[WIP] Support schema 2.10.0

+file/fillConstructor.m

@@ -255,6 +255,7 @@
         catch
             description = 'No description';
         end
+        description = formatConstructorArgumentDescription(description);
 
         docString = [docString, ...
             sprintf("%%  - %s (%s) - %s", propName, valueType, description), ...
@@ -270,6 +271,16 @@
     docString = char( strjoin(docString, newline) );
 end
 
+function description = formatConstructorArgumentDescription(description)
+    descriptionLines = splitlines(string(description));
+
+    if numel(descriptionLines) > 1
+        descriptionLines(2:end) = "%    " + descriptionLines(2:end);
+    end
+
+    description = char(strjoin(descriptionLines, newline));
+end
+
 % Todo: Mostly duplicate code from file.fillProps. Should consolidate
 function typeStr = getTypeStr(prop)
     if ischar(prop)

+tests/+sanity/GeneratedClassSmokeTest.m

@@ -0,0 +1,50 @@
+classdef (SharedTestFixtures = {tests.fixtures.GenerateCoreFixture}) ...
+        GeneratedClassSmokeTest < matlab.unittest.TestCase
+
+    methods (Test)
+        function testGeneratedClassDefinitionsHaveMetaClasses(testCase)
+            typeClassNames = schemes.utility.listGeneratedTypes();
+            typesRoot = string(schemes.utility.findRootDirectoryForGeneratedTypes());
+            isClassDefinition = arrayfun( ...
+                @(className) startsWithGeneratedClassdef(typesRoot, className), ...
+                typeClassNames);
+            typeClassNames = typeClassNames(isClassDefinition);
+
+            testCase.verifyNotEmpty(typeClassNames, ...
+                'Expected generated neurodata type classes to be available.')
+
+            for i = 1:numel(typeClassNames)
+                typeClassName = typeClassNames(i);
+                typeClassNameAsChar = char(typeClassName);
+
+                try
+                    metaClass = meta.class.fromName(typeClassNameAsChar);
+                catch ME
+                    testCase.verifyFail(sprintf( ...
+                        'Could not get metaclass for generated class "%s": %s', ...
+                        typeClassNameAsChar, ME.message))
+                    continue
+                end
+
+                testCase.verifyNotEmpty(metaClass, sprintf( ...
+                    'Expected generated class "%s" to resolve to a metaclass.', ...
+                    typeClassNameAsChar))
+
+                if ~isempty(metaClass)
+                    testCase.verifyEqual(string(metaClass.Name), typeClassName)
+                end
+            end
+        end
+    end
+end
+
+function tf = startsWithGeneratedClassdef(typesRoot, typeClassName)
+    arguments
+        typesRoot (1,1) string
+        typeClassName (1,1) string
+    end
+
+    relativeFilePath = matnwb.common.internal.classname2path(typeClassName);
+    fileText = fileread(fullfile(typesRoot, relativeFilePath));
+    tf = startsWith(strtrim(fileText), "classdef");
+end

+types/+core/AbstractFeatureSeries.m

@@ -32,7 +32,7 @@
         %
         %  - data (numeric) - Values of each feature at each time.
         %
-        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
+        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. For storing instantaneous event information, it is recommended to use an EventsTable instead of a TimeSeries with continuity set to "instantaneous".
         %
         %  - data_conversion (single) - Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
         %

+types/+core/AnnotationSeries.m

@@ -1,5 +1,5 @@
 classdef AnnotationSeries < types.core.TimeSeries & types.untyped.GroupClass
-% ANNOTATIONSERIES - Stores user annotations made during an experiment. The data[] field stores a text array, and timestamps are stored for each annotation (ie, interval=1). This is largely an alias to a standard TimeSeries storing a text array but that is identifiable as storing annotations in a machine-readable way.
+% ANNOTATIONSERIES - DEPRECATED. Use an EventsTable instead. Stores user annotations made during an experiment. The data[] field stores a text array, and timestamps are stored for each annotation (ie, interval=1). This is largely an alias to a standard TimeSeries storing a text array but that is identifiable as storing annotations in a machine-readable way.
 %
 % Required Properties:
 %  data
@@ -24,7 +24,7 @@
         %
         %  - data (char) - Annotations made during an experiment.
         %
-        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
+        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. For storing instantaneous event information, it is recommended to use an EventsTable instead of a TimeSeries with continuity set to "instantaneous".
         %
         %  - data_conversion (single) - Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
         %

+types/+core/BehavioralEvents.m

@@ -1,5 +1,5 @@
 classdef BehavioralEvents < types.core.NWBDataInterface & types.untyped.GroupClass & matnwb.mixin.HasUnnamedGroups
-% BEHAVIORALEVENTS - TimeSeries for storing behavioral events. See description of BehavioralEpochs for more details.
+% BEHAVIORALEVENTS - DEPRECATED. Use an EventsTable instead. TimeSeries for storing behavioral events. See description of BehavioralEpochs for more details.
 %
 % Required Properties:
 %  timeseries

+types/+core/CurrentClampSeries.m

@@ -36,7 +36,7 @@
         %
         %  - data (numeric) - Recorded voltage.
         %
-        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
+        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. For storing instantaneous event information, it is recommended to use an EventsTable instead of a TimeSeries with continuity set to "instantaneous".
         %
         %  - data_conversion (single) - Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
         %

