%% prt_report_my_pet % Creates report_my_pet.html in specified directory %% function prt_report_my_pet(focusSpecies, comparisonSpecies, T, f, destinationFolder, filename) % created 2016/11/24 Starrlight; modified 2018/08/22, 2019/02/22, % 2019/07/08 Bas Kooijman, 2020/04/14 Nina Marn, 2021/06/16 Bas Kooijman %% Syntax % <../prt_report_my_pet.m *prt_report_my_pet*> (focusSpecies, comparisonSpecies, T, f, destinationFolder, filename) %% Description % Writes report_my_pet.html with a list of parameters and implied model properties for selected species. % focusSpecies can be empty, or a single species; % comparisonSpecies can be empty (if focusSpecies is specified), or a cell-string of entries; their parameter values are taken from allStat. % The parameters of the focusSpeces are obtained from one of three sources: % % * allStat.mat (first input must be a character string) % * metaData, metaPar and par (first input must be a cell string), which are output structures of % , % % and % respectively, as part of the parameter estimation process. % * solutionSet_my_pet_date.mat in local directory (first input must be a scalar) as saved by method mmea of % in which several solutions are stored. % The scalar stands for the number of solutions for the focus species that are shown. % Only with the file with most recent date that starts with "solutionSet_" is used to read parameter values. % % The traits are computed using . % % Input: % % * focusSpecies: character-string with name of entry of special interest or cellstring with structures with {par, metaPar, txtPar, metaData} or a scalar; might also be empty % * comparisonSpecies: cell string with entry names, might be empty % * T: optional scalar with temperature in Kelvin for all species (default: T_typical, which is species-specific) % * f: optional scalar scaled functional response (default: 1); it applies to all species % * destinationFolder: optional string with destination folder the output html-file (default: current folder) % * filename: optional string with name of output file (default report_My_pet.html, with My_pet replaced by the first species_name) % % Output: % % * no Malab output, but a html-file is written with report-table and opens automatically in the system browser % %% Remarks % If the focus species is specified by string (rather than by data), its parameters are obtained from allStat.mat. % The parameters of the comparison species are obtained from allStat.mat, and the data of creation of that file is indicated on the top of the report. % The allStat.mat is available via the Collection tab of the Add-my-pet webpage (https://www.bio.vu.nl/thb/deb/deblab/add_my_pet/), and needs to be in the work folder or on a path. % AmPtool functions <../../../../../AmPtool/html/select.html *select*> or <../../../../../AmPtool/html/clade.html *clade*> can be used to create a cell string of comparison species. % % The difference between focus and comparison species only becomes important in the case of more than one comparison species and % color-coding is used to indicate how eccentric the focus-species is from the comparison-species. % The lava color-scheme is used, from white (high) to black (low), via red and blue, to show the value of the eccentricity. % This quantity is computed for each statistic and parameter and is the squared distance to the mean of the comparison species as a hyperbolically-transformed fraction % of the variance for the comparison-species. % Function <../../misc/html/color_lava.html *color_lava*> is used to convert the eccentricity to rgb-colors. % If the focus species also occurs in the comparison species, it