ROLLOUT 2 · pyqtgraph/pyqtgraph
pyqtgraph__pyqtgraph-3278
Solved
355 stotal time
16tool calls
19model calls
4,637tokens generated
169,191prompt tokens read
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System instructions 4,822 characters
You are a principal Python software engineer resolving a repository issue in `/workspace`. Your sole objective is to produce a minimal, root-cause source patch that passes every hidden fail-to-pass and pass-to-pass regression test on the first grading run. ## Critical Environment & Grader Rules 1. **Air-Gapped Sandbox & Available CLI Tools**: No network access. Never run `pip`, `uv`, `conda`, or `git fetch`. Note: `rg` (`ripgrep`) is NOT installed in the container — always use `grep -rn --include="*.py"` for fast exact searches so you never waste a tool call on `command not found`. 2. **Protected Grading Paths**: Before running official verification, the grading harness **strips and reverts all changes** to `tests/`, `test/`, `testing/`, `test_*.py`, `*_test.py`, `conftest.py`, `pyproject.toml`, `setup.cfg`, `pytest.ini`, and `tox.ini`. Every part of your fix MUST reside in non-test production source files. 3. **Untracked File Trap (`git add -N .`)**: `submit_patch` stages ALL untracked files inside `/workspace`! Never leave reproduction or scratch files inside `/workspace` — run reproductions inline via `python3 - <<'PY'` or inside `/tmp/repro.py` in a single `run_command`. 4. **Stdout Truncation Rule**: `run_command` truncates stdout after the first 5,000 characters from the TOP. Always run pytest quietly with short tracebacks: `pytest path/to/test_file.py -k pattern -q --tb=short --no-header` If a test file is large, redirect output to `/tmp/pytest.log` and inspect `tail -n 80 /tmp/pytest.log` so failure tracebacks at the bottom are never cut off. 5. **Strict Pacing Discipline**: `get_status` and `submit_patch` are free and do NOT count toward `max_tool_calls`. Target **16-22 counted tool calls total**, and **begin your first `edit_file` change no later than tool call 15**. Reserve at least 4 calls for verification, `git status --short && git diff`, and submission. ## Execution Protocol ### Phase 1 — Pinpoint Code & Tests Immediately (1-2 tool calls) - The user message already contains `Workspace Layout` — do NOT waste a turn running `ls` on top-level directories. - Run a single compound `run_command` with `grep -rn --include="*.py"` to locate: (a) the exact symbols, error strings, or functions from the problem description, (b) **all parallel or sibling implementations** (for example sync + async variants, `Client` + `AsyncClient`, serializer + deserializer, multiple backends/dialects, base + subclass methods, `__init__.py` / `__all__` exports), and (c) the closest existing unit test files under `tests/`. ### Phase 2 — Deep Read & Spec Anchor (2-5 tool calls) - Use `read_file` with generous `start_line` and `end_line` windows (180-300 lines per call so you read whole modules in fewer calls) on the target function/class, callers, type annotations, and neighboring tests. - Before editing, verify every explicit and implicit requirement from the issue: exact parameter names, defaults, boundary/domain edge cases, exception types/messages, `None` vs empty collection vs falsy (`0`, `False`, `""`) semantics, mutability/copying, and return types. ### Phase 3 — Reproduce Bug in One Call (1 tool call) - Run ONE concise command (`python3 - <<'PY' ... PY` or targeted `pytest ... -q --tb=short --no-header`) via `run_command` to observe the exact pre-fix failure. Do NOT spend multiple tool calls writing separate reproduction scripts. ### Phase 4 — Surgical Implementation Across All Parallel Paths (1-4 tool calls) - Begin editing by tool call 15! Use `edit_file` with 4-6 lines of exact surrounding context copied from `read_file`. - Update ALL parallel codepaths (sync/async, multiple classes/dialects, type hints) consistently so partial fixes do not fail sibling tests. - **2-Strike Edit Rule**: If `edit_file` fails twice on the same block due to whitespace or escaping, do not retry `edit_file` a third time — apply an atomic Python transformation via `run_command` and immediately verify `python3 -m py_compile path/to/file.py`. ### Phase 5 — Edge-Case Verification, Diff Hygiene & Clean Exit (2-4 tool calls) - Run a single compound `run_command` testing both your reproduction + boundary edge cases (`None`, empty input, leading/trailing delimiters, subdomain/prefix boundaries, subclass/async parity) AND the relevant existing `pytest` module(s) with `-q --tb=short --no-header`. - Run `git status --short && git diff` via `run_command`. Confirm: - ZERO untracked (`??`) files in `/workspace` (`rm -f` any untracked workspace files immediately), - ZERO modifications to `tests/` or protected config files (`git checkout -- tests/` if touched), - Minimal, clean diff with valid imports and indentation. - Call `submit_patch` once verification passes, then respond with a brief 2-sentence plain-text summary and make NO further tool calls.
Task prompt 9,569 characters
You are evaluating a software engineering task for repository pyqtgraph/pyqtgraph.
Problem Statement:
TypeError when using a record array to plot data
<!-- In the following, please describe your issue in detail! -->
<!-- If some sections do not apply, just remove them. -->
### Short description
<!-- This should summarize the issue. -->
Using a NumPy record array as data to plot results in the following:
`TypeError: Cannot compare structured or void to non-void arrays.`
### Code to reproduce
<!-- Please provide a minimal working example that reproduces the issue in the code block below.
Ideally, this should be a full example someone else could run without additional setup. -->
```python
import pyqtgraph as pg
import numpy as np
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
pg.plot(data_array)
pg.exec()
```
### Expected behavior
<!-- What should happen? -->
According to the API reference, a PlotDataItem can be initialized with a NumPy recarray with `dtype=[('x', float), ('y', float), ...]`, so the above code should plot the (uninitialized) recarray data.
### Real behavior
<!-- What happens? -->
```
Traceback (most recent call last):
File "C:\Users\_\code\recarray_test.py", line 5, in <module>
pg.plot(data_array)
File "C:\Users\_\code\.venv\lib\site-packages\pyqtgraph\__init__.py", line 392, in plot
w.plot(*args, **dataArgs)
File "C:\Users\_\code\.venv\lib\site-packages\pyqtgraph\graphicsItems\PlotItem\PlotItem.py", line 630, in plot
item = PlotDataItem(*args, **kargs)
File "C:\Users\_\code\.venv\lib\site-packages\pyqtgraph\graphicsItems\PlotDataItem.py", line 375, in __init__
self.setData(*args, **kargs)
File "C:\Users\_\code\.venv\lib\site-packages\pyqtgraph\graphicsItems\PlotDataItem.py", line 719, in setData
if 'x' in data:
TypeError: Cannot compare structured or void to non-void arrays.
```
### Tested environment(s)
* PyQtGraph version: 0.13.7
* Qt Python binding: PyQt6 6.8.1 Qt 6.8.2
* Python version: 3.9.13
* NumPy version: 2.0.2
* Operating system: Windows 11
* Installation method: pip
## Task Budget (Session terminates when any budget is exhausted)
- Time allowance: 7.5 minutes
- Tool calls allowance: 30 calls
- Max loop iterations: 40 turns
## Execution Environment Rules
- Single command timeout: 90 seconds (commands exceeding this fail without ending the session)
- Command output limit: 5000 characters
- File view limit: 150 lines per read_file call
- File character limit: 10000 characters per read_file call
- Environment is offline (no network/PyPI access). All repository and test dependencies are ALREADY pre-installed. Do NOT attempt to run pip install or download packages.
## Instructions:
0. All source code is under `/workspace`. Do NOT search outside `/workspace` (e.g. `/usr/`, `/wheels/`, system site-packages). If imports fail, the issue is in the source code under `/workspace`, not in missing system packages.
1. Analyze the problem statement and any provided hints carefully to identify all requested script paths, CLI subcommands, or Python modules.
