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Save latest changes, boundaries still missing or incomplete
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2b74fca740
@ -17,7 +17,7 @@ pqc_to_grid <- function(pqc_in, grid) {
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# Iterate over each ID in the vector
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for (id_mat in id_vector) {
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# Find the matching row in the data.table
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matching_dt <- dt[id == id_mat]
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matching_dt <- dt[dt$id == id_mat]
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# Append the matching data.table row to the result data.table
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result_dt <- rbind(result_dt, matching_dt)
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@ -36,14 +36,15 @@ test <- pqc_init
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modify_module_sizes <- function(mod_sizes, pqc_mat, init_grid) {
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# Find all unique IDs in init_grid
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unique_ids <- unique(as.vector(init_grid$id))
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unique_ids <- unique(init_grid$id)
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# remove rows from pqc_mat that are not in init_grid
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pqc_mat <- as.data.frame(pqc_mat)
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pqc_mat <- pqc_mat[pqc_mat$id %in% unique_ids, ]
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# Find the column indices where all rows are NA
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na_cols <- which(colSums(is.na(pqc_mat)) == nrow(pqc_mat))
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# Find the column indices where all rows are NaN
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na_cols <- which(sapply(pqc_mat, function(x) all(is.na(x))))
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# na_cols <- which(colSums(is.nan(pqc_mat)) == nrow(pqc_mat))
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# Build cumsum over mod_sizes
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cum_mod_sizes <- cumsum(mod_sizes)
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@ -1 +1 @@
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Subproject commit 54136c8e0c638d0dc47e85cef1428822b6c1512d
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Subproject commit d92ab31765d3850beb0b9e980b7b82696e56e4fc
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@ -1,6 +1,7 @@
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add_library(poetinitlib
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Init/InitialList.cpp
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Init/GridInit.cpp
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Init/DiffusionInit.cpp
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)
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target_link_libraries(poetinitlib PUBLIC
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166
src/Init/DiffusionInit.cpp
Normal file
166
src/Init/DiffusionInit.cpp
Normal file
@ -0,0 +1,166 @@
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#include <tug/Boundary.hpp>
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// leave above Rcpp includes, as eigen seem to have problems with a preceding
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// Rcpp include
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#include <map>
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#include <set>
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#include "InitialList.hpp"
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#include <Rcpp/proxy/ProtectedProxy.h>
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#include <Rcpp/vector/instantiation.h>
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#include <Rinternals.h>
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#include <cstddef>
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#include <cstdint>
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#include <stdexcept>
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#include <string>
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#include <vector>
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namespace poet {
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enum SEXP_TYPE { SEXP_IS_LIST, SEXP_IS_MAT, SEXP_IS_NUM };
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const std::map<std::uint8_t, std::string> tug_side_mapping = {
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{tug::BC_SIDE_RIGHT, "E"},
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{tug::BC_SIDE_LEFT, "W"},
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{tug::BC_SIDE_TOP, "N"},
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{tug::BC_SIDE_BOTTOM, "S"}};
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static Rcpp::List parseBoundaries2D(const Rcpp::List &boundaries_list,
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std::uint32_t n_cols,
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std::uint32_t n_rows) {
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Rcpp::List out_list;
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for (const auto &side : tug_side_mapping) {
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Rcpp::NumericVector type =
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(side.first == tug::BC_SIDE_RIGHT || side.first == tug::BC_SIDE_LEFT)
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? Rcpp::NumericVector(n_rows, tug::BC_TYPE_CLOSED)
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: Rcpp::NumericVector(n_cols, tug::BC_TYPE_CLOSED);
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Rcpp::NumericVector value =
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(side.first == tug::BC_SIDE_RIGHT || side.first == tug::BC_SIDE_LEFT)
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? Rcpp::NumericVector(n_rows, 0)
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: Rcpp::NumericVector(n_cols, 0);
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if (boundaries_list.containsElementNamed(side.second.c_str())) {
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const Rcpp::List mapping = boundaries_list[side.second];
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const Rcpp::NumericVector cells = mapping["cells"];
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const Rcpp::NumericVector values = mapping["sol_id"];
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if (cells.size() != values.size()) {
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throw std::runtime_error("Boundary [" + side.second +
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"] cells and values are not the same length");
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}
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}
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out_list[side.second] = Rcpp::List::create(Rcpp::Named("type") = type,
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Rcpp::Named("value") = value);
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}
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}
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static inline SEXP_TYPE get_datatype(const SEXP &input) {
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Rcpp::Function check_list("is.list");
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Rcpp::Function check_mat("is.matrix");
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if (Rcpp::as<bool>(check_list(input))) {
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return SEXP_IS_LIST;
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} else if (Rcpp::as<bool>(check_mat(input))) {
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return SEXP_IS_MAT;
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} else {
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return SEXP_IS_NUM;
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}
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}
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static Rcpp::List parseAlphas2D(const SEXP &input,
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const std::vector<std::string> &transport_names,
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std::uint32_t n_cols, std::uint32_t n_rows) {
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Rcpp::List out_list;
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SEXP_TYPE input_type = get_datatype(input);
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switch (input_type) {
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case SEXP_IS_LIST: {
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const Rcpp::List input_list(input);
