def col_defs(self): res = [ SampleIdCol(self, 'sample', model_col=common.Value.id), Col(self, 'artefact', model_col=models.Sample.artefact_id), ] if not self.parameter: res.append( CategoryCol(self, 'type', choices=get_distinct_values( common.DomainElement.name), model_col=common.DomainElement.name)) if self.parameter: res.append( LinkCol(self, 'contribution', get_object=lambda v: v.valueset.contribution)) if self.contribution: pass if not self.language: res.extend([ RegionCol(self, 'region', choices=get_distinct_values(models.Location.region)), SubRegionCol(self, 'subregion'), Col(self, 'site', model_col=models.Sample.site_name, choices=get_distinct_values(models.Sample.site_name)), ]) return res
def col_defs(self): return [ IntegerIdCol(self, 'number'), LinkCol(self, 'name'), Col( self, 'canton', sTitle='Canton', model_col=models.Variety.canton, choices=get_distinct_values(models.Variety.canton), ), Col( self, 'group', sTitle='Dialect group', model_col=models.Variety.group, choices=get_distinct_values(models.Variety.group), ), #Col(self, 'population', model_col=models.Variety.population), Col(self, 'recorded', model_col=models.Variety.recorded, sTitle='Date of recording'), Col(self, 'latitude', sDescription='<small>The geographic latitude</small>'), Col(self, 'longitude', sDescription='<small>The geographic longitude</small>'), LinkToMapCol(self, 'm'), ]
def col_defs(self): return [ IntegerIdCol(self, 'id'), LinkCol(self, 'name', sTitle='Language structure dataset'), ContributorsCol(self, 'contributors', bSearchable=False, bSortable=False, sTitle='Authors of dataset'), Col(self, 'lexifier', choices=get_distinct_values(Lect.lexifier, key=lambda v: 'z' + v if v == 'Other' else v), get_obj=lambda item: item.language, model_col=Lect.lexifier), Col(self, 'region', choices=get_distinct_values(Lect.region), get_obj=lambda item: item.language, model_col=Lect.region), CitationCol(self, 'cite', bSearchable=False, bSortable=False), IntegerIdCol(self, 'survey', get_object=lambda c: c.language.survey, bSearchable=False, bSortable=False, sTitle='Survey'), ]
def col_defs(self): return [ LinkCol(self, 'name'), LinkToMapCol(self, '#'), Col(self, 'region', model_col=Sample.region, choices=get_distinct_values(Sample.region)), Col(self, 'location', model_col=Sample.location), Col(self, 'latitude', input_size='mini', sDescription='<small>The geographic latitude</small>'), Col(self, 'longitude', input_size='mini', sDescription='<small>The geographic longitude</small>'), Col(self, 'samplesize', input_size='mini', model_col=Sample.samplesize), LangCol(self, 'languoid', get_object=lambda i: i.languoid, model_col=Languoid.name), FamilyCol(self, 'family', get_object=lambda i: i.languoid, model_col=Languoid.family_name, choices=get_distinct_values(Languoid.family_name)), ]
def col_defs(self): return [ LinkCol(self, 'name'), Col(self, 'experiments', model_col=models.Species.count_experiments, input_size='mini'), GBIFLinkCol(self, 'gbif', sTitle='GBIF', model_col=models.Species.gbif_name), Col(self, 'class', model_col=models.Species.klass, choices=get_distinct_values(models.Species.klass)), Col(self, 'order', model_col=models.Species.order, choices=get_distinct_values(models.Species.order)), Col(self, 'family', model_col=models.Species.family, choices=get_distinct_values(models.Species.family)), Col(self, 'genus', model_col=models.Species.genus, choices=get_distinct_values(models.Species.genus)), ]
def col_defs(self): res = Sentences.col_defs(self) return [ res[1], res[4], LocationCol(self, 'settlement', choices=get_distinct_values(CounterpartExample.location)), RefsCol(self, 'source', choices=get_distinct_values(common.Source.name)), res[6]]
def col_defs(self): return [ OrderNumberCol(self, 'id'), LinkCol(self, 'name', sTitle='Language'), ContributorsCol(self, 'contributors', bSearchable=False, bSortable=False), LexifierCol(self, 'lexifier', choices=get_distinct_values( Lect.lexifier, key=lambda v: 'z' + v if v == 'Other' else v)), RegionCol(self, 'region', choices=get_distinct_values(Lect.region)), CitationCol(self, 'cite', bSearchable=False, bSortable=False), ]
def col_defs(self): return [ DetailsRowLinkCol(self, '#'), WordCol(self, 'name'), Col(self, 'pos', model_col=Entry.pos, choices=get_distinct_values(Entry.pos)), Col(self, 'aspect', model_col=Entry.aspect, choices=get_distinct_values(Entry.aspect)), Col(self, 'donor', sTitle='loan from', model_col=Entry.donor, choices=get_distinct_values(Entry.donor)), Col(self, 'dialect', model_col=Entry.dialect, choices=get_distinct_values(Entry.dialect)), Col(self, 'english', model_col=Entry.english), Col(self, 'german', model_col=Entry.german), Col(self, 'russian', model_col=Entry.russian), ]