is removed from that list. % So, if the comparison species all belong to the same genus, for instance, you can change your selection of focus species, and so change colors, without affecting numbers. % If you just have a set of species and want to avoid colors, treat them all as comparison species, leaving focusSpecies empty. % If model types differ among species in the tabel, only parameter and statistics fields for the focus species are shown. % In absence of a focus species, the first comparison species serves this role. % The default name of the output file is report_My_pet, but this name is replaced by filename, if specified, which is not opened automatically. % If filename is specified, destinationFolder must be specified as well % % The search boxes in the top-line of the report can be used to symbols, units, descriptions, but also (on the top-right) to make selections from % the statictics and/or the parameters. % NA means "not applicable": the parameter or statistic does not depend on temperature or food. % nan means "not a number": the model for that species does not have that field. %% Example of use % % * If results_My_Pet.mat exists in current directory (where "My_Pet" is replaced by the name of some species, but don't replace "my_pet"): % load('results_My_Pet.mat'); prt_report_my_pet({par, metaPar, txtPar, metaData}, [], T, f, destinationFolder) % * prt_report_my_pet('Daphnia_magna') % * prt_report_my_pet('Daphnia_pulex', [], C2K(22), 0.8) % * prt_report_my_pet('Lutjanus_analis', select('Lutjanus'), C2K(21)) % * prt_report_my_pet('Nasalis_larvatus', clade('Nasalis_larvatus')) % * prt_report_my_pet([], clade('Nasalis_larvatus')) % * prt_report_my_pet(3) if solutionsSet_my_pet_date.mat was produced via estim_pars method mmea path_entries_web = [set_path2server, 'add_my_pet/entries_web/']; % links of species names to AmP collection in table head n_sol = 1; % number of solutions shown for focus species; will be overwritten if first input is a scalar % focusSpecies initiation: get parameters (separate from get statistics because of 3 possible routes for getting pars) if isempty(focusSpecies) % only comparion species, but treat first comparison species as pseudo-focus species, but no color-coding focusSpecies = comparisonSpecies{1}; specList = {focusSpecies}; [parList.(specList{1}), metaPar, txtPar, metaData, info] = allStat2par(specList{1}); if info == 0 return end datePrintNm = ['allStat version: ', datestr(date_allStat, 'yyyy/mm/dd')]; color = 0; n_spec = 1; % number of focus species, initiate total number of species elseif iscell(focusSpecies) % use metaData, metaPar and par to specify (one or more) focusSpecies par = focusSpecies{1}; metaPar = focusSpecies{2}; txtPar = focusSpecies{3}; metaData = focusSpecies{4}; metaDataFldNm = fieldnames(metaData); if isempty(strfind(metaDataFldNm{1}, '_')) % single species; name of species is recognized by the presence of "_" focusSpecies = metaData.species; specList = {focusSpecies}; color = 1; n_spec = length(specList); % number of focus species, initiate total number of species if isfield('par', 'free') par = rmfield (par, 'free'); end fldsPar = get_parfields(metaPar.model, 1); for i=1:length(fldsPar) parList.(specList{1}).(fldsPar{i}) = par.(fldsPar{i}); end datePrintNm = ['date: ',datestr(date, 'yyyy/mm/dd')]; if exist('comparisonSpecies', 'var') && ~isempty(comparisonSpecies) datePrintNm = [datePrintNm, '; allStat version: ', datestr(date_allStat, 'yyyy/mm/dd')]; end else % multispecies; no color coding, so color = 0 focusSpecies = metaDataFldNm; specList = focusSpecies; color = 0; n_spec = length(specList); % number of focus species, initiate total number of species for k = 1:n_spec par.