rename jamm files to pmat - portable mat, will add jsonmmap

NeuroJSON · Apr 9, 2023 · 8c8464f · 8c8464f
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diff --git a/.github/workflows/run_test.yml b/.github/workflows/run_test.yml
@@ -6,6 +6,7 @@ jobs:
   octave_test:
     name: Octave tests
     strategy:
+      # provided octave versions: ubuntu-20.04 = 5.2, ubuntu-22.04 = 6.4, macos-11 = 8.1, windows-2019 = 7.3
       matrix:
         os: [ubuntu-20.04, ubuntu-22.04, macos-11, windows-2019]
     runs-on: ${{ matrix.os }}
@@ -23,9 +24,9 @@ jobs:
           [[ "$RUNNER_OS" == "Linux" ]] && sudo apt-get update && sudo apt-get install -y octave
           [[ "$RUNNER_OS" == "macOS" ]] && brew install octave
           if [[ "$RUNNER_OS" == "Windows" ]]; then
-            curl --retry 3 -kL http://cdimage.debian.org/mirror/gnu.org/gnu/octave/windows/octave-8.1.0-w64-64.7z --output octave_8.1.7z
-            7z x octave_8.1.7z -ooctave -y
-            echo "$PWD/octave/octave-8.1.0-w64-64/mingw64/bin" >> $GITHUB_PATH
+            curl --retry 3 -kL http://cdimage.debian.org/mirror/gnu.org/gnu/octave/windows/octave-7.3.0-w64-64.7z --output octave_7.3.0.7z
+            7z x octave_7.3.0.7z -ooctave -y
+            echo "$PWD/octave/octave-7.3.0-w64-64/mingw64/bin" >> $GITHUB_PATH
           fi
       - name: Run octave test
         run: |

diff --git a/README.rst b/README.rst
@@ -138,7 +138,7 @@ To read BJData data files generated by JSONLab v2.0, you should call
 
    data=loadbj('my_old_data_file.bjd','Endian','B')
 
-You are strongly encouraged to convert all pre-v2.9 JSONLab generated BJD or .jamm
+You are strongly encouraged to convert all pre-v2.9 JSONLab generated BJD or .pmat
 files using the new format.
 
 
@@ -323,7 +323,7 @@ for reading and writing below files types:
 - JSON based files: ``.json`, ``.jdt`` (text JData file), ``.jmsh`` (text JMesh file),
   ``.jnii`` (text JNIfTI file), ``.jnirs`` (text JSNIRF file)
 - BJData based files: ``.bjd`, ``.jdb` (binary JData file), ``.bmsh`` (binary JMesh file),
-  ``.bnii`` (binary JNIfTI file), ``.bnirs`` (binary JSNIRF file), ``.jamm`` (MATLAB session file)
+  ``.bnii`` (binary JNIfTI file), ``.bnirs`` (binary JSNIRF file), ``.pmat`` (MATLAB session file)
 - UBJSON based files: ``.ubj``
 - MessagePack based files: ``.msgpack``
 - HDF5 based files: ``.h5``, ``.hdf5``, ``.snirf`` (SNIRF fNIRS data files) - require `EasyH5 toolbox <https://github.com/NeuroJSON/easyh5>`_
@@ -442,20 +442,20 @@ Using ``jsave/jload`` to share workspace
 Starting from JSONLab v2.0, we provide a pair of functions, ``jsave/jload`` to store
 and retrieve variables from the current workspace, similar to the ``save/load`` 
 functions in MATLAB and Octave. The files that ``jsave/jload`` reads/writes is by  
-default a binary JData file with a suffix ``.jamm``. The file size is comparable
+default a binary JData file with a suffix ``.pmat``. The file size is comparable
 (can be smaller if use ``lzma`` compression) to ``.mat`` files. This feature
 is currently experimental.
 
-The main benefits of using .jamm file to share matlab variables include
+The main benefits of using .pmat file to share matlab variables include
 
-* a ``.jamm`` file can be 50% smaller than a ``.mat`` file when using 
+* a ``.pmat`` file can be 50% smaller than a ``.mat`` file when using 
   ``jsave(..., "compression","lzma")``; the only drawback is longer saving time.
-* a ``.jamm`` file can be readily read/opened among many programming environments, including 
+* a ``.pmat`` file can be readily read/opened among many programming environments, including 
   Python, JavaScript, Go, Java etc, where .mat file support is not generally available. 
-  Parsers of ``.jamm`` files are largely compatible with UBJSON's parsers available at 
+  Parsers of ``.pmat`` files are largely compatible with UBJSON's parsers available at 
   http://ubjson.org/?page_id=48
-* a ``.jamm`` file is quasi-human-readable, one can see the internal data fields 
-  even in a command line, for example using ``strings -n 2 file.jamm | astyle``, 
+* a ``.pmat`` file is quasi-human-readable, one can see the internal data fields 
+  even in a command line, for example using ``strings -n 2 file.pmat | astyle``, 
   making the binary data easy to be understood, shared and reused. 
 * ``jsave/jload`` can also use MessagePack and JSON formats as the underlying 
   data storage format, addressing needs from a diverse set of applications. 
@@ -467,10 +467,10 @@ jsave.m
 
