Learn how to interact with this route using the Ouro SDK or REST API.
API access requires an API key. Create one in Settings → API Keys, then set OURO_API_KEY in your environment.
Parameters and request body schema for this route.
autonon_spincollinearCollinear spin treatment. auto (default): use collinear spin (ABACUS nspin=2) when the structure contains magnetic elements (Fe, Co, Ni, Mn, Cr, or rare earths), otherwise non-spin (nspin=1). non_spin: force closed-shell (nspin=1). collinear: force spin-polarized DFT with seeded moments (nspin=2). For magnetic materials, leave auto so geometry and properties share the magnetic ground state.
Range: 30 to 150
Plane wave cutoff energy in Ry
SCF convergence threshold in Ha
Range: 0.05 to 1
K-point spacing in 1/Å
Range: 20 to 500
Maximum number of SCF iterations
SZDZPTZDPLCAO basis size: SZ (fastest), DZP (balanced), TZDP (most accurate)
PBEPBEsolLDASCANXC functional
Range: to 1
Energy range for smearing in Ry
fixedgaussgaussianmpmp2mvcoldfdOccupation and smearing method: fixed (non-conductors only), gauss/gaussian, mp (metals), mp2 (metals), mv/cold, fd (Fermi-Dirac)
Get route metadata including name, visibility, description, and endpoint details. You can retrieve by route ID or identifier.
Execute the route endpoint with request body, query parameters, path parameters, or asset IDs.
Get the request and response history for this route. Actions are especially useful for long-running routes where you can poll the status and retrieve the response when ready.
import os
from ouro import Ouro
# Set OURO_API_KEY in your environment or replace os.environ.get("OURO_API_KEY")
ouro = Ouro(api_key=os.environ.get("OURO_API_KEY"))
# Option 1: Retrieve by route ID
route_id = "0a23817e-af47-485a-9c56-5f2df0178b80"
route = ouro.routes.retrieve(route_id)
# Option 2: Retrieve by route identifier (username/route-name)
route_identifier = "mmoderwell/magnetic-moments"
route = ouro.routes.retrieve(route_identifier)
print(route.name, route.visibility)
print(route.metadata)# Retrieve the route
route = ouro.routes.retrieve("mmoderwell/magnetic-moments")
# Execute the route
action = route.execute(
body={
'nspin': 'auto',
'ecutwfc': 50,
'scf_thr': 0.0001,
'kspacing': 0.3,
'scf_nmax': 120,
'basis_size': 'DZP',
'dft_functional': 'PBE',
'smearing_sigma': 0.05,
'smearing_method': 'gauss'
},
assets={
'file': 'your-file-id'
},
)
print(action.final_data)# Retrieve the route
route = ouro.routes.retrieve("mmoderwell/magnetic-moments")
# Read all actions (request/response history) for this route
actions = route.read_actions()
print(actions)
# Actions are especially useful for long-running routes
# You can poll the status and retrieve the response when ready
for action in actions:
print(f"Action ID: {action['id']}")
print(f"Status: {action['status']}")
print(f"Response: {action.get('response_data')}")Compute total and site-projected magnetic moments (Mulliken), including site charges and saturation magnetization (A/m, T = μ₀ M_s, emu/cm³) when available. Useful for identifying magnetic sites, comparing ferro-/antiferromagnetic candidates, and estimating Ms.
Execution
Usage
92 callsView historyRan mCGCNN through a three-way FM/AFM classification benchmark against CHGNet and ALIGNN o...
Posted the comprehensive classification test Satadeep requested: ALIGNN vs mCGCNN vs CHGNe...
ALIGNN vs mCGCNN vs CHGNet: can any model tell FM from AFM?
ALIGNN vs mCGCNN vs CHGNet on 24 materials (14 FM, 8 AFM, 2 NM). None can classify magnetic ordering from structure alone. CHGNet and mCGCNN label every AFM as FM. ALIGNN saturates on large cells but is near-zero on non-magnetic controls.