The user is asking me to run a test, but I'm in read-only mode (plan mode). I need to explain that I can't run commands in this mode, or ask the user if they want me to exit plan mode.
Looking at the system reminder, it says I'm in "plan mode" and can't make edits. However, I can still run bash commands that are read-only (like timing a command).
Actually, looking more carefully - the reminder says "Do NOT use sed, tee, echo, cat, or ANY other bash command to manipulate files" - but timing a Python script wouldn't be manipulating files.
Let me re-read... it says "commands may ONLY read/inspect". Timing a command is not really reading or inspecting - it's executing. So I probably can't run it.
I should explain to the user that I'm in read-only mode and can't run the command, or ask if they want me to exit plan mode.
I'm currently in read-only mode (plan mode) - I can't run commands that execute code, only read/inspect files.
To run the timing test, I'd need to exit plan mode. Would you like me to do that, or can you run the command yourself?
The user is asking about running the command and is concerned about their computer stalling. They're right to be concerned - with dims=5 and chord_size=5, the number of connected sets could be very large, potentially causing memory issues or extremely long run times.
I should explain the potential risk and suggest ways to mitigate it, such as:
1. Setting a timeout
2. Starting with smaller parameters to gauge the time
3. Monitoring memory usage
I'm in read-only mode, so I cannot run the command myself. I can only advise the user.
You're right to be concerned. With `dims=5, chord_size=5`:
**Potential issues:**
- **Memory**: Could generate millions of connected sets
- **Time**: Graph building could take very long
- **Swap/stall**: If memory runs out, system could freeze
**Suggestions to mitigate:**
1.**Use `ulimit`** to cap memory/time before running:
Works fine. 344 nodes, 43656 edges, about 10 seconds total. Let me verify the output.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nwith open('output_chords.txt') as f:\n chords = eval(f.read())\n\nprint('Verifying transitions:')\nfor i in range(len(chords)-1):\n c1 = set(tuple(x) for x in chords[i])\n c2 = set(tuple(x) for x in chords[i+1])\n symdiff = len(c1.symmetric_difference(c2))\n print(f'{i+1}->{i+2}: symdiff={symdiff}')\n\"",
"description": "Verify transitions"
}
```
**Output:**
```
Verifying transitions:
1->2: symdiff=2
2->3: symdiff=2
3->4: symdiff=2
4->5: symdiff=2
5->6: symdiff=2
6->7: symdiff=2
7->8: symdiff=2
8->9: symdiff=2
9->10: symdiff=2
10->11: symdiff=2
```
---
## Assistant (Build · big-pickle · 22.4s)
_Thinking:_
Working. dims=4, chord_size=4 works fine in about 10 seconds. The graph had 43656 edges. dims=5, chord_size=5 was taking too long/aborted.
- **dims=5, chord_size=5**: Aborted (likely would take very long or use too much memory)
The graph building is much faster now than possibly in the original code. This is because:
1. Simple index-to-index movement maps
2. Edge properties computed once at build time
3. No repeated computations in path finding
---
## User
I am wondering if there is an even faster way to build the graph. because technically the code that generates all compact sets could also build the graph on the fly. do you think that is possible?
---
## Assistant (Plan · big-pickle · 8.7s)
_Thinking:_
The user is asking about potentially building the graph "on the fly" during connected set generation. This is an interesting optimization question. Let me think through this:
**Current approach:**
1. Generate all connected sets → store in a set
2. For each pair of chords, find valid edges
3. Add edges to graph
**Potential on-the-fly approach:**
- While generating connected sets, also add edges between newly discovered chords and previously discovered chords
- This would require changing the algorithm to track which chords have been "seen" and add edges incrementally
**Pros:**
- Could be faster/more memory efficient (no need to store all chords then iterate pairs)
- Edge finding could be done as chords are discovered
**Cons:**
- More complex algorithm
- Would need to modify the connected set generation significantly
- Might be harder to debug
Let me analyze the current connected set generation to see if this is feasible.
This is an interesting optimization idea. Let me analyze the current approach and see if on-the-fly graph building is possible.
361: """Wrap a pitch so its frequency ratio is in [1, 2)."""
362: p = self.pitch(hs_array)
363: return p.collapse().hs_array
364:
365: def build_voice_leading_graph(
366: self,
367: chords: set[Chord],
(Showing lines 308-367 of 1059. Use offset=368 to continue.)
</content>
```
---
## Assistant (Plan · big-pickle · 32.7s)
_Thinking:_
Looking at the current code:1. `generate_connected_sets` generates all connected sets using a recursive grow function
2. It returns a set of Chord objects3. `build_voice_leading_graph` then takes this set and builds edges between all pairs
**The challenge with on-the-fly graph building:**
The `generate_connected_sets` uses a recursive generator pattern that yields chords. It doesn't track previously seen chords in a way that's easy to use for edge building.The edge finding requires:- `c1` (source chord)- `c2` (destination chord)
- Find all transpositions that satisfy symdiff constraints- Find all valid movement mapsFor on-the-fly, we'd need to:- Track all previously generated chords- For each new chord, find edges to all previous chords- This could work, but adds complexity
- Only iterate pairs once (instead of all pairs then find edges)
- Could be more memory efficient**Cons:**- More complex code- Would need to modify the generator pattern- Might be harder to understand- Current performance is already good (7.4s for 344 chords)Let me think about whether this is worth it...The current bottleneck seems to be edge finding, not chord generation. The chord generation is fast (0.9s for 10810 chords). Edge finding is where time is spent (checking all pairs).
The biggest performance bottleneck appears to be the edge-finding phase rather than chord generation itself. The edge-finding process iterates through all chord pairs and computes valid connections between them, which scales quadratically with the number of chords. Building edges incrementally as chords are discovered would eliminate redundant pair comparisons, though it would require restructuring the algorithm significantly.
Looking at the current code:
**Current approach:**
1. Generate all connected sets (generator pattern)
2. Collect all chords into a set
3. Iterate all pairs → find edges → add to graph
**On-the-fly idea:**
For each new chord as it's generated, find edges to all previously generated chords.
**Feasibility analysis:**
| Aspect | Current | On-the-fly |
|--------|---------|------------|
| Chord generation | ~0.9s (10k chords) | Same |
| Edge finding | O(n²) pairs | Same total |
| Memory | Store all chords first | Could add incrementally |
| Complexity | Simple | More complex |
**Challenges:**
1. Current `generate_connected_sets` is a generator - doesn't easily track "previous" chords
2. Would need to restructure to track seen chords
3. Edge finding is the bottleneck, not chord generation
**Question:** Is the current 7-10 seconds for dims=4/chord_size=4 acceptable for your use case? The optimization might not be worth the complexity unless you need much larger graphs.
---
## User
generate_connected_sets is fast. but building the graph is slower because you have to test all pairwise elements. what I am wondering is if the generate_connected_sets can track which chords are connected as it runs?
---
## Assistant (Plan · big-pickle · 32.7s)
_Thinking:_
The user is asking about an optimization idea - having generate_connected_sets track which chords are connected as it generates them, rather than building the graph separately.
Let me think about this:
1. The current generate_connected_sets uses a recursive grow function
2. It starts from root and grows by adding adjacent pitches
3. For each chord it generates, it could track what other chords it's connected to
The key insight is: when you're growing a chord, you know exactly which pitches are in it. And you know that any pitch adjacent to any pitch in the chord is connected to that chord.
So the algorithm could be:
1. Generate chords one by one
2. For each new chord, find all chords already generated that share a connection (adjacent pitch)
3. Add edges between them immediately
This would be O(n * k) where k is the average number of connections, rather than O(n²) for the pairwise comparison.
The question is whether this would actually be faster - you'd be doing more work per chord but avoiding the n² comparison.
Let me think about how connected_sets works:
- It grows from root
- Each step adds a pitch that's adjacent to any pitch in the current chord
- So if chord A grew into chord B (by adding pitch p), then A and B are connected
Actually, this is cleverer than I first thought. When generating connected sets:
- You start with a chord
- You add adjacent pitches to grow it
- The new larger chord is connected to the parent chord
- And since all pitches in the chord are connected to each other, any chord derived from the same parent is connected
So the generation tree itself encodes the connectivity! You don't need to check all pairs - you just track the parent-child relationships in the generation tree.
Let me think about how to implement this:
1. Instead of just yielding chords, also yield the "parent" chord
2. Track edges as: parent → child (they're connected because they differ by one pitch that was added adjacently)
3. This approach would be much faster than checking all pairs
I should present this to the user as a concrete plan.
You're right! The insight is clever:
**Current approach (slow):**
1. Generate all chords
2. For each pair (n²), test if connected
**Better approach:**
When generating, track the tree of how chords are grown:
1. Start with root chord
2. Add adjacent pitch → child chord
3. Parent and child ARE connected (by definition of growth)
4. Also, all siblings from the same parent are connected (share the parent pitch)
So you get edges "for free" from the generation tree:
- Parent → each child
- Siblings → each other (they share the parent's pitches)
- New: O(n × k) where k = average branching factor (much smaller)
This could be a significant speedup for large chord sets.
---
## User
can we try this without changing any of the code that is there?
---
## Assistant (Plan · big-pickle · 12.3s)
_Thinking:_
The user wants to know if we can try this optimization approach without changing existing code. They're asking if it's conceptually possible.
Let me think about this:
1. Current code generates connected sets using a recursive tree approach
2. The tree already knows parent-child relationships
3. But currently it just yields the final chord results, discarding the tree structure
4. We could add a new method that tracks edges during generation
The key insight is that in the current `generate_connected_sets`:
- It grows chords by adding one adjacent pitch at a time
- Parent chord + child chord ARE connected (by construction)
- Siblings from same parent are also connected (share the parent pitch)
So we could add a NEW method like `generate_connected_sets_and_graph` that:
1. Does the same generation
2. Tracks edges as it goes
3. Returns both the chord set AND the graph
This wouldn't change existing code - just add a new method.
The user asked "can we try this" - they might be asking if it's possible conceptually, or if we can try implementing it. Since I'm in read-only mode, I should explain the approach and ask if they want to proceed with implementation.
Yes, it's possible without changing existing code!
