Add RunLmpHDF5 #267
Add RunLmpHDF5 #267
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Signed-off-by: zjgemi <liuxin_zijian@163.com>
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (1)
dpgen2/entrypoint/submit.py (1)
Line range hint
1-1000: Overall assessment of HDF5 implementation changes.The changes in this file are focused on implementing HDF5 support in the concurrent learning workflow. The modifications are well-contained and consistent, affecting only the relevant parts of the
make_concurrent_learning_opfunction. These changes enhance the flexibility of the system by allowing users to opt for HDF5 output when desired.To ensure the robustness of this implementation, consider the following:
- Verify that the
use_hdf5flag is properly propagated from the user configuration to this point in the code.- Ensure that any downstream code that processes the output of these operations is capable of handling both HDF5 and non-HDF5 formats.
- Update relevant documentation to reflect this new option for users.
To further improve this implementation, consider:
- Creating a configuration validation step to ensure
use_hdf5is always a boolean value.- Implementing unit tests to verify the correct selection of HDF5 vs. non-HDF5 operations based on the configuration.
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (3)
- dpgen2/entrypoint/submit.py (2 hunks)
- dpgen2/op/init.py (1 hunks)
- dpgen2/op/run_lmp.py (6 hunks)
🧰 Additional context used
🪛 Ruff
dpgen2/op/__init__.py
39-39:
.run_lmp.RunLmpHDF5imported but unused; consider removing, adding to__all__, or using a redundant alias(F401)
🔇 Additional comments (9)
dpgen2/entrypoint/submit.py (2)
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236-236: Consistent application of HDF5 conditional logic for diffcsp exploration.The same conditional logic for HDF5 usage has been applied to the
diffcspexploration style, selecting betweenRunRelaxHDF5andRunRelax. This change maintains consistency with the previous modification and enhances the configurability of the exploration operations.
191-191: Conditional selection of RunLmpHDF5 or RunLmp based onuse_hdf5flag.The code now conditionally selects between
RunLmpHDF5andRunLmpbased on theuse_hdf5flag in theexplore_config. This change allows for more flexible handling of exploration configurations, particularly when HDF5 format is preferred.To ensure this change is consistently applied throughout the codebase, let's verify the usage of
RunLmpHDF5:✅ Verification successful
To accurately verify the usage of
RunLmpHDF5, please execute the following updated shell scripts:
To ensure consistent and appropriate usage of
RunLmpHDF5across the codebase, please execute the following shell scripts to inspect its context in other files:
Conditional selection of
RunLmpHDF5confirmed as unique withinsubmit.py.The conditional usage is properly encapsulated and does not affect other parts of the codebase.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for other occurrences of RunLmpHDF5 and its conditional usage # Search for RunLmpHDF5 usage echo "Occurrences of RunLmpHDF5:" rg --type python "RunLmpHDF5" # Search for conditional usage similar to the one in this file echo "\nConditional usage of RunLmpHDF5:" rg --type python "RunLmpHDF5 if.*use_hdf5.*else RunLmp"Length of output: 291
Script:
#!/bin/bash # Description: Check for other occurrences of RunLmpHDF5 and its conditional usage without specifying file type # Search for RunLmpHDF5 usage echo "Occurrences of RunLmpHDF5:" rg "RunLmpHDF5" # Search for conditional usage similar to the one in this file echo "\nConditional usage of RunLmpHDF5:" rg "RunLmpHDF5 if.*use_hdf5.*else RunLmp"Length of output: 550
Script:
#!/bin/bash # Description: Inspect the context of RunLmpHDF5 usage in dpgen2/op/__init__.py and dpgen2/op/run_lmp.py # Check usage in dpgen2/op/__init__.py echo "Context of RunLmpHDF5 in dpgen2/op/__init__.py:" rg "RunLmpHDF5" dpgen2/op/__init__.py -A 5 -B 5 # Check usage in dpgen2/op/run_lmp.py echo "\nContext of RunLmpHDF5 in dpgen2/op/run_lmp.py:" rg "RunLmpHDF5" dpgen2/op/run_lmp.py -A 5 -B 5Length of output: 854
dpgen2/op/run_lmp.py (7)
17-17: Addnumpyto the project's dependencies.The import of
numpyintroduces a new dependency. Ensure thatnumpyis added to the project's requirements (e.g.,requirements.txtorsetup.py) so that it is available in all environments where this code runs.
