plot Namespace Reference

Classes
class	LayerPlotter
class	TqdmLoggingHandler

Functions
	check_status_code (func)
	timed (method)
	plot_ATLAS (fig, x, y, label="Internal", fontsize=20)
	pairwise (iterable)
	divide_square (n, horizontal=True)
	histo2data (histo)
	systematics_from_tool (tool, only_scale=True, only_resolution=False, only_up=True)
	partition (x, n)
	generator_photon (self)
	calibrate_eta_pt (tool, etas, pts, simulation=True, particle="unconverted")
	eval_sys_eta_phi (tool, etas, phis, pt, simulation, particle="unconverted")
	eval_eta_slice (tool, etas, pts, ptype, only_material=False, only_up=True)
	beautify_sysname (sysname)
	beautify_particle (particle)
	plot_all_syst_eta_slice (etabins, supersampling_eta=3, esmodel="es2012c", decorrelation="FULL_v1", ptype="unconverted", pts=np.logspace(np.log10(5e3), 6, 100), basedir="plot", only_material=False, beautify_sysnames=False, sys_order=None, superimpose_all=False, skip_null_sys=False, min_sys=-0.02, max_sys=0.02, only_up=True, debug=False, legend_outside=False, symmetrize_labels=False, log_x=False, plot_qsum=False, abs_sys=False, atlas_label="Internal")
	values2histo (name, title, x, y)
	plot_all_Zee_syst (etas, pt=100e3, basedir="plots")
	plot_all_syst_fixed_pt (tools, names, labels, pt=100e3, ptype="unconverted", basedir="plots")
	compute_or_read_sys (tool, ptypes, eta_edges, pt_edges)
	compare_sys (esmodels=None, ptypes=None, decorrelation="FULL_ETACORRELATED_v1", eta_edges=None, pt_edges=None, basedir="plots", smearing=False, only_up=True, abs_sys=False, log_x=False)
	plot_all_syst_eta_pt (esmodel="es2012c", decorrelation="FULL_v1", ptype="unconverted", basedir="plots", eta_range=None, pt_range=None, log_pt=False, abs_sys=False, only_up=False, sys_filters=None, min_value=None, max_value=None)
	plot_all_scales (esmodels, basedir, labels=None, etas=np.arange(-4.5, 4.5, 0.01), add_patch=False, debug=False # noqa:B008(range used as constant))
	plot_all_cterms (esmodels, basedir, labels=None, etas=np.arange(-4.5, 4.5, 0.01))
	compare_two_tools_eta (tool1, tool2, pt, simulation, name, basedir, title, particle="unconverted")
	compare_two_tools_eta_phi (tool1, tool2, pt, simulation, name, basedir, title, particle="unconverted")
	compare_two_tools_eta_pt (tool1, tool2, simulation, name, basedir, title, particle="unconverted")
	check_gain (basedir, esmodel)
	check_fast (basedir, esmodel)
	check_uniformity (basedir, esmodel)
	compare_all_syst_fixed_pt (basedir, esmodels, names=None, labels=None)
	plot_resolution_eta_pt (basedir, tool, pts, etas, ptype, title)
	plot_resolution_error (basedir, **kwargs)
	plot_resolution_error_bin (eta_min, eta_max, particle, esmodel, basedir, tool=None, **kwargs)
	list_systematics (esmodels, decorrelation="FULL_ETACORRELATED_v1")
	main ()

Variables
	IgnoreCommandLineOptions
str	extensions = "pdf", "png"
	initialize
	fout = ROOT.TFile("output_plot.root", "recreate")
	log
	handler = TqdmLoggingHandler()
	plotter = LayerPlotter()

Detailed Description

Produce plots about egamma calibration systematics and corrections 

Function Documentation

beautify_particle()

plot.beautify_particle

(

particle

)

Definition at line 286 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def beautify_particle(particle):
    d = {
        "electron": "Electrons",
        "converted": "Converted photons",
        "unconverted": "Unconverted photons",
    }
    return d.get(particle, particle).capitalize()
 
 

beautify_sysname()

plot.beautify_sysname

(

sysname

)

Definition at line 255 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def beautify_sysname(sysname):
    d = {
        "EG_SCALE_PEDESTAL": "Pedestal",
        "EG_SCALE_L2GAIN": "L2 gain",
        "EG_SCALE_L1GAIN": "L1 gain",
        "EG_SCALE_PS": r"$\alpha_{PS}$",
        "EG_SCALE_S12": r"$\alpha_{1/2}$",
        "EG_SCALE_S12EXTRALASTETABINRUN2": r"$\alpha_{1/2}$ [2.4-2.5]",
        "EG_SCALE_ZEESYST": r"$Z\to ee$ cal. (sys)",
        "EG_SCALE_ZEESTAT": r"$Z\to ee$ cal. (stat)",
        "PH_SCALE_LEAKAGEUNCONV": "Leakage unconverted",
        "EG_SCALE_MATID": "ID material",
        "EG_SCALE_MATCRYO": "Cryo material",
        "EG_SCALE_MATPP0": "PP0 material",
        "EG_SCALE_WTOTS1": "$w_{tots1}$ non-lin.",
        "EG_SCALE_CONVEFFICIENCY": "Conversion efficiency",
        "EG_SCALE_MATCALO": "Calo material",
        "EG_SCALE_ZEE_STAT": r"$Z\to ee$ (stat)",
        "EG_SCALE_G4": "Geant4",
        "PH_SCALE_LEAKAGECONV": "Leakage converted",
        "PH_SCALE_CONVRADIUS": "Conv. radius",
        "PH_SCALE_CONVFAKERATE": "Conv. fake rate",
        "PH_SCALE_CONVEFFICIENCY": "Conv. efficiency",
        "EG_SCALE_LARCALIB": r"$\alpha_{1/2}$ $\mu\to e$ extrap.",
        "EG_SCALE_E4SCINTILLATOR": "Scintillators",
        "EG_SCALE_LARTEMPERATURE_EXTRA2016PRE": r"Temp. 2015 $\to$ 2016",
        "EG_SCALE_LARCALIB_EXTRA2015PRE": r"$\alpha_{1/2}$ Run 1 $\to$ Run 2",
    }
    return d.get(sysname, sysname)
 
 

calibrate_eta_pt()

plot.calibrate_eta_pt	(		tool,
			etas,
			pts,
			simulation = True,
			particle = "unconverted" )

Definition at line 180 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def calibrate_eta_pt(tool, etas, pts, simulation=True, particle="unconverted"):
    log.debug("creating TEvent and EgammaFactory")
    event = ROOT.xAOD.TEvent()
    factory = ROOT.EgammaFactory()
    result = np.ones((len(pts), len(etas)))
    ei = factory.create_eventinfo(simulation, 266904)
    assert ei.eventType(ROOT.xAOD.EventInfo.IS_SIMULATION) == simulation
    log.debug("looping")
    for ieta, eta in enumerate(etas):
        for ipt, pt in enumerate(pts):
            if particle == "unconverted":
                p = factory.create_photon(eta, 0.1, pt * np.cosh(eta), 0)
            elif particle == "converted":
                p = factory.create_photon(eta, 0.1, pt * np.cosh(eta), 100)
            elif particle == "electron":
                p = factory.create_electron(eta, 0.1, pt * np.cosh(eta))
            else:
                raise ValueError()
            result[ipt, ieta] = tool.getEnergy(p, ei)
    log.debug("deleting event")
    del event
    log.debug("returning result %s", result)
    return result
 
 

check_fast()

plot.check_fast	(		basedir,
			esmodel )

Definition at line 1369 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def check_fast(basedir, esmodel):
    tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool.setProperty("ESModel", esmodel)
    tool.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool.setProperty[bool]("doSmearing", 0)
    tool.initialize()
 
    tool_fast = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool_fast.setProperty("ESModel", esmodel)
    tool_fast.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_fast.setProperty[bool]("doSmearing", 0)
    tool_fast.setProperty[bool]("useFastSim", True)
    tool_fast.initialize()
 
    for ptype in "electron", "converted", "unconverted":
        compare_two_tools_eta(
            tool_fast,
            tool,
            pt=100e3,
            simulation=True,
            name="fast_%s_%s" % (esmodel, ptype),
            basedir=basedir,
            particle=ptype,
            title="fast correction effect %s %s 100 GeV" % (esmodel, ptype),
        )
 
 

check_gain()

plot.check_gain	(		basedir,
			esmodel )

Definition at line 1332 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def check_gain(basedir, esmodel):
    tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool.setProperty("ESModel", esmodel)
    tool.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool.setProperty[bool]("doSmearing", 0)
    tool.initialize()
 
    tool_no_gain = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool_no_gain.setProperty("ESModel", esmodel)
    tool_no_gain.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_no_gain.setProperty[bool]("doSmearing", 0)
    tool_no_gain.setProperty[bool]("useGainCorrection", 0)
    tool_no_gain.initialize()
 
    for ptype in "electron", "unconverted", "converted":
        compare_two_tools_eta_pt(
            tool_no_gain,
            tool,
            simulation=False,
            name="gain_%s_%s" % (esmodel, ptype),
            basedir=basedir,
            particle=ptype,
            title="gain correction effect - %s - %s" % (esmodel, ptype),
        )
 
    compare_two_tools_eta(
        tool_no_gain,
        tool,
        40e3,
        simulation=False,
        name="gain_%s_%s_40GeV" % (esmodel, "electron"),
        basedir=basedir,
        title="gain correction effect - %s 40 GeV electron" % esmodel,
        particle="electron",
    )
 
 

check_status_code()

plot.check_status_code

(

func

)

Definition at line 64 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def check_status_code(func):
    def wrapper(self, *args):
        status = func(self, *args)
        if not status.isSuccess():
            raise ValueError("status is not success")
        return status
 
    return wrapper
 
 

check_uniformity()

plot.check_uniformity	(		basedir,
			esmodel )

Definition at line 1396 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def check_uniformity(basedir, esmodel):
    tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool.setProperty("ESModel", esmodel)
    tool.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool.setProperty[bool]("doSmearing", 0)
    tool.initialize()
 
    tool_no_uniformity = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
    tool_no_uniformity.setProperty("ESModel", esmodel)
    tool_no_uniformity.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_no_uniformity.setProperty[bool]("doSmearing", 0)
    tool_no_uniformity.setProperty[bool]("usePhiUniformCorrection", 0)
    tool_no_uniformity.initialize()
 
    compare_two_tools_eta_phi(
        tool_no_uniformity,
        tool,
        pt=100e3,
        simulation=False,
        name="uniformity_%s" % esmodel,
        basedir=basedir,
        particle="unconverted",
        title="uniformity correction effect - %s - unconverted 100 GeV" % esmodel,
    )
 
