docs: fix spelling typos in system guides#966
docs: fix spelling typos in system guides#966njzjz-bot wants to merge 1 commit intodeepmodeling:masterfrom
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- correct obvious spelling mistakes in BondOrderSystem, System, and MultiSystems docs - avoid touching sample output files that would introduce false-positive edits Authored by OpenClaw (model: gpt-5.4)
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## master #966 +/- ##
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Coverage 86.70% 86.70%
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📝 WalkthroughWalkthroughDocumentation typo and grammar corrections across three system documentation files. Changes include spelling corrections ("hetreocycles" → "heterocycles", "infomation" → "information"), grammar fixes ("wan't" → "want"), and other textual improvements. No functional code or API modifications. Changes
Estimated code review effort🎯 1 (Trivial) | ⏱️ ~3 minutes 🚥 Pre-merge checks | ✅ 3✅ Passed checks (3 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 2
🧹 Nitpick comments (1)
docs/systems/system.md (1)
129-129: Polish wording for natural English.Consider changing “Random 8 Hf atoms” to “8 random Hf atoms” for smoother phrasing.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@docs/systems/system.md` at line 129, Change the phrase "Random 8 Hf atoms" to "8 random Hf atoms" in the sentence that currently reads "Random 8 Hf atoms in the system will be replaced by Zr atoms with the atom position unchanged" so the wording becomes natural English and reads e.g. "8 random Hf atoms in the system will be replaced by Zr atoms with the atom positions unchanged."
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@docs/systems/multi.md`:
- Line 3: The sentence describing the Class dpdata.MultiSystems has incorrect
subject-verb agreement; change "may contains" to "may contain" in the opening
sentence that mentions reading data from a dir which may contains many files of
different systems, or from a single xyz file that contains different systems
(ref: Class dpdata.MultiSystems).
In `@docs/systems/system.md`:
- Line 111: The prose uses the invalid Python expression tuple(1,2,3); update
the sentence to show valid tuple notation by replacing tuple(1,2,3) with either
(1, 2, 3) or tuple([1, 2, 3]) so readers see correct examples (reference the
original token tuple(1,2,3) and the replacements (1, 2, 3) or tuple([1, 2, 3])).
---
Nitpick comments:
In `@docs/systems/system.md`:
- Line 129: Change the phrase "Random 8 Hf atoms" to "8 random Hf atoms" in the
sentence that currently reads "Random 8 Hf atoms in the system will be replaced
by Zr atoms with the atom position unchanged" so the wording becomes natural
English and reads e.g. "8 random Hf atoms in the system will be replaced by Zr
atoms with the atom positions unchanged."
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: Organization UI
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Run ID: 4cc6007a-0d76-4691-9ada-7b2d14d992f2
📒 Files selected for processing (3)
docs/systems/bond_order_system.mddocs/systems/multi.mddocs/systems/system.md
| # `MultiSystems` | ||
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| The Class {class}`dpdata.MultiSystems` can read data from a dir which may contains many files of different systems, or from single xyz file which contains different systems. | ||
| The Class {class}`dpdata.MultiSystems` can read data from a dir which may contains many files of different systems, or from a single xyz file that contains different systems. |
There was a problem hiding this comment.
Fix subject-verb agreement in the opening sentence.
Use “may contain” instead of “may contains”.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@docs/systems/multi.md` at line 3, The sentence describing the Class
dpdata.MultiSystems has incorrect subject-verb agreement; change "may contains"
to "may contain" in the opening sentence that mentions reading data from a dir
which may contains many files of different systems, or from a single xyz file
that contains different systems (ref: Class dpdata.MultiSystems).
| ``` | ||
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| tuple(1,2,3) means don't copy atom configuration in x direction, make 2 copys in y direction, make 3 copys in z direction. | ||
| tuple(1,2,3) means don't copy atom configuration in x direction, make 2 copies in y direction, make 3 copies in z direction. |
There was a problem hiding this comment.
🧩 Analysis chain
🌐 Web query:
In Python, is tuple(1,2,3) valid syntax? What is the correct way to represent a tuple with values 1, 2, and 3?
💡 Result:
No. tuple(1,2,3) is not valid because the tuple() constructor takes at most one positional argument (an iterable), not three separate values. [1]
Correct ways to represent a tuple containing 1, 2, 3:
- Tuple literal:
t = (1, 2, 3)(also valid:t = 1, 2, 3) [2] - Using the constructor with an iterable:
t = tuple([1, 2, 3])(ortuple((1, 2, 3))) [1]
Sources:
[1] Purpose of tuple constructor in python - Stack Overflow (stackoverflow.com)
[2] TupleSyntax - Python Wiki (wiki.python.org)
Citations:
- 1: https://stackoverflow.com/questions/61704534/purpose-of-tuple-constructor-in-python?utm_source=openai
- 2: https://wiki.python.org/moin/TupleSyntax?utm_source=openai
Fix tuple notation in prose to avoid misleading users.
tuple(1,2,3) is not valid Python syntax. Use (1, 2, 3) or tuple([1, 2, 3]) instead.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@docs/systems/system.md` at line 111, The prose uses the invalid Python
expression tuple(1,2,3); update the sentence to show valid tuple notation by
replacing tuple(1,2,3) with either (1, 2, 3) or tuple([1, 2, 3]) so readers see
correct examples (reference the original token tuple(1,2,3) and the replacements
(1, 2, 3) or tuple([1, 2, 3])).
1 participant
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Notes
Authored by OpenClaw (model: gpt-5.4)
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