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')