Auswertung Experiment

Database tüddelei
DBHanlder läuft gut für DIESE Datanbank struktur...
App begonnen aber weit entfernt von gutem Stand

Classes/00_signals/Signal.m

@@ -254,7 +254,12 @@ classdef Signal
                 CallingModifier = evalin('caller','obj');
             end
 
-            CallingModifierStruct = obj.objToStructFilteredRecursive(CallingModifier);
+            if isa(CallingModifier,"Signal")
+                CallingModifierStruct = obj.objToStructFilteredRecursive(CallingModifier);
+                ModifierCopy = {CallingModifierStruct};
+            end
+
+            ModifierCopy = {CallingModifier};
 
             SignalType  = [string(class(obj))];
             TimeStamp   = [(datetime('now','TimeZone','local','Format','HH:mm:ss'))];
@@ -263,7 +268,7 @@ classdef Signal
             Nase        = [0];
             SignalCopy  = obj.signal;
             ModifierName = class(CallingModifier);
-            ModifierCopy = {CallingModifierStruct};
+            
 
             cell = {SignalType , TimeStamp , Length , SignalPower(1) , Nase, SignalCopy, ModifierName, ModifierCopy, Description};
 

Classes/04_DSP/Equalizer/EQ.m

@@ -1,4 +1,4 @@
-classdef EQ %< handle
+classdef EQ < handle
     %EQ Summary of this class goes here
     %   Detailed explanation goes here
 
@@ -289,9 +289,9 @@ classdef EQ %< handle
 
                         e_dc = e_dc - obj.DCmu*error;
 
-                        obj.error_log.e_ffe(cnt,trainloops) = e_ffe;
-                        obj.error_log.e_dfe(cnt,trainloops) = e_dfe;
-                        obj.error_log.e_(cnt,trainloops) = error;
+                        % obj.error_log.e_ffe(cnt,trainloops) = e_ffe;
+                        % obj.error_log.e_dfe(cnt,trainloops) = e_dfe;
+                        % obj.error_log.e_(cnt,trainloops) = error;
 
                         cnt = cnt+1;
                         if obj.Nb(1) > 0
@@ -460,7 +460,7 @@ classdef EQ %< handle
 
                         if 1%mu_mat ~= 0
                              e_dc = e_dc - obj.DCmu*error;
-                             error_log(cnt,dd_loop) = e_dc;
+                             % error_log(cnt,dd_loop) = e_dc;
                              cnt = cnt+1;
                         end
 

Classes/04_DSP/Equalizer/Postfilter.m

@@ -0,0 +1,60 @@
+classdef Postfilter < handle
+    %NAME Summary of this class goes here
+    %   Detailed explanation goes here
+
+    properties(Access=public)
+        ncoeff = 2;
+        burg_coeff = [];
+
+    end
+
+    methods (Access=public)
+        function obj = Postfilter(options)
+            %NAME Construct an instance of this class
+            %   Detailed explanation goes here
+
+            arguments
+                options.ncoeff double = 2
+            end
+
+            % 
+            fn = fieldnames(options);
+            for n = 1:numel(fn)
+                try
+                    obj.(fn{n}) = options.(fn{n});
+                end
+            end
+
+            % do more stuff 
+
+        end
+
+        function signalclass_out = process(obj,signalclass_in,noiseclass_in)
+
+            obj.burg_coeff = arburg(noiseclass_in.signal,obj.ncoeff);
+            signalclass_in = signalclass_in.filter(obj.burg_coeff,1);
+
+            % append to logbook
+            lbdesc = ['Postfilter'];
+            signalclass_in  = signalclass_in.logbookentry(lbdesc);
+
+            % write to output
+            signalclass_out = signalclass_in;
+
+        end
+
+        function showFilter(obj,noiseclass_in)
+
+            noiseclass_in.spectrum('displayname','Noise PSD shifted to 0dBm','fignum',123,'normalizeTo0dB',1);
+
+            [h,w] = freqz(1,obj.burg_coeff,length(noiseclass_in),"whole",noiseclass_in.fs);
+            h = h/max(abs(h));
+            hold on
+            w_ = (w - noiseclass_in.fs/2);
+            plot(w_.*1e-9,20*log10(fftshift(h)),'DisplayName',['Burg Coeffs: ', num2str(obj.burg_coeff), ' ']);
+
+        end
+
+    end
+
+end

Classes/04_DSP/Sequence Detection/MLSE.m

@@ -1,4 +1,4 @@
-classdef MLSE
+classdef MLSE < handle
     %MLSE calculates the most probable sequence for an input signal with given/ known channel impulse response of any length
 
     properties(Access=public)

Classes/DataBaseHandler/DBHandler.m

@@ -38,10 +38,22 @@ classdef DBHandler < handle
                 error('Failed to connect to the database: %s', e.message);
             end
 
-            % Get table names and the first rows of each table to understand the structure
-            obj.getTableNames();
-            obj.getTables();
-            obj.getDistinctValues();
+            if obj.dbIsHealthy
+
+                obj.refresh();
+
+            else
+                error('DB seems to be corrupt')
+            end
+            
+        end
+
+
+        function obj = refresh(obj)
+                % Get table names and the first rows of each table to understand the structure
+                obj.getTableNames();
+                obj.getTables();
+                obj.getDistinctValues();
         end
 
         function obj = getTableNames(obj)
@@ -86,10 +98,10 @@ classdef DBHandler < handle
             obj.distinctValues = struct();
 
             % Iterate over each table in obj.tables
-            tableNames = fieldnames(obj.tables);
+            tableNames_ = fieldnames(obj.tables);
 
-            for i = 1:numel(tableNames)
-                tableName = tableNames{i};
+            for i = 1:numel(tableNames_)
+                tableName = tableNames_{i};
 
                 % Initialize a sub-struct to store distinct values for each field in the table
                 obj.distinctValues.(tableName) = struct();
@@ -101,10 +113,10 @@ classdef DBHandler < handle
                 for j = 1:numel(fieldNames)
                     fieldName = fieldNames{j};
 
-                    % Skip fields ending with '_id' as they don't contain useful distinct values
-                    if endsWith(fieldName, '_id')
-                        continue;
-                    end
+                    % % Skip fields ending with '_id' as they don't contain useful distinct values
+                    % if endsWith(fieldName, '_id')
+                    %     continue;
+                    % end
 
