Skip to content

Commit

Permalink
obsolete/owtable: Reuse common summary formating
Browse files Browse the repository at this point in the history
  • Loading branch information
@ales-erjavec
ales-erjavec committed Feb 24, 2023
1 parent e38244a commit 338f4ae
Showing 1 changed file with 9 additions and 140 deletions.
149 changes: 9 additions & 140 deletions Orange/widgets/obsolete/owtable.py
View file
Original file line number Diff line number Diff line change
@@ -1,4 +1,3 @@
import threading
import itertools
import concurrent.futures

Expand All @@ -18,10 +17,8 @@
from AnyQt.QtCore import pyqtSlot as Slot

import Orange.data
from Orange.data.storage import Storage
from Orange.data.table import Table
from Orange.data.sql.table import SqlTable
from Orange.statistics import basic_stats

from Orange.widgets import gui
from Orange.widgets.data.utils.tableview import RichTableView
Expand All @@ -31,16 +28,14 @@
from Orange.widgets.utils.itemselectionmodel import (
BlockSelectionModel, ranges, selection_blocks
)
from Orange.widgets.utils.tableview import TableView, \
table_selection_to_mime_data
from Orange.widgets.utils.tableview import table_selection_to_mime_data
from Orange.widgets.utils.widgetpreview import WidgetPreview
from Orange.widgets.widget import OWWidget, MultiInput, Output, Msg
from Orange.widgets.utils import datacaching
from Orange.widgets.utils.localization import pl
from Orange.widgets.utils.annotated_data import (create_annotated_table,
ANNOTATED_DATA_SIGNAL_NAME)
from Orange.widgets.utils.itemmodels import TableModel
from Orange.widgets.utils.state_summary import format_summary_details
from Orange.widgets.data.utils import tablesummary as tsummary


TableSlot = namedtuple("TableSlot", ["input_id", "table", "summary", "view"])
Expand Down Expand Up @@ -178,7 +173,7 @@ def set_dataset(self, index: int, data: Table):
assert self.tabs.indexOf(view) != -1
self.tabs.setTabText(self.tabs.indexOf(view), datasetname)
view.dataset = data
slot = TableSlot(index, data, table_summary(data), view)
slot = TableSlot(index, data, tsummary.table_summary(data), view)
view.input_slot = slot
self._inputs[index] = slot
self._setup_table_view(view, data)
Expand All @@ -189,7 +184,7 @@ def set_dataset(self, index: int, data: Table):
def insert_dataset(self, index: int, data: Table):
datasetname = getattr(data, "name", "Data")
view = self._create_table_view()
slot = TableSlot(None, data, table_summary(data), view)
slot = TableSlot(None, data, tsummary.table_summary(data), view)
view.dataset = data
view.input_slot = slot
self._inputs.insert(index, slot)
Expand Down Expand Up @@ -310,10 +305,10 @@ def _setup_table_view(self, view, data):

def _set_input_summary(self, slot):
def format_summary(summary):
if isinstance(summary, ApproxSummary):
if isinstance(summary, tsummary.ApproxSummary):
length = summary.len.result() if summary.len.done() else \
summary.approx_len
elif isinstance(summary, Summary):
elif isinstance(summary, tsummary.Summary):
length = summary.len
return length

Expand All @@ -322,68 +317,11 @@ def format_summary(summary):
summary = format_summary(slot.summary)
details = format_summary_details(slot.table)
self.info.set_input_summary(summary, details)

self.info_text.setText("\n".join(self._info_box_text(slot)))

@staticmethod
def _info_box_text(slot):
def format_part(part):
if isinstance(part, DenseArray):
if not part.nans:
return ""
perc = 100 * part.nans / (part.nans + part.non_nans)
return f" ({perc:.1f} % missing data)"

if isinstance(part, SparseArray):
tag = "sparse"
elif isinstance(part, SparseBoolArray):
tag = "tags"
else: # isinstance(part, NotAvailable)
return ""
dens = 100 * part.non_nans / (part.nans + part.non_nans)
return f" ({tag}, density {dens:.2f} %)"