(specList{k}) = rmfield (par.(specList{k}), 'free'); end parList = par; datePrintNm = ['date: ', datestr(date, 'yyyy/mm/dd')]; if exist('comparisonSpecies', 'var') && ~isempty(comparisonSpecies) datePrintNm = [datePrintNm, '; allStat version: ', datestr(date_allStat, 'yyyy/mm/dd')]; end end elseif ischar(focusSpecies) % use allStat.mat as parameter source for focusSpecies (always single species) specList = {focusSpecies}; [parList.(specList{1}), metaPar, txtPar, metaData, info] = allStat2par(specList{1}); if info == 0 return end datePrintNm = ['allStat version: ', datestr(date_allStat, 'yyyy/mm/dd')]; color = 1; n_spec = 1; % number of focus species, initiate total number of species else % first input is a scalar with number of solutions to be shown for the focus species; no color coding if ismac || isunix list = strsplit(ls); list(end) = []; else list = cellstr(ls); end list_sol = list(Contains(list,'solutionSet_')); n_sol = length(list_sol); if n_sol == 0 fprintf('Warning from prt_report_my_pet: the first input is a scalar, but no file solutionSet_* found\n'); return end % local dir can contain several files solutionSet_*, select the most recent one datenum_sol = NaN(n_sol,1); date_sol = cell(n_sol,1); % initiate datenum vector to select the latest date of filenames that start with solutionSet_ for i = 1:n_sol solInfo = dir(which(list_sol{i})); datenum_sol(i) = solInfo.datenum; date_sol{i} = solInfo.date; end [~, i] = sort(datenum_sol); load(list_sol{i(end)}); % load the most recent solutionSet n_sol = focusSpecies; n_spec = n_sol; % number of solutions for focus species to be shown datePrintNm = ['date: ', datestr(date_sol{i(end)}, 'yyyy/mm/dd')]; % take the creation date of the selected file solutionSet_* if exist('comparisonSpecies', 'var') && ~isempty(comparisonSpecies) datePrintNm = [datePrintNm, '; allStat version: ', datestr(date_allStat, 'yyyy/mm/dd')]; end focusSpecies = fields(solutions_set.results.metaData); color = 0; % no colors metaPar = solutions_set.results.solution_1.metaPar; txtPar = solutions_set.results.txtPar; metaData.(focusSpecies{1}) = solutions_set.results.metaData.(focusSpecies{1}); specList = focusSpecies(ones(n_sol,1)); focusSpecies = focusSpecies{1}; for i=1:n_sol % scan the various solutions specList{i} = [specList{i},'_', num2str(i)]; % make sure that species names are unique parList.(specList{i}) = solutions_set.results.(['solution_', num2str(i)]).par; parList.(specList{i}) = rmfield(parList.(specList{i}),'free'); end end if n_spec == 1 modelList = {metaPar.model}; % initiate cell string for model tempList.(specList{1}) = metaData.T_typical; % initiate cell string for typical body temperature specListPrintNm = {strrep(specList{1}, '_', ' ')}; % initiate cell string for species names as they appear above the table else modelList = {metaPar.model}; modelList = modelList(ones(n_sol,1)); % initiate cell string for model specListPrintNm = cell(n_spec,1); for k = 1: n_spec if n_sol == 1 tempList.(specList{k}) = metaData.(specList{k}).T_typical; % initiate cell string for typical body temperature specListPrintNm(k) = {strrep(specList{k}, '_', ' ')}; % initiate cell string for species names as they appear above the table else tempList.(specList{k}) = metaData.(focusSpecies).T_typical; % initiate cell string for typical body temperature specListPrintNm(k) = {strrep(specList{k}, '_', ' ')}; % initiate cell string for species names as they appear above the table end end end fldsPar = fieldnmnst_st(parList.