def col_defs(self): return [ WordCol(self, 'name'), VariantCol(self, 'variant'), Col(self, 'pos', model_col=Entry.pos, choices=get_distinct_values(Entry.pos)), Col(self, 'aspect', model_col=Entry.aspect, choices=get_distinct_values(Entry.aspect)), Col(self, 'plural', model_col=Entry.plural, choices=get_distinct_values(Entry.plural)), Col(self, 'donor', sTitle='loan from', model_col=Entry.donor, choices=get_distinct_values(Entry.donor)), DialectCol( self, 'variety', model_col=common.Language.name, choices=[(l.id, l.name) for l in DBSession.query(common.Language)]), ]
def col_defs(self): return [ DetailsRowLinkCol(self, '#'), WordCol( self, 'form', get_obj=lambda i: i.unit, model_col=common.Unit.name), VariantCol(self, 'variant', get_object=lambda u: u.unit), Col( self, 'english', get_obj=lambda i: i.unitparameter, model_col=common.UnitParameter.name), Col( self, 'russian', get_obj=lambda i: i.unitparameter, model_col=Meaning.russian), Col(self, 'pos', get_object=lambda u: u.unit, model_col=Entry.pos), Col(self, 'aspect', get_object=lambda u: u.unit, model_col=Entry.aspect), Col(self, 'plural', get_object=lambda u: u.unit, model_col=Entry.plural), Col( self, 'donor', choices=get_distinct_values(Entry.donor), get_object=lambda u: u.unit, model_col=Entry.donor), DialectCol( self, 'variety', get_object=lambda u: u.unit.language, choices=[(l.id, l.name) for l in DBSession.query(common.Language)]), ]
def col_defs(self): return [ IntegerIdCol(self, 'id'), LinkCol(self, 'name', sTitle='Language'), ContributorsCol(self, 'contributors', bSearchable=False, bSortable=False), Col(self, 'lexifier', choices=get_distinct_values( Lect.lexifier, key=lambda v: 'z' + v if v == 'Other' else v), get_obj=lambda item: item.language, model_col=Lect.lexifier), Col(self, 'region', choices=get_distinct_values(Lect.region), get_obj=lambda item: item.language, model_col=Lect.region), CitationCol(self, 'cite', bSearchable=False, bSortable=False), ]
def col_defs(self): er_col = EcoregionCol(self, 'ecoregions', bSortable=False) if 'er' in self.req.params: er_col.js_args['sFilter'] = self.req.params['er'] res = [ LinkCol(self, 'name', sTitle='Species'), Col(self, 'description', sTitle='English name'), ClassificationCol(self, 'order', sTitle='Biological classification'), ThumbnailCol(self, 'thumbnail'), # TODO: second thumbnail? ] if self.languages: for i, lang in enumerate(self.languages): res.append(CommonNameCol(self, 'cn%s' % i, lang, self._langs[i])) res.append(CategoryCol(self, 'categories', self.languages, bSortable=False)) res.extend([ er_col, Col(self, 'countries', model_col=Species.countries_str, choices=get_distinct_values(Country.name), bSortable=False)]) # TODO: characteristics col? return res
def col_defs(self): if self.parameter: return [ LinkCol(self, 'sample', model_col=Sample.name, get_object=lambda i: i.valueset.language), Col(self, 'region', model_col=Sample.region, get_object=lambda i: i.valueset.language, format=lambda i: i.valueset.language.region), FamilyCol(self, 'family', get_object=lambda i: i.valueset.language.languoid, model_col=Languoid.family_name, choices=get_distinct_values(Languoid.family_name)), Col(self, 'value', model_col=Measurement.value), LinkToMapCol(self, '#', get_object=lambda i: i.valueset.language), ] if self.language: return [ LinkCol(self, 'measure', model_col=Parameter.name, get_object=lambda i: i.valueset.parameter), Col(self, 'description', get_object=lambda i: i.valueset.parameter, model_col=Parameter.description), Col(self, 'value', model_col=Measurement.value), ] return Values.col_defs(self)
def col_defs(self): cols = Sources.col_defs(self) provider = LinkCol(self, 'provider', choices=get_distinct_values(Provider.name), model_col=Provider.name, get_object=lambda i: i.provider) return cols[:-1] + [provider]
def col_defs(self): return [ LinkCol(self, 'name'), Col(self, 'sound_type', model_col=Feature.sound_type, choices=get_distinct_values(Feature.sound_type)), Col(self, 'feature', model_col=Feature.feature, choices=get_distinct_values(Feature.feature)), Col(self, 'value', sTitle='Value', model_col=Feature.value), Col(self, 'sounds', sTitle='# sounds', model_col=Feature.count_sounds), ]
def col_defs(self): return [ DetailsRowLinkCol(self, 'more'), LinkCol(self, 'name', sTitle='Lemma'), SemanticDomainCol(self, 'semantic_domain'), Col(self, 'part_of_speech', choices=get_distinct_values(Entry.ps), model_col=Entry.ps), ]
