How to run this route from Python with the Ouro SDK.
API access requires an API key. Create one in Settings → API Keys, then set OURO_API_KEY in your environment. Install the SDK with pip install ouro-py.
POST /dft/magnetic/orderingParameters and request body schema for this route.
SCF convergence threshold on the charge-density residual (ABACUS scf_thr; not an energy). The default suits screening; ABACUS's own LCAO default is 1e-7. Tighten to 1e-6 or below when comparing small energy differences such as ordering margins. Force and stress checks (such as MAE's relaxed-geometry check) always run at 1e-7 or tighter, since forces need it.
Range: 0.05 to 1
K-point spacing in 1/Å
Turn on DFT+U with an effective U in eV per element, e.g. {"Ni": 6.2}. The corrected channel (d or f) is taken from the element, and U is applied only to the elements named. Plain PBE badly underestimates local moments and magnetic ordering energies in correlated oxides and fluorides, so a Hubbard term is usually needed there (Materials Project uses roughly Fe 5.3, Co 3.32, Ni 6.2, Mn 3.9, Cr 3.7, V 3.25, Cu 4.0). Setting this also softens the default mixing_beta to 0.2 and allows more SCF iterations, which correlated oxides need; an explicit mixing_beta still wins. Leave unset for metals and intermetallics such as MnBi or Mn-Al-C, where +U is not standard and generally makes agreement worse. The scheme is Dudarev, so this is U minus Hund J, not bare U.
SZDZPTZDPLCAO basis size: SZ (fastest), DZP (balanced), TZDP (most accurate)
ferromagneticantiferromagneticferrimagnetic_by_motifferrimagnetic_by_speciesWhich families of collinear ordering to enumerate. Defaults to ferromagnetic + antiferromagnetic, which is the FM-vs-AFM question. Add ferrimagnetic strategies for multi-sublattice magnets where the sublattice moments do not cancel.
Range: to 1
Charge mixing step (0–1). Default 0.4. Difficult magnets (Mn) often need 0.20, then 0.10 if SCF still oscillates.
Range: 2 to 12
Cap on configurations to compare. Each one is a full SCF, so this is the cost dial: 6 configurations is roughly six times a moments run.
PBEPBEsolLDASCANXC functional
Signed starting moments in µB, one per atom in CIF site order. Omit to take moments from the CIF's _atom_site_moment loop when it has one, else a per-element default. Set this to seed an antiferromagnet whose sublattices are the same element (e.g. NiO as [2, -2, 0, 0]) — element defaults are uniform, so they can only ever start from a ferromagnetic guess. Seeding antiparallel moments also disables ABACUS symmetry detection, which would otherwise average the sublattices back together.
Range: to 1
Occupation smearing width in eV (converted to Rydberg for ABACUS). Typical metals: 0.05–0.10 eV. Gaps need ~0.05 eV or smaller.
Evaluate the primitive cell instead of the cell as uploaded. Cheaper, but it folds an antiferromagnetic sublattice onto one site — a conventional NiO cell reduces to a single Ni, where no ordering other than ferromagnetic can exist. Leave false for any magnetic ordering question.
Pass the ID of an Ouro asset for each of these in input_assets. Ouro loads the asset and sends it to the route.
Runs save these to Ouro. Read them by name from action.final_data.
execute returns an action: the record of this run, with its status, response, and any assets it created.
This route is long-running. Start it without waiting, then collect the result when it's done.
By default a failed run comes back as an action with status error. Pass raise_on_error=True to raise an exception instead.
Every run is saved as an action. List yours, or read the logs of a single run. See the Python SDK reference for everything an action carries.
import os
from ouro import Ouro
ouro = Ouro(api_key=os.environ.get("OURO_API_KEY"))
# The ID also works, and stays the same if the route is renamed: "67393536-da30-4983-9c21-37c9fabbb296"
route = ouro.routes.retrieve("mmoderwell/magnetic-ordering-fm-vs-afm")
action = route.execute(
body={
"scf_thr": 0.0001,
"kspacing": 0.3,
"hubbard_u": {},
"basis_size": "DZP",
"strategies": [],
"mixing_beta": 0.4,
"max_orderings": 6,
"dft_functional": "PBE",
"initial_magmoms": [],
"smearing_sigma_ev": 0.05,
"reduce_to_primitive": False,
},
input_assets={
"file": "your-file-id",
},
)
print(action.status) # "success" or "error"
print(action.final_data)
# Assets the run created are keyed by output name
cif = action.final_data["cif"]
print(cif["id"])# Returns as soon as the run is accepted
action = route.execute(
body={
"scf_thr": 0.0001,
"kspacing": 0.3,
"hubbard_u": {},
"basis_size": "DZP",
"strategies": [],
"mixing_beta": 0.4,
"max_orderings": 6,
"dft_functional": "PBE",
"initial_magmoms": [],
"smearing_sigma_ev": 0.05,
"reduce_to_primitive": False,
},
input_assets={
"file": "your-file-id",
},
wait=False,
)
print(action.id, action.status)
# Later, even from another process
action = ouro.routes.poll_action(str(action.id), poll_interval=5, timeout=1800)
print(action.final_data)from ouro import ExternalServiceError, RouteExecutionError
try:
action = route.execute(
body={
"scf_thr": 0.0001,
"kspacing": 0.3,
"hubbard_u": {},
"basis_size": "DZP",
"strategies": [],
"mixing_beta": 0.4,
"max_orderings": 6,
"dft_functional": "PBE",
"initial_magmoms": [],
"smearing_sigma_ev": 0.05,
"reduce_to_primitive": False,
},
input_assets={
"file": "your-file-id",
},
raise_on_error=True,
)
except ExternalServiceError as exc:
# The API behind this route failed
print(exc.status_code, exc.retryable)
except RouteExecutionError as exc:
print(exc.action_id, exc.status, exc.response)
except TimeoutError as exc:
# Still running on Ouro; pick it up again later
action = ouro.routes.poll_action(exc.action_id, timeout=None)route = ouro.routes.retrieve("mmoderwell/magnetic-ordering-fm-vs-afm")
# Your runs of this route
actions = route.read_actions()
for action in actions:
print(action.id, action.status, action.created_at)
# One run and its logs
action = ouro.routes.retrieve_action("your-action-id")
for entry in action.read_logs(chronological=True):
print(entry.level, entry.message)Part of service
Ouro DFT (ABACUS)
Decide the collinear magnetic ground state by comparing total energies across enumerated orderings, one SCF each at identical settings. Returns the ground-state ordering (FM / AFM / ferrimagnetic), its net moment and Ms, and the energy margin over the next ordering, plus a magCIF of the ground state and a zip of every candidate so the converged moments can be visualized. Use this rather than reading the sign of site moments from a single SCF: a seeded SCF shows a configuration is stable, not that it is preferred. Supercells are generated when the input cell cannot host an ordering. Costs one SCF per configuration, so screen with cheaper routes first.
Pricing
USDYou pay for the seconds a run takes. The most it can cost is held while it runs and the rest is returned. Failed runs are free.
Median and 95th percentile of the last 7 successful runs.
Execution
Usage
21 callsView history