 .. code-block:: matlab
 
-      jsave    % save the current workspace to jamdata.jamm
-      jsave mydata.jamm
-      jsave('mydata.jamm','vars',{'var1','var2'})
-      jsave('mydata.jamm','compression','lzma')
+      jsave    % save the current workspace to default.pmat
+      jsave mydata.pmat
+      jsave('mydata.pmat','vars',{'var1','var2'})
+      jsave('mydata.pmat','compression','lzma')
       jsave('mydata.json','compression','gzip')
 
 ----------
@@ -479,10 +479,10 @@ jload.m
 
 .. code-block:: matlab
 
-      jload    % load variables from jamdata.jamm to the current workspace
-      jload mydata.jamm   % load variables from mydata.jamm
-      vars=jload('mydata.jamm','vars',{'var1','var2'}) % return vars.var1, vars.var2
-      jload('mydata.jamm','simplifycell',0)
+      jload    % load variables from default.pmat to the current workspace
+      jload mydata.pmat   % load variables from mydata.pmat
+      vars=jload('mydata.pmat','vars',{'var1','var2'}) % return vars.var1, vars.var2
+      jload('mydata.pmat','simplifycell',0)
       jload('mydata.json')
 
 
@@ -501,7 +501,7 @@ However, we strongly recommend one to use a lightweight ``jdata`` module,
 developed by the same author, to perform the extra JData encoding and decoding
 and convert JSON data directly to convenient Python/Numpy data structures.
 The ``jdata`` module can also directly read/write UBJSON/Binary JData outputs
-from JSONLab (``.bjd, .ubj, .bnii, .bnirs, .jamm`` etc). Using binary JData
+from JSONLab (``.bjd, .ubj, .bnii, .bnirs, .pmat`` etc). Using binary JData
 files are expected to produce much smaller file sizes and faster parsing,
 while maintaining excellent portability and generality.
 
@@ -547,7 +547,7 @@ Once the necessary modules are installed, one can type ``python`` (or ``python3`
 
       data1=jd.loadt('myfile.json',object_pairs_hook=OrderedDict);
       data2=jd.loadb('myfile.ubj',object_pairs_hook=OrderedDict);
-      data3=jd.loadb('myfile.jamm',object_pairs_hook=OrderedDict);
+      data3=jd.loadb('myfile.pmat',object_pairs_hook=OrderedDict);
 
 where ``jd.loadt()`` function loads a text-based JSON file, performs
 JData decoding and converts the enclosed data into Python ``dict``, ``list`` 

diff --git a/README.txt b/README.txt
@@ -135,7 +135,7 @@ To read BJData data files generated by JSONLab v2.0, you should call
 
    data=loadbj('my_old_data_file.bjd','Endian','B')
 
-You are strongly encouraged to convert all pre-v2.9 JSONLab generated BJD or .jamm
+You are strongly encouraged to convert all pre-v2.9 JSONLab generated BJD or .pmat
 files using the new format.
 
 
@@ -291,7 +291,7 @@ for reading and writing below files types:
 * JSON based files: `.json`, `.jdt` (text JData file), `.jmsh` (text JMesh file), \
   `.jnii` (text JNIfTI file), `.jnirs` (text JSNIRF file)
 * BJData based files: `.bjd`, `.jdb` (binary JData file), `.bmsh` (binary JMesh file), \
-  `.bnii` (binary JNIfTI file), `.bnirs` (binary JSNIRF file), `.jamm` (MATLAB session file)
+  `.bnii` (binary JNIfTI file), `.bnirs` (binary JSNIRF file), `.pmat` (MATLAB session file)
 * UBJSON based files: `.ubj`
 * MessagePack based files: `.msgpack`
 * HDF5 based files: `.h5`, `.hdf5`, `.snirf` (SNIRF fNIRS data files) - require [https://github.com/fangq/easyh5 EasyH5 toolbox]
@@ -383,20 +383,20 @@ IV.Using `jsave/jload` to share workspace
 Starting from JSONLab v2.0, we provide a pair of functions, `jsave/jload` to store
 and retrieve variables from the current workspace, similar to the `save/load` 
 functions in MATLAB and Octave. The files that `jsave/jload` reads/writes is by  
-default a binary JData file with a suffix `.jamm`. The file size is comparable
+default a binary JData file with a suffix `.pmat`. The file size is comparable
 (can be smaller if use `lzma` compression) to `.mat` files. This feature
 is currently experimental.
 