                     % Construct SQL to get distinct values for the current field
                     query = sprintf('SELECT DISTINCT %s FROM %s', fieldName, tableName);
@@ -123,17 +135,38 @@ classdef DBHandler < handle
                         obj.distinctValues.(tableName).(fieldName) = distinctValues;
 
                     catch e
-                        warning('Failed to retrieve distinct values for %s.%s: %s', tableName, fieldName, e.message);
+                        % warning('Failed to retrieve distinct values for %s.%s: %s', tableName, fieldName, e.message);
                         obj.distinctValues.(tableName).(fieldName) = [];
                     end
                 end
             end
 
-            % Display the distinct values (optional, for debugging purposes)
-            disp('Distinct values for each field:');
-            disp(obj.distinctValues);
         end
 
+        function healthyDB = dbIsHealthy(obj)
+            healthyDB = false;
+
+            num_runs = obj.fetch('SELECT COUNT(*) AS total_runs FROM Runs');
+
+            num_configs = obj.fetch('SELECT COUNT(*) AS total_configurations FROM Configurations');
+
+            num_meas = obj.fetch('SELECT COUNT(*) AS total_measurements FROM Measurements');
+
+            assert((num_runs{1,1}==num_configs{1,1})&&(num_configs{1,1}==num_meas{1,1}),'Different num of entries per table');
+
+            %Check for any duplicate paths
+            duplictae_raw = obj.fetch("SELECT COALESCE(Runs.rx_raw_path,'NaN') AS rx_raw_path,  COUNT(*) AS occurrences FROM Runs GROUP BY rx_raw_path HAVING COUNT(*) > 1");
+            duplictae_sync = obj.fetch("SELECT COALESCE(Runs.rx_sync_path,'NaN') AS rx_sync_path, COUNT(*) AS occurrences FROM Runs GROUP BY rx_sync_path HAVING COUNT(*) > 1");
+
+            if size(duplictae_raw,2) > 1
+                for i = 1:size(duplictae_raw,2)-1
+                    fprintf('Raw Rx Paths: Found %d duplictaes of %s \n',duplictae_raw.occurrences(i),duplictae_raw.rx_raw_path(i));
+                end
+            end
+            healthyDB = true;
+        end
+
+
 
         function lastID = appendToTable(obj, tableName, newRow)
             % appendToTable Appends a new row to the specified table
@@ -241,11 +274,87 @@ classdef DBHandler < handle
             end
         end
 
+        function addBEREntry(obj, berValue, occurrence, runID, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, comment)
+            % addBEREntry Adds a BER entry linked to an existing or new Equalizer entry.
+            % Usage:
+            %   addBEREntry(runID, eq, ffe, dfe, mlse, pf, eqType, ffe_order, dfe_order, len_tr, mu_ffe, mu_dfe, mu_dc, berValue, comment)
+
+            if isempty(pf)
+                postfilter_taps = [];
+            else
+                postfilter_taps = pf.burg_coeff;
+            end
+
+            % Create equalizer data struct for searching and adding if necessary
+            equalizerData = struct( ...
+                'ffe', jsonencode(ffe), ...
+                'dfe', jsonencode(dfe), ...
+                'mlse', jsonencode(mlse), ...
+                'pf', jsonencode(pf), ...
+                'eq_type', string(eqType), ...
+                'ffe_order', jsonencode(ffe_order), ...
+                'dfe_order', jsonencode(dfe_order), ...
+                'postfilter_taps',jsonencode(postfilter_taps),...
+                'len_tr', len_tr, ...
+                'mu_ffe', jsonencode(mu_ffe), ...
+                'mu_dfe', mu_dfe, ...
+                'mu_dc', mu_dc, ...
+                'comment', comment ...
+                );
+
+            % Check if exact Equalizer and BER entries already exist in the DB ...
+            selectedFields = {'Runs.run_id','BERs.ber_id','Equalizer.eq_id','BERs.ber',['BERs.occurrence' ...
+                '']};
+            filterParams = obj.tables;
+            filterParams.Equalizer = equalizerData;
+            [dataTable,sql_query] = obj.queryDB(filterParams, selectedFields);
+
+            % get or insert Equalizer
+            if ~isempty(dataTable)
+                % Equalizer entry already exists, use the existing eq_id
+                cur_eq_id = dataTable.eq_id;
+            else
+                % Insert the new Equalizer entry
+                cur_eq_id = obj.appendToTable('Equalizer', equalizerData);
+            end
+
+            % skip if already here or insert BER entry
+            if ~isempty(dataTable)
+
+                % A BER entry with the same eq_id, run_id, and occurrence already exists
+                existingBERValue = dataTable.ber;
+
+                % Compare the existing BER value with the new BER value
+                if existingBERValue == berValue
+                    fprintf('The BER entry %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists. \n',berValue, cur_eq_id, runID, occurrence);
+                else
+                    fprintf('Already found BER for EQ: %.2e ~= %.2e || -- eq_id: %d -- run_id: %d -- occurrence: %d already exists.\n', berValue, existingBERValue, cur_eq_id, runID, occurrence);
+                end
+
+            else
+
+                % No such BER entry exists, insert the new BER entry
+                berData = struct( ...
+                    'run_id', runID, ...
+                    'eq_id', cur_eq_id, ...
+                    'ber', berValue, ...
+                    'occurrence', occurrence ...
+                    );
+
+                obj.appendToTable('BERs', berData);
+
+            end
+
+        end
+
+
+
+
         function answer = fetch(obj,query)
             answer = fetch(obj.conn,query);
         end
 
-        function result = getPathsWithFlexibleFilter(obj, filterParams, selectedFields)
+        function [result,query] = queryDB(obj, filterParams, selectedFields)
             % getPathsWithFlexibleFilter Retrieves values from Runs table with flexible filtering
             % and lets the user select which fields to include in the SELECT statement.
             %
@@ -257,8 +366,9 @@ classdef DBHandler < handle
             %                 If left empty, two popup windows will prompt the user for input.
             %
             % Outputs:
-            %   rxRawPaths: Cell array of values from the Runs table matching the criteria.
-            %   filteredValues: Table of distinct values for parameters included in filterParams.
+            %   result: table with sql return
+            %   query: this was send to SQL DB
+
             arguments
                 obj
                 filterParams = [];
@@ -299,7 +409,7 @@ classdef DBHandler < handle
                 fieldName = fieldParts{2};
 
                 if isnumeric(obj.tables.(tableName).(fieldName))
-                    selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', -1) AS ', fieldName];
+                    selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', ''NaN'') AS ', fieldName];
                 else
                     selectClause = [selectClause, 'COALESCE(', selectedFields{i}, ', '''') AS ', fieldName];
                 end
@@ -321,10 +431,10 @@ classdef DBHandler < handle
 