 

compare_all_syst_fixed_pt()

plot.compare_all_syst_fixed_pt	(		basedir,
			esmodels,
			names = None,
			labels = None )

Definition at line 1422 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def compare_all_syst_fixed_pt(basedir, esmodels, names=None, labels=None):
    names = names or esmodels
    labels = labels or names
    tools = []
    for esmodel in esmodels:
        if type(esmodel) is str:
            tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_%s" % esmodel)
            tool.setProperty("ESModel", esmodel)
            tool.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
            tool.setProperty[bool]("doSmearing", 0)
            tool.initialize()
            tools.append(tool)
        else:
            tools.append(esmodel)
    plot_all_syst_fixed_pt(tools, names=names, labels=labels, basedir=basedir)
 
 

compare_sys()

plot.compare_sys	(		esmodels = None,
			ptypes = None,
			decorrelation = "FULL_ETACORRELATED_v1",
			eta_edges = None,
			pt_edges = None,
			basedir = "plots",
			smearing = False,
			only_up = True,
			abs_sys = False,
			log_x = False )

Definition at line 839 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    esmodels = esmodels or ["es2012c"]
    ptypes = ptypes or ["electron"]
    if pt_edges is None:
        pt_edges = np.linspace(0, 100, 5)
    if eta_edges is None:
        eta_edges = np.array([0, 0.6, 1.0, 1.37, 1.55, 1.82, 2.47])
    pt_edges = np.asarray(pt_edges)
    eta_edges = np.asarray(eta_edges)
 
    pt_midpoints = 0.5 * (pt_edges[1:] + pt_edges[:-1])
 
    log.info(
        "comparing systematics for esmodels=%s, ptypes=%s, #pt-bins=%d, #eta-bins=%d",
        (esmodels, ptypes, len(pt_edges) - 1, len(eta_edges) - 1)
    )
 
    effects = {}
    for esmodel in esmodels:
        log.info("creating tool for %s", esmodel)
        tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
        tool.setProperty("ESModel", esmodel)
        tool.setProperty("decorrelationModel", decorrelation)
        tool.setProperty[int]("randomRunNumber", 297730)
        if not smearing:
            tool.setProperty[bool]("doSmearing", 0)
        tool.initialize()
 
        log.info("computing systematics for %s", esmodel)
 
        sys_values = compute_or_read_sys(tool, ptypes, eta_edges, pt_edges)
        effects[esmodel] = sys_values
 
        log.debug("delete tool")
        del tool
 
    def sorting_function(sys):
        return max(
            np.abs(effects[esmodel][ptype].get(sys, np.zeros(1))).max()
            for esmodel in esmodels
            for ptype in ptypes
        )
 
    all_sys = set()
    for effects_esmodel in effects.values():
        for effects_particle in effects_esmodel.values():
            all_sys |= set(effects_particle.keys())
 
    if only_up:
        all_sys = set(s for s in all_sys if "__1up" in s)
    all_sys = set(s for s in all_sys if "RESOLUTION" not in s)
    sorted_sys = sorted(all_sys, key=sorting_function, reverse=True)
 
    log.info("plot")
    log.info("sorted sys: %s", sorted_sys)
    colors = sns.color_palette("Set2", len(esmodels))
    line_styles = "--", ":", "-"
 
    for ptype, (ieta, (eta1, eta2)) in tqdm.tqdm(
        product(ptypes, enumerate(pairwise(eta_edges))),
        total=len(ptypes) * (len(eta_edges) - 1),
        desc="plotting",
        leave=False,
    ):
        nsub_x, nsub_y = divide_square(len(sorted_sys))
        fig, axs = plt.subplots(nsub_x, nsub_y, figsize=(14, 8), sharex=True)
        if hasattr(axs, "flat"):
            axs = axs.flat
        else:
            axs = [axs]
        for ax, sys in zip(axs, sorted_sys):
            for iesmodel, esmodel in enumerate(esmodels):
                if sys in effects[esmodel][ptype]:
                    values = effects[esmodel][ptype][sys][:, ieta]
                    if abs_sys:
                        values = np.abs(values)
                else:
                    values = np.zeros_like(pt_midpoints)
                ax.plot(
                    pt_midpoints / 1e3,
                    values * 100,
                    label=esmodel,
                    ls=line_styles[iesmodel],
                    color=colors[iesmodel],
                )
 
            ylimits = [0.01, 0.3, 0.7, 2.1, 5]  # possible y-axis maxima
            for ylimit in ylimits:
                if max(np.abs(values)) * 100 < ylimit:
                    if abs_sys:
                        ax.set_ylim(0, ylimit)
                    else:
                        ax.set_ylim(-ylimit, ylimit)
                    break
 
            title = sys.replace("EG_SCALE_", "").replace("PH_SCALE_", "").replace("__1up", "")
            if len(title) > 17:
                title = title[:17] + "..."
            ax.set_title(title, fontsize=9)
            ax.yaxis.set_major_locator(MaxNLocator(6, prune="both"))
            ax.xaxis.set_major_locator(MaxNLocator(4))
            ax.tick_params(axis="both", which="major", labelsize=8)
            ax.tick_params(axis="y", which="minor", left="off", right="off")
 
            if log_x:
                ax.set_xscale("log")
            ax.set_ylabel("")
 
        for ax in axs:
            if ax.is_last_row():
                ax.set_xlabel("$p_{T}$ [GeV]", fontsize=11)
            if ax.is_first_col():
                ax.set_ylabel("effect [%]", fontsize=11)
        fig.subplots_adjust(wspace=0.4, hspace=0.27, bottom=0.15)
 
        handles = [
            mlines.Line2D([], [], color=colors[i], ls=line_styles[i]) for i in range(len(esmodels))
        ]
        labels = esmodels
        fig.legend(
            handles,
            labels,
            ncol=len(esmodels),
            loc="upper center",
            bbox_to_anchor=(0.1, -0.14, 0.7, 0.2),
            mode="expand",
            borderaxespad=0.0,
        )
 
        fig.suptitle(r"%s $|\eta|\in [%.2f, %.2f]$" % (ptype, eta1, eta2), fontsize=14)
 
        figname = "compare_sys_%s_eta_%.2f_%.2f_vs_pT" % (ptype, eta1, eta2)
        log.info("saving %s", figname)
        for extension in extensions:
            fig.savefig(os.path.join(basedir, "%s.%s" % (figname, extension)))
        plt.close(fig)
 
 
@timed

compare_two_tools_eta()

plot.compare_two_tools_eta	(		tool1,
			tool2,
			pt,
			simulation,
			name,
			basedir,
			title,
			particle = "unconverted" )

Definition at line 1263 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    etas = np.arange(-4.5, 4.5, 0.01)
    r1 = calibrate_eta_pt(tool1, etas, [pt], simulation, particle)
    r2 = calibrate_eta_pt(tool2, etas, [pt], simulation, particle)
    r = r1 / r2 - 1
    r = r[0]
    print(r)
    f, ax = plt.subplots()
    r = np.nan_to_num(r)
    ax.plot(etas, r * 100)
    ax.set_xlabel(r"$\eta$")
    ax.set_ylabel("effect [%]")
    ax.set_title(title)
    ax.axis("tight")
    ax.grid()
    for extension in extensions:
        f.savefig(os.path.join(basedir, name + "." + extension))
    plt.close(f)
 
 

compare_two_tools_eta_phi()

plot.compare_two_tools_eta_phi	(		tool1,
			tool2,
			pt,
			simulation,
			name,
			basedir,
			title,
			particle = "unconverted" )

Definition at line 1285 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    etas = np.arange(-4.5, 4.5, 0.1)
    phis = np.arange(-np.pi, np.pi, 0.1)
    r1 = eval_sys_eta_phi(tool1, etas, phis, pt, simulation, particle)
    r2 = eval_sys_eta_phi(tool2, etas, phis, pt, simulation, particle)
    r = r1 / r2 - 1
    f, ax = plt.subplots()
    m = np.max(np.abs(r))
    p = ax.pcolormesh(phis, etas, r * 100, vmin=-m * 100, vmax=m * 100)
    ax.set_xlabel(r"$\phi$")
    ax.set_ylabel(r"$\eta$")
    ax.set_title(title)
    ax.axis("tight")
    cb = f.colorbar(p)
    cb.ax.set_ylabel("ratio to nominal [%]")
    for extension in extensions:
        f.savefig(os.path.join(basedir, name + "." + extension))
    plt.close(f)
 
 

compare_two_tools_eta_pt()

plot.compare_two_tools_eta_pt	(		tool1,
			tool2,
			simulation,
			name,
			basedir,
			title,
			particle = "unconverted" )

Definition at line 1307 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    etas = np.arange(-4.5, 4.5, 0.05)
    pts = np.logspace(3.2, 6, 50)
    r1 = calibrate_eta_pt(tool1, etas, pts, simulation, particle)
    r2 = calibrate_eta_pt(tool2, etas, pts, simulation, particle)
    r = r1 / r2 - 1
    f, ax = plt.subplots()
    r = np.nan_to_num(r)
    m = np.max(np.abs(r))
    p = ax.pcolormesh(etas, pts / 1e3, r * 100, vmin=-m * 100, vmax=m * 100)
    ax.set_yscale("log")
    ax.set_ylabel("$p_T$ [GeV]")
    ax.set_xlabel(r"$\eta$")
    ax.set_title(title)
    ax.axis("tight")
 
    cb = f.colorbar(p)
    cb.ax.set_ylabel("ratio to nominal [%]")
    for extension in extensions:
        f.savefig(os.path.join(basedir, name + "." + extension))
    plt.close(f)
 
 

compute_or_read_sys()

plot.compute_or_read_sys	(		tool,
			ptypes,
			eta_edges,
			pt_edges )

Definition at line 794 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def compute_or_read_sys(tool, ptypes, eta_edges, pt_edges):
    empty_set = ROOT.CP.SystematicSet()
 
    eta_edges = np.asarray(eta_edges)
    pt_edges = np.asarray(pt_edges)
 