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if (input_list.size() != transport_names.size()) {
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throw std::runtime_error(
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"Length of alphas list does not match number of transport names");
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}
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for (const auto &name : transport_names) {
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if (!input_list.containsElementNamed(name.c_str())) {
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throw std::runtime_error("Alphas list does not contain transport name");
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}
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const Rcpp::NumericMatrix alpha_mat(input_list[name]);
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if (alpha_mat.size() == 1) {
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Rcpp::NumericVector alpha(n_cols * n_rows, alpha_mat(0, 0));
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out_list[name] = Rcpp::wrap(alpha);
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} else {
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if (alpha_mat.nrow() != n_rows || alpha_mat.ncol() != n_cols) {
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throw std::runtime_error(
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"Alpha matrix does not match grid dimensions");
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}
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out_list[name] = alpha_mat;
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}
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}
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break;
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}
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case SEXP_IS_MAT: {
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Rcpp::NumericMatrix input_mat(input);
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Rcpp::NumericVector alpha(n_cols * n_rows, input_mat(0, 0));
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if (input_mat.size() != 1) {
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if (input_mat.nrow() != n_rows || input_mat.ncol() != n_cols) {
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throw std::runtime_error("Alpha matrix does not match grid dimensions");
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}
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for (std::size_t i = 0; i < n_rows; i++) {
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for (std::size_t j = 0; j < n_cols; j++) {
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alpha[i * n_cols + j] = input_mat(i, j);
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}
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}
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}
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for (const auto &name : transport_names) {
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out_list[name] = alpha;
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}
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break;
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}
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case SEXP_IS_NUM: {
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Rcpp::NumericVector alpha(n_cols * n_rows, Rcpp::as<TugType>(input));
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for (const auto &name : transport_names) {
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out_list[name] = alpha;
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}
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break;
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}
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default:
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throw std::runtime_error("Unknown data type");
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}
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return out_list;
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}
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void InitialList::initDiffusion(const Rcpp::List &diffusion_input) {
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const Rcpp::List &boundaries = diffusion_input["boundaries"];
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const SEXP &alpha_x = diffusion_input["alpha_x"];
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const SEXP &alpha_y = diffusion_input["alpha_y"];
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std::vector<std::string> colnames =
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Rcpp::as<std::vector<std::string>>(this->initial_grid.names());
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std::vector<std::string> transport_names(colnames.begin() + 1,
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colnames.begin() + 1 +
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this->module_sizes[POET_SOL]);
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this->alpha_x =
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parseAlphas2D(alpha_x, transport_names, this->n_cols, this->n_rows);
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this->alpha_y =
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parseAlphas2D(alpha_y, transport_names, this->n_cols, this->n_rows);
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}
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} // namespace poet
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@ -3,5 +3,6 @@
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namespace poet {
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void InitialList::initializeFromList(const Rcpp::List &setup) {
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initGrid(setup["grid"]);
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initDiffusion(setup["diffusion"]);
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}
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} // namespace poet
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@ -6,9 +6,13 @@
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#include <cstdint>
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#include <IPhreeqcPOET.hpp>
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#include <utility>
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#include <vector>
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namespace poet {
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using TugType = double;
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class InitialList {
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public:
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InitialList(RInside &R) : R(R){};
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@ -43,5 +47,12 @@ private:
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// Chemistry members
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IPhreeqcPOET::ModulesArray module_sizes;
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// Diffusion members
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void initDiffusion(const Rcpp::List &diffusion_input);
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Rcpp::List boundaries;
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Rcpp::List alpha_x;
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Rcpp::List alpha_y;
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};
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} // namespace poet
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396
src/poet.hpp
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396
src/poet.hpp
Normal file
@ -0,0 +1,396 @@
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#ifndef POET_H
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#define POET_H
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#include <string>
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static const char *poet_version = "tmp/ml/v0.2-107-g9990c12";
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// using the Raw string literal to avoid escaping the quotes
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static inline std::string kin_r_library = R"(## Time-stamp: "Last modified 2023-08-15 11:58:23 delucia"
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### Copyright (C) 2018-2023 Marco De Lucia, Max Luebke (GFZ Potsdam)
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###
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### POET is free software; you can redistribute it and/or modify it under the
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### terms of the GNU General Public License as published by the Free Software
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### Foundation; either version 2 of the License, or (at your option) any later
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### version.