2. Inspect existing codebase conventions and test files before making edits.
3. Verify your implementation using targeted tests or inline assertions before submitting.
4. Call submit_patch only after your implementation is complete and verified.
5. As your final action, you must return a text-only response reporting your completion to terminate the session.
## Workspace Layout
The repository is located at `/workspace`. Here is the directory tree (up to 3 levels):
```
./CHANGELOG
./CODE_OF_CONDUCT.md
./CONTRIBUTING.md
./LICENSE.txt
./MANIFEST.in
./README.md
./benchmarks
./binder
./binder/apt.txt
./binder/requirements.txt
./binder/runtime.txt
./binder/start
./doc
./doc/Makefile
./doc/listmissing.py
./doc/make.bat
./doc/requirements.txt
./doc/source
./doc/source/_static
./doc/source/api_reference
./doc/source/conf.py
./doc/source/developer_guide
./doc/source/dictionaries
./doc/source/getting_started
./doc/source/images
./doc/source/index.rst
./doc/source/user_guide
./doc/uml_overview.txt
./pyproject.toml
./pyqtgraph
./pyqtgraph/GraphicsScene
./pyqtgraph/GraphicsScene/GraphicsScene.py
./pyqtgraph/GraphicsScene/__init__.py
./pyqtgraph/GraphicsScene/exportDialog.py
./pyqtgraph/GraphicsScene/exportDialogTemplate.ui
./pyqtgraph/GraphicsScene/exportDialogTemplate_generic.py
./pyqtgraph/GraphicsScene/mouseEvents.py
./pyqtgraph/PlotData.py
./pyqtgraph/Point.py
./pyqtgraph/Qt
./pyqtgraph/Qt/OpenGLConstants.py
./pyqtgraph/Qt/OpenGLHelpers.py
./pyqtgraph/Qt/QtCore
./pyqtgraph/Qt/QtGui
./pyqtgraph/Qt/QtSvg.pyi
./pyqtgraph/Qt/QtTest.pyi
./pyqtgraph/Qt/QtWidgets
./pyqtgraph/Qt/__init__.py
./pyqtgraph/Qt/__init__.pyi
./pyqtgraph/Qt/compat
./pyqtgraph/Qt/internals.py
./pyqtgraph/SRTTransform.py
./pyqtgraph/SRTTransform3D.py
./pyqtgraph/SignalProxy.py
./pyqtgraph/ThreadsafeTimer.py
./pyqtgraph/Transform3D.py
./pyqtgraph/Vector.py
./pyqtgraph/WidgetGroup.py
./pyqtgraph/__init__.py
./pyqtgraph/colormap.py
./pyqtgraph/colors
./pyqtgraph/colors/__init__.py
./pyqtgraph/colors/maps
./pyqtgraph/colors/palette.py
./pyqtgraph/configfile.py
./pyqtgraph/console
./pyqtgraph/console/CmdInput.py
./pyqtgraph/console/Console.py
./pyqtgraph/console/__init__.py
./pyqtgraph/console/exception_widget.py
./pyqtgraph/console/repl_widget.py
./pyqtgraph/console/stackwidget.py
./pyqtgraph/debug.py
./pyqtgraph/dockarea
./pyqtgraph/dockarea/Container.py
./pyqtgraph/dockarea/Dock.py
./pyqtgraph/dockarea/DockArea.py
./pyqtgraph/dockarea/DockDrop.py
./pyqtgraph/dockarea/__init__.py
./pyqtgraph/examples
./pyqtgraph/examples/Arrow.py
./pyqtgraph/examples/AxisItem_label_overlap.py
./pyqtgraph/examples/BarGraphItem.py
./pyqtgraph/examples/CLIexample.py
./pyqtgraph/examples/ColorBarItem.py
./pyqtgraph/examples/ColorButton.py
./pyqtgraph/examples/ColorGradientPlots.py
./pyqtgraph/examples/ConsoleWidget.py
./pyqtgraph/examples/CustomGraphItem.py
./pyqtgraph/examples/DataSlicing.py
./pyqtgraph/examples/DataTreeWidget.py
./pyqtgraph/examples/DateAxisItem.py
./pyqtgraph/examples/DateAxisItem_QtDesigner.py
./pyqtgraph/examples/DateAxisItem_QtDesigner.ui
./pyqtgraph/examples/DiffTreeWidget.py
./pyqtgraph/examples/Draw.py
./pyqtgraph/examples/ErrorBarItem.py
./pyqtgraph/examples/ExampleApp.py
./pyqtgraph/examples/FillBetweenItem.py
./pyqtgraph/examples/Flowchart.py
./pyqtgraph/examples/FlowchartCustomNode.py
./pyqtgraph/examples/GLBarGraphItem.py
./pyqtgraph/examples/GLGradientLegendItem.py
./pyqtgraph/examples/GLGraphItem.py
./pyqtgraph/examples/GLImageItem.py
./pyqtgraph/examples/GLIsosurface.py
./pyqtgraph/examples/GLLinePlotItem.py
./pyqtgraph/examples/GLMeshItem.py
./pyqtgraph/examples/GLPainterItem.py
./pyqtgraph/examples/GLScatterPlotItem.py
./pyqtgraph/examples/GLSurfacePlot.py
./pyqtgraph/examples/GLTextItem.py
./pyqtgraph/examples/GLViewWidget.py
./pyqtgraph/examples/GLVolumeItem.py
./pyqtgraph/examples/GLshaders.py
./pyqtgraph/examples/GradientEditor.py
./pyqtgraph/examples/GradientWidget.py
./pyqtgraph/examples/GraphItem.py
./pyqtgraph/examples/GraphicsLayout.py
./pyqtgraph/examples/GraphicsScene.py
./pyqtgraph/examples/HistogramLUT.py
./pyqtgraph/examples/ImageItem.py
./pyqtgraph/examples/ImageView.py
./pyqtgraph/examples/InfiniteLine.py
./pyqtgraph/examples/InteractiveParameter.py
./pyqtgraph/examples/JoystickButton.py
./pyqtgraph/examples/Legend.py
./pyqtgraph/examples/LogPlotTest.py
./pyqtgraph/examples/MatrixDisplayExample.py
./pyqtgraph/examples/MouseSelection.py
./pyqtgraph/examples/MultiDataPlot.py
./pyqtgraph/examples/MultiPlotSpeedTest.py
./pyqtgraph/examples/MultiplePlotAxes.py
./pyqtgraph/examples/NonUniformImage.py
./pyqtgraph/examples/PColorMeshItem.py
./pyqtgraph/examples/PanningPlot.py
./pyqtgraph/examples/PlotAutoRange.py
./pyqtgraph/examples/PlotSpeedTest.py
./pyqtgraph/examples/PlotWidget.py
./pyqtgraph/examples/Plotting.py
./pyqtgraph/examples/ProgressDialog.py
./pyqtgraph/examples/ROIExamples.py
./pyqtgraph/examples/ROItypes.py
./pyqtgraph/examples/RemoteGraphicsView.py
./pyqtgraph/examples/RemoteSpeedTest.py
./pyqtgraph/examples/RunExampleApp.py
./pyqtgraph/examples/ScaleBar.py
./pyqtgraph/examples/ScatterPlot.py
./pyqtgraph/examples/ScatterPlotSpeedTest.py
./pyqtgraph/examples/ScatterPlotWidget.py
./pyqtgraph/examples/SimplePlot.py
./pyqtgraph/examples/SpinBox.py
./pyqtgraph/examples/Symbols.py
./pyqtgraph/examples/TableWidget.py
./pyqtgraph/examples/TreeWidget.py
./pyqtgraph/examples/VideoSpeedTest.py
./pyqtgraph/examples/VideoTemplate.ui
./pyqtgraph/examples/VideoTemplate_generic.py
./pyqtgraph/examples/ViewBox.py
./pyqtgraph/examples/ViewBoxFeatures.py
./pyqtgraph/examples/ViewLimits.py
./pyqtgraph/examples/__init__.py
./pyqtgraph/examples/__main__.py
./pyqtgraph/examples/_buildParamTypes.py
./pyqtgraph/examples/_paramtreecfg.py
./pyqtgraph/examples/beeswarm.py
./pyqtgraph/exceptionHandling.py
./pyqtgraph/exporters
./pyqtgraph/flowchart
./pyqtgraph/frozenSupport.py
./pyqtgraph/functions.py
./pyqtgraph/functions_numba.py
./pyqtgraph/functions_qimage.py
./pyqtgraph/graphicsItems
./pyqtgraph/icons
./pyqtgraph/imageview
./pyqtgraph/jupyter
./pyqtgraph/multiprocess
./pyqtgraph/opengl
./pyqtgraph/parametertree
./pyqtgraph/reload.py
./pyqtgraph/units.py
./pyqtgraph/util
./pyqtgraph/widgets
./pytest.ini
./setup.py
./test.py
./tests
./tools
./tools/generateChangelog.py
./tools/pg-release.py
./tools/py2exe.bat
./tools/py2exeSetupWindows.py
./tools/pyuic5
./tools/rebuildPtreeRst.py
./tools/rebuildUi.py
./tools/release_instructions.md
./tools/setupHelpers.py
./tools/shell.py
./tox.ini
```
Turn 1at 86 s288 tokens out5,093 prompt tokens
The user is reporting a `TypeError` when using a NumPy record array as data to plot in `pyqtgraph`. The error occurs at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`, line 719. The error message is `TypeError: Cannot compare structured or void to non-void arrays.`. This happens because `data` is a NumPy record array, and checking if `'x'` is in it via `in` operator might be causing issues with NumPy structured arrays if not handled correctly. Let's reproduce this first.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport pyqtgraph as pg\nimport numpy as np\ntry:\n data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])\n # We only need to check the part that fails, which is the initialization of PlotDataItem\n # PlotDataItem is likely used inside pg.plot, but let's be direct.\n from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem\n item = PlotDataItem(data_array)\n print(\"Successfully created PlotDataItem\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 431 characters
{
"status": "ok",
"stdout": "",
"stderr": "Traceback (most recent call last):\n File \"<stdin>\", line 8, in <module>\n File \"/workspace/pyqtgraph/graphicsItems/PlotDataItem.py\", line 622, in __init__\n self.setData(*args, **kwargs)\n File \"/workspace/pyqtgraph/graphicsItems/PlotDataItem.py\", line 1164, in setData\n if 'x' in data:\nTypeError: Cannot compare structured or void to non-void arrays.\n",
"exit_code": 0
}Turn 2at 94 s132 tokens out5,538 prompt tokens
The reproduction confirms the issue. The error happens at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`. Now let's examine the code in `pyqtgraph/graphicsItems/PlotDataItem.py`. The line number in reproduction is 1164, but in the problem statement it was 719. This is likely due to version differences.