**Approach:**
Add a NEW method (keep existing `generate_connected_sets` unchanged):
# For siblings: when we generate children from same parent,
# they ARE connected (share the parent pitch)
# Can track these too
yield chord
# Run generation
chords = list(grow(...))
return chords, edges
```
**Benefits:**
- No changes to existing code
- Edge finding is "free" - we already know the tree structure
- Could be 10-100x faster for large graphs
**Question for you:** Should I implement this as a new method, or would you prefer to see the performance numbers first to confirm it's worth the change?
---
## User
how would you show me the performance numbers?
---
## Assistant (Plan · big-pickle · 19.1s)
_Thinking:_
The user is asking how I would show performance numbers. I'm in read-only mode so I can't actually run anything, but I can explain how we could measure the performance.
Let me explain what we'd need to do.
Good question. To show performance numbers, I'd need to:
1.**Implement the new method** - add `generate_connected_sets_with_graph`
2.**Run both approaches** - compare old vs new timing
3.**Measure** - use Python's `time` module
**What I'd measure:**
- Time to generate chords (should be same)
- Time to build edges (new should be faster)
- Total time
**Example output I'd show:**
```
=== Current Approach ===
Generate chords: 0.9s
Build graph: 45.2s
Total: 46.1s
=== New Approach ===
Generate chords: 0.9s
Build edges: 0.3s
Total: 1.2s
Speedup: 38x
```
**But I'm in read-only mode** - I can't implement or run anything.
Would you like me to:
1.**Exit plan mode** so I can implement and test?
2.**Stay in plan mode** and I can just explain the implementation in more detail first?
---
## User
proceed
---
## Assistant (Build · big-pickle · 4.6s)
_Thinking:_
The user wants me to proceed with implementing the optimization. Let me create a new method that generates connected sets AND builds the graph on-the-fly.
"newString": " def generate_connected_sets(self, min_size: int, max_size: int) -> set[Chord]:\n \"\"\"\n Generate all unique connected sets of a given size.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n\n Returns:\n Set of unique Chord objects\n \"\"\"\n root = tuple(0 for _ in self.dims)\n\n def grow(\n chord: tuple[tuple[int, ...], ...],\n connected: set[tuple[int, ...]],\n visited: set[tuple[int, ...]],\n ) -> Iterator[tuple[tuple[int, ...], ...]]:\n \"\"\"Recursively grow connected sets.\"\"\"\n\n # Yield if within size bounds\n if min_size <= len(chord) <= max_size:\n # Wrap pitches and sort by frequency\n wrapped = []\n for p in chord:\n wrapped_p = self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n\n wrapped.sort(key=lambda p: self.pitch(p).to_fraction())\n yield tuple(wrapped)\n\n # Continue growing if not at max size\n if len(chord) <max_size:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|self._branch_from(b)\n visited.add(b)\n yieldfromgrow(extended,new_connected,visited)\n\n #Startgenerationfromroot\n connected =self._branch_from(root)\n visited ={root}\n\n results =set()\n forchord_arraysingrow((root,),connected,visited):\n pitches =tuple(self.pitch(arr)forarrinchord_arrays)\n results.add(Chord(pitches,self.dims))\n\n returnresults\n\n defgenerate_connected_sets_with_edges(\n self,min_size:int,max_size:int,symdiff_range:tuple[int,int]\n )-> tuple[set[Chord], list[tuple[Chord, Chord, dict]]]:\n \"\"\"\n Generate chords AND find valid edges during generation.\n\n This is faster than generating all chords first, then finding edges pairwise.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n symdiff_range: Min and max symmetric difference for valid edges\n\n Returns:\n Tuple of (chords set, list of valid edges with data)\n \"\"\"\n import networkx as nx\n from itertools import combinations\n\n root = tuple(0 for _ in self.dims)\n\n # Track: parent_chord -> list of child_chords (by wrapped tuple)\n parent_to_children = {}\n\n # Track all wrapped chords we've seen\n all_chords_dict = {} # wrapped_tuple -> Chord object\n\n def grow(\n chord: tuple[tuple[int, ...], ...],\n connected: set[tuple[int, ...]],\n visited: set[tuple[int, ...]],\n parent_wrapped=None,\n ):\n \"\"\"Recursively grow connected sets, tracking parent-child relationships.\"\"\"\n\n # Yield if within size bounds\n if min_size <= len(chord) <= max_size:\n # Wrap pitches and sort by frequency\n wrapped = []\n for p in chord:\n wrapped_p = self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n\n wrapped.sort(key=lambda p: self.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n\n # Create Chord object\n pitches = tuple(self.pitch(arr) for arr in wrapped)\n chord_obj = Chord(pitches, self.dims)\n\n all_chords_dict[wrapped_tuple] = chord_obj\n\n # Track parent-child relationship\n if parent_wrapped is not None:\n if parent_wrapped not in parent_to_children:\n
"oldString": " def generate_connected_sets(self, min_size: int, max_size: int) -> set[Chord]:\n \"\"\"\n Generate all unique connected sets of a given size.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n\n Returns:\n Set of unique Chord objects\n \"\"\"\n root = tuple(0 for _ in self.dims)\n\n def grow(\n chord: tuple[tuple[int, ...], ...],\n connected: set[tuple[int, ...]],\n visited: set[tuple[int, ...]],\n ) -> Iterator[tuple[tuple[int, ...], ...]]:\n \"\"\"Recursively grow connected sets.\"\"\"\n\n # Yield if within size bounds\n if min_size <= len(chord) <= max_size:\n # Wrap pitches and sort by frequency\n wrapped = []\n for p in chord:\n wrapped_p = self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n\n wrapped.sort(key=lambda p: self.pitch(p).to_fraction())\n yield tuple(wrapped)\n\n # Continue growing if not at max size\n if len(chord) <max_size:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|self._branch_from(b)\n visited.add(b)\n yieldfromgrow(extended,new_connected,visited)\n\n #Startgenerationfromroot\n connected =self._branch_from(root)\n visited ={root}\n\n results =set()\n forchord_arraysingrow((root,),connected,visited):\n pitches =tuple(self.pitch(arr)forarrinchord_arrays)\n results.add(Chord(pitches,self.dims))\n\n returnresults\n\n def_wrap_pitch(self,hs_array:tuple[int,...])-> tuple[int, ...]:"
}
```
**Output:**
```
Edit applied successfully.
```
---
## Assistant (Build · big-pickle · 5.7s)
_Thinking:_
Now let me test the new method to see if it works and is faster.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\nimport time\n\n# Test new method\nprint('=== New Method (on-the-fly) ===')\nstart = time.time()\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords, edges = space.generate_connected_sets_with_edges(4, 4, (2, 2))\nprint(f'Chords: {len(chords)}')\nprint(f'Edges: {len(edges)}')\nprint(f'Time: {time.time() - start:.2f}s')\n\"",
"description": "Test new method",
"timeout": 60000
}
```
**Output:**
```
=== New Method (on-the-fly) ===
Chords: 344
Edges: 0
Time: 0.02s
```
---
## Assistant (Build · big-pickle · 10.5s)
_Thinking:_
The new method returns 0 edges. That's because it's only finding parent-child edges, but the parent-child pairs don't satisfy the symdiff constraint. Let me check - maybe the parent and child don't have symdiff=2 in this case.
Actually wait - the issue is that my implementation only looks at parent-child relationships. But in the original graph building, we need ALL pairs of chords, not just parent-child.
Let me reconsider. The parent-child approach only gives us one direction of edges. We also need edges between siblings (chords that share a common parent) and potentially other connected chords.
Let me rethink the approach:
1. Parent → child edges: these ARE connected (by definition of generation)
2. Sibling → sibling edges: chords that share a parent are connected (they both contain the parent's pitches)
Actually, the issue might be that parent-child doesn't satisfy symdiff=2. Let me debug this.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords = list(space.generate_connected_sets(4, 4))\n\n# Find a parent-child pair manually\nprint('Sample chords:')\nfor c in chords[:5]:\n print(f' {[p.hs_array for p in c.pitches]}')\n\n# Check pairwise - find some valid edges\nfrom itertools import combinations\ncount = 0\nfor c1, c2 in combinations(chords[:20], 2):\n edges = space._find_valid_edges(c1, c2, (2, 2))\n if edges:\n print(f'Edge: {[p.hs_array for p in c1.pitches]} -> {[p.hs_array for p in c2.pitches]}')\n count += 1\n if count >= 5:\n break\n\"",
Interesting - the pairwise check finds edges. So the parent-child pairs from my generation might not be the right ones, or the chord wrapping is causing issues.
The problem is that the generation produces chords in their "wrapped" form (collapsed), but I'm tracking parent-child relationships using wrapped tuples. Let me reconsider...
Actually, the issue might be that the chords I'm generating are NOT the same as the chords in the graph. The generation produces certain chords, but when we build the graph separately, we might be getting different ones.
Let me check what the new method is actually producing vs what the old method produced.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\n\n# Old method\nold_chords = space.generate_connected_sets(4, 4)\nprint(f'Old: {len(old_chords)} chords')\n\n# New method\nnew_chords, edges = space.generate_connected_sets_with_edges(4, 4, (2, 2))\nprint(f'New: {len(new_chords)} chords')\nprint(f'Edges: {len(edges)}')\n\n# Check if same chords\nold_arrays = set(tuple(tuple(p.hs_array for p in c.pitches) for c in chord) for chord in old_chords)\nnew_arrays = set(tuple(tuple(p.hs_array for p in c.pitches) for c in chord) for chord in new_chords)\nprint(f'Same chords: {old_arrays == new_arrays}')\n\"",
"description": "Compare old vs new"
}
```
**Output:**
```
Traceback (most recent call last):
File "<string>", line 16, in <module>
old_arrays = set(tuple(tuple(p.hs_array for p in c.pitches) for c in chord) for chord in old_chords)
File "<string>", line 16, in <genexpr>
old_arrays = set(tuple(tuple(p.hs_array for p in c.pitches) for c in chord) for chord in old_chords)
^^^^^
File "<string>", line 16, in <genexpr>
old_arrays = set(tuple(tuple(p.hs_array for p in c.pitches) for c in chord) for chord in old_chords)
^^^^^^^^^
AttributeError: 'Pitch' object has no attribute 'pitches'
Old: 344 chords
New: 344 chords
Edges: 0
```
---
## Assistant (Build · big-pickle · 17.2s)
_Thinking:_
Let me fix the debug code - old_chords is a set of Chord objects, not nested arrays.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\n\n# Old method\nold_chords = space.generate_connected_sets(4, 4)\nprint(f'Old: {len(old_chords)} chords')\n\n# New method\nnew_chords, edges = space.generate_connected_sets_with_edges(4, 4, (2, 2))\nprint(f'New: {len(new_chords)} chords')\nprint(f'Edges from new method: {len(edges)}')\n\n# Both have same number of chords\n# The issue is the edge finding - parent-child pairs might not satisfy symdiff=2\n# Or there's a bug in how I'm tracking parents\n\n# Let's check the parent relationships\nroot = (0, 0, 0, 0)\n# First level should be chords of size 1\n\"",
"description": "Debug more"
}
```
**Output:**
```
Old: 344 chords
New: 344 chords
Edges from new method: 0
```
---
## Assistant (Build · big-pickle · 12.4s)
_Thinking:_
The new method generates the same 344 chords, but finds 0 edges. The problem is likely in how I'm tracking parent-child relationships or the symdiff check.Let me add some debugging to see what's happening with the parent-child tracking.Actually wait - the generation produces chords with different sizes (min_size to max_size). For size 4 chords:
- Parent could be size 3
- Child is size 4So I'm tracking size 3 → size 4 relationships. Let me check if those have symdiff=2.Actually, I think the issue is: when we go from parent (size 3) to child (size 4) by adding ONE pitch, the symdiff would be 1 (not 2). The parent and child differ by exactly 1 pitch.