def col_defs(self): ps = Col(self, 'prosodic_structure', sTitle='Prosodic structure', model_col=models.Form.prosodic_structure) if self.parameter: ps.choices = sorted((c for c, in DBSession.query( models.Form.prosodic_structure).join(common.ValueSet).filter( common.ValueSet.parameter == self.parameter).distinct() if c), key=lambda s: (len(s), s)) res = [ Col(self, 'description', sTitle='TPPSR form', sClass="object-language"), IPACol(self, 'name', sTitle='IPA form', sClass="ipa-text"), Col(self, 'segments', sTitle='Segments', model_col=models.Form.segments, sClass="ipa-text"), ps, ] if self.parameter: return [ DialectCol(self, 'dialect', get_object=lambda i: i.valueset.language, model_col=common.Language.name), CantonCol( self, 'canton', get_object=lambda i: i.valueset.language, choices=get_distinct_values(models.Variety.canton), ), LinkToMapCol( self, 'm', get_object=lambda i: i.valueset.language), ] + res if self.language: return res + [ ConceptCol(self, 'parameter', sTitle=self.req.translate('Parameter'), model_col=models.Concept.concepticon_gloss, get_object=lambda i: i.valueset.parameter), Col(self, 'french', sTitle='French gloss', model_col=models.Concept.french_gloss, get_object=lambda i: i.valueset.parameter), ] return res + [ ValueSetCol(self, 'valueset', bSearchable=False, bSortable=False), ]
def col_defs(self): return [ IntegerIdCol(self, 'id', sTitle='ID'), LinkCol(self, 'name'), Col(self, 'description', sTitle='Definition'), Col(self, 'semantic_field', choices=get_distinct_values(ConceptSet.semanticfield), model_col=ConceptSet.semanticfield), Col(self, 'ontological_category', choices=get_distinct_values(ConceptSet.ontological_category), model_col=ConceptSet.ontological_category), Col(self, 'representation', sDescription='number of concept lists this concept appears in', model_col=ConceptSet.representation), ]
def col_defs(self): return [ IntegerIdCol(self, 'id', sTitle='ID'), LinkCol(self, 'name'), Col(self, 'description', sTitle='Definition'), Col(self, 'semantic_field', choices=get_distinct_values(ConceptSet.semanticfield), model_col=ConceptSet.semanticfield), Col(self, 'ontological_category', choices=get_distinct_values(ConceptSet.ontological_category), model_col=ConceptSet.ontological_category), Col(self, 'representation', sDescription='number of concept lists this concept appears in', model_col=ConceptSet.representation), ]
def col_defs(self): return list( filter(lambda col: not self.semanticfield or col.name != 'sf', [ LWTCodeCol(self, 'lwt_code'), LinkCol( self, 'name', sTitle='Meaning', sDescription= "This column shows the labels of the Loanword Typology " "meanings. By clicking on a meaning label, you get more information " "about the meaning, as well as a list of all words that are counterparts " "of that meaning."), CoreListCol(self, 'core_list'), Col(self, 'cat', sTitle='Semantic category', sDescription= "Meanings were assigned to semantic categories with " "word-class-like labels: nouns, verbs, adjectives, adverbs, function " "words. No claim is made about the grammatical behavior of words " "corresponding to these meanings. The categories are intended to be " "purely semantic.", model_col=Meaning.semantic_category, choices=get_distinct_values(Meaning.semantic_category)), SemanticFieldCol( self, 'sf', sTitle='Semantic field', sDescription= "The first 22 fields are the fields of the Intercontinental " "Dictionary Series meaning list, proposed by Mary Ritchie Key, and " "ultimately based on Carl Darling Buck's (1949) Dictionary of selected " "synonyms in the principal Indo-European languages. The other two fields " "were added for the Loanword Typology project."), MeaningScoreCol(self, 'borrowed_score', sDescription=literal( '%s' % hb_borrowed_score())), MeaningScoreCol(self, 'age_score', sDescription=literal('%s' % hb_age_score())), MeaningScoreCol(self, 'simplicity_score', sDescription=literal( '%s' % hb_simplicity_score())), Col(self, 'representation', model_col=Meaning.representation, sDescription= "This column shows how many counterparts for this meaning " "there are in the 41 languages. The number can be higher than 41 because " "a language may have several counterparts for one meaning (\"synonyms\")," " and it may be lower than 41, because not all languages may have a " "counterpart for a meaning. "), ]))
def col_defs(self): return [ RecipientCol(self, 'recipient', sTitle='Recipient language'), DonorCol(self, 'donor', sTitle='Donor language'), Col(self, 'count_borrowed', sTitle='Number of borrowed affixes'), Col(self, 'count_interrel', sTitle='Number of interrelated affixes'), Col(self, 'area', choices=get_distinct_values(Pair.area)), ReliabilityCol(self, 'reliability'), LinkCol(self, 'details', model_col=Pair.name), ]