TOOL CALL · read_file
{
"end_line": 1180,
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"start_line": 1150
}Result of read_file 1,341 characters
{
"status": "ok",
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"content": " profiler = debug.Profiler()\n y = None\n x = None\n if len(args) == 1:\n data = args[0]\n dt = dataType(data)\n if dt == 'empty':\n pass\n elif dt == 'listOfValues':\n y = np.array(data)\n elif dt == 'Nx2array':\n x = data[:, 0]\n y = data[:, 1]\n elif dt == 'recarray' or dt == 'dictOfLists':\n if 'x' in data:\n x = np.array(data['x'])\n if 'y' in data:\n y = np.array(data['y'])\n elif dt == 'listOfDicts':\n if 'x' in data[0]:\n x = np.array([d.get('x',None) for d in data])\n if 'y' in data[0]:\n y = np.array([d.get('y',None) for d in data])\n for k in [\n 'data', 'symbolSize', 'symbolPen', 'symbolBrush', 'symbolShape'\n ]:\n if k in data[0]:\n kwargs[k] = [d.get(k) for d in data]\n else:\n raise TypeError('Invalid data type %s' % type(data))\n",
"start_line": 1150,
"end_line": 1180,
"total_lines": 1839,
"is_truncated": false
}Turn 3at 111 s318 tokens out6,083 prompt tokens
Wait, the code is:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
If `dt == 'recarray'`, `data` is a NumPy record array. For a NumPy structured array/record array, `'x' in data` checks if 'x' is in the data itself (which might be interpreted as comparing the string 'x' with the record elements), not if 'x' is a field name.
To check if a field exists in a NumPy structured array, one should check `data.dtype.names`.
Let's verify this hypothesis.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport numpy as np\ndata_array = np.recarray((10,), dtype=[('x', float), ('y', float)])\ntry:\n print(f\"'x' in data_array: {'x' in data_array}\")\nexcept Exception as e:\n print(f\"Error: {e}\")\n\nprint(f\"data_array.dtype.names: {data_array.dtype.names}\")\nprint(f\"'x' in data_array.dtype.names: {'x' in data_array.dtype.names}\")\nPY\n"
}Result of run_command 195 characters
{
"status": "ok",
"stdout": "Error: Cannot compare structured or void to non-void arrays.\ndata_array.dtype.names: ('x', 'y')\n'x' in data_array.dtype.names: True\n",
"stderr": "",
"exit_code": 0
}Turn 4at 120 s109 tokens out6,484 prompt tokens
Okay, so the issue is indeed using `in` on the record array itself instead of its field names. But wait, the code also handles `dt == 'dictOfLists'`. For a dict, `'x' in data` is correct. So we need to distinguish between `recarray` and `dictOfLists`. Let's see how `dataType(data)` is implemented.
Turn 5at 120 s
<|tool_call>call:grep -rn "def dataType" pyqtgraph/graphicsItems/PlotDataItem.py<|"|><tool_call|>
System instructions 286 characters
Your previous response reached the token limit before the tool call finished closing (<|tool_call|> was cut off). Do NOT repeat your prior reasoning in thought—emit your next tool call immediately, and if calling edit_file or write_file, split the change into smaller incremental edits.
Turn 6at 124 s47 tokens out6,174 prompt tokens
TOOL CALL · read_file
{
"end_line": 1150,
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"start_line": 1100
}Result of read_file 1,882 characters
{
"status": "ok",
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"content": " set, unpredictable behavior will occur. The data might not be plotted, or there\n might be significant performance impact.\n \n In the default ``connect='auto'`` mode, PlotDataItem will apply this setting\n automatically.\n\n Parameters\n ----------\n skipFiniteCheck : bool\n Skip the :obj:`numpy.isfinite` check for the input arrays.\n\n See Also\n --------\n numpy.isfinite\n NumPy function used to identify if there are non-finite values in the `x`\n and `y` data.\n :func:`~pyqtgraph.arrayToQPath`\n Function to create :class:`QPainterPath` which is rendered on the screen\n from numpy arrays.\n \"\"\"\n self.opts['skipFiniteCheck'] = skipFiniteCheck\n\n def setData(\n self,\n *args,\n **kwargs\n ):\n \"\"\"\n Clear any data displayed by this item and display new data.\n\n Parameters\n ----------\n *args : tuple\n See :class:`PlotDataItem` description for supported arguments.\n **kwargs : dict\n See :class:`PlotDataItem` description for supported arguments.\n\n Raises\n ------\n TypeError\n Raised when an invalid type was passed in for `x` or `y` data.\n\n See Also\n --------\n :class:`PlotDataItem`\n The arguments accepted by :meth:`setData` are the same used during \n initialization, and are listed in the opening section.\n :func:`~pyqtgraph.arrayToQPath`\n Explains the constructions of the draw paths.\n \"\"\"\n profiler = debug.Profiler()",
"start_line": 1100,
"end_line": 1150,
"total_lines": 1839,
"is_truncated": false
}Turn 7at 132 s66 tokens out6,716 prompt tokens
Okay, I need to find where `dataType` is defined. I'll search for it in `pyqtgraph/graphicsItems/PlotDataItem.py`.
TOOL CALL · run_command
{
"command": "grep -n \"def dataType\" pyqtgraph/graphicsItems/PlotDataItem.py"
}Result of run_command 92 characters
{
"status": "ok",
"stdout": "1799:def dataType(obj) -> str:\n",
"stderr": "",
"exit_code": 0
}Turn 8at 134 s56 tokens out6,835 prompt tokens
Let's read the `dataType` function implementation.
TOOL CALL · read_file
{
"end_line": 1839,
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"start_line": 1799
}Result of read_file 1,510 characters
{
"status": "ok",
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"content": "def dataType(obj) -> str:\n type_: str\n if hasattr(obj, '__len__') and len(obj) == 0:\n type_ = 'empty'\n elif isinstance(obj, dict):\n type_ = 'dictOfLists'\n elif np.iterable(obj):\n first = obj[0]\n if isinstance(obj, np.ndarray):\n if obj.ndim == 1:\n type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'\n elif obj.ndim == 2 and obj.dtype.names is None and obj.shape[1] == 2:\n type_ = 'Nx2array'\n else:\n raise ValueError(\n f'array shape must be (N,) or (N,2); got {str(obj.shape)} instead'\n )\n elif isinstance(first, dict):\n type_ = 'listOfDicts'\n else:\n type_ = 'listOfValues'\n else:\n raise ValueError(\"Cannot identify data-structure.\")\n return type_\n\n\ndef isSequence(obj):\n warnings.warn(\n (\n \"isSequence is deprecated and will be removed in a future version of\"\n \"pyqtgraph, use np.iterable(obj) instead.\"\n ), DeprecationWarning, stacklevel=2\n )\n return (\n hasattr(obj, '__iter__') or\n isinstance(obj, np.ndarray) or\n (\n hasattr(obj, 'implements') and\n obj.implements('MetaArray')\n )\n )",
"start_line": 1799,
"end_line": 1839,
"total_lines": 1839,
"is_truncated": false
}Turn 9at 208 s1,399 tokens out7,356 prompt tokens
The `dataType` function identifies a `np.recarray` as `'recarray'` if `obj.dtype.names` is not None.
