dpdata-minimizer

SkillAI & models

Minimize geometries with dpdata minimizer plugins via System.minimize(), including how minimizers relate to drivers (ASEMinimizer needs a dpdata Driver) and how to list supported minimizers (ase/sqm). Use when doing geometry optimization/minimization through dpdata Python API.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the dpdata-minimizer skill

What this skill tells your AI

The instructions your AI receives, as published by jinzhezenggroup/computational-chemistry-agent-skills in tools/dpdata-minimizer/SKILL.md and read by ahel’s review.

Use dpdata “minimizer plugins” to optimize/minimize geometry and return a dpdata.LabeledSystem.

Key idea

  • A Minimizer performs geometry optimization (updates coordinates) and returns labeled results.
  • dpdata exposes this as:
System.minimize(*args, minimizer: str|Minimizer, **kwargs) -> LabeledSystem

List supported minimizer keys (runtime)

from dpdata.driver import Minimizer

print(sorted(Minimizer.get_minimizers().keys()))

In the current dpdata repo, minimizer keys include:

  • ase
  • sqm

Relationship to drivers (important)

Some minimizers require a dpdata Driver object.

Example: ASEMinimizer takes a dpdata Driver in its constructor:

  • minimizer="ase" requires driver=<dpdata Driver> (e.g. the ASE driver wrapping an ASE calculator).

So you generally do:

  1. Construct a driver
  2. Construct a minimizer (or let dpdata do it by passing the right kwargs)
  3. Call System.minimize(...)

Runnable example: ASE minimizer with an ASE calculator

Use uv inline script metadata so the example runs reproducibly with uv run.

# /// script
# requires-python = ">=3.12"
# dependencies = [
#   "dpdata",
#   "numpy",
#   "ase",
# ]
# ///

import numpy as np
from ase.calculators.emt import EMT

from dpdata.driver import Driver
from dpdata.system import System

open("tmp.xyz", "w").write("""2\n\nH 0 0 0\nH 0 0 0.74\n""")

sys = System("tmp.xyz", fmt="xyz")

# Build a dpdata driver that can provide energies/forces to ASE optimizers.
ase_driver = Driver.get_driver("ase")(calculator=EMT())

# Minimize using the ASE minimizer plugin.
# NOTE: ASEMinimizer expects `driver` (not `calculator`) as input.
ls = sys.minimize(minimizer="ase", driver=ase_driver, fmax=0.05, max_steps=5)

print("coords", np.array(ls.data["coords"]).shape)
print("energies", np.array(ls.data["energies"]))
print("forces", np.array(ls.data["forces"]).shape)

Notes / gotchas

  • System.minimize(...) accepts either a minimizer key string or a Minimizer object.
  • If you previously used System.predict(driver="ase", calculator=...), be aware that minimization is different: you need to pass a driver into the minimizer (ASEMinimizer does not accept calculator=).
  • sqm minimizer requires AmberTools sqm executable and typically won’t be runnable in CI.

Signals

GitHub stars
138
Forks
26
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
dpdata-minimizer
Source
github.com/jinzhezenggroup/computational-chemistry-agent-skills