+types/+core/CurrentClampStimulusSeries.m

@@ -24,7 +24,7 @@
         %
         %  - data (numeric) - Stimulus current applied.
         %
-        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
+        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. For storing instantaneous event information, it is recommended to use an EventsTable instead of a TimeSeries with continuity set to "instantaneous".
         %
         %  - data_conversion (single) - Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
         %

+types/+core/DecompositionSeries.m

@@ -36,7 +36,7 @@
         %
         %  - data (numeric) - Data decomposed into frequency bands.
         %
-        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable.
+        %  - data_continuity (char) - Optionally describe the continuity of the data. Can be "continuous", "instantaneous", or "step". For example, a voltage trace would be "continuous", because samples are recorded from a continuous process. An array of lick times would be "instantaneous", because the data represents distinct moments in time. Times of image presentations would be "step" because the picture remains the same until the next timepoint. This field is optional, but is useful in providing information about the underlying data. It may inform the way this data is interpreted, the way it is visualized, and what analysis methods are applicable. For storing instantaneous event information, it is recommended to use an EventsTable instead of a TimeSeries with continuity set to "instantaneous".
         %
         %  - data_conversion (single) - Scalar to multiply each element in data to convert it to the specified 'unit'. If the data are stored in acquisition system units or other units that require a conversion to be interpretable, multiply the data by 'conversion' to convert the data to the specified 'unit'. e.g. if the data acquisition system stores values in this object as signed 16-bit integers (int16 range -32,768 to 32,767) that correspond to a 5V range (-2.5V to 2.5V), and the data acquisition system gain is 8000X, then the 'conversion' multiplier to get from raw data acquisition values to recorded volts is 2.5/32768/8000 = 9.5367e-9.
         %

+types/+core/DurationVectorData.m

@@ -0,0 +1,84 @@
+classdef DurationVectorData < types.hdmf_common.VectorData & types.untyped.DatasetClass
+% DURATIONVECTORDATA - A 1-dimensional VectorData that stores durations in seconds.
+%
+% Required Properties:
+%  data, description
+
+
+% READONLY PROPERTIES
+properties(SetAccess = protected)
+    unit = "seconds"; %  (char) The unit of measurement for the durations, fixed to 'seconds'.
+end
+% OPTIONAL PROPERTIES
+properties
+    resolution; %  (single) The temporal resolution of the durations, in seconds. This is typically the sampling period (1 / sampling_rate), also known as the clock period, of the data acquisition system from which the durations were recorded or derived.
+end
+
+methods
+    function obj = DurationVectorData(varargin)
+        % DURATIONVECTORDATA - Constructor for DurationVectorData
+        %
+        % Syntax:
+        %  durationVectorData = types.core.DURATIONVECTORDATA() creates a DurationVectorData object with unset property values.
+        %
+        %  durationVectorData = types.core.DURATIONVECTORDATA(Name, Value) creates a DurationVectorData object where one or more property values are specified using name-value pairs.
+        %
+        % Input Arguments (Name-Value Arguments):
+        %  - data (single) - Data property for dataset class (DurationVectorData)
+        %
+        %  - description (char) - Description of what these vectors represent.
+        %
+        %  - resolution (single) - The temporal resolution of the durations, in seconds. This is typically the sampling period (1 / sampling_rate), also known as the clock period, of the data acquisition system from which the durations were recorded or derived.
+        %
+        % Output Arguments:
+        %  - durationVectorData (types.core.DurationVectorData) - A DurationVectorData object
+
+        varargin = [{'unit' 'seconds'} varargin];
+        obj = obj@types.hdmf_common.VectorData(varargin{:});
+
+
+        p = inputParser;
+        p.KeepUnmatched = true;
+        p.PartialMatching = false;
+        p.StructExpand = false;
+        addParameter(p, 'resolution',[]);
+        addParameter(p, 'unit',[]);
+        misc.parseSkipInvalidName(p, varargin);
+        obj.resolution = p.Results.resolution;
+        obj.unit = p.Results.unit;
+
+        % Only execute validation/setup code when called directly in this class's
+        % constructor, not when invoked through superclass constructor chain
+        if strcmp(class(obj), 'types.core.DurationVectorData') %#ok<STISA>
+            cellStringArguments = convertContainedStringsToChars(varargin(1:2:end));
+            types.util.checkUnset(obj, unique(cellStringArguments));
+        end
+    end
+    %% SETTERS
+    function set.resolution(obj, val)
+        obj.resolution = obj.validate_resolution(val);
+    end
+    %% VALIDATORS
+
+    function val = validate_data(obj, val)
+        val = types.util.checkDtype('data', 'single', val);
+        types.util.validateShape('data', {[Inf]}, val)
+    end
+    function val = validate_resolution(obj, val)
+        val = types.util.checkDtype('resolution', 'single', val);
+        types.util.validateShape('resolution', {[1]}, val)
+    end
+    %% EXPORT
+    function refs = export(obj, writer, fullpath, refs)
+        refs = export@types.hdmf_common.VectorData(obj, writer, fullpath, refs);
+        if any(strcmp(refs, fullpath))
+            return;
+        end
+        if ~isempty(obj.resolution)
+            writer.writeAttribute([fullpath '/resolution'], obj.resolution);
+        end
+        writer.writeAttribute([fullpath '/unit'], obj.unit);
+    end
+end
+
+end