             % Loop through each table in filterParams
             filterClauses = [];
-            tableNames = fieldnames(filterParams);
+            tableNames_ = fieldnames(filterParams);
 
-            for t = 1:numel(tableNames)
-                tableName = tableNames{t};
+            for t = 1:numel(tableNames_)
+                tableName = tableNames_{t};
                 tableParams = filterParams.(tableName);
 
                 % Loop through each parameter in the table
@@ -343,12 +453,14 @@ classdef DBHandler < handle
                     elseif isnumeric(value) && isnan(value)
                         % If value is NaN, use IS NULL in SQL
                         filterClause = sprintf('%s IS NULL', fullName);
-                    elseif isnumeric(value)
+                    elseif isnumeric(value) && ~isEnumeration(value)
                         filterClause = sprintf('%s = %f', fullName, value);
-                    elseif islogical(value) || (isnumeric(value) && ismember(value, [0, 1]))
+                    elseif islogical(value) || (isnumeric(value) && ismember(value, [0, 1])) && ~isEnumeration(value)
                         filterClause = sprintf('%s = %d', fullName, value);
                     elseif ischar(value) || isstring(value)
-                        filterClause = sprintf('%s = "%s"', fullName, value);
+                        filterClause = sprintf('%s = ''%s''', fullName, char(value)); %nicht nach string suchen sondern nach chararray -> 'bla' statt "bla"
+                    elseif isEnumeration(value)
+                        filterClause = sprintf('%s = ''%s''', fullName, value);
                     else
                         error('Unsupported data type for field "%s".', fullName);
                     end
@@ -376,6 +488,7 @@ classdef DBHandler < handle
         end
 
 
+
         function selectedFields = promptSelectFields(obj)
             % promptSelectFields Prompts the user to select fields from multiple tables to include in the SELECT statement using settingsdlg.
 
@@ -436,41 +549,67 @@ classdef DBHandler < handle
             % promptFilterParameters Prompts the user to enter filter parameters using the settingsdlg framework.
 
             % Get all possible parameters from all tables (excluding sqlite_sequence)
-            tableNames = fieldnames(obj.tables);
-            tableNames = setdiff(tableNames, {'sqlite_sequence'}); % Remove sqlite_sequence
+            tableNames_ = fieldnames(obj.tables);
+            tableNames_ = setdiff(tableNames_, {'sqlite_sequence'}); % Remove sqlite_sequence
 
             % Prepare the inputs for settingsdlg with sections and separators
             promptSettings = {};
             allFieldsFullName = {};
             convertedFieldNames = {};
 
-            for i = 1:numel(tableNames)
+            for i = 1:numel(tableNames_)
                 % Add a separator for each table section
                 promptSettings{end + 1} = 'separator';
-                promptSettings{end + 1} = tableNames{i};
+                promptSettings{end + 1} = tableNames_{i};
 
                 % Get all fields from the current table
-                tableFields = fieldnames(obj.tables.(tableNames{i}));
+                tableFields = fieldnames(obj.tables.(tableNames_{i}));
 
                 % Prepare each field to be added to the dialog
                 for j = 1:numel(tableFields)
                     fieldName = tableFields{j};
-                    fullName = sprintf('%s.%s', tableNames{i}, fieldName);
+                    fullName = sprintf('%s.%s', tableNames_{i}, fieldName);
                     convertedName = strrep(fullName, '.', '_'); % Replace '.' with '_'
 
+                    % Skip fields that do not have distinct values stored
+                    if ~isfield(obj.distinctValues.(tableNames_{i}), fieldName)
+                        continue;
+                    end
+
+                    % Get the distinct values for the field
+                    distinctValues_ = obj.distinctValues.(tableNames_{i}).(fieldName);
+
+                    % Prepare distinct values for dropdown
+                    if isempty(distinctValues_)
+                        % If there are no distinct values, use only an "All" entry
+                        distinctValues_ = {'All'};
+                    else
+                        % Ensure distinctValues is a cell array of strings
+                        if isnumeric(distinctValues_)
+                            distinctValues_ = arrayfun(@(x) num2str(x), distinctValues_, 'UniformOutput', false);
+                        elseif isstring(distinctValues_)
+                            distinctValues_ = cellstr(distinctValues_);
+                        elseif iscell(distinctValues_) && ~iscellstr(distinctValues_)
+                            distinctValues_ = cellfun(@num2str, distinctValues_, 'UniformOutput', false);
+                        end
+
+                        % Add an "All" option at the beginning of the distinct values list
+                        distinctValues_ = [{'All'}; distinctValues_];
+                    end
+
                     allFieldsFullName{end + 1} = fullName; % Add full name to the list
                     convertedFieldNames{end + 1} = convertedName; % Store the converted name
 
                     % Add the field name and value setting to the prompt
                     promptSettings{end + 1} = {sprintf('%s', fullName), convertedName};
-                    promptSettings{end + 1} = [];
+                    promptSettings{end + 1} = distinctValues_; % Add distinct values as dropdown options
                 end
             end
 
             % Create the settings dialog
             [settings, button] = settingsdlg(...
                 'title', 'Input Parameters for Filtering', ...
-                'description', 'Enter the values for each field to filter. Leave empty to include all values. Type NaN for NULL.', ...
+                'description', 'Enter the values for each field to filter. Select "All" to include all values.', ...
                 promptSettings{:} ...
                 );
 
@@ -497,7 +636,7 @@ classdef DBHandler < handle
                 end
 
                 % Assign values to the respective fields under each table
-                if isempty(value)
+                if strcmp(value, 'All')
                     filterParams.(tableName).(fieldName) = []; % Set to empty to include all values
                 elseif isnumeric(value) && isnan(value)
                     filterParams.(tableName).(fieldName) = NaN; % Use NaN to handle as NULL
@@ -510,5 +649,6 @@ classdef DBHandler < handle
 
 
 
+
     end
 end

Datatypes/db_mode.m

@@ -0,0 +1,9 @@
+classdef db_mode < int32
+
+    enumeration
+        no_db       (0)
+        db_precoded (1)
+        db_encoded  (2)
+    end
+
+end

Datatypes/equalizer_structure.m

@@ -0,0 +1,11 @@
+classdef equalizer_structure < int32
+
+    enumeration
+        ffe             (0)
+        vnle            (1)
+        vnle_pf_mlse    (2)
+        db_precoded     (3)
+        db_encoded 	    (4)
+    end
+
+end

