#which is annoying bc the result sucks but whatever I checked the rasters and it’s actually identical so

[exopelagic]

okay facing consequences of my actions

#I thought I’d gotten away with it this time #okay it’s 3am and I may have discovered something that completely ruins me #everyone is asleep so I can’t tell if this is me being sleep deprived or not! #so I need to sleep now but I haven’t cleaned my code up or written my answers #I do Not have time #if I don’t sleep now I’m gonna be having a bad time tomorrow morning and I am significantly less productive rn than I could be #with other people around I kinda need that y #so I should go to bed. but also. this code needs cleaning. but also. even if I fall asleep now I’m only getting like 5 hours MAX #I need a good few hours tomorrow morning to have a shot at doing this properly #so it would be more useful to sleep now and wake up as early as possible than keep going tonight bc I’m not going to finish tonight #okay. fuck. I hate this #if I could think straight I’d be able to fix this easy which is probably a good reason to sleep #it’s just an annoying logical problem that I gotta follow through bc currently I’m stuck between three possibilities and there might be more #I have these two rasters and I gotta calculate the area overlap #the first method counts the number of presence points in each (probably) and then counts the number in overlap raster w manually set values #the second counts total predicted points and points where they’re predicted to be alone and does a calculation with that for each species #that one with all points from both species + pseudoabsence. vs method 3 which does that with just individual species coordinates #method 1&2 are now homologous now I JUST caught the logical error but method 3 is what he gave us #but actually he might have fucked up in not including pseudoabsence #i don’t know if method 3 works for two different species either honestly #it gives me results I like much more (my overlap is 100% for one of the species and that shoooouldnt rlly happen even if it’s possible) but #I think it might actually just be wrong because it can’t account for #wait so the line is taking the prediction for all coordinates for each species for each species’ initial coordinates. and not pseudoabsence #and that set of predictions for each species coordinate set is then taken and yeah it’s no longer comparable you can’t count each alone #not with two different species bc you need an overlapping dataset to do that OKAY I have solved that logical problem my initial method works #which is annoying bc the result sucks but whatever I checked the rasters and it’s actually identical so #okay now I’ve figured that out. twenty minutes later. sleep I think it’ll help most #luke.txt