def getAnalysisMethodLs(call_method_id, phenotype_method_id): """ 2009-1-30 """ affiliated_table_name = model.Stock_250kDB.ResultsMethod.table.name #alias is 's' extra_condition = 's.call_method_id=%s and s.phenotype_method_id=%s'%\ (call_method_id, phenotype_method_id) list_info = hc.getAnalysisMethodInfo(affiliated_table_name, extra_condition=extra_condition) analysis_method_ls = [] for i in range(len(list_info.id_ls)): id = list_info.id_ls[i] label = list_info.label_ls[i] description = list_info.description_ls[i] analysis_method_ls.append([id, label, description]) return analysis_method_ls
def getAnalysisMethodLsGivenTypeAndPhenotypeMethod(type_id, call_method_id, phenotype_method_id, extra_table_name=None): """ 2009-2-22 add argument extra_table_name 2008-12-30 """ affiliated_table_name = model.Stock_250kDB.ResultsMethod.table.name #alias is 's' if not extra_table_name: extra_table_name = model.Stock_250kDB.CandidateGeneTopSNPTestRM.table.name extra_tables = ' %s c '%extra_table_name extra_condition = 'c.results_id=s.id and c.type_id=%s and s.call_method_id=%s and s.phenotype_method_id=%s'%\ (type_id, call_method_id, phenotype_method_id) list_info = hc.getAnalysisMethodInfo(affiliated_table_name, extra_condition=extra_condition, extra_tables=extra_tables) analysis_method_ls = [] for i in range(len(list_info.id_ls)): id = list_info.id_ls[i] label = list_info.label_ls[i] analysis_method_ls.append([id, label]) return analysis_method_ls
def getAnalysisMethodLsGivenTypeAndPhenotypeMethod(type_id, phenotype_method_id, extra_table_name=None): """ 2009-4-13 added results_gene2type into the condition to restrict analysis_methods type_id is actually used now. 2009-3-4 """ affiliated_table_name = model.Stock_250kDB.ResultsMethod.table.name #alias is 's' type = ScoreRankHistogramType.get(type_id) call_method_id = type.call_method_id if not extra_table_name: extra_table_name = model.Stock_250kDB.ResultsGene.table.name extra_tables = ' %s c, %s y '%(extra_table_name, "results_gene2type") extra_condition = 'c.results_id=s.id and s.call_method_id=%s and s.phenotype_method_id=%s and y.score_rank_histogram_type_id=%s and y.results_gene_id=c.id'%\ (call_method_id, phenotype_method_id, type_id) list_info = hc.getAnalysisMethodInfo(affiliated_table_name, extra_condition=extra_condition, extra_tables=extra_tables) analysis_method_ls = [] for i in range(len(list_info.id_ls)): id = list_info.id_ls[i] label = list_info.label_ls[i] analysis_method_ls.append([id, label]) return analysis_method_ls
def call_method(self, id=None):
if id is None:
id = request.params.get('id', 17)
MAFVsScorePlot = model.Stock_250kDB.MAFVsScorePlot
affiliated_table_name = model.Stock_250kDB.ResultsMethod.table.name
extra_condition = 's.call_method_id=%s and s.id=m.results_method_id'%id
extra_tables = '%s m'%model.Stock_250kDB.MAFVsScorePlot.table.name
c.phenotype_info = hc.getPhenotypeInfo(affiliated_table_name, extra_condition, extra_tables)
c.analysis_info = hc.getAnalysisMethodInfo(affiliated_table_name, extra_condition, extra_tables)
rows = MAFVsScorePlot.query.filter(MAFVsScorePlot.results_method.has(call_method_id=id))
data_matrix = numpy.zeros([len(c.phenotype_info.phenotype_method_id_ls), len(c.analysis_info.id_ls)], numpy.int)
data_matrix[:] = -1
counter = 0
for row in rows:
row_index = c.phenotype_info.phenotype_method_id2index[row.results_method.phenotype_method_id]
col_index = c.analysis_info.id2index[row.results_method.analysis_method_id]
data_matrix[row_index, col_index] = row.id
counter +=1
c.counter = counter
c.data_matrix = data_matrix
c.call_method_id = id
return render('/maf_vs_score_call_method.html')
