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Fixturize tests/frame/test_arithmetic #22736

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Sep 26, 2018
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18 changes: 10 additions & 8 deletions pandas/tests/frame/conftest.py
Original file line number Diff line number Diff line change
Expand Up @@ -70,9 +70,10 @@ def mixed_float_frame():
Columns are ['A', 'B', 'C', 'D'].
"""
df = DataFrame(tm.getSeriesData())
df.A = df.A.astype('float16')
df.A = df.A.astype('float32')
df.B = df.B.astype('float32')
df.C = df.C.astype('float64')
df.C = df.C.astype('float16')
df.D = df.D.astype('float64')
return df


Expand All @@ -84,9 +85,10 @@ def mixed_float_frame2():
Columns are ['A', 'B', 'C', 'D'].
"""
df = DataFrame(tm.getSeriesData())
df.D = df.D.astype('float16')
df.D = df.D.astype('float32')
df.C = df.C.astype('float32')
df.B = df.B.astype('float64')
df.B = df.B.astype('float16')
df.D = df.D.astype('float64')
return df


Expand All @@ -99,10 +101,10 @@ def mixed_int_frame():
"""
df = DataFrame({k: v.astype(int)
for k, v in compat.iteritems(tm.getSeriesData())})
df.A = df.A.astype('uint8')
df.B = df.B.astype('int32')
df.C = df.C.astype('int64')
df.D = np.ones(len(df.D), dtype='uint64')
df.A = df.A.astype('int32')
df.B = np.ones(len(df.B), dtype='uint64')
df.C = df.C.astype('uint8')
df.D = df.C.astype('int64')
return df


Expand Down
197 changes: 78 additions & 119 deletions pandas/tests/frame/test_arithmetic.py
Original file line number Diff line number Diff line change
Expand Up @@ -4,8 +4,7 @@
import pytest
import numpy as np

from pandas.compat import range, PY3
import pandas.io.formats.printing as printing
from pandas.compat import range

import pandas as pd
import pandas.util.testing as tm
Expand Down Expand Up @@ -127,132 +126,92 @@ def test_df_add_flex_filled_mixed_dtypes(self):
'B': ser * 2})
tm.assert_frame_equal(result, expected)

def test_arith_flex_frame(self):
seriesd = tm.getSeriesData()
frame = pd.DataFrame(seriesd).copy()

mixed_float = pd.DataFrame({'A': frame['A'].copy().astype('float32'),
'B': frame['B'].copy().astype('float32'),
'C': frame['C'].copy().astype('float16'),
'D': frame['D'].copy().astype('float64')})

intframe = pd.DataFrame({k: v.astype(int)
for k, v in seriesd.items()})
mixed_int = pd.DataFrame({'A': intframe['A'].copy().astype('int32'),
'B': np.ones(len(intframe), dtype='uint64'),
'C': intframe['C'].copy().astype('uint8'),
'D': intframe['D'].copy().astype('int64')})

# force these all to int64 to avoid platform testing issues
intframe = pd.DataFrame({c: s for c, s in intframe.items()},
dtype=np.int64)

ops = ['add', 'sub', 'mul', 'div', 'truediv', 'pow', 'floordiv', 'mod']
if not PY3:
aliases = {}
else:
aliases = {'div': 'truediv'}
def test_arith_flex_frame(self, all_arithmetic_operators, float_frame,
mixed_float_frame):

for op in ops:
try:
alias = aliases.get(op, op)
f = getattr(operator, alias)
result = getattr(frame, op)(2 * frame)
exp = f(frame, 2 * frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float, op)(2 * mixed_float)
exp = f(mixed_float, 2 * mixed_float)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

# vs mix int
if op in ['add', 'sub', 'mul']:
result = getattr(mixed_int, op)(2 + mixed_int)
exp = f(mixed_int, 2 + mixed_int)

# no overflow in the uint
dtype = None
if op in ['sub']:
dtype = dict(B='uint64', C=None)
elif op in ['add', 'mul']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)

# rops
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rops were only tested within that if-block. Now they're all tested

r_f = lambda x, y: f(y, x)
result = getattr(frame, 'r' + op)(2 * frame)
exp = r_f(frame, 2 * frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float, op)(2 * mixed_float)
exp = f(mixed_float, 2 * mixed_float)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

result = getattr(intframe, op)(2 * intframe)
exp = f(intframe, 2 * intframe)
tm.assert_frame_equal(result, exp)

# vs mix int
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For some reason, this part was tested twice. only once in cleaned-up version

if op in ['add', 'sub', 'mul']:
result = getattr(mixed_int, op)(2 + mixed_int)
exp = f(mixed_int, 2 + mixed_int)

# no overflow in the uint
dtype = None
if op in ['sub']:
dtype = dict(B='uint64', C=None)
elif op in ['add', 'mul']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)
except:
printing.pprint_thing("Failing operation %r" % op)
raise

# ndim >= 3
ndim_5 = np.ones(frame.shape + (3, 4, 5))
op = all_arithmetic_operators # one instance of parametrized fixture
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put comments on the prior line

if op.startswith('__r'):
# get op without "r" and invert it
tmp = getattr(operator, op[:2] + op[3:])
f = lambda x, y: tmp(y, x)
else:
f = getattr(operator, op)

result = getattr(float_frame, op)(2 * float_frame)
exp = f(float_frame, 2 * float_frame)
tm.assert_frame_equal(result, exp)

