def enumerate_collection(_inferred_intent: List[Clause],
ldf: LuxDataFrame) -> VisList:
"""
Given specifications that have been expanded thorught populateOptions,
recursively iterate over the resulting list combinations to generate a vis list.
Parameters
----------
ldf : lux.luxDataFrame.LuxDataFrame
LuxDataFrame with underspecified intent.
Returns
-------
VisList: list[lux.Vis]
vis list with compiled lux.Vis objects.
"""
import copy
intent = Compiler.populate_wildcard_options(_inferred_intent, ldf)
attributes = intent['attributes']
filters = intent['filters']
if len(attributes) == 0 and len(filters) > 0:
ldf.filter_specs = filters
return []
collection = []
# TODO: generate combinations of column attributes recursively by continuing to accumulate attributes for len(colAtrr) times
def combine(col_attrs, accum):
last = (len(col_attrs) == 1)
n = len(col_attrs[0])
for i in range(n):
column_list = copy.deepcopy(accum + [col_attrs[0][i]])
if last:
if len(
filters
) > 0: # if we have filters, generate combinations for each row.
for row in filters:
_inferred_intent = copy.deepcopy(column_list +
[row])
vis = Vis(
_inferred_intent,
title=
f"{row.attribute} {row.filter_op} {row.value}")
collection.append(vis)
else:
vis = Vis(column_list)
collection.append(vis)
else:
combine(col_attrs[1:], column_list)
combine(attributes, [])
return VisList(collection)
def enumerateCollection(specLst: List[Spec],
ldf: LuxDataFrame) -> ViewCollection:
"""
Given specifications that have been expanded thorught populateOptions,
recursively iterate over the resulting list combinations to generate a View collection.
Parameters
----------
ldf : lux.luxDataFrame.LuxDataFrame
LuxDataFrame with underspecified context.
Returns
-------
ViewCollection: list[lux.View]
view collection with compiled lux.View objects.
"""
import copy
specs = Compiler.populateWildcardOptions(specLst, ldf)
attributes = specs['attributes']
filters = specs['filters']
if len(attributes) == 0 and len(filters) > 0:
ldf.filterSpecs = filters
return []
collection = []
# TODO: generate combinations of column attributes recursively by continuing to accumulate attributes for len(colAtrr) times
def combine(colAttrs, accum):
last = (len(colAttrs) == 1)
n = len(colAttrs[0])
for i in range(n):
columnList = copy.deepcopy(accum + [colAttrs[0][i]])
if last:
if len(
filters
) > 0: # if we have filters, generate combinations for each row.
for row in filters:
specLst = copy.deepcopy(columnList + [row])
view = View(
specLst,
title=
f"{row.attribute} {row.filterOp} {row.value}")
collection.append(view)
else:
view = View(columnList)
collection.append(view)
else:
combine(colAttrs[1:], columnList)
combine(attributes, [])
return ViewCollection(collection)
def _repr_html_(self):
from IPython.display import display
check_import_lux_widget()
import luxWidget
if (self.data is None):
raise Exception(
"No data is populated in Vis. In order to generate data required for the vis, use the 'refresh_source' function to populate the Vis with a data source (e.g., vis.refresh_source(df))."
)
else:
from lux.luxDataFrame.LuxDataframe import LuxDataFrame
widget = luxWidget.LuxWidget(
currentVis=LuxDataFrame.current_view_to_JSON([self]),
recommendations=[],
intent="")
display(widget)
def _repr_html_(self):
from IPython.display import display
check_import_lux_widget()
import luxWidget
if (self.data is None):
raise Exception("No data populated in View. Use the 'load' function (e.g., view.load(df)) to populate the view with a data source.")
else:
from lux.luxDataFrame.LuxDataframe import LuxDataFrame
# widget = LuxDataFrame.render_widget(input_current_view=self,render_target="viewOnly")
widget = luxWidget.LuxWidget(
currentView= LuxDataFrame.current_view_to_JSON([self]),
recommendations=[],
context={}
)
display(widget)
def _repr_html_(self):
self.widget = None
from IPython.display import display
from lux.luxDataFrame.LuxDataframe import LuxDataFrame
# widget = LuxDataFrame.renderWidget(inputCurrentView=self,renderTarget="viewCollectionOnly")
recommendation = {
"action": "View Collection",
"description": "Shows a view collection defined by the context"
}
recommendation["collection"] = self
checkImportLuxWidget()
import luxWidget
recJSON = LuxDataFrame.recToJSON([recommendation])
self.widget = luxWidget.LuxWidget(currentView={},
recommendations=recJSON,
context={})
display(self.widget)
def pandas_to_lux(df):
from lux.luxDataFrame.LuxDataframe import LuxDataFrame
values = df.values.tolist()
ldf = LuxDataFrame(values, columns=df.columns)
return (ldf)