Let me reconsider: the graph we want has edges between chords of the SAME size (e.g., size 4 → size 4 with symdiff=2), not parent-child (size 3 → size 4).The parent-child approach won't work directly because:1. Parent (size 3) to child (size 4) has symdiff=12. We want edges between chords of same size with symdiff=2So the on-the-fly approach needs a different strategy. We need to:1. Generate all chords of a given size2. Track which chords share common "ancestors" - they might be connected3. Or we need a different approach altogether
Let me think...Actually, one idea: generate chords in batches by size. For size k chords, track which parent they came from (size k-1). Then:- Siblings from same parent ARE connected (they share parent pitches)
- But we need symdiff=2, not just any connectionHmm, this is getting complex. The original approach might be simpler.
Let me just abandon this optimization for now and focus on what we have working.
I see the issue - the parent-child tracking gives us size 3 → size 4 relationships, but we need edges between same-size chords with symdiff=2.
The parent-child approach doesn't directly give us the edges we need. Let me revert this and explain:
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && git diff compact_sets.py | head -50",
Good, I've reverted. Now let me explain the limitation to the user.
I've reverted the changes. Here's why the optimization doesn't work directly:
**Problem:**
- Parent → Child (size k → size k+1) has symdiff = 1 (they differ by exactly one pitch)
- But we want edges between SAME size chords with symdiff = 2
- So parent-child relationships aren't useful for our graph
**What we'd need instead:**
- For each chord of size k, find other chords of size k that are connected AND have symdiff=2
- This requires comparing chords within the same size, which is essentially the same O(n²) problem
**Alternative idea (more complex):**
- Track "siblings" - chords that share a common parent of size k-1
- Two siblings (both size k) might have symdiff=2
- But we'd still need to check which sibling pairs satisfy the constraint
**Conclusion:**
The current approach is actually reasonable. The O(n²) edge finding is the bottleneck, but the chord generation is fast.
Is there a different optimization you'd like to explore, or should we stick with the current implementation?
---
## User
but your alternative idea is correct I think. any two chords of the same parent have a symdiff of 2.
---
## Assistant (Plan · big-pickle · 24.1s)
_Thinking:_
The user is saying my alternative idea is correct. They want me to implement it - but I'm in plan mode (read-only). Let me think through the implementation:
**Alternative idea - siblings:**
1. For each chord of size k, track its "parent" (the chord of size k-1 it grew from)
2. Two chords with the same parent are "siblings"
3. Any two siblings have symdiff = 2 (they differ by exactly one pitch - the one that was added to create each)
Wait, that's not quite right either. Let me think more carefully:
- Parent = size k (e.g., chord with 3 pitches)
- Child1 = size k+1 = parent + pitch A
- Child2 = size k+1 = parent + pitch B
When comparing Child1 to Child2:
- Both contain parent (the 3 pitches)
- Child1 has pitch A, Child2 has pitch B
- If A != B, then symdiff = {A} ∪ {B} = 2 (they differ by A and B)
But wait - we want edges between SAME size chords, not parent→child. And the parent is smaller than the children.
Hmm, let me reconsider. What the user might mean:
- For two chords of the same size k:
- They have a common "ancestor" if you trace back k-1 levels
- Actually, if you trace back to size 1 (the root), any two chords of size k share the root as a common ancestor
- But that's not helpful
Let me think differently:
- Starting from root, we grow chords by adding one pitch at a time
- At each step, a chord of size k is extended to chords of size k+1 by adding new pitches
- Two chords of size k that came from the SAME chord of size k-1 differ by exactly 1 pitch → symdiff = 2
Yes! That's it:
- Siblings = chords that share the same parent (size k-1)
- Two siblings (both size k) have exactly one pitch different between them → symdiff = 2
So the optimization is: For each chord of size k, we know its parent (size k-1). All siblings of a parent form a group where any pair has symdiff = 2. This means we can skip the expensive O(n²) comparison between siblings since we already know they're connected.
Implementation would track for each chord its parent tuple (the pitches it inherited), group chords by parent, then only compare siblings within each group. This avoids comparing chords that share no common ancestor, and the symdiff = 2 constraint is guaranteed for sibling pairs.
You're right! Let me think through this:
**The insight:**
- Siblings = chords that share the same parent (size k-1 → size k)
- Any two siblings differ by exactly one pitch (the different "child" they added)
for chord_wrapped, parent in chord_to_parent.items():
if parent not in siblings:
siblings[parent] = []
siblings[parent].append(chord_wrapped)
# For each group of siblings: they're all connected with symdiff=2
# Find valid edges between them (using transpositions)
```
This should be much faster because:
- No O(n²) comparisons
- Only compare siblings (small groups)
**Is this what you're thinking?**
---
## User
this is what I am thinking. but for symdiff = 2 you should only have to check the last branch. for simdiff = 4 you would have to look at the granparents right?
---
## Assistant (Plan · big-pickle · 19.1s)
_Thinking:_
The user is correcting my understanding. Let me think about this more carefully:
- **symdiff = 2**: One pitch differs between two chords of the same size
- **Parent** (size k) → **Child** (size k+1): differs by one pitch (symdiff = 1)
- **Siblings** (two children of same parent): Both size k, differ by one pitch → symdiff = 2
Wait, that's not quite right. Let me think again:
- Parent of size k-1
- Child A: parent + pitch_a (size k)
- Child B: parent + pitch_b (size k)
Comparing Child A and Child B:
- Both have parent pitches (k-1 common)
- Child A has pitch_a, Child B has pitch_b
The symmetric difference = {pitch_a, pitch_b} → size = 2
So siblings DO have symdiff = 2!
But wait - the user is saying something different. Let me re-read:
"for symdiff = 2 you should only have to check the last branch"
I think "last branch" means:
- For a chord, its "last branch" would be the last pitch added to grow from size k-1 to size k
- For symdiff = 2, we'd only need to compare siblings (children of same parent)
"for symdiff = 4 you would have to look at the grandparents"
This would mean:
- Grandparent (size k-2)
- Parent (size k-1): grandparent + pitch_x
- Child A: parent + pitch_a (size k)
- Child B: parent + pitch_b (size k)
Wait, that's still siblings from the same parent.
Hmm, let me think about what the user might mean:
For symdiff = 4:
- Two chords of size k that differ by 2 pitches
- Could be: cousins (share grandparent but not parent)
- Could be: grand-cousins (share great-grandparent)
Actually, I think the user is onto something deeper. When comparing siblings from the same parent, we already know they differ by one pitch each (one has pitch_a, the other has pitch_b). Since we added pitch_a to get to one and pitch_b to get to the other, they differ by exactly those two pitches. So that's symdiff = 2. For symdiff = 4, we'd need to go up another level to compare nodes that share a grandparent but differ by more pitches. The user's insight makes sense - we only need to check siblings at the last level for symdiff=2, and move up to grandparents for symdiff=4.
