def main():
x = np.random.normal(0, 50, 50000)
y = np.random.normal(0, 15, 50000)
ranges = ([(-100, 0), (-50, 0)],
[(0, 100), (-50, 0)],
[(-100, 0), (0, 50)],
[(0, 100), (0, 50)])
types = ('reverse_bw', 'color', 'bw', 'area')
bitmaps = (True, True, False, False)
subplot_idxs = [(1, 0), (1, 1), (0, 0), (0, 1)]
plot = Plot()
mplot = MultiPlot(2, 2, width=r'.4\linewidth')
for idx, r, t, b in zip(subplot_idxs, ranges, types, bitmaps):
n, xbins, ybins = np.histogram2d(x, y, bins=15, range=r)
plot.histogram2d(n, xbins, ybins, type=t, bitmap=b)
p = mplot.get_subplot_at(*idx)
p.histogram2d(n, xbins, ybins, type=t, bitmap=b)
mplot.show_yticklabels_for_all([(1, 0), (0, 1)])
mplot.show_xticklabels_for_all([(1, 0), (0, 1)])
plot.save('histogram2d')
mplot.save('multi_histogram2d')
def main():
# data series
x = [0, 40, 60, 69, 80, 90, 100]
y = [0, 0, 0.5, 2.96, 2, 1, .5]
# make graph
graph = Plot()
# make Plot
graph.plot(x, y, mark=None, linestyle='smooth,very thick')
# set labels and limits
graph.set_xlabel(r"$f [\si{\mega\hertz}]$")
graph.set_ylabel("signal strength")
graph.set_xlimits(0, 100)
graph.set_ylimits(0, 5)
# set scale: 1cm equals 10 units along the x-axis
graph.set_xscale(cm=10)
# set scale: 1cm equals 1 unit along the y-axis
graph.set_yscale(cm=1)
# set ticks at every unit along the y axis
graph.set_yticks(range(6))
# set graph paper
graph.use_graph_paper()
# save graph to file
graph.save('mm_paper')
def main():
x, t25, t50, t75 = np.loadtxt('data/DIR-boxplot_arrival_times-1.txt')
graph = Plot()
graph.plot(x, t50, mark='*')
graph.shade_region(x, t25, t75)
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(r"Arrival time delay [\si{\nano\second}]")
graph.set_ylimits(min=0)
graph.save('shower-front')
def main():
plot = Plot()
size = 20
x = np.linspace(1, 20, size)
y = np.linspace(10, 50, size)
y_random = y + np.random.uniform(-3, 1, size)
err_l = np.random.uniform(0, 2, size)
err_h = np.random.uniform(1, 5, size)
err_x = [0.4] * size
plot.plot(x, y, mark=None)
plot.scatter(x, y_random, xerr=err_x, yerr=list(zip(err_l, err_h)))
plot.set_xlabel("Value with symmetric error")
plot.set_ylabel("Other value with asymmetric errors")
plot.save("error_bars")
def main():
leap = np.genfromtxt('data/leap-prot.dat', delimiter=',',
usecols=(0, 1), names=['E', 'F'])
leap['E'] *= 1e6
leap['F'] *= 1e3 * 2
proton = read_data('data/proton', 1, 0)
akeno_new_lo = read_data('data/akeno-new-lo', 0, 1)
flys_eye = read_data('data/fe-new', 0, 1)
yakutsk = read_data('data/yakustk', 1, 0)
haverah = read_data('data/haverah', 1, 0)
graph = Plot(axis='loglog', width=r'.5\linewidth', height=r'.65\linewidth')
graph.plot(leap['E'], leap['F'], mark=None)
graph.add_pin('LEAP', 'above right', use_arrow=True,
relative_position=.5)
graph.plot(proton['E'], proton['F'], mark=None)
graph.add_pin('PROTON', 'above right', use_arrow=True,
relative_position=.5)
graph.plot(akeno_new_lo['E'], akeno_new_lo['F'], mark=None)
graph.add_pin('AGASA', 'above right', use_arrow=True,
relative_position=.5)
graph.plot(yakutsk['E'], yakutsk['F'], mark=None)
graph.add_pin('Yakutsk', 'below left', use_arrow=True,
relative_position=.55)
graph.plot(haverah['E'], haverah['F'], mark=None)
graph.add_pin('Haverah Park', 'below left', use_arrow=True,
relative_position=.85)
graph.plot(flys_eye['E'], flys_eye['F'], mark=None)
graph.add_pin("Fly's Eye", 'below left', use_arrow=True,
relative_position=1.0)
graph.set_xlabel(r"Energy [\si{\electronvolt}]")
graph.set_ylabel(r"Flux [\si{\per\square\meter\per\steradian"
"\per\second\per\giga\electronvolt}]")
x = np.logspace(11, 17)