(specList{1})); % fieldnames of all pars are taken from first species only if exist('T', 'var') % fix temperature for all species T_free = 0; else T_free = 1; % temperature for each species equals typical body temperature end % scaled functional response for all species if ~exist('f', 'var') || isempty(f) f = 1; end % path+filename of output file if ~exist('filename','var') || isempty(filename) fnm = ['report_', specList{1}, '.html']; else fnm = filename; end if exist('destinationFolder','var') fileName = [destinationFolder, fnm]; else fileName = ['report_', specList{1}, '.html']; end % focus species: get statistics for k = 1:n_spec if T_free Ti = tempList.(specList{k}); % temperature for statistics else Ti = T; end [statList.(specList{k}), txtStat.(specList{k})] = statistics_st(modelList{k}, parList.(specList{k}), Ti, f); statList.(specList{k}) = rmfield(statList.(specList{k}), {'T','f'}); % remove fields T and f, because it is already in txtStat end fldsStat = fieldnmnst_st(statList.(specList{1})); % fieldnames of all statistics are taken from first species only % comparison species if exist('comparisonSpecies', 'var') && ~isempty(comparisonSpecies) comparisonSpecies = comparisonSpecies(~ismember(comparisonSpecies,focusSpecies)); % remove focus species from comparison species specList = [specList; comparisonSpecies(:)]; n_spec = length(specList); % list of all entries to be shown in the table for k = n_sol+1:n_spec % parameters [parList.(specList{k}), metaPark, txtPark, metaDatak] = allStat2par(specList{k}); modelList{k} = metaPark.model; if ~strcmp(modelList{1},modelList{k}) fldsPark = get_parfields(modelList{k}, 1); for j = 1:length(fldsPar) if ~ismember(fldsPar{j}, fldsPark) parList.(specList{k}).(fldsPar{j}) = NaN; end end end tempList.(specList{k}) = metaDatak.T_typical; if T_free Ti = tempList.(specList{k}); % temperature for statistics else Ti = T; end % statistics [statList.(specList{k}), txtStat.(specList{k})] = statistics_st(modelList{k}, parList.(specList{k}), Ti, f); specListPrintNm{k} = strrep(specList{k}, '_', ' '); % list of all species names to be shown in the table if ~strcmp(modelList{1},modelList{k}) statList.(specList{k}) = rmfield(statList.(specList{k}), {'T','f'}); % remove fields T and f, because it is already in txtStat fldsStatk = fieldnmnst_st(statList.(specList{k})); % fieldnames of all statistics for j = 1:length(fldsStat) if ~ismember(fldsStat{j}, fldsStatk) statList.(specList{k}).(fldsStat{j}) = NaN; txtStat.(specList{k}).temp.(fldsStat{j}) = NaN; end end end end end % font color-coding, based on eccentricity of focus species, relative to comparison species if color == 1 && n_spec > 2 % parameters eccPar = zeros(length(fldsPar),1); % initiate eccentricity quantifyer for i = 1:length(fldsPar) pari = zeros(n_spec-1,1); for k = 2:n_spec % fill parameters if isfield(parList.(specList{k}),(fldsPar{i})) pari(k-1) = parList.(specList{k}).(fldsPar{i}); else pari(k-1) = NaN; end end pariMean = mean(pari); pariVar = max(1e-4, var(pari)); eccPar(i) = (parList.(specList{1}).(fldsPar{i}) - pariMean)^2/ pariVar; eccPar(i) = 0.9 * eccPar(i)/(1 + eccPar(i)); % make sure that eccentricity is between 0 and 0.9 (avoiding white for eccentricity 1) if isnan(eccPar(i)) eccPar(i) = 0; end end % statistics eccStat = zeros(length(fldsStat),1); % initiate eccentricity quantifyer for i = 1:length(fldsStat) stati = zeros(n_spec-1,1); for k = 2:n_spec % fill statistics stati(k-1) = statList.(specList{k}).(fldsStat{i}); end statMean = mean(stati); statVar = max(1e-4, var(stati)); eccStat(i) = (statList.(specList{1}).(fldsStat{i}) - statMean)^2/ statVar; eccStat(i) = 0.9 * eccStat(i)/(1 + eccStat(i)); % make sure that eccentricity is between 0 and 0.9 (avoiding white for eccentricity 1) if isnan(eccStat(i)) eccStat(i) = 0; end end end % write table oid = fopen(fileName, 'w+'); % open file for writing, delete existing content fprintf(oid, '\n'); fprintf(oid, '\n'); fprintf(oid, '\n'); fprintf(oid,[' ', specList{1}, '\n']); fprintf(oid, ' \n\n'); fprintf(oid, '\n\n'); fprintf(oid, '\n\n'); % search boxes above the table fprintf(oid, '
