def setUp(self):
self.data_dict = {
'ItemA': panel_data1(),
'ItemB': panel_data2(),
'ItemC': panel_data3(),
'ItemD': panel_data1(),
}
self.panel = SparsePanel(self.data_dict)
def setUp(self):
self.data_dict = {
'ItemA': panel_data1(),
'ItemB': panel_data2(),
'ItemC': panel_data3(),
'ItemD': panel_data1(),
}
with tm.assert_produces_warning(FutureWarning):
self.panel = SparsePanel(self.data_dict)
def setUp(self):
self.data_dict = {
"ItemA": panel_data1(),
"ItemB": panel_data2(),
"ItemC": panel_data3(),
"ItemD": panel_data1(),
}
self.panel = SparsePanel(self.data_dict)
def test_constructor(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.assertRaises(ValueError, SparsePanel, self.data_dict,
items=['Item0', 'ItemA', 'ItemB'])
with tm.assertRaisesRegexp(TypeError,
"input must be a dict, a 'list' was "
"passed"):
SparsePanel(['a', 'b', 'c'])
def setUp(self):
self.data_dict = {
'ItemA' : panel_data1(),
'ItemB' : panel_data2(),
'ItemC' : panel_data3(),
'ItemD' : panel_data1(),
}
self.panel = SparsePanel(self.data_dict)
def setUp(self):
self.data_dict = {
'ItemA': panel_data1(),
'ItemB': panel_data2(),
'ItemC': panel_data3(),
'ItemD': panel_data1(),
}
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.panel = SparsePanel(self.data_dict)
def _read_sparse_panel(self, group, where=None):
default_fill_value = getattr(group._v_attrs, 'default_fill_value')
default_kind = getattr(group._v_attrs, 'default_kind')
items = self._read_index(group, 'items')
sdict = {}
for name in items:
key = 'sparse_frame_%s' % name
node = getattr(group, key)
sdict[name] = self._read_sparse_frame(node)
return SparsePanel(sdict, items=items, default_kind=default_kind,
default_fill_value=default_fill_value)
def test_to_frame(self):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_(np.array_equal(slp.values, dlp.values))
self.assert_(slp.index.equals(dlp.index))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception,
self.panel.to_frame,
filter_observations=False)
def test_to_frame(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_numpy_array_equal(slp.values, dlp.values)
self.assertTrue(slp.index.equals(dlp.index))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
with tm.assert_produces_warning(FutureWarning):
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception, self.panel.to_frame,
filter_observations=False)
def test_from_dict(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
fd = SparsePanel.from_dict(self.data_dict)
tm.assert_sp_panel_equal(fd, self.panel)
class TestSparsePanel(tm.TestCase, test_panel.SafeForLongAndSparse,
test_panel.SafeForSparse):
_multiprocess_can_split_ = True
def setUp(self):
self.data_dict = {
'ItemA': panel_data1(),
'ItemB': panel_data2(),
'ItemC': panel_data3(),
'ItemD': panel_data1(),
}
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.panel = SparsePanel(self.data_dict)
@staticmethod
def _test_op(panel, op):
# arithmetic tests
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = op(panel, 1)
tm.assert_sp_frame_equal(result['ItemA'], op(panel['ItemA'], 1))
def test_constructor(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.assertRaises(ValueError, SparsePanel, self.data_dict,
items=['Item0', 'ItemA', 'ItemB'])
with tm.assertRaisesRegexp(TypeError,
"input must be a dict, a 'list' was "
"passed"):
SparsePanel(['a', 'b', 'c'])
# deprecation GH11157
def test_deprecation(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
SparsePanel()
# GH 9272
def test_constructor_empty(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