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###
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### POET is distributed in the hope that it will be useful, but WITHOUT ANY
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### WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
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### A PARTICULAR PURPOSE. See the GNU General Public License for more details.
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###
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### You should have received a copy of the GNU General Public License along with
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### this program; if not, write to the Free Software Foundation, Inc., 51
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### Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
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## Simple function to check file extension. It is needed to check if
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## the GridFile is SUM (MUFITS format) or rds/RData
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FileExt <- function(x) {
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pos <- regexpr("\\.([[:alnum:]]+)$", x)
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ifelse(pos > -1L, substring(x, pos + 1L), "")
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}
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master_init <- function(setup) {
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msgm("Process with rank 0 reading GRID properties")
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## Setup the directory where we will store the results
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verb <- FALSE
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if (local_rank == 0) {
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verb <- TRUE ## verbosity loading MUFITS results
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if (!dir.exists(fileout)) {
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dir.create(fileout)
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msgm("created directory ", fileout)
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} else {
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msgm("dir ", fileout, " already exists, I will overwrite!")
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}
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if (!exists("store_result")) {
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msgm("store_result doesn't exist!")
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} else {
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msgm("store_result is ", store_result)
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}
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} else {
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}
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setup$iter <- 1
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setup$maxiter <- setup$iterations
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setup$timesteps <- setup$timesteps
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setup$simulation_time <- 0
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if (is.null(setup[["store_result"]])) {
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setup$store_result <- TRUE
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}
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if (setup$store_result) {
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if (is.null(setup[["out_save"]])) {
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setup$out_save <- seq(1, setup$iterations)
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}
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}
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return(setup)
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}
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## This function, called only by master, stores on disk the last
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## calculated time step if store_result is TRUE and increments the
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## iteration counter
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master_iteration_end <- function(setup) {
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iter <- setup$iter
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## max digits for iterations
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dgts <- as.integer(ceiling(log10(setup$iterations + 1)))
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## string format to use in sprintf
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fmt <- paste0("%0", dgts, "d")
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## Write on disk state_T and state_C after every iteration
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## comprised in setup$out_save
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if (setup$store_result) {
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if (iter %in% setup$out_save) {
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nameout <- paste0(fileout, "/iter_", sprintf(fmt=fmt, iter), ".rds")
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info <- list(
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tr_req_dt = as.integer(setup$req_dt)
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## tr_allow_dt = setup$allowed_dt,
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## tr_inniter = as.integer(setup$inniter)
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)
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saveRDS(list(
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T = setup$state_T, C = setup$state_C,
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simtime = as.integer(setup$simtime),
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tr_info = info
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), file = nameout)
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msgm("results stored in <", nameout, ">")
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}
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}
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msgm("done iteration", iter, "/", setup$maxiter)
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setup$iter <- setup$iter + 1
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return(setup)
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}