def col_defs(self): cols = Sources.col_defs(self) provider = LinkCol( self, "provider", choices=get_distinct_values(Provider.name), model_col=Provider.name, get_object=lambda i: i.provider, ) return cols[:-1] + [provider]
def col_defs(self): return [ DetailsRowLinkCol(self, '#', button_text='view'), Col(self, 'name', format=wrap_fname), ViewCol(self, 'view'), Col(self, 'size', format=lambda i: util.format_size(i)), Col(self, 'mime_type', sTitle='media type', choices=get_distinct_values(models.File.mime_type)), Col(self, 'date', model_col=models.File.date_created, bSearchable=False), # TODO: link to download! Col(self, 'id', sTitle='MD5 checksum'), ]
def col_defs(self): return [ IdCol(self, 'id'), LinkCol(self, 'name', sTitle='Concept'), Col(self, 'Languages', model_col=Concept.representation), Col(self, 'semantic_field', model_col=Concept.semanticfield, choices=get_distinct_values(Concept.semanticfield)), ConcepticonLink(self, 'Concepticon'), ]
def get_legends(self): if self.ctx.multivalued: def value_li(de): return HTML.label( map_marker_img(self.req, de), literal(de.abbr), style='margin-left: 1em; margin-right: 1em;') yield Legend(self, 'values', map(value_li, self.ctx.domain), label='Legend') def li(label, label_class, input_class, onclick, type_='checkbox', name='', checked=False): input_attrs = dict( type=type_, class_=input_class + ' inline', name=name, value=label, onclick=onclick) if checked: input_attrs['checked'] = 'checked' return HTML.label( HTML.input(**input_attrs), ' ', label, class_="%s" % label_class, style="margin-left:5px; margin-right:5px;", ) def lexifier_li(lexifier): return li( lexifier, 'stay-open', 'stay-open lexifier', JS("APICS.toggle_languages")(self.eid), type_='radio', name='lexifier') for legend in super(FeatureMap, self).get_legends(): yield legend items = [li( '--any--', 'stay-open', 'stay-open lexifier', JS("APICS.toggle_languages")(self.eid), type_="radio", name='lexifier', checked=True)] for l in get_distinct_values( Lect.lexifier, key=lambda v: 'z' + v if v == 'Other' else v ): items.append(lexifier_li(l)) yield Legend(self, 'lexifier', items, stay_open=True)
def col_defs(self): return [ LinkCol(self, 'name', sTitle='Concept'), Col(self, 'indonesian', model_col=Concept.indonesian, bSearchable=True), Col(self, '# lects', model_col=Concept.representation, bSearchable=False, sDescription='<small>The number of languages where this concept is given</small>'), Col(self, 'semantic_field', model_col=Concept.semanticfield, choices=get_distinct_values(Concept.semanticfield)), ConcepticonLink(self, 'Concepticon'), ]
def col_defs(self): return [ IdCol(self, 'id', sTitle='Code'), LinkCol(self, 'name'), BiomeCol(self, 'category'), Col(self, 'status', sDescription=Ecoregion.gbl_stat.doc, model_col=Ecoregion.gbl_stat, choices=get_distinct_values(Ecoregion.gbl_stat)), LinkToMapCol(self, 'm', sTitle=''), Col(self, 'w', sTitle='', format=lambda i: external_link(i.wwf_url(), 'WWF')) ]
def col_defs(self): return [ IdCol(self, "id"), LinkCol(self, "name", sTitle="Concept"), Col(self, "Languages", model_col=Concept.representation), Col( self, "semantic_field", model_col=Concept.semanticfield, choices=get_distinct_values(Concept.semanticfield), ), ConcepticonLink(self, "Concepticon"), ]
def col_defs(self): return [ Col(self, 'ID', model_col=common.Parameter.id), LinkCol(self, 'gloss', model_col=common.Parameter.name), Col(self, 'domain', choices=get_distinct_values(models.Domain.name), get_object=lambda i: i.subdomain.domain, model_col=models.Domain.name), Col(self, 'subdomain', choices=get_distinct_values(models.Subdomain.name), get_object=lambda i: i.subdomain, model_col=models.Subdomain.name), ConcepticonCol( self, 'concepticon', input_size='mini', model_col=models.Concept.concepticon_id), TsammalexCol( self, 'tsammalex', input_size='mini', model_col=models.Concept.tsammalex_taxon), ImagesCol(self, 'images', model_col=models.Concept.count_images), VideosCol(self, 'videos', model_col=models.Concept.count_videos), ]
def col_defs(self): return [ DetailsRowLinkCol(self, '#', button_text='watch'), Col(self, 'name'), Col(self, 'description', sTitle='Category', choices=get_distinct_values(models.Movie.description)), Col(self, 'duration', format=lambda i: util.format_duration(i)), PlaceCol(self, 'place'), # # TODO: avi/qt/mp4 # FileCol(self, 'mp4'), FileCol(self, 'quicktime'), FileCol(self, 'avi', subtype='x-msvideo'), ]
def col_defs(self): return [ LinkCol(self, 'name'), Col(self, '#', bSearchable=False, sDescription='Number of inventories', model_col=Variety.count_inventories), FamilyCol(self, 'family', Variety), Col(self, 'latitude'), Col(self, 'longitude'), Col(self, 'macroarea', model_col=Variety.macroarea, choices=get_distinct_values(Variety.macroarea)), ]
