alpha=0.4,
linewidth=0.5)
ax.legend(loc='lower right')
# Add difference
ax = plt.subplot(gs[3, 0], sharex=ax)
ax.set_xlabel('x')
diff_factor = 1.e-7
ax.set_ylabel(r'diff., $\times10^{-7}$')
diff = integral_n - integral_a
ax.bar(x_edges[:-1], diff / diff_factor, bar_width * 2.0, align='edge')
# Freeze axis limits and draw bin edges
ax.autoscale(enable=True, axis='y')
ymin, ymax = ax.get_ylim()
ax.vlines(integrator.points.xedges.data(),
ymin,
ymax,
linestyle='--',
alpha=0.4,
linewidth=0.5)
# Save figure and graph as images
savefig(tutorial_image_name('png'))
savegraph(fcn.sum, tutorial_image_name('png', suffix='graph'), rankdir='TB')
plt.show()
narray = np.exp(-0.5 * (X - 15.0)**2 / 10.0**2 - 0.5 * (Y - 30.0)**2 / 3.0**2)
# Create a histogram instance with data, stored in `narray`
# and edges, stored in `edges`
hist = C.Histogram2d(edgesx, edgesy, narray)
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('pcolorfast')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_pcolorfast(colorbar=True)
savefig(tutorial_image_name('png', suffix='pcolorfast'))
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('imshow')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_imshow(colorbar=True)
savefig(tutorial_image_name('png', suffix='imshow'))
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('matshow')
narray = np.exp(-0.5 * (X - cx[15])**2 / 150.0**2 - 0.5 *
(Y - cy[20])**2 / 0.10**2)
# Create a histogram instance with data, stored in `narray`
# and edges, stored in `edges`
hist = C.Histogram2d(edgesx, edgesy, narray)
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('pcolormesh')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_pcolormesh(colorbar=True)
savefig(tutorial_image_name('png', suffix='pcolormesh'))
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('pcolor')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_pcolor(colorbar=True)
savefig(tutorial_image_name('png', suffix='pcolor'))
plt.show()
# Create a histogram instance with data, stored in `narray`
# and edges, stored in `edges`
hist = C.Histogram2d(edgesx, edgesy, narray)
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = plt.subplot(111, projection='3d')
ax.set_title('surface')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_surface(cmap='viridis', colorbar=True)
savefig(tutorial_image_name('png', suffix='surface'))
fig = plt.figure()
ax = plt.subplot(111, projection='3d')
ax.set_title('bar3d')
ax.minorticks_on()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
hist.hist.hist.plot_bar3d(cmap=True, colorbar=True)
savefig(tutorial_image_name('png', suffix='bar3d'))
fig = plt.figure()
ax = plt.subplot(111, projection='3d')
ax.set_title('wireframe')
# Freeze axis limits and draw bin edges
ax.autoscale(enable=True, axis='y')
ymin, ymax = ax.get_ylim()
ax.vlines(integrator.points.xedges.data(),
ymin,
ymax,
linestyle='--',
alpha=0.4,
linewidth=0.5)
ax.legend(loc='lower right')
ymin, ymax = ax.get_ylim()
# Save figure and graph as images
savefig(tutorial_image_name('png', suffix='1'))
# Do more plotting
fig = plt.figure()
ax = plt.subplot(111)
ax.minorticks_on()
# ax.grid()
ax.set_ylabel('f(x)')
ax.set_title(r'$a\,\sin(x)+b\,\sin(kx)$')
ax.autoscale(enable=True, axis='y')
ax.set_ylim(ymin, ymax)
ax.axhline(0.0, linestyle='--', color='black', linewidth=1.0, alpha=0.5)
def plot_sample():
label = 'a={}, b={}, k={}'.format(*(p.value() for p in (pa, pb, pk)))
integrator.points.setLabel('Sampler\n(Gauss-Legendre)')
integrator.hist.setLabel('Integrator\n(convolution)')
sin_t.sin.setLabel('sin(ax+by)')
arg_t.sum.setLabel('ax+by')
# Make 2d color plot
fig = plt.figure()
ax = plt.subplot(111, xlabel='x', ylabel='y', title=r'$\int\int\sin(ax+by)$')
ax.minorticks_on()
ax.set_aspect('equal')
# Draw the function and integrals
integrator.hist.hist.plot_pcolormesh(colorbar=True)
# Save figure
savefig(tutorial_image_name('png'))
# Add integration points and save
ax.scatter(X, Y, c='red', marker='.', s=0.2)
ax.set_xlim(-0.5, 0.5)
ax.set_ylim(0.0, 1.0)
savefig(tutorial_image_name('png', suffix='zoom'))
# Plot 3d function and a histogram
fig = plt.figure()
ax = plt.subplot(111,
xlabel='x',
ylabel='y',
title=r'$\sin(ax+by)$',
projection='3d')
ax.set_title('Plot title (left)')
ax.minorticks_on()
ax.grid()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
plt.ticklabel_format(style='sci',
axis='y',
scilimits=(-2, 2),
useMathText=True)
hist1.hist.hist.plot_hist(label='exp(+)')
hist2.hist.hist.plot_hist(label='exp(-)')
hist3.hist.hist.plot_hist(label='gauss')
ax.legend()
savefig(tutorial_image_name('png', suffix='hist'))
fig = plt.figure()
ax = plt.subplot(111)
ax.set_title('Plot title (left)')
ax.minorticks_on()
ax.grid()
ax.set_xlabel('x label')
ax.set_ylabel('y label')
plt.ticklabel_format(style='sci',
axis='y',
scilimits=(-2, 2),
useMathText=True)
hist1.hist.hist.plot_bar(label='exp(+)', alpha=0.4)
hist2.hist.hist.plot_bar(label='exp(-)', alpha=0.4)