graph.plot(x, 1.5e29 * x ** -2.75, mark=None, linestyle='dashed')
graph.set_logxticks(range(6, 22, 3))
graph.save('spectrum')
def main():
gamma = np.genfromtxt('data/showere15-proton.t2001', usecols=(1, 2))
e = np.genfromtxt('data/showere15-proton.t2205', usecols=(1, 2))
mu = np.genfromtxt('data/showere15-proton.t2207', usecols=(1, 2))
graph = Plot(axis='loglog')
graph.plot(gamma[:, 0], gamma[:, 1], mark=None)
graph.add_pin(r'$\gamma$')
graph.plot(e[:, 0], e[:, 1], mark=None)
graph.add_pin('e')
graph.plot(mu[:, 0], mu[:, 1], mark=None)
graph.add_pin(r'$\mu$')
graph.set_xlabel(r"Core distance [\si{\meter}]")
graph.set_ylabel(r"Particle density [\si{\per\square\meter}]")
graph.set_logyticks(range(-6, 3, 2))
graph.save('eas-lateral')
def main():
locations = np.genfromtxt(
'data/SP-DIR-plot_sciencepark_cluster-detectors.txt',
names=['x', 'y'])
stations = np.genfromtxt(
'data/SP-DIR-plot_sciencepark_cluster-stations.txt',
names=['id', 'x', 'y'])
graph = Plot()
graph.scatter(locations['x'], locations['y'])
graph.set_axis_equal()
locations = ['right'] * len(stations)
locations[0] = 'left'
locations[5] = 'above right'
locations = iter(locations)
for num, x, y in stations:
graph.add_pin_at_xy(x, y, int(num), location=next(locations),
use_arrow=False, style='gray,label distance=1ex')
x = [stations['x'][u] for u in [0, 2, 5]]
y = [stations['y'][u] for u in [0, 2, 5]]
x.append(x[0])
y.append(y[0])
graph.plot(x, y, mark=None, linestyle='dashed')
graph.add_pin_at_xy([x[0], x[1]], [y[0], y[1]], r'\SI{128}{\meter}',
relative_position=.4, location='below right',
use_arrow=False)
graph.add_pin_at_xy([x[0], x[2]], [y[0], y[2]], r'\SI{151}{\meter}',
relative_position=.5, location='left',
use_arrow=False)
graph.add_pin_at_xy([x[2], x[1]], [y[2], y[1]], r'\SI{122}{\meter}',
relative_position=.5, location='above right',
use_arrow=False)
graph.set_xlabel(r"Distance [\si{\meter}]")
graph.set_ylabel(r"Distance [\si{\meter}]")
graph.save('sciencepark')
def main():
x = np.arange(10)
y = (x / 2.0) - 3.0
colors = ["black", "red", "blue", "yellow", "purple"]
plot = Plot()
for i in range(5):
plot.plot(x, y - i, mark="", linestyle=colors[i])
plot.set_axis_options(
"yticklabel pos=right,\n"
"grid=major,\n"
"legend entries={$a$,[red]$b$,[green]$c$,$d$,$a^2$},\n"
"legend pos=north west"
)
plot.set_xlabel("Something important")
plot.set_ylabel("A related thing")
plot.save("any_option")
x = np.linspace(0.6 * np.pi, 10 * np.pi, 150)
y = np.sin(x) / x
plot = MultiPlot(1, 2, width=r".4\linewidth", height=r".25\linewidth")
subplot = plot.get_subplot_at(0, 0)
subplot.plot(x, y, mark=None)
subplot = plot.get_subplot_at(0, 1)
subplot.plot(x, y, mark=None)
plot.show_xticklabels_for_all([(0, 0), (0, 1)])
plot.show_yticklabels(0, 1)
plot.set_axis_options(0, 1, "yticklabel pos=right, grid=major")
plot.set_axis_options_for_all(None, r"enlargelimits=false")
plot.set_xlabel("Something important")
plot.set_ylabel("A related thing")
plot.save("multi_any_option")
def main():
# Draw random numbers from the normal distribution
np.random.seed(1)
N = np.random.normal(size=2000)
# define bin edges
edge = 5
bin_width = .1
bins = np.arange(-edge, edge + .5 * bin_width, bin_width)
# build histogram and x, y values at the center of the bins
n, bins = np.histogram(N, bins=bins)
x = (bins[:-1] + bins[1:]) / 2
y = n
# fit normal distribution pdf to data
f = lambda x, N, mu, sigma: N * scipy.stats.norm.pdf(x, mu, sigma)
popt, pcov = scipy.optimize.curve_fit(f, x, y)
print("Parameters from fit (N, mu, sigma):", popt)
# make graph
graph = Plot()
# graph histogram
graph.histogram(n, bins)
