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-rwxr-xr-xwqflask/wqflask/show_trait/DataEditingPage.py389
1 files changed, 196 insertions, 193 deletions
diff --git a/wqflask/wqflask/show_trait/DataEditingPage.py b/wqflask/wqflask/show_trait/DataEditingPage.py
index bb6156c3..affcd449 100755
--- a/wqflask/wqflask/show_trait/DataEditingPage.py
+++ b/wqflask/wqflask/show_trait/DataEditingPage.py
@@ -185,7 +185,10 @@ class DataEditingPage(templatePage):
# # We'll get this part working later
# print("Calling dispBasicStatistics")
# self.dispBasicStatistics(fd, thisTrait)
- # #self.dispMappingTools(fd, title4Body, thisTrait)
+
+ self.build_correlation_tools(fd, thisTrait)
+
+ # self.dispMappingTools(fd, title4Body, thisTrait)
#############################
## Trait Value Table
@@ -1126,214 +1129,214 @@ class DataEditingPage(templatePage):
#title2Body.append(submitTable)
- def dispCorrelationTools(self, fd, title3Body, thisTrait):
+ def build_correlation_tools(self, fd, thisTrait):
- _Species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=fd.RISet)
+ #species = webqtlDatabaseFunction.retrieveSpecies(cursor=self.cursor, RISet=fd.RISet)
RISetgp = fd.RISet
+
+ # We're checking a string here!
+ assert isinstance(RISetgp, basestring), "We need a string type thing here"
if RISetgp[:3] == 'BXD':
RISetgp = 'BXD'
if RISetgp:
- sample_correlation = HT.Input(type='button',name='sample_corr', value=' Compute ', Class="button sample_corr")
- lit_correlation = HT.Input(type='button',name='lit_corr', value=' Compute ', Class="button lit_corr")
- tissue_correlation = HT.Input(type='button',name='tiss_corr', value=' Compute ', Class="button tiss_corr")
- methodText = HT.Span("Calculate:", Class="ffl fwb fs12")
-
- databaseText = HT.Span("Database:", Class="ffl fwb fs12")
- databaseMenu1 = HT.Select(name='database1')
- databaseMenu2 = HT.Select(name='database2')
- databaseMenu3 = HT.Select(name='database3')
-
- nmenu = 0
- self.cursor.execute('SELECT PublishFreeze.FullName,PublishFreeze.Name FROM \
- PublishFreeze,InbredSet WHERE PublishFreeze.InbredSetId = InbredSet.Id \
- and InbredSet.Name = "%s" and PublishFreeze.public > %d' % \
- (RISetgp,webqtlConfig.PUBLICTHRESH))
+ #sample_correlation = HT.Input(type='button',name='sample_corr', value=' Compute ', Class="button sample_corr")
+ #lit_correlation = HT.Input(type='button',name='lit_corr', value=' Compute ', Class="button lit_corr")
+ #tissue_correlation = HT.Input(type='button',name='tiss_corr', value=' Compute ', Class="button tiss_corr")
+ #methodText = HT.Span("Calculate:", Class="ffl fwb fs12")
+ #
+ #databaseText = HT.Span("Database:", Class="ffl fwb fs12")
+ #databaseMenu1 = HT.Select(name='database1')
+ #databaseMenu2 = HT.Select(name='database2')
+ #databaseMenu3 = HT.Select(name='database3')
+
+ dataset_menu = []
+ print("[tape4] webqtlConfig.PUBLICTHRESH:", webqtlConfig.PUBLICTHRESH)
+ print("[tape4] type webqtlConfig.PUBLICTHRESH:", type(webqtlConfig.PUBLICTHRESH))
+ self.cursor.execute('''SELECT PublishFreeze.FullName,PublishFreeze.Name FROM
+ PublishFreeze,InbredSet WHERE PublishFreeze.InbredSetId = InbredSet.Id
+ and InbredSet.Name = %s and PublishFreeze.public > %s''',
+ (RISetgp, webqtlConfig.PUBLICTHRESH))
for item in self.cursor.fetchall():
- databaseMenu1.append(item)
- databaseMenu2.append(item)
