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@shyuep shyuep released this 14 Jun 21:57
· 17 commits to master since this release
v2025.6.14
682bfd8
  • Treat LATTICE_CONSTRAINTS as is for INCARs.
  • PR #4425 JDFTXOutfileSlice.trajectory revision by @benrich37
    Major changes:
    • feature 1: JDFTXOutfileSlice.trajectory is now initialized with frame_properties set
      -- JOutStructure.properties filled with relevant data for frame_properties
      -- More properties added to JOutStructure.site_properties

    Todos

    • Remove class attributes in JOutStructure now redundant to data stored in JOutStructure.properties and JOutStructure.site_properties
  • PR #4431 Single source of truth for POTCAR directory structure by @esoteric-ephemera
    Modifies the pymatgen CLI to use the same POTCAR library directory structure as in pymatgen.io.vasp.inputs to close #4430. Possibly breaking from the CLI side (the directory structure will change)
    Pinging @mkhorton since #4424 was probably motivated by similar concerns?
  • PR #4433 Speed up symmetry functions with faster is_periodic_image algorithm by @kavanase
    I noticed that in some of our doped testing workflows, SpacegroupAnalyzer.get_primitive_standard_structure() is one of the main bottlenecks (as to be expected). One of the dominant cost factors here is the usage of is_periodic_image, which can be expensive for large structures due to many np.allclose() calls.
    This PR implements a small change to instead use an equivalent (but faster) pure Python loop, which also breaks early if the tolerance is exceeded.
    In my test case, this reduced the time spent on is_periodic_image (and thus SpacegroupAnalyzer.get_primitive_standard_structure()) from 35s to 10s.
  • PR #4432 Fingerprint sources by @JaGeo
    Add correct papers to tanimoto fingerprints
  • PR #4061 Fix branch directory check in io.vasp.outputs.get_band_structure_from_vasp_multiple_branches by @DanielYang59

    Summary

    • Fix branch directory check in io.vasp.outputs.get_band_structure_from_vasp_multiple_branches, to fix #4060
    • Improve unit test (waiting for data, I don't have experience with "VASP multi-branch bandstructure calculation")
  • PR #4409 Packmol constraints by @davidwaroquiers
    Added possibility to set individual constraints in packmol.
    Added some sanity checks.
    Added unit tests.
  • PR #4428 Fixes a bug in NanoscaleStability.plot_one_stability_map and plot_all_stability_map. by @kmu
    Major changes:
    • Replaced incorrect ax.xlabel() and ax.ylabel() calls with correct ax.set_xlabel() and ax.set_ylabel().
    • Added ax.legend() to plot_all_stability_map so that labels passed via ax.plot(..., label=...) are displayed.
    • Added test_plot() to test_surface_analysis.py.
  • PR #4424 Add additional name mappings for new LDA v64 potcars by @mkhorton
    As title.
  • PR #4426 Fix uncertainty as int for EnergyAdjustment by @DanielYang59
    • Avoid == or != for possible float comparison
    • Fix uncertainty as int for EnergyAdjustment cannot generate repr:
    from pymatgen.entries.computed_entries import EnergyAdjustment
print(EnergyAdjustment(10, uncertainty=0))
    Gives: 
    Traceback (most recent call last):
File "/Users/yang/developer/pymatgen/test_json.py", line 25, in <module>
print(EnergyAdjustment(10, uncertainty=0))
File "/Users/yang/developer/pymatgen/src/pymatgen/entries/computed_entries.py", line 108, in __repr__
return f"{type(self).__name__}({name=}, {value=:.3}, {uncertainty=:.3}, {description=}, {generated_by=})"
^^^^^^^^^^^^^^^^^
ValueError: Precision not allowed in integer format specifier
  • PR #4421 Cache Lattice property (lengths/angles/volume) for much faster Structure.as_dict by @DanielYang59

    Summary

    Cache frequently used Lattice properties

    Currently length/angles/volume is not cached and is frequently used, for example accessing all lattice parameter related property would lead to length/angles being repeatedly calculated: https://github.com/materialsproject/pymatgen/blob/34608d0b92166e5fc4a9dd52ed465ae7dccfa525/src/pymatgen/core/lattice.py#L475-L524
    structure.as_dict now around 8x faster
    Before (1000 structure, each has 10-100 atoms): 
    Total time: 3.29617 s
File: create_dummp_json_structure.py
Function: generate_and_save_structures at line 34
Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
34                                           @profile
35                                           def generate_and_save_structures(n, output_dir):
36         1         20.0     20.0      0.0      os.makedirs(output_dir, exist_ok=True)
37
38      1001        222.0      0.2      0.0      for i in range(n):
39      1000     291789.0    291.8      8.9          structure = generate_dummy_structure()
40      1000        583.0      0.6      0.0          filename = f"structure_{i:04d}.json.gz"
41      1000       1942.0      1.9      0.1          filepath = os.path.join(output_dir, filename)
42
43      2000     224549.0    112.3      6.8          with gzip.open(filepath, "wb") as f:
44      1000    2761900.0   2761.9     83.8              dct = structure.as_dict()
45      1000      15163.0     15.2      0.5              f.write(orjson.dumps(dct))
    Now: 
    Total time: 0.949622 s
File: create_dummp_json_structure.py
Function: generate_and_save_structures at line 34
Line #      Hits         Time  Per Hit   % Time  Line Contents
==============================================================
34                                           @profile
35                                           def generate_and_save_structures(n, output_dir):
36         1         37.0     37.0      0.0      os.makedirs(output_dir, exist_ok=True)
37
38      1001        195.0      0.2      0.0      for i in range(n):
39      1000     286696.0    286.7     30.2          structure = generate_dummy_structure()
40      1000        511.0      0.5      0.1          filename = f"structure_{i:04d}.json.gz"
41      1000       1843.0      1.8      0.2          filepath = os.path.join(output_dir, filename)
42
43      2000     214130.0    107.1     22.5          with gzip.open(filepath, "wb") as f:
44      1000     431677.0    431.7     45.5              dct = structure.as_dict()
45      1000      14533.0     14.5      1.5              f.write(orjson.dumps(dct))
    Also note lattice (the performance bottleneck) is not used in the dict for site: https://github.com/materialsproject/pymatgen/blob/34608d0b92166e5fc4a9dd52ed465ae7dccfa525/src/pymatgen/core/structure.py#L2856-L2857
    So we could modify as_dict to control whether lattice would be generated at all
    This could reduce the runtime slightly so I guess it's not worth the effort: 
    Total time: 0.867376 s
  • PR #4391 Add custom as_dict/from_dict method for proper initialization of attributes of IcohpCollection by @naik-aakash
    Currently IcohpCollection instance is not serialized correctly, thus I added custom from_dict and as_dict methods here.

Contributors

mkhorton, davidwaroquiers, and 7 other contributors
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