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Fabro 2026-03-16 08:00:35 -04:00
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52
checkpoint.json
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@ -1,30 +1,37 @@
{
"timestamp": "2026-03-16T11:58:07.402704Z",
"current_node": "setup",
"timestamp": "2026-03-16T12:00:34.997886Z",
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"graph.goal": "Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels\nConsider the following model:\r\n\r\n```python\r\nfrom astropy.modeling import models as m\r\nfrom astropy.modeling.separable import separability_matrix\r\n\r\ncm = m.Linear1D(10) & m.Linear1D(5)\r\n```\r\n\r\nIt's separability matrix as you might expect is a diagonal:\r\n\r\n```python\r\n>>> separability_matrix(cm)\r\narray([[ True, False],\r\n [False, True]])\r\n```\r\n\r\nIf I make the model more complex:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & m.Linear1D(10) & m.Linear1D(5))\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, False],\r\n [False, False, False, True]])\r\n```\r\n\r\nThe output matrix is again, as expected, the outputs and inputs to the linear models are separable and independent of each other.\r\n\r\nIf however, I nest these compound models:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & cm)\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, True],\r\n [False, False, True, True]])\r\n```\r\nSuddenly the inputs and outputs are no longer separable?\r\n\r\nThis feels like a bug to me, but I might be missing something?\n",
"failure_signature": "setup|deterministic|script failed with exit code: <n> ## stdout fatal: destination path '.' already exists and is not an empty directory.",
"failure_signature": "",
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"outcome": "fail",
"response.solve": "The fix is applied. Here's a summary:\n\n## Root Cause\n\nIn `astropy/modeling/separable.py`, the `_cstack` function handles the `&` (concatenation) operator for computing separability matrices. When the right operand is already an ndarray (which happens when it's a nested CompoundModel that has already been recursively evaluated by `_separable`), line 245 was:\n\n```python\ncright[-right.shape[0]:, -right.shape[1]:] = 1\n```\n\nThis set the entire bottom-right block to `1`, **discarding** the actual separability information that was computed for the nested compound model. This made all outputs appear to depend on all inputs for that sub-model.\n\n## Fix\n\nChanged line 245 from `= 1` to `= right`:\n\n```python\ncright[-right.shape[0]:, -right.shape[1]:] = right\n```\n\nThis preserves the actual separability matrix computed for the nested compound model, just like the `left` branch already correctly does on line 240 (`= left`).\n\nThis is a one-line fix that makes the `right` branch consistent with the `left` branch — both now properly copy the pre-computed separability matrix instead of replacing it with all ones.",
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"current.preamble": "Goal: Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels\nConsider the following model:\r\n\r\n```python\r\nfrom astropy.modeling import models as m\r\nfrom astropy.modeling.separable import separability_matrix\r\n\r\ncm = m.Linear1D(10) & m.Linear1D(5)\r\n```\r\n\r\nIt's separability matrix as you might expect is a diagonal:\r\n\r\n```python\r\n>>> separability_matrix(cm)\r\narray([[ True, False],\r\n [False, True]])\r\n```\r\n\r\nIf I make the model more complex:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & m.Linear1D(10) & m.Linear1D(5))\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, False],\r\n [False, False, False, True]])\r\n```\r\n\r\nThe output matrix is again, as expected, the outputs and inputs to the linear models are separable and independent of each other.\r\n\r\nIf however, I nest these compound models:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & cm)\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, True],\r\n [False, False, True, True]])\r\n```\r\nSuddenly the inputs and outputs are no longer separable?\r\n\r\nThis feels like a bug to me, but I might be missing something?\n\n",
"current.preamble": "Goal: Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels\nConsider the following model:\r\n\r\n```python\r\nfrom astropy.modeling import models as m\r\nfrom astropy.modeling.separable import separability_matrix\r\n\r\ncm = m.Linear1D(10) & m.Linear1D(5)\r\n```\r\n\r\nIt's separability matrix as you might expect is a diagonal:\r\n\r\n```python\r\n>>> separability_matrix(cm)\r\narray([[ True, False],\r\n [False, True]])\r\n```\r\n\r\nIf I make the model more complex:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & m.Linear1D(10) & m.Linear1D(5))\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, False],\r\n [False, False, False, True]])\r\n```\r\n\r\nThe output matrix is again, as expected, the outputs and inputs to the linear models are separable and independent of each other.\r\n\r\nIf however, I nest these compound models:\r\n```python\r\n>>> separability_matrix(m.Pix2Sky_TAN() & cm)\r\narray([[ True, True, False, False],\r\n [ True, True, False, False],\r\n [False, False, True, True],\r\n [False, False, True, True]])\r\n```\r\nSuddenly the inputs and outputs are no longer separable?\r\n\r\nThis feels like a bug to me, but I might be missing something?\n\n\n## Completed stages\n- **setup**: fail\n - Script: `git clone https://github.com/astropy/astropy.git . && git checkout d16bfe05a744909de4b27f5875fe0d4ed41ce607 && sed -i 's/requires = \\[\"setuptools\",/requires = \\[\"setuptools==68.0.0\",/' pyproject.toml && python -m pip install -e .[test] --verbose`\n - Stdout:\n ```\n fatal: destination path '.' already exists and is not an empty directory.\n ```\n - Stderr: (empty)\n\n## Context\n- failure_class: deterministic\n- failure_signature: setup|deterministic|script failed with exit code: <n> ## stdout fatal: destination path '.' already exists and is not an empty directory.\n",
"internal.retry_count.setup": 1,
"last_response": "The fix is applied. Here's a summary:\n\n## Root Cause\n\nIn `astropy/modeling/separable.py`, the `_cstack` function handles the `&` (concatenation) operator for computing separability matrices. When the ",
"command.output": "fatal: destination path '.' already exists and is not an empty directory.\n"
},
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@ -44,14 +51,37 @@
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"last_response": "The fix is applied. Here's a summary:\n\n## Root Cause\n\nIn `astropy/modeling/separable.py`, the `_cstack` function handles the `&` (concatenation) operator for computing separability matrices. When the ",
"response.solve": "The fix is applied. Here's a summary:\n\n## Root Cause\n\nIn `astropy/modeling/separable.py`, the `_cstack` function handles the `&` (concatenation) operator for computing separability matrices. When the right operand is already an ndarray (which happens when it's a nested CompoundModel that has already been recursively evaluated by `_separable`), line 245 was:\n\n```python\ncright[-right.shape[0]:, -right.shape[1]:] = 1\n```\n\nThis set the entire bottom-right block to `1`, **discarding** the actual separability information that was computed for the nested compound model. This made all outputs appear to depend on all inputs for that sub-model.\n\n## Fix\n\nChanged line 245 from `= 1` to `= right`:\n\n```python\ncright[-right.shape[0]:, -right.shape[1]:] = right\n```\n\nThis preserves the actual separability matrix computed for the nested compound model, just like the `left` branch already correctly does on line 240 (`= left`).\n\nThis is a one-line fix that makes the `right` branch consistent with the `left` branch — both now properly copy the pre-computed separability matrix instead of replacing it with all ones."
},
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nodes/solve/prompt.md Normal file
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Goal: Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as you might expect is a diagonal:
```python
>>> separability_matrix(cm)
array([[ True, False],
[False, True]])
```
If I make the model more complex:
```python
>>> separability_matrix(m.Pix2Sky_TAN() & m.Linear1D(10) & m.Linear1D(5))
array([[ True, True, False, False],
[ True, True, False, False],
[False, False, True, False],
[False, False, False, True]])
```
The output matrix is again, as expected, the outputs and inputs to the linear models are separable and independent of each other.
If however, I nest these compound models:
```python
>>> separability_matrix(m.Pix2Sky_TAN() & cm)
array([[ True, True, False, False],
[ True, True, False, False],
[False, False, True, True],
[False, False, True, True]])
```
Suddenly the inputs and outputs are no longer separable?
This feels like a bug to me, but I might be missing something?
## Completed stages
- **setup**: fail
- Script: `git clone https://github.com/astropy/astropy.git . && git checkout d16bfe05a744909de4b27f5875fe0d4ed41ce607 && sed -i 's/requires = \["setuptools",/requires = \["setuptools==68.0.0",/' pyproject.toml && python -m pip install -e .[test] --verbose`
- Stdout:
```
fatal: destination path '.' already exists and is not an empty directory.
```
- Stderr: (empty)
## Context
- failure_class: deterministic
- failure_signature: setup|deterministic|script failed with exit code: <n> ## stdout fatal: destination path '.' already exists and is not an empty directory.
Fix this GitHub issue in the repository. Make the minimal code change needed.