```python
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Then in `setData`:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
The error `TypeError: Cannot compare structured or void to non-void arrays.` happens at `if 'x' in data:`.
As I found in my repro script:
```python
import numpy as np
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
try:
print(f"'x' in data_array: {'x' in data_array}")
except Exception as e:
print(f"Error: {e}")
print(f"data_array.dtype.names: {data_array.dtype.names}")
print(f"'x' in data_array.dtype.names: {'x' in data_array.dtype.names}")
```
Output:
```
Error: Cannot compare structured or void to non-void arrays.
data_array.dtype.names: ('x', 'y')
'x' in data_array.dtype.names: True
```
So for NumPy structured/record arrays, you should use `data.dtype.names` to check for field existence, not `'x' in data`.
Wait, if `dt == 'dictOfLists'`, `data` is a dict, so `'x' in data` works.
If `dt == 'recarray'`, `data` is a numpy array, so `'x' in data` fails in newer NumPy versions (like 2.0.2 mentioned in the issue).
I should change the check to be compatible with both dicts and recarrays.
If `dt == 'recarray'`, I should check `data.dtype.names`.
Actually, I can check if it's a numpy array.
But `dt` already tells me if it's a `recarray` or `dictOfLists`.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `if 'x' in data` is correct.
If `dt == 'recarray'`, `data` is a numpy structured array. `if 'x' in data` is what fails.
I should check the fields of the recarray.
Correct way for recarray: `if 'x' in data.dtype.names:` (if names is not None).
Let's refine the logic.
If `dt == 'recarray'`:
if data.dtype.names and 'x' in data.dtype.names:
x = np.array(data['x'])
# ... same for y
Else if `dt == 'dictOfLists'`:
if 'x' in data:
x = np.array(data['x'])
# ... same for y
Wait, `dataType` returns `'recarray'` ONLY if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `data.dtype.names` is guaranteed to be not None.
So for `dt == 'recarray'`, I can use `'x' in data.dtype.names`.
But I want to avoid duplicating the logic.
Maybe:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
# For recarray, check dtype.names; for dict, check keys.
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `'x' in data` works.
Let's double check how `np.recarray` accessed fields. `data['x']` works.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `names` is the dict. `names and 'x' in names` works.
Let's verify this with a small script first.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport numpy as np\n# Case 1: recarray\ndata_rec = np.recarray((10,), dtype=[('x', float), ('y', float)])\ndt_rec = 'recarray'\nnames_rec = data_rec.dtype.names if dt_rec == 'recarray' else data_rec\nprint(f\"recarray 'x' in names: {'x' in names_rec}\")\nprint(f\"recarray data['x']: {data_rec['x'][:2]}\")\n\n# Case 2: dict\ndata_dict = {'x': [1, 2], 'y': [3, 4]}\ndt_dict = 'dictOfLists'\nnames_dict = data_dict.dtype.names if dt_dict == 'recarray' else data_dict\nprint(f\"dict 'x' in names: {'x' in names_dict}\")\nprint(f\"dict data['x']: {data_dict['x idea' if False else 'x'][:2]}\")\nPY\n"
}Result of run_command 193 characters
{
"status": "ok",
"stdout": "recarray 'x' in names: True\nrecarray data['x']: [4.70610241e-310 0.00000000e+000]\ndict 'x' in names: True\ndict data['x']: [1, 2]\n",
"stderr": "",
"exit_code": 0
}Turn 10at 254 s808 tokens out8,866 prompt tokens
The logic seems sound.
Now I need to apply it to `pyqtgraph/graphicsItems/PlotDataItem.py`.
Let's check the exact lines again.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
I'll replace:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
with:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, `names` for a dict will be the dict itself. If the dict is empty, `names` is falsy. So `names and 'x' in names` is safe.
Actually, `if 'x' in names:` is enough because for a dict it works, and for a tuple (which `dtype.names` is) it also works.
The only issue is if `names` is `None`.
`data.dtype.names` can be `None`. But `dataType` returns `'recarray'` only if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `names` will be a tuple.
If `dt == 'dictOfLists'`, `names` will be a dict.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Actually, I should probably handle the case where `data` is an empty dict, but `dataType` already handles empty:
```python
if hasattr(obj, '__len__') and len(obj) == 0:
type_ = 'empty'
```
So if `dt == 'dictOfLists'`, `data` is not empty.
Let's double check `dataType` again:
```python
elif isinstance(obj, dict):
type_ = 'dictOfLists'
```
Yes.
So the proposed change:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, there's one more thing. `PlotDataItem` is initialized with `setData`.
Is there anywhere else in the codebase where this pattern occurs?
The user mentioned `PlotDataItem` specifically, but `PlotDataItem` might be used by other things.
Let's search for `dt == 'recarray'` in the whole repository.
TOOL CALL · run_command
{
"command": "grep -rn \"dt == 'recarray'\" ."
}Result of run_command 166 characters
{
"status": "ok",
"stdout": "./pyqtgraph/graphicsItems/PlotDataItem.py:1163: elif dt == 'recarray' or dt == 'dictOfLists':\n",
"stderr": "",
"exit_code": 0
}Turn 11at 265 s196 tokens out9,747 prompt tokens
It seems it's only in `PlotDataItem.py`. Let's apply the fix.
TOOL CALL · edit_file
{
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"new_string": " elif dt == 'recarray' or dt == 'dictOfLists':\n names = data.dtype.names if dt == 'recarray' else data\n if 'x' in names:\n x = np.array(data['x'])\n if 'y' in names:\n y = np.array(data['y'])",
"old_string": " elif dt == 'recarray' or dt == 'dictOfLists':\n if 'x' in data:\n x = np.array(data['x'])\n if 'y' in data:\n y = np.array(data['y'])"
}Result of edit_file 769 characters
{
"status": "ok",
"filepath": "pyqtgraph/graphicsItems/PlotDataItem.py",
"occurrences": 1,
"strategy": "exact",
"diff": "--- a/pyqtgraph/graphicsItems/PlotDataItem.py\n+++ b/pyqtgraph/graphicsItems/PlotDataItem.py\n@@ -1161,9 +1161,10 @@\n x = data[:, 0]\n y = data[:, 1]\n elif dt == 'recarray' or dt == 'dictOfLists':\n- if 'x' in data:\n+ names = data.dtype.names if dt == 'recarray' else data\n+ if 'x' in names:\n x = np.array(data['x'])\n- if 'y' in data:\n+ if 'y' in names:\n y = np.array(data['y'])\n elif dt == 'listOfDicts':\n if 'x' in data[0]:\n",
"is_truncated": false
}Turn 12at 270 s133 tokens out10,201 prompt tokens
Now let's verify the fix with the reproduction script.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport pyqtgraph as pg\nimport numpy as np\ntry:\n data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])\n from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem\n item = PlotDataItem(data_array)\n print(\"Successfully created PlotDataItem\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 95 characters
{
"status": "ok",
"stdout": "Successfully created PlotDataItem\n",
"stderr": "",
"exit_code": 0
}Turn 13at 279 s141 tokens out10,378 prompt tokens
It works now. I should also check if it still works for `dictOfLists`.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport pyqtgraph as pg\nimport numpy as np\ntry:\n data_dict = {'x': np.arange(10), 'y': np.arange(10)}\n from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem\n item = PlotDataItem(data_dict)\n print(\"Successfully created PlotDataItem with dict\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 105 characters
{
"status": "ok",
"stdout": "Successfully created PlotDataItem with dict\n",
"stderr": "",
"exit_code": 0
}Turn 14at 290 s138 tokens out10,565 prompt tokens
And what about a recarray without 'x' or 'y'?
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport pyqtgraph as pg\nimport numpy as np\ntry:\n data_array = np.recarray((10,), dtype=[('a', float), ('b', float)])\n from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem\n item = PlotDataItem(data_array)\n print(\"Successfully created PlotDataItem with other fields\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 113 characters
{
"status": "ok",
"stdout": "Successfully created PlotDataItem with other fields\n",
"stderr": "",
"exit_code": 0
}Turn 15at 297 s139 tokens out10,750 prompt tokens
Now let's check the case where one of them is missing.