Datatypes/isEnumeration.m

@@ -0,0 +1,11 @@
+function result = isEnumeration(value)
+    % isEnumeration Checks if a given value is an instance of an enumeration class
+    % Usage:
+    %   result = isEnumeration(value);
+    
+    % Get meta information about the class of the value
+    metaInfo = metaclass(value);
+    
+    % Check if the meta information indicates an enumeration class
+    result = metaInfo.Enumeration;
+end

Functions/EQ_structures/duobinary_signaling.m

@@ -1,4 +1,15 @@
-function duobinary_signaling()
+function [eq_signal,eq_noise,ber,numErrors] = duobinary_signaling(EQ, MLSE,M ,rx_signal, tx_symbols, tx_bits)
+    %Duobinary Signaling
 
+    [eq_signal, eq_noise] = EQ.process(rx_signal,tx_symbols);
+
+    eq_signal = MLSE.process(eq_signal);
+
+    eq_signal = Duobinary().decode(eq_signal);
+
+    % M = numel(unique(eq_signal.signal));
+    rx_bits = PAMmapper(M,0).demap(eq_signal);
+
+    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
 
 end

Functions/EQ_structures/duobinary_target.m

@@ -1,4 +1,17 @@
-function duobinary_target()
+function [eq_signal,eq_noise,ber,numErrors] = duobinary_target(EQ, MLSE,M, rx_signal, tx_symbols, tx_bits)
+    
+    %Duobinary Targeting
 
+    [eq_signal, eq_noise] = EQ.process(rx_signal,Duobinary().encode(tx_symbols));
 
+    % dir = [1,1];
+    eq_signal = MLSE.process(eq_signal);
+
+    eq_signal = Duobinary().decode(eq_signal);
+
+    % M = numel(unique(tx_symbols.signal));
+    rx_bits = PAMmapper(M,0).demap(eq_signal);
+
+    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+    
 end

Functions/EQ_structures/vnle.m

@@ -1,4 +1,25 @@
-function eq_signal = vnle(EQ,rx_signal,tx_symbols)
-    %VNLE
-    eq_signal = EQ.process(rx_signal,tx_symbols);
+function [eq_signal,eq_noise,ber,numErrors] = vnle(EQ,M,rx_signal,tx_symbols,tx_bits)
+    %VNLE Apply an equalization algorithm to the received signal and calculate BER
+    %   This function takes an equalizer object, a received signal, and the 
+    %   transmitted symbols to apply equalization, map the received signal back to bits,
+    %   and compute the bit error rate (BER).
+    %
+    %   Inputs:
+    %     EQ         - Equalizer object that provides the equalization method
+    %     rx_signal  - Received signal that needs to be equalized
+    %     tx_symbols - Transmitted symbols used as a reference for BER calculation
+    %
+    %   Outputs:
+    %     eq_signal  - Equalized version of the received signal
+    %     ber        - Bit error rate after equalization
+    %     numErrors  - Number of bit errors detected
+
+    %FFE or VNLE
+    [eq_signal,eq_noise] = EQ.process(rx_signal,tx_symbols);
+    
+    % M = numel(unique(tx_symbols.signal));
+    rx_bits = PAMmapper(M,0).demap(eq_signal);
+
+    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+
 end

Functions/EQ_structures/vnle_postfilter_mlse.m

@@ -1,4 +1,18 @@
-function vnle_postfilter_mlse()
+function [eq_signal,eq_noise,ber,numErrors] = vnle_postfilter_mlse(eq_,pf_,mlse_,M,rx_signal,tx_symbols,tx_bits)
+    
+    %FFE or VNLE
+    [eq_signal,eq_noise] = eq_.process(rx_signal,tx_symbols);
 
+    eq_signal = pf_.process(eq_signal,eq_noise);
 
+    %M = numel(unique(tx_symbols.signal));
+    mlse_.DIR = pf_.burg_coeff;
+    mlse_.trellis_states = PAMmapper(M,0).levels;
+    mlse_.M = M;
+    eq_signal = mlse_.process(eq_signal);
+    
+    rx_bits = PAMmapper(M,0).demap(eq_signal);
+
+    [~,numErrors,ber,~] = calc_ber(rx_bits.signal,tx_bits.signal,"skip_front",100,"skip_end",150,"returnErrorLocation",1);
+    
 end

Functions/Lab_helper/showCurrentMeasurement.m

@@ -1,5 +1,8 @@
 function showCurrentMeasurement(varargin)
-    % showCurrentMeasurement displays measurement data in a figure with variable names
+    
+    % USEFUL FOR LAB!
+
+    % showCurrentMeasurement displays lab measurement data in a table figure with variable names
     % as column headers and values listed below. Calling the function multiple times
     % with the same variable names but different values adds more data points.
     %