def col_defs(self): return [ DetailsRowLinkCol(self, 'd'), LinkCol(self, 'name'), Col(self, 'description', sTitle='Title'), Col(self, 'year', input_size='mini'), Col(self, 'author'), Col(self, 'DLP', sTitle='DLP', model_col=models.Document.project_doc), Col(self, 'type', input_size='mini', model_col=models.Document.doctype, choices=get_distinct_values(models.Document.doctype)), DocumentCol(self, '#'), TypeCol(self, 'bibtex_type'), ]
def col_defs(self): type_col = Col(self, 'type', model_col=models.Experiment.type, choices=get_distinct_values(models.Experiment.type)) if self.parameter: return [ ValueNameCol(self, 'value'), LinkCol(self, 'language', model_col=Language.name, get_object=lambda i: i.valueset.language), Col(self, 'sample_size', model_col=models.Experiment.sample_size), type_col, RefsCol(self, 'source'), DetailsRowLinkCol(self, '#', button_text='abstract'), ] if self.language: return [ ValueNameCol(self, 'value'), Col(self, 'sample_size', model_col=models.Experiment.sample_size), type_col, LinkCol(self, 'parameter', model_col=Parameter.name, get_object=lambda i: i.valueset.parameter), RefsCol(self, 'source'), DetailsRowLinkCol(self, '#', button_text='abstract'), ] return [ ValueNameCol(self, 'value'), LinkCol(self, 'language', model_col=Language.name, get_object=lambda i: i.valueset.language), Col(self, 'sample_size', model_col=models.Experiment.sample_size), type_col, LinkCol(self, 'parameter', model_col=Parameter.name, get_object=lambda i: i.valueset.parameter), RefsCol(self, 'source'), DetailsRowLinkCol(self, '#', button_text='abstract'), ]
def col_defs(self): return [ LinkCol(self, 'name'), IdCol(self, 'id', sTitle='WALS code', sClass='left'), Col(self, 'iso_codes', sTitle='ISO 639-3', model_col=WalsLanguage.iso_codes), LinkCol(self, 'genus', model_col=Genus.name, get_object=lambda i: i.genus), LinkCol(self, 'family', model_col=Family.name, get_object=lambda i: i.genus.family), Col(self, 'macroarea', model_col=WalsLanguage.macroarea, choices=get_distinct_values(WalsLanguage.macroarea)), Col(self, 'latitude'), Col(self, 'longitude'), CountriesCol(self, 'countries'), ]
def col_defs(self): cols= [ LinkCol( self, 'language', model_col=common.Language.name, get_obj=lambda i: i.language), LinkCol(self, 'name'), Col(self, 'description'), ] if not self.crossgramdata: cols.append(LinkCol( self, 'contribution', model_col=models.CrossgramData.name, get_obj=lambda i: i.contribution, choices=get_distinct_values(models.CrossgramData.name))) return cols
def col_defs(self): return [ LinkCol(self, 'name'), Col(self, '#', bSearchable=False, sDescription='Number of inventories', model_col=Variety.count_inventories), FamilyCol(self, 'family', Variety), Col(self, 'latitude'), Col(self, 'longitude'), Col(self, 'macroarea', model_col=Variety.macroarea, choices=get_distinct_values(Variety.macroarea)), ]
def col_defs(self): return [ IdCol(self, 'id', sTitle='Code'), LinkCol(self, 'name'), BiomeCol(self, 'category'), Col(self, 'status', sDescription=Ecoregion.gbl_stat.doc, model_col=Ecoregion.gbl_stat, choices=get_distinct_values(Ecoregion.gbl_stat)), LinkToMapCol(self, 'm', sTitle=''), Col(self, 'w', sTitle='', format=lambda i: external_link(i.wwf_url(), 'WWF')) ]
def col_defs(self): return [ LinkCol(self, 'name', sTitle=self.req._('Name')), Col(self, 'Island', sTitle=self.req._('Island'), model_col=models.Variety.island, choices=get_distinct_values(models.Variety.island)), Col(self, 'latitude', sDescription='<small>The geographic latitude</small>'), Col(self, 'longitude', sDescription='<small>The geographic longitude</small>'), LinkToMapCol(self, 'm'), ]
def col_defs(self): res = [ LinkCol(self, 'name'), ] if not self.contribution: res.append( LinkCol(self, 'featurelist', model_col=Contribution.name, choices=get_distinct_values(Contribution.name), get_object=lambda o: o.valueset.contribution)) if not self.parameter: res.append( LinkCol(self, 'metafeature', model_col=Parameter.name, get_object=lambda o: o.valueset.parameter)) return res
def col_defs(self): res = [ LinkCol(self, 'name', sTitle='primary text', sClass="object-language"), TsvCol(self, 'analyzed', sTitle='analyzed text'), TsvCol(self, 'gloss', sTitle='gloss', sClass="gloss"), Col(self, 'description', sTitle=self.req.translate('translation'), sClass="translation"), DetailsRowLinkCol(self, 'd', button_text='show', sTitle='IGT'), ] if not self.dictionary: res.insert(-1, LinkCol( self, 'dictionary', model_col=Dictionary.name, get_obj=lambda i: i.dictionary, choices=get_distinct_values(Dictionary.name))) return res