\n'); fprintf(oid, ' \n'); fprintf(oid, ' \n'); fprintf(oid, ' \n'); fprintf(oid, ' \n'); fprintf(oid, '
\n\n'); % open table fprintf(oid, ' \n'); % table head: % row with species print names and source dates fprintf(oid, ' \n'); for k = 1:n_spec if k == 1 && ~isempty(strfind(datePrintNm, 'date')) % no link if focusSpecies is specified by data, rather than by string fprintf(oid, ' \n', specListPrintNm{k}); else % links to AmP entries fprintf(oid, ' \n', path_entries_web, specList{k}, specList{k}, specListPrintNm{k}); end end fprintf(oid, ' \n', datePrintNm); fprintf(oid, ' \n\n'); % row with table header fprintf(oid, ' \n'); for k = 1:n_spec fprintf(oid, ' \n'); end fprintf(oid, ' \n'); fprintf(oid, ' \n\n'); % row with model fprintf(oid, ' \n'); for k = 1:n_spec fprintf(oid,[' \n']); end fprintf(oid, ' \n'); fprintf(oid, ' \n\n'); % row with typical body temperature fprintf(oid, ' \n'); for k = 1:n_spec fprintf(oid,[' \n']); end fprintf(oid, ' \n'); fprintf(oid, ' \n\n'); % parameters: for i = 1:length(fldsPar) txtPar.fresp.(fldsPar{i}) = 'NA'; % no parameter depends on functional response if isempty(strfind(txtPar.units.(fldsPar{i}),'d')) txtPar.temp.(fldsPar{i}) = 'NA'; else txtPar.temp.(fldsPar{i}) = num2str(20); % time-dependent pars are at T_ref end fprintf(oid, ' \n', fldsPar{i}, fldsPar{i}, txtPar.units.(fldsPar{i})); for k = 1:n_spec if ~isfield(parList.(specList{k}),(fldsPar{i})) parList.(specList{k}).(fldsPar{i}) = NaN; txtPar.temp.(fldsPar{i}) = 'NA'; end fprintf(oid, ' \n', parList.(specList{k}).(fldsPar{i}), txtPar.temp.(fldsPar{i})); end fprintf(oid, ' \n', txtPar.fresp.(fldsPar{i}), txtPar.label.(fldsPar{i})); fprintf(oid, ' \n\n'); end % statistics for i = 1:length(fldsStat) if isnan(txtStat.(specList{1}).fresp.(fldsStat{i})) txtStat.(specList{1}).fresp.(fldsStat{i}) = 'NA'; else txtStat.(specList{1}).fresp.(fldsStat{i}) = num2str(txtStat.(specList{1}).fresp.(fldsStat{i})); end fprintf(oid, ' \n', fldsStat{i}, fldsStat{i}, txtStat.(specList{1}).units.(fldsStat{i})); for k = 1:n_spec if isnan(txtStat.(specList{k}).temp.(fldsStat{i})) txtStat.(specList{k}).temp.(fldsStat{i}) = 'NA'; else txtStat.(specList{k}).temp.(fldsStat{i}) = num2str(K2C(txtStat.(specList{k}).temp.(fldsStat{i}))); end fprintf(oid, ' \n', statList.(specList{k}).(fldsStat{i}), txtStat.(specList{k}).temp.(fldsStat{i})); end label = txtStat.(specList{1}).label.(fldsStat{i}); label = strrep(label, '<', '<'); label = strrep(label, '>', '>'); % html cannot show < or > fprintf(oid, ' \n', txtStat.(specList{1}).fresp.(fldsStat{i}), label); fprintf(oid, ' \n'); end % close table fprintf(oid, '
%s%s %s
model -', modelList{k}, ' NANA typified model
T_typical °C', num2str(K2C(tempList.(specList{k}))), ' NANA typical body temperature
%s %s%g %s%s %s
%s %s%g %s%s %s
\n\n'); % search/selection facilities % symbol fprintf(oid, ' \n'); fprintf(oid, '\n'); fprintf(oid, '\n'); fclose(oid); %if ~exist('fileName','var') web(fileName,'-browser') % open html in systems browser %end end function sel = Contains(nm, str) % this fuction is the same as Matlab built-in-function contains, but the R2016a version does not work with cell input n = length(nm); sel = true(n,1); for i=1:n sel(i) = ~isempty(strfind(nm{i}, str)); end end