void DataTypeArray::serializeTextCSV(const IColumn & column, size_t row_num, WriteBuffer & ostr, const FormatSettings & settings) const
{
/// There is no good way to serialize an array in CSV. Therefore, we serialize it into a string, and then write the resulting string in CSV.
WriteBufferFromOwnString wb;
serializeText(column, row_num, wb, settings);
writeCSV(wb.str(), ostr);
}
bool TwoDAFile::writeCSV(const Common::UString &fileName) const {
Common::WriteFile file;
if (!file.open(fileName))
return false;
writeCSV(file);
file.close();
return true;
}
void writeData(solver *Solver, input *params)
{
if (params->plot_type == 0) {
writeCSV(Solver,params);
}
else if (params->plot_type == 1) {
writeParaview(Solver,params);
}
}
void DataTypeArray::serializeTextCSV(const IColumn & column, size_t row_num, WriteBuffer & ostr) const
{
/// There is no good way to serialize an array in CSV. Therefore, we serialize it into a string, and then write the resulting string in CSV.
String s;
{
WriteBufferFromString wb(s);
serializeText(column, row_num, wb);
}
writeCSV(s, ostr);
}
void DataTypeArray::serializeTextCSV(const IColumn & column, size_t row_num, WriteBuffer & ostr) const
{
/// Хорошего способа сериализовать массив в CSV нет. Поэтому сериализуем его в строку, а затем полученную строку запишем в CSV.
String s;
{
WriteBufferFromString wb(s);
serializeText(column, row_num, wb);
}
writeCSV(s, ostr);
}
// Helper function to write an Eigen::MatrixXd to a CSV file.
static void writeEigenMatrixXdCSV(const Eigen::MatrixXd& matrix, const std::string& filename) {
StringMatrix string_matrix;
string_matrix.reserve(matrix.rows());
StringRow string_row;
string_row.reserve(matrix.cols());
for (size_t i = 0u; i < matrix.rows(); ++i) {
string_row.clear();
for (size_t j = 0u; j < matrix.cols(); ++j) {
string_row.push_back(std::to_string(matrix(i,j)));
}
string_matrix.push_back(string_row);
}
writeCSV(string_matrix, filename);
}
void DataTypeAggregateFunction::serializeTextCSV(const IColumn & column, size_t row_num, WriteBuffer & ostr) const
{
writeCSV(serializeToString(function, column, row_num), ostr);
}
void menuWriteCSV(){
clr();
printf("Generando archivo CSV...");
writeCSV();
}
int main(int argc, char* argv[])
{
/**************************** config **********************************/
int N = 512;
int scaleby = 16384;
/**********************************************************************/
if ( argc != 3 ) {
printf( "usage: %s input-file-name output-file-name\n", argv[0] );
return 1;
}
char* fin = argv[1];
char* fout = argv[2];
int i,j,axis;
int nLines = getNumberOfLines(fin);
int log2nLines = fix_log2(nLines);
int padLines = (1<<(log2nLines+1)) - nLines;
int dataLines = 1<<(log2nLines+1);
// FFT size and input signal size
int log2n = fix_log2(N);
int loops = dataLines>>log2n;
// read CSV and pad with 0's until the next power of 2^m
readCSV(fin, 6, 0, nLines);
for ( i=0; i<padLines; ++i ) {
for ( axis=0; axis<6; ++axis ) {
dataIn[nLines+i][axis] = 0;
}
}
for ( axis=0; axis<6; ++axis ) {
// remove the mean, keep only signal with amp > 1, and scale the data
int sum = 0, mean = 0;
for ( j=0; j<nLines; j++ ) {
sum += dataIn[j][axis];
}
mean = sum>>log2nLines;
for ( j=0; j<nLines; j++ ) {
dataIn[j][axis] -= mean;
}
int scalefactor = fix_log2(scaleby);
for ( j=0; j<nLines; j++ ) {
if (dataIn[j][axis] != 0) {
dataIn[j][axis] <<= scalefactor;
}
}
// loop over the data in N segments and FFT
int re[N], im[N], amp[N];
for ( j=0; j<N; ++j ) { amp[j] = 0; }
for ( j=0; j<loops; ++j ) {
for( i=0; i<N; i++ ) {
im[i] = 0;
re[i] = dataIn[N*j+i][axis];
}
// compute the FFT of the samples
fix_fft(re,im,log2n,0);
for (i=1; i<N; i++){
amp[i] += re[i]*re[i] + im[i]*im[i];
}
}
// average the frequency-bin amplitudes over nonzero sampled dataset
int nonzeros = 0;
for ( j=0; j<N; ++j ) {
if ( amp[j] != 0 ) ++nonzeros;
}
for ( j=1; j<N; j++ ) {
amp[j] = sqrt(amp[j]);
amp[j] >>= fix_log2(nonzeros);
}
// store in six-axis array
for ( j=0; j<N; ++j ) {
ampFull[j][axis] = amp[j];
}
}
writeCSV(fout, ampFull, 6, N/2);
return 0;
}
