/* -------------------------------------------------------------------- */
void DiffPreFilter(DATASET_INFO *set, float out[])
{
size_t i;
for (i = set->nPoints-1; i > 0; --i)
if (isMissingValue(out[i], set->missingValue) || isMissingValue(out[i-1], set->missingValue))
out[i] = set->missingValue;
else
out[i] = out[i] - out[i-1];
out[0] = 0.0;
} /* END DIFFPREFILTER */
void Utils::replaceMissingWithMAX_VALUE(double_array &array_Renamed) {
for (int i = 0; i < array_Renamed.size(); i++) {
if (isMissingValue(array_Renamed[i])) {
array_Renamed[i] = std::numeric_limits<double>::max();
}
}
}
/* -------------------------------------------------------------------- */
void DetrendMean(DATASET_INFO *set, float out[])
{
size_t i;
float datum;
for (i = 0; i < set->nPoints; ++i)
{
datum = out[i];
if (isMissingValue(datum, set->missingValue))
out[i] = out[i-1];
else
out[i] = datum - set->stats.mean;
}
} /* END DETRENDMEAN */
/* -------------------------------------------------------------------- */
void DetrendLinear(DATASET_INFO *set, float out[])
{
size_t i;
float datum, *out1;
out1 = new float[set->nPoints];
LinearLeastSquare(set, out, out1);
for (i = 0; i < set->nPoints; ++i)
{
datum = out[i];
if (isMissingValue(datum, set->missingValue))
out[i] = out[i-1];
else
out[i] = datum - out1[i];
}
delete [] out1;
} /* END DETRENDLINEAR */
template<> QString valueToString<QTime>(QTime value) {
return isMissingValue(value) ? QString("NA") :value.toString("0:0:0");
}
template<> QString valueToString<QDate>(QDate value) {
return isMissingValue(value) ? QString("NA") :value.toString("d/M/yyyy");
}
template<> QString valueToString<char>(char value) {
return isMissingValue(value) ? QString("NA") :QString(value);
}
/* -------------------------------------------------------------------- */
void ComputeStats(DATASET_INFO *set)
{
size_t i, missCnt, len = 0;
double y, sum, sigma;
/* Read in variables units from file.
*/
buffer[0] = '\0';
if (set->varInfo->inVarID != COMPUTED)
{
nc_inq_attlen(dataFile[set->fileIndex].ncid, set->varInfo->inVarID,
"units", (size_t *)&len);
nc_get_att_text(dataFile[set->fileIndex].ncid, set->varInfo->inVarID,
"units", buffer);
buffer[len] = '\0';
while (isspace(buffer[--len]) || buffer[len] == 0) // Strip trailing spaces.
buffer[len] = '\0';
if (strcmp(buffer, "C") == 0 ||
strcmp(buffer, "deg_C") == 0)
{
buffer[0] = 0xb0;
buffer[1] = 'C';
buffer[2] = '\0';
}
}
else
strcpy(buffer, "Unknown");
set->stats.units = buffer;
missCnt = 0;
sum = sigma = 0.0;
set->stats.min = FLT_MAX;
set->stats.max = -FLT_MAX;
for (i = 0; i < set->nPoints; ++i)
{
if (isMissingValue((y = set->data[i]), set->missingValue) ||
y < set->stats.outlierMin || y > set->stats.outlierMax)
{
++missCnt;
continue;
}
set->stats.min = std::min(set->stats.min, y);
set->stats.max = std::max(set->stats.max, y);
sum += y;
}
if (set->nPoints == missCnt)
{
set->stats.mean = 0.0;
set->stats.min = 0.0;
set->stats.max = 0.0;
}
else
{
set->stats.nPoints = set->nPoints - missCnt;
set->stats.mean = sum / set->stats.nPoints;
}
for (i = 0; i < set->nPoints; ++i)
if (!isMissingValue((y = set->data[i]), set->missingValue) ||
y < set->stats.outlierMin || y > set->stats.outlierMax)
sigma += pow(y - set->stats.mean, 2.0);
set->stats.variance = sigma / (set->stats.nPoints - 1);
set->stats.sigma = (float)sqrt(sigma / (set->stats.nPoints - 1));
} /* END COMPUTESTATS */