-The main benefits of using .jamm file to share matlab variables include
+The main benefits of using .pmat file to share matlab variables include
 
-* a `.jamm` file can be 50% smaller than a `.mat` file when using \
+* a `.pmat` file can be 50% smaller than a `.mat` file when using \
   `jsave(..., "compression","lzma")`; the only drawback is longer saving time.
-* a `.jamm` file can be readily read/opened among many programming environments, including \
+* a `.pmat` file can be readily read/opened among many programming environments, including \
   Python, JavaScript, Go, Java etc, where `.mat` file support is not generally available. \
-  Parsers of `.jamm` is largely compatible with UBJSON's parsers available at \
+  Parsers of `.pmat` is largely compatible with UBJSON's parsers available at \
   http://ubjson.org/?page_id=48
-* a `.jamm` file is quasi-human-readable, one can see the internal data fields \
-  even in a command line, for example using `strings -n 2 file.jamm | astyle`, \
+* a `.pmat` file is quasi-human-readable, one can see the internal data fields \
+  even in a command line, for example using `strings -n 2 file.pmat | astyle`, \
   making the binary data easy to be understood, shared and reused. 
 * `jsave/jload` can also use MessagePack and JSON formats as the underlying \
   data storage format, addressing needs from diverse applications. \
@@ -405,18 +405,18 @@ The main benefits of using .jamm file to share matlab variables include
 
 === jsave.m ===
 
-      jsave    % save the current workspace to jamdata.jamm
-      jsave mydata.jamm
-      jsave('mydata.jamm','vars',{'var1','var2'})
-      jsave('mydata.jamm','compression','lzma')
+      jsave    % save the current workspace to default.pmat
+      jsave mydata.pmat
+      jsave('mydata.pmat','vars',{'var1','var2'})
+      jsave('mydata.pmat','compression','lzma')
       jsave('mydata.json','compression','gzip')
 
 === jload.m ===
 
-      jload    % load variables from jamdata.jamm to the current workspace
-      jload mydata.jamm   % load variables from mydata.jamm
-      vars=jload('mydata.jamm','vars',{'var1','var2'}) % return vars.var1, vars.var2
-      jload('mydata.jamm','simplifycell',0)
+      jload    % load variables from default.pmat to the current workspace
+      jload mydata.pmat   % load variables from mydata.pmat
+      vars=jload('mydata.pmat','vars',{'var1','var2'}) % return vars.var1, vars.var2
+      jload('mydata.pmat','simplifycell',0)
       jload('mydata.json')
 
 -------------------------------------------------------------------------------
@@ -434,7 +434,7 @@ However, we strongly recommend one to use a lightweight `jdata` module,
 developed by the same author, to perform the extra JData encoding and decoding
 and convert JSON data directly to convenient Python/Numpy data structures.
 The `jdata` module can also directly read/write UBJSON/Binary JData outputs
-from JSONLab (`.bjd, .ubj, .bnii, .bnirs, .jamm` etc). Using binary JData
+from JSONLab (`.bjd, .ubj, .bnii, .bnirs, .pmat` etc). Using binary JData
 files are exptected to produce much smaller file sizes and faster parsing,
 while maintainining excellent portability and generality.
 
@@ -469,7 +469,7 @@ Once the necessary modules are installed, one can type `python` (or `python3`),
 
       data1=jd.loadt('myfile.json',object_pairs_hook=OrderedDict);
       data2=jd.loadb('myfile.ubj',object_pairs_hook=OrderedDict);
-      data3=jd.loadb('myfile.jamm',object_pairs_hook=OrderedDict);
+      data3=jd.loadb('myfile.pmat',object_pairs_hook=OrderedDict);
 
 where `jd.loadt()` function loads a text-based JSON file, performs
 JData decoding and converts the enclosed data into Python `dict`, `list` 

diff --git a/jdatadecode.m b/jdatadecode.m
@@ -476,7 +476,7 @@
                 switch(lower(fext))
                     case {'.json','.jnii','.jdt','.jdat','.jmsh','.jnirs'}
                         newdata=loadjson(uripath, opt);
-                    case {'.bjd' ,'.bnii','.jdb','.jbat','.bmsh','.bnirs', '.jamm'}
+                    case {'.bjd' ,'.bnii','.jdb','.jbat','.bmsh','.bnirs', '.pmat'}
                         newdata=loadbj(uripath, opt);
                     case {'.ubj'}
                         newdata=loadubjson(uripath, opt);