- databaseMenu3.append(item)
- nmenu += 1
- self.cursor.execute('SELECT GenoFreeze.FullName,GenoFreeze.Name FROM GenoFreeze,\
- InbredSet WHERE GenoFreeze.InbredSetId = InbredSet.Id and InbredSet.Name = \
- "%s" and GenoFreeze.public > %d' % (RISetgp,webqtlConfig.PUBLICTHRESH))
+ dataset_menu.append(dict(tissue=None,
+ datasets=item))
+
+ self.cursor.execute('''SELECT GenoFreeze.FullName,GenoFreeze.Name FROM GenoFreeze,
+ InbredSet WHERE GenoFreeze.InbredSetId = InbredSet.Id and InbredSet.Name =
+ %s and GenoFreeze.public > %s''',
+ (RISetgp, webqtlConfig.PUBLICTHRESH))
for item in self.cursor.fetchall():
- databaseMenu1.append(item)
- databaseMenu2.append(item)
- databaseMenu3.append(item)
- nmenu += 1
+ dataset_menu.append(dict(tissue=None,
+ datasets=item))
+
#03/09/2009: Xiaodong changed the SQL query to order by Name as requested by Rob.
self.cursor.execute('SELECT Id, Name FROM Tissue order by Name')
for item in self.cursor.fetchall():
- TId, TName = item
- databaseMenuSub = HT.Optgroup(label = '%s ------' % TName)
- self.cursor.execute('SELECT ProbeSetFreeze.FullName,ProbeSetFreeze.Name FROM ProbeSetFreeze, ProbeFreeze, \
- InbredSet WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeFreeze.TissueId = %d and \
- ProbeSetFreeze.public > %d and ProbeFreeze.InbredSetId = InbredSet.Id and InbredSet.Name like "%s%%" \
- order by ProbeSetFreeze.CreateTime desc, ProbeSetFreeze.AvgId ' % (TId,webqtlConfig.PUBLICTHRESH, RISetgp))
- for item2 in self.cursor.fetchall():
- databaseMenuSub.append(item2)
- nmenu += 1
- databaseMenu1.append(databaseMenuSub)
- databaseMenu2.append(databaseMenuSub)
- databaseMenu3.append(databaseMenuSub)
- if nmenu:
- if thisTrait and thisTrait.db != None:
- databaseMenu1.selected.append(thisTrait.db.fullname)
- databaseMenu2.selected.append(thisTrait.db.fullname)
- databaseMenu3.selected.append(thisTrait.db.fullname)
-
- criteriaText = HT.Span("Return:", Class="ffl fwb fs12")
-
- criteriaMenu1 = HT.Select(name='criteria1', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);")
- criteriaMenu1.append(('top 100','100'))
- criteriaMenu1.append(('top 200','200'))
- criteriaMenu1.append(('top 500','500'))
- criteriaMenu1.append(('top 1000','1000'))
- criteriaMenu1.append(('top 2000','2000'))
- criteriaMenu1.append(('top 5000','5000'))
- criteriaMenu1.append(('top 10000','10000'))
- criteriaMenu1.append(('top 15000','15000'))
- criteriaMenu1.append(('top 20000','20000'))
-
- criteriaMenu2 = HT.Select(name='criteria2', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);")
- criteriaMenu2.append(('top 100','100'))
- criteriaMenu2.append(('top 200','200'))
- criteriaMenu2.append(('top 500','500'))
- criteriaMenu2.append(('top 1000','1000'))
- criteriaMenu2.append(('top 2000','2000'))
- criteriaMenu2.append(('top 5000','5000'))
- criteriaMenu2.append(('top 10000','10000'))
- criteriaMenu2.append(('top 15000','15000'))
- criteriaMenu2.append(('top 20000','20000'))
-
- criteriaMenu3 = HT.Select(name='criteria3', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);")
- criteriaMenu3.append(('top 100','100'))
- criteriaMenu3.append(('top 200','200'))
- criteriaMenu3.append(('top 500','500'))
- criteriaMenu3.append(('top 1000','1000'))
- criteriaMenu3.append(('top 2000','2000'))
- criteriaMenu3.append(('top 5000','5000'))
- criteriaMenu3.append(('top 10000','10000'))
