# pylint: disable=no-member,invalid-name,redefined-outer-name
"""ArviZ plotting backends."""
import re
import numpy as np
from pandas import DataFrame
from ...rcparams import rcParams
__all__ = [
"to_cds",
"output_notebook",
"output_file",
"ColumnDataSource",
"create_layout",
"show_layout",
]
[docs]
def to_cds(
data,
var_names=None,
groups=None,
dimensions=None,
group_info=True,
var_name_format=None,
index_origin=None,
):
"""Transform data to ColumnDataSource (CDS) compatible with Bokeh.
Uses `_ARVIZ_GROUP_` and `_ARVIZ_CDS_SELECTION_` to separate var_name
from group and dimensions in CDS columns.
Parameters
----------
data : obj
Any object that can be converted to an az.InferenceData object
Refer to documentation of az.convert_to_inference_data for details
var_names : str or list of str, optional
Variables to be processed, if None all variables are processed.
groups : str or list of str, optional
Select groups for CDS. Default groups are {"posterior_groups", "prior_groups",
"posterior_groups_warmup"}
- posterior_groups: posterior, posterior_predictive, sample_stats
- prior_groups: prior, prior_predictive, sample_stats_prior
- posterior_groups_warmup: warmup_posterior, warmup_posterior_predictive,
warmup_sample_stats
ignore_groups : str or list of str, optional
Ignore specific groups from CDS.
dimension : str, or list of str, optional
Select dimensions along to slice the data. By default uses ("chain", "draw").
group_info : bool
Add group info for `var_name_format`
var_name_format : str or tuple of tuple of string, optional
Select column name format for non-scalar input.
Predefined options are {"brackets", "underscore", "cds"}
"brackets":
- add_group_info == False: ``theta[0,0]``
- add_group_info == True: ``theta_posterior[0,0]``
"underscore":
- add_group_info == False: ``theta_0_0``
- add_group_info == True: ``theta_posterior_0_0_``
"cds":
- add_group_info == False: ``theta_ARVIZ_CDS_SELECTION_0_0``
- add_group_info == True: ``theta_ARVIZ_GROUP_posterior__ARVIZ_CDS_SELECTION_0_0``
tuple:
Structure:
- tuple: (dim_info, group_info)
- dim_info: (str: `.join` separator,
str: dim_separator_start,
str: dim_separator_end)
- group_info: (str: group separator start, str: group separator end)
Example: ((",", "[", "]"), ("_", ""))
- add_group_info == False: ``theta[0,0]``
- add_group_info == True: ``theta_posterior[0,0]``
index_origin : int, optional
Start parameter indices from `index_origin`. Either 0 or 1.
Returns
-------
bokeh.models.ColumnDataSource object
"""
from ...utils import flatten_inference_data_to_dict
if var_name_format is None:
var_name_format = "cds"
cds_dict = flatten_inference_data_to_dict(
data=data,
var_names=var_names,
groups=groups,
dimensions=dimensions,
group_info=group_info,
index_origin=index_origin,
var_name_format=var_name_format,
)
cds_data = ColumnDataSource(DataFrame.from_dict(cds_dict, orient="columns"))
return cds_data
[docs]
def output_notebook(*args, **kwargs):
"""Wrap func:`bokeh.plotting.output_notebook`."""
import bokeh.plotting as bkp
return bkp.output_notebook(*args, **kwargs)
[docs]
def output_file(*args, **kwargs):
"""Wrap :func:`bokeh.plotting.output_file`."""
import bokeh.plotting as bkp
return bkp.output_file(*args, **kwargs)
[docs]
def ColumnDataSource(*args, **kwargs):
"""Wrap bokeh.models.ColumnDataSource."""
from bokeh.models import ColumnDataSource
return ColumnDataSource(*args, **kwargs)
[docs]
def create_layout(ax, force_layout=False):
"""Transform bokeh array of figures to layout."""
ax = np.atleast_2d(ax)
subplot_order = rcParams["plot.bokeh.layout.order"]
if force_layout:
from bokeh.layouts import gridplot as layout
ax = ax.tolist()
layout_args = {
"sizing_mode": rcParams["plot.bokeh.layout.sizing_mode"],
"toolbar_location": rcParams["plot.bokeh.layout.toolbar_location"],
}
elif any(item in subplot_order for item in ("row", "column")):
# check number of rows
match = re.match(r"(\d*)(row|column)", subplot_order)
n = int(match.group(1)) if match.group(1) is not None else 1
subplot_order = match.group(2)
# set up 1D list of axes
ax = [item for item in ax.ravel().tolist() if item is not None]
layout_args = {"sizing_mode": rcParams["plot.bokeh.layout.sizing_mode"]}
if subplot_order == "row" and n == 1:
from bokeh.layouts import row as layout
elif subplot_order == "column" and n == 1:
from bokeh.layouts import column as layout
else:
from bokeh.layouts import layout
if n != 1:
ax = np.array(ax + [None for _ in range(int(np.ceil(len(ax) / n)) - len(ax))])
ax = ax.reshape(n, -1) if subplot_order == "row" else ax.reshape(-1, n)
ax = ax.tolist()
else:
if subplot_order in ("square", "square_trimmed"):
ax = [item for item in ax.ravel().tolist() if item is not None]
n = int(np.ceil(len(ax) ** 0.5))
ax = ax + [None for _ in range(n**2 - len(ax))]
ax = np.array(ax).reshape(n, n)
ax = ax.tolist()
if (subplot_order == "square_trimmed") and any(
all(item is None for item in row) for row in ax
):
from bokeh.layouts import layout
ax = [row for row in ax if any(item is not None for item in row)]
layout_args = {"sizing_mode": rcParams["plot.bokeh.layout.sizing_mode"]}
else:
from bokeh.layouts import gridplot as layout
layout_args = {
"sizing_mode": rcParams["plot.bokeh.layout.sizing_mode"],
"toolbar_location": rcParams["plot.bokeh.layout.toolbar_location"],
}
# ignore "fixed" sizing_mode without explicit width and height
if layout_args.get("sizing_mode", "") == "fixed":
layout_args.pop("sizing_mode")
return layout(ax, **layout_args)
[docs]
def show_layout(ax, show=True, force_layout=False):
"""Create a layout and call bokeh show."""
if show is None:
show = rcParams["plot.bokeh.show"]
if show:
import bokeh.plotting as bkp
layout = create_layout(ax, force_layout=force_layout)
bkp.show(layout)
def _copy_docstring(lib, function):
"""Extract docstring from function."""
import importlib
try:
module = importlib.import_module(lib)
func = getattr(module, function)
doc = func.__doc__
except ImportError:
doc = f"Failed to import function {function} from {lib}"
if not isinstance(doc, str):
doc = ""
return doc
# TODO: try copying substitutions too, or autoreplace them ourselves
if output_notebook.__doc__ is not None: # if run with python -OO, __doc__ is stripped
output_notebook.__doc__ += "\n\n" + _copy_docstring(
"bokeh.plotting", "output_notebook"
).replace("|save|", "save").replace("|show|", "show")
output_file.__doc__ += "\n\n" + _copy_docstring("bokeh.plotting", "output_file").replace(
"|save|", "save"
).replace("|show|", "show")
ColumnDataSource.__doc__ += "\n\n" + _copy_docstring("bokeh.models", "ColumnDataSource")
