selection.py 文件源码

def wt_plot(self, pdf):
        """
        Create a plot of the linear fit of the wild type variant.

        *pdf* is an open PdfPages instance.

        Only created for selections that use WLS or OLS scoring and have a wild type specified. 
        Uses :py:func:`~plots.fit_axes` for the plotting.
        """
        logging.info("Creating wild type fit plot", extra={'oname' : self.name})

        # get the data and calculate log ratios
        if "variants" in self.labels:
            wt_label = "variants"
        elif "identifiers" in self.labels:
            wt_label = "identifiers"
        data = self.store.select("/main/{}/counts".format(wt_label), where='index = "{}"'.format(WILD_TYPE_VARIANT)).ix[0]
        sums = self.store['/main/{}/counts'.format(wt_label)].sum(axis="index")  # sum of complete cases (N')
        yvalues = np.log(data + 0.5) - np.log(sums + 0.5)
        xvalues = [tp / float(max(self.timepoints)) for tp in self.timepoints]

        # fit the line
        X = sm.add_constant(xvalues) # fit intercept
        if self.scoring_method == "WLS":
            W =  1 / (1 / (data + 0.5) + 1 / (sums + 0.5))
            fit = sm.WLS(yvalues, X, weights=W).fit()
        elif self.scoring_method == "OLS":
            fit = sm.OLS(yvalues, X).fit()
        else:
            raise ValueError('Invalid regression scoring method "{}" [{}]'.format(self.scoring_method, self.name))
        intercept, slope = fit.params
        slope_se = fit.bse['x1']

        # make the plot
        fig, ax = plt.subplots()
        fig.set_tight_layout(True)
        fit_axes(ax, xvalues, yvalues, slope, intercept, xlabels=self.timepoints)
        fit_axes_text(ax, cornertext="Slope {:3.2f}\nSE {:.1f}".format(slope, slope_se))
        ax.set_title("Wild Type Shape\n{}".format(self.name))
        ax.set_ylabel("Log Ratio (Complete Cases)")

        pdf.savefig(fig)
        plt.close(fig)