Functions/helper_functions_community/cbrewer2/cbrewer2.m

@@ -1,260 +0,0 @@
-%CBREWER2 Interpolated versions of Cynthia Brewer's ColorBrewer colormaps
-%   CBREWER2(CNAME, NCOL) returns the colour scheme CNAME with the number
-%   of colours equal to NCOL. If there is a ColorBrewer scheme with exactly
-%   this number of colours, the color scheme is returned as-is. If NCOL
-%   larger (or smaller) than the designed colormaps for this scheme, the
-%   largest (smallest) one is interpolated to provide enough colours,
-%   unless the requested colour scheme CNAME is a qualitative palette. For
-%   a qualitative scheme, the colours are repeated, cycling from the
-%   beginning again, to output the requested NCOL colours.
-%
-%   CBREWER2(CNAME) without an NCOL input will use the same number of
-%   colours as the current colormap.
-%
-%   CBREWER2(CNAME, NCOL, INTERP_METHOD) allows you to change the method
-%   used for the interpolation. The default is 'cubic'.
-%
-%   CBREWER2(CNAME, NCOL, INTERP_METHOD, INTERP_SPACE) allows you to
-%   change the colorspace used for the interpolation. By default, this is
-%   in the CIELAB colorspace, which is approximately perceptually uniform.
-%   Options for INTERP_SPACE are
-%     'rgb' : interpolation in sRGB (as used in original CBREWER)
-%     'lab' : interpolation in CIELAB (default)
-%     'lch' : interpolation in CIELCH_ab (not recommended due to the
-%               discontinuities at C=0 and H=0)
-%     Anything else supported by COLORSPACE will also function.
-%
-%   The input format CBREWER2(TYPE, ...) can also be used, where TYPE is
-%   one of 'seq', 'div', 'qual'. This input is redandant and will be
-%   ignored. This input format is provided for backwards compatibility with
-%   the original CBREWER.
-%
-%   Example 1 (sequential heatmap):
-%       C = [0 2 4 6; 8 10 12 14; 16 18 20 22];
-%       imagesc(C);
-%       colorbar;
-%       colormap(cbrewer('YlOrRd', 256);
-%
-%   Example 2 (line plot):
-%       x = 0:0.01:2;
-%       sc = [0.5; 1; 2];
-%       t0 = [0; 0.2; 0.4];
-%       t = bsxfun(@rdivide, bsxfun(@plus, x, t0), sc);
-%       y = sin(t * 2 * pi);
-%       cmap = cbrewer2('Set1', numel(sc));
-%       axes('ColorOrder', cmap, 'NextPlot', 'ReplaceChildren');
-%       plot(x, y);
-%
-%   Example 3 (divergent heatmap):
-%       [X,Y,Z] = peaks(30);
-%       surfc(X,Y,Z);
-%       colormap(cbrewer2('RdBu'));
-%
-%   This product includes color specifications and designs developed by
-%   Cynthia Brewer (http://colorbrewer.org/). For more information on
-%   ColorBrewer, please visit http://colorbrewer.org/.
-%
-%   CBREWER2 uses a cached copy of the Cynthia Brewer color schemes which
-%   was converted to .mat format by Charles Robert for use with CBREWER.
-%   CBREWER is available from the MATLAB FileExchange under the MIT license.
-%
-%   See also CBREWER, BREWERMAP, COLORSPACE, INTERP1.
-
-
-%   Copyright (c) 2016 Scott Lowe
-%
-%   Licensed under the Apache License, Version 2.0 (the "License");
-%   you may not use this file except in compliance with the License.
-%   You may obtain a copy of the License at
-%
-%       http://www.apache.org/licenses/LICENSE-2.0
-%
-%   Unless required by applicable law or agreed to in writing, software
-%   distributed under the License is distributed on an "AS IS" BASIS,
-%   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-%   See the License for the specific language governing permissions and
-%   limitations under the License.
-
-
-function colormap = cbrewer2(...
-    cname, ncol, interp_method, interp_space, varargin)
-
-% Definitions -------------------------------------------------------------
-
-% List of all of Cynthia Brewer's colormaps and their types
-%  seq: sequential
-%  div: divergent
-%  qual: qualitative
-cbdict = {...
-    'Blues',    'seq'; ...
-    'BuGn',     'seq'; ...
-    'BuPu',     'seq'; ...
-    'GnBu',     'seq'; ...
-    'Greens',   'seq'; ...
-    'Greys',    'seq'; ...
-    'Oranges',  'seq'; ...
-    'OrRd',     'seq'; ...
-    'PuBu',     'seq'; ...
-    'PuBuGn',   'seq'; ...
-    'PuRd',     'seq'; ...
-    'Purples',  'seq'; ...
-    'RdPu',     'seq'; ...
-    'Reds',     'seq'; ...
-    'YlGn',     'seq'; ...
-    'YlGnBu',   'seq'; ...
-    'YlOrBr',   'seq'; ...
-    'YlOrRd',   'seq'; ...
-    'BrBG',     'div'; ...
-    'PiYG',     'div'; ...
