def setUp(self):
self.data_dict = {
'ItemA' : panel_data1(),
'ItemB' : panel_data2(),
'ItemC' : panel_data3(),
'ItemD' : panel_data1(),
}
self.panel = SparseWidePanel(self.data_dict)
def setUp(self):
self.data_dict = {
"ItemA": panel_data1(),
"ItemB": panel_data2(),
"ItemC": panel_data3(),
"ItemD": panel_data1(),
}
self.panel = SparseWidePanel(self.data_dict)
def test_from_dict(self):
fd = SparseWidePanel.from_dict(self.data_dict)
assert_sp_panel_equal(fd, self.panel)
class TestSparseWidePanel(TestCase,
test_panel.SafeForLongAndSparse,
test_panel.SafeForSparse):
@staticmethod
def assert_panel_equal(x, y):
assert_sp_panel_equal(x, y)
def setUp(self):
self.data_dict = {
'ItemA' : panel_data1(),
'ItemB' : panel_data2(),
'ItemC' : panel_data3(),
'ItemD' : panel_data1(),
}
self.panel = SparseWidePanel(self.data_dict)
@staticmethod
def _test_op(panel, op):
# arithmetic tests
result = op(panel, 1)
assert_sp_frame_equal(result['ItemA'], op(panel['ItemA'], 1))
def test_constructor(self):
self.assertRaises(Exception, SparseWidePanel, self.data_dict,
items=['Item0', 'ItemA', 'ItemB'])
def test_from_dict(self):
fd = SparseWidePanel.from_dict(self.data_dict)
assert_sp_panel_equal(fd, self.panel)
def test_pickle(self):
def _test_roundtrip(panel):
pickled = pickle.dumps(panel, protocol=pickle.HIGHEST_PROTOCOL)
unpickled = pickle.loads(pickled)
assert_sp_panel_equal(panel, unpickled)
_test_roundtrip(self.panel)
def test_dense_to_sparse(self):
wp = WidePanel.from_dict(self.data_dict)
dwp = wp.to_sparse()
self.assert_(isinstance(dwp['ItemA']['A'], SparseSeries))
def test_to_dense(self):
dwp = self.panel.to_dense()
dwp2 = WidePanel.from_dict(self.data_dict)
assert_panel_equal(dwp, dwp2)
def test_to_long(self):
def _compare_with_dense(panel):
slp = panel.to_long()
dlp = panel.to_dense().to_long()
self.assert_(np.array_equal(slp.values, dlp.values))
self.assert_(np.array_equal(slp.major_labels,
dlp.major_labels))
self.assert_(np.array_equal(slp.minor_labels,
dlp.minor_labels))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
zero_panel = SparseWidePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_long)
self.assertRaises(Exception, self.panel.to_long,
filter_observations=False)
def test_long_to_wide_sparse(self):
pass
def test_values(self):
pass
def test_setitem(self):
self.panel['ItemE'] = self.panel['ItemC']
self.panel['ItemF'] = self.panel['ItemC'].to_dense()
assert_sp_frame_equal(self.panel['ItemE'], self.panel['ItemC'])
assert_sp_frame_equal(self.panel['ItemF'], self.panel['ItemC'])
assert_almost_equal(self.panel.items, ['ItemA', 'ItemB', 'ItemC',
'ItemD', 'ItemE', 'ItemF'])
self.assertRaises(Exception, self.panel.__setitem__, 'item6', 1)
def test_delitem_pop(self):
del self.panel['ItemB']
assert_almost_equal(self.panel.items, ['ItemA', 'ItemC', 'ItemD'])
crackle = self.panel['ItemC']
pop = self.panel.pop('ItemC')
self.assert_(pop is crackle)
assert_almost_equal(self.panel.items, ['ItemA', 'ItemD'])
self.assertRaises(KeyError, self.panel.__delitem__, 'ItemC')
def test_copy(self):
cop = self.panel.copy()
assert_sp_panel_equal(cop, self.panel)
def test_reindex(self):
def _compare_with_dense(swp, items, major, minor):
swp_re = swp.reindex(items=items, major=major,
minor=minor)
dwp_re = swp.to_dense().reindex(items=items, major=major,
minor=minor)
assert_panel_equal(swp_re.to_dense(), dwp_re)
_compare_with_dense(self.panel, self.panel.items[:2],
self.panel.major_axis[::2],
self.panel.minor_axis[::2])
_compare_with_dense(self.panel, None,
self.panel.major_axis[::2],
self.panel.minor_axis[::2])
self.assertRaises(ValueError, self.panel.reindex)
# TODO: do something about this later...
self.assertRaises(Exception, self.panel.reindex,
items=['item0', 'ItemA', 'ItemB'])
def test_operators(self):
def _check_ops(panel):
def _dense_comp(op):
dense = panel.to_dense()
sparse_result = op(panel)
dense_result = op(dense)
assert_panel_equal(sparse_result.to_dense(), dense_result)
op1 = lambda x: x + 2
_dense_comp(op1)
op2 = lambda x: x.add(x.reindex(major=x.major_axis[::2]))
_dense_comp(op2)
op3 = lambda x: x.subtract(x.mean(0), axis=0)
_dense_comp(op3)
op4 = lambda x: x.subtract(x.mean(1), axis=1)
_dense_comp(op4)
op5 = lambda x: x.subtract(x.mean(2), axis=2)
_dense_comp(op5)
# TODO: this case not yet supported!
# op6 = lambda x: x.add(x.to_long())
# _dense_comp(op6)
_check_ops(self.panel)
def test_major_xs(self):
def _dense_comp(sparse):
dense = sparse.to_dense()
for idx in sparse.major_axis:
dslice = dense.major_xs(idx)
sslice = sparse.major_xs(idx)
assert_frame_equal(dslice, sslice)
_dense_comp(self.panel)
def test_minor_xs(self):
def _dense_comp(sparse):
dense = sparse.to_dense()
for idx in sparse.minor_axis:
dslice = dense.minor_xs(idx)
sslice = sparse.minor_xs(idx).to_dense()
assert_frame_equal(dslice, sslice)
_dense_comp(self.panel)