# vs mix float
result = getattr(mixed_float_frame, op)(2 * mixed_float_frame)
exp = f(mixed_float_frame, 2 * mixed_float_frame)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

@pytest.mark.parametrize('op', ['__add__', '__sub__', '__mul__'])
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Broke up the test like you wanted

def test_arith_flex_frame_mixed(self, op, int_frame, mixed_int_frame,
float_frame, mixed_float_frame):

if op.startswith('__r'):
# get op without "r" and invert it
tmp = getattr(operator, op[:2] + op[3:])
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make this a named function to avoid the tmp something like

def f(x, y):
    # comment
    op = op.replace('__r', '__')
    return getattr(operator, op)

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this comment applies to the prior test actually. I don't think you need this here at all, as op is just add, mul, sub.

did you mean to test the reverse of these as well?

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make this a named function to avoid the tmp something like [...]

Best I can come up with is the following. Is this what you meant?

[...]
# one instance of parametrized fixture
op = all_arithmetic_operators

def f(x, y):
    if op.startswith('__r'):
        # get op without "r" and invert it
        return getattr(operator, op.replace('__r', '__'))(y, x)
    return getattr(operator, op)(x, y)
[...]

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this comment applies to the prior test actually. I don't think you need this here at all, as op is just add, mul, sub. did you mean to test the reverse of these as well?

That was indeed not necessary anymore. Removed

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ok this is fine (your change). note that I suspect we do this in other places, maybe see if you can make a more generalized version of this that we can then include in the pandas.util.testing (but followon-PR)

f = lambda x, y: tmp(y, x)
else:
f = getattr(operator, op)

# vs mix int
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might be more clear to move these to a separate test (from here down)

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I don't want to get into orthogonal changes here. I haven't changed anything about this except removing the indentation. This goes for the test split requested below as well.

result = getattr(mixed_int_frame, op)(2 + mixed_int_frame)
exp = f(mixed_int_frame, 2 + mixed_int_frame)

# no overflow in the uint
dtype = None
if op in ['__sub__']:
dtype = dict(B='uint64', C=None)
elif op in ['__add__', '__mul__']:
dtype = dict(C=None)
tm.assert_frame_equal(result, exp)
_check_mixed_int(result, dtype=dtype)

# vs mix float
result = getattr(mixed_float_frame, op)(2 * mixed_float_frame)
exp = f(mixed_float_frame, 2 * mixed_float_frame)
tm.assert_frame_equal(result, exp)
_check_mixed_float(result, dtype=dict(C=None))

# vs plain int
result = getattr(int_frame, op)(2 * int_frame)
exp = f(int_frame, 2 * int_frame)
tm.assert_frame_equal(result, exp)

def test_arith_flex_frame_corner(self, all_arithmetic_operators,
float_frame):

op = all_arithmetic_operators

# Check that arrays with dim >= 3 raise
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can you add a comment here on what this is testing

Added (and expanded)

for dim in range(3, 6):
arr = np.ones((1,) * dim)
msg = "Unable to coerce to Series/DataFrame"
with tm.assert_raises_regex(ValueError, msg):
f(frame, ndim_5)
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This part (testing via the f of the op) is removed because it's testing the same thing as testing the op from the frame directly below

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Can you separate out these dimension-specific tests?

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Split them out in a separate test


with tm.assert_raises_regex(ValueError, msg):
getattr(frame, op)(ndim_5)
getattr(float_frame, op)(arr)

# res_add = frame.add(frame)
# res_sub = frame.sub(frame)
# res_mul = frame.mul(frame)
# res_div = frame.div(2 * frame)

# tm.assert_frame_equal(res_add, frame + frame)
# tm.assert_frame_equal(res_sub, frame - frame)
# tm.assert_frame_equal(res_mul, frame * frame)
# tm.assert_frame_equal(res_div, frame / (2 * frame))
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Did this commented-out stuff go somewhere else? Or just determined to be redundant?

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Determined to be redundant with test_arith_flex_frame, which checks all arith_ops, and much more thoroughly.


const_add = frame.add(1)
tm.assert_frame_equal(const_add, frame + 1)
const_add = float_frame.add(1)
tm.assert_frame_equal(const_add, float_frame + 1)

# corner cases
result = frame.add(frame[:0])
tm.assert_frame_equal(result, frame * np.nan)
result = float_frame.add(float_frame[:0])
tm.assert_frame_equal(result, float_frame * np.nan)

result = float_frame[:0].add(float_frame)
tm.assert_frame_equal(result, float_frame * np.nan)

result = frame[:0].add(frame)
tm.assert_frame_equal(result, frame * np.nan)
with tm.assert_raises_regex(NotImplementedError, 'fill_value'):
frame.add(frame.iloc[0], fill_value=3)
float_frame.add(float_frame.iloc[0], fill_value=3)

with tm.assert_raises_regex(NotImplementedError, 'fill_value'):
frame.add(frame.iloc[0], axis='index', fill_value=3)

def test_arith_flex_series(self):
arr = np.array([[1., 2., 3.],
[4., 5., 6.],
[7., 8., 9.]])
df = pd.DataFrame(arr, columns=['one', 'two', 'three'],
index=['a', 'b', 'c'])
float_frame.add(float_frame.iloc[0], axis='index', fill_value=3)

def test_arith_flex_series(self, simple_frame):
df = simple_frame

row = df.xs('a')
col = df['two']
Expand Down