-    'PRGn',     'div'; ...
-    'PuOr',     'div'; ...
-    'RdBu',     'div'; ...
-    'RdGy',     'div'; ...
-    'RdYlBu',   'div'; ...
-    'RdYlGn', 	'div'; ...
-    'Spectral', 'div'; ...
-    'Accent',   'qual'; ...
-    'Dark2',    'qual'; ...
-    'Paired',   'qual'; ...
-    'Pastel1',  'qual'; ...
-    'Pastel2',  'qual'; ...
-    'Set1',     'qual'; ...
-    'Set2',     'qual'; ...
-    'Set3',     'qual'; ...
-    };
-
-
-% Input handling ----------------------------------------------------------
-
-narginchk(1, 5);
-
-% Initialise variables if not supplied
-if nargin<2
-    ncol = [];
-end
-if nargin<3
-    interp_method = [];
-end
-if nargin<4
-    interp_space = [];
-end
-if nargin<5
-    varargin = {[]};
-end
-
-% Check if the colormap type was unnecessarily input
-types = unique(cbdict(:, 2));
-if nargin > 1 && ischar(cname) && ischar(ncol)
-    LI = ismember({cname ncol}, types);
-    if ~any(LI); error('Number of colors cannot be a string'); end;
-    if all(LI); error('Incorrect colormap name'); end;
-    if LI(1)
-        vgn = {cname; ncol; interp_method; interp_space};
-        cname           = vgn{2};
-        ncol            = vgn{3};
-        interp_method   = vgn{4};
-        interp_space    = varargin{1};
-        ctype_input     = vgn{1};
-    elseif LI(2)
-        vgn = {cname; ncol; interp_method; interp_space};
-        cname           = vgn{1};
-        ncol            = vgn{3};
-        interp_method   = vgn{4};
-        interp_space    = varargin{1};
-        ctype_input     = vgn{2};
-    end
-else
-    ctype_input = '';
-end
-
-% Default values
-if isempty(ncol)
-    % Number of colours in the colormap
-    ncol = size(get(gcf,'colormap'), 1);
-end
-if isempty(interp_method)
-    interp_method = 'pchip';
-end
-if isempty(interp_space)
-    interp_space = 'lab';
-end
-
-
-% Load colorbrewer data ---------------------------------------------------
-Tmp = load('colorbrewer.mat');
-colorbrewer = Tmp.colorbrewer;
-
-[TF, idict] = ismember(lower(cname), lower(cbdict(:, 1)));
-
-if ~TF
-    error('%s is not a recognised Brewer colormap',cname);
-end
-
-cname = cbdict{idict, 1};
-ctype = cbdict{idict, 2};
-
-if (~isfield(colorbrewer.(ctype), cname))
-    error('Colormap %s is not present in loaded data',cname);
-end
-
-
-% Main script -------------------------------------------------------------
-
-if ncol > length(colorbrewer.(ctype).(cname))
-    % If we specified too many colours, we take the maximum and interpolate
-    colormap = colorbrewer.(ctype).(cname){length(colorbrewer.(ctype).(cname))};
-    colormap = colormap ./ 255;
-elseif isempty(colorbrewer.(ctype).(cname){ncol})
-    % If we specified too few colours, we take the minimum and interpolate
-    nmin = find(~cellfun(@isempty, colorbrewer.(ctype).(cname)), 1);
-    colormap = colorbrewer.(ctype).(cname){nmin};
-    colormap = colormap./255;
-else
-    % If we specified a number of colours in the pre-designed range, no
-    % need to interpolate
-    colormap = (colorbrewer.(ctype).(cname){ncol}) ./ 255;
-    return;
-end
-
-% Don't interpolate if qualitative type
-if strcmp(ctype,'qual')
-    if size(colormap, 1) >= ncol
-        colormap = colormap(1:ncol, :);
-        return;
-    end
-    warning('CBREWER2:QualTooManyColors', ...
-        ['Too many colors requested: cannot interpolate a qualitative' ...
-        ' colorscheme']);
-    % Cycle the colours from the beginning again, so we have enough to
-    % return
-    colormap = repmat(colormap, ceil(ncol / size(colormap, 1)), 1);
-    colormap = colormap(1:ncol, :);
-    return;
-end
-
-% Make sure we have colorspace downloaded from the FEX
-if ~strcmpi(interp_space, 'rgb') && ~exist('colorspace.m', 'file')
-    P = requireFEXpackage(28790);
-    if isempty(P);
-        error(...
-            ['You need to download COLORSPACE from the MATLAB FEX and' ...
-            ' add it to the MATLAB path.']);
-    end;
-end
-
-% Move to perceptually uniform space
-if ~strcmpi(interp_space,'rgb')
-    colormap = colorspace(['rgb->' interp_space], colormap);
-end
-
-% Linearly interpolate
-X  = linspace(0, 1, size(colormap, 1));
-XI = linspace(0, 1, ncol);
-colormap = interp1(X, colormap, XI, interp_method);
-
-% Move from perceptually uniform space back to sRGB
-if ~strcmpi(interp_space,'rgb')
-    colormap = colorspace(['rgb<-' interp_space], colormap);
-end
-
-end