30-30: Verify the availability ofHDF5Datasets.The
HDF5Datasetsclass is imported fromdflow.python. Confirm that this class is available in the version ofdflow.pythonused by the project and that it functions as expected.
205-205: Refactor to use theget_model_devimethod.The
executemethod now usesself.get_model_devito process themodel_devioutput. This change promotes extensibility by allowing subclasses to customize howmodel_deviis handled.
218-220: Introduceget_model_devimethod for extensibility.The
get_model_devimethod is added to theRunLmpclass, returning themodel_devi_fileby default. This allows subclasses to override this method to customize the processing ofmodel_devi.
252-258: Adduse_hdf5argument to support HDF5 output.A new argument
use_hdf5is introduced in thelmp_argsmethod to toggle the usage of HDF5 for storing trajectories and model deviations. Ensure that this parameter is correctly integrated into the task configuration and that users are aware of its functionality.
396-397: Ensure correct handling ofHDF5Datasetsartifacts.In the overridden
get_output_signmethod ofRunLmpHDF5, the types fortrajandmodel_devioutputs are changed toArtifact(HDF5Datasets). Confirm that downstream components expect this artifact type and can handle HDF5 data appropriately.
400-401:⚠️ Potential issueUse appropriate method to read HDF5 files.
The
get_model_devimethod inRunLmpHDF5usesnp.loadtxtto readmodel_devi_file. Since HDF5 files are in binary format,np.loadtxtis not suitable for reading them. Consider using theh5pylibrary or other appropriate methods to read HDF5 datasets.Apply the following changes:
- Import the
h5pylibrary.- Update the
get_model_devimethod to useh5pyfor reading the HDF5 file.+import h5py class RunLmpHDF5(RunLmp): @classmethod def get_output_sign(cls): output_sign = super().get_output_sign() output_sign["traj"] = Artifact(HDF5Datasets) output_sign["model_devi"] = Artifact(HDF5Datasets) return output_sign def get_model_devi(self, model_devi_file): - return np.loadtxt(model_devi_file) + with h5py.File(model_devi_file, 'r') as f: + data = f['/path/to/dataset'][...] + return dataEnsure to replace
'/path/to/dataset'with the actual dataset path within the HDF5 file.
| @@ -36,6 +36,7 @@ | |||
| ) | |||
| from .run_lmp import ( | |||
| RunLmp, | |||
| RunLmpHDF5, | |||
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💡 Codebase verification
Define __all__ in dpgen2/op/__init__.py to include RunLmpHDF5
The __all__ variable is not defined in dpgen2/op/__init__.py. To make RunLmpHDF5 part of the public API and resolve the unused import warning, consider adding an __all__ list that includes RunLmpHDF5 along with other public classes and functions.
Example:
__all__ = [
"CollectData",
"CollRunCaly",
"DiffCSPGen",
"PrepCalyDPOptim",
"PrepCalyInput",
"PrepCalyModelDevi",
"PrepDPTrain",
"PrepLmp",
"PrepRelax",
"RunCalyDPOptim",
"RunCalyModelDevi",
"RunDPTrain",
"RunLmp",
"RunLmpHDF5",
"RunRelax",
"RunRelaxHDF5",
"SelectConfs",
]🔗 Analysis chain
Consider adding RunLmpHDF5 to all if it's part of the public API
The addition of RunLmpHDF5 to the imports is good, as it makes the new functionality available to other parts of the package. However, the static analysis tool has flagged this import as unused within this file.
If RunLmpHDF5 is intended to be part of the public API of this package, consider adding it to the __all__ list (if one exists) to explicitly define what should be imported when using from dpgen2.op import *.