def col_defs(self): return [ LinkToMapCol(self, 'm'), LinkCol(self, 'name'), SubGroupCol(self, 'subfamily', choices=get_distinct_values(models.Doculect.subfamily), model_col=models.Doculect.subfamily), Col(self, 'glottocode', model_col=models.Doculect.glotto_code), Col(self, 'isocode', sTitle='ISO Code', model_col=models.Doculect.iso_code), Col(self, 'latitude', sDescription='<small>The geographic latitude</small>'), Col(self, 'longitude', sDescription='<small>The geographic longitude</small>'), ]
def col_defs(self): res = [ LinkCol(self, 'name', sTitle='primary text', sClass="object-language"), TsvCol(self, 'analyzed', sTitle='analyzed text'), TsvCol(self, 'gloss', sTitle='gloss', sClass="gloss"), Col(self, 'description', sTitle=self.req.translate('translation'), sClass="translation"), ] if self.dictionary and self.dictionary.count_example_audio: res.append(MediaCol(self, 'exaudio', 'audio', sTitle='')) res.append(DetailsRowLinkCol(self, 'd', button_text='show', sTitle='IGT')) if not self.dictionary: res.insert(-1, LinkCol( self, 'dictionary', model_col=Dictionary.name, get_obj=lambda i: i.dictionary, choices=get_distinct_values(Dictionary.name))) return res
def col_defs(self): return list(filter(lambda col: not self.semanticfield or col.name != 'sf', [ LWTCodeCol(self, 'lwt_code'), LinkCol( self, 'name', sTitle='Meaning', sDescription="This column shows the labels of the Loanword Typology " "meanings. By clicking on a meaning label, you get more information " "about the meaning, as well as a list of all words that are counterparts " "of that meaning."), CoreListCol(self, 'core_list'), Col(self, 'cat', sTitle='Semantic category', sDescription="Meanings were assigned to semantic categories with " "word-class-like labels: nouns, verbs, adjectives, adverbs, function " "words. No claim is made about the grammatical behavior of words " "corresponding to these meanings. The categories are intended to be " "purely semantic.", model_col=Meaning.semantic_category, choices=get_distinct_values(Meaning.semantic_category)), SemanticFieldCol( self, 'sf', sTitle='Semantic field', sDescription="The first 22 fields are the fields of the Intercontinental " "Dictionary Series meaning list, proposed by Mary Ritchie Key, and " "ultimately based on Carl Darling Buck's (1949) Dictionary of selected " "synonyms in the principal Indo-European languages. The other two fields " "were added for the Loanword Typology project."), MeaningScoreCol( self, 'borrowed_score', sDescription='%s' % hb_borrowed_score()), MeaningScoreCol( self, 'age_score', sDescription='%s' % hb_age_score()), MeaningScoreCol( self, 'simplicity_score', sDescription='%s' % hb_simplicity_score()), Col(self, 'representation', model_col=Meaning.representation, sDescription="This column shows how many counterparts for this meaning " "there are in the 41 languages. The number can be higher than 41 because " "a language may have several counterparts for one meaning (\"synonyms\")," " and it may be lower than 41, because not all languages may have a " "counterpart for a meaning. "), ]))
def col_defs(self): return [ LinkCol(self, 'name'), IdCol(self, 'id', sTitle='WALS code', sClass='left'), Col(self, 'iso_codes', sTitle='ISO 639-3', model_col=WalsLanguage.iso_codes), LinkCol(self, 'genus', model_col=Genus.name, get_object=lambda i: i.genus), LinkCol(self, 'family', model_col=Family.name, get_object=lambda i: i.genus.family), Col(self, 'macroarea', model_col=WalsLanguage.macroarea, choices=get_distinct_values(WalsLanguage.macroarea)), Col(self, 'latitude'), Col(self, 'longitude'), CountriesCol(self, 'countries'), ]
def __init__(self, dt, name, **kw): kw.setdefault('sTitle', dt.req.translate('Type')) kw.setdefault('choices', get_distinct_values(Sentence.type)) super(TypeCol, self).__init__(dt, name, **kw)
def __init__(self, dt, name, language_cls, **kw): self._col = getattr(language_cls, 'macroarea') kw['choices'] = get_distinct_values(self._col) self.language_cls = language_cls Col.__init__(self, dt, name, **kw)
def __init__(self, dt, name, model_col, **kw): kw['model_col'] = model_col kw['choices'] = get_distinct_values(model_col) super(ClassCol, self).__init__(dt, name, **kw)
def __init__(self, dt, name, **kw): kw['choices'] = get_distinct_values(Languoid.lineage) kw['model_col'] = Languoid.lineage Col.__init__(self, dt, name, **kw)
def __init__(self, dt, name, cls, attribute = 'combinatory_status', **kw): self._col = getattr(cls, attribute) self.attribute = attribute kw['choices'] = get_distinct_values(self._col) Col.__init__(self, dt, name, **kw)
