Algorithm¶
full name: tenpy.algorithms.algorithm.Algorithm
parent module:
tenpy.algorithms.algorithm
type: class
Inheritance Diagram
Methods
|
Initialize self. |
Return necessary data to resume a |
|
Resume a run that was interrupted. |
|
Actually run the algorithm. |
Class Attributes and Properties
|
-
class
tenpy.algorithms.algorithm.
Algorithm
(psi, model, options, *, resume_data=None)[source]¶ Bases:
object
Base class and common interface for a tensor-network based algorithm in TeNPy.
- Parameters
psi – Tensor network to be updated by the algorithm.
model (
Model
| None) – Model with the representation of the hamiltonian suitable for the algorithm. None for algorithms which don’t require a model.options (dict-like) – Optional parameters for the algorithm. In the online documentation, you can find the correct set of options in the Config Index.
resume_data (None | dict) – Can only be passed as keyword argument. By default (
None
) ignored. If a dict, it should contain the data returned byget_resume_data()
when intending to continue/resume an interrupted run.
Options
-
config
Algorithm
¶ option summary Truncation parameters as described in :cfg:config:`truncation`.
-
option
trunc_params
: dict¶ Truncation parameters as described in
truncation
.
-
option
-
psi
¶ Tensor network to be updated by the algorithm.
-
checkpoint
¶ An event that the algorithm emits at regular intervalls when it is in a “well defined” step, where an intermediate status report, measurements and/or interrupting and saving to disk for later resume make sense.
- Type
-
resume_run
()[source]¶ Resume a run that was interrupted.
In case we saved an intermediate result at a
checkpoint
, this function allows to resume therun()
of the algorithm (after re-initialization with the resume_data). Since most algorithms just have a while loop with break conditions, the default behaviour implemented here is to just callrun()
.
-
get_resume_data
()[source]¶ Return necessary data to resume a
run()
interrupted at a checkpoint.At a
checkpoint
, you can savepsi
,model
andoptions
along with the data returned by this function. When the simulation aborts, you can resume it using this saved data with:eng = AlgorithmClass(psi, model, options, resume_data=resume_data) eng.resume_run(resume_data)
An algorithm which doesn’t support this should override resume_run to raise an Error.
- Returns
resume_data – Dictionary with necessary data (apart from copies of psi, model, options) that allows to continue the simulation from where we are now.
- Return type