    # TODO: replace midpoints with supersampling
    eta_midpoints = 0.5 * (eta_edges[1:] + eta_edges[:-1])
    pt_midpoints = 0.5 * (pt_edges[1:] + pt_edges[:-1])
 
    log.debug("getting list of systematics")
    all_syst = tool.recommendedSystematics()
    log.debug("%d systematics found", len(all_syst))
 
    results = {ptype: {} for ptype in ptypes}
 
    with tqdm.tqdm(total=len(ptypes) * (len(all_syst) + 1), leave=False) as pbar:
        for iptype, ptype in enumerate(ptypes):
            log.debug("computing for particle=%s", ptype)
            tool.applySystematicVariation(empty_set)
            log.debug(
                "computing nominal energies for eta=%s, pt=%s, particle=%s",
                eta_midpoints,
                pt_midpoints,
                ptype,
            )
 
            values_nominal = calibrate_eta_pt(tool, eta_midpoints, pt_midpoints, particle=ptype)
            pbar.update(1)
 
            for isys, sys in enumerate(all_syst):
                sys_name = sys.name()
                sys_set = ROOT.CP.SystematicSet()
                sys_set.insert(sys)
                tool.applySystematicVariation(sys_set)
                values_sys = calibrate_eta_pt(tool, eta_midpoints, pt_midpoints, particle=ptype)
                ratio = values_sys / values_nominal - 1
 
                results[ptype][sys_name] = ratio
                pbar.update(1)
 
    return results
 
 
@timed

divide_square()

plot.divide_square	(		n,
			horizontal = True )

divide a figure into a square number of subplots in an optimized way 

Definition at line 115 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def divide_square(n, horizontal=True):
    """ divide a figure into a square number of subplots in an optimized way """
    if horizontal:
        x = np.ceil(np.sqrt(n))
        y = np.floor(np.sqrt(n))
        if (x * y) < n:
            x += 1
    else:
        x = np.floor(np.sqrt(n))
        y = np.ceil(np.sqrt(n))
        if (x * y) < n:
            y += 1
    return int(x), int(y)
 
 

eval_eta_slice()

plot.eval_eta_slice	(		tool,
			etas,
			pts,
			ptype,
			only_material = False,
			only_up = True )

Definition at line 225 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def eval_eta_slice(tool, etas, pts, ptype, only_material=False, only_up=True):
    sys_set = ROOT.CP.SystematicSet()
    tool.applySystematicVariation(sys_set)
    nominal = calibrate_eta_pt(tool, etas, pts, particle=ptype)
    all_syst = tool.recommendedSystematics()
 
    results = {}
    for sys in all_syst:
        sys_name = sys.name()
        if "RESOLUTION" in sys_name:
            continue
        if "1down" in sys_name and only_up:
            continue
        if only_material:
            if "MAT" not in sys_name:
                continue
        log.info("computing sys %s, %d eta samplings", sys_name, len(etas))
        sys_set = ROOT.CP.SystematicSet()
        sys_set.insert(sys)
        tool.applySystematicVariation(sys_set)
 
        sys = calibrate_eta_pt(tool, etas, pts, particle=ptype)
 
        ratio = sys / nominal
 
        ratio = np.average(ratio - 1, axis=1)  # average the supersampling
        results[sys_name] = ratio
    return results
 
 

eval_sys_eta_phi()

plot.eval_sys_eta_phi	(		tool,
			etas,
			phis,
			pt,
			simulation,
			particle = "unconverted" )

Definition at line 205 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def eval_sys_eta_phi(tool, etas, phis, pt, simulation, particle="unconverted"):
    event = ROOT.xAOD.TEvent()
    factory = ROOT.EgammaFactory()
    result = np.ones((len(etas), len(phis)))
    ei = factory.create_eventinfo(simulation, 100000)
    for ieta, eta in enumerate(etas):
        for iphi, phi in enumerate(phis):
            if particle == "unconverted":
                p = factory.create_photon(eta, phi, pt * np.cosh(eta), 0)
            elif particle == "converted":
                p = factory.create_photon(eta, phi, pt * np.cosh(eta), 100)
            elif particle == "electron":
                p = factory.create_electron(eta, phi, pt * np.cosh(eta))
            else:
                raise ValueError()
            result[ieta, iphi] = tool.getEnergy(p, ei)
    del event
    return result
 
 

generator_photon()

plot.generator_photon

(

self

)

Definition at line 169 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def generator_photon(self):
    store = ROOT.xAOD.TStore()
 
    factory = ROOT.EgammaFactory(store)
    for eta in np.arange(-2.5, 2.5, 0.05):
        for e in np.arange(1e3, 1000e3, 100e3):
            photon = factory.create_photon(eta, 0.1, e, 0)
            yield photon
    store.clear()
 
 

histo2data()

plot.histo2data

(

histo

)

Definition at line 130 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def histo2data(histo):
    xs = []
    ys = []
    exs = []
    eys = []
    for ibin in range(1, histo.GetNbinsX() + 1):
        xs.append(histo.GetBinCenter(ibin))
        ys.append(histo.GetBinContent(ibin))
        eys.append(histo.GetBinError(ibin))
        exs.append(0.5 * histo.GetBinWidth(ibin))
    return np.array(xs), np.array(exs), np.array(ys), np.array(eys)
 
 

list_systematics()

plot.list_systematics	(		esmodels,
			decorrelation = "FULL_ETACORRELATED_v1" )

Definition at line 1655 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def list_systematics(esmodels, decorrelation="FULL_ETACORRELATED_v1"):
    if type(esmodels) is str:
        esmodels = [esmodels]
    elif esmodels is None:
        log.warning("no esmodel specified, using es2012c")
        esmodels = ["es2012c"]
    syslist_esmodel = {}
    for esmodel in esmodels:
        log.debug("creating tool for %s", esmodel)
        tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
        tool.setProperty("ESModel", esmodel)
        tool.setProperty("decorrelationModel", decorrelation)
        tool.initialize()
        syslist_esmodel[esmodel] = [s.name() for s in systematics_from_tool(tool, only_scale=False)]
 
    for esmodel, sys_list in syslist_esmodel.items():
        print("esmodel: %s %s UP variations" % (esmodel, len(sys_list)))
        for sysname in sys_list:
            print("   {:10s}".format(sysname))
 
    if len(esmodels) > 1:
        log.info("comparing the %s esmodels", len(esmodels))
        all_sys = set([item for sublist in syslist_esmodel.values() for item in sublist])
        print(" " * 40 + "".join(" [%d] " % i for i in range(len(esmodels))))
        for sysname in sorted(all_sys):
            cross = "".join(
                [
                    "  x  " if sysname in syslist_esmodel[esmodel] else "     "
                    for esmodel in esmodels
                ]
            )
            print(("{:40s}".format(sysname) + cross))
        for iesmodel, esmodel in enumerate(esmodels):
            print("[%d] = %s" % (iesmodel, esmodel))
 
 
@timed

main()

plot.main

(

)

Definition at line 1692 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def main():
    from argparse import ArgumentParser, RawDescriptionHelpFormatter
 
    parser = ArgumentParser(
        formatter_class=RawDescriptionHelpFormatter,
        epilog="""
to produce paper plots for systematics:
    python plot.py sys_eta_slices --beautify-sysnames --sys-order paper_run1 --superimpose-all --skip-null-sys --esmodels es2016PRE --min-sys-value -0.01 --max-sys-value 0.02 --symmetrize-labels  --pt-bins-logspace 5E3 1E6 100
 
    # python plot.py sys_eta_slices --beautify-sysnames --sys-order paper_run1 --superimpose-all --skip-null-sys --esmodels es2016data_mc15c_summer_improved --min-sys-value -0.01 --max-sys-value 0.02 --symmetrize-labels  --pt-bins-logspace 5E3 1E6 100
 
to produce paper plot for resolution (the name of the esmodels here are the ones used by the internal class)
   python plot.py resolution-err --esmodels es2017 --abs-sys --pt-bins-linspace 5E3 200E3 200
 
to compare systematics between tools vs pT:
    python plot.py compare_sys --particles electron converted unconverted --esmodels es2016data_mc15c_summer_improved es2016data_mc15c_summer --eta-bins 0 0.6 1.0 1.37 1.55 1.82 2.47 --pt-bins-logspace 5E3 1500E3 50 --abs-sys --log-x
 
to plot all systematics in a 2d plot (eta, pt):
    python plot.py all_sys --esmodel es2016data_mc15c_summer es2012c --decorrelation=FULL_ETACORRELATED_v1 --eta-bins-linspace -2.5 2.5 50 --pt-bins-linspace 15E3 100E3 50 --particles converted unconverted --sys-filters *LARCALIB* *LARELECUNCONV*
 
to produce scale factor correction (doScaleCorrection on/off):
    python plot.py scale --esmodels es2015PRE es2016data_mc15c_summer
 
to list the systematics:
    python plot.py list-systematics --esmodels es2012c es2016data_mc15c_summer es2016data_mc15c_summer_improved es2017_R21_PRE
""",
    )
    parser.add_argument(
        "action",
        choices=[
            "compare_sys",
            "compute_sys",
            "uA2MeV",
            "zee",
            "material",
            "scale",
            "cterm",
            "all",
            "gain",
            "uniformity",
            "sys_fixed_pt",
            "sys_eta_slices",
            "all_sys",
            "resolution",
            "fast",
            "resolution-err",
            "list-systematics",
        ],
        default="all",
        help="what to do",
    )
    parser.add_argument("--esmodels", nargs="*", help="esmodel to consider")
    parser.add_argument("--decorrelation", default="FULL_ETACORRELATED_v1")
    parser.add_argument(
        "--particles",
        nargs="*",
        help="the particle (electron/converted/unconverted)",
        default=["electron"],
    )
    parser.add_argument("--beautify-sysnames", action="store_true")
    parser.add_argument("--eta-bins", nargs="*", type=float, help="edges of the eta-bins")
    parser.add_argument(
        "--eta-bins-linspace", nargs=3, type=float, help="edge of the eta-bins as min max nbins"
    )
    parser.add_argument("--pt-bins", nargs="*", type=float, help="edges of the pt-bins")
    parser.add_argument(
        "--pt-bins-linspace", nargs=3, type=float, help="edge of the eta-bins as min max nbins"
    )
    parser.add_argument(
        "--pt-bins-logspace", nargs=3, type=float, help="edge of the eta-bins as min max nbins"
    )
    parser.add_argument(
        "--super-sampling-eta", type=int, default=5, help="how many point to average inside a bin"
    )
    parser.add_argument(
        "--sys-order",
        choices=["paper_run1", "paper_run2"],
        help="how to order systematics, options: paper_run1, paper_run2",
    )
    parser.add_argument("--debug", action="store_true")
    parser.add_argument(
        "--superimpose-all", action="store_true", help="superimpose sum of systematics"
    )
    parser.add_argument("--skip-null-sys", action="store_true", help="do not plot null systematics")
    parser.add_argument("--yrange", nargs=2, type=float)
    parser.add_argument("--add-down", action="store_true", help="plot also the down systematics")
    parser.add_argument(
        "--legend-outside", action="store_true", help="draw the legend outside the plot"
    )
    parser.add_argument("--symmetrize-labels", action="store_true")
    parser.add_argument(
        "--abs-sys", action="store_true", help="consider the abs value of the systeamatics"
    )
    parser.add_argument("--log-x", action="store_true", help="use log scale")
    parser.add_argument("--log-pt", action="store_true", help="use log scale for pT")
    parser.add_argument(
        "--sys-filters", nargs="*", help="list of wildcard to filter systematic names"
    )
    parser.add_argument("--min-sys-value", type=float, help="min value for the systematic axis")
    parser.add_argument("--max-sys-value", type=float, help="max value for the systematic axis")
    parser.add_argument("--grid", action="store_true", help="show grid")
    parser.add_argument(
        "--plot-qsum",
        action="store_true",
        help="plot the quadrature sum of the systematics for debug (should be equal to 1NP up)",
    )
    parser.add_argument(
        "--atlas-label", default="Internal", help='Internal, Preliminary, ..., use "" for papers'
    )
    args = parser.parse_args()
 
