public static Unit Register(Assembly asm)
{
#if COREFX13
Types = Types.AddRange(asm.DefinedTypes);
var newStructs = asm.DefinedTypes.Filter(t => t.IsValueType).ToList();
Structs = Structs.AddRange(newStructs);
var newClassInstances = newStructs.Filter(t => t.ImplementedInterfaces.Exists(i => i == typeof(Typeclass)));
AllClassInstances = AllClassInstances.AddRange(newClassInstances);
foreach (var ci in newClassInstances)
{
var typeClasses = ci.ImplementedInterfaces
.Filter(i => typeof(Typeclass).GetTypeInfo().IsAssignableFrom(i.GetTypeInfo()))
.Map(t => t.GetTypeInfo())
.Freeze();
ClassInstances = typeClasses.Fold(ClassInstances, (s, x) => s.AddOrUpdate(x, Some: cis => cis.AddOrUpdate(ci), None: () => Set <OrdTypeInfo, TypeInfo>(ci)));
}
#endif
return(unit);
}
public Replica ApplyRemoteOps(Lst <Operation> ops) => Copy(receivedOps: ops.AddRange(ReceivedOps)).ApplyRemote();
public static MatchResults MatchEventExpectations(IReadOnlyList <IEventExpectation> expectations, IReadOnlyList <NormalizedResult> results)
{
// deal with some edge cases first
if (expectations is null)
{
throw new ArgumentNullException(nameof(expectations));
}
if (results is null)
{
throw new ArgumentNullException(nameof(results));
}
// for each expectation
// find closest event, pair the results
var erroredExpectations = new Lst <ExpectationResult>();
var unmatchedExpectations = expectations.Index().ToHashMap();
// find distances between all expectations and all results
var distances = DenseMatrix.Create(expectations.Count, results.Count, double.PositiveInfinity);
for (int i = 0; i < expectations.Count; i++)
{
var expectation = expectations[i];
// do some error checking. If errors are found rows are skipped and distance is infinite
if (expectation.ErrorIfNoResults(results).Case is ExpectationResult error)
{
unmatchedExpectations = unmatchedExpectations.Remove(i);
erroredExpectations += error;
continue;
}
// measure all distances to each result
var rowDistances = results.Select(r => expectation.Distance(r));
var either = expectation.ErrorIfCannotMeasureDistance(rowDistances);
switch (either.Case)
{
case ExpectationResult distanceError:
unmatchedExpectations = unmatchedExpectations.Remove(i);
erroredExpectations += distanceError;
break;
case double[] values:
distances.SetRow(i, rowDistances.Select(v => v.IfFail(double.PositiveInfinity)).ToArray());
break;
default:
throw new InvalidOperationException();
}
}
// order distances from closest to furthest, keeping indexes
var ordered = distances.EnumerateIndexed().OrderBy(tuple => tuple.Item3);
var paired = new Lst <ExpectationMatch>();
var unmatchedResults = results.Index().ToHashMap();
// the first item is the best-matched expectation-result tuple, the last, the worst
foreach (var(i, j, d) in ordered)
{
if (d == double.PositiveInfinity)
{
// error case - reported already, but if we're here every other distance after this is an error
break;
}
if (unmatchedExpectations.IsEmpty || unmatchedResults.IsEmpty)
{
// we've run out of expectations or results there's no reason to continue
break;
}
var expectation = unmatchedExpectations.Find(i);
var result = unmatchedResults.Find(j);
if (expectation.Case is IEventExpectation e && result.Case is NormalizedResult r)
{
// add the match
paired += new ExpectationMatch(e, r);
unmatchedExpectations = unmatchedExpectations.Remove(i);
unmatchedResults = unmatchedResults.Remove(j);
}
// do nothing - other iterations will or will not match
}
// all expectations should have been matched with a result or should have generated an error
// anything left over means there are more expectations than results
erroredExpectations = erroredExpectations.AddRange(
unmatchedExpectations.Values.Select(CommonExpectations.ErrorIfNotEnoughResults));
// finally report results
return(new MatchResults(
paired,
erroredExpectations.ToArray(),
unmatchedResults.Values.ToArray()));
}