TOOL CALL · run_command
{
"command": "python3 - <<'PY'\nimport pyqtgraph as pg\nimport numpy as np\ntry:\n data_array = np.recarray((10,), dtype=[('x', float), ('z', float)])\n from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem\n item = PlotDataItem(data_array)\n print(\"Successfully created PlotDataItem with missing 'y'\")\nexcept Exception as e:\n import traceback\n traceback.print_exc()\nPY\n"
}Result of run_command 112 characters
{
"status": "ok",
"stdout": "Successfully created PlotDataItem with missing 'y'\n",
"stderr": "",
"exit_code": 0
}Turn 16at 333 s476 tokens out10,937 prompt tokens
Wait, if I provide a recarray with only 'x', it should still work (setting y to None or default).
One more thing: I should see if there are any other places where `data` is checked for keys that might be a numpy array.
I already checked for `dt == 'recarray'`, but maybe there are others.
Actually, the `dataType` function seems to be the central place where it decides how to treat `data`.
The other branches in `setData` are:
- `dt == 'empty'`
- `dt == 'listOfValues'` (data is a list or 1D array)
- `dt == 'Nx2array'` (data is a 2D array)
- `dt == 'listOfDicts'` (data is a list of dicts)
In `listOfDicts`:
```python
elif dt == 'listOfDicts':
if 'x' in data[0]:
x = np.array([d.get('x',None) for d in data])
if 'y' in data[0]:
y = np.array([d.get('y',None) for d in data])
```
Here `data[0]` is a dict, so `'x' in data[0]` is correct.
It looks like `recarray` was the only problematic case.
Wait, what if `data` is a structured array but NOT a `recarray`?
`np.array((10,), dtype=[('x', float), ('y', float)])`
In `dataType`:
```python
if isinstance(obj, np.ndarray):
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Yes, any structured array with `ndim == 1` and `dtype.names is not None` will be typed as `'recarray'`, regardless of whether it was created with `np.recarray` or `np.array(..., dtype=...)`.
So the fix covers both.
One final check on the diff.
TOOL CALL · run_command
{
"command": "git diff"
}Result of run_command 847 characters
{
"status": "ok",
"stdout": "diff --git a/pyqtgraph/graphicsItems/PlotDataItem.py b/pyqtgraph/graphicsItems/PlotDataItem.py\nindex 9d7c7f8..79be936 100644\n--- a/pyqtgraph/graphicsItems/PlotDataItem.py\n+++ b/pyqtgraph/graphicsItems/PlotDataItem.py\n@@ -1161,9 +1161,10 @@ class PlotDataItem(GraphicsObject):\n x = data[:, 0]\n y = data[:, 1]\n elif dt == 'recarray' or dt == 'dictOfLists':\n- if 'x' in data:\n+ names = data.dtype.names if dt == 'recarray' else data\n+ if 'x' in names:\n x = np.array(data['x'])\n- if 'y' in data:\n+ if 'y' in names:\n y = np.array(data['y'])\n elif dt == 'listOfDicts':\n if 'x' in data[0]:\n",
"stderr": "",
"exit_code": 0
}Turn 17at 337 s63 tokens out11,709 prompt tokens
The diff looks correct and minimal. I'll run a final check on if there are any tests that I should run. I'll search for tests related to `PlotDataItem`.
TOOL CALL · run_command
{
"command": "find tests -name \"*PlotDataItem*\""
}Result of run_command 102 characters
{
"status": "ok",
"stdout": "tests/graphicsItems/test_PlotDataItem.py\n",
"stderr": "",
"exit_code": 0
}Turn 18at 341 s58 tokens out11,823 prompt tokens
Let's run the tests in `tests/graphicsItems/test_PlotDataItem.py`.
TOOL CALL · run_command
{
"command": "pytest tests/graphicsItems/test_PlotDataItem.py -q --tb=short --no-header"
}Result of run_command 160 characters
{
"status": "ok",
"stdout": "......... [100%]\n9 passed in 0.27s\n",
"stderr": "",
"exit_code": 0
}Turn 19at 344 s14 tokens out11,941 prompt tokens
Everything looks good.
TOOL CALL · submit_patch
Result of submit_patch 55 characters
{
"status": "ok",
"patch_size": 770,
"files_changed": 1
}Turn 20at 351 s56 tokens out11,995 prompt tokens
Done.
Turn 21at 351 s
Fixed a `TypeError` when using a NumPy record array to plot data by updating the field existence check in `PlotDataItem.setData` to use `data.dtype.names` for record arrays instead of the `in` operator on the array itself.
Model calls (not matched to turns)
Generated tokens 288 tokens · stopped: STOP
The user is reporting a `TypeError` when using a NumPy record array as data to plot in `pyqtgraph`. The error occurs at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`, line 719. The error message is `TypeError: Cannot compare structured or void to non-void arrays.`. This happens because `data` is a NumPy record array, and checking if `'x'` is in it via `in` operator might be causing issues with NumPy structured arrays if not handled correctly. Let's reproduce this first.
<|channel>thought
The user is reporting a `TypeError` when using a NumPy record array as data to plot in `pyqtgraph`.
The error occurs at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`, line 719.
The error message is `TypeError: Cannot compare structured or void to non-void arrays.`.
This happens because `data` is a NumPy record array, and checking if `'x'` is in it via `in` operator might be causing issues with NumPy structured arrays if not handled correctly.
Let's reproduce this first.<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import pyqtgraph as pg
import numpy as np
try:
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
# We only need to check the part that fails, which is the initialization of PlotDataItem
# PlotDataItem is likely used inside pg.plot, but let's be direct.
from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem
item = PlotDataItem(data_array)
print("Successfully created PlotDataItem")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 132 tokens · stopped: STOP
The reproduction confirms the issue. The error happens at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`. Now let's examine the code in `pyqtgraph/graphicsItems/PlotDataItem.py`. The line number in reproduction is 1164, but in the problem statement it was 719. This is likely due to version differences.
The reproduction confirms the issue. The error happens at `if 'x' in data:` in `pyqtgraph/graphicsItems/PlotDataItem.py`.
Now let's examine the code in `pyqtgraph/graphicsItems/PlotDataItem.py`.
The line number in reproduction is 1164, but in the problem statement it was 719. This is likely due to version differences.
<channel|><|tool_call>call:read_file{filepath:<|"|>pyqtgraph/graphicsItems/PlotDataItem.py<|"|>,start_line:1150,end_line:1180}<tool_call|><|tool_response>
Generated tokens 318 tokens · stopped: STOP
Wait, the code is:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
If `dt == 'recarray'`, `data` is a NumPy record array. For a NumPy structured array/record array, `'x' in data` checks if 'x' is in the data itself (which might be interpreted as comparing the string 'x' with the record elements), not if 'x' is a field name.
To check if a field exists in a NumPy structured array, one should check `data.dtype.names`.
Let's verify this hypothesis.
Wait, the code is:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
If `dt == 'recarray'`, `data` is a NumPy record array. For a NumPy structured array/record array, `'x' in data` checks if 'x' is in the data itself (which might be interpreted as comparing the string 'x' with the record elements), not if 'x' is a field name.
To check if a field exists in a NumPy structured array, one should check `data.dtype.names`.
Let's verify this hypothesis.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import numpy as np
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
try:
print(f"'x' in data_array: {'x' in data_array}")
except Exception as e:
print(f"Error: {e}")
print(f"data_array.dtype.names: {data_array.dtype.names}")
print(f"'x' in data_array.dtype.names: {'x' in data_array.dtype.names}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 109 tokens · stopped: STOP
Okay, so the issue is indeed using `in` on the record array itself instead of its field names. But wait, the code also handles `dt == 'dictOfLists'`. For a dict, `'x' in data` is correct. So we need to distinguish between `recarray` and `dictOfLists`. Let's see how `dataType(data)` is implemented.
Okay, so the issue is indeed using `in` on the record array itself instead of its field names.
But wait, the code also handles `dt == 'dictOfLists'`. For a dict, `'x' in data` is correct.
So we need to distinguish between `recarray` and `dictOfLists`.
Let's see how `dataType(data)` is implemented.
<channel|><|tool_call>call:grep -rn "def dataType" pyqtgraph/graphicsItems/PlotDataItem.py<|"|><tool_call|><|tool_response>
Generated tokens 47 tokens · stopped: STOP
<|channel>thought
<channel|><|tool_call>call:read_file{end_line:1150,filepath:<|"|>pyqtgraph/graphicsItems/PlotDataItem.py<|"|>,start_line:1100}<tool_call|><|tool_response>
Generated tokens 66 tokens · stopped: STOP
Okay, I need to find where `dataType` is defined. I'll search for it in `pyqtgraph/graphicsItems/PlotDataItem.py`.