def __init__(self, dt, name, **kw): kw.setdefault('sTitle', dt.req.translate('Type')) kw.setdefault('choices', get_distinct_values(Sentence.type)) super(TypeCol, self).__init__(dt, name, **kw)
def __init__(self, dt, name, **kw): kw['sFilter'] = LanguoidStatus.established.value kw['choices'] = get_distinct_values(Languoid.status) super(StatusCol, self).__init__(dt, name, **kw)
def col_defs(self): name_col = ValueNameCol(self, 'value') if self.parameter and self.parameter.domain: name_col.choices = [(de.name, de.description) for de in self.parameter.domain] cols = [] if self.parameter: cols = [ LinkCol(self, 'Name', model_col=common.Language.name, get_object=lambda i: i.valueset.language), Col(self, 'Glottocode', model_col=common.Language.id, get_object=lambda i: i.valueset.language), LinkCol( self, 'Contributor', model_col=common.Contributor.name, get_object=lambda i: i.valueset.contribution. contributor_assocs[0].contributor, ) ] elif self.language: cols = [ IdCol(self, 'Feature Id', sClass='left', model_col=common.Parameter.id, get_object=lambda i: i.valueset.parameter), LinkCol(self, 'Feature', model_col=common.Parameter.name, get_object=lambda i: i.valueset.parameter) ] elif self.family: cols = [ LinkCol(self, 'Name', model_col=common.Language.name, get_object=lambda i: i.valueset.language) ] if not self.feature: cols.extend([ IdCol(self, 'Feature Id', sClass='left', model_col=common.Parameter.id, get_object=lambda i: i.valueset.parameter), LinkCol( self, 'Feature', model_col=common.Parameter.name, get_object=lambda i: i.valueset.parameter, choices=get_distinct_values(common.Parameter.name), ) ]) cols = cols + [ name_col, RefsCol(self, 'Source', model_col=common.ValueSet.source, get_object=lambda i: i.valueset), Col(self, 'Comment', model_col=common.Value.description), #Col(self, 'Contributed By', model_col=common.Contribution.name, # get_object=lambda i: i.valueset.contribution) ] return cols
def __init__(self, dt, name, **kw): kw['choices'] = [(sd, sd.replace('_', ' ')) for sd in get_distinct_values(Entry.sd)] kw['model_col'] = Entry.sd Col.__init__(self, dt, name, **kw)
def col_defs(self): get_word = lambda item: item.word get_vocabulary = lambda item: item.valueset.contribution get_meaning = lambda item: item.valueset.parameter word_form_col = LinkCol( self, 'word_form', model_col=Word.name, get_object=get_word, sDescription="<p>The word is given in the usual orthography or " "transcription, and in the usual citation form.</p><p>Click on a word to " "get more information than is shown in this table.</p>") borrowed_col = Col( self, 'borrowed', sTitle='Borrowed status', model_col=Word.borrowed, get_object=get_word, choices=get_distinct_values(Word.borrowed), sDescription="<p>There are five borrowed statuses, reflecting decreasing " "likelihood that the word is a loanword:</p><ol>" "<li>clearly borrowed</li><li>probably borrowed</li><li>perhaps borrowed</li>" "<li>very little evidence for borrowing</li>" "<li>no evidence for borrowing</li></ol>") if self.parameter: return [ IntegerIdCol( self, 'vocid', sTitle='Voc. ID', model_col=common.Contribution.id, get_object=get_vocabulary, sDescription="The vocabulary ID corresponds to the ordering to the " "chapters on the book <em>Loanwords in the World's Languages</em>. " "Languages are listed in rough geographical order from west to east, " "from Africa via Europe to Asia and the Americas, so that " "geographically adjacent languages are next to each other."), VocabularyCol(self, 'vocabulary', get_object=get_vocabulary), word_form_col, borrowed_col, CounterpartScoreCol(self, 'borrowed_score'), CounterpartScoreCol(self, 'age_score'), CounterpartScoreCol(self, 'simplicity_score'), ] if self.contribution: return [ word_form_col, LWTCodeCol( self, 'lwt_code', get_object=get_meaning), LinkCol( self, 'meaning', model_col=common.Parameter.name, get_object=get_meaning, sDescription="This column shows the labels of the Loanword Typology " "meanings. By clicking on a meaning label, you get more information " "about the meaning, as well as a list of all words that are " "counterparts of that meaning."), CoreListCol(self, 'core_list', get_object=get_meaning), borrowed_col, SourceWordsCol( self, 'source_words', bSearchable=False, bSortable=False, sDescription="For (possible) loanwords, this column shows the words " "in the source languages that served as models."), ] return [] # pragma: no cover
