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About
ArviZ not only builds on top of matplotlib's rcParams but also adds its own rcParams instance to handle specific settings. This post will only graze matplotlib's rcParams, which are already detailed in matplotlib's docs; it will dive into specific ArviZ rcParams.
Introduction
Paraphrasing the description on rcParams in the documentation of matplotlib:
ArviZ uses arvizrc configuration files to customize all kinds of properties, which we call rcParams. You can control the defaults of many properties in ArviZ:data loading mode (lazy or eager), automatically showing generated plots, the default information criteria and so on. There are several ways of modifying
arviz.rcParamsinstance, each of them targeted to specific needs.
arvizrc file
To define default values on a per user or per project basis, arvizrc file should be used. When imported, ArviZ search for an arvizrc file in several locations sorted below by priority:
$PWD/arvizrc$ARVIZ_DATA/arvizrc- On Linux,
$XDG_CONFIG_HOME/arviz/arvizrc(if$XDG_CONFIG_HOMEis defined)- or
$HOME/.config/arviz/arvizrc(if$XDG_CONFIG_HOMEis not defined)
- On other platforms,
$HOME/.arviz/arvizrcif$HOMEis defined
Once one of these files is found, ArviZ stops looking and loads its configuration. If none of them are present, the values hardcoded in ArviZ codebase are used. The file used to set the default values in ArviZ can be obtained with the following command:
import arviz as az
print(az.rcparams.get_arviz_rcfile())
ArviZ has loaded a file used to set defaults on a per user basis. Unless I use a different rc file in the current directory or modify rcParams as explained above, this configuration will be automatically used every time ArviZ is imported. This can be really useful to define the favourite backend or information criterion, written once in the rc file and ArviZ automatically uses the desired values.
az.rcParams["data.load"] = "eager"
Note that rcParams is the instance to be modified, exactly like in matplotlib.
Another option is to define a dictionary with several new defaults and update rcParams all at once.
rc = {
"data.load": "lazy",
"plot.max_subplots": 30,
"stats.ic_scale": "negative_log",
"plot.matplotlib.constrained_layout": False
}
az.rcParams.update(rc)
rc_context
Eventually, to temporarily use a different set of defaults, ArviZ also has a rc_context function. Its main difference and advantage is that it is a context manager, therefore, all code executed inside the context will use the defaults defined by rc_context but once we exit the context, everything goes back to normal.
#collapse-hide
idata = az.load_arviz_data("centered_eight")
print(az.summary(idata, var_names="theta", kind="stats"))
with az.rc_context({"data.index_origin": 1}):
print(az.summary(idata, var_names="theta", kind="stats"))
print(az.summary(idata, var_names="theta", kind="stats"))
ArviZ default settings
Here are the default ArviZ settings (also available in GitHub)
from arviz.rcparams import RcParams, defaultParams
print(RcParams([(key, default) for key, (default, _) in defaultParams.items()]))