    if args.debug:
        log.setLevel(logging.DEBUG)
        log.debug("DEBUG activated")
 
    if args.eta_bins_linspace:
        args.eta_bins = np.linspace(
            args.eta_bins_linspace[0], args.eta_bins_linspace[1], int(args.eta_bins_linspace[2] + 1)
        )
    if args.pt_bins_linspace:
        args.pt_bins = np.linspace(
            args.pt_bins_linspace[0], args.pt_bins_linspace[1], int(args.pt_bins_linspace[2] + 1)
        )
    if args.pt_bins_logspace:
        args.pt_bins = np.logspace(
            np.log10(args.pt_bins_logspace[0]),
            np.log10(args.pt_bins_logspace[1]),
            int(args.pt_bins_logspace[2] + 1),
        )
 
    basedir = "plots"
    if not os.path.exists(basedir):
        os.makedirs(basedir)
 
    if args.action == "list-systematics":
        list_systematics(args.esmodels, args.decorrelation)
 
    if args.action == "compute_sys":
        log.info("computing systematics")
        for esmodel in args.esmodels or ["es2012c"]:
            tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
            tool.setProperty("ESModel", esmodel)
            tool.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
            tool.setProperty[bool]("doSmearing", 0)
            tool.initialize()
            result = compute_or_read_sys(tool, ["electron"], args.eta_bins, args.pt_bins)
            print(result)
 
    if args.action == "compare_sys":
        log.info("comparing systematics")
        compare_sys(
            args.esmodels,
            ptypes=args.particles,
            decorrelation=args.decorrelation,
            eta_edges=args.eta_bins,
            pt_edges=args.pt_bins,
            abs_sys=args.abs_sys,
            log_x=args.log_x,
        )
 
    if args.action == "resolution-err":
        log.info("plotting resolution error")
        plot_resolution_error(basedir="plots", **vars(args))
 
    if args.action == "zee" or args.action == "all":
        log.info("plotting scale systematics")
        plot_all_Zee_syst(etas=np.arange(-2.5, 2.5, 0.01), pt=100e3, basedir="plots")
 
    if args.action == "all" or args.action == "uA2MeV":
        log.info("plotting uA2MeV")
        tool_es2015PRE_nouA2MeV = ROOT.CP.EgammaCalibrationAndSmearingTool(
            "tool_es2015PRE_nouA2MeV"
        )
        tool_es2015PRE_nouA2MeV.setProperty("ESModel", "es2015PRE")
        tool_es2015PRE_nouA2MeV.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
        tool_es2015PRE_nouA2MeV.setProperty[bool]("doSmearing", 0)
        tool_es2015PRE_nouA2MeV.setProperty[bool]("use_uA2MeV_2015_first2weeks_correction", 0)
        tool_es2015PRE_nouA2MeV.initialize()
 
        tool_es2015PRE = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_es2015PRE")
        tool_es2015PRE.setProperty("ESModel", "es2015PRE")
        tool_es2015PRE.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
        tool_es2015PRE.setProperty[bool]("doSmearing", 0)
        tool_es2015PRE.initialize()
 
        compare_two_tools_eta(
            tool_es2015PRE,
            tool_es2015PRE_nouA2MeV,
            100e3,
            simulation=False,
            name="uA2MeV",
            basedir=basedir,
            title="with uA2MeV correction / without",
            particle="electron",
        )
 
        del tool_es2015PRE_nouA2MeV
        del tool_es2015PRE
 
    if args.action == "all" or args.action == "scale":
        log.info("plotting scales")
        plot_all_scales(
            esmodels=args.esmodels,
            labels=args.esmodels,
            basedir=basedir,
            etas=np.arange(-2.5, 2.5, 0.01),
            add_patch=False,
            debug=args.debug,
        )
    if args.action == "all" or args.action == "fast":
        log.info("plotting full / fast scale")
        check_fast(basedir, "es2015PRE")
        plot_all_scales(
            esmodels=("es2015PRE", ("es2015PRE", ("useFastSim",), (True,), (bool,))),
            labels=("2015PRE", "2015PRE FAST"),
            basedir=basedir,
            etas=np.arange(-2.5, 2.5, 0.01),
        )
    if args.action == "all" or args.action == "cterm":
        log.info("plotting smearings")
        plot_all_cterms(
            esmodels=("es2012c", "es2012XX", "es2015PRE"),
            labels=("2012", "new", "new + temp"),
            basedir=basedir,
            etas=np.arange(-2.5, 2.5, 0.01),
        )
 
    if args.action == "gain" or args.action == "all":
        check_gain(basedir, "es2015PRE")
 
    if args.action == "uniformity" or args.action == "all":
        check_uniformity(basedir, "es2012c")
        check_uniformity(basedir, "es2015PRE")
 
    if args.action == "sys_fixed_pt" or args.action == "all":
        tool_es2015PRE_notemp = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_es2015PRE_notemp")
        tool_es2015PRE_notemp.setProperty("ESModel", "es2015PRE")
        tool_es2015PRE_notemp.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
        tool_es2015PRE_notemp.setProperty[bool]("doSmearing", 0)
        tool_es2015PRE_notemp.setProperty[bool]("use_temp_correction201215", 0)
        tool_es2015PRE_notemp.initialize()
 
        compare_all_syst_fixed_pt(
            basedir,
            ("es2012c", tool_es2015PRE_notemp, "es2015PRE"),
            names=("es2012c", "es2015_no_temp", "es2015PRE"),
            labels=("es2012c", r"$\oplus$ 7/8 diff $\oplus$ 34/68 diff", r"$\oplus$ LAr temperature"),
        )
 
    if args.action == "sys_eta_slices" or args.action == "all":
        if not args.eta_bins:
            eta_bins = ((0.0, 0.6), (0.6, 1.45), (1.52, 1.7), (1.7, 1.9), (1.9, 2.5), (1.4, 1.6))
            log.warning("no eta-binning specified using %s", eta_bins)
        else:
            eta_bins = list(pairwise(args.eta_bins))
            log.info("eta-bin: %s", eta_bins)
        for ptype in "electron", "unconverted", "converted":
            log.debug("plot all sys FULL_ETACORRELATED_v1 eta slice %s", ptype)
            plot_all_syst_eta_slice(
                eta_bins,
                supersampling_eta=args.super_sampling_eta,
                esmodel=args.esmodels[0],
                decorrelation="FULL_ETACORRELATED_v1",
                ptype=ptype,
                basedir=basedir,
                beautify_sysnames=args.beautify_sysnames,
                sys_order=args.sys_order,
                superimpose_all=args.superimpose_all,
                skip_null_sys=args.skip_null_sys,
                max_sys=args.max_sys_value,
                min_sys=args.min_sys_value,
                debug=args.debug,
                only_up=not args.add_down,
                symmetrize_labels=args.symmetrize_labels,
                legend_outside=args.legend_outside,
                pts=args.pt_bins,
                log_x=args.log_x,
                plot_qsum=args.plot_qsum,
                abs_sys=args.abs_sys,
                atlas_label=args.atlas_label,
            )
 
    if args.action == "material" or args.action == "all":
        if not os.path.exists("material"):
            os.makedirs("material")
        etabins = ((0.0, 0.6), (0.6, 1.45), (1.52, 1.7), (1.7, 1.9), (1.9, 2.5))
        for ptype in "electron", "unconverted", "converted":
            plot_all_syst_eta_slice(
                etabins,
                supersampling_eta=args.super_sampling_eta,
                esmodel=args.esmodels[0],
                decorrelation="FULL_ETACORRELATED_v1",
                ptype=ptype,
                basedir="material",
                only_material=True,
                beautify_sysnames=args.beautify_sysnames,
                sys_order=args.sys_order,
                skip_null_sys=args.skip_null_sys,
                max_sys=args.max_sys_value,
                min_sys=args.min_sys_value,
                debug=args.debug,
                only_up=not args.add_down,
                legend_outside=args.legend_outside,
                symmetrize_labels=args.symmetrize_labels,
                log_x=args.log_x,
                plot_qsum=args.plot_qsum,
                abs_sys=args.abs_sys,
                atlas_label=args.atlas_label,
            )
 
    if args.action == "all_sys" or args.action == "all":
        for esmodel in args.esmodels:
            for ptype in args.particles:
                log.info("plotting sys for %s %s", ptype, esmodel)
                plot_all_syst_eta_pt(
                    esmodel=esmodel,
                    decorrelation=args.decorrelation,
                    ptype=ptype,
                    basedir=basedir,
                    eta_range=args.eta_bins,
                    pt_range=args.pt_bins,
                    log_pt=args.log_pt,
                    abs_sys=args.abs_sys,
                    sys_filters=args.sys_filters,
                    min_value=args.min_sys_value,
                    max_value=args.max_sys_value,
                )
 
    if args.action == "resolution" or args.action == "all":
        tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
        tool.setProperty("ESModel", "es2015PRE")
        tool.initialize()
        pts = np.logspace(3.2, 6, 50)
        etas = np.linspace(-2.49, 2.49, 100)
        plot_resolution_eta_pt(
            basedir, tool, pts, etas, "electron", title="resolution electron es2015PRE"
        )
        plot_resolution_eta_pt(
            basedir, tool, pts, etas, "converted", title="resolution converted es2015PRE"
        )
        plot_resolution_eta_pt(
            basedir, tool, pts, etas, "unconverted", title="resolution unconverted es2015PRE"
        )
 
 

pairwise()

plot.pairwise

(

iterable

)

Definition at line 108 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def pairwise(iterable):
    "s -> (s0,s1), (s1,s2), (s2, s3), ..."
    a, b = tee(iterable)
    next(b, None)
    return zip(a, b)
 
 

partition()

plot.partition	(		x,
			n )

Definition at line 157 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def partition(x, n):
    r = []
    for xx in x:
        r.append(xx)
        if len(r) == n:
            yield r
            r = []
            continue
    if len(r) > 0:
        yield r
 
 

plot_all_cterms()

plot.plot_all_cterms	(		esmodels,
			basedir,
			labels = None,
			etas = np.arange(-4.5, 4.5, 0.01) )

