コード例 #1
0
ファイル: overlay.py プロジェクト: skhal/bsm_analyze
def plot(limit_type, low_mass, high_mass, logy=True):
    '''
    Application entry point
    '''

    supported_limit_types = ("narrow", "wide", "kk")
    if limit_type not in supported_limit_types:
        raise RuntimeError("supported limit types: {0!r}".format(
                            supported_limit_types))

    data = load_data(low_mass, high_mass)

    class Limits(object): pass

    # container for low and high limits
    limits = Limits
    limits.low = {
            "visible": None,
            "invisible": None
            }

    limits.high = copy.deepcopy(limits.low)
    limits.low_fix_observed = copy.deepcopy(limits.low)

    # convert YAML to dictionary
    split_point = {
            "narrow": 1000,
            "wide": 1100,
            "kk": 1000
            }.get(limit_type)

    (limits.low["visible"],
     limits.low["invisible"]) = get_limits(data.low, is_low_mass=True,
                                           split_point=split_point,
                                           transform_x=gev_to_tev)

    (limits.high["visible"],
     limits.high["invisible"]) = get_limits(data.high, is_low_mass=False,
                                            split_point=split_point,
                                            transform_x=gev_to_tev)

    (limits.low_fix_observed["visible"],
     limits.low_fix_observed["invisible"]) = get_limits(data.low, is_low_mass=True,
                                                        split_point=split_point,
                                                        low_mass_x=True,
                                                        transform_x=gev_to_tev)

    smooth.data(limits.high["visible"], n=2)

    legend = ROOT.TLegend(0.5, 0.50, 0.80, 0.88)

    line_width = 3
    combo = ROOT.TMultiGraph()

    # 2 sigma band
    cur = limits.low["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["two_sigma_down"], cur["two_sigma_up"])
    graph.SetFillColor(ROOT.kGray + 1)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_2s_lm = graph

    cur = limits.high["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["two_sigma_down"], cur["two_sigma_up"])
    graph.SetFillColor(ROOT.kGray + 1)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_2s_hm = graph

    # 1 sigma band
    cur = limits.low["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["one_sigma_down"], cur["one_sigma_up"])
    graph.SetFillColor(ROOT.kGray)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_1s_lm = graph

    cur = limits.high["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["one_sigma_down"], cur["one_sigma_up"])
    graph.SetFillColor(ROOT.kGray)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_1s_hm = graph

    # expected
    cur = limits.low["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kBlack)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "Expected (95% CL)", "l")

    cur = limits.high["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kBlack)
    graph.SetLineWidth(line_width)
    combo.Add(graph)

    # observed
    cur = limits.low_fix_observed["visible"]
    graph = ROOT.TGraph(len(cur["observed_x"]), cur["observed_x"], cur["observed"])
    graph.SetLineColor(ROOT.kRed + 1)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "Observed (95% CL)", "l")

    cur = limits.high["visible"]
    graph = ROOT.TGraph(len(cur["observed_x"]), cur["observed_x"], cur["observed"])
    graph.SetLineColor(ROOT.kRed + 1)
    graph.SetLineWidth(line_width)
    combo.Add(graph)

    # Theory
    theories = {
            "narrow": ([theory.zprime, 1.2, False], ),
            "wide": ([theory.zprime, 10.0, False], ),
            "kk": ([theory.kk, None, None], )
            }.get(limit_type)

    for index, (theory_function, theory_width, use_old_theory) in enumerate(theories, 0):
        class Theory(object): pass

        x, y, label = (theory_function(theory_width, use_old_theory)
                        if theory_width
                        else theory_function())

        # remove all the points below 500 GeV
        x, y = zip(*[(xi, yi) for xi, yi in zip(x, y) if not 500 > xi])

        x = gev_to_tev(x)
        graph = ROOT.TGraph(len(x), array('d', x), array('d', y))
        graph.SetLineColor([ROOT.kBlue + 1, ROOT.kMagenta + 1, ROOT.kGreen + 1][index] if index < 3 else ROOT.kBlue + 1)
        graph.SetLineWidth(3)
        graph.SetLineStyle(2)
        combo.Add(graph)
        legend.AddEntry(graph, label, "l")

        theory_data = Theory()
        theory_data.x = x
        theory_data.y = y

        if limit_type != 'kk':
            print("low mass".capitalize())
            expected_exclusion, observed_exclusion = exclude(limits.low["visible"], theory_data)

            print("Expected exclusion:", expected_exclusion)
            print("Observed exclusion:", observed_exclusion)

            print()

        print("high mass".capitalize())
        expected_exclusion, observed_exclusion = exclude(limits.high["visible"], theory_data)

        print("Expected exclusion:", expected_exclusion)
        print("Observed exclusion:", observed_exclusion)

    legend.AddEntry(g_1s_lm, "#pm 1 #sigma Expected", "f")
    legend.AddEntry(g_2s_lm, "#pm 2 #sigma Expected", "f")

