def select_rows(self, identifiers, using_ids=True, change_current=True,
scroll=True):
'''
Select rows identified by identifiers. identifiers can be a set of ids,
row numbers or QModelIndexes.
'''
rows = set([x.row() if hasattr(x, 'row') else x for x in
identifiers])
if using_ids:
rows = set([])
identifiers = set(identifiers)
m = self.model()
for row in xrange(m.rowCount(QModelIndex())):
if m.id(row) in identifiers:
rows.add(row)
rows = list(sorted(rows))
if rows:
row = rows[0]
if change_current:
self.set_current_row(row, select=False)
if scroll:
self.scroll_to_row(row)
sm = self.selectionModel()
sel = QItemSelection()
m = self.model()
max_col = m.columnCount(QModelIndex()) - 1
# Create a range based selector for each set of contiguous rows
# as supplying selectors for each individual row causes very poor
# performance if a large number of rows has to be selected.
for k, g in itertools.groupby(enumerate(rows), lambda (i,x):i-x):
group = list(map(operator.itemgetter(1), g))
sel.merge(QItemSelection(m.index(min(group), 0),
m.index(max(group), max_col)), sm.Select)
def select_rows(self, identifiers, using_ids=True, change_current=True,
scroll=True):
'''
Select rows identified by identifiers. identifiers can be a set of ids,
row numbers or QModelIndexes.
'''
rows = set([x.row() if hasattr(x, 'row') else x for x in
identifiers])
if using_ids:
rows = set([])
identifiers = set(identifiers)
m = self.model()
for row in xrange(m.rowCount(QModelIndex())):
if m.id(row) in identifiers:
rows.add(row)
rows = list(sorted(rows))
if rows:
row = rows[0]
if change_current:
self.set_current_row(row, select=False)
if scroll:
self.scroll_to_row(row)
sm = self.selectionModel()
sel = QItemSelection()
m = self.model()
max_col = m.columnCount(QModelIndex()) - 1
# Create a range based selector for each set of contiguous rows
# as supplying selectors for each individual row causes very poor
# performance if a large number of rows has to be selected.
for k, g in itertools.groupby(enumerate(rows), lambda (i,x):i-x):
group = list(map(operator.itemgetter(1), g))
sel.merge(QItemSelection(m.index(min(group), 0),
m.index(max(group), max_col)), sm.Select)
def select_rows(self, rows):
sel = QItemSelection()
sm = self.selectionModel()
m = self.model()
# Create a range based selector for each set of contiguous rows
# as supplying selectors for each individual row causes very poor
# performance if a large number of rows has to be selected.
for k, g in itertools.groupby(enumerate(rows), lambda (i,x):i-x):
group = list(map(operator.itemgetter(1), g))
sel.merge(QItemSelection(m.index(min(group), 0), m.index(max(group), 0)), sm.Select)
def select_rows(self, rows):
sel = QItemSelection()
sm = self.selectionModel()
m = self.model()
# Create a range based selector for each set of contiguous rows
# as supplying selectors for each individual row causes very poor
# performance if a large number of rows has to be selected.
for k, g in itertools.groupby(enumerate(rows), lambda (i,x):i-x):
group = list(map(operator.itemgetter(1), g))
sel.merge(QItemSelection(m.index(min(group), 0), m.index(max(group), 0)), sm.Select)
