def run_example(save=True):
##########################################
# first define some objects to play with #
##########################################
random = TRandom(getpid())
# Create a histogram to play with
bin_edges = array("d", [2, 3, 5, 7, 11, 13, 17, 19])
hist_1 = TH1F("some_histogram_1", "", len(bin_edges) - 1, bin_edges)
hist_2 = TH1F("some_histogram_2", "", len(bin_edges) - 1, bin_edges)
# Fill histogram from a random number generation
for i in range(len(bin_edges) + 1):
hist_1.SetBinContent(i + 1, random.Poisson(42))
hist_1.SetBinError(i + 1, random.Gaus(10))
hist_2.SetBinContent(i + 1, random.Poisson(42))
hist_2.SetBinError(i + 1, random.Gaus(10))
###################################
# The actual plotting starts here #
###################################
# Generate 3 styles with constant markerstyle
styles = generate_styles(StyleObject1D, 2, markerstyle=34)
# Create a figure with one cell (1 column and one row)
figure = ROOTFigure(1, 1, size=(400, 600), row_margin=0.05, column_margin=0.1)
# plot is actually defined automatically now since it's a 1x1 grid
# hence the following should be skipped
# plot = figure.define_plot(0, 0)
# so one can add an object via the figure...
figure.add_object(hist_1, style=styles[0], label="MyHist1")
# ...or obtain the current single plot cell
plot = figure.change_plot()
# ...and add another object via
plot.add_object(hist_2, style=styles[1], label="MyHist2")
# Set some axis limits and titles explicitly
plot.axes("x", title="x_title")
plot.axes("y", limits=[0, 120], title="y_title")
figure.create()
if save:
figure.save("example_one_plot.eps")
return True
def run_example(save=True):
##########################################
# first define some objects to play with #
##########################################
random = TRandom(getpid())
# Create a histogram to play with
bin_edges = array("d", [2, 3, 5, 7, 11, 13, 17, 19])
hist_1 = TH2F("some_histogram_1", "", len(bin_edges) - 1, bin_edges, len(bin_edges) - 1, bin_edges)
#hist_2 = TH1F("some_histogram_2", "", len(bin_edges) - 1, bin_edges)
# Fill histogram from a random number generation
for i in range(len(bin_edges) + 1):
for j in range(len(bin_edges) + 1):
hist_1.SetBinContent(i + 1, j + 1, random.Poisson(42))
hist_1.SetBinError(i + 1, j + 1, random.Gaus(10))
hist_2 = hist_1.ProjectionX()
###################################
# The actual plotting starts here #
###################################
# Generate 3 styles with constant markerstyle
style = StyleObject1D()
style.draw_options = "colz"
style_2 = StyleObject1D()
# Create a figure with one cell (1 column and one row)
figure = ROOTFigure(1, 2, size=(400, 600), row_margin=((0.06, 0.005), (0.005, 0.05)), column_margin=(0.11, 0.1))
# plot is actually defined automatically now since it's a 1x1 grid
# hence the following should be skipped
plot_1 = figure.define_plot()
plot_1.axes("x", title="x_title", title_offset=2.5)
plot_1.axes("y", title="y_title_1", title_offset=1.9)
