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Sep 25, 2013
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TST/CLN: pare down the eval test suite #4974

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87 changes: 44 additions & 43 deletions pandas/computation/tests/test_eval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -129,8 +129,8 @@ def setup_data(self):
Series([1, 2, np.nan, np.nan, 5]), nan_df1)
self.pandas_rhses = (DataFrame(randn(10, 5)), Series(randn(5)),
Series([1, 2, np.nan, np.nan, 5]), nan_df2)
self.scalar_lhses = randn(), np.float64(randn()), np.nan
self.scalar_rhses = randn(), np.float64(randn()), np.nan
self.scalar_lhses = randn(),
self.scalar_rhses = randn(),

self.lhses = self.pandas_lhses + self.scalar_lhses
self.rhses = self.pandas_rhses + self.scalar_rhses
Expand Down Expand Up @@ -180,7 +180,6 @@ def test_floor_division(self):
for lhs, rhs in product(self.lhses, self.rhses):
self.check_floor_division(lhs, '//', rhs)

@slow
def test_pow(self):
for lhs, rhs in product(self.lhses, self.rhses):
self.check_pow(lhs, '**', rhs)
Expand All @@ -198,13 +197,13 @@ def test_compound_invert_op(self):
@slow
def test_chained_cmp_op(self):
mids = self.lhses
cmp_ops = tuple(set(self.cmp_ops) - set(['==', '!=', '<=', '>=']))
cmp_ops = '<', '>'# tuple(set(self.cmp_ops) - set(['==', '!=', '<=', '>=']))
for lhs, cmp1, mid, cmp2, rhs in product(self.lhses, cmp_ops,
mids, cmp_ops, self.rhses):
self.check_chained_cmp_op(lhs, cmp1, mid, cmp2, rhs)

def check_complex_cmp_op(self, lhs, cmp1, rhs, binop, cmp2):
skip_these = 'in', 'not in'
skip_these = _scalar_skip
ex = '(lhs {cmp1} rhs) {binop} (lhs {cmp2} rhs)'.format(cmp1=cmp1,
binop=binop,
cmp2=cmp2)
Expand Down Expand Up @@ -264,7 +263,7 @@ def check_complex_cmp_op(self, lhs, cmp1, rhs, binop, cmp2):

@skip_incompatible_operand
def check_chained_cmp_op(self, lhs, cmp1, mid, cmp2, rhs):
skip_these = 'in', 'not in'
skip_these = _scalar_skip

def check_operands(left, right, cmp_op):
if (np.isscalar(left) and np.isnan(left) and not np.isscalar(right)
Expand Down Expand Up @@ -318,11 +317,7 @@ def check_operands(left, right, cmp_op):
ex1 = 'lhs {0} mid {1} rhs'.format(cmp1, cmp2)
ex2 = 'lhs {0} mid and mid {1} rhs'.format(cmp1, cmp2)
ex3 = '(lhs {0} mid) & (mid {1} rhs)'.format(cmp1, cmp2)
try:
expected = _eval_single_bin(lhs_new, '&', rhs_new, self.engine)
except TypeError:
import ipdb; ipdb.set_trace()
raise
expected = _eval_single_bin(lhs_new, '&', rhs_new, self.engine)

for ex in (ex1, ex2, ex3):
result = pd.eval(ex, engine=self.engine,
Expand Down Expand Up @@ -729,9 +724,8 @@ def setup_ops(self):

def check_chained_cmp_op(self, lhs, cmp1, mid, cmp2, rhs):
ex1 = 'lhs {0} mid {1} rhs'.format(cmp1, cmp2)
self.assertRaises(NotImplementedError, pd.eval, ex1,
local_dict={'lhs': lhs, 'mid': mid, 'rhs': rhs},
engine=self.engine, parser=self.parser)
with tm.assertRaises(NotImplementedError):
pd.eval(ex1, engine=self.engine, parser=self.parser)


class TestEvalPythonPython(TestEvalNumexprPython):
Expand Down Expand Up @@ -783,7 +777,8 @@ def check_chained_cmp_op(self, lhs, cmp1, mid, cmp2, rhs):

class TestAlignment(object):

index_types = 'i', 'f', 's', 'u', 'dt', # 'p'
index_types = 'i', 'u', 'dt'
lhs_index_types = index_types + ('f', 's') # 'p'

def check_align_nested_unary_op(self, engine, parser):
skip_if_no_ne(engine)
Expand All @@ -798,23 +793,23 @@ def test_align_nested_unary_op(self):

def check_basic_frame_alignment(self, engine, parser):
skip_if_no_ne(engine)
args = product(self.index_types, repeat=2)
for r_idx_type, c_idx_type in args:
df = mkdf(10, 10, data_gen_f=f, r_idx_type=r_idx_type,
args = product(self.lhs_index_types, self.index_types,
self.index_types)
for lr_idx_type, rr_idx_type, c_idx_type in args:
df = mkdf(10, 10, data_gen_f=f, r_idx_type=lr_idx_type,
c_idx_type=c_idx_type)
df2 = mkdf(20, 10, data_gen_f=f, r_idx_type=r_idx_type,
df2 = mkdf(20, 10, data_gen_f=f, r_idx_type=rr_idx_type,
c_idx_type=c_idx_type)
res = pd.eval('df + df2', engine=engine, parser=parser)
assert_frame_equal(res, df + df2)

