17.1.1.17. pysisyphus.tsoptimizers package

17.1.1.17.1. Submodules

17.1.1.17.2. pysisyphus.tsoptimizers.RSIRFOptimizer module

class pysisyphus.tsoptimizers.RSIRFOptimizer.RSIRFOptimizer(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]

17.1.1.17.3. pysisyphus.tsoptimizers.RSPRFOptimizer module

class pysisyphus.tsoptimizers.RSPRFOptimizer.RSPRFOptimizer(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]

17.1.1.17.4. pysisyphus.tsoptimizers.TRIM module

class pysisyphus.tsoptimizers.TRIM.TRIM(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]

17.1.1.17.5. pysisyphus.tsoptimizers.TSHessianOptimizer module

class pysisyphus.tsoptimizers.TSHessianOptimizer.TSHessianOptimizer(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: HessianOptimizer

Optimizer to find first-order saddle points.

__init__(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Baseclass for transition state optimizers utilizing Hessian information.

Several arguments expect a typed primitive or an iterable of typed primitives. A typed primitive is specified as (PrimType, int, int, ...), e.g., for a bond between atoms 0 and 1: (BOND, 0, 1) or for a bend between the atom triple 0, 1, 2 as (BEND, 0, 1, 2).

Parameters:

geometry (Geometry) -- Geometry to be optimized.
roots (Optional[List[int]], default: None) -- Indices of modes to maximize along, e.g., to optimize saddle points of 2nd order. Overrides 'root'.
root (int, default: 0) -- Index of imaginary mode to maximize along. Shortcut for 'roots' with only one root.
hessian_ref (Optional[str], default: None) -- Filename pointing to a pysisyphus HDF5 Hessian.
rx_modes (iterable of (iterable of (typed_prim, phase_factor))) -- Select initial root(s) by overlap with a modes constructed from the given typed primitives with respective phase factors.
prim_coord (typed_prim) -- Select initial root/imaginary mode by overlap with this internal coordinate. Shortcut for 'rx_modes' with only one internal coordinate.
rx_coords (iterable of (typed_prim)) -- Construct imaginary mode comprising the given typed prims by modifying a model Hessian.
hessian_init (Literal['calc', 'unit', 'fischer', 'lindh', 'simple', 'swart', 'xtb', 'xtb1', 'xtbff'], default: 'calc') -- Type of initial model Hessian.
hessian_update (Literal['none', None, False, 'bfgs', 'damped_bfgs', 'flowchart', 'bofill', 'ts_bfgs', 'ts_bfgs_org', 'ts_bfgs_rev'], default: 'bofill') -- Type of Hessian update. Defaults to BFGS for minimizations and Bofill for saddle point searches.
hessian_recalc_reset (bool, default: True) -- Whether to skip Hessian recalculation after reset. Undocumented.
max_micro_cycles (int, default: 50) -- Maximum number of RS iterations.
trust_radius (float, default: 0.3) -- Initial trust radius in whatever unit the optimization is carried out.
trust_max (float, default: 0.5) -- Maximum trust radius.
augment_bonds (bool, default: False) -- Try to derive additional streching coordinates from the imaginary mode.
min_line_search (bool, default: False) -- Carry out line search along the imaginary mode.
max_line_search (bool, default: False) -- Carry out line search in the subspace that is minimized.
assert_neg_eigval (bool, default: False) -- Check for the existences for at least one significant negative eigenvalue. If enabled and no negative eigenvalue is present the optimization will be aborted.
**kwargs -- Keyword arguments passed to the HessianOptimizer/Optimizer baseclass.

static do_line_search(e0, e1, g0, g1, prev_step, maximize, logger=None)[source]

prepare_opt(*args, **kwargs)[source]

property root

property roots

step_and_grad_from_line_search(energy, gradient_trans, eigvecs, min_indices, max_indices)[source]

update_ts_mode(eigvals, eigvecs)[source]

valid_updates = ('bofill', 'ts_bfgs', 'ts_bfgs_org', 'ts_bfgs_rev')

17.1.1.17.6. Module contents

class pysisyphus.tsoptimizers.RSIRFOptimizer(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]

class pysisyphus.tsoptimizers.RSPRFOptimizer(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]

class pysisyphus.tsoptimizers.TRIM(geometry, roots=None, root=0, hessian_ref=None, rx_modes=None, prim_coord=None, rx_coords=None, hessian_init='calc', hessian_update='bofill', hessian_recalc_reset=True, max_micro_cycles=50, trust_radius=0.3, trust_max=0.5, augment_bonds=False, min_line_search=False, max_line_search=False, assert_neg_eigval=False, **kwargs)[source]

Bases: TSHessianOptimizer

optimize()[source]