def values_eq(a, b):
if a.shape != b.shape:
return False
if a.typecode != b.typecode:
return False
a_eq_b = numpy.asarray(compare(a, '==', b))
if a_eq_b.all():
return True
# maybe the trouble is that there are NaNs
a = numpy.asarray(a)
b = numpy.asarray(b)
a_missing = numpy.isnan(a)
if a_missing.any():
b_missing = numpy.isnan(b)
return numpy.all(a_eq_b + (a_missing == b_missing))
else:
return False
def values_eq(a, b, force_same_dtype=True):
if a.shape != b.shape:
return False
if force_same_dtype and a.typecode != b.typecode:
return False
a_eq_b = np.asarray(compare(a, '==', b))
if a_eq_b.all():
return True
# maybe the trouble is that there are NaNs
a = np.asarray(a)
b = np.asarray(b)
a_missing = np.isnan(a)
if a_missing.any():
b_missing = np.isnan(b)
return np.all(a_eq_b + (a_missing == b_missing))
else:
return False
def values_eq(a, b):
if a.shape != b.shape:
return False
if a.typecode != b.typecode:
return False
return numpy.asarray(compare(a, '==', b)).all()
def values_eq(a, b):
if a.shape != b.shape:
return False
if a.typecode != b.typecode:
return False
return numpy.asarray(compare(a, '==', b)).all()