Definition at line 1202 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_all_cterms(esmodels, basedir, labels=None, etas=np.arange(-4.5, 4.5, 0.01)):  # noqa: B008 (used as constant)
    labels = labels or esmodels
    cterms_all_models = {}
    for esmodel, label in zip(esmodels, labels):
 
        tool_with = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_with")
        tool_with.setProperty("ESModel", esmodel)
        tool_with.setProperty[bool]("doSmearing", 1)
        tool_with.initialize()
 
        tool_without = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_without")
        tool_without.setProperty("ESModel", esmodel)
        tool_without.setProperty[bool]("doSmearing", 0)
        tool_without.initialize()
 
        event = ROOT.xAOD.TEvent()  # noqa: F841
        factory = ROOT.EgammaFactory()
        ei = factory.create_eventinfo(True, 100000)
 
        cterms = []
        for eta in etas:
            el = factory.create_electron(eta, 0.1, 40e3)
            en_without = tool_without.getEnergy(el, ei)
            ratios = np.zeros(1000)
            for repetition in range(1000):
                en_with = tool_with.getEnergy(el, ei)
                ratios[repetition] = en_with / en_without
            cterms.append(np.std(ratios))
        cterms_all_models[label] = cterms
 
    f, ax = plt.subplots()
    for k, v in cterms_all_models.items():
        ax.plot(etas, v, label=k)
    ax.set_xlabel(r"$\eta$")
    ax.set_ylabel("std (energy with additional cterm / energy without)")
 
    ax.add_patch(
        patches.Rectangle(
            (-2.47, 0.028 - 0.027),
            +2.47 - 1.55,
            2 * 0.027,
            alpha=0.4,
            label="13 TeV cterm 3 bins",
            color="k",
        )
    )
    ax.add_patch(
        patches.Rectangle((-1.37, -0.003 - 0.014), +1.37 * 2, 2 * 0.014, alpha=0.4, color="k")
    )
    ax.add_patch(
        patches.Rectangle((1.55, 0.028 - 0.027), +2.47 - 1.55, 2 * 0.027, alpha=0.4, color="k")
    )
    ax.set_ylim(-0.03, 0.06)
 
    ax.grid()
    ax.legend()
    for extension in extensions:
        f.savefig(os.path.join(basedir, "cterms.%s" % extension))
    plt.close(f)
 
 

plot_all_scales()

plot.plot_all_scales	(		esmodels,
			basedir,
			labels = None,
			etas = np.arange(-4.5, 4.5, 0.01),
			add_patch = False,
			debug = False  # noqa: B008 (range used as constant) )

Definition at line 1078 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    log.info("comparing scale factors %s", esmodels)
    log.warning("<mu> fixed")
    labels = labels or esmodels
    scales = {}
 
    for esmodel, label in zip(esmodels, labels):
        energy_with = []
        energy_without = []
 
        key_properties = []
        value_properties = []
        type_properties = []
 
        if type(esmodel) is not str:
            key_properties = esmodel[1]
            value_properties = esmodel[2]
            type_properties = esmodel[3]
            esmodel = esmodel[0]
 
        tool_with = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_with")
        tool_without = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_without")
 
        for tool in tool_with, tool_without:
            if debug:
                tool.msg().setLevel(0)
            tool.setProperty("ESModel", esmodel)
            tool.setProperty[bool]("doSmearing", 0)
            for k, v, t in zip(key_properties, value_properties, type_properties):
                tool.setProperty[t](k, v)
 
        tool_with.setProperty[bool]("doScaleCorrection", 1)
        tool_without.setProperty[bool]("doScaleCorrection", 0)
 
        tool_with.initialize()
        tool_without.initialize()
 
        event = ROOT.xAOD.TEvent()  # noqa: F841
        factory = ROOT.EgammaFactory()
        log.warning("using eveninfo 266904")
        ei = factory.create_eventinfo(False, 266904)
 
        for eta in etas:
            el = factory.create_electron(eta, 0.1, 40e3)
            en_with = tool_with.getEnergy(el, ei)
            en_without = tool_without.getEnergy(el, ei)
            energy_with.append(en_with)
            energy_without.append(en_without)
        scales[label] = np.array(energy_without) / np.array(energy_with) - 1
 
    f, ax = plt.subplots()
    for k, v in scales.items():
        ax.plot(etas, v * 100, label=k)
    ax.set_xlabel(r"$\eta$", fontsize=15, x=1, ha="right")
    ax.set_ylabel("energy without scale factors / energy with scale factors - 1 [%]", fontsize=10)
    ax.grid()
 
    if add_patch:
        ax.add_patch(
            patches.Rectangle(
                (-2.47, -0.013 * 100 - 0.0168 * 100),
                +2.47 - 1.55,
                2 * 0.0168 * 100,
                alpha=0.4,
                label="13 TeV scales 3 bins",
                color="k",
            )
        )
        # ax.add_patch(patches.Rectangle((-1.55, 0.00419 * 100 - 0.001 * 100), +1.55 - 1.37, 2 * 0.001 * 100, alpha=0.4, color='k'))
        ax.add_patch(
            patches.Rectangle(
                (-1.37, -0.0121 * 100 - 0.0052 * 100),
                2 * +1.37,
                2 * 0.0052 * 100,
                alpha=0.4,
                color="k",
            )
        )
        ax.add_patch(
            patches.Rectangle(
                (1.55, -0.013 * 100 - 0.0168 * 100),
                +2.47 - 1.55,
                2 * 0.0168 * 100,
                alpha=0.4,
                color="k",
            )
        )
 
        ax.add_patch(
            patches.Rectangle(
                (-2.47, -0.00649344 * 100 - 0.00465043 * 100),
                +2.47 * 2,
                2 * 0.00465043 * 100,
                alpha=0.5,
                label="13 TeV scales 1 bin",
                color="orange",
            )
        )
 
    ax.legend()
 
    for extension in extensions:
        f.savefig(os.path.join(basedir, "scales.%s" % extension))
    plt.close(f)
 
    # ratio plot
    reference = labels[0]
    ratio = {label: scales[label] - scales[reference] for label in labels}
    f, ax = plt.subplots()
    for k, v in ratio.items():
        ax.plot(etas, v, label=k)
    ax.set_xlabel(r"$\eta$", fontsize=15, x=1, ha="right")
    ax.set_ylabel("scales - scales (%s)" % reference, fontsize=10)
    ax.grid()
    ax.legend()
    f.tight_layout()
 
    for extension in extensions:
        f.savefig(os.path.join(basedir, "scales_difference_%s.%s" % (reference, extension)))
    plt.close(f)
 
 

plot_all_syst_eta_pt()

plot.plot_all_syst_eta_pt	(		esmodel = "es2012c",
			decorrelation = "FULL_v1",
			ptype = "unconverted",
			basedir = "plots",
			eta_range = None,
			pt_range = None,
			log_pt = False,
			abs_sys = False,
			only_up = False,
			sys_filters = None,
			min_value = None,
			max_value = None )

Plot a 2D map (eta, pT) of the value of the systematic in %

Definition at line 989 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    """
    Plot a 2D map (eta, pT) of the value of the systematic in %
    """
    log.debug("creating tool")
    tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
    tool.setProperty("ESModel", esmodel)
    tool.setProperty("decorrelationModel", decorrelation)
    tool.setProperty[int]("doSmearing", 0)
    log.warning("setting randomRunNumber to 297730")
    tool.setProperty[int]("randomRunNumber", 297730)
    tool.initialize()
 
    etas = eta_range if eta_range is not None else np.arange(-3, 3, 0.1)
    pts = pt_range if pt_range is not None else np.logspace(4, 7, 100)
 
    nominal = calibrate_eta_pt(tool, etas, pts, particle=ptype)
 
    all_syst = tool.recommendedSystematics()
 
    nplotted = 0
 
    for sys in tqdm.tqdm(all_syst):
        sys_name = sys.name()
        if "RESOLUTION" in sys_name:
            log.debug("skipping %s", sys_name)
            continue
        if only_up and "1up" not in sys_name:
            log.debug("skipping %s", sys_name)
            continue
        if sys_filters is not None:
            if not any(fnmatch(sys_name, sys_filter) for sys_filter in sys_filters):
                log.debug("skipping %s", sys_name)
                continue
        nplotted += 1
        log.info("computing sys %s", sys_name)
 
        sys_set = ROOT.CP.SystematicSet()
        sys_set.insert(sys)
        tool.applySystematicVariation(sys_set)
 
        sys = calibrate_eta_pt(tool, etas, pts, particle=ptype)
 
        ratio = sys / nominal
        ratio[nominal == 0] = 1
        # TODO: check why nan
        ratio[np.isnan(ratio)] = 1
        ratio = ratio - 1
        vmax = max_value or np.percentile(np.abs(ratio), 95)
        if abs_sys:
            ratio = np.abs(ratio)
 
        f, ax = plt.subplots()
        p = ax.pcolormesh(etas, pts / 1e3, ratio * 100.0, vmin=-vmax * 100, vmax=vmax * 100)
        ax.set_title("%s\n%s\n%s" % (ptype, esmodel, sys_name), loc="left")
        ax.set_xlabel(r"$\eta$", x=1.0, ha="right")
        ax.set_ylabel(r"$p_T$ [GeV]", y=1.0, ha="right")
        if log_pt:
            ax.set_yscale("log")
        cb = f.colorbar(p)
        cb.ax.set_ylabel("systematic effect [%]")
        for extension in extensions:
            f.savefig(
                os.path.join(
                    basedir, "%s_%s_%s_%s.%s" % (ptype, esmodel, decorrelation, sys_name, extension)
                )
            )
        plt.close(f)
 
    if nplotted == 0:
        log.warning("no systematic plotted")
    else:
        log.info("%d systematic plotted", nplotted)
 
 
@timed

plot_all_syst_eta_slice()

plot.plot_all_syst_eta_slice	(		etabins,
			supersampling_eta = 3,
			esmodel = "es2012c",
			decorrelation = "FULL_v1",
			ptype = "unconverted",
			pts = np.logspace(np.log10(5e3), 6, 100),
			basedir = "plot",
			only_material = False,
			beautify_sysnames = False,
			sys_order = None,
			superimpose_all = False,
			skip_null_sys = False,
			min_sys = -0.02,
			max_sys = 0.02,
			only_up = True,
			debug = False,
			legend_outside = False,
			symmetrize_labels = False,
			log_x = False,
			plot_qsum = False,
			abs_sys = False,
			atlas_label = "Internal" )

Definition at line 295 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

):
    tool = ROOT.CP.EgammaCalibrationAndSmearingTool("tool")
    tool.setProperty("ESModel", esmodel)
    tool.setProperty("decorrelationModel", decorrelation)
    tool.setProperty[bool]("doSmearing", 0)
    log.warning("setting randomRunNumber to 297730")
    tool.setProperty[int]("randomRunNumber", 297730)
    if debug:
        tool.msg().setLevel(0)
 
    tool.initialize()
 
    if superimpose_all:
        tool_all = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_all")
        tool_all.setProperty("ESModel", esmodel)
        tool_all.setProperty("decorrelationModel", "1NP_v1")
        tool_all.setProperty[bool]("doSmearing", 0)
        log.warning("setting randomRunNumber to 297730")
        tool_all.setProperty[int]("randomRunNumber", 297730)
        tool_all.initialize()
 