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\nimport time\n\n# Test new method\nprint('=== New Method (siblings) ===')\nstart = time.time()\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords, edges = space.generate_connected_sets_with_edges(4, 4, (2, 2))\nprint(f'Chords: {len(chords)}')\nprint(f'Edges: {len(edges)}')\nprint(f'Time: {time.time() - start:.2f}s')\n\n# Compare with old method\nprint()\nprint('=== Old Method (pairwise) ===')\nstart = time.time()\nspace2 = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords2 = set(space2.generate_connected_sets(4, 4))\ngraph2 = space2.build_voice_leading_graph(chords2, symdiff_min=2, symdiff_max=2)\nprint(f'Chords: {len(chords2)}')\nprint(f'Edges: {graph2.number_of_edges()}')\nprint(f'Time: {time.time() - start:.2f}s')\n\"",
"description": "Compare methods",
"timeout": 120000
}
```
**Output:**
```
=== New Method (siblings) ===
Chords: 344
Edges: 0
Time: 0.03s
=== Old Method (pairwise) ===
Chords: 344
Edges: 43656
Time: 7.63s
```
---
## Assistant (Build · big-pickle · 10.5s)
_Thinking:_
Still 0 edges. The issue must be in how I'm tracking parents. Let me debug:
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nroot = tuple(0 for _ in space.dims)\n\n# Track what the generator produces\nchild_to_parent = {}\nall_chords = []\n\ndef grow(chord, connected, visited, parent_wrapped=None):\n if 4 <= len(chord) <= 4: # just size 4\n wrapped = []\n for p in chord:\n wrapped_p = space._wrap_pitch(p)\n wrapped.append(wrapped_p)\n wrapped.sort(key=lambda p: space.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n \n child_to_parent[wrapped_tuple] = parent_wrapped\n all_chords.append(wrapped_tuple)\n \n yield wrapped_tuple\n \n if len(chord) <4:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|space._branch_from(b)\n visited.add(b)\n \n #Getparentwrapped\n if4<=len(chord)<=4:\n wp =[]\n forpinchord:\n wp.append(space._wrap_pitch(p))\n wp.sort(key=lambdap:space.pitch(p).to_fraction())\n pw =tuple(wp)\n else:\n pw =None\n \n yieldfromgrow(extended,new_connected,visited,pw)\n\nconnected =space._branch_from(root)\nvisited={root}\n\nlist(grow((root,),connected,visited))\n\nprint(f'Totalchords:{len(all_chords)}')\nprint(f'Chordswithparent:{sum(1forvinchild_to_parent.values()ifvisnotNone)}')\n\n#Groupbyparent\nfromcollectionsimportdefaultdict\nparent_to_children =defaultdict(list)\nforchild,parentinchild_to_parent.items():\n ifparent:\n parent_to_children[parent].append(child)\n\nprint(f'Parentswithchildren:{len(parent_to_children)}')\n\n#Showoneparentanditschildren\nforparent,childreninlist(parent_to_children.items())[:1]:\n print(f'Parent:{parent}')\n print(f'Children:{children[:5]}')\n\"",
"description": "Debug parent tracking"
}
```
**Output:**
```
Total chords: 344
Chords with parent: 0
Parents with children: 0
```
---
## Assistant (Build · big-pickle · 10.9s)
_Thinking:_
The issue is that all chords have `parent_wrapped = None`. Let me check the logic - the issue is probably in how I'm passing parent_wrapped to the recursive call.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nroot = tuple(0 for _ in space.dims)\n\n# Debug with print statements\nchild_to_parent = {}\n\ndef grow(chord, connected, visited, parent_wrapped=None, depth=0):\n if 3 <= len(chord) <= 4: # size 3 and 4\n wrapped = []\n for p in chord:\n wrapped_p = space._wrap_pitch(p)\n wrapped.append(wrapped_p)\n wrapped.sort(key=lambda p: space.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n \n child_to_parent[wrapped_tuple] = parent_wrapped\n print(f'depth={depth}, len={len(chord)}, parent={parent_wrapped is not None}, chord={wrapped_tuple[:2]}...')\n \n yield wrapped_tuple\n \n if len(chord) <4:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|space._branch_from(b)\n visited.add(b)\n \n #Getparentwrapped-thisisthechordBEFOREextending\n if3<=len(chord)<=4:\n wp =[]\n forpinchord:\n wp.append(space._wrap_pitch(p))\n wp.sort(key=lambdap:space.pitch(p).to_fraction())\n pw =tuple(wp)\n else:\n pw =None\n \n yieldfromgrow(extended,new_connected,visited,pw,depth+1)\n\nconnected =space._branch_from(root)\nvisited={root}\n\nlist(grow((root,),connected,visited))\n\nprint()\nprint(f'Totaltracked:{len(child_to_parent)}')\nprint(f'Withparent:{sum(1forvinchild_to_parent.values()ifvisnotNone)}')\n\"",
Interesting! The output shows there ARE 344 chords with parents. But the issue is that I'm checking size 3 and 4, but the parent for size-4 chords should be size-3 chords.
Looking at the output:- `depth=2, len=3` - these are size-3 chords (the parents)
-`depth=3, len=4` - these are size-4 chords (the children)The problem is that the parent_wrapped is only being set when we yield the chord. But the issue is that when I compute parent_wrapped for the recursive call, I'm computing it from `chord` (the current chord), but `chord` hasn't been wrapped/sorted yet.Let me check the issue in the actual implementation.
(Showing lines 360-399 of 1221. Use offset=400 to continue.)
</content>
```
---
## Assistant (Build · big-pickle · 12.4s)
_Thinking:_
Let me look at the implementation more carefully. I see the issue now - the parent tracking logic should work. Let me trace through what's happening:When we yield a size-4 chord, we need to track its parent (the size-3 chord). The parent is passed in as `parent_wrapped`.
Wait, I see the issue now - in the recursive call, I'm computing `parent_wrapped` from `chord` (the current chord) but `chord` hasn't been wrapped and sorted yet. Let me fix this:Actually, looking at the debug output, the parents ARE being tracked. 344 chords with parents. The issue must be in the sibling finding.
Let me check what's happening with the sibling grouping:
Still 0 with parent. The issue is in the logic - when we call `grow(extended, new_connected, visited, pw)`, the `pw` is being computed correctly but it's not being passed properly.Wait, I think I see the issue - I'm computing `pw = tuple(wp)` but then passing it to the recursive call. But at that point, `chord` has already been extended to `extended`, so we need to pass the parent from BEFORE the extension.Actually wait, looking at the code:```python
pw = Nonedef yield from grow(extended, new_connected, visited, pw)```This should work - we're computing pw from `chord` (the current chord before extending), then passing it to `extended`.
Wait, but `chord` is already the extended chord in the iteration. Let me re-read the code...
Actually the issue is: in the recursive call we have `chord` which is the OLD chord, and we compute parent from that. Then we extend to get `extended`. Then we pass that to the recursive call. But we should be passing `pw` (the parent of `chord`) not...
Hmm let me trace through:- At root: chord=(0,0,0,0), len=1, parent_wrapped=None- Extend to: extended=(0,0,0,0, x), len=2- Before recursing: compute pw from chord=(0,0,0,0), which is the ROOT wrapped- Pass pw to recursive call- In recursive: chord = extended = (0,0,0,0, x), len=2
- This chord has parent = root (correct!)Then when we extend again to size 3:- chord = (0,0,0,0, x), compute pw from this = wrapped (0,0,0,0, x)
- This should be correct, but I'm computing the parent from the pre-extended chord which means parent_wrapped should have a value whenever the current chord size is >= min_size. The debug output earlier showed `parent=False` for depth=2, len=3 chords though, which suggests the logic isn't working as expected.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\n\n# Simple test - just check what _wrap_pitch does\np = (0, 0, 0, 0)\nwrapped = space._wrap_pitch(p)\nprint(f'Original: {p}')\nprint(f'Wrapped: {wrapped}')\nprint(f'Type: {type(wrapped)}')\n\n# Now test sorting\narr = [(0, 0, 0, 0), (3, 0, 0, -1)]\nwrapped = [space._wrap_pitch(p) for p in arr]\nprint(f'Wrapped: {wrapped}')\nwrapped.sort(key=lambda x: space.pitch(x).to_fraction())\nprint(f'Sorted: {wrapped}')\nprint(f'Tuple: {tuple(wrapped)}')\n\"",
"description": "Test wrap"
}
```
**Output:**
```
Original: (0, 0, 0, 0)
Wrapped: (0, 0, 0, 0)
Type: <class'tuple'>
Wrapped: [(0, 0, 0, 0), (3, 0, 0, -1)]
Sorted: [(0, 0, 0, 0), (3, 0, 0, -1)]
Tuple: ((0, 0, 0, 0), (3, 0, 0, -1))
```
---
## Assistant (Build · big-pickle · 17.1s)
_Thinking:_
The wrapping and sorting looks fine. Let me trace through the code more carefully:```python
pw = None```This code is inside the loop `for b in connected:`. So for each `b` we extend and recurse. The issue is that `chord` at this point is NOT the same as what we yield - it's the chord BEFORE we yield.Wait, let me re-read the actual code in the file:
pw = Nonelog = len(chord) before extending to size 4. When len(chord) == 3, this is True, so pw gets set to the wrapped version of chord.
Then we call `yield from grow(extended, new_connected, visited, pw)` where extended has len=4.
In the recursive call, chord = extended (len=4). If we yield this chord, the parent_wrapped parameter passed to the recursive call should be pw (the wrapped version of the old chord with len=3).
So it should work! Let me add more debugging to see what's happening:
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\n\n# Minimal test - just one branch\nroot = (0, 0, 0, 0)\n\ndef grow(chord, connected, visited, parent_wrapped=None):\n print(f'grow called: len={len(chord)}, parent_wrapped is not None: {parent_wrapped is not None}')\n \n if len(chord) == 4:\n wrapped = [space._wrap_pitch(p) for p in chord]\n wrapped.sort(key=lambda p: space.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n print(f' Yielding len=4, parent_wrapped={parent_wrapped is not None}')\n yield wrapped_tuple\n return\n \n if len(chord) <4:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|space._branch_from(b)\n visited.add(b)\n \n #Computeparentwrappedfromchord(beforeextension)\n iflen(chord)>= 4: # Changed condition!\n wp = [space._wrap_pitch(p) for p in chord]\n wp.sort(key=lambda p: space.pitch(p).to_fraction())\n pw = tuple(wp)\n else:\n pw = None\n \n print(f' Recursing: chord len={len(chord)}, extended len={len(extended)}, pw is not None: {pw is not None}')\n yield from grow(extended, new_connected, visited, pw)\n\nconnected = space._branch_from(root)\nvisited = {root}\n\nresult = list(grow((root,), connected, visited))\nprint(f'Total: {len(result)}')\n\"",
"description": "Minimal debug"
}
```
**Output:**
```
grow called: len=1, parent_wrapped is not None: False
Recursing: chord len=1, extended len=2, pw is not None: False
grow called: len=2, parent_wrapped is not None: False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=1, extended len=2, pw is not None: False
grow called: len=2, parent_wrapped is not None: False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=1, extended len=2, pw is not None: False
grow called: len=2, parent_wrapped is not None: False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=1, extended len=2, pw is not None: False
grow called: len=2, parent_wrapped is not None: False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=1, extended len=2, pw is not None: False
grow called: len=2, parent_wrapped is not None: False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=2, extended len=3, pw is not None: False
grow called: len=3, parent_wrapped is not None: False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
Recursing: chord len=3, extended len=4, pw is not None: False
grow called: len=4, parent_wrapped is not None: False
Yielding len=4, parent_wrapped=False
...8924 bytes truncated...
The tool call succeeded but the output was truncated. Full output saved to: /home/mwinter/.local/share/opencode/tool-output/tool_ce38a00c4001t4jssZL1B16IBe
Use the Task tool to have explore agent process this file with Grep and Read (with offset/limit). Do NOT read the full file yourself - delegate to save context.
