forked from lijiext/lammps
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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