This update contains several small new features or usability improvements.
Descriptions and authorship information can be accessed from the pull
requests listed below.
Allow setting sigma parameter directly for metadynamics
https://github.com/Colvars/colvars/pull/325
Remove default values for lowerWall and upperWall legacy keywords
https://github.com/Colvars/colvars/pull/324
biasActualColvar option to bypass extended-Lagragian for a bias
https://github.com/Colvars/colvars/pull/321
Flexible restart-reading
https://github.com/Colvars/colvars/pull/320
232 lines
6.1 KiB
C++
232 lines
6.1 KiB
C++
// -*- c++ -*-
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// This file is part of the Collective Variables module (Colvars).
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// The original version of Colvars and its updates are located at:
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// https://github.com/Colvars/colvars
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// Please update all Colvars source files before making any changes.
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// If you wish to distribute your changes, please submit them to the
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// Colvars repository at GitHub.
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#include "colvarmodule.h"
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#include "colvarproxy.h"
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#include "colvar.h"
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#include "colvarbias_histogram.h"
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colvarbias_histogram::colvarbias_histogram(char const *key)
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: colvarbias(key),
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grid(NULL), out_name("")
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{
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provide(f_cvb_bypass_ext_lagrangian); // Allow histograms of actual cv for extended-Lagrangian
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}
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int colvarbias_histogram::init(std::string const &conf)
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{
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colvarbias::init(conf);
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enable(f_cvb_scalar_variables);
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enable(f_cvb_history_dependent);
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size_t i;
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get_keyval(conf, "outputFile", out_name, std::string(""));
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get_keyval(conf, "outputFileDX", out_name_dx, std::string(""));
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get_keyval(conf, "outputFreq", output_freq, cvm::restart_out_freq);
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/// with VMD, this may not be an error
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// if ( output_freq == 0 ) {
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// cvm::error("User required histogram with zero output frequency");
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// }
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colvar_array_size = 0;
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{
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bool colvar_array = false;
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get_keyval(conf, "gatherVectorColvars", colvar_array, colvar_array);
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if (colvar_array) {
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for (i = 0; i < num_variables(); i++) { // should be all vector
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if (colvars[i]->value().type() != colvarvalue::type_vector) {
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cvm::error("Error: used gatherVectorColvars with non-vector colvar.\n", INPUT_ERROR);
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return INPUT_ERROR;
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}
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if (i == 0) {
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colvar_array_size = colvars[i]->value().size();
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if (colvar_array_size < 1) {
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cvm::error("Error: vector variable has dimension less than one.\n", INPUT_ERROR);
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return INPUT_ERROR;
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}
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} else {
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if (colvar_array_size != colvars[i]->value().size()) {
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cvm::error("Error: trying to combine vector colvars of different lengths.\n", INPUT_ERROR);
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return INPUT_ERROR;
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}
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}
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}
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} else {
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for (i = 0; i < num_variables(); i++) { // should be all scalar
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if (colvars[i]->value().type() != colvarvalue::type_scalar) {
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cvm::error("Error: only scalar colvars are supported when gatherVectorColvars is off.\n", INPUT_ERROR);
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return INPUT_ERROR;
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}
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}
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}
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}
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if (colvar_array_size > 0) {
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weights.assign(colvar_array_size, 1.0);
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get_keyval(conf, "weights", weights, weights);
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}
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for (i = 0; i < num_variables(); i++) {
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colvars[i]->enable(f_cv_grid); // Could be a child dependency of a f_cvb_use_grids feature
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}
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grid = new colvar_grid_scalar();
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grid->init_from_colvars(colvars);
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if (is_enabled(f_cvb_bypass_ext_lagrangian)) {
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grid->request_actual_value();
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}
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{
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std::string grid_conf;
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if (key_lookup(conf, "histogramGrid", &grid_conf)) {
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grid->parse_params(grid_conf);
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grid->check_keywords(grid_conf, "histogramGrid");
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}
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}
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return COLVARS_OK;
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}
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colvarbias_histogram::~colvarbias_histogram()
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{
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if (grid) {
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delete grid;
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grid = NULL;
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}
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}
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int colvarbias_histogram::update()
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{
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int error_code = COLVARS_OK;
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// update base class
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error_code |= colvarbias::update();
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if (cvm::debug()) {
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cvm::log("Updating histogram bias " + this->name);
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}
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// assign a valid bin size
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bin.assign(num_variables(), 0);
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if (out_name.size() == 0) {
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// At the first timestep, we need to assign out_name since
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// output_prefix is unset during the constructor
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if (cvm::step_relative() == 0) {
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out_name = cvm::output_prefix() + "." + this->name + ".dat";
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cvm::log("Histogram " + this->name + " will be written to file \"" + out_name + "\"");
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}
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}
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if (out_name_dx.size() == 0) {
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if (cvm::step_relative() == 0) {
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out_name_dx = cvm::output_prefix() + "." + this->name + ".dx";
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cvm::log("Histogram " + this->name + " will be written to file \"" + out_name_dx + "\"");
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}
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}
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if (colvar_array_size == 0) {
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// update indices for scalar values
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size_t i;
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for (i = 0; i < num_variables(); i++) {
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bin[i] = grid->current_bin_scalar(i);
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}
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if (grid->index_ok(bin)) {
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grid->acc_value(bin, 1.0);
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}
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} else {
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// update indices for vector/array values
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size_t iv, i;
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for (iv = 0; iv < colvar_array_size; iv++) {
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for (i = 0; i < num_variables(); i++) {
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bin[i] = grid->current_bin_scalar(i, iv);
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}
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if (grid->index_ok(bin)) {
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grid->acc_value(bin, weights[iv]);
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}
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}
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}
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if (output_freq && (cvm::step_absolute() % output_freq) == 0) {
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write_output_files();
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}
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error_code |= cvm::get_error();
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return error_code;
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}
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int colvarbias_histogram::write_output_files()
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{
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if (!has_data) {
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// nothing to write
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return COLVARS_OK;
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}
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if (out_name.size()) {
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cvm::log("Writing the histogram file \""+out_name+"\".\n");
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cvm::backup_file(out_name.c_str());
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std::ostream *grid_os = cvm::proxy->output_stream(out_name);
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if (!grid_os) {
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return cvm::error("Error opening histogram file "+out_name+
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" for writing.\n", FILE_ERROR);
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}
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grid->write_multicol(*grid_os);
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cvm::proxy->close_output_stream(out_name);
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}
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if (out_name_dx.size()) {
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cvm::log("Writing the histogram file \""+out_name_dx+"\".\n");
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cvm::backup_file(out_name_dx.c_str());
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std::ostream *grid_os = cvm::proxy->output_stream(out_name_dx);
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if (!grid_os) {
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return cvm::error("Error opening histogram file "+out_name_dx+
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" for writing.\n", FILE_ERROR);
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}
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grid->write_opendx(*grid_os);
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cvm::proxy->close_output_stream(out_name_dx);
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}
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return COLVARS_OK;
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}
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std::istream & colvarbias_histogram::read_state_data(std::istream& is)
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{
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if (! read_state_data_key(is, "grid")) {
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return is;
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}
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if (! grid->read_raw(is)) {
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return is;
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}
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return is;
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}
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std::ostream & colvarbias_histogram::write_state_data(std::ostream& os)
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{
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std::ios::fmtflags flags(os.flags());
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os.setf(std::ios::fmtflags(0), std::ios::floatfield);
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os << "grid\n";
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grid->write_raw(os, 8);
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os.flags(flags);
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return os;
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}
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