@slow
def test_basic_frame_alignment(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_basic_frame_alignment, engine, parser

def check_frame_comparison(self, engine, parser):
skip_if_no_ne(engine)
args = product(self.index_types, repeat=2)
args = product(self.lhs_index_types, repeat=2)
for r_idx_type, c_idx_type in args:
df = mkdf(10, 10, data_gen_f=f, r_idx_type=r_idx_type,
c_idx_type=c_idx_type)
Expand All @@ -826,18 +821,19 @@ def check_frame_comparison(self, engine, parser):
res = pd.eval('df < df3', engine=engine, parser=parser)
assert_frame_equal(res, df < df3)

@slow
def test_frame_comparison(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_frame_comparison, engine, parser

def check_medium_complex_frame_alignment(self, engine, parser):
skip_if_no_ne(engine)
args = product(self.index_types, repeat=4)
args = product(self.lhs_index_types, self.index_types,
self.index_types, self.index_types)

for r1, c1, r2, c2 in args:
df = mkdf(5, 2, data_gen_f=f, r_idx_type=r1, c_idx_type=c1)
df2 = mkdf(10, 2, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
df3 = mkdf(15, 2, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
df = mkdf(3, 2, data_gen_f=f, r_idx_type=r1, c_idx_type=c1)
df2 = mkdf(4, 2, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
df3 = mkdf(5, 2, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
res = pd.eval('df + df2 + df3', engine=engine, parser=parser)
assert_frame_equal(res, df + df2 + df3)

Expand All @@ -864,20 +860,19 @@ def testit(r_idx_type, c_idx_type, index_name):
expected = df + s
assert_frame_equal(res, expected)

args = product(self.index_types, self.index_types, ('index',
'columns'))
args = product(self.lhs_index_types, self.index_types,
('index', 'columns'))
for r_idx_type, c_idx_type, index_name in args:
testit(r_idx_type, c_idx_type, index_name)

@slow
def test_basic_frame_series_alignment(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_basic_frame_series_alignment, engine, parser

def check_basic_series_frame_alignment(self, engine, parser):
skip_if_no_ne(engine)
def testit(r_idx_type, c_idx_type, index_name):
df = mkdf(10, 10, data_gen_f=f, r_idx_type=r_idx_type,
df = mkdf(10, 7, data_gen_f=f, r_idx_type=r_idx_type,
c_idx_type=c_idx_type)
index = getattr(df, index_name)
s = Series(np.random.randn(5), index[:5])
Expand All @@ -892,19 +887,18 @@ def testit(r_idx_type, c_idx_type, index_name):
expected = s + df
assert_frame_equal(res, expected)

args = product(self.index_types, self.index_types, ('index',
'columns'))
args = product(self.lhs_index_types, self.index_types,
('index', 'columns'))
for r_idx_type, c_idx_type, index_name in args:
testit(r_idx_type, c_idx_type, index_name)

@slow
def test_basic_series_frame_alignment(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_basic_series_frame_alignment, engine, parser

def check_series_frame_commutativity(self, engine, parser):
skip_if_no_ne(engine)
args = product(self.index_types, self.index_types, ('+', '*'),
args = product(self.lhs_index_types, self.index_types, ('+', '*'),
('index', 'columns'))
for r_idx_type, c_idx_type, op, index_name in args:
df = mkdf(10, 10, data_gen_f=f, r_idx_type=r_idx_type,
Expand All @@ -921,20 +915,28 @@ def check_series_frame_commutativity(self, engine, parser):
if engine == 'numexpr':
assert_frame_equal(a, b)

@slow
def test_series_frame_commutativity(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_series_frame_commutativity, engine, parser

def check_complex_series_frame_alignment(self, engine, parser):
skip_if_no_ne(engine)
index_types = [self.index_types] * 4
args = product(('index', 'columns'), ('df', 'df2'), *index_types)
for index_name, obj, r1, r2, c1, c2 in args:
df = mkdf(10, 5, data_gen_f=f, r_idx_type=r1, c_idx_type=c1)
df2 = mkdf(20, 5, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
index = getattr(locals()[obj], index_name)
s = Series(np.random.randn(5), index[:5])

import random
args = product(self.lhs_index_types, self.index_types,
self.index_types, self.index_types)
n = 3
m1 = 5
m2 = 2 * m1

for r1, r2, c1, c2 in args:
index_name = random.choice(['index', 'columns'])
obj_name = random.choice(['df', 'df2'])

df = mkdf(m1, n, data_gen_f=f, r_idx_type=r1, c_idx_type=c1)
df2 = mkdf(m2, n, data_gen_f=f, r_idx_type=r2, c_idx_type=c2)
index = getattr(locals().get(obj_name), index_name)
s = Series(np.random.randn(n), index[:n])

if r2 == 'dt' or c2 == 'dt':
if engine == 'numexpr':
Expand Down Expand Up @@ -1004,7 +1006,6 @@ def check_performance_warning_for_poor_alignment(self, engine, parser):
"".format(1, 's', np.log10(s.size - df.shape[1])))
assert_equal(msg, expected)


def test_performance_warning_for_poor_alignment(self):
for engine, parser in ENGINES_PARSERS:
yield self.check_performance_warning_for_poor_alignment, engine, parser
Expand Down