def correlation_plots(self, x_analyte, y_analyte, window=15, filt=True, recalc=False, samples=None, subset=None, outdir=None):
        """
        Plot the local correlation between two analytes.

        Parameters
        ----------
        x_analyte, y_analyte : str
            The names of the x and y analytes to correlate.
        window : int, None
            The rolling window used when calculating the correlation.
        filt : bool
            Whether or not to apply existing filters to the data before
            calculating this filter.
        recalc : bool
            If True, the correlation is re-calculated, even if it is already present.

        Returns
        -------
        None
        """
        if outdir is None:
            outdir = self.report_dir + '/correlations/'
        if not os.path.isdir(outdir):
            os.mkdir(outdir)
        
        if subset is not None:
            samples = self._get_samples(subset)
        elif samples is None:
            samples = self.subsets['All_Analyses']
        elif isinstance(samples, str):
            samples = [samples]

        with self.pbar.set(total=len(samples), desc='Drawing Plots') as prog:
            for s in samples:
                f, a = self.data[s].correlation_plot(x_analyte=x_analyte, y_analyte=y_analyte,
                                                     window=window, filt=filt, recalc=recalc)
                f.savefig('{}/{}_{}-{}.pdf'.format(outdir, s, x_analyte, y_analyte))
                plt.close(f)
                prog.update()
        return
def correlation_plots(self, x_analyte, y_analyte, window=15, filt=True, recalc=False, samples=None, subset=None, outdir=None):
        """
        Plot the local correlation between two analytes.

        Parameters
        ----------
        x_analyte, y_analyte : str
            The names of the x and y analytes to correlate.
        window : int, None
            The rolling window used when calculating the correlation.
        filt : bool
            Whether or not to apply existing filters to the data before
            calculating this filter.
        recalc : bool
            If True, the correlation is re-calculated, even if it is already present.

        Returns
        -------
        None
        """
        if outdir is None:
            outdir = self.report_dir + '/correlations/'
        if not os.path.isdir(outdir):
            os.mkdir(outdir)
        
        if subset is not None:
            samples = self._get_samples(subset)
        elif samples is None:
            samples = self.subsets['All_Analyses']
        elif isinstance(samples, str):
            samples = [samples]

        with self.pbar.set(total=len(samples), desc='Drawing Plots') as prog:
            for s in samples:
                f, a = self.data[s].correlation_plot(x_analyte=x_analyte, y_analyte=y_analyte,
                                                     window=window, filt=filt, recalc=recalc)
                f.savefig('{}/{}_{}-{}.pdf'.format(outdir, s, x_analyte, y_analyte))
                plt.close(f)
                prog.update()
        return
def correlation_plots ( self , x_analyte , y_analyte , window = 15 , filt = True , recalc = False , samples = None , subset = None , outdir = None ) : if outdir is None : outdir = self . report_dir + '/correlations/' if not os . path . isdir ( outdir ) : os . mkdir ( outdir ) if subset is not None : samples = self . _get_samples ( subset ) elif samples is None : samples = self . subsets [ 'All_Analyses' ] elif isinstance ( samples , str ) : samples = [ samples ] with self . pbar . set ( total = len ( samples ) , desc = 'Drawing Plots' ) as prog : for s in samples : f , a = self . data [ s ] . correlation_plot ( x_analyte = x_analyte , y_analyte = y_analyte , window = window , filt = filt , recalc = recalc ) f . savefig ( '{}/{}_{}-{}.pdf' . format ( outdir , s , x_analyte , y_analyte ) ) plt . close ( f ) prog . update ( ) return
Plot the local correlation between two analytes.

        Parameters
        ----------
        x_analyte, y_analyte : str
            The names of the x and y analytes to correlate.
        window : int, None
            The rolling window used when calculating the correlation.
        filt : bool
            Whether or not to apply existing filters to the data before
            calculating this filter.
        recalc : bool
            If True, the correlation is re-calculated, even if it is already present.

        Returns
        -------
        None
Plot the local correlation between two analytes .