    # Draw
    cv = ROOT.TCanvas()
    style.canvas(cv)

    combo.Draw("3al")

    # Split point
    if limit_type != 'kk':
        line = ROOT.TGraph(2)
        line.SetPoint(0, split_point * 1e-3, 1e1)
        line.SetPoint(1, split_point * 1e-3, 3e-2)
        line.SetLineColor(ROOT.kGray + 2)
        line.SetLineStyle(2)
        line.SetLineWidth(3)
        line.Draw("L")

    legend.Draw()

    if logy:
        cv.SetLogy(True)

    style.combo(combo, maximum=1e2 if logy else None)
    combo.GetXaxis().SetRangeUser(0, 4)
    style.legend(legend)
    legend.SetTextSize(0.04)

    plot_labels = labels.create({
        #"narrow": "{0:.1f}% Width Assumption".format(theory_width if theory_width else 0),
        "narrow": "Z' with 1% Decay Width",
 
        "wide": "Z' with 10% Decay Width",
        "kk": "KK Gluon Assumption"}.get(limit_type, None))
    map(ROOT.TObject.Draw, plot_labels)

    cv.Update()
    cv.SaveAs("limits-{0}.pdf".format(limit_type))
コード例 #2
0
ファイル: overlay.py プロジェクト: baites/exo_limits
def plot(limit_type, low_mass, high_mass, logy=True, smooth_data=True):
    '''
    Application entry point
    '''

    supported_limit_types = ("narrow", "wide", "kk")
    if limit_type not in supported_limit_types:
        raise RuntimeError("supported limit types: {0!r}".format(
                            supported_limit_types))

    data = load_data(low=low_mass, high=high_mass, scale_high=0.1)

    if smooth_data:
        smooth.data(data.low, n=40, log=logy)
        smooth.data(data.high, n=40, log=logy)

    # Computting splitting point based on expected values
    split_point = 0
    mass_high_min = min(data.high.keys())
    for mass_low in sorted(data.low.keys()):
        if mass_low < mass_high_min:
            continue
        mass_high = 0
        for mass in sorted(data.high.keys()):
            if mass >= mass_low:
                mass_high = mass
                break
        if data.low[mass_low][0] > data.high[mass_high][0]:
            print(mass_low, mass_high)
            split_point = mass_high
            break

    class Limits(object): pass

    # container for low and high limits
    limits = Limits
    limits.low = {
            "visible": None,
            "invisible": None
            }

    limits.high = copy.deepcopy(limits.low)
    limits.low_fix_observed = copy.deepcopy(limits.low)

    (limits.low["visible"],
     limits.low["invisible"]) = get_limits(data.low, is_low_mass=True,
                                           split_point=split_point,
                                           transform_x=gev_to_tev)

    (limits.high["visible"],
     limits.high["invisible"]) = get_limits(data.high, is_low_mass=False,
                                            split_point=split_point,
                                            transform_x=gev_to_tev)

    (limits.low_fix_observed["visible"],
     limits.low_fix_observed["invisible"]) = get_limits(data.low, is_low_mass=True,
                                                        split_point=split_point,
                                                        low_mass_x=True,
                                                        transform_x=gev_to_tev)

    legend = ROOT.TLegend(0.5, 0.50, 0.80, 0.88)

    line_width = 3
    combo = ROOT.TMultiGraph()

    # 2 sigma band
    cur = limits.low["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["two_sigma_down"], cur["two_sigma_up"])
    graph.SetFillColor(ROOT.kGray + 1)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_2s_lm = graph

    cur = limits.high["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["two_sigma_down"], cur["two_sigma_up"])
    graph.SetFillColor(ROOT.kGray + 1)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_2s_hm = graph

    # 1 sigma band
    cur = limits.low["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["one_sigma_down"], cur["one_sigma_up"])
    graph.SetFillColor(ROOT.kGray)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_1s_lm = graph

    cur = limits.high["visible"]
    graph = ROOT.TGraphAsymmErrors(len(cur["x"]), cur["x"], cur["expected"],
                                   cur["xerr"], cur["xerr"],
                                   cur["one_sigma_down"], cur["one_sigma_up"])
    graph.SetFillColor(ROOT.kGray)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_1s_hm = graph

    # expected
    cur = limits.low["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kBlack)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "Expected (95% CL)", "l")

    cur = limits.high["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kBlack)
    graph.SetLineWidth(line_width)
    combo.Add(graph)


