3RNN/Lib/site-packages/sklearn/utils/_estimator_html_repr.py
2024-05-26 19:49:15 +02:00

497 lines
18 KiB
Python

import html
import itertools
from contextlib import closing
from inspect import isclass
from io import StringIO
from pathlib import Path
from string import Template
from .. import __version__, config_context
from .fixes import parse_version
class _IDCounter:
"""Generate sequential ids with a prefix."""
def __init__(self, prefix):
self.prefix = prefix
self.count = 0
def get_id(self):
self.count += 1
return f"{self.prefix}-{self.count}"
def _get_css_style():
return Path(__file__).with_suffix(".css").read_text(encoding="utf-8")
_CONTAINER_ID_COUNTER = _IDCounter("sk-container-id")
_ESTIMATOR_ID_COUNTER = _IDCounter("sk-estimator-id")
_CSS_STYLE = _get_css_style()
class _VisualBlock:
"""HTML Representation of Estimator
Parameters
----------
kind : {'serial', 'parallel', 'single'}
kind of HTML block
estimators : list of estimators or `_VisualBlock`s or a single estimator
If kind != 'single', then `estimators` is a list of
estimators.
If kind == 'single', then `estimators` is a single estimator.
names : list of str, default=None
If kind != 'single', then `names` corresponds to estimators.
If kind == 'single', then `names` is a single string corresponding to
the single estimator.
name_details : list of str, str, or None, default=None
If kind != 'single', then `name_details` corresponds to `names`.
If kind == 'single', then `name_details` is a single string
corresponding to the single estimator.
dash_wrapped : bool, default=True
If true, wrapped HTML element will be wrapped with a dashed border.
Only active when kind != 'single'.
"""
def __init__(
self, kind, estimators, *, names=None, name_details=None, dash_wrapped=True
):
self.kind = kind
self.estimators = estimators
self.dash_wrapped = dash_wrapped
if self.kind in ("parallel", "serial"):
if names is None:
names = (None,) * len(estimators)
if name_details is None:
name_details = (None,) * len(estimators)
self.names = names
self.name_details = name_details
def _sk_visual_block_(self):
return self
def _write_label_html(
out,
name,
name_details,
outer_class="sk-label-container",
inner_class="sk-label",
checked=False,
doc_link="",
is_fitted_css_class="",
is_fitted_icon="",
):
"""Write labeled html with or without a dropdown with named details.
Parameters
----------
out : file-like object
The file to write the HTML representation to.
name : str
The label for the estimator. It corresponds either to the estimator class name
for a simple estimator or in the case of a `Pipeline` and `ColumnTransformer`,
it corresponds to the name of the step.
name_details : str
The details to show as content in the dropdown part of the toggleable label. It
can contain information such as non-default parameters or column information for
`ColumnTransformer`.
outer_class : {"sk-label-container", "sk-item"}, default="sk-label-container"
The CSS class for the outer container.
inner_class : {"sk-label", "sk-estimator"}, default="sk-label"
The CSS class for the inner container.
checked : bool, default=False
Whether the dropdown is folded or not. With a single estimator, we intend to
unfold the content.
doc_link : str, default=""
The link to the documentation for the estimator. If an empty string, no link is
added to the diagram. This can be generated for an estimator if it uses the
`_HTMLDocumentationLinkMixin`.
is_fitted_css_class : {"", "fitted"}
The CSS class to indicate whether or not the estimator is fitted. The
empty string means that the estimator is not fitted and "fitted" means that the
estimator is fitted.
is_fitted_icon : str, default=""
The HTML representation to show the fitted information in the diagram. An empty
string means that no information is shown.
"""
# we need to add some padding to the left of the label to be sure it is centered
padding_label = " " if is_fitted_icon else "" # add padding for the "i" char
out.write(
f'<div class="{outer_class}"><div'
f' class="{inner_class} {is_fitted_css_class} sk-toggleable">'
)
name = html.escape(name)
if name_details is not None:
name_details = html.escape(str(name_details))
label_class = (
f"sk-toggleable__label {is_fitted_css_class} sk-toggleable__label-arrow"
)
checked_str = "checked" if checked else ""
est_id = _ESTIMATOR_ID_COUNTER.get_id()
if doc_link:
doc_label = "<span>Online documentation</span>"
if name is not None:
doc_label = f"<span>Documentation for {name}</span>"
doc_link = (
f'<a class="sk-estimator-doc-link {is_fitted_css_class}"'
f' rel="noreferrer" target="_blank" href="{doc_link}">?{doc_label}</a>'
)
padding_label += "&nbsp;" # add additional padding for the "?" char
fmt_str = (
'<input class="sk-toggleable__control sk-hidden--visually"'
f' id="{est_id}" '
f'type="checkbox" {checked_str}><label for="{est_id}" '
f'class="{label_class} {is_fitted_css_class}">{padding_label}{name}'
f"{doc_link}{is_fitted_icon}</label><div "
f'class="sk-toggleable__content {is_fitted_css_class}">'
f"<pre>{name_details}</pre></div> "
)
out.write(fmt_str)
else:
out.write(f"<label>{name}</label>")
out.write("</div></div>") # outer_class inner_class
def _get_visual_block(estimator):
"""Generate information about how to display an estimator."""
