[codex] Promote specialized attributes of included typed datasets

+file/Attribute.m

@@ -8,6 +8,7 @@
         dtype; %type of value
         dependent; %set externally.  If the attribute is actually dependent on an untyped dataset/group
         dependent_fullname; %set externally. This is the full name, including names of potential parent groups separated by underscore. A value will only be present if it would differ from dependent.
+        promoted_to_container = false; % set externally when promoted from a typed dataset onto the containing class API
         scalar; %if the value is scalar or an array
         dimnames;
         shape;
@@ -25,6 +26,7 @@
             obj.dtype = '';
             obj.dependent = '';
             obj.dependent_fullname = '';
+            obj.promoted_to_container = false;
             obj.scalar = true;
             obj.shape = {};
             obj.dimnames = {};

+file/Group.m

@@ -161,7 +161,14 @@
                         PropertyMap = [PropertyMap; Sub_Attribute_Map];
                     end
                     PropertyMap(SubData.name) = SubData;
-                else
+                else % Typed dataset
+                    includedAttributes = getIncludedTypedDatasetAttributes(obj, SubData);
+                    if ~isempty(includedAttributes)
+                        attrNames = {includedAttributes.name};
+                        attrNames = strcat(SubData.name, '_', attrNames);
+                        PropertyMap = [PropertyMap; ...
+                            containers.Map(attrNames, num2cell(includedAttributes))];
+                    end
                     if isempty(SubData.name)
                         PropertyMap(lower(SubData.type)) = SubData;
                     else
@@ -253,3 +260,26 @@
         end
     end
 end
+
+function includedAttributes = getIncludedTypedDatasetAttributes(GroupObj, datasetObj)
+% getIncludedTypedDatasetAttributes - Return attributes declared on a named
+% included typed dataset instance.
+%
+% This is used for reuse by inclusion (`neurodata_type_inc` without
+% `neurodata_type_def`), where an existing typed dataset is embedded as a
+% named component of another type. Promotion decisions are resolved later,
+% once namespace context is available, so we can distinguish newly added
+% attributes from modifications of attributes already defined on the
+% included dataset type.
+
+    includedAttributes = file.Attribute.empty;
+    if isempty(GroupObj.type) || isempty(datasetObj.name) || isempty(datasetObj.attributes)
+        return;
+    end
+
+    for iAttr = 1:length(datasetObj.attributes)
+        attribute = datasetObj.attributes(iAttr);
+        attribute.dependent = datasetObj.name;
+        includedAttributes(end+1) = attribute; %#ok<AGROW>
+    end
+end

+file/fillClass.m

@@ -12,6 +12,7 @@
     defaults = {};
     dependent = {};
     hidden = {}; % special hidden properties for hard-coded workarounds
+
     %separate into readonly, required, and optional properties
     for iGroup = 1:length(allProperties)
         propertyName = allProperties{iGroup};
@@ -165,7 +166,7 @@
         inherited);
     setterFcns = file.fillSetters(setdiff(nonInherited, union(readonly, hiddenAndReadonly)), classprops);
     validatorFcns = file.fillValidators(allProperties, classprops, namespace, namespace.getFullClassName(name), inherited);
-    exporterFcns = file.fillExport(nonInherited, class, superclassNames{1}, required);
+    exporterFcns = file.fillExport(nonInherited, class, superclassNames{1}, required, classprops);
     methodBody = strjoin({constructorBody...
         '%% SETTERS' setterFcns...
         '%% VALIDATORS' validatorFcns...

+file/fillExport.m

@@ -1,4 +1,4 @@
-function festr = fillExport(propertyNames, RawClass, parentName, required)
+function festr = fillExport(propertyNames, RawClass, parentName, required, classprops)
     exportHeader = 'function refs = export(obj, fid, fullpath, refs)';
     if isa(RawClass, 'file.Dataset')
         propertyNames = propertyNames(~strcmp(propertyNames, 'data'));
@@ -22,6 +22,11 @@
         propertyName = propertyNames{i};
         pathProps = traverseRaw(propertyName, RawClass);
         prop = pathProps{end};
+        if nargin >= 5 && isa(prop, 'file.Attribute') ...
+                && isKey(classprops, propertyName) ...
+                && isa(classprops(propertyName), 'file.Attribute')
+            prop = classprops(propertyName);
+        end
         elideProps = pathProps(1:end-1);
         elisions = cell(length(elideProps),1);
         % Construct elisions
@@ -222,6 +227,7 @@
 