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## function for the workers to compute chemistry through PHREEQC
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slave_chemistry <- function(setup, data) {
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base <- setup$base
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first <- setup$first
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prop <- setup$prop
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immobile <- setup$immobile
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kin <- setup$kin
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ann <- setup$ann
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iter <- setup$iter
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timesteps <- setup$timesteps
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dt <- timesteps[iter]
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state_T <- data ## not the global field, but the work-package
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## treat special H+/pH, e-/pe cases
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state_T <- RedModRphree::Act2pH(state_T)
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## reduction of the problem
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if (setup$reduce) {
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reduced <- ReduceStateOmit(state_T, omit = setup$ann)
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} else {
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reduced <- state_T
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}
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## form the PHREEQC input script for the current work package
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inplist <- SplitMultiKin(
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data = reduced, procs = 1, base = base, first = first,
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ann = ann, prop = prop, minerals = immobile, kin = kin, dt = dt
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)
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## if (local_rank==1 & iter==1)
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## RPhreeWriteInp("FirstInp", inplist)
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tmpC <- RunPQC(inplist, procs = 1, second = TRUE)
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## recompose after the reduction
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if (setup$reduce) {
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state_C <- RecomposeState(tmpC, reduced)
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} else {
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state_C <- tmpC
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}
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## the next line is needed since we don't need all columns of
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## PHREEQC output
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return(state_C[, prop])
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}
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## This function, called by master
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master_chemistry <- function(setup, data) {
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state_T <- setup$state_T
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msgm(" chemistry iteration", setup$iter)
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## treat special H+/pH, e-/pe cases
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state_T <- RedModRphree::Act2pH(state_T)
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## reduction of the problem
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if (setup$reduce) {
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reduced <- ReduceStateOmit(state_T, omit = setup$ann)
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} else {
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reduced <- state_T
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}
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## inject data from workers
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res_C <- data
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rownames(res_C) <- NULL
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## print(res_C)
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if (nrow(res_C) > nrow(reduced)) {
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res_C <- res_C[seq(2, nrow(res_C), by = 2), ]
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}
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## recompose after the reduction
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if (setup$reduce) {
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state_C <- RecomposeState(res_C, reduced)
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} else {
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state_C <- res_C
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}
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setup$state_C <- state_C
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setup$reduced <- reduced
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return(setup)
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}
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## Adapted version for "reduction"
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ReduceStateOmit <- function(data, omit = NULL, sign = 6) {
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require(mgcv)
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rem <- colnames(data)
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if (is.list(omit)) {
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indomi <- match(names(omit), colnames(data))
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datao <- data[, -indomi]
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} else {
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datao <- data
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}
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datao <- signif(datao, sign)
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red <- mgcv::uniquecombs(datao)
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inds <- attr(red, "index")
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now <- ncol(red)
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## reattach the omitted column(s)
