def test_LearnDataProxyModel():
"""Test class RadioButtonModel"""
from clair.qtgui import LearnDataProxyModel, ListingsModel
from clair.coredata import make_listing_frame, DataStore
csr = Qt.CheckStateRole
#Create test data
listings = make_listing_frame(1)
#Product "foo" is present, "bar" absent, nothing is known about "baz"
listings["expected_products"][0] = ["foo", "bar", "baz"]
listings["products"][0] = ["foo"]
listings["products_absent"][0] = ["bar"]
data_store = DataStore()
data_store.merge_listings(listings)
#Create listings model that we can adapt
lsmod = ListingsModel()
lsmod.setDataStore(data_store)
mo = LearnDataProxyModel()
mo.setListingsModel(lsmod, 3, 4, 5)
mo.setRow(lsmod.index(0, 0))
print mo.values
#Test size
assert mo.columnCount() == 4
assert mo.rowCount() == 4 #includes additional empty row
#Test data conversion
#1st row: [True, False, "foo", ...]
assert bool(mo.data(mo.index(0, 0), csr)) == True
assert bool(mo.data(mo.index(0, 1), csr)) == False
assert mo.data(mo.index(0, 2)) == "foo"
#2nd row: [False, True, "bar", ...]
assert bool(mo.data(mo.index(1, 0), csr)) == False
assert bool(mo.data(mo.index(1, 1), csr)) == True
assert mo.data(mo.index(1, 2)) == "bar"
#3rd row: [False, False, "baz", ...]
assert bool(mo.data(mo.index(2, 0), csr)) == False
assert bool(mo.data(mo.index(2, 1), csr)) == False
assert mo.data(mo.index(2, 2)) == "baz"
#Change the data
mo.setData(mo.index(0, 0), False, csr)
mo.setData(mo.index(1, 0), True, csr)
mo.setData(mo.index(2, 1), True, csr)
#Test conversion back to internal format
assert data_store.listings["expected_products"][0] == ["foo", "bar", "baz"]
assert data_store.listings["products"][0] == ["bar"]
assert data_store.listings["products_absent"][0] == ["baz"]
print "finished successfully."
def test_LearnDataProxyModel_GUI():
"""Test class RadioButtonModel"""
from clair.qtgui import LearnDataProxyModel, ListingsModel
from clair.coredata import make_listing_frame, DataStore
print "Start"
app = QApplication(sys.argv)
#Create test data
listings = make_listing_frame(1)
#Product "foo" is present, "bar" absent, nothing is known about "baz"
listings["expected_products"][0] = ["foo", "bar", "baz"]
listings["products"][0] = ["foo"]
listings["products_absent"][0] = ["bar"]
data_store = DataStore()
data_store.merge_listings(listings)
#Create listings model that we can adapt
lsmod = ListingsModel()
lsmod.setDataStore(data_store)
mo = LearnDataProxyModel()
mo.setListingsModel(lsmod, 3, 4, 5)
mo.setRow(lsmod.index(0, 0))
view = QTreeView()
view.setModel(mo)
view.show()
app.exec_()
print mo.values
print "expectedProducts:", data_store.listings["expected_products"][0]
print "products: ", data_store.listings["products"][0]
print "productsAbsent: ", data_store.listings["products_absent"][0]
print "End"