# so one can add an object via the figure...
plot_1.add_object(hist_1, style=style)
plot = figure.define_plot(share_x=plot_1)
plot.add_object(hist_2, style=style_2)
plot.axes("y", title="ProjectionX", title_offset=1.9)
figure.create()
if save:
figure.save("test_2D_plot.eps")
return True
pvalHist = TH1D("pval", "pval", 100000, 0, 1.0)
allpvalHist = TH1D("allpval", "allpval", 100000, 0, 1.0)
pvalCdfHist = TH1D("pvalCdf", "pvalCdf", 100000, 0, 1.0)
lastTime = time.time()
for runnum in xrange(0, n):
newTime = time.time()
if newTime - lastTime > 10:
print runnum
lastTime = newTime
#print runnum
data.Reset()
massArr = array.array('d')
massWindowArr = array.array('d')
candArr = array.array('d')
data.FillRandom("eventpdf", rand.Poisson(nEvents))
for i in range(0, n_massbins):
mass = minmass + i * (maxmass - minmass) / (n_massbins - 1)
massArr.append(mass)
massWindowArr.append(1.4 * mres.Eval(mass))
minbin = data.GetXaxis().FindBin(mass - 1.4 * mres.Eval(mass))
maxbin = data.GetXaxis().FindBin(mass + 1.4 * mres.Eval(mass))
candArr.append(data.Integral(minbin, maxbin))
minPval = 1.0
nbkg = 0.5
for i in xrange(0, len(massArr)):
if fitBackground:
mass = massArr[i]
sigMassArr = array.array('d')
sigCandArr = array.array('d')
def run_example(save=True):
##########################################
# first define some objects to play with #
##########################################
random = TRandom(getpid())
# Create a histogram to play with
bin_edges = array("d", [2, 3, 5, 7, 11, 13, 17, 19])
hist_1 = TH1F("some_histogram_1", "", len(bin_edges) - 1, bin_edges)
hist_2 = TH1F("some_histogram_2", "", len(bin_edges) - 1, bin_edges)
# Fill histogram from a random number generation
for i in range(len(bin_edges) + 1):
hist_1.SetBinContent(i + 1, random.Poisson(42))
hist_1.SetBinError(i + 1, random.Gaus(10))
hist_2.SetBinContent(i + 1, random.Poisson(42))
hist_2.SetBinError(i + 1, random.Gaus(10))
###################################
# The actual plotting starts here #
###################################
# Generate 5 styles, keep markerstyle the same for all
styles = generate_styles(StyleObject1D, 5, markerstyle=21)
# the overall figure with a grid of 3 columns and 4 rows (default is 1 column and 1 row)
figure = ROOTFigure(3, 4, size=(600, 600), column_margin=(0.05, 0.025))
# define a plot from cell (1, 1) to cell (2, 2)
figure.define_plot(1, 1, 2, 2, y_log=True)
# internally, set to current plot so we can add objects
figure.add_object(hist_1, style=styles[0], label="MyLabel1")
figure.add_object(hist_2, style=styles[1], label="MyLabel2")
# define another plot and store the return value in plot2 cause we want to share its x and y-axis later
# since this should only take one cell, we only need low column and low row
plot2 = figure.define_plot(0, 0, 1, 0)
# add same objects as above
figure.add_object(hist_1, style=styles[0], label="MyLabel1")
figure.add_object(hist_2, style=styles[1], label="MyLabel2")
# now add another plot and we want to share the y-axis again
figure.define_plot(2, 0, share_y=plot2)
figure.add_object(hist_1, style=styles[2], label="MyLabel4")
# now add another plot and we want to share the x-axis
plot3 = figure.define_plot(0, 1)
figure.add_object(hist_1, style=styles[2], label="MyLabel5")
# now add another plot and we want to share the x-axis again
figure.define_plot(0, 2, 0, 3, share_x=plot3)
figure.add_object(hist_1, style=styles[2], label="MyLabel6")
plot4 = figure.define_plot(1, 3)
figure.add_object(hist_1, style=styles[2], label="MyLabel7")
figure.define_plot(2, 3, share_y=plot4)
figure.add_object(hist_1, style=styles[3], label="MyLabel8")
figure.add_object(hist_2, style=styles[4], label="MyLabel9")
# until now, nothing actually happened, the above is really only a specification
# only with this call things are actually created and drawn
figure.create()
if save:
figure.save("test_plot_arrangement.eps")
return True
def run_example(save=True):