    # compute the eta-inclusive one, just to sort
    log.info("compute sys inclusively, just to sort sys by importance")
    results = eval_eta_slice(
        tool,
        np.linspace(-2.5, 2.5, 20),
        np.linspace(10e3, 200e3, 10),  # use this range to mimic the range in the paper
        ptype,
        only_material,
    )
    sorted_sys_name = sorted(list(results), key=lambda k: -np.max(np.abs(results[k])))
    if skip_null_sys:
        sorted_sys_name = [
            sys_name for sys_name in sorted_sys_name if np.sum(results[sys_name]) != 0
        ]
    if sys_order is not None:
        if sys_order == "paper_run1":
            partitions = [
                [
                    "EG_SCALE_PS__1up",
                    "EG_SCALE_S12__1up",
                    "EG_SCALE_LARCALIB__1up",
                    "EG_SCALE_L2GAIN__1up",
                ],
                [
                    "EG_SCALE_MATID__1up",
                    "EG_SCALE_MATCRYO__1up",
                    "EG_SCALE_MATCALO__1up",
                    "EG_SCALE_ZEESYST__1up",
                ],
            ]
            if esmodel == "es2016PRE":
                partitions += [
                    [
                        "EG_SCALE_PEDESTAL__1up",
                        "EG_SCALE_LARCALIB_EXTRA2015PRE__1up",
                        "EG_SCALE_LARTEMPERATURE_EXTRA2016PRE__1up",
                        "EG_SCALE_E4SCINTILLATOR__1up",
                    ]
                ]
        elif sys_order == "paper_run2":
            partitions = [
                [
                    "EG_SCALE_PS__1up",
                    "EG_SCALE_S12__1up",
                    "EG_SCALE_LARCALIB__1up",
                    "EG_SCALE_LARCALIB_EXTRA2015PRE__1up",
                    "EG_SCALE_S12EXTRALASTETABINRUN2",
                ],
                [
                    "EG_SCALE_MATID__1up",
                    "EG_SCALE_MATCRYO__1up",
                    "EG_SCALE_MATCALO__1up",
                    "EG_SCALE_MATPP0__1up",
                    "EG_SCALE_ZEESYST__1up",
                ],
                [
                    "EG_SCALE_L2GAIN__1up",
                    "EG_SCALE_WTOTS1__1up",
                    "EG_SCALE_PEDESTAL__1up",
                    "EG_SCALE_E4SCINTILLATOR__1up",
                ],
                [
                    "PH_SCALE_CONVEFFICIENCY__1up",
                    "PH_SCALE_CONVFAKERATE__1up",
                    "PH_SCALE_CONVRADIUS__1up",
                    "PH_SCALE_LEAKAGECONV__1up",
                    "PH_SCALE_LEAKAGEUNCONV__1up",
                ],
            ]
        else:
            raise ValueError("cannot understand sys_order = %s" % sys_order)
        flat_list = [item for sublist in partitions for item in sublist]
        remainers = [item for item in sorted_sys_name if item not in flat_list]
        partitions = chain(partitions, partition(remainers, 4))
    else:
        partitions = partition(sorted_sys_name, 4)
    partitions = list(partitions)
 
    for etamin, etamax in tqdm.tqdm(etabins):
        log.info("plotting eta range %.2f %.2f", etamin, etamax)
        etas = np.linspace(etamin, etamax, supersampling_eta + 2)[1:-1]
        results = eval_eta_slice(tool, etas, pts, ptype, only_material, only_up=only_up)
        result_values = np.array(list(results.values()))
        qsum = np.sqrt((result_values ** 2).sum(axis=0))
 
        if superimpose_all:
            results_all = eval_eta_slice(tool_all, etas, pts, ptype, only_up=False)
 
        for ip, p in enumerate(partitions):
            log.info("plotting %d/%d", ip + 1, len(partitions))
 
            f, ax = plt.subplots()
            if superimpose_all:
                # max_up_down = np.max(np.abs([results_all["EG_SCALE_ALL__1down"],
                # results_all["EG_SCALE_ALL__1up"]]), axis=0)
                # ax.fill_between(pts / 1E3, -max_up_down * 100., max_up_down * 100,
                # color='0.8', label='total')
                # ax.plot(pts/1E3, np.sqrt(np.sum([r ** 2 for r in results.values()], axis=0)) * 100., 'r:')
                if only_up:
                    if abs_sys:
                        ax.fill_between(
                            pts / 1e3,
                            0,
                            results_all["EG_SCALE_ALL__1up"] * 100,
                            color="0.8",
                            label="Total",
                        )
                    else:
                        ax.fill_between(
                            pts / 1e3,
                            -results_all["EG_SCALE_ALL__1up"] * 100.0,
                            results_all["EG_SCALE_ALL__1up"] * 100,
                            color="0.8",
                            label="Total",
                        )
                else:
                    ax.fill_between(
                        pts / 1e3,
                        results_all["EG_SCALE_ALL__1down"] * 100.0,
                        results_all["EG_SCALE_ALL__1up"] * 100,
                        color="0.8",
                        label="Total",
                    )
            for isys, sys_name in enumerate(p):
                color = "C%d" % isys  # TODO: fix, use cycle
                if sys_name not in results:
                    continue  # TODO: FIXME
                r = results[sys_name]
                r[np.isnan(r)] = 0
                sys_label = (
                    beautify_sysname(sys_name.replace("__1up", ""))
                    if beautify_sysnames
                    else sys_name
                )
                if not only_up:
                    sys_label += " UP"
                if abs_sys:
                    mask_positive = r >= 0
                    r = np.abs(r)
                    ax.plot(
                        pts[mask_positive] / 1e3,
                        r[mask_positive] * 100.0,
                        label=sys_label,
                        color=color,
                    )
                    ax.plot(pts[~mask_positive] / 1e3, r[~mask_positive] * 100.0, "--", color=color)
                else:
                    ax.plot(pts / 1e3, r * 100.0, label=sys_label, color=color)
 
            if not only_up:
                ax.set_prop_cycle(None)
                for sys_name in p:
                    sys_name = sys_name.replace("up", "down")
                    if sys_name not in results:
                        continue  # TODO: FIXME
                    r = results[sys_name]
                    r[np.isnan(r)] = 0
                    sys_label = (
                        beautify_sysname(sys_name.replace("__1down", ""))
                        if beautify_sysnames
                        else sys_name
                    )
                    sys_label += " DOWN"
                    ax.plot(pts / 1e3, r * 100.0, label=sys_label, linestyle="--")
 
            if plot_qsum:
                ax.plot(pts / 1e3, qsum * 100, label="quadrature sum", linestyle=":")
 
            ax.set_xlabel("$E_T$ [GeV]", ha="right", x=1.0, fontsize=19)
            if abs_sys:
                ax.set_ylabel("Uncertainty [%]", ha="right", y=1.0, fontsize=19)
            else:
                ax.set_ylabel("Signed uncertainty [%]", ha="right", y=1.0, fontsize=19)
 
            ax.tick_params(axis="both", which="major", labelsize=17)
 
            ax.axis("tight")
 
            if max_sys is None and min_sys is None:
                max_sys = max(2, np.max(np.abs(ax.get_ylim())))
                min_sys = -max_sys
 
            ax.set_ylim(min_sys * 100, max_sys * 100)
 
            if legend_outside:
                ax.legend(
                    bbox_to_anchor=(0.0, 1.0, 1, 0.2),
                    mode="expand",
                    borderaxespad=0.0,
                    loc=3,
                    frameon=True,
                    fontsize=17 if only_up else 14,
                    borderpad=1,
                    ncol=1 if only_up else 2,
                )
                f.subplots_adjust(top=0.65)
                plot_ATLAS(f, 0.2, 0.58, label=atlas_label)
                f.text(0.2, 0.2, beautify_particle(ptype), transform=ax.transAxes, fontsize=16)
                f.text(
                    0.2,
                    0.25,
                    r"$%.2f < \eta < %.2f$" % (etamin, etamax),
                    transform=ax.transAxes,
                    fontsize=16,
                )
            else:
                ax.legend(
                    loc=1,
                    frameon=False,
                    fontsize=13 if only_up else 9,
                    borderpad=1,
                    ncol=1 if only_up else 2,
                )
 
                plot_ATLAS(f, 0.16, 0.80, label=atlas_label, fontsize=19)
                f.text(0.16, 0.74, beautify_particle(ptype), transform=ax.transAxes, fontsize=16)
                f.text(
                    0.16,
                    0.68,
                    r"$%.2f < \eta < %.2f$" % (etamin, etamax),
                    transform=ax.transAxes,
                    fontsize=16,
                )
 
            if log_x:
                ax.set_xscale("log")
 
            for extension in extensions:
                f.savefig(
                    os.path.join(
                        basedir,
                        "%s_%s_%s_%.2f_%.2f_%d.%s"
                        % (ptype, esmodel, decorrelation, etamin, etamax, ip, extension),
                    ),
                    bbox_inches="tight",
                )
            plt.close(f)
 
 

plot_all_syst_fixed_pt()

plot.plot_all_syst_fixed_pt	(		tools,
			names,
			labels,
			pt = 100e3,
			ptype = "unconverted",
			basedir = "plots" )

Definition at line 758 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_all_syst_fixed_pt(tools, names, labels, pt=100e3, ptype="unconverted", basedir="plots"):
    for tool in tools:
        empty_set = ROOT.CP.SystematicSet()
        tool.applySystematicVariation(empty_set)
    etas_histo = np.linspace(-5, 5, 101, True)
    etas = 0.5 * (etas_histo[1:] + etas_histo[:-1])
    nominals = [calibrate_eta_pt(tool, etas, [pt], particle=ptype)[0] for tool in tools]
    all_syst = tools[0].recommendedSystematics()
    for sys in all_syst:
        sys_name = sys.name()
        sys_set = ROOT.CP.SystematicSet()
        sys_set.insert(sys)
        log.info("plotting sys %s %s", sys_name, ptype)
 
        f, ax = plt.subplots()
 
        for tool, nominal, name, label in zip(tools, nominals, names, labels):
            tool.applySystematicVariation(sys_set)
            sys = calibrate_eta_pt(tool, etas, [pt], particle=ptype)[0]
            ratio = sys / nominal - 1
            ax.plot(etas, ratio * 100, label=label)
            histo = values2histo(name + "_" + sys_name, label, etas_histo, ratio * 100)
            fout.WriteTObject(histo)
 
        ax.grid()
        ax.legend()
        ax.set_ylabel("effect [%]")
        ax.set_title(ptype + " " + sys_name + " at $p_{T}$ = %.2f GeV" % (pt / 1e3))
        ax.set_xlabel(r"$\eta$")
        for extension in extensions:
            f.savefig(
                os.path.join(basedir, "%s_%s_pt_%.2f.%s" % (ptype, sys_name, pt / 1e3, extension))
            )
        plt.close(f)
 