if hasattr(estimator, "_sk_visual_block_"):
try:
return estimator._sk_visual_block_()
except Exception:
return _VisualBlock(
"single",
estimator,
names=estimator.__class__.__name__,
name_details=str(estimator),
)
if isinstance(estimator, str):
return _VisualBlock(
"single", estimator, names=estimator, name_details=estimator
)
elif estimator is None:
return _VisualBlock("single", estimator, names="None", name_details="None")
# check if estimator looks like a meta estimator (wraps estimators)
if hasattr(estimator, "get_params") and not isclass(estimator):
estimators = [
(key, est)
for key, est in estimator.get_params(deep=False).items()
if hasattr(est, "get_params") and hasattr(est, "fit") and not isclass(est)
]
if estimators:
return _VisualBlock(
"parallel",
[est for _, est in estimators],
names=[f"{key}: {est.__class__.__name__}" for key, est in estimators],
name_details=[str(est) for _, est in estimators],
)
return _VisualBlock(
"single",
estimator,
names=estimator.__class__.__name__,
name_details=str(estimator),
)
def _write_estimator_html(
out,
estimator,
estimator_label,
estimator_label_details,
is_fitted_css_class,
is_fitted_icon="",
first_call=False,
):
"""Write estimator to html in serial, parallel, or by itself (single).
For multiple estimators, this function is called recursively.
Parameters
----------
out : file-like object
The file to write the HTML representation to.
estimator : estimator object
The estimator to visualize.
estimator_label : str
The label for the estimator. It corresponds either to the estimator class name
for simple estimator or in the case of `Pipeline` and `ColumnTransformer`, it
corresponds to the name of the step.
estimator_label_details : str
The details to show as content in the dropdown part of the toggleable label.
It can contain information as non-default parameters or column information for
`ColumnTransformer`.
is_fitted_css_class : {"", "fitted"}
The CSS class to indicate whether or not the estimator is fitted or not. The
empty string means that the estimator is not fitted and "fitted" means that the
estimator is fitted.
is_fitted_icon : str, default=""
The HTML representation to show the fitted information in the diagram. An empty
string means that no information is shown. If the estimator to be shown is not
the first estimator (i.e. `first_call=False`), `is_fitted_icon` is always an
empty string.
first_call : bool, default=False
Whether this is the first time this function is called.
"""
if first_call:
est_block = _get_visual_block(estimator)
else:
is_fitted_icon = ""
with config_context(print_changed_only=True):
est_block = _get_visual_block(estimator)
# `estimator` can also be an instance of `_VisualBlock`
if hasattr(estimator, "_get_doc_link"):
doc_link = estimator._get_doc_link()
else:
doc_link = ""
if est_block.kind in ("serial", "parallel"):
dashed_wrapped = first_call or est_block.dash_wrapped
dash_cls = " sk-dashed-wrapped" if dashed_wrapped else ""
out.write(f'<div class="sk-item{dash_cls}">')
if estimator_label:
_write_label_html(
out,
estimator_label,
estimator_label_details,
doc_link=doc_link,
is_fitted_css_class=is_fitted_css_class,
is_fitted_icon=is_fitted_icon,
)
kind = est_block.kind
out.write(f'<div class="sk-{kind}">')
est_infos = zip(est_block.estimators, est_block.names, est_block.name_details)
for est, name, name_details in est_infos:
if kind == "serial":
_write_estimator_html(
out,
est,
name,
name_details,
is_fitted_css_class=is_fitted_css_class,
)
else: # parallel
out.write('<div class="sk-parallel-item">')
# wrap element in a serial visualblock
serial_block = _VisualBlock("serial", [est], dash_wrapped=False)
_write_estimator_html(
out,
serial_block,
name,
name_details,
is_fitted_css_class=is_fitted_css_class,
)
out.write("</div>") # sk-parallel-item
out.write("</div></div>")
elif est_block.kind == "single":
_write_label_html(
out,
est_block.names,
est_block.name_details,
outer_class="sk-item",
inner_class="sk-estimator",
checked=first_call,
doc_link=doc_link,
is_fitted_css_class=is_fitted_css_class,
is_fitted_icon=is_fitted_icon,
)
def estimator_html_repr(estimator):
"""Build a HTML representation of an estimator.
Read more in the :ref:`User Guide <visualizing_composite_estimators>`.
Parameters
----------
estimator : estimator object
The estimator to visualize.
Returns
-------
html: str
HTML representation of estimator.