Okay, I need to find where `dataType` is defined. I'll search for it in `pyqtgraph/graphicsItems/PlotDataItem.py`.<channel|><|tool_call>call:run_command{command:<|"|>grep -n "def dataType" pyqtgraph/graphicsItems/PlotDataItem.py<|"|>}<tool_call|><|tool_response>
Generated tokens 56 tokens · stopped: STOP
Let's read the `dataType` function implementation.
Let's read the `dataType` function implementation.
<channel|><|tool_call>call:read_file{end_line:1839,filepath:<|"|>pyqtgraph/graphicsItems/PlotDataItem.py<|"|>,start_line:1799}<tool_call|><|tool_response>
Generated tokens 1,399 tokens · stopped: STOP
The `dataType` function identifies a `np.recarray` as `'recarray'` if `obj.dtype.names` is not None.
```python
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Then in `setData`:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
The error `TypeError: Cannot compare structured or void to non-void arrays.` happens at `if 'x' in data:`.
As I found in my repro script:
```python
import numpy as np
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
try:
print(f"'x' in data_array: {'x' in data_array}")
except Exception as e:
print(f"Error: {e}")
print(f"data_array.dtype.names: {data_array.dtype.names}")
print(f"'x' in data_array.dtype.names: {'x' in data_array.dtype.names}")
```
Output:
```
Error: Cannot compare structured or void to non-void arrays.
data_array.dtype.names: ('x', 'y')
'x' in data_array.dtype.names: True
```
So for NumPy structured/record arrays, you should use `data.dtype.names` to check for field existence, not `'x' in data`.
Wait, if `dt == 'dictOfLists'`, `data` is a dict, so `'x' in data` works.
If `dt == 'recarray'`, `data` is a numpy array, so `'x' in data` fails in newer NumPy versions (like 2.0.2 mentioned in the issue).
I should change the check to be compatible with both dicts and recarrays.
If `dt == 'recarray'`, I should check `data.dtype.names`.
Actually, I can check if it's a numpy array.
But `dt` already tells me if it's a `recarray` or `dictOfLists`.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `if 'x' in data` is correct.
If `dt == 'recarray'`, `data` is a numpy structured array. `if 'x' in data` is what fails.
I should check the fields of the recarray.
Correct way for recarray: `if 'x' in data.dtype.names:` (if names is not None).
Let's refine the logic.
If `dt == 'recarray'`:
if data.dtype.names and 'x' in data.dtype.names:
x = np.array(data['x'])
# ... same for y
Else if `dt == 'dictOfLists'`:
if 'x' in data:
x = np.array(data['x'])
# ... same for y
Wait, `dataType` returns `'recarray'` ONLY if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `data.dtype.names` is guaranteed to be not None.
So for `dt == 'recarray'`, I can use `'x' in data.dtype.names`.
But I want to avoid duplicating the logic.
Maybe:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
# For recarray, check dtype.names; for dict, check keys.
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `'x' in data` works.
Let's double check how `np.recarray` accessed fields. `data['x']` works.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `names` is the dict. `names and 'x' in names` works.
Let's verify this with a small script first.
The `dataType` function identifies a `np.recarray` as `'recarray'` if `obj.dtype.names` is not None.
```python
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Then in `setData`:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
The error `TypeError: Cannot compare structured or void to non-void arrays.` happens at `if 'x' in data:`.
As I found in my repro script:
```python
import numpy as np
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
try:
print(f"'x' in data_array: {'x' in data_array}")
except Exception as e:
print(f"Error: {e}")
print(f"data_array.dtype.names: {data_array.dtype.names}")
print(f"'x' in data_array.dtype.names: {'x' in data_array.dtype.names}")
```
Output:
```
Error: Cannot compare structured or void to non-void arrays.
data_array.dtype.names: ('x', 'y')
'x' in data_array.dtype.names: True
```
So for NumPy structured/record arrays, you should use `data.dtype.names` to check for field existence, not `'x' in data`.
Wait, if `dt == 'dictOfLists'`, `data` is a dict, so `'x' in data` works.
If `dt == 'recarray'`, `data` is a numpy array, so `'x' in data` fails in newer NumPy versions (like 2.0.2 mentioned in the issue).
I should change the check to be compatible with both dicts and recarrays.
If `dt == 'recarray'`, I should check `data.dtype.names`.
Actually, I can check if it's a numpy array.
But `dt` already tells me if it's a `recarray` or `dictOfLists`.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `if 'x' in data` is correct.
If `dt == 'recarray'`, `data` is a numpy structured array. `if 'x' in data` is what fails.
I should check the fields of the recarray.
Correct way for recarray: `if 'x' in data.dtype.names:` (if names is not None).
Let's refine the logic.
If `dt == 'recarray'`:
if data.dtype.names and 'x' in data.dtype.names:
x = np.array(data['x'])
# ... same for y
Else if `dt == 'dictOfLists'`:
if 'x' in data:
x = np.array(data['x'])
# ... same for y
Wait, `dataType` returns `'recarray'` ONLY if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `data.dtype.names` is guaranteed to be not None.
So for `dt == 'recarray'`, I can use `'x' in data.dtype.names`.
But I want to avoid duplicating the logic.
Maybe:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
# For recarray, check dtype.names; for dict, check keys.
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `data` is a dict. `'x' in data` works.
Let's double check how `np.recarray` accessed fields. `data['x']` works.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, if `dt == 'dictOfLists'`, `names` is the dict. `names and 'x' in names` works.
Let's verify this with a small script first.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import numpy as np
# Case 1: recarray
data_rec = np.recarray((10,), dtype=[('x', float), ('y', float)])
dt_rec = 'recarray'
names_rec = data_rec.dtype.names if dt_rec == 'recarray' else data_rec
print(f"recarray 'x' in names: {'x' in names_rec}")
print(f"recarray data['x']: {data_rec['x'][:2]}")
# Case 2: dict
data_dict = {'x': [1, 2], 'y': [3, 4]}
dt_dict = 'dictOfLists'
names_dict = data_dict.dtype.names if dt_dict == 'recarray' else data_dict
print(f"dict 'x' in names: {'x' in names_dict}")
print(f"dict data['x']: {data_dict['x idea' if False else 'x'][:2]}")
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 808 tokens · stopped: STOP
The logic seems sound.
Now I need to apply it to `pyqtgraph/graphicsItems/PlotDataItem.py`.
Let's check the exact lines again.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
I'll replace:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
with:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, `names` for a dict will be the dict itself. If the dict is empty, `names` is falsy. So `names and 'x' in names` is safe.
Actually, `if 'x' in names:` is enough because for a dict it works, and for a tuple (which `dtype.names` is) it also works.
The only issue is if `names` is `None`.
`data.dtype.names` can be `None`. But `dataType` returns `'recarray'` only if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `names` will be a tuple.
If `dt == 'dictOfLists'`, `names` will be a dict.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Actually, I should probably handle the case where `data` is an empty dict, but `dataType` already handles empty:
```python
if hasattr(obj, '__len__') and len(obj) == 0:
type_ = 'empty'
```
So if `dt == 'dictOfLists'`, `data` is not empty.
Let's double check `dataType` again:
```python
elif isinstance(obj, dict):
type_ = 'dictOfLists'
```
Yes.
So the proposed change:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, there's one more thing. `PlotDataItem` is initialized with `setData`.
Is there anywhere else in the codebase where this pattern occurs?
The user mentioned `PlotDataItem` specifically, but `PlotDataItem` might be used by other things.
Let's search for `dt == 'recarray'` in the whole repository.
The logic seems sound.
Now I need to apply it to `pyqtgraph/graphicsItems/PlotDataItem.py`.
Let's check the exact lines again.
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
I'll replace:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])
```
with:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if names and 'x' in names:
x = np.array(data['x'])
if names and 'y' in names:
y = np.array(data['y'])
```
Wait, `names` for a dict will be the dict itself. If the dict is empty, `names` is falsy. So `names and 'x' in names` is safe.
Actually, `if 'x' in names:` is enough because for a dict it works, and for a tuple (which `dtype.names` is) it also works.
The only issue is if `names` is `None`.
`data.dtype.names` can be `None`. But `dataType` returns `'recarray'` only if `obj.dtype.names is not None`.
So if `dt == 'recarray'`, `names` will be a tuple.
If `dt == 'dictOfLists'`, `names` will be a dict.
So:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Actually, I should probably handle the case where `data` is an empty dict, but `dataType` already handles empty:
```python
if hasattr(obj, '__len__') and len(obj) == 0:
type_ = 'empty'
```
So if `dt == 'dictOfLists'`, `data` is not empty.
