Normalise array order after circular interpolation.

When appending to an array, NumPy 1.7 always returns the same C/Fortran order independent of the axis:

```python
>>> import numpy as np
>>> np.__version__
'1.7.2'
>>> a = np.arange(60).reshape(3,4,5)
>>> np.append(a, a[:1], axis=0).flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : False
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
>>> np.append(a, a[:, :1], axis=1).flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : False
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
>>> np.append(a, a[:, :, :1], axis=2).flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : False
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
```

But 1.6 has varying order depending on the append axis:

```python
>>> import numpy as np
>>> np.__version__
'1.6.0'
>>> a = np.arange(60).reshape(3,4,5)
>>> np.append(a, a[:1], axis=0).flags
  C_CONTIGUOUS : True
  F_CONTIGUOUS : False
  OWNDATA : True
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
>>> np.append(a, a[:, :1], axis=1).flags
  C_CONTIGUOUS : False
  F_CONTIGUOUS : False
  OWNDATA : False
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
>>> np.append(a, a[:, :, :1], axis=2).flags
  C_CONTIGUOUS : False
  F_CONTIGUOUS : True
  OWNDATA : False
  WRITEABLE : True
  ALIGNED : True
  UPDATEIFCOPY : False
```

This change forces the relevant test results to have C-order.

Fixes:
 - iris.tests.analysis.test_interpolate.Test_linear__circular_wrapping
  - test_positive
  - test_symmetric
 - iris.tests.test_interpolation.TestLinear1dInterpolation
  - test_circular_vs_non_circular_coord
  - test_simple_multiple_points_circular
 - iris.tests.test_interpolation.TestNearestLinearInterpolRealData
  - test_circular