Even more thorough automatic tests for (linear) operators

nifty5/extra.py

@@ -17,8 +17,10 @@
 
 import numpy as np
 
+from .domain_tuple import DomainTuple
 from .field import Field
 from .linearization import Linearization
+from .multi_domain import MultiDomain
 from .operators.linear_operator import LinearOperator
 from .sugar import from_random
 
@@ -76,6 +78,13 @@ def _check_linearity(op, domain_dtype, atol, rtol):
     _assert_allclose(val1, val2, atol=atol, rtol=rtol)
 
 
+def _domain_check(op):
+    for dd in [op.domain, op.target]:
+        if not isinstance(dd, (DomainTuple, MultiDomain)):
+            raise TypeError('The domain and the target of an operator need to',
+                            'be instances of either DomainTuple or MultiDomain.')
+
+
 def consistency_check(op, domain_dtype=np.float64, target_dtype=np.float64,
                       atol=0, rtol=1e-7, only_r_linear=False):
     """
@@ -109,6 +118,7 @@ def consistency_check(op, domain_dtype=np.float64, target_dtype=np.float64,
     """
     if not isinstance(op, LinearOperator):
         raise TypeError('This test tests only linear operators.')
+    _domain_check(op)
     _check_linearity(op, domain_dtype, atol, rtol)
     _full_implementation(op, domain_dtype, target_dtype, atol, rtol,
                          only_r_linear)
@@ -162,6 +172,7 @@ def check_jacobian_consistency(op, loc, tol=1e-8, ntries=100):
     tol : float
         Tolerance for the check.
     """
+    _domain_check(op)
     for _ in range(ntries):
         lin = op(Linearization.make_var(loc))
         loc2, lin2 = _get_acceptable_location(op, loc, lin)