     propertyChecks = {};
     dependencyCheck = {};
+    preExportString = '';
 
     if isa(prop, 'file.Attribute') && ~isempty(prop.dependent)
         %if attribute is dependent, check before writing
@@ -254,6 +260,13 @@
             warnIfMissingRequiredDependentAttributeStr = ...
                 sprintf('obj.throwErrorIfRequiredDependencyMissing(''%s'', ''%s'', fullpath)', name, depPropname);
         end
+
+        if prop.promoted_to_container
+            preExportString = sprintf([ ...
+                'if isempty(obj.%1$s) && ~isempty(obj.%2$s) && isobject(obj.%2$s) && isprop(obj.%2$s, ''%3$s'') && ~isempty(obj.%2$s.%3$s)\n' ...
+                '    obj.%1$s = obj.%2$s.%3$s;\n' ...
+                'end'], name, depPropname, prop.name);
+        end
     end
 
     if ~prop.required
@@ -273,6 +286,10 @@
         end
     end
 
+    if ~isempty(preExportString)
+        dataExportString = sprintf('%s\n%s', preExportString, dataExportString);
+    end
+
     if ~isempty(dependencyCheck)
         dataExportString = sprintf('%s\nif %s\n%s\nend', ...
             dataExportString, ...

+file/fillSetters.m

@@ -43,13 +43,29 @@
             warnIfDependencyMissingString = sprintf(...
                 'obj.warnIfAttributeDependencyMissing(''%s'', ''%s'')', ...
                 propname, parentname);
+
+            syncPromotedDatasetAttributeString = '';
+            if prop.promoted_to_container
+                syncPromotedDatasetAttributeString = sprintf([ ...
+                    'if ~isempty(obj.%1$s) && isobject(obj.%1$s) && isprop(obj.%1$s, ''%2$s'')\n' ...
+                    '    if ~isempty(obj.%3$s)\n' ...
+                    '        obj.%1$s.%2$s = obj.%3$s;\n' ...
+                    '    elseif ~isempty(obj.%1$s.%2$s)\n' ...
+                    '        obj.%3$s = obj.%1$s.%2$s;\n' ...
+                    '    end\n' ...
+                    'end'], parentname, prop.name, propname);
+            end
 
-            postsetFunctionStr = strjoin({...
+            postsetLines = {...
                 sprintf('function postset_%s(obj)', propname), ...
                 file.addSpaces(conditionStr, 4), ...
                 file.addSpaces(warnIfDependencyMissingString, 8), ...
                 file.addSpaces('end', 4), ...
-                'end'}, newline);
+                'end'};
+            if ~isempty(syncPromotedDatasetAttributeString)
+                postsetLines = [postsetLines(1:end-1), {file.addSpaces(syncPromotedDatasetAttributeString, 4)}, postsetLines(end)];
+            end
+            postsetFunctionStr = strjoin(postsetLines, newline);
         end
     end
 end

+file/processClass.m

@@ -32,6 +32,7 @@
                 class = patchVectorData(class);
             end
             props = class.getProps();
+            props = markPromotedAttributesForIncludedTypedDatasets(class, props, namespace);
 
             % Apply patches for special cases of schema/specification errors
             class = applySchemaVersionPatches(nodename, class, props, namespace);
@@ -53,6 +54,81 @@
     end
 end
 
