/// <summary>
/// Initializes a new <see cref="MarkovChainsNameGenerator"/> instance with specified
/// <see cref="MarkovChainMap{T}"/>, minimum frequency, minimum and maximum lengths, with specified capitalization
/// and whitespace-handling modes, with specified <see cref="Random"/> used to generate outputs, and eventually a
/// list of forbidden and/or already-produced outputs.
/// </summary>
/// <param name="map"><see cref="MarkovChainMap{T}"/> of strings used to produce outputs.</param>
/// <param name="random"><see cref="Random"/> which will be used for generating outputs. If null, a new
/// <see cref="Random"/> will be created automatically.</param>
/// <param name="minFrequency">The minimum frequency considered while producing random outputs. Please see
/// <see cref="Sieve{T}.MinFrequency"/>.</param>
/// <param name="minLength">The minimum length of produced outputs. Will be lower-bounded to one, eventually.
/// </param>
/// <param name="maxLength">The maximum length of produced outputs. Will be lower-bounded to
/// <paramref name="minLength"/>, eventually.</param>
/// <param name="capitalize">Whether or not outputs will be capitalized.</param>
/// <param name="skipWhitespace">Whether or not whitespaces will be ignored while parsing the sample file into a
/// <see cref="MarkovChainMap{T}"/>. Please see <see cref="MarkovChainStringMapBuilder.SkipWhitespace"/>.</param>
/// <param name="blacklistedNames">A list of forbiden and/or already produced outputs. This list will be qualified
/// further while new outputs are generated.</param>
/// <exception cref="ArgumentNullException"><paramref name="map"/> is null.</exception>
public MarkovChainsNameGenerator(MarkovChainMap <string> map, Random random = null,
int minFrequency = DefaultMinFrequency, int minLength = DefaultMinLength, int maxLength = DefaultMaxLength,
bool capitalize = true, bool skipWhitespace = true, IEnumerable <string> blacklistedNames = null)
: this(random, map.Depth, minFrequency, minLength, maxLength, capitalize, skipWhitespace, blacklistedNames)
{
_map = map;
}
/// <summary>
/// Merges the contents of a specified <see cref="MarkovChainMap{T}"/> with those of this one.
/// </summary>
/// <param name="other"><see cref="MarkovChainMap{T}"/> whose contents to merge to those of this map.</param>
/// <exception cref="NullReferenceException"><paramref name="other"/> is null.</exception>
public void Merge(MarkovChainMap <T> other)
{
T key;
foreach (var pair in other)
{
key = pair.Key;
EventuallyAdd(key, new FrequencyMap <T>());
this[key].Merge(pair.Value);
}
}
/// <summary>
/// Builds a new <see cref="MarkovChainMap{T}"/> from specified list of samples, and returns the result.
/// </summary>
/// <param name="samples">A collection of <typeparamref name="T"/> samples used to build the
/// <see cref="MarkovChainMap{T}"/>.</param>
/// <returns>A new <see cref="MarkovChainMap{T}"/> built from <paramref name="samples"/>.</returns>
/// <exception cref="ArgumentNullException"><paramref name="samples"/> is null.</exception>
public MarkovChainMap <T> Train(IEnumerable <T> samples)
{
MarkovChainMap <T> map = new MarkovChainMap <T>(_depth);
foreach (T sample in samples)
{
if (sample != null)
{
Train(map, sample);
}
}
return(map);
}
/// <summary>
/// Qualifies specified map with new data from specified sample.
/// </summary>
/// <param name="map"><see cref="MarkovChainMap{T}"/> to qualify.</param>
/// <param name="sample"><typeparamref name="T"/> value to train <paramref name="map"/> with.</param>
protected virtual void Train(MarkovChainMap <T> map, T sample)
{
T[] array = _partition(sample);
int length = array.Length;
int depth = 1;
FrequencyMap <T> frequencyMap;
StateFrequency stateFrequency;
T key, value;
int position, current, limit;
while (depth <= _depth)
{
if (depth < length)
{
limit = length - depth;
for (position = 0; (current = position + depth) < length; position++)
{
key = _aggregate(array, position, depth);
value = array[position + depth];
map.EventuallyAdd(key, new FrequencyMap <T>());
frequencyMap = map[key];
frequencyMap.EventuallyAdd(value, new StateFrequency());
stateFrequency = frequencyMap[value];
if (position == 0)
{
stateFrequency.IncrementFirst();
}
else if (current < limit)
{
stateFrequency.IncrementInner();
}
else
{
stateFrequency.IncrementLast();
}
}
}
depth++;
}
}
/// <summary>
/// Builds a new <see cref="MarkovChainMap{T}"/> from specified samples file. Please see
/// <see cref="MarkovChainStringMapBuilder.TrainFromFile(string, string)"/>.
/// </summary>
/// <param name="path">Path to the file containing the samples.</param>
/// <param name="commentSpecifier">An eventual comment specifier. Lines in the file beginning with this value
/// will not be parsed.</param>
public void TrainMapBuilder(string path, string commentSpecifier = "%")
{
_map = _mapBuilder.TrainFromFile(path, commentSpecifier);
}