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## FIXME: control if more than one ann is present
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if (is.list(omit)) {
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red <- cbind(red, rep(data[1, indomi], nrow(red)))
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colnames(red)[now + 1] <- names(omit)
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ret <- red[, colnames(data)]
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} else {
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ret <- red
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}
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rownames(ret) <- NULL
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attr(ret, "index") <- inds
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return(ret)
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}
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## Attach the name of the calling function to the message displayed on
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## R's stdout
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msgm <- function(...) {
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if (local_rank == 0) {
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fname <- as.list(sys.call(-1))[[1]]
|
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prefix <- paste0("R: ", fname, " ::")
|
||||
cat(paste(prefix, ..., "\n"))
|
||||
}
|
||||
invisible()
|
||||
}
|
||||
|
||||
|
||||
## Function called by master R process to store on disk all relevant
|
||||
## parameters for the simulation
|
||||
StoreSetup <- function(setup) {
|
||||
|
||||
to_store <- vector(mode = "list", length = 4)
|
||||
## names(to_store) <- c("Sim", "Flow", "Transport", "Chemistry", "DHT")
|
||||
names(to_store) <- c("Sim", "Transport", "DHT", "Cmdline")
|
||||
|
||||
## read the setup R file, which is sourced in kin.cpp
|
||||
tmpbuff <- file(filesim, "r")
|
||||
setupfile <- readLines(tmpbuff)
|
||||
close.connection(tmpbuff)
|
||||
|
||||
to_store$Sim <- setupfile
|
||||
|
||||
## to_store$Flow <- list(
|
||||
## snapshots = setup$snapshots,
|
||||
## gridfile = setup$gridfile,
|
||||
## phase = setup$phase,
|
||||
## density = setup$density,
|
||||
## dt_differ = setup$dt_differ,
|
||||
## prolong = setup$prolong,
|
||||
## maxiter = setup$maxiter,
|
||||
## saved_iter = setup$iter_output,
|
||||
## out_save = setup$out_save )
|
||||
|
||||
to_store$Transport <- setup$diffusion
|
||||
|
||||
## to_store$Chemistry <- list(
|
||||
## nprocs = n_procs,
|
||||
## wp_size = work_package_size,
|
||||
## base = setup$base,
|
||||
## first = setup$first,
|
||||
## init = setup$initsim,
|
||||
## db = db,
|
||||
## kin = setup$kin,
|
||||
## ann = setup$ann)
|
||||
|
||||
if (dht_enabled) {
|
||||
to_store$DHT <- list(
|
||||
enabled = dht_enabled,
|
||||
log = dht_log
|
||||
## signif = dht_final_signif,
|
||||
## proptype = dht_final_proptype
|
||||
)
|
||||
} else {
|
||||
to_store$DHT <- FALSE
|
||||
}
|
||||
|
||||
if (dht_enabled) {
|
||||
to_store$DHT <- list(
|
||||
enabled = dht_enabled,
|
||||
log = dht_log
|
||||
#signif = dht_final_signif,
|
||||
#proptype = dht_final_proptype
|
||||
)
|
||||
} else {
|
||||
to_store$DHT <- FALSE
|
||||
}
|
||||
|
||||
saveRDS(to_store, file = paste0(fileout, "/setup.rds"))
|
||||
msgm("initialization stored in ", paste0(fileout, "/setup.rds"))
|
||||
}
|
||||
|
||||
GetWorkPackageSizesVector <- function(n_packages, package_size, len) {
|
||||
ids <- rep(1:n_packages, times=package_size, each = 1)[1:len]
|
||||
return(as.integer(table(ids)))
|
||||
}
|
||||
)";
|
||||
|
||||
static inline std::string init_r_library = R"(input <- readRDS("/home/max/Storage/poet/build/apps/out.rds")
|
||||
|
||||
grid_def <- matrix(c(2, 3), nrow = 2, ncol = 5)
|
||||
|
||||
library(data.table)
|
||||
|
||||
pqc_to_grid <- function(pqc_in, grid) {
|
||||
# Convert the input DataFrame to a data.table
|
||||
dt <- data.table(pqc_in)
|
||||
|
||||
# Flatten the matrix into a vector
|
||||
id_vector <- as.vector(t(grid))
|
||||
|
||||
# Initialize an empty data.table to store the results
|
||||
result_dt <- data.table()
|
||||
|
||||
# Iterate over each ID in the vector
|
||||
for (id_mat in id_vector) {
|
||||
# Find the matching row in the data.table
|
||||
matching_dt <- dt[id == id_mat]
|
||||
|
||||
# Append the matching data.table row to the result data.table
|
||||
result_dt <- rbind(result_dt, matching_dt)
|
||||
}
|
||||
|
||||
# Remove all columns which only contain NaN
|
||||
# result_dt <- result_dt[, colSums(is.na(result_dt)) != nrow(result_dt)]
|
||||
|
||||
res_df <- as.data.frame(result_dt)
|
||||
|
||||
return(res_df[, colSums(is.na(res_df)) != nrow(res_df)])
|
||||
}
|
||||
|
||||
pqc_init <- pqc_to_grid(input, grid_def)
|
||||
test <- pqc_init
|
||||
|
||||
modify_module_sizes <- function(mod_sizes, pqc_mat, init_grid) {
|
||||
# Find all unique IDs in init_grid
|
||||
unique_ids <- unique(as.vector(init_grid$id))
|
||||
|
||||
# remove rows from pqc_mat that are not in init_grid
|
||||
pqc_mat <- as.data.frame(pqc_mat)
|
||||
pqc_mat <- pqc_mat[pqc_mat$id %in% unique_ids, ]
|
||||
|
||||
# Find the column indices where all rows are NA
|
||||
na_cols <- which(colSums(is.na(pqc_mat)) == nrow(pqc_mat))
|
||||
|
||||
# Build cumsum over mod_sizes
|
||||
cum_mod_sizes <- cumsum(mod_sizes)
|
||||
|
||||
# Find the indices where the value of na_cols is equal to the value of cum_mod_sizes
|
||||
idx <- which(cum_mod_sizes %in% na_cols)
|
||||
|
||||
# Set the value of mod_sizes to 0 at the indices found in the previous step
|
||||
mod_sizes[idx] <- 0
|
||||
|
||||
return(mod_sizes)
|
||||
}
|
||||
|
||||
# mod_sizes <- c(7, 0, 4, 2, 0)
|
||||
|
||||
# unique_ids <- unique(as.vector(pqc_init$id))
|
||||
|
||||
# tmp <- as.data.frame(input)
|
||||
# pqc_test <- tmp[tmp$id %in% unique_ids, ]
|
||||
# na_cols <- which(colSums(is.na(pqc_test)) == nrow(pqc_test))
|
||||
# cum_mod_sizes <- cumsum(mod_sizes)
|
||||
|
||||
# # Get the indices of the columns of cum_mod_sizes where the value of the column is equal to the value of na_cols
|
||||
# idx <- which(cum_mod_sizes %in% na_cols)
|
||||
# mod_sizes[idx] <- 0
|
||||
|
||||
# idx <- which(na_cols == cum_mod_sizes)
|
||||
|
||||
|
||||
|
||||
# idx <- which(na_cols[1] >= cum_mod_sizes)
|
||||
|
||||
# mod_sizes <- modify_module_sizes(mod_sizes, pqc_init, pqc_init)
|
||||
|
||||
# remove column with all NA
|
||||
)";
|
||||
|
||||
#endif // POET_H
|
||||
Loading…
x
Reference in New Issue
Block a user