def plot_graph(self, fit_objective):
plt.subplot(self.gs[0])
y_min = None
y_max = None
for i_dataset in range(0, fit_objective.fitObjectCount()):
# retrieving data from fit suite
real_data = fit_objective.experimentalData(i_dataset).data()
sim_data = fit_objective.simulationResult(i_dataset).data()
# data values
sim_values = sim_data.getArray()
real_values = real_data.getArray()
# default font properties dictionary to use
font = {'family': 'serif',
'weight': 'normal',
'size': label_fontsize}
plt.semilogy(sim_data.getAxis(0).getBinCenters(), sim_values, 'b',
real_data.getAxis(0).getBinCenters(), real_values, 'k--')
if y_min is None or y_min > 0.5 * np.min(real_values):
y_min = 0.5 * np.min(real_values)
if y_max is None or y_max < 5 * np.max(real_values):
y_max = 5 * np.max(real_values)
plt.ylim((y_min, y_max))
xlabel = ba.get_axes_labels(fit_objective.experimentalData(i_dataset), ba.AxesUnits.DEFAULT)[0]
plt.legend(['BornAgain', 'Reference'], loc='upper right', prop=font)
plt.xlabel(xlabel, fontdict=font)
plt.ylabel("Intensity", fontdict=font)
plt.title("Specular data fitting", fontdict=font)
def plot_result(sim_result, ref_result, bin_start=0, bin_end=-1):
"""
Plots the graphs of obtained simulation data
"""
sim_data = sim_result.array()
ref_data = ref_result.array()
plt.semilogy(
get_real_data_axis(bin_start, bin_end) * 180 / np.pi,
get_real_data_values(bin_start, bin_end), sim_result.axis(), sim_data,
ref_result.axis(), ref_data)
xlabel = ba.get_axes_labels(sim_result, ba.AxesUnits.DEFAULT)[0]
ylabel = "Intensity"
plt.xlabel(xlabel, fontsize=16)
plt.ylabel(ylabel, fontsize=16)
plt.legend(['Experimental data', 'Simulation', 'Reference'],
loc='upper right',
fontsize=16)
plt.show()
def plot(fontsize=16):
"""
Creates 4 plots: 2D experiment, 2D simulation, slice along Qz and slice along Qy
"""
plt.style.use('seaborn-talk')
matplotlib.rcParams['xtick.labelsize'] = fontsize
matplotlib.rcParams['ytick.labelsize'] = fontsize
data = load_data()
plt.figure(figsize=(22, 17))
zmin = 0.1
zmax = 2.0e+06
qz_slice = 0.4
qy_slice = 0.64
# ====================
# Experiment 2D
# ====================
plt.subplot(2, 2, 1)
ba.plot_colormap(data, units=ba.AxesUnits.QSPACE, zmin=zmin, zmax=zmax)
plt.axhline(y=qz_slice, color='0.5', linestyle='--', linewidth=1)
plt.axvline(x=qy_slice, color='0.5', linestyle='--', linewidth=1)
plt.title("Experiment", fontsize=fontsize)
# ax.tick_params(axis='both', which='major', labelsize=fontsize)
# ====================
# Simulation 2D
# ====================
result = run_simulation()
axes_labels = ba.get_axes_labels(result, ba.AxesUnits.QSPACE)
plt.subplot(2, 2, 2)
ba.plot_colormap(result, units=ba.AxesUnits.QSPACE, zmin=zmin, zmax=zmax)
plt.axhline(y=qz_slice, color='0.5', linestyle='--', linewidth=1)
plt.axvline(x=qy_slice, color='0.5', linestyle='--', linewidth=1)
plt.title("BornAgain simulation", fontsize=fontsize)
# ====================
# projection along Qz
# ====================
plt.subplot(2, 2, 3)
exp_qz = data.histogram2d(ba.AxesUnits.QSPACE).projectionY(qy_slice)
sim_qz = result.histogram2d(ba.AxesUnits.QSPACE).projectionY(qy_slice)
plt.semilogy(exp_qz.getBinCenters(),
exp_qz.getBinValues(),
color='k',
marker='.',
markersize=5,
linestyle='None',
label="Experiment")
plt.semilogy(sim_qz.getBinCenters(),
sim_qz.getBinValues(),
color='g',
linewidth=2,
label="Simulation")
# plt.xlim(0.1, 1.21) # uncomment and edit to set x axis limits
# plt.ylim(0.5, zmax) # uncomment and edit to set y axis limits
plt.xlabel(axes_labels[1], fontsize=fontsize)
plt.ylabel(r'$\mathrm{I(Q_z)}$, a.u.', fontsize=fontsize)
plt.legend(fontsize=fontsize)
plt.title(r"Slice along $Q_z$", fontsize=fontsize)
# =====================
# projection along Qy
# =====================
plt.subplot(2, 2, 4)
exp_qy = data.histogram2d(ba.AxesUnits.QSPACE).projectionX(qz_slice)
sim_qy = result.histogram2d(ba.AxesUnits.QSPACE).projectionX(qz_slice)
plt.semilogy(exp_qy.getBinCenters(),
exp_qy.getBinValues(),
color='k',
marker='.',
markersize=5,
linestyle='None',
label="Experiment")
plt.semilogy(sim_qy.getBinCenters(),
sim_qy.getBinValues(),
color='g',
linewidth=2,
label="Simulation")
# plt.xlim(-0.81, 0.71) # uncomment and edit to set x axis limits
# plt.ylim(0.5, zmax) # uncomment and edit to set y axis limits
plt.xlabel(axes_labels[0], fontsize=fontsize)
plt.ylabel(r'$\mathrm{I(Q_y)}$, a.u.', fontsize=fontsize)
plt.legend(fontsize=fontsize)
plt.title(r"Slice along $Q_y$", fontsize=fontsize)
# plt.savefig("{}.png".format("my_meso")) # uncomment to save figure
# uncomment to save slices to text files
# np.savetxt("{}_slice_qz.txt".format("my_meso"), np.column_stack([sim_qz.getBinCenters(), sim_qz.getBinValues()]))
# np.savetxt("{}_slice_qy.txt".format("my_meso"), np.column_stack([sim_qy.getBinCenters(), sim_qy.getBinValues()]))
plt.show()