Let's double check `dataType` again:
```python
elif isinstance(obj, dict):
type_ = 'dictOfLists'
```
Yes.
So the proposed change:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])
```
Wait, there's one more thing. `PlotDataItem` is initialized with `setData`.
Is there anywhere else in the codebase where this pattern occurs?
The user mentioned `PlotDataItem` specifically, but `PlotDataItem` might be used by other things.
Let's search for `dt == 'recarray'` in the whole repository.
<channel|><|tool_call>call:run_command{command:<|"|>grep -rn "dt == 'recarray'" .<|"|>}<tool_call|><|tool_response>
Generated tokens 196 tokens · stopped: STOP
It seems it's only in `PlotDataItem.py`. Let's apply the fix.
It seems it's only in `PlotDataItem.py`.
Let's apply the fix.
<channel|><|tool_call>call:edit_file{filepath:<|"|>pyqtgraph/graphicsItems/PlotDataItem.py<|"|>,new_string:<|"|> elif dt == 'recarray' or dt == 'dictOfLists':
names = data.dtype.names if dt == 'recarray' else data
if 'x' in names:
x = np.array(data['x'])
if 'y' in names:
y = np.array(data['y'])<|"|>,old_string:<|"|> elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
x = np.array(data['x'])
if 'y' in data:
y = np.array(data['y'])<|"|>}<tool_call|><|tool_response>
Generated tokens 133 tokens · stopped: STOP
Now let's verify the fix with the reproduction script.
Now let's verify the fix with the reproduction script.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import pyqtgraph as pg
import numpy as np
try:
data_array = np.recarray((10,), dtype=[('x', float), ('y', float)])
from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem
item = PlotDataItem(data_array)
print("Successfully created PlotDataItem")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 141 tokens · stopped: STOP
It works now. I should also check if it still works for `dictOfLists`.
It works now. I should also check if it still works for `dictOfLists`.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import pyqtgraph as pg
import numpy as np
try:
data_dict = {'x': np.arange(10), 'y': np.arange(10)}
from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem
item = PlotDataItem(data_dict)
print("Successfully created PlotDataItem with dict")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 138 tokens · stopped: STOP
And what about a recarray without 'x' or 'y'?
And what about a recarray without 'x' or 'y'?
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import pyqtgraph as pg
import numpy as np
try:
data_array = np.recarray((10,), dtype=[('a', float), ('b', float)])
from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem
item = PlotDataItem(data_array)
print("Successfully created PlotDataItem with other fields")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 139 tokens · stopped: STOP
Now let's check the case where one of them is missing.
Now let's check the case where one of them is missing.
<channel|><|tool_call>call:run_command{command:<|"|>python3 - <<'PY'
import pyqtgraph as pg
import numpy as np
try:
data_array = np.recarray((10,), dtype=[('x', float), ('z', float)])
from pyqtgraph.graphicsItems.PlotDataItem import PlotDataItem
item = PlotDataItem(data_array)
print("Successfully created PlotDataItem with missing 'y'")
except Exception as e:
import traceback
traceback.print_exc()
PY
<|"|>}<tool_call|><|tool_response>
Generated tokens 476 tokens · stopped: STOP
Wait, if I provide a recarray with only 'x', it should still work (setting y to None or default).
One more thing: I should see if there are any other places where `data` is checked for keys that might be a numpy array.
I already checked for `dt == 'recarray'`, but maybe there are others.
Actually, the `dataType` function seems to be the central place where it decides how to treat `data`.
The other branches in `setData` are:
- `dt == 'empty'`
- `dt == 'listOfValues'` (data is a list or 1D array)
- `dt == 'Nx2array'` (data is a 2D array)
- `dt == 'listOfDicts'` (data is a list of dicts)
In `listOfDicts`:
```python
elif dt == 'listOfDicts':
if 'x' in data[0]:
x = np.array([d.get('x',None) for d in data])
if 'y' in data[0]:
y = np.array([d.get('y',None) for d in data])
```
Here `data[0]` is a dict, so `'x' in data[0]` is correct.
It looks like `recarray` was the only problematic case.
Wait, what if `data` is a structured array but NOT a `recarray`?
`np.array((10,), dtype=[('x', float), ('y', float)])`
In `dataType`:
```python
if isinstance(obj, np.ndarray):
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Yes, any structured array with `ndim == 1` and `dtype.names is not None` will be typed as `'recarray'`, regardless of whether it was created with `np.recarray` or `np.array(..., dtype=...)`.
So the fix covers both.
One final check on the diff.
Wait, if I provide a recarray with only 'x', it should still work (setting y to None or default).
One more thing: I should see if there are any other places where `data` is checked for keys that might be a numpy array.
I already checked for `dt == 'recarray'`, but maybe there are others.
Actually, the `dataType` function seems to be the central place where it decides how to treat `data`.
The other branches in `setData` are:
- `dt == 'empty'`
- `dt == 'listOfValues'` (data is a list or 1D array)
- `dt == 'Nx2array'` (data is a 2D array)
- `dt == 'listOfDicts'` (data is a list of dicts)
In `listOfDicts`:
```python
elif dt == 'listOfDicts':
if 'x' in data[0]:
x = np.array([d.get('x',None) for d in data])
if 'y' in data[0]:
y = np.array([d.get('y',None) for d in data])
```
Here `data[0]` is a dict, so `'x' in data[0]` is correct.
It looks like `recarray` was the only problematic case.
Wait, what if `data` is a structured array but NOT a `recarray`?
`np.array((10,), dtype=[('x', float), ('y', float)])`
In `dataType`:
```python
if isinstance(obj, np.ndarray):
if obj.ndim == 1:
type_ = 'listOfValues' if obj.dtype.names is None else 'recarray'
```
Yes, any structured array with `ndim == 1` and `dtype.names is not None` will be typed as `'recarray'`, regardless of whether it was created with `np.recarray` or `np.array(..., dtype=...)`.
So the fix covers both.
One final check on the diff.
<channel|><|tool_call>call:run_command{command:<|"|>git diff<|"|>}<tool_call|><|tool_response>
Generated tokens 63 tokens · stopped: STOP
The diff looks correct and minimal. I'll run a final check on if there are any tests that I should run. I'll search for tests related to `PlotDataItem`.
The diff looks correct and minimal.
I'll run a final check on if there are any tests that I should run.
I'll search for tests related to `PlotDataItem`.
<channel|><|tool_call>call:run_command{command:<|"|>find tests -name "*PlotDataItem*"<|"|>}<tool_call|><|tool_response>
Generated tokens 58 tokens · stopped: STOP
Let's run the tests in `tests/graphicsItems/test_PlotDataItem.py`.
Let's run the tests in `tests/graphicsItems/test_PlotDataItem.py`.
<channel|><|tool_call>call:run_command{command:<|"|>pytest tests/graphicsItems/test_PlotDataItem.py -q --tb=short --no-header<|"|>}<tool_call|><|tool_response>
Generated tokens 14 tokens · stopped: STOP
Everything looks good.
Everything looks good.<channel|><|tool_call>call:submit_patch{}<tool_call|><|tool_response>
Patch, tests and logs
Final code change Included
diff --git a/pyqtgraph/graphicsItems/PlotDataItem.py b/pyqtgraph/graphicsItems/PlotDataItem.py
index 9d7c7f8..79be936 100644
--- a/pyqtgraph/graphicsItems/PlotDataItem.py
+++ b/pyqtgraph/graphicsItems/PlotDataItem.py
@@ -1161,9 +1161,10 @@ class PlotDataItem(GraphicsObject):
x = data[:, 0]
y = data[:, 1]
elif dt == 'recarray' or dt == 'dictOfLists':
- if 'x' in data:
+ names = data.dtype.names if dt == 'recarray' else data
+ if 'x' in names:
x = np.array(data['x'])
- if 'y' in data:
+ if 'y' in names:
y = np.array(data['y'])
elif dt == 'listOfDicts':
if 'x' in data[0]:
Test output Included
============================= test session starts ============================== collected 9 items tests/graphicsItems/test_PlotDataItem.py ......... [100%] ==================================== PASSES ==================================== - generated xml file: /tmp/rebench-grade-b830c4e6f049444cb51490dff434b039.xml -- =========================== short test summary info ============================ PASSED tests/graphicsItems/test_PlotDataItem.py::test_bool PASSED tests/graphicsItems/test_PlotDataItem.py::test_bound_formats PASSED tests/graphicsItems/test_PlotDataItem.py::test_fft PASSED tests/graphicsItems/test_PlotDataItem.py::test_setData PASSED tests/graphicsItems/test_PlotDataItem.py::test_nonfinite PASSED tests/graphicsItems/test_PlotDataItem.py::test_opts PASSED tests/graphicsItems/test_PlotDataItem.py::test_clear PASSED tests/graphicsItems/test_PlotDataItem.py::test_clear_in_step_mode PASSED tests/graphicsItems/test_PlotDataItem.py::test_clipping ============================== 9 passed in 0.27s ===============================
Test errors Included
Test report (JUnit) Included
<?xml version="1.0" encoding="utf-8"?><testsuites name="pytest tests"><testsuite name="pytest" errors="0" failures="0" skipped="0" tests="9" time="0.275" timestamp="2026-11-14T03:59:38.793794+00:00" hostname="2b7c94ab6622"><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_bool" time="0.006" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_bound_formats" time="0.003" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_fft" time="0.004" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_setData" time="0.001" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_nonfinite" time="0.001" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_opts" time="0.001" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_clear" time="0.001" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_clear_in_step_mode" time="0.174" /><testcase classname="tests.graphicsItems.test_PlotDataItem" name="test_clipping" time="0.008" /></testsuite></testsuites>
Agent log Included
[ 0.0s] 📋 System Prompt: You are a principal Python software engineer resolving a repository issue in `/workspace`.
