LMR configuration

Overview

The LMR configuration groups a set of user defined parameters detailing the reconstruction experiment including: the proxy data to use, the fields to be reconstructed, and aspects of the data assimilation method. The config_template.yml and LMR_config_template.py file should be copied into the source directory from the config_templs/ directory as config.yml and LMR_config.py. This is the default file searched for by the code to run a reconstruction and holds the parameters available to users. Use cases are described below followed by a general outline of the parameters available.

General configuration

When running a reconstruction, the LMR_wrapper.py script is set up to look for config.yml in the code directory to use as the configuration. This file is a YAML ( YAML Ain’t Markup Language ; useful primer) document that gets read in at runtime. Each section of the file describes the user parameters for a specific aspect of the reconstruction. Casting of the values from the file into python are done by the yaml parser, so when editing the file please try and maintain the same data type as the template.

wrapper:

Parameters related to orchestrating the reconstruction realizations. I.e. Monte-Carlo iterations, parameter space searches.

core:

High-level reconstruction parameters such as main data and output directories, experiment name, and DA controls.

proxies:

Parameters controlling which proxy database to use, how the proxies are selected, and which observation models are used.

psms:

Parameters for setting up and using different proxy observation models.

prior:

Parameters describing data source and fields to use as the prior state estimate during a reconstruction.

Note

If config.yml is not found or if any extraneous parameters (including misspellings) are found in the file, the reconstruction code will exit immediately.

Custom configuration files

If you would like to use a file other than config.yml as the reconstruction configuration LMR_wrapper.py is set up to so the first runtime argument can be passed as the configuration to use

LMR_wrapper.py /path/to/a/different_config.yml

With this you might store common configurations somewhere else instead of constantly changing config.yml.

Note

If the file specified as an argument is not found, the code will exit immediately.

Legacy configuration

The LMR code was originally set up to use LMR_config.py as the primary configuration mechanism. It provided an easy object-oriented way to encapsulate parameters passed around to different classes at runtime. The nature of providing parameter listings that couldn’t be changed during an experiment at by outside references to the configuration reduced the readability. To switch away from using the YAML files just set the following flag at the top of LMR_config.py

LEGACY_CONFIG = True

This means all parameters will be specified within LMR_config.py between the commented sections

##** BEGIN User Parameters **##
parameter1 = True
parameter2 = '/test_dir'
##** END User Parameters **##

Programmatic config updating

In some instances you may want to update configuration values on the fly. There are a few different ways to accomplish this within LMR_config.py.

A more permanent change which will be propagated to all subsequent Config instances can be accomplished by editing the values of a class definition directly.

LMR_config.core.nexp = 'New_experiment'
LMR_config.core.nens = 20
LMR_config.proxies.pages.datadir_proxy = '/new/path/to/proxy/data'

You can also permanently update the configuration using dictionaries much like those imported from the YAML files.

update_dict = {'core': {'nexp': 'New_experiment',
                        'nens': 20},
               'proxies': {'pages': {'datadir_proxy': '/new/path/to/proxy/data'}}}
LMR_config.update_config_class_yaml(update_dict, LMR_config)

If only temporary changes to the configuration are necessary, instead just pass the dictionary of update key/value pairs to the constructor.

update_dict = {'core': {'nexp': 'New_experiment',
                        'nens': 20},
               'proxies': {'pages': {'datadir_proxy': '/new/path/to/proxy/data'}}}
cfg = LMR_config.Config(**update_dict)

This will make no alterations to the imported LMR_config.py.

Reference