- criteriaMenu3.append(('top 15000','15000'))
- criteriaMenu3.append(('top 20000','20000'))
-
-
- self.MDPRow1 = HT.TR(Class='mdp1')
- self.MDPRow2 = HT.TR(Class='mdp2')
- self.MDPRow3 = HT.TR(Class='mdp3')
-
- correlationMenus1 = HT.TableLite(
- HT.TR(HT.TD(databaseText), HT.TD(databaseMenu1, colspan="3")),
- HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu1)),
- self.MDPRow1, cellspacing=0, width="619px", cellpadding=2)
- correlationMenus1.append(HT.Input(name='orderBy', value='2', type='hidden')) # to replace the orderBy menu
- correlationMenus2 = HT.TableLite(
- HT.TR(HT.TD(databaseText), HT.TD(databaseMenu2, colspan="3")),
- HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu2)),
- self.MDPRow2, cellspacing=0, width="619px", cellpadding=2)
- correlationMenus2.append(HT.Input(name='orderBy', value='2', type='hidden'))
- correlationMenus3 = HT.TableLite(
- HT.TR(HT.TD(databaseText), HT.TD(databaseMenu3, colspan="3")),
- HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu3)),
- self.MDPRow3, cellspacing=0, width="619px", cellpadding=2)
- correlationMenus3.append(HT.Input(name='orderBy', value='2', type='hidden'))
+ tissue_id, tissue_name = item
+ #databaseMenuSub = HT.Optgroup(label = '%s ------' % tissue_name)
+ #dataset_sub_menu = []
+ print("phun9")
+ self.cursor.execute('''SELECT ProbeSetFreeze.FullName,ProbeSetFreeze.Name FROM ProbeSetFreeze, ProbeFreeze,
+ InbredSet WHERE ProbeSetFreeze.ProbeFreezeId = ProbeFreeze.Id and ProbeFreeze.TissueId = %s and
+ ProbeSetFreeze.public > %s and ProbeFreeze.InbredSetId = InbredSet.Id and InbredSet.Name like %s
+ order by ProbeSetFreeze.CreateTime desc, ProbeSetFreeze.AvgId ''',
+ (tissue_id, webqtlConfig.PUBLICTHRESH, "%" + RISetgp + "%"))
+ print("phun8")
+ dataset_sub_menu = [item for item in self.cursor.fetchall() if item]
+ #for item2 in self.cursor.fetchall():
+ # dataset_sub_menu.append(item2)
+ if dataset_sub_menu:
+ dataset_menu.append(dict(tissue=tissue_name,
+ datasets=dataset_sub_menu))
+ # ("**heading**", tissue_name))
+ #dataset_menu.append(dataset_sub_menu)
+
+ dataset_menu_selected = None
+ if len(dataset_menu):
+ if thisTrait and thisTrait.db:
+ dataset_menu_selected = thisTrait.db.fullname
- else:
- correlationMenus = ""
+ #criteriaText = HT.Span("Return:", Class="ffl fwb fs12")
+ #criteriaMenu1 = HT.Select(name='criteria1', selected='500', onMouseOver="if (NS4 || IE4) activateEl('criterias', event);")
+
+ return_results_menu = []
+
+ for counter in (100, 200, 500, 1000, 2000, 5000, 10000, 15000, 20000):
+ return_results_menu.append(('top %s' % (counter,), str(counter)))
+
+ #criteriaMenu1.append(('top 100','100'))
+ #criteriaMenu1.append(('top 200','200'))
+ #criteriaMenu1.append(('top 500','500'))
+ #criteriaMenu1.append(('top 1000','1000'))
+ #criteriaMenu1.append(('top 2000','2000'))
+ #criteriaMenu1.append(('top 5000','5000'))
+ #criteriaMenu1.append(('top 10000','10000'))
+ #criteriaMenu1.append(('top 15000','15000'))
+ #criteriaMenu1.append(('top 20000','20000'))
+
+ #self.MDPRow1 = HT.TR(Class='mdp1')
+ #self.MDPRow2 = HT.TR(Class='mdp2')
+ #self.MDPRow3 = HT.TR(Class='mdp3')
+
+ # correlationMenus1 = HT.TableLite(
+ # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu1, colspan="3")),
+ # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu1)),
