On 19/07/2017 17:43, Peter Otten wrote:
Sydney Shall wrote:
I am learning to use unittest.
I have written a program that runs as it should.
247 tests give me a satisfactory answer.
I have now added one more test and I get an error which I do not
understand.
The two relevant tests are:
def test_type_capitalsadvanced(self):
self.assertEqual(type(self.capitalsadvanced), numpy.ndarray)
def test_zero_in_capitalsadvanced(self):
self.assertIn(self.capitalsadvanced, 0.0)
The error message is:
Traceback (most recent call last):
File
"/Users/sydney/Capital/Capital_with_productivity/Current_Versions/testPOCWP_V2.py",
line 320, in test_zero_in_capitalsadvanced
self.assertIn(self.capitalsadvanced, 0.0)
File "/Users/sydney/anaconda/lib/python3.6/unittest/case.py", line
1077, in assertIn
if member not in container:
TypeError: argument of type 'float' is not iterable
Final output from the tests is :
Ran 247 tests in 1.179s
FAILED (failures=9, errors=1)
The failures all arise from a 'nan'.
I don't think so. To fix the traceback shown above you have to swap the
arguments in assertIn():
def test_zero_in_capitalsadvanced(self):
self.assertIn(0.0, self.capitalsadvanced)
Digression: once this is done you may still get failures when searching for
NaN in a sequence as it does not compare equal to itself:
nan = float("nan")
nan == nan
False
a = numpy.array([nan])
nan in a
False
This is how it should be (*), but unfortunately Python's builtin
list/set/dict/tuple all assume that obj is obj implies obj == obj which
makes the result of containment test hard to predict:
nan in [nan]
True
nan in [float("nan")]
False
(*) See for example
<https://en.wikipedia.org/wiki/Floating-point_arithmetic>:
"every NaN compares unequal to every value, including itself"
It is this problem that I am trying to resolve.
My problem is that the first test tells me correctly that the object
capitalsadvanced is a numpy.ndarray. But the second test error message
says it is a float.
I should add that the program creates the initial data set by making use
of the random function which is given a mean to work with. Thus each
test run will be with different input data. But repeated tests show the
same errors.
When I run the same tests with predetermined, fixed data I get no errors
and no 'nan' errors.
Any guidance will be very welcome.
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Peter,
Thanks for your comment.
This has helped to cure the first error.
For the second error, regarding 'nan' finding 'nan', I received the
following output.
FAIL: test_nan_in_capitalsadvanced (__main__.TestPOC)
----------------------------------------------------------------------
Traceback (most recent call last):
File
"/Users/sydney/Capital/Capital_with_productivity/Current_Versions/testPOCWP_V2.py",
line 323, in test_nan_in_capitalsadvanced
self.assertIn('nan', self.capitalsadvanced)
AssertionError: 'nan' not found in array([ 12026.72641072,
12434.53700436, 12185.56314119, ...,
12488.04714281, 12479.4662866 , 12310.66016998])
Could I use assertNotIn with the other problems?
Thanks again.
Sydney
--
Sydney
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