 

plot_all_Zee_syst()

plot.plot_all_Zee_syst	(		etas,
			pt = 100e3,
			basedir = "plots" )

Definition at line 588 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_all_Zee_syst(etas, pt=100e3, basedir="plots"):
 
    tool_es2012c = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_es2012c")
    tool_es2012c.setProperty("ESModel", "es2012c")
    tool_es2012c.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_es2012c.setProperty[int]("doSmearing", 0)
    tool_es2012c.initialize()
 
    tool_es2015PRE = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_es2015PRE")
    tool_es2015PRE.setProperty("ESModel", "es2015PRE")
    tool_es2015PRE.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_es2015PRE.setProperty[bool]("doSmearing", 0)
    tool_es2015PRE.initialize()
 
    tool_es2015PRE_notemp = ROOT.CP.EgammaCalibrationAndSmearingTool("tool_es2015PRE_notemp")
    tool_es2015PRE_notemp.setProperty("ESModel", "es2015PRE")
    tool_es2015PRE_notemp.setProperty("decorrelationModel", "FULL_ETACORRELATED_v1")
    tool_es2015PRE_notemp.setProperty[bool]("doSmearing", 0)
    tool_es2015PRE_notemp.setProperty[int]("use_temp_correction201215", 0)
    tool_es2015PRE_notemp.initialize()
 
    tools = [tool_es2012c, tool_es2015PRE_notemp, tool_es2015PRE]
 
    nominal_es2012c = calibrate_eta_pt(tool_es2012c, etas, [pt], particle="electron")[0]
    nominal_es2015PRE = calibrate_eta_pt(tool_es2015PRE, etas, [pt], particle="electron")[0]
    nominal_es2015PRE_notemp = calibrate_eta_pt(
        tool_es2015PRE_notemp, etas, [pt], particle="electron"
    )[0]
 
    # up variations
    sys = ROOT.CP.SystematicVariation("EG_SCALE_ZEESYST", 1)
    sys_set = ROOT.CP.SystematicSet()
    sys_set.insert(sys)
 
    for tool in tools:
        tool.applySystematicVariation(sys_set)
 
    sys_up_es2012c = calibrate_eta_pt(tool_es2012c, etas, [pt], particle="electron")[0]
    sys_up_es2015PRE = calibrate_eta_pt(tool_es2015PRE, etas, [pt], particle="electron")[0]
    sys_up_es2015PRE_notemp = calibrate_eta_pt(
        tool_es2015PRE_notemp, etas, [pt], particle="electron"
    )[0]
 
    ratio_sys_up_es2012c = sys_up_es2012c / nominal_es2012c - 1
    ratio_sys_up_es2015PRE = sys_up_es2015PRE / nominal_es2015PRE - 1
    ratio_sys_up_es2015PRE_notemp = sys_up_es2015PRE_notemp / nominal_es2015PRE_notemp - 1
 
    # down variations
    sys = ROOT.CP.SystematicVariation("EG_SCALE_ZEESYST", -1)
    sys_set = ROOT.CP.SystematicSet()
    sys_set.insert(sys)
 
    for tool in tools:
        tool.applySystematicVariation(sys_set)
 
    sys_down_es2012c = calibrate_eta_pt(tool_es2012c, etas, [pt], particle="electron")[0]
    sys_down_es2015PRE = calibrate_eta_pt(tool_es2015PRE, etas, [pt], particle="electron")[0]
    sys_down_es2015PRE_notemp = calibrate_eta_pt(
        tool_es2015PRE_notemp, etas, [pt], particle="electron"
    )[0]
 
    ratio_sys_down_es2012c = sys_down_es2012c / nominal_es2012c - 1
    ratio_sys_down_es2015PRE = sys_down_es2015PRE / nominal_es2015PRE - 1
    ratio_sys_down_es2015PRE_notemp = sys_down_es2015PRE_notemp / nominal_es2015PRE_notemp - 1
 
    # up stat
    sys = ROOT.CP.SystematicVariation("EG_SCALE_ZEESTAT", 1)
    sys_set = ROOT.CP.SystematicSet()
    sys_set.insert(sys)
    tool_es2015PRE.applySystematicVariation(sys_set)
    stat_up_es2015PRE = calibrate_eta_pt(tool_es2015PRE, etas, [pt], particle="electron")[0]
    ratio_stat_up = stat_up_es2015PRE / nominal_es2015PRE - 1
 
    # down stat
    sys = ROOT.CP.SystematicVariation("EG_SCALE_ZEESTAT", -1)
    sys_set = ROOT.CP.SystematicSet()
    sys_set.insert(sys)
    tool_es2015PRE.applySystematicVariation(sys_set)
    stat_down_es2015PRE = calibrate_eta_pt(tool_es2015PRE, etas, [pt], particle="electron")[0]
    ratio_stat_down = stat_down_es2015PRE / nominal_es2015PRE - 1
 
    ratio_full_down = -np.sqrt(ratio_stat_down ** 2 + ratio_sys_down_es2015PRE ** 2)
    ratio_full_up = np.sqrt(ratio_stat_up ** 2 + ratio_sys_up_es2015PRE ** 2)
 
    fig, ax = plt.subplots()
 
    ax.fill_between(
        etas,
        ratio_full_down,
        ratio_full_up,
        color="#d69e8f",
        interpolate=False,
        label=r"$\cdots\oplus$ stat = 2015PRE (stat $\oplus$ sys)",
        alpha=0.6,
    )
    ax.fill_between(
        etas,
        ratio_sys_down_es2015PRE,
        ratio_sys_up_es2015PRE,
        color="#d7d790",
        interpolate=False,
        label=r"$\cdots\oplus$ temp = 2015PRE sys",
        alpha=0.6,
    )
    ax.fill_between(
        etas,
        ratio_sys_down_es2015PRE_notemp,
        ratio_sys_up_es2015PRE_notemp,
        color="#91da95",
        label=r"$\cdots\oplus$ 7/8 TeV diff $\oplus$ 34/68 bins diff",
        alpha=0.6,
    )
    ax.fill_between(
        etas,
        ratio_sys_down_es2012c,
        ratio_sys_up_es2012c,
        color="#93dcd1",
        interpolate=False,
        label="2012c",
        alpha=0.6,
    )
 
    p1 = patches.Rectangle((0, 0), 1, 1, color="#d69e8f")
    p2 = patches.Rectangle((0, 0), 1, 1, color="#d7d790")
    p3 = patches.Rectangle((0, 0), 1, 1, color="#91da95")
    p4 = patches.Rectangle((0, 0), 1, 1, color="#93dcd1")
 
    legend1 = ax.legend(
        [p4, p3, p2, p1],
        [
            "2012c",
            r"$\cdots\oplus$ 7/8 TeV diff $\oplus$ 34/68 bins diff",
            r"$\cdots\oplus$ temp = 2015PRE sys",
            r"$\cdots\oplus$ stat = 2015PRE (stat $\oplus$ sys)",
        ],
        loc="upper right",
        numpoints=1,
        title="errors",
    )
 
    f = ROOT.TFile("~/Data6_scaledData.root")
    histo_scale = f.Get("alpha")
    x, ex, y, ey = histo2data(histo_scale)
 
    h1 = ax.errorbar(x, y, yerr=ey, xerr=ex, fmt="o", zorder=11)
 
    f2 = ROOT.TFile("~/uA2MeV.root")
    histo_uA2MeV = f2.Get("histo_uA2MeV_week12")
    x, ex, y, ey = histo2data(histo_uA2MeV)
    (line_uA2MeV,) = ax.plot(x, y - 1, "k-", zorder=10, label="expected deviation")
    ax.plot(-x, y - 1, "k-", zorder=10)
 
    ax.set_xlabel(r"$\eta$")
    ax.set_ylim(-0.08, 0.08)
 
    ax.legend(
        [h1, line_uA2MeV],
        ["scales 13 TeV|es2015 PRE", "expected deviation"],
        loc="lower right",
        numpoints=1,
    )
    ax.add_artist(legend1)
 
    ax.grid()
 
    fig.savefig("Zee_sys.png")
    fig.savefig("Zee_sys.svg")
    fig.savefig("Zee_sys.pdf")
 
 

plot_ATLAS()

plot.plot_ATLAS	(		fig,
			x,
			y,
			label = "Internal",
			fontsize = 20 )

Definition at line 92 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_ATLAS(fig, x, y, label="Internal", fontsize=20):
    label = fig.text(x, y, "ATLAS", fontsize=fontsize, fontstyle="italic", fontweight="bold")
 
    def on_draw(event):
        x_right = label.get_window_extent().transformed(fig.transFigure.inverted()).max[0]
        fig.text(x_right, y, label, fontsize=fontsize)
        fig.canvas.mpl_disconnect(cid)
        return False
 
    cid = fig.canvas.mpl_connect("draw_event", on_draw)
    fig.canvas.draw()
 
 

plot_resolution_error()

plot.plot_resolution_error	(		basedir,
		**	kwargs )

Definition at line 1476 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_resolution_error(basedir, **kwargs):
    esmodels = kwargs["esmodels"] or (
        "es2012c",
        "es2015PRE",
        "es2015PRE_res_improved",
        "es2016PRE",
        "es2017",
    )
    if kwargs["eta_bins"] is not None:
        eta_bins = pairwise(kwargs["eta_bins"])
    else:
        eta_bins = (0, 0.4), (0.4, 0.6), (0.6, 1.37), (1.52, 1.8), (1.8, 2.37)
    for esmodel in esmodels:
        log.debug("plotting resolution error for %s", esmodel)
        tool = ROOT.AtlasRoot.egammaEnergyCorrectionTool()
        if kwargs["debug"]:
            tool.msg().setLevel(0)
        tool.setESModel(getattr(ROOT.egEnergyCorr, esmodel))
        tool.initialize()
        for particle in ("electron", "converted", "unconverted"):
            log.info("plotting resolution %s", particle)
            for eta_min, eta_max in tqdm.tqdm(eta_bins):
                plot_resolution_error_bin(
                    eta_min, eta_max, particle, esmodel, basedir, tool=tool, **kwargs
                )
 
 

plot_resolution_error_bin()

plot.plot_resolution_error_bin	(		eta_min,
			eta_max,
			particle,
			esmodel,
			basedir,
			tool = None,
		**	kwargs )

