Add sqrt member to AffineScalarFunc to make numpy.linalg.norm work

uncertainties/test_umath.py

@@ -341,3 +341,21 @@ def test_power_wrt_ref():
  Checks special cases of the umath_core.pow() power operator.
  '''
  test_uncertainties.power_wrt_ref(umath_core.pow, math.pow)
+
+def test_numpy_sqrt():
+ '''
+ Checks if numpys sqrt method works due to AffineScalarFunc having basic math
+ functions as members.
+ '''
+ try:
+ import numpy
+ except ImportError:
+ import warnings
+ warnings.warn("Test not performed because NumPy is not available")
+ return
+
+ a = ufloat(0.3, 0.01)
+ if not(numpy.sqrt(a) == umath_core.sqrt(a)):
+ raise Exception('Numpy sqrt (%s) and math sqrt (%s) do not match!' 
+ % (numpy.sqrt(a), math.sqrt(a)))
+

uncertainties/umath_core.py

@@ -211,6 +211,8 @@ def _deriv_pow_1(x, y):
  'tanh': [lambda x: 1-math.tanh(x)**2]
  }
 
+make_an_attribute_of = ['sqrt']
+
 # Many built-in functions in the math module are wrapped with a
 # version which is uncertainty aware:
 
@@ -261,6 +263,8 @@ def wrapped_func(*args, **kwargs):
 
  # !! The same effect could be achieved with globals()[...] = ...
  setattr(this_module, name, wraps(wrapped_func, func))
+ if name in make_an_attribute_of:
+ setattr(AffineScalarFunc, name, wraps(wrapped_func, func))
 
  many_scalars_to_scalar_funcs.append(name)
 

uncertainties/unumpy/test_unumpy.py

@@ -68,6 +68,8 @@ def test_numpy():
  # TypeError (see PR #12700 in numpy repository)
  pass
  else:
+ # NOTE: if exp would be added as member method to AffineScalarFunc
+ # like sqrt already is, this would expectedly work
  raise Exception("numpy.exp unexpectedly worked")
 
  # Calculation of the mean, global and with a specific axis:
@@ -329,3 +331,21 @@ def test_obsolete():
  mat_obs = unumpy.umatrix.__call__(([1, 2], [1, 4])) # Obsolete call
  mat = unumpy.umatrix([1, 2], [1, 4])
  assert arrays_close(mat_obs, mat)
+
+def test_numpy_linalg_norm():
+ '''
+ Checks if numpy.linalg.norm method works.
+ ''' 
+ a = unumpy.uarray([3,4], [1,1])
+ magnitude = unumpy.nominal_values(numpy.linalg.norm(a))
+ if not(magnitude == 5):
+ raise Exception('numpy.linalg.norm([3,4]) does not return correct result!\n'
+ 'Expected 5, got %f' % magnitude)
+
+ if not (numpy.linalg.norm(a) == numpy.sqrt(numpy.sum(numpy.power(a, 2)))):
+ raise Exception('numpy.linalg.norm(%s) does not return correct result!\n'
+ 'Expected %s, got %s' 
+ % (a, 
+ numpy.sqrt(numpy.sum(numpy.power(a, 2))),
+ numpy.linalg.norm(a)))
+