To verify if __all__ is defined in this file and if so, what it contains, you can run the following script:
If __all__ is not defined, consider adding it to explicitly control what's exported:
__all__ = [
"CollectData",
"CollRunCaly",
"DiffCSPGen",
"PrepCalyDPOptim",
"PrepCalyInput",
"PrepCalyModelDevi",
"PrepDPTrain",
"PrepLmp",
"PrepRelax",
"RunCalyDPOptim",
"RunCalyModelDevi",
"RunDPTrain",
"RunLmp",
"RunLmpHDF5",
"RunRelax",
"RunRelaxHDF5",
"SelectConfs",
]🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for __all__ definition in __init__.py
# Test: Search for __all__ definition
rg --type python '__all__\s*=' dpgen2/op/__init__.py
# If __all__ is not found, suggest adding it
if [ $? -ne 0 ]; then
echo "__all__ not found. Consider adding it with RunLmpHDF5 included."
fi
Length of output: 240
Script:
#!/bin/bash
# Description: Check for __all__ definition in __init__.py without specifying file type
# Test: Search for __all__ definition
rg '__all__\s*=' dpgen2/op/__init__.py
# Capture the exit status
if [ $? -ne 0 ]; then
echo "__all__ not found. Consider adding it with RunLmpHDF5 included."
else
echo "__all__ is defined."
fi
Length of output: 195
🧰 Tools
🪛 Ruff
39-39:
.run_lmp.RunLmpHDF5imported but unused; consider removing, adding to__all__, or using a redundant alias(F401)
| Argument( | ||
| "use_hdf5", | ||
| bool, | ||
| optional=True, | ||
| default=False, | ||
| doc=doc_use_hdf5, | ||
| ), |
There was a problem hiding this comment.
Implement logic for use_hdf5 in the execute method.
The use_hdf5 parameter is added, but the execute method does not currently utilize it to alter the behavior of the class. Consider implementing conditional logic in the execute method to handle cases when use_hdf5 is True, such as processing outputs differently or initializing RunLmpHDF5.
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## master #267 +/- ##
==========================================
- Coverage 83.70% 83.65% -0.05%
==========================================
Files 104 104
Lines 6015 6028 +13
==========================================
+ Hits 5035 5043 +8
- Misses 980 985 +5 ☔ View full report in Codecov by Sentry. |
Signed-off-by: zjgemi <liuxin_zijian@163.com>
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (3)
dpgen2/exploration/render/traj_render_lammps.py (3)
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74-92: Enhance documentation and error handling inget_ele_tempmethod.The
get_ele_tempmethod introduces new functionality, but its purpose and behavior are not immediately clear from the implementation.Consider the following improvements:
- Add a docstring explaining the method's purpose, parameters, and return value.
- Document the significance of different
use_ele_tempvalues (0, 1, 2).- Consider using an enum for
use_ele_tempto make the code more self-documenting.- Add error handling for the case where
optional_outputsis empty or None.- Clarify the purpose and impact of the
setup_ele_tempfunction calls.Example docstring:
def get_ele_temp(self, optional_outputs): """ Process optional output files to extract electronic temperature data. Args: optional_outputs (List[Path]): List of paths to optional output files. Returns: List[float]: List of electronic temperatures extracted from the files. Raises: ValueError: If use_ele_temp is not 0, 1, or 2. """🧰 Tools
🪛 Ruff
62-65: Use ternary operator
dd = fname.get_data() if isinstance(fname, HDF5Dataset) else np.loadtxt(fname)instead ofif-else-block(SIM108)
🪛 GitHub Check: pyright
[failure] 66-66:
Argument of type "Unknown | NDArray[float64] | None" cannot be assigned to parameter "a" of type "ArrayLike" in function "shape" (reportGeneralTypeIssues)
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94-102: Improve documentation and error handling inset_ele_tempmethod.The
set_ele_tempmethod modifies thesystem.datadictionary based onuse_ele_temp, but its behavior and purpose are not immediately clear.Consider the following improvements:
- Add a docstring explaining the method's purpose, parameters, and side effects.