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nodes/solve/provider_used.json Normal file
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{
"mode": "agent",
"provider": "anthropic",
"model": "claude-opus-4-6"
}

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nodes/solve/response.md Normal file
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@ -0,0 +1,23 @@
The fix is applied. Here's a summary:
## Root Cause
In `astropy/modeling/separable.py`, the `_cstack` function handles the `&` (concatenation) operator for computing separability matrices. When the right operand is already an ndarray (which happens when it's a nested CompoundModel that has already been recursively evaluated by `_separable`), line 245 was:
```python
cright[-right.shape[0]:, -right.shape[1]:] = 1
```
This set the entire bottom-right block to `1`, **discarding** the actual separability information that was computed for the nested compound model. This made all outputs appear to depend on all inputs for that sub-model.
## Fix
Changed line 245 from `= 1` to `= right`:
```python
cright[-right.shape[0]:, -right.shape[1]:] = right
```
This preserves the actual separability matrix computed for the nested compound model, just like the `left` branch already correctly does on line 240 (`= left`).
This is a one-line fix that makes the `right` branch consistent with the `left` branch — both now properly copy the pre-computed separability matrix instead of replacing it with all ones.

6
nodes/solve/status.json Normal file
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@ -0,0 +1,6 @@
{
"status": "success",
"notes": "Stage completed: solve",
"failure_reason": null,
"timestamp": "2026-03-16T12:00:34.997519+00:00"
}