if slot is None:
return ["No data."]
summary = slot.summary
text = []
if isinstance(summary, ApproxSummary):
if summary.len.done():
ninst = summary.len.result()
text.append(f"{ninst} {pl(ninst, 'instance')}")
else:
ninst = summary.approx_len
text.append(f"~{ninst} {pl(ninst, 'instance')}")
elif isinstance(summary, Summary):
ninst = summary.len
text.append(f"{ninst} {pl(ninst, 'instance')}")
if sum(p.nans for p in [summary.X, summary.Y, summary.M]) == 0:
text[-1] += " (no missing data)"

nattrs = len(summary.domain.attributes)
text.append(f"{nattrs} {pl(nattrs, 'feature')}"
+ format_part(summary.X))

if not summary.domain.class_vars:
text.append("No target variable.")
summary = ["No data."]
else:
nclasses = len(summary.domain.class_vars)
if nclasses > 1:
c_text = f"{nclasses} {pl(nclasses, 'outcome')}"
elif summary.domain.has_continuous_class:
c_text = "Numeric outcome"
else:
nvalues = len(summary.domain.class_var.values)
c_text = f"Target with {nvalues} {pl(nvalues, 'value')}"
text.append(c_text + format_part(summary.Y))

nmetas = len(summary.domain.metas)
if nmetas:
text.append(f"{nmetas} {pl(nmetas, 'meta attribute')}"
+ format_part(summary.M))
else:
text.append("No meta attributes.")
return text
summary = tsummary.format_summary(slot.summary)
self.info_text.setText("\n".join(summary))

def _on_current_tab_changed(self, index):
"""Update the status bar on current tab change"""
Expand Down Expand Up @@ -590,75 +528,6 @@ def send_report(self):
self.report_table(view)


# Table Summary

# Basic statistics for X/Y/metas arrays
DenseArray = namedtuple(
"DenseArray", ["nans", "non_nans", "stats"])
SparseArray = namedtuple(
"SparseArray", ["nans", "non_nans", "stats"])
SparseBoolArray = namedtuple(
"SparseBoolArray", ["nans", "non_nans", "stats"])
NotAvailable = namedtuple("NotAvailable", [])

#: Orange.data.Table summary
Summary = namedtuple(
"Summary",
["len", "domain", "X", "Y", "M"])

#: Orange.data.sql.table.SqlTable summary
ApproxSummary = namedtuple(
"ApproxSummary",
["approx_len", "len", "domain", "X", "Y", "M"])


def table_summary(table):
if isinstance(table, SqlTable):
approx_len = table.approx_len()
len_future = concurrent.futures.Future()

def _len():
len_future.set_result(len(table))
threading.Thread(target=_len).start() # KILL ME !!!

return ApproxSummary(approx_len, len_future, table.domain,
NotAvailable(), NotAvailable(), NotAvailable())
else:
domain = table.domain
n_instances = len(table)
# dist = basic_stats.DomainBasicStats(table, include_metas=True)
bstats = datacaching.getCached(
table, basic_stats.DomainBasicStats, (table, True)
)

dist = bstats.stats
# pylint: disable=unbalanced-tuple-unpacking
X_dist, Y_dist, M_dist = numpy.split(
dist, numpy.cumsum([len(domain.attributes),
len(domain.class_vars)]))

def parts(array, density, col_dist):
array = numpy.atleast_2d(array)
nans = sum([dist.nans for dist in col_dist])
non_nans = sum([dist.non_nans for dist in col_dist])
if density == Storage.DENSE:
return DenseArray(nans, non_nans, col_dist)
elif density == Storage.SPARSE:
return SparseArray(nans, non_nans, col_dist)
elif density == Storage.SPARSE_BOOL:
return SparseBoolArray(nans, non_nans, col_dist)
elif density == Storage.MISSING:
return NotAvailable()
else:
assert False
return None

X_part = parts(table.X, table.X_density(), X_dist)
Y_part = parts(table.Y, table.Y_density(), Y_dist)
M_part = parts(table.metas, table.metas_density(), M_dist)
return Summary(n_instances, domain, X_part, Y_part, M_part)


def is_sortable(table):
if isinstance(table, SqlTable):
return False
Expand Down

0 comments on commit 338f4ae

Please sign in to comment.