sp = SparsePanel()
self.assertEqual(len(sp.items), 0)
self.assertEqual(len(sp.major_axis), 0)
self.assertEqual(len(sp.minor_axis), 0)
def test_from_dict(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
fd = SparsePanel.from_dict(self.data_dict)
tm.assert_sp_panel_equal(fd, self.panel)
def test_pickle(self):
def _test_roundtrip(panel):
result = self.round_trip_pickle(panel)
tm.assertIsInstance(result.items, Index)
tm.assertIsInstance(result.major_axis, Index)
tm.assertIsInstance(result.minor_axis, Index)
tm.assert_sp_panel_equal(panel, result)
_test_roundtrip(self.panel)
def test_dense_to_sparse(self):
wp = Panel.from_dict(self.data_dict)
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
dwp = wp.to_sparse()
tm.assertIsInstance(dwp['ItemA']['A'], SparseSeries)
def test_to_dense(self):
dwp = self.panel.to_dense()
dwp2 = Panel.from_dict(self.data_dict)
tm.assert_panel_equal(dwp, dwp2)
def test_to_frame(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_numpy_array_equal(slp.values, dlp.values)
self.assert_index_equal(slp.index, dlp.index,
check_names=False)
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception, self.panel.to_frame,
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()
tm.assert_sp_frame_equal(self.panel['ItemE'], self.panel['ItemC'])
tm.assert_sp_frame_equal(self.panel['ItemF'], self.panel['ItemC'])
expected = pd.Index(['ItemA', 'ItemB', 'ItemC',
'ItemD', 'ItemE', 'ItemF'])
tm.assert_index_equal(self.panel.items, expected)
self.assertRaises(Exception, self.panel.__setitem__, 'item6', 1)
def test_set_value(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
def _check_loc(item, major, minor, val=1.5):
res = self.panel.set_value(item, major, minor, val)
self.assertIsNot(res, self.panel)
self.assertEqual(res.get_value(item, major, minor), val)
_check_loc('ItemA', self.panel.major_axis[4],
self.panel.minor_axis[3])
_check_loc('ItemF', self.panel.major_axis[4],
self.panel.minor_axis[3])
_check_loc('ItemF', 'foo', self.panel.minor_axis[3])
_check_loc('ItemE', 'foo', 'bar')
def test_delitem_pop(self):
del self.panel['ItemB']
tm.assert_index_equal(self.panel.items,
pd.Index(['ItemA', 'ItemC', 'ItemD']))
crackle = self.panel['ItemC']
pop = self.panel.pop('ItemC')
self.assertIs(pop, crackle)
tm.assert_almost_equal(self.panel.items, pd.Index(['ItemA', 'ItemD']))
self.assertRaises(KeyError, self.panel.__delitem__, 'ItemC')
def test_copy(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
cop = self.panel.copy()
tm.assert_sp_panel_equal(cop, self.panel)
def test_reindex(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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)
tm.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'])
# test copying
cp = self.panel.reindex(self.panel.major_axis, copy=True)
cp['ItemA']['E'] = cp['ItemA']['A']
self.assertNotIn('E', self.panel['ItemA'])
def test_operators(self):
def _check_ops(panel):
def _dense_comp(op):
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
dense = panel.to_dense()
sparse_result = op(panel)
dense_result = op(dense)
tm.assert_panel_equal(sparse_result.to_dense(),
dense_result)
def _mixed_comp(op):
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
result = op(panel, panel.to_dense())
expected = op(panel.to_dense(), panel.to_dense())
tm.assert_panel_equal(result, expected)
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)
_mixed_comp(Panel.multiply)
_mixed_comp(Panel.subtract)
