Page Comparison

General Information

...

Analog outputs are then connected to the T7:
U - channel 1 - AIN0
V - channel 2 - AIN1
W - channel 3 - AIN2
sonic speed - channel 4 - AIN3

Sample Dataset taken over 10 min:

And zoomed in to ~half a second of data taking:

...

Note: this will take data for 10 minutes. It also takes data at a rate of 1 kHz, which is unecessary, as the anemometer takes data at 32 Hz.

Code Block

language	py

# -*- coding: utf-8 -*-
"""
Created on Fri Oct 15 13:55:10 2021
@author: brodi, elanaku
"""
# saves anemometer data
from datetime import datetime, timedelta
import pandas as pd
from labjack import ljm
from sqlalchemy import create_engine
import time

DEVICE = None
PIN_VX = "AIN0"
PIN_VY = "AIN1"
PIN_VZ = "AIN2"
PIN_VSONIC = "AIN3"

sample_time = .001


db_fi = 'sqlite:///anemometer.db'

start = datetime.now()
end = start + timedelta(seconds=60*10)

def readout(PIN_VX, PIN_VY, PIN_VZ, PIN_VSONIC):
    vx = ljm.eReadName(handle, PIN_VX)
    vy = ljm.eReadName(handle, PIN_VY)
    vz = ljm.eReadName(handle, PIN_VZ)
    vsonic = ljm.eReadName(handle, PIN_VSONIC)
    return (datetime.now(), vx, vy, vz, vsonic)

try:
    handle = ljm.openS("Any","Any","Any")
    engine = create_engine(db_fi, echo = False)
    sqlite_connection = engine.connect()
    options = {"index": False, "if_exists": "append"}



    while datetime.now() < end:
        it = 200
        i = 0
        res = []
        while i < it:
            res.append(readout(PIN_VX, PIN_VY, PIN_VZ, PIN_VSONIC))
            time.sleep(sample_time)
            i += 1

        anem = pd.DataFrame(res, columns = ["t", "vx", "vy", "vz", "vsonic"])

        anem.to_sql("anemometer", sqlite_connection, **options)



finally:
    ljm.close(handle)
    sqlite_connection.close()

...

Which gives the first plots in the previous section.

Troubleshooting: Corrupted Data File

If for some reason the anemometer database file becomes corrupted so you can't open it or analyze the data, you can dump the data from that file into a new, uncorrupted file with the command:

$ sqlite3 old_file.db .recover | sqlite3 new_file.db