output_dir="my_results/Hifiman HE400i 2016"Įach time I ran this script, I change the final directory, such that the resulting files are not mixed up with other headphones. Then I placed the "Hifiman HE400i 2016.csv" which is the csv file I got from 'WebPlotDigitizer' earlier.Įach time I ran this script, I change the directory and csv filename.Ĥ. I first created a directory for each headphone in the "C:\Users\user\AutoEq\my_data" folder. We need this file, since the algorithm needs to know what preference curve you're running it against.ģ. In other words, it's just frequency and '0' gain for all frequencies. File "Zero.csv" is simply the flat frequency compensation curve. I first created a 'my_input" in the "C:\Users\user\AutoEq\" folder.įrom the "compensation" directory, I copied the file called "zero.csv" and pasted into "C:\Users\user\AutoEq\my_input".
When installing, check the "Use the native Windows Secure Channel library" option, not the "use the OpenSSL library". Note: The instructions are already provided on the AutoEQ github page, but I figure I'd simplify it for those interested.ġ.
How to install AutoEQ for Windows 64-bit: I followed the steps to install the required dependencies, in Windows 10. I wanted to do this, because I could load the file next time I come back to WebPlotDigitizer, without repeating my steps, and for a backup.ġ3. Hit "Close", then File> "Save Project", hit "Download Project File (.tar)".
Now that the algorithm found the data points, we need to export this into. but I want the best possible accuracy.ġ1. I believe this sampling frequency becomes acceptable to use.
I used Excel's "Remove Duplicates" function to remove any. When later running AutoEQ, it runs mostly fine, but sometimes it reports 1 data point (which is like 0.07% error rate) that is duplicate. So I decided to stick with "2", which gave me ~1363 data points.
But later I ran into an issue where duplicate entries prevented 'AutoEQ' code from running (and only fixable until you remove those duplicate entries). To increase your sampling rate, I first tried "1", which resulted in ~3119 data points. If you run it with 10, the algorithm collects ~381 data points. Default was 10, which is the sampling frequency.