- Document the significance of different
use_ele_tempvalues and their impact on 'fparam' and 'aparam'.- Add error handling or logging for cases where
use_ele_tempis 0 or any unexpected value.- Consider using an enum for
use_ele_tempto make the code more self-documenting.Example docstring:
def set_ele_temp(self, system, ele_temp): """ Set electronic temperature data in the system object. Args: system (dpdata.System): The system object to modify. ele_temp (float): The electronic temperature value to set. Side effects: Modifies system.data['fparam'] or system.data['aparam'] based on use_ele_temp. Note: This method has no effect if use_ele_temp is 0 or any value other than 1 or 2. """🧰 Tools
🪛 Ruff
62-65: Use ternary operator
dd = fname.get_data() if isinstance(fname, HDF5Dataset) else np.loadtxt(fname)instead ofif-else-block(SIM108)
🪛 GitHub Check: pyright
[failure] 66-66:
Argument of type "Unknown | NDArray[float64] | None" cannot be assigned to parameter "a" of type "ArrayLike" in function "shape" (reportGeneralTypeIssues)
Line range hint
104-140: Address potential issues and improve error handling inget_confsmethod.The
get_confsmethod has been updated to incorporate electronic temperature functionality, but there are some potential issues and areas for improvement.Consider the following changes:
- Replace the assertion
assert ntraj == len(optional_outputs)with a more robust check:if optional_outputs is not None and ntraj != len(optional_outputs): raise ValueError("Number of trajectories must match the number of optional outputs")- Investigate and address the root cause of the type ignore comment on line 127. If possible, resolve the type mismatch without suppressing the type checker.
- Add error handling for cases where
get_ele_temporset_ele_tempmight fail.- Consider adding a docstring to explain the method's purpose, parameters, and return value.
Example docstring:
def get_confs( self, trajs: Union[List[Path], List[HDF5Dataset]], id_selected: List[List[int]], type_map: Optional[List[str]] = None, conf_filters: Optional["ConfFilters"] = None, optional_outputs: Optional[List[Path]] = None, ) -> dpdata.MultiSystems: """ Extract configurations from trajectories based on selected IDs and apply filters. Args: trajs: List of trajectory files or HDF5Datasets. id_selected: List of lists containing selected frame IDs for each trajectory. type_map: Optional mapping of atom types. conf_filters: Optional filters to apply to configurations. optional_outputs: Optional list of paths to additional output files. Returns: A MultiSystems object containing the selected and filtered configurations. Raises: ValueError: If the number of trajectories doesn't match the number of optional outputs. """🧰 Tools
🪛 Ruff
62-65: Use ternary operator
dd = fname.get_data() if isinstance(fname, HDF5Dataset) else np.loadtxt(fname)instead ofif-else-block(SIM108)
🪛 GitHub Check: pyright
[failure] 66-66:
Argument of type "Unknown | NDArray[float64] | None" cannot be assigned to parameter "a" of type "ArrayLike" in function "shape" (reportGeneralTypeIssues)
📜 Review details
Configuration used: CodeRabbit UI
Review profile: CHILL
📒 Files selected for processing (2)
- dpgen2/exploration/render/traj_render_lammps.py (1 hunks)
- pyproject.toml (1 hunks)
🧰 Additional context used
🔇 Additional comments (1)
pyproject.toml (1)
20-20: Verify the necessity of updating pydflow dependency.The pydflow dependency has been updated from '>=1.8.88' to '>=1.8.95'. This change might be necessary due to new features or bug fixes in pydflow that are required for this project.
To ensure this update is intentional and necessary, please run the following script:
Can you confirm if this update is required for any specific features or bug fixes in the latest pydflow version?
| @@ -60,18 +60,18 @@ | |||
|
|
|||
| def _load_one_model_devi(self, fname, model_devi): | |||
| if isinstance(fname, HDF5Dataset): | |||
| dd = fname.get_data() | |||
| dd = fname.get_data() # type: ignore | |||
There was a problem hiding this comment.
Investigate and address the root cause of the type ignore comment.
The addition of # type: ignore suggests a potential type mismatch that's being suppressed. While this allows the code to pass type checking, it may hide underlying issues.
Consider investigating the root cause of this type mismatch. If possible, modify the code to resolve the type issue without needing to suppress the type checker. If the suppression is absolutely necessary, add a comment explaining why it's needed and any potential risks.
Signed-off-by: zjgemi <liuxin_zijian@163.com>
for more information, see https://pre-commit.ci
Signed-off-by: zjgemi <liuxin_zijian@163.com>
Summary by CodeRabbit
RunLmpHDF5option for improved data handling and output types.RunLmpclass with new methods for better processing of model deviation files and output data storage options.TrajRenderLammpsclass, including better management of temperature settings.pydflowdependency to>=1.8.95.