First, thanks for making this awesome app! I'm halfway through HSK5 and have been studying with Pleco all the way from the beginning.
I'm currently developing a Python script that computes various statistics of my Pleco database. As part of one application, I'm trying to predict a forecast of how many (and which) cards will be due on the day since the last review session (i.e. "tomorrow").
Unfortunately, when I implement the card selection algorithm following the description here, my implementation predicts too few cards (around 20 when it should be around 60).
The card selection settings I'm using
Am I doing something wrong about the card selection algorithm? (It's also possible that I'm getting time stamps and time zones mixed up but I'm concerned there's something more fundamental that I'm getting wrong).
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Thanks for taking the time to read this! I feel that there's a lot of really interesting information in the pleco database that when visualized could provide interesting insights into my learning behavior.
I'm currently developing a Python script that computes various statistics of my Pleco database. As part of one application, I'm trying to predict a forecast of how many (and which) cards will be due on the day since the last review session (i.e. "tomorrow").
Unfortunately, when I implement the card selection algorithm following the description here, my implementation predicts too few cards (around 20 when it should be around 60).
The card selection settings I'm using
- Repetition-spaced
- Calendar days
- 100 points per day
- limit to 0 new cards per day
Python:
for row in pleco_flash_scores_1:
up_to = <end of day tomorrow as timestamp>
wait_for = score / score_per_day * <number of seconds per day>
if row.lastreviewedtime + wait_for < up_to:
print("card {{row.card}} will be due tomorrow")
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Thanks for taking the time to read this! I feel that there's a lot of really interesting information in the pleco database that when visualized could provide interesting insights into my learning behavior.