def col_defs(self): get_word = lambda item: item.word get_vocabulary = lambda item: item.valueset.contribution get_meaning = lambda item: item.valueset.parameter word_form_col = LinkCol( self, 'word_form', model_col=Word.name, get_object=get_word, sDescription=literal( "<p>The word is given in the usual orthography or " "transcription, and in the usual citation form.</p><p>Click on a word to " "get more information than is shown in this table.</p>")) borrowed_col = Col( self, 'borrowed', sTitle='Borrowed status', model_col=Word.borrowed, get_object=get_word, choices=get_distinct_values(Word.borrowed), sDescription=literal( "<p>There are five borrowed statuses, reflecting decreasing " "likelihood that the word is a loanword:</p><ol>" "<li>clearly borrowed</li><li>probably borrowed</li><li>perhaps borrowed</li>" "<li>very little evidence for borrowing</li>" "<li>no evidence for borrowing</li></ol>")) if self.parameter: return [ IntegerIdCol( self, 'vocid', sTitle='Voc. ID', model_col=common.Contribution.id, get_object=get_vocabulary, sDescription= "The vocabulary ID corresponds to the ordering to the " "chapters on the book <em>Loanwords in the World's Languages</em>. " "Languages are listed in rough geographical order from west to east, " "from Africa via Europe to Asia and the Americas, so that " "geographically adjacent languages are next to each other." ), VocabularyCol(self, 'vocabulary', get_object=get_vocabulary), word_form_col, borrowed_col, CounterpartScoreCol(self, 'borrowed_score'), CounterpartScoreCol(self, 'age_score'), CounterpartScoreCol(self, 'simplicity_score'), ] if self.contribution: return [ word_form_col, LWTCodeCol(self, 'lwt_code', get_object=get_meaning), LinkCol( self, 'meaning', model_col=common.Parameter.name, get_object=get_meaning, sDescription= "This column shows the labels of the Loanword Typology " "meanings. By clicking on a meaning label, you get more information " "about the meaning, as well as a list of all words that are " "counterparts of that meaning."), CoreListCol(self, 'core_list', get_object=get_meaning), borrowed_col, SourceWordsCol( self, 'source_words', bSearchable=False, bSortable=False, sDescription= "For (possible) loanwords, this column shows the words " "in the source languages that served as models."), ] return [] # pragma: no cover
def col_defs(self): kw = {} if self.language: kw['bSearchable'] = False kw['bSortable'] = False name_col = ApicsValueNameCol(self, 'value', **kw) if self.parameter and self.parameter.domain: name_col.choices = [de.name for de in self.parameter.domain] class ValueLanguageCol(LinkCol): def search(self, qs): if self.dt.language: return ValueSet.language_pk == int(qs) if self.dt.parameter: return icontains(self.dt.vs_lang.name, qs) def order(self): if self.dt.parameter: return cast(self.dt.vs_lang.id, Integer) if self.dt.language: return ValueSet.language_pk lang_col = ValueLanguageCol( self, 'language', model_col=Language.name, get_obj=lambda item: item.valueset.language, bSearchable=bool(self.parameter or self.language), bSortable=bool(self.parameter or self.language)) if self.language: if self.language.lects: lang_col.choices = [ (l.pk, l.name) for l in [self.language] + self.language.lects] lang_col.js_args['sTitle'] = 'lect' else: lang_col = None get_param = lambda i: i.valueset.parameter if self.parameter: return nfilter([ lang_col, name_col, Col(self, 'lexifier', format=lambda i: i.valueset.language.lexifier, model_col=self.vs_lect.lexifier, choices=get_distinct_values( Lect.lexifier, key=lambda v: 'z' + v if v == 'Other' else v)), LinkToMapCol( self, 'm', get_object=lambda i: None if i.valueset.language.language_pk else i.valueset.language), DetailsRowLinkCol(self, 'more') if self.parameter.feature_type != 'sociolinguistic' else None, RefsCol(self, 'source') if self.parameter.feature_type != 'segment' else None, ]) if self.language: return nfilter([ IntegerIdCol(self, 'id', get_obj=get_param, model_col=Parameter.id), LinkCol(self, 'parameter', get_obj=get_param, model_col=Parameter.name), name_col, lang_col, DetailsRowLinkCol(self, 'more'), RefsCol(self, 'source'), ]) return [ LinkCol(self, 'parameter', get_obj=get_param, model_col=Parameter.name), name_col, lang_col, DetailsRowLinkCol(self, 'more'), RefsCol(self, 'source'), ]
def __init__(self, dt, name, model_col, **kw): kw['model_col'] = model_col kw['choices'] = get_distinct_values(model_col) super(ClassCol, self).__init__(dt, name, **kw)
def __init__(self, dt, name, **kw): #kw['sFilter'] = LanguoidStatus. kw['choices'] = get_distinct_values(Languoid.status) super(StatusCol, self).__init__(dt, name, **kw)
def __init__(self, dt, name, **kw): kw['choices'] = get_distinct_values(Transcription.datatype) super(DatatypeCol, self).__init__(dt, name, **kw)