Parameters and options¶
(We use parameter and option synonymously.)
Standard simulations in TeNPy can be defined by just set of options collected in a dictionary (possibly containing
other parameter dictionaries).
It can be convenient to represent these options in a [yaml] file, say
parameters.yml, which might look like this:
output_filename : params_output.h5 overwrite_output : True model_class : SpinChain model_params : L : 14 bc_MPS : finite initial_state_params: method : lat_product_state product_state : [[up], [down]] algorithm_class: TwoSiteDMRG algorithm_params: trunc_params: chi_max: 120 svd_min: 1e.-8 max_sweeps: 10 mixer : True
Note that the default values and even the allowed/used option names often depend on other parameters.
For example, the model_class parameter above given to a
Simulation selects a model class,
and diffent model classes might have completely different parameters.
This gives you freedom to define your own parameters when you implement a model, but it also makes it a little bit harder to keep track of allowed values.
In the TeNPy documentation, we use the
Options sections of doc-strings to define parameters that are read out.
Each documented parameter is attributed to one set of parameters, called “config”, and managed in a
Config class at runtime.
The above example represents the config for a Simulation, with the model_params representing the config given as
options to the model for initialization.
Sometimes, there is also a structure of one config including the parameters from another one:
For example, the generic parameters for time evolution algorithms,
TimeEvolutionAlgorithm are included
TEBDEngine config, similarly to the sub-classing used.
During runtime, the
Config class logs the first use of any parameter (with DEBUG log-level, if
the default is used, and with INFO log-level, if it is non-default). Moreover, the default is saved into the parameter
dictionary. Hence, it will contain the full set of all used parameters, default and non-default, at the end of a
simulation, e.g., in the sim_params of the results returned by
If you add extra options to your configuration that TeNPy doesn’t read out by the end of the simulation, it will issue a warning. Getting such a warnings is an indicator for a typo in your configuration, or an option being in the wrong config dictionary.