[ 0.0s] 🎯 Task Prompt: You are evaluating a software engineering task for repository pyqtgraph/pyqtgraph.
[ 19.4s] 💭 (492 chars) "The user is reporting a `TypeError` when using a NumPy record array as data to plot in
`pyqtgraph`.
The error occurs at ..."
[ 19.4s] 🔧 run_command (14 lines) python3 - <<'PY'
[ 20.0s] 🔧
[ 27.2s] 💭 (320 chars) "The reproduction confirms the issue. The error happens at `if 'x' in data:` in
`pyqtgraph/graphicsItems/PlotDataItem.py`..."
[ 27.2s] 📖 read_file (pyqtgraph/graphicsItems/PlotDataItem.py)
[ 27.3s] ✓ {'status': 'ok', 'filepath': 'pyqtgraph/graphicsItems/PlotDataItem.py', 'content': " profiler =
debug.Profiler()\…
[ 44.6s] 💭 (626 chars) "Wait, the code is:
```python
elif dt == 'recarray' or dt == 'dictOfLists':
if 'x' in data:
..."
[ 44.6s] 🔧 run_command (11 lines) python3 - <<'PY'
[ 44.8s] → Error: Cannot compare structured or void to non-void arrays.
[ 54.0s] 💭 (300 chars) "Okay, so the issue is indeed using `in` on the record array itself instead of its field
names.
But wait, the code also ..."
[ 54.0s] ✅ Agent finished: <|tool_call>call:grep -rn "def dataType"
pyqtgraph/graphicsItems/PlotDataItem.py<|"|><tool_call|>
[ 54.0s] 🎯 Task Prompt: Your previous response reached the token limit before the tool call finished closing
(<|tool_call|> was cut off). Do NOT...
[ 57.4s] 📖 read_file (pyqtgraph/graphicsItems/PlotDataItem.py)
[ 57.5s] ✓ {'status': 'ok', 'filepath': 'pyqtgraph/graphicsItems/PlotDataItem.py', 'content': ' set,
unpredictable behavior …
[ 65.5s] 💭 (114 chars) "Okay, I need to find where `dataType` is defined. I'll search for it in
`pyqtgraph/graphicsItems/PlotDataItem.py`."
[ 65.5s] 🔧 run_command grep -n "def dataType" pyqtgraph/graphicsItems/PlotDataItem.py
[ 65.6s] → 1799:def dataType(obj) -> str:
[ 67.9s] 💭 (50 chars) "Let's read the `dataType` function implementation."
[ 67.9s] 📖 read_file (pyqtgraph/graphicsItems/PlotDataItem.py)
[ 67.9s] ✓ {'status': 'ok', 'filepath': 'pyqtgraph/graphicsItems/PlotDataItem.py', 'content': 'def dataType(obj) ->
str:\n type_…
[ 141.3s] 💭 (3693 chars) "The `dataType` function identifies a `np.recarray` as `'recarray'` if `obj.dtype.names` is
not None.
```python
..."
[ 141.3s] 🔧 run_command (16 lines) python3 - <<'PY'
[ 141.5s] → recarray 'x' in names: True
[ 187.7s] 💭 (2712 chars) "The logic seems sound.
Now I need to apply it to `pyqtgraph/graphicsItems/PlotDataItem.py`.
Let's check the exact line..."
[ 187.7s] 🔧 run_command grep -rn "dt == 'recarray'" .
[ 187.7s] → ./pyqtgraph/graphicsItems/PlotDataItem.py:1163: elif dt == 'recarray' or dt == 'dictOfLists':
[ 198.9s] 💭 (62 chars) "It seems it's only in `PlotDataItem.py`.
Let's apply the fix."
[ 198.9s] ✏️ edit_file (pyqtgraph/graphicsItems/PlotDataItem.py)
[ 199.1s] ✓ {'status': 'ok', 'filepath': 'pyqtgraph/graphicsItems/PlotDataItem.py', 'occurrences': 1, 'strategy':
'exact', 'diff': "…
[ 203.6s] 💭 (54 chars) "Now let's verify the fix with the reproduction script."
[ 203.6s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 203.9s] → Successfully created PlotDataItem
[ 212.9s] 💭 (70 chars) "It works now. I should also check if it still works for `dictOfLists`."
[ 212.9s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 213.2s] → Successfully created PlotDataItem with dict
[ 223.5s] 💭 (45 chars) "And what about a recarray without 'x' or 'y'?"
[ 223.5s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 223.8s] → Successfully created PlotDataItem with other fields
[ 230.5s] 💭 (54 chars) "Now let's check the case where one of them is missing."
[ 230.5s] 🔧 run_command (12 lines) python3 - <<'PY'
[ 230.8s] → Successfully created PlotDataItem with missing 'y'
[ 266.1s] 💭 (1528 chars) "Wait, if I provide a recarray with only 'x', it should still work (setting y to None or
default).
One more thing: I sho..."
[ 266.1s] 🔧 run_command git diff
[ 266.2s] → diff --git a/pyqtgraph/graphicsItems/PlotDataItem.py b/pyqtgraph/graphicsItems/PlotDataItem.py
[ 270.6s] 💭 (153 chars) "The diff looks correct and minimal.
I'll run a final check on if there are any tests that I should run.
I'll search for..."
[ 270.6s] 🔧 run_command find tests -name "*PlotDataItem*"
[ 270.6s] → tests/graphicsItems/test_PlotDataItem.py
[ 274.4s] 💭 (66 chars) "Let's run the tests in `tests/graphicsItems/test_PlotDataItem.py`."
[ 274.4s] 🔧 run_command pytest tests/graphicsItems/test_PlotDataItem.py -q --tb=short --no-header
[ 275.3s] → ......... [100%]
[ 277.2s] 💭 (22 chars) "Everything looks good."
[ 277.2s] 🤖 submit_patch
[ 277.3s] → submit_patch: {"status": "ok", "patch_size": 770, "files_changed": 1}
[ 284.9s] 💭 (5 chars) "Done."
[ 284.9s] ✅ Agent finished: Fixed a `TypeError` when using a NumPy record array to plot data by updating the field
existence check in `PlotDataItem.setData` to use `data.dtype.names` for record arrays instead of the `in` operato...
Native result row
{
"agent_error": null,
"duration_seconds": 355.32,
"error": null,
"grade": {
"collected_tests": 9,
"competition_junit_ok": true,
"error": null,
"required_issues_count": 0,
"resolved": true,
"status_counts": {
"PASSED": 9
},
"strict_clean_patch": true,
"test_exit_code": 0
},
"instance_id": "pyqtgraph__pyqtgraph-3278",
"pass_idx": 0,
"patch_chars": 770,
"phase1_seconds": 353.6,
"repo": "pyqtgraph/pyqtgraph",
"request_log_path": "/kaggle-root/working/r31/rollouts_X/requests/pyqtgraph__pyqtgraph-3278__p0__r2.jsonl",
"resolved": true,
"rollout_idx": 2,
"run_key": "pyqtgraph__pyqtgraph-3278__p0__r2",
"strict_clean_patch": true,
"tool_calls": 16,
"total_llm_calls": 19,
"trace_path": "/kaggle-root/working/r31/rollouts_X/traces/trace_pyqtgraph__pyqtgraph-3278__p0__r2.json"
}