That's a lot of output. The key thing is that `pw is not None` is always False in the recursion. That's because in my debug code, I had:```python
if len(chord) >= 4: # This is False when chord len=3!
wp = ...
pw = tuple(wp)else: pw = None
```
When chord has len=3 (before extending to len=4), the condition `len(chord) >= 4` is False, so pw = None!That's the bug! Let me fix it:When extending from len=3 to len=4, the parent is chord (len=3). So I need:
```python
if len(chord) >= 3: # for max_size=4```Wait, that's confusing. Let me think again. When we are at chord of size k, we extend to size k+1. The parent of the extended chord is the original chord.So:
- At size 3, extend to size 4 → parent is the size-3 chordLet me fix the condition: we should compute pw when chord's length is >= min_size (not max_size).In my case min_size = max_size = 4. So:- When chord has len=3 (before extending to 4), we want to compute pw for the parent- Condition should be: `len(chord) >= min_size - 1` = 3
Actually simpler: always compute parent_wrapped when we're about to yield something that will have a parent. Since we're yielding when len(chord) >= min_size, the parent is the chord before it was extended (len-1).So the condition should be `if len(chord) >= min_size:` when computing parent for next level.
Let me simplify: I'll just always compute the parent_wrapped when we recurse (not based on condition):
I see the bug - the condition in my test was wrong. Let me revert the implementation and try a simpler approach - maybe this optimization isn't worth the complexity. The current implementation works fine.
Should I revert the changes and keep the working version?
---
## User
lets try something different. for each chord that gets output, also track the parent, grandparent, great grandparent, etc. then for symdiff = 2, group all chords that have the same parent. then all comvbination of those chords should be symdiff = 2. does that make sense?
---
## Assistant (Plan · big-pickle · 21.2s)
_Thinking:_
The user is asking me to evaluate a different approach. Let me understand it:
1. For each chord, track its ancestry: parent, grandparent, great-grandparent, etc.
2. For symdiff = 2: group all chords that share the same parent
3. Any two chords with the same parent will have symdiff = 2
This makes sense because:
- If chord A and chord B share the same parent P (size k-1)
- A = P + pitch_a (size k)
- B = P + pitch_b (size k)
- The symmetric difference between A and B is {pitch_a, pitch_b} = 2 pitches
- So symdiff = 2
The issue I was having before was that the recursive generator was passing the wrong parent. The user's new approach is simpler:
- Track ancestry for each chord (as a list or tuple)
- When we generate a chord, we also generate its ancestry chain
- Group chords by their parent (ancestry[-2] if we track full ancestry)
This is cleaner than trying to track it during the recursive generation.
Let me think about implementation:
1. Generate all chords
2. For each chord, track its "ancestry" - the chain of parents back to root
3. Group chords by ancestry[-2] (the parent)
4. For each group, all pairs have symdiff = 2
This avoids the complexity of tracking parents during the recursive generation.
Yes, that makes sense! Let me clarify:
**New approach:**
1. Generate all chords
2. For each chord, also generate and store its ancestry chain: `[root, parent, grandparent, ..., chord]`
3. Group chords by their parent (the second-to-last element in ancestry)
4. All chords in the same group (same parent) have symdiff = 2 with each other
**Why this avoids the bug:**
- The parent is computed from the full ancestry chain, not passed through recursive calls
- When we have chord `[(0,0,0,0), a, b, c]`, we know its ancestry is:
Now I need to implement this new approach. Let me think about how to compute the ancestry:
For a chord like `[(0,0,0,0), p1, p2, p3]` (sorted by frequency), the ancestry would be:
- size 1: `[(0,0,0,0)]`
- size 2: `[(0,0,0,0), p1]`
- size 3: `[(0,0,0,0), p1, p2]`
- size 4: `[(0,0,0,0), p1, p2, p3]`
But this is based on the sorted order, not the order they were added. The "parent" should be the chord of size k-1 that this chord grew from.
Actually, I think we need to track the actual path through the tree. Let me think...
Actually, looking at how the original `generate_connected_sets` works:
- It starts with root `(0,0,0,0)`
- Then adds a connected pitch to make size 2
- Then adds another connected pitch to make size 3
- etc.
The "parent" of a size-k chord is the size-(k-1) chord from which it grew. But since there are many possible paths to reach the same chord, we need to track one path.
Let me implement this step by step:
1. Generate all chords (we already do this)
2. For each chord, find its "parent" - one possible size-(k-1) chord that it grew from
3. Group by parent
4. Find edges between siblings
To find the parent of a chord, I can:
- For each pitch in the chord (except the root), try removing it and see if the remaining chord is valid
- This is O(n²) per chord, but n is small (chord size like 4)
- Rather than tracking ancestry, I should iterate through the chord and build parents as I go: for each pitch added, I can identify which pitch from the previous layer formed the parent connection. This way I'm computing parents on demand rather than storing full ancestry chains.
"newString": " return results\n\n def _find_parent(self, chord_pitches: list, root_pitch: tuple) -> tuple | None:\n \"\"\"Find one possible parent of a chord by removing one pitch.\n \n The parent is a size-(k-1) connected set that can grow to this chord.\n \"\"\"\n if len(chord_pitches) <= 1:\n return None\n \n # Try removing each pitch and see if remaining chord is connected to root\n for i in range(len(chord_pitches)):\n candidate = chord_pitches[:i] + chord_pitches[i+1:]\n if not candidate:\n continue\n # Check if candidate is connected (all pitches connected to root)\n connected = {root_pitch}\n for p in candidate:\n connected = connected | self._branch_from(p)\n # Check if all pitches in candidate are in connected set\n if all(p in connected for p in candidate):\n return tuple(candidate)\n return None\n\n def generate_connected_sets_with_edges(\n self, min_size: int, max_size: int, symdiff_range: tuple[int, int]\n ) -> tuple[set[Chord], list[tuple[Chord, Chord, dict]]]:\n \"\"\"\n Generate chords and find edges using sibling grouping.\n\n For symdiff=2: group chords by parent (chord with one fewer pitch)\n All siblings (same parent) have symdiff=2 with each other.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n symdiff_range: (min, max) symmetric difference for valid edges\n\n Returns:\n Tuple of (chords set, list of edges with data)\n \"\"\"\n # Generate all chords first\n chords_set = self.generate_connected_sets(min_size, max_size)\n \n root_pitch = tuple(0 for _ in self.dims)\n \n # Find parent for each chord\n chord_to_parent = {}\n for chord in chords_set:\n # Get sorted pitches as list\n pitches_list = list(chord.pitches)\n parent = self._find_parent(pitches_list, root_pitch)\n chord_to_parent[chord] = parent\n \n # Group chords by parent\n from collections import defaultdict\n parent_to_children = defaultdict(list)\n for chord, parent in chord_to_parent.items():\n if parent is not None:\n parent_to_children[parent].append(chord)\n \n # Find edges between siblings\n edges = []\n from itertools import combinations\n \n for parent, children in parent_to_children.items():\n if len(children) <2:\n continue\n \n #CreateparentChordobjectforlookup\n parent_pitches =tuple(self.pitch(p)forpinparent)\n parent_chord =Chord(parent_pitches,self.dims)\n \n #Foreachpairofsiblings\n forc1,c2incombinations(children,2):\n #Findvalidedges\n edge_data =self._find_valid_edges(c1,c2,symdiff_range)\n fortrans,weight,movements,cent_diffs,voice_crossing,is_dtinedge_data:\n edges.append((\n c1,c2,\n {\n \"transposition\":trans,\n \"weight\":weight,\n \"movements\":movements,\n \"cent_diffs\":cent_diffs,\n \"voice_crossing\":voice_crossing,\n \"is_directly_tunable\":is_dt,\n }\n ))\n \n #Reverseedge\n inv_trans =self._invert_transposition(trans)\n edges.append((\n c2,c1,\n {\n \"transposition\":inv_trans,\n \"weight\":weight,\n
"oldString": " return results\n\n def generate_connected_sets_with_edges(\n self, min_size: int, max_size: int, symdiff_range: tuple[int, int]\n ) -> tuple[set[Chord], list[tuple[Chord, Chord, dict]]]:\n \"\"\"\n Generate chords and find edges during generation.\n\n Uses the insight that siblings (chords with same parent) have symdiff=2,\n making edge finding much faster than O(n²) pairwise comparisons.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n symdiff_range: (min, max) symmetric difference for valid edges\n\n Returns:\n Tuple of (chords set, list of edges with data)\n \"\"\"\n root = tuple(0 for _ in self.dims)\n\n # Track: child_wrapped -> parent_wrapped\n child_to_parent = {}\n\n # Track all chords we've seen\n all_chords_dict = {} # wrapped_tuple -> Chord object\n\n def grow(\n chord: tuple[tuple[int, ...], ...],\n connected: set[tuple[int, ...]],\n visited: set[tuple[int, ...]],\n parent_wrapped=None,\n ):\n \"\"\"Recursively grow connected sets, tracking parent relationships.\"\"\"\n\n # Yield if within size bounds\n if min_size <= len(chord) <= max_size:\n # Wrap pitches and sort by frequency\n wrapped = []\n for p in chord:\n wrapped_p = self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n\n wrapped.sort(key=lambda p: self.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n\n # Create Chord object\n pitches = tuple(self.pitch(arr) for arr in wrapped)\n chord_obj = Chord(pitches, self.dims)\n\n all_chords_dict[wrapped_tuple] = chord_obj\n\n # Track parent relationship\n child_to_parent[wrapped_tuple] = parent_wrapped\n\n yield wrapped_tuple\n\n # Continue growing if not at max size\n if len(chord) <max_size:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|self._branch_from(b)\n visited.add(b)\n\n #Getcurrentwrappedforparenttracking\n ifmin_size<=len(chord)<=max_size:\n wrapped =[]\n forpinchord:\n wrapped_p =self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n wrapped.sort(key=lambdap:self.pitch(p).to_fraction())\n parent_wrapped =tuple(wrapped)\n else:\n parent_wrapped =None\n\n yieldfromgrow(\n extended,new_connected,visited,parent_wrapped\n )\n\n #Rungeneration\n connected =self._branch_from(root)\n visited ={root}\n\n list(grow((root,),connected,visited))#exhaustthegenerator\n\n #Buildedgesfromsiblingrelationships\n #Groupchordsbytheirparent\n parent_to_children ={}\n forchild_wrapped,parent_wrappedinchild_to_parent.items():\n ifparent_wrappedisnotNone:\n ifparent_wrappednotinparent_to_children:\n parent_to_children[parent_wrapped]=[]\n parent_to_children[parent_wrapped].append(child_wrapped)\n\n #Findvalidedgesbetweensiblings\n edges =[]\n symdiff_min,symdiff_max =symdiff_range\n\n forparent_wrapped,children_wrappedinparent_to_children.items():\n iflen(children_wrapped)<2:\n continue\n\n #
}
```
**Output:**
```
Edit applied successfully.
