gseapy/gsea.py
def _heatmat(self, df, classes, pheno_pos, pheno_neg):
        """only use for gsea heatmap"""
        width = len(classes) if len(classes) >= 6 else  5
        cls_booA =list(map(lambda x: True if x == pheno_pos else False, classes))
        cls_booB =list(map(lambda x: True if x == pheno_neg else False, classes))
        datA = df.loc[:, cls_booA]
        datB = df.loc[:, cls_booB]
        datAB=pd.concat([datA,datB], axis=1)
        self._width = width
        self.heatmat = datAB
        return
def _heatmat(self, df, classes, pheno_pos, pheno_neg):
        width = len(classes) if len(classes) >= 6 else  5
        cls_booA =list(map(lambda x: True if x == pheno_pos else False, classes))
        cls_booB =list(map(lambda x: True if x == pheno_neg else False, classes))
        datA = df.loc[:, cls_booA]
        datB = df.loc[:, cls_booB]
        datAB=pd.concat([datA,datB], axis=1)
        self._width = width
        self.heatmat = datAB
        return
def _heatmat ( self , df , classes , pheno_pos , pheno_neg ) : width = len ( classes ) if len ( classes ) >= 6 else 5 cls_booA = list ( map ( lambda x : True if x == pheno_pos else False , classes ) ) cls_booB = list ( map ( lambda x : True if x == pheno_neg else False , classes ) ) datA = df . loc [ : , cls_booA ] datB = df . loc [ : , cls_booB ] datAB = pd . concat ( [ datA , datB ] , axis = 1 ) self . _width = width self . heatmat = datAB return
only use for gsea heatmap
only use for gsea heatmap