+ # self.MDPRow1, cellspacing=0, width="619px", cellpadding=2)
+ # correlationMenus1.append(HT.Input(name='orderBy', value='2', type='hidden')) # to replace the orderBy menu
+ # correlationMenus2 = HT.TableLite(
+ # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu2, colspan="3")),
+ # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu2)),
+ # self.MDPRow2, cellspacing=0, width="619px", cellpadding=2)
+ # correlationMenus2.append(HT.Input(name='orderBy', value='2', type='hidden'))
+ # correlationMenus3 = HT.TableLite(
+ # HT.TR(HT.TD(databaseText), HT.TD(databaseMenu3, colspan="3")),
+ # HT.TR(HT.TD(criteriaText), HT.TD(criteriaMenu3)),
+ # self.MDPRow3, cellspacing=0, width="619px", cellpadding=2)
+ # correlationMenus3.append(HT.Input(name='orderBy', value='2', type='hidden'))
+ #
+ #else:
+ # correlationMenus = ""
- corr_row = HT.TR()
- corr_container = HT.Div(id="corr_tabs", Class="ui-tabs")
- if (thisTrait.db != None and thisTrait.db.type =='ProbeSet'):
- corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1"), HT.Href(text='Literature r', url="#corrtabs-2"), HT.Href(text='Tissue r', url="#corrtabs-3")]
- else:
- corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1")]
-
- corr_tabs = HT.List(corr_tab_list)
- corr_container.append(corr_tabs)
-
- if correlationMenus1 or correlationMenus2 or correlationMenus3:
- sample_div = HT.Div(id="corrtabs-1")
- sample_container = HT.Span()
-
- sample_type = HT.Input(type="radio", name="sample_method", value="1", checked="checked")
- sample_type2 = HT.Input(type="radio", name="sample_method", value="2")
-
- sampleTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
- sampleTD = HT.TD(correlationMenus1, HT.BR(),
- "Pearson", sample_type, " "*3, "Spearman Rank", sample_type2, HT.BR(), HT.BR(),
- sample_correlation, HT.BR(), HT.BR())
-
- sampleTD.append(HT.Span("The ",HT.Href(url="/correlationAnnotation.html#sample_r", target="_blank", text="Sample Correlation")," is computed between trait data and",
- " any ",HT.BR()," other traits in the sample database selected above. Use ",
- HT.Href(url="/glossary.html#Correlations", target="_blank", text="Spearman Rank"),
- HT.BR(),"when the sample size is small (<20) or when there are influential \
- outliers.", HT.BR(),Class="fs12"))
-
- sampleTable.append(sampleTD)
-
- sample_container.append(sampleTable)
- sample_div.append(sample_container)
- corr_container.append(sample_div)
-
- literature_div = HT.Div(id="corrtabs-2")
- literature_container = HT.Span()
-
- literatureTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
- literatureTD = HT.TD(correlationMenus2,HT.BR(),lit_correlation, HT.BR(), HT.BR())
- literatureTD.append(HT.Span("The ", HT.Href(url="/correlationAnnotation.html", target="_blank",text="Literature Correlation"), " (Lit r) between this gene and all other genes is computed",HT.BR(),
- "using the ", HT.Href(url="https://grits.eecs.utk.edu/sgo/sgo.html", target="_blank", text="Semantic Gene Organizer"),
- " and human, rat, and mouse data from PubMed. ", HT.BR(),"Values are ranked by Lit r, \
- but Sample r and Tissue r are also displayed.", HT.BR(), HT.BR(),
- HT.Href(url="/glossary.html#Literature", target="_blank", text="More on using Lit r"), Class="fs12"))
- literatureTable.append(literatureTD)
-
- literature_container.append(literatureTable)
- literature_div.append(literature_container)
