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Merge pull request #6030 from ByteHamster/rework-smart-shuffle 

Rework smart shuffle
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ByteHamster 2022-08-25 22:02:20 +02:00 committed by GitHub
parent 732462438a a265d17f54
commit 38dcfa9d35
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1 changed files with 38 additions and 64 deletions
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96
core/src/main/java/de/danoeh/antennapod/core/util/FeedItemPermutors.java
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@ -8,6 +8,7 @@ import java.util.Collections;
import java.util.Comparator;
import java.util.Date;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Locale;
import java.util.Map;
@ -116,38 +117,23 @@ public class FeedItemPermutors {
* prefer a more balanced ordering that avoids having to listen to clusters of consecutive
* episodes from the same feed. This is what "Smart Shuffle" tries to accomplish.
*
* The Smart Shuffle algorithm involves spreading episodes from each feed out over the whole
* queue. To do this, we calculate the number of episodes in each feed, then a common multiple
* (not the smallest); each episode is then spread out, and we sort the resulting list of
* episodes by "spread out factor" and feed name.
* Assume the queue looks like this: `ABCDDEEEEEEEEEE`.
* This method first starts with a queue of the final size, where each slot is empty (null).
* It takes the podcast with most episodes (`E`) and places the episodes spread out in the queue: `EE_E_EE_E_EE_EE`.
* The podcast with the second-most number of episodes (`D`) is then
* placed spread-out in the *available* slots: `EE_EDEE_EDEE_EE`.
* This continues, until we end up with: `EEBEDEECEDEEAEE`.
*
* For example, given a queue containing three episodes each from three different feeds
* (A, B, and C), a simple pubdate sort might result in a queue that looks like the following:
*
* B1, B2, B3, A1, A2, C1, C2, C3, A3
*
* (note that feed B episodes were all published before the first feed A episode, so a simple
* pubdate sort will often result in significant clustering of episodes from a single feed)
*
* Using Smart Shuffle, the resulting queue would look like the following:
*
* A1, B1, C1, A2, B2, C2, A3, B3, C3
*
* (note that episodes above <i>aren't strictly ordered in terms of pubdate</i>, but episodes
* of each feed <b>do</b> appear in pubdate order)
* Note that episodes aren't strictly ordered in terms of pubdate, but episodes of each feed are.
*
* @param queue A (modifiable) list of FeedItem elements to be reordered.
* @param ascending {@code true} to use ascending pubdate in the reordering;
* {@code false} for descending.
*/
private static void smartShuffle(List<FeedItem> queue, boolean ascending) {
// Divide FeedItems into lists by feed
Map<Long, List<FeedItem>> map = new HashMap<>();
while (!queue.isEmpty()) {
FeedItem item = queue.remove(0);
for (FeedItem item : queue) {
Long id = item.getFeedId();
if (!map.containsKey(id)) {
map.put(id, new ArrayList<>());
@ -156,55 +142,43 @@ public class FeedItemPermutors {
}
// Sort each individual list by PubDate (ascending/descending)
Comparator<FeedItem> itemComparator = ascending
? (f1, f2) -> f1.getPubDate().compareTo(f2.getPubDate())
: (f1, f2) -> f2.getPubDate().compareTo(f1.getPubDate());
// Calculate the spread
long spread = 0;
List<List<FeedItem>> feeds = new ArrayList<>();
for (Map.Entry<Long, List<FeedItem>> mapEntry : map.entrySet()) {
List<FeedItem> feedItems = mapEntry.getValue();
Collections.sort(feedItems, itemComparator);
if (spread == 0) {
spread = feedItems.size();
} else if (spread % feedItems.size() != 0){
spread *= feedItems.size();
}
Collections.sort(mapEntry.getValue(), itemComparator);
feeds.add(mapEntry.getValue());
}
// Create a list of the individual FeedItems lists, and sort it by feed title (ascending).
// Doing this ensures that the feed order we use is predictable/deterministic.
ArrayList<Integer> emptySlots = new ArrayList<>();
for (int i = 0; i < queue.size(); i++) {
queue.set(i, null);
emptySlots.add(i);
}
List<List<FeedItem>> feeds = new ArrayList<>(map.values());
Collections.sort(feeds,
(f1, f2) -> f1.get(0).getFeed().getTitle().compareTo(f2.get(0).getFeed().getTitle()));
// Spread each episode out
Map<Long, List<FeedItem>> spreadItems = new HashMap<>();
// Starting with the largest feed, place items spread out through the empty slots in the queue
Collections.sort(feeds, (f1, f2) -> Integer.compare(f2.size(), f1.size()));
for (List<FeedItem> feedItems : feeds) {
long thisSpread = spread / feedItems.size();
if (thisSpread == 0) {
thisSpread = 1;
double spread = (double) emptySlots.size() / (feedItems.size() + 1);
Iterator<Integer> emptySlotIterator = emptySlots.iterator();
int skipped = 0;
int placed = 0;
while (emptySlotIterator.hasNext()) {
int nextEmptySlot = emptySlotIterator.next();
skipped++;
if (skipped >= spread * (placed + 1)) {
if (queue.get(nextEmptySlot) != null) {
throw new RuntimeException("Slot to be placed in not empty");
}
queue.set(nextEmptySlot, feedItems.get(placed));
emptySlotIterator.remove();
placed++;
if (placed == feedItems.size()) {
break;
}
// Starting from 0 ensures we front-load, so the queue starts with one episode from
// each feed in the queue
long itemSpread = 0;
for (FeedItem feedItem : feedItems) {
if (!spreadItems.containsKey(itemSpread)) {
spreadItems.put(itemSpread, new ArrayList<>());
}
spreadItems.get(itemSpread).add(feedItem);
itemSpread += thisSpread;
}
}
// Go through the spread items and add them to the queue
List<Long> spreads = new ArrayList<>(spreadItems.keySet());
Collections.sort(spreads);
for (long itemSpread : spreads) {
queue.addAll(spreadItems.get(itemSpread));
}
}
}