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Found 4 results

  1. Hi Nic Here a little input for a super improvement: Would it be possible to display the favorite points in percent? Especially if you are travelling in a unfamiliar area and don't want to miss the best caches, this would be a very useful function! Of course you should also be able to filter or sort by percentage. If the % display is output via the API, I guess it would be relatively easy to implement such a function. Thanks!
  2. Wakisashi

    Hidden Date Filtering

    I would find it resourceful if you could filter cache lists for a certain day and month. In project-gc you can create lists for caches hidden on a certain date (month and day; not year). Therefore after finding a Jan 01 cache. It would be helpful to be able to show all caches hidden on 01/01 so they could be deleted from the list. After disabling the filter only remaining dates for fill in would be left. Thanks! Chris
  3. Wakisashi

    Hidden Month Filtering

    It would be great if you could easily filter hidden month caches in one filter. Say I wanted to see all caches hidden in 2001 in January (not a specific day). I would create 1 filter to see all caches hidden on Jan 2001 (without specifying a specific day). I know you can get around this by creating 2 filters. One for any cache hidden on or after 01/01/2001, and another filter for everything on or before 31/01/2001. The second process may be challenging for others to figure out. Might be cool to name the new filter “Jasmer (Month & Year)”. This request would be helpful to those working on their Jasmer grids. Thanks, Chris
  4. First of all: thanks for the great app! Highly appreciated. When I search for caches, I sometimes want to see "nice" caches. So with a lot of favorite points. When I order or filter, I am not completely satisfied by the result. A cache that is viewed by thousands of people and got 30 favo's so far is weighted higher then a new cache that is seen by 25 (premium) people and all of them gave it a favorite point. A solution might be to order by the percentage favorites so the percentage of people that gave the cache a favo. The problem with that approach is that a cache that is only found once and got a favo, will have a score of 100% and will be on the top of the list. In my opinion, a weighted rating for both filtering and sorting would be ideal. A good formulae could be: weighted rating = ( cache_favo_percentage * nr_premium_finds + avg_favo_percentage * 30 ) / ( nr_premium_finds + 30 ) or simplified: weighted rating = ( nr_favos + 3 ) / ( nr_premium_finds + 30 ) (as avg_favo_percentage doesn't have to be very accurate and we know that the maximum of this number is 10%) The idea is that with no finds, the weighting rating is the average favo percentage of all the caches in the world. This is a good starting point as we don't have any other information for this cache. The more finds this cache gets, the more accurate we can determine the actual favo percentage, so the global average will be weighted less and less. IMDB.com uses something similar for scoring their movies. See the attachment. Note that this formula might seem complex, but it is trivial to compute. And I think it is relatively easy for users to understand. Maybe you can call it the cachly weighted favo score in the filter and sort screens. (or the jasper favo score if you like that better ;-) ) Here are some examples on the differences. The third column shows the favo percentage. The last column is the score based on the weighted percentage. finds favos percentage weighted percentage 0 0 NaN 10% 1 0 0% 10% 1 1 100% 13% 3 0 0% 9% 3 1 33% 12% 3 3 100% 18% 10 1 10% 10% 10 3 30% 15% 10 5 50% 20% 100 0 0% 2% 100 3 3% 5% 100 20 20% 18% 1000 0 0% 0% 1000 8 1% 1% 1000 20 2% 2% Ordered by favos (which is common now): finds favos percentage weighted percentage 100 20 20% 18% 1000 20 2% 2% 1000 8 1% 1% 10 5 50% 20% 3 3 100% 18% 10 3 30% 15% 100 3 3% 5% 1 1 100% 13% 3 1 33% 12% 10 1 10% 10% 0 0 NaN 10% 1 0 0% 10% 3 0 0% 9% 100 0 0% 2% 1000 0 0% 0% Ordered by favo percentage (This is already better as is gives less eight on the cache with 1000 finds and 8 favos.): finds favos percentage weighted percentage 0 0 NaN 10% 3 3 100% 18% 1 1 100% 13% 10 5 50% 20% 3 1 33% 12% 10 3 30% 15% 100 20 20% 18% 10 1 10% 10% 100 3 3% 5% 1000 20 2% 2% 1000 8 1% 1% 1 0 0% 10% 3 0 0% 9% 100 0 0% 2% 1000 0 0% 0% Ordered by cachly weighted favo score: finds favos percentage weighted percentage 10 5 50% 20% 3 3 100% 18% 100 20 20% 18% 10 3 30% 15% 1 1 100% 13% 3 1 33% 12% 0 0 NaN 10% 10 1 10% 10% 1 0 0% 10% 3 0 0% 9% 100 3 3% 5% 100 0 0% 2% 1000 20 2% 2% 1000 8 1% 1% 1000 0 0% 0%
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