FL::ParseResult AB::analyze(
const TimeSeries &ts, Forest &forest, Patterns::Matcher &matcher, PatternsSet &patterns, MetricsSet &metrics)
{
ParseResult result;
try
{
if (ts.size() < 2)
throw EAnalyze(E_INVALID_INPUT);
Tree *tree = new Tree(ts);
const int up = IDGenerator::idOf("a");
const int down = IDGenerator::idOf("b");
for (int i = 0; i < ts.size()-1; i += 1)
{
const int &id = (ts.value(i) <= ts.value(i+1)) ? up : down;
tree->add(new Node(NULL, id, i, i+1, 0));
}
forest.push_back(tree);
result.treesAdded = 1;
result.nodesAdded = (ts.size() + 1) / 2;
}
catch (const EAnalyze &e)
{
m_lastError = e;
}
return result;
}
bool FileCSV::save(const std::string &fileName, TimeSeries &ts)
{
std::ofstream file(fileName.c_str());
if (!file.is_open())
return false;
// Write header
for (unsigned int i = 0; i < ts.header().size(); ++i)
{
file << ts.header()[i];
if (i < ts.header().size() - 1)
file << m_separator;
}
// Write data
for (int row = 0; row < ts.size(); ++row)
{
file << std::endl << ts.time(row) << m_separator << ts.value(row);
}
file << std::endl;
file.close();
return true;
}
TEST_F(DataFixture,TimeSeries_AddSubtractSameTimePeriod)
{
std::string units = "W";
Date startDate(Date(MonthOfYear(MonthOfYear::Feb),21));
DateTime startDateTime(startDate, Time(0,1,0,0));
// interval
Time interval = Time(0,1,0,0);
Vector intervalValues(3);
intervalValues(0) = 0;
intervalValues(1) = 1;
intervalValues(2) = 2;
TimeSeries intervalTimeSeries(startDateTime, interval, intervalValues, units);
ASSERT_TRUE(!intervalTimeSeries.values().empty());
// detailed
DateTimeVector dateTimes;
dateTimes.push_back(startDateTime + Time(0,0,0,0));
dateTimes.push_back(startDateTime + Time(0,0,30,0));
dateTimes.push_back(startDateTime + Time(0,1,0,0));
dateTimes.push_back(startDateTime + Time(0,1,30,0));
dateTimes.push_back(startDateTime + Time(0,2,0,0));
Vector detailedValues(5);
detailedValues(0) = 0.0; // 1:00
detailedValues(1) = 0.5; // 1:30
detailedValues(2) = 1.0; // 2:00
detailedValues(3) = 1.5; // 2:30
detailedValues(4) = 2.0; // 3:00
TimeSeries detailedTimeSeries(dateTimes, detailedValues, units);
ASSERT_TRUE(!detailedTimeSeries.values().empty());
// sum and difference
TimeSeries sum = intervalTimeSeries + detailedTimeSeries;
TimeSeries diff1 = intervalTimeSeries - detailedTimeSeries;
TimeSeries diff2 = detailedTimeSeries - intervalTimeSeries;
ASSERT_TRUE(!sum.values().empty());
ASSERT_TRUE(!diff1.values().empty());
ASSERT_TRUE(!diff2.values().empty());
// EXPECT_EQ((unsigned)5, sum.dateTimes().size());
// EXPECT_EQ((unsigned)5, diff1.dateTimes().size());
// EXPECT_EQ((unsigned)5, diff2.dateTimes().size());
EXPECT_EQ((unsigned)5, sum.daysFromFirstReport().size());
EXPECT_EQ((unsigned)5, diff1.daysFromFirstReport().size());
EXPECT_EQ((unsigned)5, diff2.daysFromFirstReport().size());
// EXPECT_EQ(startDateTime, sum.dateTimes().front());
// EXPECT_EQ(startDateTime, diff1.dateTimes().front());
// EXPECT_EQ(startDateTime, diff2.dateTimes().front());
EXPECT_EQ(startDateTime, sum.firstReportDateTime());
EXPECT_EQ(startDateTime, diff1.firstReportDateTime());
EXPECT_EQ(startDateTime, diff2.firstReportDateTime());
DateTime endDateTime = startDateTime + Time(0,2,0,0);
// EXPECT_EQ(endDateTime, sum.dateTimes().back());
// EXPECT_EQ(endDateTime, diff1.dateTimes().back());
// EXPECT_EQ(endDateTime, diff2.dateTimes().back());
EXPECT_EQ(endDateTime, sum.firstReportDateTime() + Time(sum.daysFromFirstReport(sum.daysFromFirstReport().size()-1)));
EXPECT_EQ(endDateTime, diff1.firstReportDateTime() + Time(diff1.daysFromFirstReport(diff1.daysFromFirstReport().size()-1)));
EXPECT_EQ(endDateTime, diff2.firstReportDateTime() + Time(diff2.daysFromFirstReport(diff2.daysFromFirstReport().size()-1)));
// 1:00
EXPECT_EQ(0, sum.value(Time(0,0,0,0)));
EXPECT_EQ(0, diff1.value(Time(0,0,0,0)));
EXPECT_EQ(0, diff2.value(Time(0,0,0,0)));
// 1:30
EXPECT_EQ(1.5, sum.value(Time(0,0,30,0)));
EXPECT_EQ(0.5, diff1.value(Time(0,0,30,0)));
EXPECT_EQ(-0.5, diff2.value(Time(0,0,30,0)));
// 2:00
EXPECT_EQ(2, sum.value(Time(0,1,0,0)));
EXPECT_EQ(0.0, diff1.value(Time(0,1,0,0)));
EXPECT_EQ(0.0, diff2.value(Time(0,1,0,0)));
// 2:30
EXPECT_EQ(3.5, sum.value(Time(0,1,30,0)));
EXPECT_EQ(0.5, diff1.value(Time(0,1,30,0)));
EXPECT_EQ(-0.5, diff2.value(Time(0,1,30,0)));
// Test helper function for summing a vector.
TimeSeriesVector sumAndDiffs;
sumAndDiffs.push_back(sum);
sumAndDiffs.push_back(diff1);
sumAndDiffs.push_back(diff2);
TimeSeries ans = openstudio::sum(sumAndDiffs);
EXPECT_FALSE(ans.values().empty());
// 1:00
EXPECT_DOUBLE_EQ(0, ans.value(Time(0,0,0,0)));
// 1:30
EXPECT_DOUBLE_EQ(1.5, ans.value(Time(0,0,30,0)));
// 2:00
EXPECT_DOUBLE_EQ(2.0, ans.value(Time(0,1,0,0)));
// 2:30
EXPECT_DOUBLE_EQ(3.5, ans.value(Time(0,1,30,0)));
// Test multiplication and division with a scalar
sumAndDiffs.push_back(sum/2.0);
sumAndDiffs.push_back(3.0*diff1);
ans = openstudio::sum(sumAndDiffs);
EXPECT_FALSE(ans.values().empty());
// 1:00
EXPECT_DOUBLE_EQ(0, ans.value(Time(0,0,0,0)));
// 1:30
EXPECT_DOUBLE_EQ(3.75, ans.value(Time(0,0,30,0)));
// 2:00
EXPECT_DOUBLE_EQ(3.0, ans.value(Time(0,1,0,0)));
// 2:30
EXPECT_DOUBLE_EQ(6.75, ans.value(Time(0,1,30,0)));
}
