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How to use convert_hist method in yandex-tank

Best Python code snippet using yandex-tank

compare.py

Source:compare.py

...49        return Status.INCONCLUSIVE50        #  raise RuntimeError("Shouldn't happen")51    def ensure_plots(self, report_dir: Path, plot_dir: Path):52        if isinstance(self.item_a, ROOT.TH2):53            h2_a = convert_hist(self.item_a)54            h2_b = convert_hist(self.item_b)55            for proj in [0, 1]:56                h1_a = h2_a.project(proj)57                h1_b = h2_b.project(proj)58                fig, _ = plot_ratio(h1_a, h1_b)59        elif isinstance(self.item_a, ROOT.TEfficiency):60            a, a_err = convert_hist(self.item_a)61            b, b_err = convert_hist(self.item_b)62            lowest = 063            nonzero = numpy.concatenate(64                [a.values()[a.values() > 0], b.values()[b.values() > 0]]65            )66            if len(nonzero) > 0:67                lowest = numpy.min(nonzero)68            fig, (ax, rax) = plot_ratio_eff(a, a_err, b, b_err)69            ax.set_ylim(bottom=lowest * 0.9)70        elif isinstance(self.item_a, ROOT.TH1):71            a = convert_hist(self.item_a)72            b = convert_hist(self.item_b)73            fig, _ = plot_ratio(a, b)74        self._generic_plots.append(plot_to_uri(fig))75        if plot_dir is not None:76            safe_key = self.key.replace("/", "_")77            fig.savefig(plot_dir / f"{safe_key}.pdf")78    @property79    def first_plot_index(self):80        for i, v in enumerate(self.checks):81            if v.plot is not None:82                return i83    @property84    def generic_plots(self) -> List[Path]:85        return self._generic_plots86@dataclass...

root_helpers.py

Source:root_helpers.py

...84            name=_process_axis_title(axis.GetTitle()),85        )86        #  print(ax)87        return ax88def convert_hist(item):89    if isinstance(item, ROOT.TH2):90        h = hist.Hist(91            convert_axis(item.GetXaxis()),92            convert_axis(item.GetYaxis()),93            storage=hist.storage.Weight(),94            name=_process_axis_title(item.GetTitle()),95            label=_process_axis_title(item.GetZaxis().GetTitle()),96        )97        cont, err = get_bin_content_error(item)98        h.view().value = cont99        h.view().variance = err ** 2100        return h101    elif isinstance(item, ROOT.TEfficiency):102        passed = convert_hist(item.GetPassedHistogram())103        #  total = convert_hist(item.GetTotalHistogram())104        eff = passed[:]105        eff.reset()106        eff.name = _process_axis_title(item.GetTitle())107        nbins = item.GetPassedHistogram().GetNbinsX()108        values = numpy.zeros(nbins)109        error = numpy.zeros((2, nbins))110        for b in range(1, nbins + 1):111            values[b - 1] = item.GetEfficiency(b)112            #  error[b - 1] = 0.5 * (113            #  item.GetEfficiencyErrorUp(b) + item.GetEfficiencyErrorLow(b)114            #  )115            if values[b - 1] != 0:116                error[1][b - 1] = item.GetEfficiencyErrorUp(b)117                error[0][b - 1] = item.GetEfficiencyErrorLow(b)...

直方图均衡化.py

Source:直方图均衡化.py

...38    return result394041# è¿è¡å¾çåè¡¡åå¤ç42def convert_hist(img, h, w, result):43    for i in range(h):44        for j in range(w):45            key = img[i, j]46            img[i, j] = result[key]4748    return img495051result = all_np(img, h, w)52new_image = convert_hist(img, h, w, result)5354# image2 = cv.equalizeHist(img)55# cv.imshow("new image", new_image)56# cv.imshow("new image2", image2)57# cv.waitKey(0)58# todo need confirm whether this is make by precision59# my result60# [[ 50 139 255 255 216]61#  [ 88  50 139 203 139]62#  [139 191  24 191 152]63# [ 88 255  88 191  24]]6465# expectation is66[
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