-
- if thisTrait.db != None:
- if (thisTrait.db.type =='ProbeSet'):
- corr_container.append(literature_div)
-
- tissue_div = HT.Div(id="corrtabs-3")
- tissue_container = HT.Span()
-
- tissue_type = HT.Input(type="radio", name="tissue_method", value="4", checked="checked")
- tissue_type2 = HT.Input(type="radio", name="tissue_method", value="5")
-
- tissueTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
- tissueTD = HT.TD(correlationMenus3,HT.BR(),
- "Pearson", tissue_type, "&nbsp;"*3, "Spearman Rank", tissue_type2, HT.BR(), HT.BR(),
- tissue_correlation, HT.BR(), HT.BR())
- tissueTD.append(HT.Span("The ", HT.Href(url="/webqtl/main.py?FormID=tissueCorrelation", target="_blank", text="Tissue Correlation"),
- " (Tissue r) estimates the similarity of expression of two genes",HT.BR()," or \
- transcripts across different cells, tissues, or organs (",HT.Href(url="/correlationAnnotation.html#tissue_r", target="_blank", text="glossary"),"). \
- Tissue correlations",HT.BR()," are generated by analyzing expression in multiple samples usually taken from \
- single cases.",HT.BR(),HT.Bold("Pearson")," and ",HT.Bold("Spearman Rank")," correlations have been computed for all pairs \
- of genes",HT.BR()," using data from mouse samples.",
- HT.BR(), Class="fs12"))
- tissueTable.append(tissueTD)
-
- tissue_container.append(tissueTable)
- tissue_div.append(tissue_container)
- if thisTrait.db != None:
- if (thisTrait.db.type =='ProbeSet'):
- corr_container.append(tissue_div)
-
- corr_row.append(HT.TD(corr_container))
-
- corr_script = HT.Script(language="Javascript")
- corr_script_text = """$(function() { $("#corr_tabs").tabs(); });"""
- corr_script.append(corr_script_text)
-
- submitTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%", Class="target4")
- submitTable.append(corr_row)
- submitTable.append(corr_script)
-
- title3Body.append(submitTable)
+ #corr_row = HT.TR()
+ #corr_container = HT.Div(id="corr_tabs", Class="ui-tabs")
+ #
+ #if (thisTrait.db != None and thisTrait.db.type =='ProbeSet'):
+ # corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1"),
+ # HT.Href(text='Literature r', url="#corrtabs-2"),
+ # HT.Href(text='Tissue r', url="#corrtabs-3")]
+ #else:
+ # corr_tab_list = [HT.Href(text='Sample r', url="#corrtabs-1")]
+ #
+ #corr_tabs = HT.List(corr_tab_list)
+ #corr_container.append(corr_tabs)
+
+ #if correlationMenus1 or correlationMenus2 or correlationMenus3:
+ #sample_div = HT.Div(id="corrtabs-1")
+ #sample_container = HT.Span()
+ #
+ #sample_type = HT.Input(type="radio", name="sample_method", value="1", checked="checked")
+ #sample_type2 = HT.Input(type="radio", name="sample_method", value="2")
+ #
+ #sampleTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
+ #sampleTD = HT.TD(correlationMenus1, HT.BR(),
+ # "Pearson", sample_type, "&nbsp;"*3, "Spearman Rank", sample_type2, HT.BR(), HT.BR(),
+ # sample_correlation, HT.BR(), HT.BR())
+ #
+ #sampleTD.append(HT.Span("The ",
+ # HT.Href(url="/correlationAnnotation.html#sample_r", target="_blank",
+ # text="Sample Correlation")," is computed between trait data and",
+ # " any ",HT.BR()," other traits in the sample database selected above. Use ",
+ # HT.Href(url="/glossary.html#Correlations", target="_blank", text="Spearman Rank"),
+ # HT.BR(),"when the sample size is small (<20) or when there are influential \
