All nosetests fail on fresh installation

I've just tried pulling the master branch and running the nosetests and all 9 of them fail. There seem to be two main categories of error:

The first and most common error is:

ERROR: force_call_test.non_periodic_test
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
    self.test(*self.arg)
  File "/home/jacob/python/amp/tests/CuOPd_test/gaussian_neural_test/force_call_test.py", line 181, in non_periodic_test
    images]
  File "/mnt/Omega/python/ase/ase/calculators/calculator.py", line 348, in get_potential_energy
    energy = self.get_property('energy', atoms)
  File "/mnt/Omega/python/ase/ase/calculators/calculator.py", line 387, in get_property
    self.calculate(atoms, [name], system_changes)
  File "/mnt/Omega/python/amp/__init__.py", line 189, in calculate
    calculate_derivatives=False)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 157, in calculate_fingerprints
    self.fingerprints.calculate_items(images, cores=cores, log=log)
  File "/mnt/Omega/python/amp/utilities.py", line 160, in calculate_items
    d[key] = self.calc.calculate(images[key], key)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 204, in calculate
    indexfp = self.get_fingerprint(index, symbol, neighborsymbols, Rs)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 240, in get_fingerprint
    self.globals.cutoff, home, self.fortran)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 450, in calculate_G2
    ridge += (np.exp(-eta * (Rij ** 2.) / (cutoff ** 2.)) *
TypeError: unsupported operand type(s) for ** or pow(): 'dict' and 'float'

These errors can be fixed by changing most instances of the cutoff variable in the amp/descriptor/gaussian.py file to cutoff['kwargs']['Rc'], which I assume was intended?

Changing the above then leads to 5 of the nosetests failing, all with errors similar to the following:

ERROR: train_test.non_periodic_0th_bfgs_step_test
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
    self.test(*self.arg)
  File "/home/jacob/python/amp/tests/CuOPd_test/gaussian_neural_test/train_test.py", line 198, in non_periodic_0th_bfgs_step_test
    calc.train(images=images,)
  File "/mnt/Omega/python/amp/__init__.py", line 242, in train
    calculate_derivatives=calculate_derivatives)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 157, in calculate_fingerprints
    self.fingerprints.calculate_items(images, cores=cores, log=log)
  File "/mnt/Omega/python/amp/utilities.py", line 160, in calculate_items
    d[key] = self.calc.calculate(images[key], key)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 204, in calculate
    indexfp = self.get_fingerprint(index, symbol, neighborsymbols, Rs)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 240, in get_fingerprint
    self.globals.cutoff, home, self.fortran)
  File "/mnt/Omega/python/amp/descriptor/gaussian.py", line 437, in calculate_G2
    ridge = fmodules.calculate_g2(numbers=numbers, rs=Rs,
AttributeError: 'NoneType' object has no attribute 'calculate_g2'

Which is the result of no fmodules file in the amp master directory. Again, I assume this is meant to be compiled from the two .f90 files:

f2py -c -m fmodules descriptor/gaussian.f90 descriptor/zernike.f90

But this is not documented in the README, or doc/ so I cannot confirm. Despite these additions, the final test still fails:

........E
======================================================================
ERROR: test_gaussian_neural.train_test
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/local/lib/python2.7/dist-packages/nose/case.py", line 197, in runTest
    self.test(*self.arg)
  File "/home/jacob/python/amp/tests/test_gaussian_neural.py", line 55, in train_test
    calc.train(images=train_images,)
  File "/mnt/Omega/python/amp/__init__.py", line 259, in train
    raise TrainingConvergenceError('Amp did not converge upon '
TrainingConvergenceError: Amp did not converge upon training. See log file for more information.
-------------------- >> begin captured stdout << ---------------------
Warning: Desired error not necessarily achieved due to precision loss.
         Current function value: 0.000305
         Iterations: 85
         Function evaluations: 129
         Gradient evaluations: 117

--------------------- >> end captured stdout << ----------------------

----------------------------------------------------------------------
Ran 9 tests in 129.791s

FAILED (errors=1)

However, each time the convergence level is different. Is this meant to happen, or have I made a mistake?

See attached file for log of the final run attempt.

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