You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Problem
The Algae-WISE data consists of 59 266 seconds (~16.48 hours) of acquisition (including transit). Considering the acquisition rate of the instruments, it takes a maximum of five seconds to create a discrete data point. So we have a potential database of 59 266 / 5 = 11 853 observations. It takes a minimum of 5 minutes to process a single discrete observation. So it would take (5x60)x11 853 = 3 555 900 seconds (~ 987 hours) to process it all (overestimate including transit data).
Solution
You can automate the process and leave the qualitative eye of the operator to deal with problematic observations only.
To make efficient automation, we first have to clean the data for transit recording:
Speed_N <= 10
Lu < threshold
Then we need to create the time interval that will be used to discretize the data:
Start from a DateTime (x) take the next DateTime (y) with a minimum of three seconds difference and try to process.
If there is not enough data (HOCR) take the next DateTime (y) (normally one second further) and try to process. Repeat
If the next DateTime (y) has more than 10 seconds difference, start again with the next DateTime (y)
Describe alternatives
No alternative considered as of now
Additional context
Add any other context or screenshots about the feature request here.
The text was updated successfully, but these errors were encountered:
Problem
The Algae-WISE data consists of 59 266 seconds (~16.48 hours) of acquisition (including transit). Considering the acquisition rate of the instruments, it takes a maximum of five seconds to create a discrete data point. So we have a potential database of 59 266 / 5 = 11 853 observations. It takes a minimum of 5 minutes to process a single discrete observation. So it would take (5x60)x11 853 = 3 555 900 seconds (~ 987 hours) to process it all (overestimate including transit data).
Solution
You can automate the process and leave the qualitative eye of the operator to deal with problematic observations only.
To make efficient automation, we first have to clean the data for transit recording:
Then we need to create the time interval that will be used to discretize the data:
DateTime
(x) take the nextDateTime
(y) with a minimum of three seconds difference and try to process.DateTime
(y) (normally one second further) and try to process. RepeatDateTime
(y) has more than 10 seconds difference, start again with the nextDateTime
(y)Describe alternatives
No alternative considered as of now
Additional context
Add any other context or screenshots about the feature request here.
The text was updated successfully, but these errors were encountered: