breaking: change internal prec of quip/gap/xyz to float64

[wanghan-iapcm]

Summary by CodeRabbit

• Precision Improvements

  • Updated numpy array data types from float32 to float64 for enhanced numerical precision
  • Refined energy and virial value representations in test data files using scientific notation
  • Removed redundant error handling code

• Test Data Updates

  • Updated energy value formats in multiple test XYZ files for improved accuracy

[codecov]

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 85.16%. Comparing base (18ba98d) to head (93f6fc3).
Report is 25 commits behind head on devel.

Additional details and impacted files

@@           Coverage Diff           @@
##            devel     #777   +/-   ##
=======================================
  Coverage   85.16%   85.16%           
=======================================
  Files          81       81           
  Lines        7530     7530           
=======================================
  Hits         6413     6413           
  Misses       1117     1117           

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[codspeed-hq]

CodSpeed Performance Report

Merging #777 will not alter performance

_{Comparing wanghan-iapcm:break-xyz-prec (93f6fc3) with devel (18ba98d)}

Summary

✅ 2 untouched benchmarks

[coderabbitai]

📝 Walkthrough

Walkthrough

The pull request introduces precision-related modifications to the QuipGapxyzSystems class in the quip_gap_xyz.py file. The primary change involves converting numpy array data types from float32 to float64 for various numerical arrays such as virials, cells, coordinates, energies, and forces. This modification aims to enhance numerical precision without altering the underlying functionality. Simultaneously, test files have been updated with more precise scientific notation for energy values, maintaining the dataset's structural integrity.

Changes

File	Change Summary
dpdata/xyz/quip_gap_xyz.py	- Changed numpy array data types from float32 to float64 for multiple arrays - Removed redundant RuntimeError line for virials variable
tests/xyz/*.xyz	- Updated energy values to scientific notation format - Maintained dataset structure and content

Sequence Diagram

sequenceDiagram
    participant Data as Numpy Arrays
    participant Converter as QuipGapxyzSystems
    
    Data->>Converter: Input arrays (float32)
    Converter->>Converter: Convert to float64
    Converter-->>Data: Processed arrays with higher precision

Loading

The sequence diagram illustrates the conversion process from float32 to float64 within the QuipGapxyzSystems class, highlighting the precision enhancement without changing the fundamental data handling logic.

---

📜 Recent review details

Configuration used: CodeRabbit UI
Review profile: CHILL
Plan: Pro

📥 Commits

Reviewing files that changed from the base of the PR and between 18ba98d and 93f6fc3.

📒 Files selected for processing (4)

• dpdata/xyz/quip_gap_xyz.py (2 hunks)
• tests/xyz/xyz_unittest.field.xyz (2 hunks)
• tests/xyz/xyz_unittest.sort.xyz (2 hunks)
• tests/xyz/xyz_unittest.xyz (2 hunks)

🔇 Additional comments (4)

dpdata/xyz/quip_gap_xyz.py (1)

164-164: LGTM! Precision enhancement looks good.

The conversion from float32 to float64 for numerical arrays (virials, cells, coords, energies, forces) aligns well with scientific computing requirements where higher precision is often necessary. However, be aware that this change doubles the memory usage for these arrays.

Let's verify the precision requirements and usage across the codebase:

Also applies to: 178-181

✅ Verification successful

Precision change to float64 is consistent with codebase patterns

The conversion to float64 in quip_gap_xyz.py aligns with the established patterns in the codebase, where production code (e.g., cp2k module) consistently uses float64 precision for scientific computations, while float32 is only used in test data for efficiency.

🏁 Scripts executed

The following scripts were executed for the analysis:

Script:

#!/bin/bash
# Description: Check for any float32 specifications that might need updating
# and verify the scientific computing context

# Look for float32/float64 type specifications
rg -i "float(32|64)" --type python

# Look for numpy array creation patterns
ast-grep --pattern 'np.array($x).astype($type)'

Length of output: 117

---

Script:

#!/bin/bash
# Search for float precision patterns
rg "float(32|64)|np\.(float32|float64)"

# Search for numpy dtype specifications
rg "dtype\s*=\s*(np\.)?(float|f)(32|64)"

# Look for astype conversions
rg "astype\((np\.)?(float|f)(32|64)\)"

# Check for array creation with explicit types
rg "np\.array.*dtype\s*="

Length of output: 10632

tests/xyz/xyz_unittest.xyz (1)

16-16: LGTM! Test data precision update is consistent.

The energy values have been updated to use scientific notation with higher precision, matching the float64 precision enhancement in the implementation.

Also applies to: 28-28

tests/xyz/xyz_unittest.sort.xyz (1)

16-16: LGTM! Test data consistency maintained.

The energy values have been updated consistently with the other test files, maintaining data integrity across the test suite.

Also applies to: 28-28

tests/xyz/xyz_unittest.field.xyz (1)

19-19: LGTM! Field format precision update is consistent.

The energy values have been updated to match the higher precision format while maintaining the specific field structure requirements.

Also applies to: 31-31

Finishing Touches

• 📝 Generate Docstrings (Beta)

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