    # observed
    cur = limits.low_fix_observed["visible"]
    graph = ROOT.TGraph(len(cur["observed_x"]), cur["observed_x"], cur["observed"])
    graph.SetLineColor(ROOT.kRed + 1)
    graph.SetLineWidth(line_width)
    graph.SetLineStyle(2)
    combo.Add(graph)
    legend.AddEntry(graph, "Observed (95% CL)", "l")

    cur = limits.high["visible"]
    graph = ROOT.TGraph(len(cur["observed_x"]), cur["observed_x"], cur["observed"])
    graph.SetLineColor(ROOT.kRed + 1)
    graph.SetLineWidth(line_width)
    graph.SetLineStyle(2)
    combo.Add(graph)

    # Theory
    theories = {
            "narrow": ([theory.zprime, 1.2, False], ),
            "wide": ([theory.zprime, 10.0, False], ),
            "kk": ([theory.kkgluon, None, None], )
            }.get(limit_type)

    for index, (theory_function, theory_width, use_old_theory) in enumerate(theories, 0):
        class Theory(object): pass

        x, y, label = (theory_function(theory_width, use_old_theory)
                        if theory_width
                        else theory_function())

        # remove all the points below 500 GeV
        x, y = zip(*[(xi, yi) for xi, yi in zip(x, y) if not 500 > xi])

        x = gev_to_tev(x)
        graph = ROOT.TGraph(len(x), array('d', x), array('d', y))
        graph.SetLineColor([ROOT.kBlue + 1, ROOT.kMagenta + 1, ROOT.kGreen + 1][index] if index < 3 else ROOT.kBlue + 1)
        graph.SetLineWidth(3)
        graph.SetLineStyle(9)
        combo.Add(graph)
        legend.AddEntry(graph, label, "l")

        theory_data = Theory()
        theory_data.x = x
        theory_data.y = y

        '''
        print("low mass".capitalize())
        expected_exclusion, observed_exclusion = exclude(limits.low["visible"], theory_data)

        print("Expected exclusion:", expected_exclusion)
        print("Observed exclusion:", observed_exclusion)

        print()
        print("high mass".capitalize())
        expected_exclusion, observed_exclusion = exclude(limits.high["visible"], theory_data)

        print("Expected exclusion:", expected_exclusion)
        print("Observed exclusion:", observed_exclusion)
        '''

    legend.AddEntry(g_1s_lm, "Expected #pm 1 s.d.", "f")
    legend.AddEntry(g_2s_lm, "Expected #pm 2 s.d.", "f")

    # Draw
    cv = ROOT.TCanvas()
    style.canvas(cv)

    combo.Draw("3al")

    # Split point
    line = ROOT.TGraph(2)
    line.SetPoint(0, split_point * 1e-3, 1e1)
    line.SetPoint(1, split_point * 1e-3, 5e-3)
    line.SetLineColor(ROOT.kGray + 2)
    line.SetLineStyle(9)
    line.SetLineWidth(3)
    line.Draw("L")

    legend.Draw()

    if logy:
        cv.SetLogy(True)

    if limit_type == 'kk':
        style.combo(combo, maximum=4e2 if logy else None,
                    minimum=1e-2 if logy else None,
                    ytitle="Upper Limit #sigma_{g_{KK}} x B [pb]")
    else:
        style.combo(combo, maximum=4e2 if logy else None)

    style.legend(legend)
    legend.SetTextSize(0.04)

    plot_labels = labels.create({
        #"narrow": "{0:.1f}% Width Assumption".format(theory_width if theory_width else 0),
        "narrow": "Z' with 1.2% Decay Width",
 
        "wide": "Z' with 10% Decay Width",
        "kk": "KK Gluon"}.get(limit_type, None))
    map(ROOT.TObject.Draw, plot_labels)

    cv.Update()
    cv.SaveAs("limits-{0}.pdf".format(limit_type))
コード例 #3
0
ファイル: overlay.py プロジェクト: baites/exo_simple_limits
def plot(limit_type, filename, logy=True, smooth_data=True):
    """
    Application entry point
    """

    supported_limit_types = ("narrow", "wide", "kk")
    if limit_type not in supported_limit_types:
        raise RuntimeError("supported limit types: {0!r}".format(supported_limit_types))

    data = load_data(filename, 0.1)

    if smooth_data:
        smooth.data(data, n=40, log=logy)

    # print(sorted(data.keys()))
    # for m in sorted(data.keys()):
    #    print(m, data[m][0])

    legend = ROOT.TLegend(0.5, 0.50, 0.80, 0.88)

    line_width = 3
    combo = ROOT.TMultiGraph()

    # 2 sigma band
    cur = get_limits(data)
    graph = ROOT.TGraphAsymmErrors(
        len(cur["x"]), cur["x"], cur["expected"], cur["xerr"], cur["xerr"], cur["two_sigma_down"], cur["two_sigma_up"]
    )
    graph.SetFillColor(ROOT.kGray + 1)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_2s = graph