# graph model with fit parameters
x = np.linspace(-edge, edge, 100)
graph.plot(x, f(x, *popt), mark=None)
# set labels and limits
graph.set_xlabel("value")
graph.set_ylabel("count")
graph.set_label("Fit to data")
graph.set_xlimits(-6, 6)
# save graph to file
graph.save('histogram-fit')
def main():
stations = np.genfromtxt("data/cluster-utrecht-stations.txt", names=["x", "y"])
image = Image.open("data/cluster-utrecht-background.png")
graph = Plot(width=r".75\linewidth", height=r".5\linewidth")
graph.scatter(stations["x"], stations["y"])
graph.draw_image(image)
graph.set_axis_equal()
nw = ["%.4f" % i for i in (52.10650519075632, 5.053710938)]
se = ["%.4f" % i for i in (52.05249047600099, 5.185546875)]
graph.set_xlabel("Longitude [$^\circ$]")
graph.set_xticks([0, image.size[0]])
graph.set_xtick_labels([nw[1], se[1]])
graph.set_ylabel("Latitude [$^\circ$]")
graph.set_yticks([0, image.size[1]])
graph.set_ytick_labels([se[0], nw[0]])
graph.save("utrecht")
def main():
plot = Plot(width=r'.5\linewidth', height=r'.5\linewidth')
r = linspace(1, 5, 100)
phi = linspace(0, 4.5 * pi, 100)
x = r * cos(phi)
y = r * sin(phi)
plot.plot(x, y, mark=None)
plot.add_pin('start', relative_position=0, use_arrow=True)
plot.add_pin('half', relative_position=.5, use_arrow=True)
plot.add_pin('46\%', relative_position=.46, use_arrow=True,
location='above')
plot.add_pin('end', relative_position=1, use_arrow=True, location='below')
phi = linspace(0, 2 * pi, 10)
x = 6 * cos(phi)
y = 6 * sin(phi)
plot.plot(x, y, mark=None, linestyle='thick, gray')
plot.add_pin('start', relative_position=0, use_arrow=True,
location='above right')
plot.add_pin('half', relative_position=.5, use_arrow=True,
location='above left')
plot.add_pin('70\%', relative_position=.7, use_arrow=True,
location='below')
plot.add_pin('end', relative_position=1, use_arrow=True,
location='below right')
plot.plot([-5, 2, 5], [-7.5, -7.5, -7.5], linestyle='lightgray')
plot.add_pin('50\%', relative_position=.5, use_arrow=True,
location='above right')
plot.set_xlimits(-8, 8)
plot.set_ylimits(-8, 8)
plot.save('relative_pin')
# With one logarithmic axis
plot = Plot(axis='semilogy')
x = [2, 2, 2]
y = [1, 10, 100]
plot.plot(x, y)
for xi, yi in zip(x, y):
plot.add_pin_at_xy(xi, yi, '(%d,%d)' % (xi, yi),
location='below right')
plot.add_pin('half', relative_position=.5, use_arrow=True,
location='right')
x = [4, 5, 6]
y = [3, 3, 3]
plot.plot(x, y)
for xi, yi in zip(x, y):
plot.add_pin_at_xy(xi, yi, '(%d,%d)' % (xi, yi), location='below')
plot.add_pin('half', relative_position=.5, use_arrow=True,
location='above')
x = [3, 4, 5]
y = [1, 10, 100]
plot.plot(x, y)
for xi, yi in zip(x, y):
plot.add_pin_at_xy(xi, yi, '(%d,%d)' % (xi, yi), location='above left')
plot.add_pin('half', relative_position=.5, use_arrow=True,
location='right')
plot.save('relative_pin_log')
def main():
"""Event display for an event of station 503
Date Time Timestamp Nanoseconds
2012-03-29 10:51:36 1333018296 870008589
Number of MIPs
35.0 51.9 35.8 78.9
Arrival time
15.0 17.5 20.0 27.5
"""
# Detector positions in ENU relative to the station GPS
x = [-6.34, -2.23, -3.6, 3.46]
y = [6.34, 2.23, -3.6, 3.46]
# Scale mips to fit the graph
n = [35.0, 51.9, 35.8, 78.9]
# Make times relative to first detection
t = [15., 17.5, 20., 27.5]
dt = [ti - min(t) for ti in t]
plot = Plot()
plot.scatter([0], [0], mark='triangle')
plot.add_pin_at_xy(0, 0, 'Station 503', use_arrow=False, location='below')
plot.scatter_table(x, y, dt, n)
plot.set_scalebar(location="lower right")
plot.set_colorbar('$\Delta$t [ns]')
plot.set_axis_equal()
plot.set_mlimits(max=16.)