diff --git a/jload.m b/jload.m
@@ -13,9 +13,9 @@
 % created on 2020/05/31
 %
 % input:
-%      fname: (optional) input file name; if not given, load 'jamdata.jamm'
+%      fname: (optional) input file name; if not given, load 'default.pmat'
 %           if fname has a '.json' or '.jdt' suffix, a text-based
-%           JSON/JData file will be expected; if the suffix is '.jamm' or
+%           JSON/JData file will be expected; if the suffix is '.pmat' or
 %           '.jdb', a Binary JData file will be expected.
 %      opt: (optional) a struct to store parsing options, opt can be replaced by 
 %           a list of ('param',value) pairs - the param string is equivallent
@@ -41,10 +41,10 @@
 %               load the variables to the current workspace ('caller')
 %
 % examples:
-%      jload  % load all variables in jamdata.jamm to the 'caller' workspace 
-%      jload mydat.jamm
-%      jload('mydat.jamm','vars', {'v1','v2',...}) % load selected variables
-%      varlist=jload('mydat.jamm','simplifycell',1)
+%      jload  % load all variables in default.pmat to the 'caller' workspace 
+%      jload mydat.pmat
+%      jload('mydat.pmat','vars', {'v1','v2',...}) % load selected variables
+%      varlist=jload('mydat.pmat','simplifycell',1)
 %
 % license:
 %     BSD or GPL version 3, see LICENSE_{BSD,GPLv3}.txt files for details 
@@ -53,7 +53,7 @@
 %
 
 if(nargin==0)
-    filename=[pwd filesep 'jamdata.jamm'];
+    filename=[pwd filesep 'default.pmat'];
 end
 
 opt=varargin2struct(varargin{:});

diff --git a/jsave.m b/jsave.m
@@ -11,9 +11,9 @@
 % created on 2020/05/31
 %
 % input:
-%      fname: (optional) output file name; if not given, save to 'jamdata.jamm'
+%      fname: (optional) output file name; if not given, save to 'default.pmat'
 %           if fname has a '.json' or '.jdt' suffix, a text-based
-%           JSON/JData file will be created (slow); if the suffix is '.jamm' or
+%           JSON/JData file will be created (slow); if the suffix is '.pmat' or
 %           '.jdb', a Binary JData (https://github.com/NeuroJSON/bjdata/) file will be created.
 %      opt: (optional) a struct to store parsing options, opt can be replaced by 
 %           a list of ('param',value) pairs - the param string is equivallent
@@ -34,9 +34,9 @@
 %      varlist: a list of variables loaded
 %
 % examples:
-%      jsave  % save all variables in the 'caller' workspace to jamdata.jamm
-%      jsave('mydat.jamm','vars', {'v1','v2',...}) % save selected variables
-%      jsave('mydat.jamm','compression','lzma')
+%      jsave  % save all variables in the 'caller' workspace to jamdata.pmat
+%      jsave('mydat.pmat','vars', {'v1','v2',...}) % save selected variables
+%      jsave('mydat.pmat','compression','lzma')
 %
 % license:
 %     BSD or GPL version 3, see LICENSE_{BSD,GPLv3}.txt files for details 
@@ -45,7 +45,7 @@
 %
 
 if(nargin==0)
-    filename=[pwd filesep 'jamdata.jamm'];
+    filename=[pwd filesep 'default.pmat'];
 end
 
 opt=varargin2struct(varargin{:});

diff --git a/loadjson.m b/loadjson.m
@@ -514,7 +514,7 @@
 
 function [num, pos] = parse_number(inputstr, pos, varargin)
     currstr=inputstr(pos:min(pos+30,end));
-    [num, one, err, delta] = sscanf(currstr, '%f', 1);
+    [num, tmp, err, delta] = sscanf(currstr, '%f', 1);
     if ~isempty(err)
         pos=error_pos('Error reading number at position %d',inputstr,pos);
     end
@@ -529,7 +529,7 @@
     end
     varargout{3}=index_esc;
     if(nargout>3)
-            varargout{4}={};
+        varargout{4}={};
     end
     switch(inputstr(pos))
         case '"'
@@ -600,7 +600,7 @@
 		object(str)=val;
 	    else
 		object.(encodevarname(str,varargin{:}))=val;
-	    end
+            end
             [cc,pos]=next_char(inputstr,pos);
             if cc == '}'
                 break;