+function props = markPromotedAttributesForIncludedTypedDatasets(classObj, props, namespace)
+    if ~isa(classObj, 'file.Group') || isempty(classObj.datasets)
+        return;
+    end
+
+    for iDataset = 1:length(classObj.datasets)
+        datasetObj = classObj.datasets(iDataset);
+        if isempty(datasetObj.type) || isempty(datasetObj.name) || isempty(datasetObj.attributes)
+            continue;
+        end
+
+        datasetNamespace = namespace.getNamespace(datasetObj.type);
+        if isempty(datasetNamespace)
+            continue;
+        end
+
+        schemaAttributeNames = getSchemaDefinedAttributeNames(datasetObj.type, datasetNamespace);
+        for iAttr = 1:length(datasetObj.attributes)
+            attribute = datasetObj.attributes(iAttr);
+            propertyName = [datasetObj.name '_' attribute.name];
+            if ~isKey(props, propertyName)
+                continue;
+            end
+
+            if any(strcmp(attribute.name, schemaAttributeNames))
+                remove(props, propertyName);
+            else
+                promotedAttribute = props(propertyName);
+                promotedAttribute.promoted_to_container = true;
+                props(propertyName) = promotedAttribute;
+            end
+        end
+    end
+end
+
+function attributeNames = getSchemaDefinedAttributeNames(typeName, namespace)
+    persistent schemaAttributeNameCache
+
+    if isempty(schemaAttributeNameCache)
+        schemaAttributeNameCache = containers.Map('KeyType', 'char', 'ValueType', 'any');
+    end
+
+    cacheKey = strjoin({namespace.name, namespace.version, typeName}, '::');
+    if isKey(schemaAttributeNameCache, cacheKey)
+        attributeNames = schemaAttributeNameCache(cacheKey);
+        return;
+    end
+
+    typeSpec = namespace.getClass(typeName);
+    if isempty(typeSpec)
+        attributeNames = {};
+        return;
+    end
+
+    branch = [{typeSpec} namespace.getRootBranch(typeName)];
+    spec.internal.resolveInheritedFields(typeSpec, branch(2:end))
+    spec.internal.expandFieldsInheritedByInclusion(typeSpec)
+
+    switch typeSpec('class_type')
+        case 'groups'
+            classObj = file.Group(typeSpec);
+        case 'datasets'
+            classObj = file.Dataset(typeSpec);
+        otherwise
+            attributeNames = {};
+            return;
+    end
+
+    typeProps = classObj.getProps();
+    propNames = keys(typeProps);
+    isAttribute = cellfun(@(name) isa(typeProps(name), 'file.Attribute'), propNames);
+    attributeNames = propNames(isAttribute);
+    schemaAttributeNameCache(cacheKey) = attributeNames;
+end
+
 function class = patchVectorData(class)
     %% Unit Attribute
     % derived from schema 2.6.0
@@ -95,4 +171,4 @@
     source('required') = false;
 
     class.attributes(end+1) = file.Attribute(source);
-end
+end

+tests/+system/UnitTimesIOTest.m

@@ -1,4 +1,4 @@
 classdef UnitTimesIOTest < tests.system.PyNWBIOTest
     methods
         function addContainer(~, file)
             file.units = types.core.Units( ...
@@ -40,17 +40,34 @@
                 , 'data', 1 ...
                 );
 
-            % set optional hidden vector data attributes
-            file.units.spike_times.resolution = 3;
+            % set optional Units table dataset attributes via promoted container API
+            file.units.spike_times_resolution = 3;
             Units = file.units;
-            [Units.waveform_mean.sampling_rate ...
-                , Units.waveform_sd.sampling_rate ...
-                , Units.waveforms.sampling_rate ... 
+            [Units.waveform_mean_sampling_rate ...
+                , Units.waveform_sd_sampling_rate ...
+                , Units.waveforms_sampling_rate ...
                 ] = deal(1);
         end
 
         function c = getContainer(~, file)
             c = file.units;
         end
     end
-end
+
+    methods (Test)
+        function testLegacyNestedSpikeTimesResolutionIsPreserved(testCase)
+            spikeTimes = types.hdmf_common.VectorData( ...
+                'data', 11, ...
+                'description', 'the spike times for each unit in seconds');
+            spikeTimes.resolution = 1/20000;
+
+            units = types.core.Units( ...
+                'colnames', {'spike_times'}, ...
+                'description', 'data on spiking units', ...
+                'spike_times', spikeTimes);
+
+            testCase.verifyEqual(units.spike_times.resolution, 1/20000);
+            testCase.verifyEqual(units.spike_times_resolution, 1/20000);
+        end
+    end
+end