Examples
--------
>>> from sklearn.utils._estimator_html_repr import estimator_html_repr
>>> from sklearn.linear_model import LogisticRegression
>>> estimator_html_repr(LogisticRegression())
'<style>...</div>'
"""
from sklearn.exceptions import NotFittedError
from sklearn.utils.validation import check_is_fitted
if not hasattr(estimator, "fit"):
status_label = "<span>Not fitted</span>"
is_fitted_css_class = ""
else:
try:
check_is_fitted(estimator)
status_label = "<span>Fitted</span>"
is_fitted_css_class = "fitted"
except NotFittedError:
status_label = "<span>Not fitted</span>"
is_fitted_css_class = ""
is_fitted_icon = (
f'<span class="sk-estimator-doc-link {is_fitted_css_class}">'
f"i{status_label}</span>"
)
with closing(StringIO()) as out:
container_id = _CONTAINER_ID_COUNTER.get_id()
style_template = Template(_CSS_STYLE)
style_with_id = style_template.substitute(id=container_id)
estimator_str = str(estimator)
# The fallback message is shown by default and loading the CSS sets
# div.sk-text-repr-fallback to display: none to hide the fallback message.
#
# If the notebook is trusted, the CSS is loaded which hides the fallback
# message. If the notebook is not trusted, then the CSS is not loaded and the
# fallback message is shown by default.
#
# The reverse logic applies to HTML repr div.sk-container.
# div.sk-container is hidden by default and the loading the CSS displays it.
fallback_msg = (
"In a Jupyter environment, please rerun this cell to show the HTML"
" representation or trust the notebook. <br />On GitHub, the"
" HTML representation is unable to render, please try loading this page"
" with nbviewer.org."
)
html_template = (
f"<style>{style_with_id}</style>"
f'<div id="{container_id}" class="sk-top-container">'
'<div class="sk-text-repr-fallback">'
f"<pre>{html.escape(estimator_str)}</pre><b>{fallback_msg}</b>"
"</div>"
'<div class="sk-container" hidden>'
)
out.write(html_template)
_write_estimator_html(
out,
estimator,
estimator.__class__.__name__,
estimator_str,
first_call=True,
is_fitted_css_class=is_fitted_css_class,
is_fitted_icon=is_fitted_icon,
)
out.write("</div></div>")
html_output = out.getvalue()
return html_output
class _HTMLDocumentationLinkMixin:
"""Mixin class allowing to generate a link to the API documentation.
This mixin relies on three attributes:
- `_doc_link_module`: it corresponds to the root module (e.g. `sklearn`). Using this
mixin, the default value is `sklearn`.
- `_doc_link_template`: it corresponds to the template used to generate the
link to the API documentation. Using this mixin, the default value is
`"https://scikit-learn.org/{version_url}/modules/generated/
{estimator_module}.{estimator_name}.html"`.
- `_doc_link_url_param_generator`: it corresponds to a function that generates the
parameters to be used in the template when the estimator module and name are not
sufficient.
The method :meth:`_get_doc_link` generates the link to the API documentation for a
given estimator.
This useful provides all the necessary states for
:func:`sklearn.utils.estimator_html_repr` to generate a link to the API
documentation for the estimator HTML diagram.
Examples
--------
If the default values for `_doc_link_module`, `_doc_link_template` are not suitable,
then you can override them:
>>> from sklearn.base import BaseEstimator
>>> estimator = BaseEstimator()
>>> estimator._doc_link_template = "https://website.com/{single_param}.html"
>>> def url_param_generator(estimator):
... return {"single_param": estimator.__class__.__name__}
>>> estimator._doc_link_url_param_generator = url_param_generator
>>> estimator._get_doc_link()
'https://website.com/BaseEstimator.html'
"""
_doc_link_module = "sklearn"
_doc_link_url_param_generator = None
@property
def _doc_link_template(self):
sklearn_version = parse_version(__version__)
if sklearn_version.dev is None:
version_url = f"{sklearn_version.major}.{sklearn_version.minor}"
else:
version_url = "dev"
return getattr(
self,
"__doc_link_template",
(
f"https://scikit-learn.org/{version_url}/modules/generated/"
"{estimator_module}.{estimator_name}.html"
),
)
@_doc_link_template.setter
def _doc_link_template(self, value):
setattr(self, "__doc_link_template", value)
def _get_doc_link(self):
"""Generates a link to the API documentation for a given estimator.
This method generates the link to the estimator's documentation page
by using the template defined by the attribute `_doc_link_template`.
Returns
-------
url : str
The URL to the API documentation for this estimator. If the estimator does
not belong to module `_doc_link_module`, the empty string (i.e. `""`) is
returned.
"""
if self.__class__.__module__.split(".")[0] != self._doc_link_module:
return ""
if self._doc_link_url_param_generator is None:
estimator_name = self.__class__.__name__
# Construct the estimator's module name, up to the first private submodule.
# This works because in scikit-learn all public estimators are exposed at
# that level, even if they actually live in a private sub-module.
estimator_module = ".".join(
itertools.takewhile(
lambda part: not part.startswith("_"),
self.__class__.__module__.split("."),
)
)
return self._doc_link_template.format(
estimator_module=estimator_module, estimator_name=estimator_name
)
return self._doc_link_template.format(
**self._doc_link_url_param_generator(self)
)