Functions/helper_functions_community/cbrewer2/requireFEXpackage.m

@@ -1,194 +0,0 @@
-function AddedPath = requireFEXpackage(FEXSubmissionID)
-%Function requireFEXpackage - 
-%installs Matlab Central File Exchange (FEX) submission 
-%with given ID into the directory chosen by the user.
-%A new FEX submissions may use previous FEX submissions as its part.
-%The function 'requireFEXpackage' helps in adding those previous
-%submissions to the user's MATLAB installation. 
-%
-%This function is a part of File Exchange submission 31069. 
-%Download the entire submission:
-%http://www.mathworks.com/matlabcentral/fileexchange/31069
-%
-% SYNTAX: 
-%    AddedPath = requireFEXpackage(FEXSubmissionID)
-%
-% INPUT: 
-%    ID of the required submission to File Exchange 
-%
-% OUTPUT: 
-%    the path to that submission added to the user's MATLAB path.
-%
-% HOW TO CALL:
-%    The command 
-%           P = requireFEXpackage(8277)
-%    will download and install the package with ID 8277 
-%    (namely, nice 'fminsearchbnd' by John D'Errico)
-%
-% EXAMPLES -- HOW TO USE:
-%
-% EXAMPLE 1 (using 'exist' command):
-%
-%     % first, somewhere in the very beginning of your code,
-%     % check if the function 'fminsearchbnd' from the FEX package 8277 
-%     % is on your MATLAB path, and if it is not there, 
-%     % require the FEX package 8277:
-%     if ~(exist('fminsearchbnd', 'file') == 2)
-%         P = requireFEXpackage(8277);  % fminsearchbnd is part of 8277
-%     end
-% 
-%     % Then just use 'fminsearchbnd' where you need it:
-%     syms x
-%     RosenbrockBananaFunction = @(x) (1-x(1)).^2 + 100*(x(2)-x(1).^2).^2;
-%     x = fminsearchbnd(RosenbrockBananaFunction,[3 3])
-
-% EXAMPLE 2 (using 'try-catch' command):
-%
-%     syms x
-%     RosenbrockBananaFunction = @(x) (1-x(1)).^2+100*(x(2)-x(1).^2).^2;
-%     try 
-%        % if function 'fminsearchbnd' already exists in your MATLAB
-%        % installation, just use it:
-%        x = fminsearchbnd(RosenbrockBananaFunction,[3 3])
-%     catch 
-%        % if function 'fminsearchbnd' is not present in your MATLAB
-%        % installation, first get the package 8277 (to which it belongs) 
-%        % from the MATLAB Central File Exchange (FEX)
-%        P = requireFEXpackage(8277);  % fminsearchbnd is part of 8277
-%        % and then use that function:
-%        x = fminsearchbnd(RosenbrockBananaFunction,[3 3])
-%     end
-% 
-%
-% NOTE: on Mac platform, the title of the dialog box for 
-% choosing the directory for installing the required FEX package 
-% is not shown; this is not a bug, this is how UIGETDIR works on Macs --  
-% see the documentation for UIGETDIR
-% http://www.mathworks.com/help/techdoc/ref/uigetdir.html
-%
-% (C) Igor Podlubny, 2011
-
-% Copyright (c) 2011, Igor Podlubny
-% All rights reserved.
-% 
-% Redistribution and use in source and binary forms, with or without
-% modification, are permitted provided that the following conditions are
-% met:
-% 
-%     * Redistributions of source code must retain the above copyright
-%       notice, this list of conditions and the following disclaimer.
-%     * Redistributions in binary form must reproduce the above copyright
-%       notice, this list of conditions and the following disclaimer in
-%       the documentation and/or other materials provided with the distribution
-% 
-% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
-% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
-% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
-% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
-% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
-% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
-% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
-% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
-% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-% POSSIBILITY OF SUCH DAMAGE.
-
-
-ID = num2str(FEXSubmissionID);
-
-% Ask user for the confirmation of the installation
-% of the required FEX package
-yes = ['YES, Install package ' ID];
-no = 'NO, do not install';
-userchoice = questdlg(['The Matlab function/toolbox, which you are running, ' ... 
-    'requires the presence of the package ' ID ... 
-    ' from Matlab Central File Exchange.' ...
-     sprintf('\n\n') ...
-    'Would you like to install the FEX package ' ID ' now?'] , ...
-	['Required package ' ID], ...
-	yes, no, yes);
-
-% Handle response
-switch userchoice
-    case yes,
-        install = 1;			
-    case no,
-        install = 0;
-    otherwise,
-        install = 0;
-end
-
-
-if install == 1
-    baseURL = 'http://www.mathworks.com/matlabcentral/fileexchange/';
-    query = '?download=true';
-
-    location = uigetdir(pwd, ['Select the directory for installing the required FEX package' ID ]);
-    if location ~= 0
-        % download package 'ID' from Matlab Central File Exchange
-        filetosave = [location filesep ID '.zip'];
-        FEXpackage = [baseURL ID query];
-        [f,status] = urlwrite(FEXpackage,filetosave);
-        if status==0 
-            warndlg(['No connection to Matlab Central File Exchange,' ' or package ' ID ' does not exist.' ... 
-                ' Package ' ID ' has not been installed. ' ...
-                ' Check you internet settings and the ID of the required package, and try again. '] , ...
-                ['No connection to Matlab Central File Exchange' ' or package ' ID ' does not exist'], ...
-                'modal');
-            AddedPath = '';            
-            return
-        end
-        % unzip the downloaded file to the subdirectory 'ID'
-        todir = [location filesep ID];
-        % if the directory 'ID' doesn't exist at given location, create it
-        if ~(exist([location filesep ID], 'dir') == 7)
-            mkdir(location, ID);
-        end
-        try 
-            unzip(filetosave, todir);
-            % after unzipping, delete the downloaded ZIP file
-            delete(filetosave);
-            % prepend the paths to the downloaded package to the MATLAB path
-            P = genpath([location filesep ID]);
-            path(P,path);
-        catch
-            % if the FEX package is not ZIP, then it is a single m-file
-            % just move the file to the ID directory
-            [pathstr, name, ext] = fileparts(filetosave);
-            movefile(filetosave, [todir filesep name '.m']);
-            P = genpath([location filesep ID]);
-            path(P,path);
-        end
-    else
-        P = '';
-    end
-
-    AddedPath = P; 
-else
-    AddedPath = '';
-end
-
-
-if install == 1,
-    % Ask user about reviewing and saving the modified MATLAB path, 
-    % and take him to PATHTOOL, if the user wants to save the modified path
-    yes = 'YES, I want to review and save the MATLAB path';
-    no = 'NO, I don''t want to save the path permanently';
-    userchoice = questdlg(['After adding the package ' ID ... 
-        ' from Matlab Central File Exchange to your MATLAB installation,' ...
-        ' the MATLAB path has been modified accordingly. ', ...
-        'Would you like to review and save the modified MATLAB path?'] , ...
-        'Review and save the modified MATLAB path for future use?', ...
-        yes, no, yes);
-    
-    % Handle response
-    switch userchoice
-        case yes,
-            pathtool;			
-        case no,
-        otherwise,
-    end
-end
-
-
-

