[Tutor] unitest with random inputs

[Sydney Shall]

On 19/07/2017 18:42, Steven D'Aprano wrote:
> On Wed, Jul 19, 2017 at 05:01:53PM +0200, Sydney Shall wrote:
> 
> [...]
>>   def test_zero_in_capitalsadvanced(self):
>>          self.assertIn(self.capitalsadvanced, 0.0)
>>
>> The error message is:
>>
>> Traceback (most recent call last):
> [...]
>> in assertIn
>>      if member not in container:
>> TypeError: argument of type 'float' is not iterable
> 
> You are trying to test whether capitalsadvanced is in 0.0. Reverse the
> arguments:
> 
>          self.assertIn(0.0, self.capitalsadvanced)
> 
> which will test whether 0.0 is in self.capitalsadvanced.
> 
> 
>> FAILED (failures=9, errors=1)
>>
>> The failures all arise from a 'nan'.
>> It is this problem that I am trying to resolve.
> 
> Well, since you don't show us what those failing tests are, we cannot
> possibly tell you how to fix them.
> 
> Start by showing us *one* failing test, and what the failure is.
> 
> 
Thank you Steve.

The remaining 'nan' problems are shown below.

runfile('/Users/sydney/Capital/Capital_with_productivity/Current_Versions/testPOCWP_V2.py', 
wdir='/Users/sydney/Capital/Capital_with_productivity/Current_Versions')
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1582: 
RuntimeWarning: invalid value encountered in true_divide

/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1637: 
RuntimeWarning: invalid value encountered in true_divide
   constantcapitals is divided, element-wise by the array
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1665: 
RuntimeWarning: invalid value encountered in true_divide
   capitalsadvanced.
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1695: 
RuntimeWarning: invalid value encountered in true_divide
   The output is a numpy array of floats; and they are ratios of (Variable
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1729: 
RuntimeWarning: invalid value encountered in true_divide
   The method returns is a numpy array of floats; the ratios of (Variable
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1758: 
RuntimeWarning: invalid value encountered in true_divide
   The method returns a numpy array of floats, which are the ratios of
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1787: 
RuntimeWarning: invalid value encountered in true_divide
   The method returns a numpy array of floats which are the individual
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:1816: 
RuntimeWarning: invalid value encountered in true_divide
   The method returns a numpy array of floats which are the ratios of (New
..............................................................................................................FF.F.FFF..FF...F......./Users/sydney/anaconda/lib/python3.6/unittest/case.py:1077: 
FutureWarning: elementwise comparison failed; returning scalar instead, 
but in the future will perform elementwise comparison
   if member not in container:
F............................................../Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:2311: 
RuntimeWarning: invalid value encountered in double_scalars
   values in UCC.
/Users/sydney/Capital/Capital_with_productivity/Current_Versions/PopulationOfCapitalsWithProductivityV16_Python36.py:2256: 
RuntimeWarning: invalid value encountered in double_scalars

....................................................................

I have looked carefully at the lines indicated and they almost all 
involve 4 specific numpy.ndarrays. I suspect from the logic that they 
all results from the commonest array in the list.

The last error is different, but I belie that it is related.



-- 
Sydney