def test_difference_big_variation_success():
df1 = util.iris(['petalwidth'], size=40)
df2 = util.iris(['petalwidth'], size=10)
test_df = df1.copy()
df1.loc[4, 'petalwidth'] = np.int64(50)
df1.loc[5, 'petalwidth'] = pd.Timestamp(1596509236)
df1.loc[6, 'petalwidth'] = np.float(1.56)
df1.loc[7, 'petalwidth'] = np.array('test')
df1.loc[8, 'petalwidth'] = np.bool(False)
df1.loc[10, 'petalwidth'] = np.NaN
arguments = {
'parameters': {},
'named_inputs': {
'input data 1': 'df1',
'input data 2': 'df2'
},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
result = util.execute(instance.generate_code(), {'df1': df1, 'df2': df2})
diff_oper = df1.eq(df2)
for i in range(40):
if diff_oper.iloc[i, 0:].all():
test_df.drop(i, inplace=True)
assert result['out'].eq(test_df).equals(test_df.eq(result['out']))
assert len(result['out']) == 35
def test_difference_missing_input_implies_no_code_success():
arguments = {
'parameters': {},
'named_inputs': {},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
assert instance.generate_code() is None
def test_difference_no_output_implies_no_code_success():
arguments = {
'parameters': {},
'named_inputs': {
'input data 1': 'df1',
'input data 2': 'df2'
},
'named_outputs': {}
}
instance = DifferenceOperation(**arguments)
assert instance.generate_code() is None
def test_difference_one_col_success():
df1 = util.iris(['sepallength'], size=15)
df2 = util.iris(['sepallength'], size=10)
df1.loc[7:9, 'sepallength'] = 1
test_df = df1.copy()
arguments = {
'parameters': {},
'named_inputs': {
'input data 1': 'df1',
'input data 2': 'df2'
},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
result = util.execute(instance.generate_code(), {'df1': df1, 'df2': df2})
assert result['out'].equals(test_df.loc[7:14, 'sepallength'].to_frame())
assert len(result['out']) == 8
def test_difference_success():
slice_size = 10
df = [
'df',
util.iris(['sepallength', 'sepalwidth', 'petalwidth', 'petallength'],
slice_size)
]
arguments = {
'parameters': {},
'named_inputs': {
'input data': df[0],
},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
result = util.execute(instance.generate_code(), dict([df]))
assert result['out'].equals(util.iris(size=slice_size))
def test_difference_input2_is_bigger_success():
"""It only returns the dataframe column, maybe it should return nothing?"""
df1 = util.iris(['petalwidth'], size=10)
df2 = util.iris(['petalwidth'], size=15)
test_df = df1.copy().drop(range(10))
arguments = {
'parameters': {},
'named_inputs': {
'input data 1': 'df1',
'input data 2': 'df2'
},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
result = util.execute(instance.generate_code(), {'df1': df1, 'df2': df2})
assert result['out'].equals(test_df)
assert len(result['out']) == 0
def test_difference_different_cols_success():
"""Returns nothing"""
df1 = util.iris(['petalwidth'], size=20)
df2 = util.iris(['class'], size=10)
test_df = df1.copy().drop(columns='petalwidth', index=range(20))
arguments = {
'parameters': {
'attributes': 2
},
'named_inputs': {
'input data 1': 'df1',
'input data 2': 'df2'
},
'named_outputs': {
'output data': 'out'
}
}
instance = DifferenceOperation(**arguments)
result = util.execute(instance.generate_code(), {'df1': df1, 'df2': df2})
assert result['out'].equals(test_df)
assert len(result['out']) == 0