Functions/helper_functions_community/linspecer.m

@@ -1,261 +0,0 @@
-% function lineStyles = linspecer(N)
-% This function creates an Nx3 array of N [R B G] colors
-% These can be used to plot lots of lines with distinguishable and nice
-% looking colors.
-% 
-% lineStyles = linspecer(N);  makes N colors for you to use: lineStyles(ii,:)
-% 
-% colormap(linspecer); set your colormap to have easily distinguishable 
-%                      colors and a pleasing aesthetic
-% 
-% lineStyles = linspecer(N,'qualitative'); forces the colors to all be distinguishable (up to 12)
-% lineStyles = linspecer(N,'sequential'); forces the colors to vary along a spectrum 
-% 
-% % Examples demonstrating the colors.
-% 
-% LINE COLORS
-% N=6;
-% X = linspace(0,pi*3,1000); 
-% Y = bsxfun(@(x,n)sin(x+2*n*pi/N), X.', 1:N); 
-% C = linspecer(N);
-% axes('NextPlot','replacechildren', 'ColorOrder',C);
-% plot(X,Y,'linewidth',5)
-% ylim([-1.1 1.1]);
-% 
-% SIMPLER LINE COLOR EXAMPLE
-% N = 6; X = linspace(0,pi*3,1000);
-% C = linspecer(N)
-% hold off;
-% for ii=1:N
-%     Y = sin(X+2*ii*pi/N);
-%     plot(X,Y,'color',C(ii,:),'linewidth',3);
-%     hold on;
-% end
-% 
-% COLORMAP EXAMPLE
-% A = rand(15);
-% figure; imagesc(A); % default colormap
-% figure; imagesc(A); colormap(linspecer); % linspecer colormap
-% 
-%   See also NDHIST, NHIST, PLOT, COLORMAP, 43700-cubehelix-colormaps
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% by Jonathan Lansey, March 2009-2013 – Lansey at gmail.com               %
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-% 
-%% credits and where the function came from
-% The colors are largely taken from:
-% http://colorbrewer2.org and Cynthia Brewer, Mark Harrower and The Pennsylvania State University
-% 
-% 
-% She studied this from a phsychometric perspective and crafted the colors
-% beautifully.
-% 
-% I made choices from the many there to decide the nicest once for plotting
-% lines in Matlab. I also made a small change to one of the colors I
-% thought was a bit too bright. In addition some interpolation is going on
-% for the sequential line styles.
-% 
-% 
-%%
-
-function lineStyles=linspecer(N,varargin)
-
-if nargin==0 % return a colormap
-    lineStyles = linspecer(128);
-    return;
-end
-
-if ischar(N)
-    lineStyles = linspecer(128,N);
-    return;
-end
-
-if N<=0 % its empty, nothing else to do here
-    lineStyles=[];
-    return;
-end
-
-% interperet varagin
-qualFlag = 0;
-colorblindFlag = 0;
-
-if ~isempty(varargin)>0 % you set a parameter?
-    switch lower(varargin{1})
-        case {'qualitative','qua'}
-            if N>12 % go home, you just can't get this.
-                warning('qualitiative is not possible for greater than 12 items, please reconsider');
-            else
-                if N>9
-                    warning(['Default may be nicer for ' num2str(N) ' for clearer colors use: whitebg(''black''); ']);
-                end
-            end
-            qualFlag = 1;
-        case {'sequential','seq'}
-            lineStyles = colorm(N);
-            return;
-        case {'white','whitefade'}
-            lineStyles = whiteFade(N);return;
-        case 'red'
-            lineStyles = whiteFade(N,'red');return;
-        case 'blue'
-            lineStyles = whiteFade(N,'blue');return;
-        case 'green'
-            lineStyles = whiteFade(N,'green');return;
-        case {'gray','grey'}
-            lineStyles = whiteFade(N,'gray');return;
-        case {'colorblind'}
-            colorblindFlag = 1;
-        otherwise
-            warning(['parameter ''' varargin{1} ''' not recognized']);
-    end
-end      
-% *.95
-% predefine some colormaps
-  set3 = colorBrew2mat({[141, 211, 199];[ 255, 237, 111];[ 190, 186, 218];[ 251, 128, 114];[ 128, 177, 211];[ 253, 180, 98];[ 179, 222, 105];[ 188, 128, 189];[ 217, 217, 217];[ 204, 235, 197];[ 252, 205, 229];[ 255, 255, 179]}');
-set1JL = brighten(colorBrew2mat({[228, 26, 28];[ 55, 126, 184]; [ 77, 175, 74];[ 255, 127, 0];[ 255, 237, 111]*.85;[ 166, 86, 40];[ 247, 129, 191];[ 153, 153, 153];[ 152, 78, 163]}'));
-set1 = brighten(colorBrew2mat({[ 55, 126, 184]*.85;[228, 26, 28];[ 77, 175, 74];[ 255, 127, 0];[ 152, 78, 163]}),.8);
-
-% colorblindSet = {[215,25,28];[253,174,97];[171,217,233];[44,123,182]};
-colorblindSet = {[215,25,28];[253,174,97];[171,217,233]*.8;[44,123,182]*.8};
-
-set3 = dim(set3,.93);
-
-if colorblindFlag
-    switch N
-        %     sorry about this line folks. kind of legacy here because I used to
-        %     use individual 1x3 cells instead of nx3 arrays
-        case 4
-            lineStyles = colorBrew2mat(colorblindSet);
-        otherwise
-            colorblindFlag = false;
-            warning('sorry unsupported colorblind set for this number, using regular types');
-    end
-end
-if ~colorblindFlag
-    switch N
-        case 1
-            lineStyles = { [  55, 126, 184]/255};
-        case {2, 3, 4, 5 }
-            lineStyles = set1(1:N);
-        case {6 , 7, 8, 9}
-            lineStyles = set1JL(1:N)';
-        case {10, 11, 12}
-            if qualFlag % force qualitative graphs
-                lineStyles = set3(1:N)';
-            else % 10 is a good number to start with the sequential ones.
-                lineStyles = cmap2linspecer(colorm(N));
-            end
-        otherwise % any old case where I need a quick job done.
-            lineStyles = cmap2linspecer(colorm(N));
-    end
-end
-lineStyles = cell2mat(lineStyles);
-
-end
-
-% extra functions
-function varIn = colorBrew2mat(varIn)
-for ii=1:length(varIn) % just divide by 255
-    varIn{ii}=varIn{ii}/255;
-end        
-end
-
-function varIn = brighten(varIn,varargin) % increase the brightness
-
-if isempty(varargin),
-    frac = .9; 
-else
-    frac = varargin{1}; 
-end
-
-for ii=1:length(varIn)
-    varIn{ii}=varIn{ii}*frac+(1-frac);
-end        
-end
-
-function varIn = dim(varIn,f)
-    for ii=1:length(varIn)
-        varIn{ii} = f*varIn{ii};
-    end
-end
-
-function vOut = cmap2linspecer(vIn) % changes the format from a double array to a cell array with the right format
-vOut = cell(size(vIn,1),1);
-for ii=1:size(vIn,1)
-    vOut{ii} = vIn(ii,:);
-end
-end
-%%
-% colorm returns a colormap which is really good for creating informative
-% heatmap style figures.
-% No particular color stands out and it doesn't do too badly for colorblind people either.
-% It works by interpolating the data from the
-% 'spectral' setting on http://colorbrewer2.org/ set to 11 colors
-% It is modified a little to make the brightest yellow a little less bright.
-function cmap = colorm(varargin)
-n = 100;
-if ~isempty(varargin)
-    n = varargin{1};
-end
-
-if n==1
-    cmap =  [0.2005    0.5593    0.7380];
-    return;
-end
-if n==2
-     cmap =  [0.2005    0.5593    0.7380;
-              0.9684    0.4799    0.2723];
-          return;
-end
-
-frac=.95; % Slight modification from colorbrewer here to make the yellows in the center just a bit darker
-cmapp = [158, 1, 66; 213, 62, 79; 244, 109, 67; 253, 174, 97; 254, 224, 139; 255*frac, 255*frac, 191*frac; 230, 245, 152; 171, 221, 164; 102, 194, 165; 50, 136, 189; 94, 79, 162];
-x = linspace(1,n,size(cmapp,1));
-xi = 1:n;
-cmap = zeros(n,3);
-for ii=1:3
-    cmap(:,ii) = pchip(x,cmapp(:,ii),xi);
-end
-cmap = flipud(cmap/255);
-end
-
-function cmap = whiteFade(varargin)
-n = 100;
-if nargin>0
-    n = varargin{1};
-end
-
-thisColor = 'blue';
-
-if nargin>1
-    thisColor = varargin{2};
-end
-switch thisColor
-    case {'gray','grey'}
-        cmapp = [255,255,255;240,240,240;217,217,217;189,189,189;150,150,150;115,115,115;82,82,82;37,37,37;0,0,0];
-    case 'green'
-        cmapp = [247,252,245;229,245,224;199,233,192;161,217,155;116,196,118;65,171,93;35,139,69;0,109,44;0,68,27];
-    case 'blue'
-        cmapp = [247,251,255;222,235,247;198,219,239;158,202,225;107,174,214;66,146,198;33,113,181;8,81,156;8,48,107];
-    case 'red'
-        cmapp = [255,245,240;254,224,210;252,187,161;252,146,114;251,106,74;239,59,44;203,24,29;165,15,21;103,0,13];
-    otherwise
-        warning(['sorry your color argument ' thisColor ' was not recognized']);
-end
-
-cmap = interpomap(n,cmapp);
-end
-
-% Eat a approximate colormap, then interpolate the rest of it up.
-function cmap = interpomap(n,cmapp)
-    x = linspace(1,n,size(cmapp,1));
-    xi = 1:n;
-    cmap = zeros(n,3);
-    for ii=1:3
-        cmap(:,ii) = pchip(x,cmapp(:,ii),xi);
-    end
-    cmap = (cmap/255); % flipud??
-end
-
-
-