ManyBodyCore

class qcmanybody.ManyBodyCore(molecule, bsse_type, levels, *, return_total_data, supersystem_ie_only, embedding_charges)[source]

Bases: object

Attributes Summary

`compute_map`
`has_supersystem`

Methods Summary

`analyze`(component_results)
`format_calc_plan`([sset])	Formulate per-modelchem and per-body job count data and summary text.
`iterate_molecules`()	Iterate over all the molecules needed for the computation.
`resize_gradient`(grad, bas, *[, reverse])
`resize_hessian`(hess, bas, *[, reverse])

Attributes Documentation

Parameters:

molecule (Molecule)
bsse_type (Sequence[BsseEnum])
levels (Mapping[Union[int, Literal['supersystem']], str])
return_total_data (bool)
supersystem_ie_only (bool)
embedding_charges (Mapping[int, Sequence[float]])

compute_map

has_supersystem

Methods Documentation

analyze(component_results)[source]

Parameters:

component_results (Dict[str, Dict[str, Union[float, ndarray]]]) –

Nested dictionary with results from all individual molecular system calculations, including all subsystem/basis combinations, all model chemistries, and all properties (e.g., e/g/h).

For example, the below is the format for a nocp gradient run on a helium dimer with 1-body at CCSD and 2-body at MP2. The outer string key can be generated with the qcmanybody.utils.labeler function. The inner string key is any property; QCManyBody presently knows how to process energy/gradient/Hessian.

{'["ccsd", [1], [1]]': {'energy': -2.87, 'gradient': array([[0., 0., 0.]])},
 '["ccsd", [2], [2]]': {'energy': -2.87, 'gradient': array([[0., 0., 0.]])},
 '["mp2", [1], [1]]': {'energy': -2.86, 'gradient': array([[0., 0., 0.]])},
 '["mp2", [2], [2]]': {'energy': -2.86, 'gradient': array([[0., 0., 0.]])},
 '["mp2", [1, 2], [1, 2]]': {'energy': -5.73, 'gradient': array([[ 0., 0., 0.0053], [ 0., 0., -0.0053]])},
}

format_calc_plan(sset='all')[source]

Formulate per-modelchem and per-body job count data and summary text.

Parameters:

sset (str) – Among {“all”, “nocp”, “cp”, “vmfc_compute”}, which data structure to return.

Return type:

Tuple[str, Dict[str, Dict[int, int]]]

Returns:

info –

A text summary with per- model chemistry and per- n-body-level job counts.

Model chemistry "c4-ccsd" (§A):         22
     Number of 1-body computations:     16 (nocp: 0, cp: 0, vmfc_compute: 16)
     Number of 2-body computations:      6 (nocp: 0, cp: 0, vmfc_compute: 6)

Model chemistry "c4-mp2" (§B):          28
     Number of 1-body computations:     12 (nocp: 0, cp: 0, vmfc_compute: 12)
     Number of 2-body computations:     12 (nocp: 0, cp: 0, vmfc_compute: 12)
     Number of 3-body computations:      4 (nocp: 0, cp: 0, vmfc_compute: 4)