##########################################
# first define some objects to play with #
##########################################
random = TRandom(getpid())
# Construct a TGraph to play with
n_points = 100
graph = TGraph(n_points)
for i in range(n_points):
graph.SetPoint(i, random.Gaus(16.5, 5), random.Poisson(21))
# Create a histogram to play with
bin_edges = array("d", [2, 3, 5, 7, 11, 13, 17, 19])
hist = TH1F("some_histogram", "", len(bin_edges) - 1, bin_edges)
# Fill histogram from a random number generation
for i in range(len(bin_edges) - 1):
hist.SetBinContent(i + 1, random.Poisson(42))
hist.SetBinError(i + 1, random.Gaus(10))
# And now add a function
func = TF1("func", "84*sin(x)*sin(x)/x", 1, 10)
###################################
# The actual plotting starts here #
###################################
# Generate 5 styles, keep markerstyle the same for all
styles = generate_styles(StyleObject1D, 5, markerstyle=34)
styles_graphs = generate_styles(StyleObject1D,
5,
markerstyle=21,
draw_options=["P"])
# make explicity style for the function
func_style = StyleObject1D()
func_style.linecolor = kBlack
# number of columns and rows
n_cols = 3
n_rows = 4
# Define a MxN grid with overall margins on the left, bottom, right and top
figure = make_grid(ROOTFigure, (n_cols, n_rows),
0.08,
0.05,
0.05,
0.05,
size=(1000, 1000),
x_title="x_title",
y_title="y_title")
for i in range(n_cols * n_rows):
# change current plot
figure.change_plot(i)
# Add a histogram
figure.add_object(hist,
style=styles[i % len(styles)],
label=f"MyHist{i}")
# Add another object, say a TGraph
figure.add_object(graph,
style=styles_graphs[i % len(styles_graphs)],
label=f"MyGraph_{i}")
# Add another object, now a TF1
figure.add_object(func, style=func_style, label=f"MyFunc_{i}")
# And some text
figure.add_text("Text", 0.5, 0.1)
figure.create()
if save:
figure.save("test_grid_mxn.eps")
return True
def run_example(save=True):
##########################################
# first define some objects to play with #
##########################################
random = TRandom(getpid())
# Create a histogram to play with
bin_edges = array("d", [2, 3, 5, 7, 11, 13, 17, 19])
hist_1 = TH1F("some_histogram_1", "", len(bin_edges) - 1, bin_edges)
hist_2 = TH1F("some_histogram_2", "", len(bin_edges) - 1, bin_edges)
# Fill histogram from a random number generation
for i in range(len(bin_edges) + 1):
hist_1.SetBinContent(i + 1, random.Poisson(42))
hist_1.SetBinError(i + 1, random.Gaus(10))
hist_2.SetBinContent(i + 1, random.Poisson(42))
hist_2.SetBinError(i + 1, random.Gaus(10))
# Ratio, make use of function to clone a ROOT object which will immediately
# acquire a new name so no problems with overlapping names and ROOT complaining
h_ratio = clone_root(hist_1)
h_ratio.Divide(hist_2)
###################################
# The actual plotting starts here #
###################################
# Generate 2 styles with constant markerstyle
styles = generate_styles(StyleObject1D, 2, markerstyles=34, markersizes=2)
# Create a figure with one cell (1 column and one row)
figure = ROOTFigure(1,
2,
size=(400, 600),
row_margin=[(0.1, 0), (0, 0.1)],
column_margin=0.1,
height_ratios=[1, 2])
# since counting starts in the bottom left corner and we use the automatic generation of plot
# the first one will be the ratio
ratio_plot = figure.define_plot()
# add the ratio
figure.add_object(h_ratio, style=styles[0])
# set axis
ratio_plot.axes("x", title="x_axis", title_offset=3)
ratio_plot.axes("y", title="Hist1 / Hist2", title_offset=1.8)
# share the x-axis with the ratio plot
main_plot = figure.define_plot(share_x=ratio_plot)
# add nominal histograms
figure.add_object(hist_1, style=styles[0], label="Hist1")
figure.add_object(hist_2, style=styles[1], label="Hist2")
# set y-axis
main_plot.axes("y", title="Entries")
# create and save
figure.create()
if save:
figure.save("example_ratio_plot.eps")
return True
