# Copyright 2019-2020 The Lux Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
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import lux
from lux.interestingness.interestingness import interestingness
from lux.processor.Compiler import Compiler
from lux.utils import utils
[docs]def enhance(ldf):
"""
Given a set of vis, generates possible visualizations when an additional attribute is added to the current vis.
Parameters
----------
ldf : lux.core.frame
LuxDataFrame with underspecified intent.
Returns
-------
recommendations : Dict[str,obj]
object with a collection of visualizations that result from the Enhance action.
"""
filters = utils.get_filter_specs(ldf._intent)
# Collect variables that already exist in the intent
attr_specs = list(filter(lambda x: x.value == "" and x.attribute != "Record", ldf._intent))
fltr_str = [fltr.attribute + fltr.filter_op + str(fltr.value) for fltr in filters]
attr_str = [str(clause.attribute) for clause in attr_specs]
intended_attrs = f'<p class="highlight-intent">{", ".join(attr_str + fltr_str)}</p>'
if len(attr_specs) == 1:
recommendation = {
"action": "Enhance",
"description": f"Augmenting current {intended_attrs} intent with additional attribute.",
"long_description": f"Enhance adds an additional attribute displaying how {intended_attrs} changes with respect to other attributes. Visualizations are ranked based on interestingness. The top 15 visualizations are displayed.",
}
elif len(attr_specs) == 2:
recommendation = {
"action": "Enhance",
"description": f"Further breaking down current {intended_attrs} intent by additional attribute.",
"long_description": f"Enhance adds an additional attribute as the color to break down the {intended_attrs} distribution",
}
# if there are too many column attributes, return don't generate Enhance recommendations
else:
recommendation = {"action": "Enhance"}
recommendation["collection"] = []
return recommendation
intent = ldf._intent.copy()
# Clear channel so that channel not enforced based on input vis intent
for clause in intent:
clause.channel = ""
intent = filters + attr_specs
intent.append("?")
vlist = lux.vis.VisList.VisList(intent, ldf)
# Then use the data populated in the vis list to compute score
for vis in vlist:
vis.score = interestingness(vis, ldf)
vlist.sort()
vlist = vlist.showK()
recommendation["collection"] = vlist
return recommendation