Source code for lux.action.custom

#  Copyright 2019-2020 The Lux Authors.
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#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
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#      http://www.apache.org/licenses/LICENSE-2.0
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from lux.interestingness.interestingness import interestingness
import lux
from lux.executor.PandasExecutor import PandasExecutor
from lux.executor.SQLExecutor import SQLExecutor
import lux


[docs]def custom(ldf): """ Generates user-defined vis based on the intent. Parameters ---------- ldf : lux.core.frame LuxDataFrame with underspecified intent. Returns ------- recommendations : Dict[str,obj] object with a collection of visualizations that result from the Distribution action. """ recommendation = { "action": "Current Vis", "description": "Shows the list of visualizations generated based on user specified intent", "long_description": "Shows the list of visualizations generated based on user specified intent", } recommendation["collection"] = ldf.current_vis vlist = ldf.current_vis lux.config.executor.execute(vlist, ldf) for vis in vlist: vis.score = interestingness(vis, ldf) # ldf.clear_intent() vlist.sort(remove_invalid=True) return recommendation
[docs]def custom_actions(ldf): """ Generates user-defined vis based on globally defined actions. Parameters ---------- ldf : lux.core.frame LuxDataFrame with underspecified intent. Returns ------- recommendations : Dict[str,obj] object with a collection of visualizations that were previously registered. """ if len(lux.config.actions) > 0 and (len(ldf) > 0 or lux.config.executor.name != "PandasExecutor"): recommendations = [] for action_name in lux.config.actions.keys(): display_condition = lux.config.actions[action_name].display_condition if display_condition is None or (display_condition is not None and display_condition(ldf)): args = lux.config.actions[action_name].args if args: recommendation = lux.config.actions[action_name].action(ldf, args) else: recommendation = lux.config.actions[action_name].action(ldf) recommendations.append(recommendation) return recommendations else: return []