+ # outliers.", HT.BR(),Class="fs12"))
+
+ #sampleTable.append(sampleTD)
+
+ #sample_container.append(sampleTable)
+ #sample_div.append(sample_container)
+ #corr_container.append(sample_div)
+ #
+ #literature_div = HT.Div(id="corrtabs-2")
+ #literature_container = HT.Span()
+
+ #literatureTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
+ #literatureTD = HT.TD(correlationMenus2,HT.BR(),lit_correlation, HT.BR(), HT.BR())
+ #literatureTD.append(HT.Span("The ", HT.Href(url="/correlationAnnotation.html", target="_blank",text="Literature Correlation"), " (Lit r) between this gene and all other genes is computed",HT.BR(),
+ # "using the ", HT.Href(url="https://grits.eecs.utk.edu/sgo/sgo.html", target="_blank", text="Semantic Gene Organizer"),
+ # " and human, rat, and mouse data from PubMed. ", HT.BR(),"Values are ranked by Lit r, \
+ # but Sample r and Tissue r are also displayed.", HT.BR(), HT.BR(),
+ # HT.Href(url="/glossary.html#Literature", target="_blank", text="More on using Lit r"), Class="fs12"))
+ #literatureTable.append(literatureTD)
+ #
+ #literature_container.append(literatureTable)
+ #literature_div.append(literature_container)
+ #
+ #if thisTrait.db != None:
+ # if (thisTrait.db.type =='ProbeSet'):
+ # corr_container.append(literature_div)
+ #
+ #tissue_div = HT.Div(id="corrtabs-3")
+ #tissue_container = HT.Span()
+ #
+ #tissue_type = HT.Input(type="radio", name="tissue_method", value="4", checked="checked")
+ #tissue_type2 = HT.Input(type="radio", name="tissue_method", value="5")
+ #
+ #tissueTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%")
+ #tissueTD = HT.TD(correlationMenus3,HT.BR(),
+ # "Pearson", tissue_type, "&nbsp;"*3, "Spearman Rank", tissue_type2, HT.BR(), HT.BR(),
+ # tissue_correlation, HT.BR(), HT.BR())
+ #tissueTD.append(HT.Span("The ", HT.Href(url="/webqtl/main.py?FormID=tissueCorrelation", target="_blank", text="Tissue Correlation"),
+ #" (Tissue r) estimates the similarity of expression of two genes",HT.BR()," or \
+ #transcripts across different cells, tissues, or organs (",HT.Href(url="/correlationAnnotation.html#tissue_r", target="_blank", text="glossary"),"). \
+ #Tissue correlations",HT.BR()," are generated by analyzing expression in multiple samples usually taken from \
+ #single cases.",HT.BR(),HT.Bold("Pearson")," and ",HT.Bold("Spearman Rank")," correlations have been computed for all pairs \
+ #of genes",HT.BR()," using data from mouse samples.",
+ #HT.BR(), Class="fs12"))
+ #tissueTable.append(tissueTD)
+ #
+ #tissue_container.append(tissueTable)
+ #tissue_div.append(tissue_container)
+ #if thisTrait.db != None:
+ # if (thisTrait.db.type =='ProbeSet'):
+ # corr_container.append(tissue_div)
+ #
+ #corr_row.append(HT.TD(corr_container))
+ #
+ #corr_script = HT.Script(language="Javascript")
+ #corr_script_text = """$(function() { $("#corr_tabs").tabs(); });"""
+ #corr_script.append(corr_script_text)
+ #
+ #submitTable = HT.TableLite(cellspacing=0, cellpadding=0, width="100%", Class="target4")
+ #submitTable.append(corr_row)
+ #submitTable.append(corr_script)
+ #
+ #title3Body.append(submitTable)
+ self.correlation_tools = dict(dataset_menu = dataset_menu,
+ dataset_menu_selected = dataset_menu_selected,
+ return_results_menu = return_results_menu)
def dispMappingTools(self, fd, title4Body, thisTrait):