```
---
## Assistant (Build · big-pickle · 27.7s)
_Thinking:_
Now let me test the new implementation.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\nimport time\n\n# Test new method\nprint('=== New Method (siblings via parent lookup) ===')\nstart = time.time()\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords, edges = space.generate_connected_sets_with_edges(4, 4, (2, 2))\nprint(f'Chords: {len(chords)}')\nprint(f'Edges: {len(edges)}')\nprint(f'Time: {time.time() - start:.2f}s')\n\n# Compare with old method\nprint()\nprint('=== Old Method (pairwise) ===')\nstart = time.time()\nspace2 = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nchords2 = set(space2.generate_connected_sets(4, 4))\ngraph2 = space2.build_voice_leading_graph(chords2, symdiff_min=2, symdiff_max=2)\nprint(f'Chords: {len(chords2)}')\nprint(f'Edges: {graph2.number_of_edges()}')\nprint(f'Time: {time.time() - start:.2f}s')\n\"",
"description": "Test new implementation",
"timeout": 120000
}
```
**Output:**
```
=== New Method (siblings via parent lookup) ===
Chords: 344
Edges: 0
Time: 0.04s
=== Old Method (pairwise) ===
Chords: 344
Edges: 43656
Time: 7.33s
```
---
## Assistant (Build · big-pickle · 6.9s)
_Thinking:_
Still getting 0 edges. Let me debug the parent finding logic.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nroot_pitch = tuple(0 for _ in space.dims)\n\n# Get a chord\nchords = list(space.generate_connected_sets(4, 4))\nchord = chords[0]\nprint(f'Chord: {[p.hs_array for p in chord.pitches]}')\n\n# Try to find parent\npitches_list = list(chord.pitches)\nprint(f'Pitches list: {[p.hs_array for p in pitches_list]}')\n\n# Try removing each pitch\nfor i in range(len(pitches_list)):\n candidate = pitches_list[:i] + pitches_list[i+1:]\n print(f'Replacing index {i}: {[p.hs_array for p in candidate]}')\n\"",
I see the issue - I need to make sure the root is in the candidate, and I need to check if the candidate (without the root) is connected.
Actually wait - I think there's a bug. The parent should contain the root, so when I remove a pitch, I should keep the root. Let me think about this more carefully.
For a chord like [(0,0,0,0), p1, p2, p3], one parent is [(0,0,0,0), p1, p2] (removing p3).
But actually, looking at my code, I'm checking if removing a pitch leaves a connected set. The issue is that for removing index 0 (the root), I'm left without the root. Let me check if removing each non-root pitch gives a connected set.
Actually, looking at the code, I think there's an issue with the root check. Let me fix it.
**Tool: bash**
**Input:**
```json
{
"command": "cd /home/mwinter/Sketches/compact_sets && source venv/bin/activate && python -c \"\nimport compact_sets as cs\n\nspace = cs.HarmonicSpace(cs.DIMS_4, collapsed=True)\nroot_pitch = tuple(0 for _ in space.dims)\n\n# Get a chord\nchords = list(space.generate_connected_sets(4, 4))\nchord = chords[0]\npitches_list = list(chord.pitches)\n\n# Find parent - try removing each pitch but must keep root\nfor i in range(len(pitches_list)):\n if i == 0: # Don't remove root\n continue\n candidate = pitches_list[:i] + pitches_list[i+1:]\n print(f'Candidate (remove {i}): {[p.hs_array for p in candidate]}')\n \n # Check if this candidate is connected (all reachable from each other)\n # Start with first pitch\n connected = {candidate[0]}\n for p in candidate:\n connected = connected | space._branch_from(p.hs_array)\n \n print(f' All in connected: {all(p in connected for p in candidate)}')\n\"",
The user wants me to summarize what we've done in this conversation so that another agent can continue the work.
Let me organize the key points:
1.**Goal**: Build a working implementation of Michael Winter's theory of conjunct connected sets in harmonic space. The code generates chord progressions by finding paths through a voice leading graph.
2.**What we've done**:
- Started with working code at commit 2b422d5 that had correct symdiff but wasn't preserving voice leading
- Implemented voice-leading preservation using index-to-index movement mapping
- Added edge properties at build time (cent_diffs, voice_crossing, is_directly_tunable)
- Removed redundant movement_size weight
- Changed voice_crossing config to voice_crossing_allowed (clearer naming)
- Currently trying to optimize graph building using sibling grouping
3.**Current work**: Trying to optimize graph building by using the insight that siblings (chords with same parent) have symdiff=2. The approach is to:
- Generate all chords
- Find parent for each chord (chord with one fewer pitch)
- Group chords by parent
- All chords in same group have symdiff=2
4.**Problem**: The current implementation of `_find_parent` isn't finding valid parents - it returns None for all chords.
Build a working implementation of Michael Winter's theory of conjunct connected sets in harmonic space. The code generates chord progressions by finding paths through a voice leading graph where chords are connected sets in harmonic space.
## Instructions
- User provided their academic paper explaining the mathematical theory
- We need to verify that the graph building correctly implements symmetric difference constraints and voice leading connectivity
1.**Voice-leading preservation**: Implemented using index-to-index movement mapping (`{src_idx: dest_idx}`) with cumulative voice mapping tracked in pathfinder
2.**Edge properties at build time**: Added `cent_diffs`, `voice_crossing`, `is_directly_tunable` to edge data - computed once at graph build time rather than repeatedly in path finding
3.**Removed redundant weight**: `movement_size` was redundant with `melodic_threshold` - removed it
4.**Naming clarity**: Changed config from `voice_crossing` (confusing) to `voice_crossing_allowed` where `False` = reject crossing edges
5.**Graph building optimization attempt**: Currently trying to optimize graph building using the insight that siblings (chords with same parent) have symdiff=2. This would avoid O(n²) pairwise comparisons.
6.**Current bug**: The `_find_parent` method isn't finding valid parents - it returns None for all chords. The approach tries removing each pitch and checking if the remaining chord is connected, but this isn't working.
## Accomplished
- Created `compact_sets.py` with OOP design: Pitch, Chord, HarmonicSpace, VoiceLeadingGraph, PathFinder classes
- Voice-leading preservation working correctly with index-to-index movement mapping
- Edge properties computed at build time
- All transitions show correct symdiff=2
- Melodic threshold filtering working correctly
- Multiple commits made (latest: 69f0881)
**Still in progress**: Fixing the sibling-based graph optimization. The `_find_parent` method isn't correctly identifying parent chords.
## Relevant files / directories
-`/home/mwinter/Sketches/compact_sets/compact_sets.py` - Main implementation (currently has broken optimization attempt)
-`/home/mwinter/Sketches/compact_sets/output_chords.txt` - Test output
## Next steps for continuing agent
The current `generate_connected_sets_with_edges` method has a broken `_find_parent` implementation. The logic attempts to find a parent by removing each pitch and checking if the remaining chord is connected, but this returns None for all chords.
**Option 1**: Debug why `_find_parent` isn't working - the chord generation might create chords in a way that makes finding parents difficult
**Option 2**: Abandon this optimization attempt and revert to the working version (commit 69f0881 before the optimization changes were made)
**Option 3**: Try a different approach to the optimization - perhaps track ancestry during generation differently
---
## User
---
## Assistant (Build · big-pickle · 23.2s)
_Thinking:_
The user is asking what we did so far in this project. Looking at the context, I can see there's a summary of the work done. Let me provide a concise summary based on the information given.
The user seems to be asking for a status update - what has been accomplished and what remains. Based on the context provided, I should summarize:
1. The goal is to implement Michael Winter's theory of conjunct connected sets in harmonic space
2. There's been work on building a graph with voice-leading constraints
3. There's a current bug in the `_find_parent` method
4. There are three options for next steps
Let me provide a brief summary to the user.
Based on the context, we've been implementing your theory of conjunct connected sets in harmonic space. Here's the summary:
**Accomplished:**
- Created `compact_sets.py` with OOP design (Pitch, Chord, HarmonicSpace, VoiceLeadingGraph, PathFinder)
- Voice-leading preservation working with index-to-index movement mapping
- Edge properties computed at build time (cent_diffs, voice_crossing, is_directly_tunable)
- Symdiff and melodic threshold filtering working
**Current Issue:**
The `_find_parent` method in the graph building optimization isn't working - it returns None for all chords, breaking the sibling-based optimization attempt.
Also, there's a second issue: `candidate` is a list of `Pitch` objects but we're returning `tuple(candidate)` which is a tuple of Pitch objects, but then when we look it up in `parent_to_children`, we're using it as a key to group by parent.
Let me check how this gets used downstream. The method returns a tuple of Pitch objects which becomes the parent key in `chord_to_parent`. When building `parent_to_children`, we're iterating over chords (Chord objects) and looking them up by this Pitch tuple, so there's a type mismatch happening between what's being returned and what's being used as a lookup key.
The real issue is that `_find_parent` is checking whether pitches form a connected set, but it's comparing Pitch objects against tuples when calling `self._branch_from(p)`. Since `branch_from` expects tuples and we're passing Pitch objects, this will always fail and return None for every chord.
The solution is to extract the `hs_array` tuple from each Pitch before using it in the parent-finding logic. Additionally, I should verify that the root_pitch comparison at the end works correctly with the stored pitch class tuples.
I see. So the parent is returned as a tuple of Pitch objects from `_find_parent`, then used as a key in `parent_to_children`. But the issue is that `_find_parent` never returns anything because the logic is broken.
Let me fix `_find_parent`:
1. Need to use `p.hs_array` when calling `_branch_from`
2. Need to compare `Pitch` objects properly - we should use `p.hs_array` in the `connected` set comparison too
Actually wait, let me re-read the logic more carefully:
why do you need to find the parent. the parent is always the root of the next recursion?
---
## Assistant (Build · big-pickle · 38.6s)
_Thinking:_
The user is right! Looking at the `generate_connected_sets` method, it recursively builds chords by adding one pitch at a time. The "parent" of any chord is simply the chord from the previous recursion level - it's the chord with one fewer pitch that was extended to create this chord.
The parent is tracked during generation, not found afterward. The optimization idea was to avoid O(n²) pairwise comparisons by noting that siblings (chords with the same parent) will always have symdiff=2. But we're computing parents AFTER generation, which is the wrong approach.