# TODO: this case not yet supported!
# op6 = lambda x: x.add(x.to_frame())
# _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)
tm.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()
tm.assert_frame_equal(dslice, sslice)
_dense_comp(self.panel)
def test_from_dict(self):
fd = SparsePanel.from_dict(self.data_dict)
assert_sp_panel_equal(fd, self.panel)
def test_constructor_empty(self):
with tm.assert_produces_warning(FutureWarning):
sp = SparsePanel()
self.assertEqual(len(sp.items), 0)
self.assertEqual(len(sp.major_axis), 0)
self.assertEqual(len(sp.minor_axis), 0)
def test_from_dict(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
fd = SparsePanel.from_dict(self.data_dict)
tm.assert_sp_panel_equal(fd, self.panel)
def test_deprecation(self):
with tm.assert_produces_warning(FutureWarning):
SparsePanel()
class TestSparsePanel(TestCase, test_panel.SafeForLongAndSparse, test_panel.SafeForSparse):
@classmethod
def assert_panel_equal(cls, 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 = SparsePanel(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, SparsePanel, self.data_dict, items=["Item0", "ItemA", "ItemB"])
def test_from_dict(self):
fd = SparsePanel.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 = Panel.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 = Panel.from_dict(self.data_dict)
assert_panel_equal(dwp, dwp2)
def test_to_frame(self):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_(np.array_equal(slp.values, dlp.values))
self.assert_(slp.index.equals(dlp.index))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=["ItemA"]))
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception, self.panel.to_frame, 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_set_value(self):
def _check_loc(item, major, minor, val=1.5):
res = self.panel.set_value(item, major, minor, val)
self.assert_(res is not self.panel)
self.assertEquals(res.get_value(item, major, minor), val)
_check_loc("ItemA", self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc("ItemF", self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc("ItemF", "foo", self.panel.minor_axis[3])
_check_loc("ItemE", "foo", "bar")
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"])
# test copying
cp = self.panel.reindex(self.panel.major_axis, copy=True)
cp["ItemA"]["E"] = cp["ItemA"]["A"]
self.assert_("E" not in self.panel["ItemA"])
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_frame())
# _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)
def test_from_dict(self):
fd = SparsePanel.from_dict(self.data_dict)
assert_sp_panel_equal(fd, self.panel)
class TestSparsePanel(tm.TestCase, test_panel.SafeForLongAndSparse,
test_panel.SafeForSparse):
_multiprocess_can_split_ = True
@classmethod
def assert_panel_equal(cls, x, y):
tm.assert_sp_panel_equal(x, y)
def setUp(self):
self.data_dict = {
'ItemA': panel_data1(),
'ItemB': panel_data2(),
'ItemC': panel_data3(),
'ItemD': panel_data1(),
}
with tm.assert_produces_warning(FutureWarning):
self.panel = SparsePanel(self.data_dict)
@staticmethod
def _test_op(panel, op):
# arithmetic tests
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
result = op(panel, 1)
tm.assert_sp_frame_equal(result['ItemA'], op(panel['ItemA'], 1))
def test_constructor(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
self.assertRaises(ValueError, SparsePanel, self.data_dict,
items=['Item0', 'ItemA', 'ItemB'])
with tm.assertRaisesRegexp(TypeError,
"input must be a dict, a 'list' was "
"passed"):
SparsePanel(['a', 'b', 'c'])
# deprecation GH11157
def test_deprecation(self):
with tm.assert_produces_warning(FutureWarning):
SparsePanel()
# GH 9272
def test_constructor_empty(self):
with tm.assert_produces_warning(FutureWarning):
sp = SparsePanel()
self.assertEqual(len(sp.items), 0)
self.assertEqual(len(sp.major_axis), 0)
self.assertEqual(len(sp.minor_axis), 0)
def test_from_dict(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
fd = SparsePanel.from_dict(self.data_dict)
tm.assert_sp_panel_equal(fd, self.panel)
def test_pickle(self):
def _test_roundtrip(panel):
result = self.round_trip_pickle(panel)
tm.assertIsInstance(result.items, Index)
tm.assertIsInstance(result.major_axis, Index)
tm.assertIsInstance(result.minor_axis, Index)
tm.assert_sp_panel_equal(panel, result)
_test_roundtrip(self.panel)
def test_dense_to_sparse(self):
wp = Panel.from_dict(self.data_dict)
dwp = wp.to_sparse()
tm.assertIsInstance(dwp['ItemA']['A'], SparseSeries)
def test_to_dense(self):
dwp = self.panel.to_dense()
dwp2 = Panel.from_dict(self.data_dict)