Definition at line 1503 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_resolution_error_bin(eta_min, eta_max, particle, esmodel, basedir, tool=None, **kwargs):
    if tool is None:
        tool = ROOT.AtlasRoot.egammaEnergyCorrectionTool()
        tool.setESModel(getattr(ROOT.egEnergyCorr, esmodel))
        tool.initialize()
 
    ptype = {
        "electron": ROOT.PATCore.ParticleType.Electron,
        "unconverted": ROOT.PATCore.ParticleType.UnconvertedPhoton,
        "converted": ROOT.PATCore.ParticleType.ConvertedPhoton,
    }[particle]
 
    variations_name_up = {
        "Zsmearing up": ROOT.egEnergyCorr.Resolution.ZSmearingUp,
        "sampling up": ROOT.egEnergyCorr.Resolution.SamplingTermUp,
        "material ID up": ROOT.egEnergyCorr.Resolution.MaterialIDUp,
        "material calo up": ROOT.egEnergyCorr.Resolution.MaterialCaloUp,
        "material gap up": ROOT.egEnergyCorr.Resolution.MaterialGapUp,
        "material cryo up": ROOT.egEnergyCorr.Resolution.MaterialCryoUp,
        "pileup up": ROOT.egEnergyCorr.Resolution.PileUpUp,
        "material ibl up": ROOT.egEnergyCorr.Resolution.MaterialIBLUp,
        "material pp0 up": ROOT.egEnergyCorr.Resolution.MaterialPP0Up,
        "all up": ROOT.egEnergyCorr.Resolution.AllUp,
    }
    variations_name_down = {
        "Zsmearing down": ROOT.egEnergyCorr.Resolution.ZSmearingDown,
        "sampling down": ROOT.egEnergyCorr.Resolution.SamplingTermDown,
        "material ID down": ROOT.egEnergyCorr.Resolution.MaterialIDDown,
        "material calo down": ROOT.egEnergyCorr.Resolution.MaterialCaloDown,
        "material gap down": ROOT.egEnergyCorr.Resolution.MaterialGapDown,
        "material cryo down": ROOT.egEnergyCorr.Resolution.MaterialCryoDown,
        "pileup down": ROOT.egEnergyCorr.Resolution.PileUpDown,
        "material ibl down": ROOT.egEnergyCorr.Resolution.MaterialIBLDown,
        "material pp0 down": ROOT.egEnergyCorr.Resolution.MaterialPP0Down,
        "all down": ROOT.egEnergyCorr.Resolution.AllDown,
    }
    #                 ^    ^
    all_errors = [{}, {}]  # up and down
    #                  ,--,
 
    pt_range = kwargs.get("pt_bins")
    if pt_range is None:
        pt_range = np.linspace(10e3, 2000e3, 100)
 
    nsamples_eta = kwargs["super_sampling_eta"] or 5
    eta_range = np.linspace(eta_min, eta_max, nsamples_eta + 2)[1:-1]
 
    only_up = True
 
    for side, errors, variations_name in zip(
        ("up", "down"), all_errors, (variations_name_up, variations_name_down)
    ):
        if only_up and side == "down":
            continue
 
        for variation_name, variation_id in variations_name.items():
            errors_var_pt_eta = np.zeros((len(pt_range), len(eta_range)))
            for ipt, pt in enumerate(pt_range):
                for ieta, eta in enumerate(eta_range):
                    energy = pt * np.cosh(eta)
                    log.debug(
                        "evaluating systematics %s in eta=%.2f pt=%.2f on resolution",
                        (variation_name, eta, pt)
                    )
                    errors_var_pt_eta[ipt, ieta] = tool.getResolutionError(
                        ROOT.PATCore.ParticleDataType.Full, energy, eta, eta, ptype, variation_id
                    )
            errors[variation_name] = errors_var_pt_eta.mean(
                axis=1
            )  # average over different eta points inside the eta-bin
            if kwargs["abs_sys"]:
                errors[variation_name] = np.abs(errors[variation_name])
 
#    sorted_keys_up = sorted(
#        variations_name_up.keys(), key=lambda x: np.abs(all_errors[0][x].mean())
#    )
    totals = [
        np.sqrt(np.sum([e ** 2 for k, e in errors.items() if "all " not in k]))
        for errors in all_errors
    ]
 
    fig, ax = plt.subplots()
    if only_up:
        ax.fill_between(pt_range / 1e3, 0, all_errors[0]["all up"], color="0.8")
    else:
        ax.fill_between(
            pt_range / 1e3, all_errors[0]["all up"], all_errors[1]["all down"], color="0.8"
        )
    #    ax.fill_between(pt_range / 1E3, totals[0], -totals[-1], color='0.8')
    #    totals[1] *= -1
 
    colors = ["b", "g", "r", "c", "m", "y", "violet", "pink", "orange"]
    props = mpl.rcParams["axes.prop_cycle"] # noqa: F841
 
    for side, errors, total in zip(("up", "down"), all_errors, totals):
        if only_up and side == "down":
            continue
        # ax.plot(pt_range / 1E3, total, label='sum %s' % side, color='k')
        ax.plot(pt_range / 1e3, errors["all %s" % side], "k", label="all %s" % side)
        colors_iter = cycle(colors)
        for k in sorted(errors.keys()):
            if "all" in k:
                continue
            v = errors[k]
            linestyle = "-"
            if "down" in k:
                linestyle = "--"
            if "all" in k:
                linestyle = ":"
            ax.plot(pt_range / 1e3, v, linestyle, label=k, color=next(colors_iter))
 
    fig.text(0.16, 0.73, beautify_particle(particle), transform=ax.transAxes, fontsize=15)
    fig.text(
        0.16,
        0.67,
        r"$%.2f < \eta < %.2f$" % (eta_min, eta_max),
        transform=ax.transAxes,
        fontsize=15,
    )
 
    ax.set_title("%s" % esmodel)
    ax.set_ylabel("relative resolution error [%]", ha="right", y=1.0, fontsize=19)
    ax.set_xlabel("$E_T$ [GeV]", ha="right", x=1.0, fontsize=19)
    if kwargs["abs_sys"]:
        ax.set_ylim(0, 0.6)
    else:
        ax.set_ylim(-1.7, 1.7)
    ax.set_xlim(np.min(pt_range) / 1e3, np.max(pt_range) / 1e3)
 
    fig.subplots_adjust(bottom=0.35)
 
    ax.legend(
        loc=3,
        bbox_to_anchor=(0.0, -0.5, 1, 0.2),
        mode="expand",
        ncol=4,
        borderaxespad=0.0,
        fontsize=10,
    )
 
    plot_ATLAS(fig, 0.16, 0.8, "Internal", fontsize=19)
 
    if kwargs["grid"]:
        ax.grid()
    filename = os.path.join(
        basedir, "error_relresolution_%s_%s_eta%.2f-%.2f" % (esmodel, particle, eta_min, eta_max)
    )
    for ext in "png", "pdf":
        fig.savefig(filename + "." + ext, bbox_inches="tight")
    plt.close(fig)
 
 

plot_resolution_eta_pt()

plot.plot_resolution_eta_pt	(		basedir,
			tool,
			pts,
			etas,
			ptype,
			title )

Definition at line 1439 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def plot_resolution_eta_pt(basedir, tool, pts, etas, ptype, title):
    event = ROOT.xAOD.TEvent()  # noqa: F841
    factory = ROOT.EgammaFactory()
    result = np.ones((len(pts), len(etas)))
    eta_centers = 0.5 * (etas[1:] + etas[:-1])
    pt_centers = 0.5 * (pts[1:] + pts[:-1])
 
    result = np.zeros((len(eta_centers), len(pt_centers)))
 
    for ieta, eta in enumerate(eta_centers):
        for ipt, pt in enumerate(pt_centers):
            e = pt * np.cosh(eta)
            if ptype == "electron":
                p = factory.create_electron(eta, 0.1, e)
            elif ptype == "converted":
                p = factory.create_converted_photon(eta, 0.1, e)
            elif ptype == "unconverted":
                p = factory.create_unconverted_photon(eta, 0.1, e)
            else:
                raise ValueError()
            res = tool.getResolution(p)
            result[ieta, ipt] = res
 
    fig, ax = plt.subplots()
    vmin, vmax = np.percentile(result, (2, 98))
    p = ax.pcolormesh(pts / 1e3, etas, result, vmin=vmin, vmax=vmax)
    ax.set_title(title)
    ax.axis("tight")
    ax.set_xlabel(r"$p_T$ [GeV]")
    ax.set_ylabel(r"$\eta$")
    ax.set_xscale("log")
    cb = fig.colorbar(p)
    cb.ax.set_ylabel("resolution")
    for extension in extensions:
        fig.savefig(os.path.join(basedir, "resolution_%s.%s" % (ptype, extension)))
 
 

systematics_from_tool()

plot.systematics_from_tool	(		tool,
			only_scale = True,
			only_resolution = False,
			only_up = True )

return name of the systematics 

Definition at line 143 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def systematics_from_tool(tool, only_scale=True, only_resolution=False, only_up=True):
    """ return name of the systematics """
    _ = tool.recommendedSystematics()
    for sys in _:
        sys_name = sys.name()
        if only_scale and "RESOLUTION" in sys_name:
            continue
        if only_resolution and "SCALE" in sys_name:
            continue
        if only_up and "1down" in sys_name:
            continue
        yield sys
 
 

timed()

plot.timed

(

method

)

Definition at line 79 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def timed(method):
    @wraps(method)
    def timed(*args, **kw):
        ts = time.time()
        result = method(*args, **kw)
        te = time.time()
 
        log.info("function %s run in  %d second", method.__name__, te - ts)
        return result
 
    return timed
 
 

values2histo()

plot.values2histo	(		name,
			title,
			x,
			y )

Definition at line 578 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

def values2histo(name, title, x, y):
    histo = ROOT.TH1F(name, title, len(x) - 1, x)
    for (
        ibin,
        yy,
    ) in enumerate(y, 1):
        histo.SetBinContent(ibin, yy)
    return histo
 
 

Variable Documentation

extensions

str plot.extensions = "pdf", "png"

Definition at line 61 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

fout

plot.fout = ROOT.TFile("output_plot.root", "recreate")

Definition at line 105 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

handler

plot.handler = TqdmLoggingHandler()

Definition at line 2055 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

IgnoreCommandLineOptions

plot.IgnoreCommandLineOptions

Definition at line 29 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

initialize

plot.initialize

Definition at line 74 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

log

plot.log

Definition at line 2053 of file PhysicsAnalysis/ElectronPhotonID/ElectronPhotonFourMomentumCorrection/python/plot.py.

plotter

plot.plotter = LayerPlotter()

Definition at line 178 of file Reconstruction/egamma/egammaLayerRecalibTool/python/plot.py.