public Dictionary <string, string> GetStatistics()
{
if (_statistics != null)
{
return(_statistics);
}
Logger.Current.Info("Calculating dataContainer '{0}' statistics...", Id);
_statistics = new Dictionary <string, string>();
long matrixCount = (long)Users.Count * Items.Count;
double sparsity = (double)100L * (matrixCount - Feedbacks.Count) / matrixCount;
var users = new Dictionary <string, int>();
var items = new Dictionary <string, int>();
foreach (Feedback f in Feedbacks)
{
string userId = f.User.Id;
string itemId = f.Item.Id;
if (!users.ContainsKey(userId))
{
users[userId] = 1;
}
else
{
users[userId]++;
}
if (!items.ContainsKey(itemId))
{
items[itemId] = 1;
}
else
{
items[itemId]++;
}
}
var feedbackAttrs = Feedbacks.First().Attributes.Values.Select(a => a.Name).Distinct().ToList();
var userAttrs = Feedbacks.First().User.Attributes.Values.Select(a => a.Name).Distinct().ToList();
var itemAttrs = Feedbacks.First().Item.Attributes.Values.Select(a => a.Name).Distinct().ToList();
_statistics.Add("containerId", Id);
_statistics.Add("feedbacks", Feedbacks.Count.ToString());
_statistics.Add("users", Users.Count.ToString());
_statistics.Add("items", Items.Count.ToString());
_statistics.Add("sparsity", string.Format("{0:0.00}", sparsity));
_statistics.Add("usrMinFb", users.Values.Min().ToString());
_statistics.Add("usrMaxFb", users.Values.Max().ToString());
_statistics.Add("usrAvgFb", string.Format("{0:0.00}", users.Values.Average()));
_statistics.Add("itmMinFb", items.Values.Min().ToString());
_statistics.Add("itmMaxFb", items.Values.Max().ToString());
_statistics.Add("itmAvgFb", string.Format("{0:0.00}", items.Values.Average()));
_statistics.Add("allFeedbackAttrs", feedbackAttrs.Count > 0 ? feedbackAttrs.Aggregate((a, b) => a + "|" + b) : "NA");
_statistics.Add("allUserAttrs", userAttrs.Count > 0 ? userAttrs.Aggregate((a, b) => a + "|" + b) : "NA");
_statistics.Add("allItemAttrs", itemAttrs.Count > 0 ? itemAttrs.Aggregate((a, b) => a + "|" + b) : "NA");
return(_statistics);
}