assert_panel_equal(dwp, dwp2)
def test_to_frame(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_numpy_array_equal(slp.values, dlp.values)
self.assertTrue(slp.index.equals(dlp.index))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
with tm.assert_produces_warning(FutureWarning):
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception, self.panel.to_frame,
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()
tm.assert_sp_frame_equal(self.panel['ItemE'], self.panel['ItemC'])
tm.assert_sp_frame_equal(self.panel['ItemF'], self.panel['ItemC'])
expected = pd.Index(['ItemA', 'ItemB', 'ItemC',
'ItemD', 'ItemE', 'ItemF'])
tm.assert_index_equal(self.panel.items, expected)
self.assertRaises(Exception, self.panel.__setitem__, 'item6', 1)
def test_set_value(self):
def _check_loc(item, major, minor, val=1.5):
res = self.panel.set_value(item, major, minor, val)
self.assertIsNot(res, self.panel)
self.assertEqual(res.get_value(item, major, minor), val)
_check_loc('ItemA', self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc('ItemF', self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc('ItemF', 'foo', self.panel.minor_axis[3])
_check_loc('ItemE', 'foo', 'bar')
def test_delitem_pop(self):
del self.panel['ItemB']
tm.assert_index_equal(self.panel.items,
pd.Index(['ItemA', 'ItemC', 'ItemD']))
crackle = self.panel['ItemC']
pop = self.panel.pop('ItemC')
self.assertIs(pop, crackle)
tm.assert_almost_equal(self.panel.items, pd.Index(['ItemA', 'ItemD']))
self.assertRaises(KeyError, self.panel.__delitem__, 'ItemC')
def test_copy(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
cop = self.panel.copy()
tm.assert_sp_panel_equal(cop, self.panel)
def test_reindex(self):
with tm.assert_produces_warning(FutureWarning, check_stacklevel=False):
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'])
# test copying
cp = self.panel.reindex(self.panel.major_axis, copy=True)
cp['ItemA']['E'] = cp['ItemA']['A']
self.assertNotIn('E', self.panel['ItemA'])
def test_operators(self):
def _check_ops(panel):
def _dense_comp(op):
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
dense = panel.to_dense()
sparse_result = op(panel)
dense_result = op(dense)
assert_panel_equal(sparse_result.to_dense(), dense_result)
def _mixed_comp(op):
with tm.assert_produces_warning(FutureWarning,
check_stacklevel=False):
result = op(panel, panel.to_dense())
expected = op(panel.to_dense(), panel.to_dense())
assert_panel_equal(result, expected)
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)
_mixed_comp(Panel.multiply)
_mixed_comp(Panel.subtract)
# TODO: this case not yet supported!
# op6 = lambda x: x.add(x.to_frame())
# _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)
class TestSparsePanel(TestCase, test_panel.SafeForLongAndSparse,
test_panel.SafeForSparse):
@classmethod
def assert_panel_equal(cls, 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 = SparsePanel(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,
SparsePanel,
self.data_dict,
items=['Item0', 'ItemA', 'ItemB'])
def test_from_dict(self):
fd = SparsePanel.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 = Panel.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 = Panel.from_dict(self.data_dict)
assert_panel_equal(dwp, dwp2)
def test_to_frame(self):
def _compare_with_dense(panel):
slp = panel.to_frame()
dlp = panel.to_dense().to_frame()
self.assert_(np.array_equal(slp.values, dlp.values))
self.assert_(slp.index.equals(dlp.index))
_compare_with_dense(self.panel)
_compare_with_dense(self.panel.reindex(items=['ItemA']))
zero_panel = SparsePanel(self.data_dict, default_fill_value=0)
self.assertRaises(Exception, zero_panel.to_frame)
self.assertRaises(Exception,
self.panel.to_frame,
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_set_value(self):
def _check_loc(item, major, minor, val=1.5):
res = self.panel.set_value(item, major, minor, val)
self.assert_(res is not self.panel)
self.assertEquals(res.get_value(item, major, minor), val)
_check_loc('ItemA', self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc('ItemF', self.panel.major_axis[4], self.panel.minor_axis[3])
_check_loc('ItemF', 'foo', self.panel.minor_axis[3])
_check_loc('ItemE', 'foo', 'bar')
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'])
# test copying
cp = self.panel.reindex(self.panel.major_axis, copy=True)
cp['ItemA']['E'] = cp['ItemA']['A']
self.assert_('E' not in self.panel['ItemA'])
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_frame())
# _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)
