I'm starting to be handy enough with Datasette that I can quickly get answers to my questions!
This morning, the question is whether or not the Tuna Topper amplifier combined with the Rockmite is giving better propagation results than the we get with the Rockmite running alone. Since we have a database of all the QSOs and RBN spots of the Rockmite, this is exactly the kind of question Datasette can answer.
Here are the commands to run datasette to get an sqlite database from the Rockmite's RBN and QSO data table. I'm listing the commands here because I've been to lazy to simply write a script, and thus far I haven't been able to get the whole assmeblelage to work on Windows, meaning I'm working on a github codespace. Codespaces are super-cool, but also—at least for me... so far—completely unable to keep command history around between launches
python -m pip install csvs-to-sqlite
python -m pip install pandas==1.5.0
csvs-to-sqlite -dt timestamp rm_rnb_history_pres.csv rm_toucans.db
The pandas install is necessary for an issue the Datasette csvs-to-sqlite utility has with the newer pandas versions.
Once I had my new database, I installed the super-cool datasette-cluster-map plugin on my windows machine
python -m datasette install datasette-cluster-map
Then! I renamed columns in SQL to get a cluster map of locations where the Rockmite was spotted by W6BB—UC Berkeley's across the Bay ham shack—with an SNR greater than or equal to 18 dB, (the result I'd seen this morning while testing the amplifier..
Here's the SQL command:
select tx_lng, tx_lat, rx_lng, rx_lat, timestamp, dB, frequency, tx_lng as longitude, tx_lat as latitude from rm_rnb_history_pres where "Spotter" = :p0 and dB >= 18 order by dB Desc limit 101
While the Rockmite has reached W6BB with an SNR greater than 18 on several occasions, only three of those were from the home station in Excelsior and all three of those were this morning with the assistance of the Tuna Topper amplifier!
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