDER BY dateTime) AS prev_outTemp, outTemp FROM archive) AS g
>>>>>>>>>>>>>>> WHERE ABS(g.outTemp-g.prev_outTemp) > 1;
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> For my own database, this returns
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> 1192323300|2007-10-13 17:55:00|64.099998|63.0
>>>>>>>>>>>>>>> 1192382100|2007-10-14 10:15:00|51.900002|53.0
>>>>>>>>>>>>>>> 1192756800|2007-10-18 18:20:00|44.700001|46.700001
>>>>>>>>>>>>>>> 1192757100|2007-10-18 18:25:00|46.700001|49.5
>>>>>>>>>>>>>>> 1192757400|2007-10-18 18:30:00|49.5|47.400002
>>>>>>>>>>>>>>> ...
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> You would then need to arrange to delete those specific
>>>>>>>>>>>>>>> timestamps.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>> The select statement will only work with modern versions of
>>>>>>>>>>>>>>> sqlite, which have the LAG() function.
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> On Thu, Sep 30, 2021 at 3:35 AM [email protected]
>>>>>>>>>>>>>>>> <[email protected]> wrote:
>>>>>>>>>>>>>>>> Hi there,
>>>>>>>>>>>>>>>> I need to remove some temperature spikes from my weewx.sdb
>>>>>>>>>>>>>>>> database. I know this has been already asked many times, but
>>>>>>>>>>>>>>>> my case is different. I need to delete spikes in which the
>>>>>>>>>>>>>>>> values are climatically acceptable: so, it is not sufficient
>>>>>>>>>>>>>>>> to give (temperature is intended in °C)
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> echo "delete from archive where outTemp < -6;" | sudo sqlite3
>>>>>>>>>>>>>>>> /home/weewx/archive/weewx.sdb
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> for solving the problem. In my case, the spike was about 16°C
>>>>>>>>>>>>>>>> when temperature was about 20°C (see the graph below)
>>>>>>>>>>>>>>>>
>>>>>>>>>>>>>>>> What I need to do is something like: DELETE if Δt = 300 AND
>>>>>>>>>>>>>>>> |ΔT| > 5, where
>>>>>>>>>>>>>>>> Δt is time difference (in seconds, I chose 300 because my
>>>>>>>>>>>>>>>> archive interval is 5 minutes) and ΔT is the temperature
>>>>>>>>>>>>>>>> difference in that time bin.
>>>>>>>>>>>>>>>> In other words I am thinking about using a differential
>>>>>>>>>>>>>>>> approach. It seems to me that this can be the only solution,
>>>>>>>>>>>>>>>> is this possible with sqlite3?
>>>>>>>>>>>>>>>> Thank you,
>>>>>>>>>>>>>>>> Andrea
>>>>>>>>>>>>>>>
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