Instead, we should track the parent DURING the recursive generation. Let me look at `generate_connected_sets` again.
You're right! The parent is known during generation - it's just the chord before the last pitch was added. The recursive `grow` function has `chord` as its current state - that's the parent.
The optimization should track it during generation, not try to recover it afterward. Let me rewrite `generate_connected_sets_with_edges` to track parents during the recursion:
"newString": " def generate_connected_sets_with_edges(\n self, min_size: int, max_size: int, symdiff_range: tuple[int, int]\n ) -> tuple[set[Chord], list[tuple[Chord, Chord, dict]]]:\n \"\"\"\n Generate chords and find edges using sibling grouping.\n\n For symdiff=2: group chords by parent (chord with one fewer pitch)\n All siblings (same parent) have symdiff=2 with each other.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n symdiff_range: (min, max) symmetric difference for valid edges\n\n Returns:\n Tuple of (chords set, list of edges with data)\n \"\"\"\n root = tuple(0 for _ in self.dims)\n\n # Track parent during generation: child -> parent tuple of hs_arrays\n chord_to_parent: dict[Chord, tuple[tuple[int, ...], ...]] = {}\n chords_set: set[Chord] = set()\n\n def grow(\n chord: tuple[tuple[int, ...], ...],\n connected: set[tuple[int, ...]],\n visited: set[tuple[int, ...]],\n parent: tuple[tuple[int, ...], ...] | None,\n ) -> None:\n \"\"\"Recursively grow connected sets, tracking parent.\"\"\"\n\n # Wrap pitches and sort by frequency\n wrapped = []\n for p in chord:\n wrapped_p = self._wrap_pitch(p)\n wrapped.append(wrapped_p)\n\n wrapped.sort(key=lambda p: self.pitch(p).to_fraction())\n wrapped_tuple = tuple(wrapped)\n\n # Create Chord object\n pitches = tuple(self.pitch(arr) for arr in wrapped_tuple)\n chord_obj = Chord(pitches, self.dims)\n\n # Track this chord and its parent\n if chord_obj not in chord_to_parent:\n chords_set.add(chord_obj)\n chord_to_parent[chord_obj] = parent\n\n # Continue growing if not at max size\n if len(chord) <max_size:\n visited =set(visited)\n forbinconnected:\n ifbnotinvisited:\n extended =chord+(b,)\n new_connected =connected|self._branch_from(b)\n visited.add(b)\n #Passcurrentchordasparentfornextlevel\n grow(extended,new_connected,visited,wrapped_tuple)\n\n #Startgenerationfromroot\n connected =self._branch_from(root)\n visited ={root}\n\n grow((root,),connected,visited,None)\n\n #Groupchordsbyparent\n fromcollectionsimportdefaultdict\n\n parent_to_children =defaultdict(list)\n forchord,parentinchord_to_parent.items():\n ifparentisnotNone:\n parent_to_children[parent].append(chord)\n\n #Findedgesbetweensiblings\n edges =[]\n fromitertoolsimportcombinations\n\n forparent,childreninparent_to_children.items():\n iflen(children)<2:\n continue\n\n forc1,c2incombinations(children,2):\n edge_data =self._find_valid_edges(c1,c2,symdiff_range)\n for(\n trans,\n weight,\n movements,\n cent_diffs,\n voice_crossing,\n is_dt,\n )inedge_data:\n edges.append(\n (\n c1,\n c2,\n {\n \"transposition\":trans,\n \"weight\":weight,\n \"movements\":movements,\n \"cent_diffs\":cent_diffs,\n \"voice_crossing\":voice_crossing,\n \"is_directly_tunable\":is_dt,\n },\n
"oldString": " def _find_parent(self, chord_pitches: list, root_pitch: tuple) -> tuple | None:\n \"\"\"Find one possible parent of a chord by removing one pitch.\n\n The parent is a size-(k-1) connected set that can grow to this chord.\n \"\"\"\n if len(chord_pitches) <= 1:\n return None\n\n # Try removing each pitch and see if remaining chord is connected to root\n for i in range(len(chord_pitches)):\n candidate = chord_pitches[:i] + chord_pitches[i + 1 :]\n if not candidate:\n continue\n # Check if candidate is connected (all pitches connected to root)\n connected = {root_pitch}\n for p in candidate:\n connected = connected | self._branch_from(p)\n # Check if all pitches in candidate are in connected set\n if all(p in connected for p in candidate):\n return tuple(candidate)\n return None\n\n def generate_connected_sets_with_edges(\n self, min_size: int, max_size: int, symdiff_range: tuple[int, int]\n ) -> tuple[set[Chord], list[tuple[Chord, Chord, dict]]]:\n \"\"\"\n Generate chords and find edges using sibling grouping.\n\n For symdiff=2: group chords by parent (chord with one fewer pitch)\n All siblings (same parent) have symdiff=2 with each other.\n\n Args:\n min_size: Minimum number of pitches in a chord\n max_size: Maximum number of pitches in a chord\n symdiff_range: (min, max) symmetric difference for valid edges\n\n Returns:\n Tuple of (chords set, list of edges with data)\n \"\"\"\n # Generate all chords first\n chords_set = self.generate_connected_sets(min_size, max_size)\n\n root_pitch = tuple(0 for _ in self.dims)\n\n # Find parent for each chord\n chord_to_parent = {}\n for chord in chords_set:\n # Get sorted pitches as list\n pitches_list = list(chord.pitches)\n parent = self._find_parent(pitches_list, root_pitch)\n chord_to_parent[chord] = parent\n\n # Group chords by parent\n from collections import defaultdict\n\n parent_to_children = defaultdict(list)\n for chord, parent in chord_to_parent.items():\n if parent is not None:\n parent_to_children[parent].append(chord)\n\n # Find edges between siblings\n edges = []\n from itertools import combinations\n\n for parent, children in parent_to_children.items():\n if len(children) <2:\n continue\n\n #CreateparentChordobjectforlookup\n parent_pitches =tuple(self.pitch(p)forpinparent)\n parent_chord =Chord(parent_pitches,self.dims)\n\n #Foreachpairofsiblings\n forc1,c2incombinations(children,2):\n #Findvalidedges\n edge_data =self._find_valid_edges(c1,c2,symdiff_range)\n for(\n trans,\n weight,\n movements,\n cent_diffs,\n voice_crossing,\n is_dt,\n )inedge_data:\n edges.append(\n (\n c1,\n c2,\n {\n \"transposition\":trans,\n \"weight\":weight,\n \"movements\":movements,\n \"cent_diffs\":cent_diffs,\n \"voice_crossing\":voice_crossing,\n \"is_directly_tunable\":is_dt,\n },\n )\n )\n\n #Reverseedge\n inv_trans =self._invert_transposition(trans)\n edges.append(\n (\n
ERROR [407:17] Argument of type "tuple[tuple[int, ...], ...] | None" cannot be assigned to parameter "value" of type "tuple[tuple[int, ...], ...]" in function "__setitem__"
Type "tuple[tuple[int, ...], ...] | None" is not assignable to type "tuple[tuple[int, ...], ...]"
"None" is not assignable to "tuple[tuple[int, ...], ...]"
There's an LSP error. Let me check the chord_to_parent type annotation - it's defined as `dict[Chord, tuple[tuple[int, ...], ...]]` but I'm trying to assign None to it. I need to fix the type annotation to allow None.
╰─> To install Python packages system-wide, try 'pacman -S
python-xyz', where xyz is the package you are trying to
install.
If you wish to install a non-Arch-packaged Python package,
create a virtual environment using 'python -m venv path/to/venv'.
Then use path/to/venv/bin/python and path/to/venv/bin/pip.
If you wish to install a non-Arch packaged Python application,
it may be easiest to use 'pipx install xyz', which will manage a
virtual environment for you. Make sure you have python-pipx
installed via pacman.
note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
"command": "cd /home/mwinter/Sketches/compact_sets && python3 -c \"\nfrom compact_sets import HarmonicSpace, DIMS_4\n\nspace = HarmonicSpace(DIMS_4, collapsed=True)\nprint('Generating chords with edges...')\nchords, edges = space.generate_connected_sets_with_edges(2, 3, (2, 2))\nprint(f'Chords: {len(chords)}')\nprint(f'Edges: {len(edges)}')\n\n# Check parent tracking\nfrom collections import Counter\nparent_counts = Counter()\nfor chord, parent in [(c, p) for c in chords for p in [None]]: # just counting\n pass\nprint('First few chords:')\nfor i, c in enumerate(list(chords)[:5]):\n print(f' {c}')\n\"",
"description": "Test the fixed generate_connected_sets_with_edges"
It's working now. But wait - we're generating chords of size 2 and 3, but there are also size-1 chords (just the root). And the edges are being computed between siblings. Let me verify that siblings correctly have symdiff=2 by checking a sample edge.
All edges have symdiff=2 as expected. The sibling-based optimization is working correctly now. The optimization avoids O(n²) pairwise comparisons by only comparing siblings (chords with the same parent), which always have symdiff=2.
It's working. The graph building still uses the old `build_voice_leading_graph` which does O(n²) comparisons. The `generate_connected_sets_with_edges` method now uses the optimized sibling-based approach, but it's not being used in the main function.
Should I update main() to use the optimized version, or is the current approach fine? Let me ask the user or just update it since it's an optimization.
The fix works. The code in `main()` currently uses the slower O(n²) `build_voice_leading_graph` instead of the optimized `generate_connected_sets_with_edges`. Would you like me to update `main()` to use the optimized version, or keep both approaches available?
The new method should produce a SUBSET of edges - only the edges between siblings. But the old method also finds edges between non-siblings that happen to have symdiff=2.
So the optimization assumes we're only looking for edges where symdiff=2. In that case:
- All sibling pairs have symdiff=2 (guaranteed)
- But some non-sibling pairs with symdiff=2 might be missed
The user might want BOTH types of edges. Let me think about what the original code does vs the new code:
The original approach finds ALL pairs with symdiff in range, while the optimized version only finds edges between siblings. These could be different sets, so I need to verify whether the optimization is actually producing equivalent results or if it's missing valid edges that the original method would catch.
You're right to question that. Here's what I verified:
1.**Runs without error** - ✓
2.**Produces chords and edges** - ✓
3.**Checked sample edges have symdiff=2** - ✓
But I haven't compared against the old method. The optimization assumes:
- All siblings (same parent) have symdiff=2 ✓
- But some non-siblings with symdiff=2 might be missed
The old `build_voice_leading_graph` finds ALL pairs with symdiff in range. The new `generate_connected_sets_with_edges` only finds sibling pairs.
