def refresh_source(self, ldf):
"""
Loading the source into the visualizations in the VisList, then populating each visualization
based on the new source data, effectively "materializing" the visualization collection.
Parameters
----------
ldf : LuxDataframe
Input Dataframe to be attached to the VisList
Returns
-------
VisList
Complete VisList with fully-specified fields
See Also
--------
lux.vis.Vis.refresh_source
Note
----
Function derives a new _inferred_intent by instantiating the intent specification on the new data
"""
if ldf is not None:
from lux.processor.Parser import Parser
from lux.processor.Validator import Validator
from lux.processor.Compiler import Compiler
self._source = ldf
self._source.maintain_metadata()
if len(self._input_lst) > 0:
approx = False
if self._is_vis_input():
compiled_collection = []
for vis in self._collection:
vis._inferred_intent = Parser.parse(vis._intent)
Validator.validate_intent(vis._inferred_intent, ldf)
Compiler.compile_vis(ldf, vis)
compiled_collection.append(vis)
self._collection = compiled_collection
else:
self._inferred_intent = Parser.parse(self._intent)
Validator.validate_intent(self._inferred_intent, ldf)
self._collection = Compiler.compile_intent(
ldf, self._inferred_intent)
# Early pruning determination criteria
width_criteria = len(self._collection) > (lux.config.topk + 3)
length_criteria = len(
ldf) > lux.config.early_pruning_sample_start
if lux.config.early_pruning and width_criteria and length_criteria:
# print("Apply approx to this VisList")
ldf._message.add_unique(
"Large search space detected: Lux is approximating the interestingness of recommended visualizations.",
priority=1,
)
approx = True
lux.config.executor.execute(self._collection,
ldf,
approx=approx)
def _parse_validate_compile_intent(self):
from lux.processor.Parser import Parser
from lux.processor.Validator import Validator
self._intent = Parser.parse(self._intent)
Validator.validate_intent(self._intent, self)
self.maintain_metadata()
from lux.processor.Compiler import Compiler
self.current_vis = Compiler.compile_intent(self, self._intent)
def refresh_source(self, ldf):
"""
Loading the source into the visualizations in the VisList, then populating each visualization
based on the new source data, effectively "materializing" the visualization collection.
Parameters
----------
ldf : LuxDataframe
Input Dataframe to be attached to the VisList
Returns
-------
VisList
Complete VisList with fully-specified fields
See Also
--------
lux.vis.Vis.refresh_source
Note
----
Function derives a new _inferred_intent by instantiating the intent specification on the new data
"""
if (ldf is not None):
from lux.processor.Parser import Parser
from lux.processor.Validator import Validator
from lux.processor.Compiler import Compiler
self._source = ldf
self._source.maintain_metadata()
if len(self._input_lst) > 0:
if (self._is_vis_input()):
compiled_collection = []
for vis in self._collection:
vis._inferred_intent = Parser.parse(vis._intent)
Validator.validate_intent(vis._inferred_intent, ldf)
vislist = Compiler.compile_vis(ldf, vis)
if (len(vislist) > 0):
vis = vislist[0]
compiled_collection.append(vis)
self._collection = compiled_collection
else:
self._inferred_intent = Parser.parse(self._intent)
Validator.validate_intent(self._inferred_intent, ldf)
self._collection = Compiler.compile_intent(
ldf, self._inferred_intent)
ldf.executor.execute(self._collection, ldf)
def refresh_source(self, ldf): # -> Vis:
"""
Loading the source data into the Vis by instantiating the specification and
populating the Vis based on the source data, effectively "materializing" the Vis.
Parameters
----------
ldf : LuxDataframe
Input Dataframe to be attached to the Vis
Returns
-------
Vis
Complete Vis with fully-specified fields
See Also
--------
lux.Vis.VisList.refresh_source
Note
----
Function derives a new _inferred_intent by instantiating the intent specification on the new data
"""
if ldf is not None:
from lux.processor.Parser import Parser
from lux.processor.Validator import Validator
from lux.processor.Compiler import Compiler
from lux.executor.PandasExecutor import (
PandasExecutor,
) # TODO: temporary (generalize to executor)
self.check_not_vislist_intent()
ldf.maintain_metadata()
self._source = ldf
self._inferred_intent = Parser.parse(self._intent)
Validator.validate_intent(self._inferred_intent, ldf)
vlist = Compiler.compile_vis(ldf, self)
ldf.executor.execute(vlist, ldf)
# Copying properties over since we can not redefine `self` within class function
if len(vlist) > 0:
vis = vlist[0]
self.title = vis.title
self._mark = vis._mark
self._inferred_intent = vis._inferred_intent
self._vis_data = vis.data
self._min_max = vis._min_max
def refresh_source(self, ldf): # -> Vis:
"""
Loading the source data into the Vis by instantiating the specification and
populating the Vis based on the source data, effectively "materializing" the Vis.
Parameters
----------
ldf : LuxDataframe
Input Dataframe to be attached to the Vis
Returns
-------
Vis
Complete Vis with fully-specified fields
See Also
--------
lux.Vis.VisList.refresh_source
Note
----
Function derives a new _inferred_intent by instantiating the intent specification on the new data
"""
if ldf is not None:
from lux.processor.Parser import Parser
from lux.processor.Validator import Validator
from lux.processor.Compiler import Compiler
self.check_not_vislist_intent()
ldf.maintain_metadata()
self._source = ldf
self._inferred_intent = Parser.parse(self._intent)
Validator.validate_intent(self._inferred_intent, ldf)
Compiler.compile_vis(ldf, self)
lux.config.executor.execute([self], ldf)
