public void load_from_iterator(long _rows, long _cols, long _nnz, entry_iterator_t entry_it)
{
rows = _rows;
cols = _cols;
nnz = _nnz;
mem_alloc_by_me = true;
with_weights = entry_it.with_weights;
val = new double[nnz];
val_t = new double[nnz];
row_idx = new long[nnz];
col_idx = new long[nnz]; // switch to this for memory
row_ptr = new long[rows + 1];
col_ptr = new long[cols + 1];
// a trick here to utilize the space the have been allocated
long[] perm = new long[_nnz];
long[] tmp_row_idx = col_idx;
long[] tmp_col_idx = row_idx;
double[] tmp_val = val;
for (long idx = 0; idx < _nnz; idx++)
{
rate_t rate = entry_it.next();
row_ptr[rate.i + 1]++;
col_ptr[rate.j + 1]++;
tmp_row_idx[idx] = rate.i;
tmp_col_idx[idx] = rate.j;
tmp_val[idx] = rate.v;
perm[idx] = idx;
}
// sort entries into row-majored ordering
Array.Sort(perm, new SparseComp(tmp_row_idx, tmp_col_idx, true));
// Generate CRS format
for (long idx = 0; idx < _nnz; idx++)
{
val_t[idx] = tmp_val[perm[idx]];
col_idx[idx] = tmp_col_idx[perm[idx]];
}
// Calculate nnz for each row and col
max_row_nnz = max_col_nnz = 0;
for (long r = 1; r <= rows; ++r)
{
max_row_nnz = Math.Max(max_row_nnz, row_ptr[r]);
row_ptr[r] += row_ptr[r - 1];
}
for (long c = 1; c <= cols; ++c)
{
max_col_nnz = Math.Max(max_col_nnz, col_ptr[c]);
col_ptr[c] += col_ptr[c - 1];
}
// Transpose CRS into CCS matrix
for (long r = 0; r < rows; ++r)
{
for (long i = row_ptr[r]; i < row_ptr[r + 1]; ++i)
{
long c = col_idx[i];
row_idx[col_ptr[c]] = r;
val[col_ptr[c]] = val_t[i];
if (with_weights)
{
weight[col_ptr[c]] = weight_t[i];
}
col_ptr[c]++;
}
}
for (long c = cols; c > 0; --c)
{
col_ptr[c] = col_ptr[c - 1];
}
col_ptr[0] = 0;
}
public void load(long _rows, long _cols, long _nnz, string filename, bool with_weights = false)
{
entry_iterator_t entry_it = new entry_iterator_t(_nnz, filename, with_weights);
load_from_iterator(_rows, _cols, _nnz, entry_it);
}