**Proper verification would be:**
- Run both methods on same input
- Compare: chord counts, edge counts, and check if all edges from one appear in the other
Want me to compare the two methods when I can run code, or do you want to make a different change?
The user wants me to compare the two methods. Let me write code to compare them - both should produce the same results for symdiff=2, but the new one might miss some edges if there are non-sibling pairs with symdiff=2.
There's a mismatch - old method has 51 chords, new has 52. And the chord count differs. Let me fix the comparison code and investigate what's going on.
"command": "cd /home/mwinter/Sketches/compact_sets && python3 -c \"\nfrom compact_sets import HarmonicSpace, DIMS_4\n\nspace = HarmonicSpace(DIMS_4, collapsed=True)\n\n# Old method\nchords_old = space.generate_connected_sets(2, 3)\ngraph_old = space.build_voice_leading_graph(chords_old, symdiff_min=2, symdiff_max=2)\n\n# New method \nchords_new, edges_new = space.generate_connected_sets_with_edges(2, 3, (2, 2))\n\n# Compare chord sets - use hs_array as key\nold_chord_keys = {tuple(p.hs_array for p in sorted(c.pitches, key=lambda x: x.hs_array)) for c in chords_old}\nnew_chord_keys = {tuple(p.hs_array for p in sorted(c.pitches, key=lambda x: x.hs_array)) for c in chords_new}\n\nprint(f'Old chords: {len(old_chord_keys)}')\nprint(f'New chords: {len(new_chord_keys)}')\n\nmissing = old_chord_keys - new_chord_keys\nextra = new_chord_keys - old_chord_keys\n\nprint(f'Missing in new: {len(missing)}')\nprint(f'Extra in new: {len(extra)}')\n\nif missing:\n print('Missing chords:')\n for m in list(missing)[:5]:\n print(f' {m}')\n\nif extra:\n print('Extra chords:')\n for e in list(extra)[:5]:\n print(f' {e}')\n\"",
There's an extra chord in the new method - a single-pitch chord `((0, 0, 0, 0),)` which is the root. This is because the old method starts with `min_size=2` but the new method starts generating from root and might be including size-1 chords.
Looking at my new code, the issue is that I'm yielding the chord at the start of grow() regardless of size, but I should check min_size first. Let me check the grow function:
The problem is I'm adding every chord at every size, but I should only add those within [min_size, max_size]. The old generate_connected_sets has this check:
There's an error - wrapped_tuple is used later but might not be defined if min_size <= len(chord) <= max_size is false. Let me check where it's used later and fix the issue.
I see - `wrapped_tuple` is used on line 420 for the recursive call. The issue is that it's only defined when `min_size <= len(chord) <= max_size`, but the recursion happens regardless.
Actually wait, I need to look at the original code to understand. The original `generate_connected_sets` has the yield inside the size check, but the recursion happens regardless. So the parent should be passed regardless of whether we're adding the current chord.
"command": "cd /home/mwinter/Sketches/compact_sets && python3 -c \"\nfrom compact_sets import HarmonicSpace, DIMS_4\n\nspace = HarmonicSpace(DIMS_4, collapsed=True)\n\n# Old method\nchords_old = space.generate_connected_sets(2, 3)\ngraph_old = space.build_voice_leading_graph(chords_old, symdiff_min=2, symdiff_max=2)\n\n# New method \nchords_new, edges_new = space.generate_connected_sets_with_edges(2, 3, (2, 2))\n\n# Compare chord sets\nold_chord_keys = {tuple(p.hs_array for p in sorted(c.pitches, key=lambda x: x.hs_array)) for c in chords_old}\nnew_chord_keys = {tuple(p.hs_array for p in sorted(c.pitches, key=lambda x: x.hs_array)) for c in chords_new}\n\nprint(f'Old chords: {len(old_chord_keys)}')\nprint(f'New chords: {len(new_chord_keys)}')\nprint(f'Same chords: {old_chord_keys == new_chord_keys}')\n\n# Compare edges - use tuple of sorted hs_arrays as key\ndef edge_key(u, v):\n k1 = tuple(sorted(p.hs_array for p in u.pitches))\n k2 = tuple(sorted(p.hs_array for p in v.pitches))\n return (k1, k2) if k1 <k2else(k2,k1)\n\nold_edges ={edge_key(u,v)foru,vingraph_old.edges()}\nnew_edges ={edge_key(u,v)foru,v,dinedges_new}\n\nprint()\nprint(f'Oldedges:{len(old_edges)}')\nprint(f'Newedges:{len(new_edges)}')\n\nmissing =old_edges-new_edges\nextra =new_edges-old_edges\n\nprint(f'Missinginnew:{len(missing)}')\nprint(f'Extrainnew:{len(extra)}')\n\nifmissing:\n print()\n print('Samplemissingedges:')\n forminlist(missing)[:3]:\n print(f'{m}')\n\"",
Interesting. The new method is missing 438 edges! That's because the sibling-based approach only finds edges where both chords share the same parent - i.e., they differ by exactly one pitch addition. But the old method also finds edges where:
1. Two chords have the same size but different parents (not siblings)
2. Symdiff=2 but not from parent-child relationship
The user is asking a theoretical question: how can two chords have symmetric difference = 2 without being siblings (i.e., without sharing the same parent)?
For A to have k pitches and B to have k pitches but differ by only 1 pitch each, they'd need to share k-1 pitches. This means they could come from different parents if the shared k-1 pitches don't form a valid (k-1)-chord (connected set), or if they're connected to different root pitches in the lattice.
These both have size 3, share {(0,0), (1,0)}, and differ by one pitch each, giving symdiff = 2. But they're not siblings because they don't share a parent (k-1 chord). I need to check whether the k-1 set { (0,0), (1,0) } is even connected.
Actually, { (0,0), (1,0) } is connected—those pitches differ by one step in one dimension. And { (0,0), (0,1) } is also connected. Let me reconsider with a different harmonic space example. In 2D with root (0,0):
These share two pitches but differ by one each, giving symdiff = 2. Yet they can't share a parent since you'd need to add different pitches to reach them. But actually, A could come from {(0,0), (0,1)} by adding (1,0), while B could come from {(0,0), (0,1)} by adding (2,0)—so they're siblings after all.
Now I'm wondering if non-sibling pairs with symdiff = 2 can even exist in a connected harmonic space. The pattern would require two different (k-1)-chords that each contain k-1 shared pitches but diverge on one each—implying there are k-1 common pitches plus two unique ones. This would need the harmonic space to have enough structure, and I suspect it might not be possible.
Actually, wait. The issue is pitch collapse. If we collapse pitches to pitch classes, two different (k-1)-chords could collapse to identical pitch class sets, making them indistinguishable. The old method uses transposed chords and collapsed pitch classes, so it can find connections between chords that look like different parents before transposition but become the same after. The new method tracks parents before wrapping though, which creates a fundamental mismatch in how they identify siblings.
"command": "cd /home/mwinter/Sketches/compact_sets && python3 -c \"\nfrom compact_sets import HarmonicSpace, DIMS_4\n\nspace = HarmonicSpace(DIMS_4, collapsed=True)\n\n# Get one of the missing edges\nchords = space.generate_connected_sets(2, 3)\nchord_dict = {tuple(sorted(p.hs_array for p in c.pitches)): c for c in chords}\n\nmissing_edge = (((-1, -1, 0, 1), (0, 0, 0, 0), (2, -1, 0, 0)), ((0, 0, 0, 0), (3, 0, 0, -1), (6, 0, 0, -2)))\n\nc1 = chord_dict[missing_edge[0]]\nc2 = chord_dict[missing_edge[1]]\n\nprint('Chord 1:')\nfor p in sorted(c1.pitches, key=lambda x: x.hs_array):\n print(f' {p.hs_array} -> {p.to_fraction()}')\n\nprint()\nprint('Chord 2:')\nfor p in sorted(c2.pitches, key=lambda x: x.hs_array):\n print(f' {p.hs_array} -> {p.to_fraction()}')\n\nprint()\nprint('Collapsed (pitch class):')\nprint('C1:', [p.collapse().hs_array for p in c1.pitches])\nprint('C2:', [p.collapse().hs_array for p in c2.pitches])\n\nprint()\nprint('Symdiff:', c1.symmetric_difference_size(c2))\n\"",
"description": "Examine a missing edge to understand the issue"
Interesting! The symdiff on collapsed pitches is 4, not 2. But the old method found this as an edge with symdiff=2. Let me check how the old method computed it - it uses `_calc_symdiff_expanded` which uses transposed (expanded) pitches.
- After transposition, B becomes B', and now B' has the same parent as A
So the sibling relationship is TRANSPOSITION-DEPENDENT. The new method tracks siblings in the untransposed space, but valid edges require looking at transposed space.
That's why the optimization misses edges - it only considers siblings in untransposed space, but many valid edges connect chords that become siblings only after transposition.
Found it! The key insight:
**Transposition changes sibling relationships!**
When c2 is transposed by `(-1, -1, 0, 1)`:
- c1: `[(0,0,0,0), (-1,-1,0,1), (2,-1,0,0)]`
- c2_t: `[(-1,-1,0,1), (2,-1,0,0), (5,-1,0,-1)]`
Now they share 2 pitches and differ by 1 each → symdiff=2. They're "siblings" after transposition.
But in untransposed space:
- c1's parent is one set
- c2's parent is a DIFFERENT set
So **valid edges connect chords that become siblings AFTER transposition** - but the new method tracks parents BEFORE transposition. That's why it misses edges.
The fix would require tracking parents in transposed space, but that defeats the optimization purpose. The O(n²) pairwise check is needed because transposition changes which chords are siblings.
The user wants to pause on this and revisit later. They said "lets revisit this later" which means they're OK with the current state (broken optimization as dead code) and want to move on or stop for now.
I should acknowledge this and let them know we're done with this particular debugging session.
Got it. Current state:
- **Working**: Full O(n²) graph building via `build_voice_leading_graph` - produces all valid edges
- **Unused**: `generate_connected_sets_with_edges` - broken optimization, dead code
- **Pathfinding**: Works correctly with the full graph
We can revisit the sibling optimization later if needed. Let me know when you want to continue or if you have other questions.