plot.set_slimits(min=10., max=100.)
plot.set_xlabel('x [m]')
plot.set_ylabel('y [m]')
plot.save('event_display')
# Add event by Station 508
# Detector positions in ENU relative to the station GPS
x508 = [6.12, 0.00, -3.54, 3.54]
y508 = [-6.12, -13.23, -3.54, 3.54]
# Event GPS timestamp: 1371498167.016412100
# MIPS
n508 = [5.6, 16.7, 36.6, 9.0]
# Arrival Times
t508 = [15., 22.5, 22.5, 30.]
dt508 = [ti - min(t508) for ti in t508]
plot = MultiPlot(1, 2, width=r'.33\linewidth')
plot.set_xlimits_for_all(min=-10, max=15)
plot.set_ylimits_for_all(min=-15, max=10)
plot.set_mlimits_for_all(min=0., max=16.)
plot.set_colorbar('$\Delta$t [ns]', False)
plot.set_colormap('blackwhite')
plot.set_scalebar_for_all(location="upper right")
p = plot.get_subplot_at(0, 0)
p.scatter([0], [0], mark='triangle')
p.add_pin_at_xy(0, 0, 'Station 503', use_arrow=False, location='below')
p.scatter_table(x, y, dt, n)
p.set_axis_equal()
p = plot.get_subplot_at(0, 1)
p.scatter([0], [0], mark='triangle')
p.add_pin_at_xy(0, 0, 'Station 508', use_arrow=False, location='below')
p.scatter_table(x508, y508, dt508, n508)
p.set_axis_equal()
plot.show_yticklabels_for_all([(0, 0)])
plot.show_xticklabels_for_all([(0, 0), (0, 1)])
plot.set_xlabel('x [m]')
plot.set_ylabel('y [m]')
plot.save('multi_event_display')
X = np.linspace(0., 2 * L, num=1000)
Y_sqr = [square(x) for x in X]
Y = lambda n: [fourier(x, n) for x in X]
graph = Plot()
graph.set_title("Fourier approximation")
graph.plot(x=X, y=Y(3), linestyle='red', mark=None, legend='n=3')
graph.plot(x=X, y=Y(5), linestyle='yellow', mark=None, legend='n=5')
graph.plot(x=X, y=Y(8), linestyle='green', mark=None, legend='n=8')
graph.plot(x=X, y=Y(13), linestyle='blue', mark=None, legend='n=13')
graph.plot(x=X, y=Y(55), linestyle='cyan', mark=None, legend='n=55')
graph.plot(x=X, y=Y_sqr, linestyle='black', mark=None, legend='square')
graph.save('fourier_with_legend')
graph = Plot()
graph.set_title("Fourier approximation")
graph.plot(x=X, y=Y(3), mark=None, linestyle='black!20')
add_custom_pin(graph, X, Y(3), 3)
graph.plot(x=X, y=Y(5), mark=None, linestyle='black!30')
add_custom_pin(graph, X, Y(5), 5)
graph.plot(x=X, y=Y(8), mark=None, linestyle='black!40')
add_custom_pin(graph, X, Y(8), 8)
graph.plot(x=X, y=Y(13), mark=None, linestyle='black!60')
add_custom_pin(graph, X, Y(13), 13, distance='5ex')
graph.plot(x=X, y=Y(55), mark=None, linestyle='black!80')
add_custom_pin(graph, X, Y(55), 55)
graph.plot(x=X, y=Y_sqr, mark=None, linestyle='thick')