    # 1 sigma band
    graph = ROOT.TGraphAsymmErrors(
        len(cur["x"]), cur["x"], cur["expected"], cur["xerr"], cur["xerr"], cur["one_sigma_down"], cur["one_sigma_up"]
    )
    graph.SetFillColor(ROOT.kGray)
    graph.SetLineWidth(0)
    combo.Add(graph)
    g_1s = graph

    # expected
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kBlack)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "Expected (95% Bayesian)", "l")

    # observed
    graph = ROOT.TGraph(len(cur["observed_x"]), cur["observed_x"], cur["observed"])
    graph.SetLineColor(ROOT.kRed + 1)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "Observed (95% Bayesian)", "l")

    # Theory
    theories = {
        "narrow": ([theory.zprime, 1.2, False],),
        "wide": ([theory.zprime, 10.0, False],),
        "kk": ([theory.kkgluon, None, None],),
    }.get(limit_type)

    for index, (theory_function, theory_width, use_old_theory) in enumerate(theories, 0):

        class Theory(object):
            pass

        x, y, label = theory_function(theory_width, use_old_theory) if theory_width else theory_function()

        # remove all the points below 500 GeV
        x, y = zip(*[(xi, yi) for xi, yi in zip(x, y) if not 750 > xi])

        graph = ROOT.TGraph(len(x), array("d", x), array("d", y))
        graph.SetLineColor([ROOT.kBlue + 1, ROOT.kMagenta + 1, ROOT.kGreen + 1][index] if index < 3 else ROOT.kBlue + 1)
        graph.SetLineWidth(3)
        graph.SetLineStyle(2)
        combo.Add(graph)
        legend.AddEntry(graph, label, "l")

        theory_data = Theory()
        theory_data.x = x
        theory_data.y = y

        expected_exclusion, observed_exclusion = exclude(cur, theory_data)
        print("Expected exclusion:", expected_exclusion)
        print("Observed exclusion:", observed_exclusion)

    legend.AddEntry(g_1s, "#pm 1 s.d. Expected", "f")
    legend.AddEntry(g_2s, "#pm 2 s.d. Expected", "f")

    # Draw
    cv = ROOT.TCanvas()
    style.canvas(cv)

    combo.Draw("3al")
    legend.Draw()

    if logy:
        cv.SetLogy(True)

    if limit_type == "kk":
        style.combo(
            combo,
            ytitle="Upper Limit #sigma_{g_{KK}} x B [pb]",
            maximum=1e2 if logy else None,
            minimum=1e-2 if logy else None,
        )
    else:
        style.combo(combo, maximum=1e2 if logy else None)

    style.legend(legend)
    legend.SetTextSize(0.04)

    plot_labels = labels.create(
        {"narrow": "Narrow Width Assumption", "wide": "10% Width Assumption", "kk": "KK Gluon Assumption"}.get(
            limit_type, None
        )
    )

    map(ROOT.TObject.Draw, plot_labels)

    cv.Update()
    cv.SaveAs("limits-{0}.pdf".format(limit_type))
コード例 #4
0
ファイル: expected.py プロジェクト: skhal/bsm_analyze
def main():
    if 4 != len(sys.argv):
        raise RuntimeError("insufficient arguments")

    data = load_data(*sys.argv[1:3])

    # container for low and high limits
    class Limits(object): pass

    limits = Limits()
    limits.low = {
            "visible": None,
            "invisible": None
            }

    limits.high = copy.deepcopy(limits.low)

    # convert YAML to dictionary
    (limits.low["visible"],
     limits.low["invisible"]) = get_limits(data.low, is_low_mass=True)

    (limits.high["visible"],
     limits.high["invisible"]) = get_limits(data.high, is_low_mass=False)

    legend = ROOT.TLegend(0.5, 0.50, 0.80, 0.80)
    legend.SetHeader("Expected limits")

    line_width = 3
    combo = ROOT.TMultiGraph()

    # expected
    cur = limits.low["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kAzure - 7)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "threshold", "l")

    cur = limits.low["invisible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kAzure + 2)
    graph.SetLineWidth(line_width)
    graph.SetLineStyle(7)
    combo.Add(graph)

    cur = limits.high["visible"]
    graph = ROOT.TGraph(len(cur["x"]), cur["x"], cur["expected"])
    graph.SetLineColor(ROOT.kOrange + 2)
    graph.SetLineWidth(line_width)
    combo.Add(graph)
    legend.AddEntry(graph, "boosted", "l")

    # Draw
    cv = ROOT.TCanvas()
    style.canvas(cv)

    combo.Draw("3al")
    legend.Draw()

    cv.SetLogy(True)
    style.combo(combo)
    style.legend(legend)

    plot_labels = labels.create(sys.argv[3])
    map(ROOT.TObject.Draw, plot_labels)

    cv.Update()
    cv.SaveAs("expected.png")

    raw_input("enter")