- #1
johnpjust
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Warning...this requires scripting and iteration, and is not theoretical -- it is a real problem I haven't been able to solve, but I'm sure someone here can... :-)
Data: each .csv file is a test recorded at a time interval of 7.5Hz and each file has 3 columns. The first column is time in seconds, the second column is a multiplier (see formula below), and third column is the measured value (to be "transformed"). There is also a corresponding value for each log in the "W.csv" file.
Formula (to produce a value for each file): R = [W_log_Val] / [#.log_val] -->
Additional Constraint: A plot of the R values against VF values should show no trend/pattern, where -->
Example:
applying a SQRT transformation to the measured value "col3_val" helps significantly, but the CV is still around 8-9% and does not satisfy the constraint.
See example of trend after applying sqrt in attached PDF
Data: each .csv file is a test recorded at a time interval of 7.5Hz and each file has 3 columns. The first column is time in seconds, the second column is a multiplier (see formula below), and third column is the measured value (to be "transformed"). There is also a corresponding value for each log in the "W.csv" file.
Formula (to produce a value for each file): R = [W_log_Val] / [#.log_val] -->
- W_log_Val is the corresponding value for that file located in the "W.csv" file.
- the #.log_val = ∑(col2_val)*(F(col3_val)) (a summation over the rows in the file)
- F(col3_val) is the function/transformation of the measured value to be found
Additional Constraint: A plot of the R values against VF values should show no trend/pattern, where -->
- VF = [#.log_val]/[Ts]
- "Ts" = the total time for each log (i.e., the value in the last row of the first column for each log)
Example:
applying a SQRT transformation to the measured value "col3_val" helps significantly, but the CV is still around 8-9% and does not satisfy the constraint.
See example of trend after applying sqrt in attached PDF
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