from matplotlib import cm
selected_paths = ["/media/abdu924/Important/Owncloud/alps_data/2site/U1.0/dd_interaction/tmp_data/b18_magnon_U1.0Sx_unfold",
"/media/abdu924/Important/Owncloud/alps_data/2site/U1.0/dd_interaction/tmp_data/b25_magnon_U1.0Sx_unfold",
"/media/abdu924/Important/Owncloud/alps_data/2site/U1.0/dd_interaction/tmp_data/b30_magnon_U1.0Sx_unfold"][::1]
selected_paths_sp = ["/media/abdu924/Important/Owncloud/alps_data/Magnon/t0125/spectra/U1.0/b18",
"/media/abdu924/Important/Owncloud/alps_data/Magnon/t0125/spectra/U1.0/b25Sx",
"/media/abdu924/Important/Owncloud/alps_data/Magnon/t0125/spectra/U1.0/b30hz0"][::1]
full_csv_name = 'data_real_normal.csv'
#full_csv_name = 'data_real_weak_1.6.csv'
#full_csv_name = 'data_real_bubble.csv'
x_labels = [r'$\Gamma$', 'X', 'M', r'$\Gamma$']
x_positions = [0, 1., 2., 3.385]
y_labels = [2, 4]
y_positions = [0.2, 0.4]
all_component_names = ['Na-Nb', 'Sz', 're_yy']
mode_style = "physical"
#mode_style = "diagonal"
cross_hopping = 0
parity = "odd"
impurity_solver = "alps"
U_val = 4.0
beta = 30.0
doping = 0
selected_components = [1, 2, 8]
legends = [0.28, 0.30, 0.37][::1]
site = [2, 2, 2, 2, 2, 2, 2, 2, 2 ,2,2][::1]
axes = []
betas = [ 18., 25., 30., 30.0, 30.0, 30.0, 30.0, 30.0][::1]
temps = [0.056, 0.040 , 0.033]
phase = ['(AFM)', '(AFM)', '(N)'][::1]
moment_x = [ [0.0,0] ,[0.62, -0.62], [0.74, -0.74], [0.3968,0],[0.01,0] ]
moment_z = [[0., 0.0] ,[0., 0.0], [0., 0.0], [0, 0.793], [0, 0.531]]
#moment_x = [ [0.74, -0.74] ,[0.73, -0.73], [0.431,-0.431], [0.3968,-0.3968], [0.,-0.] ]
#moment_z = [[0.0, 0.0] ,[0.222, 0.222], [0.668, 0.668], [0.793, 0.793], [0.9984, 0.9984]]
fig = plt.figure(figsize = (len(selected_components) * 2.2 * fig_width, len(selected_paths) * 3 * fig_height), frameon=False)
component_index = 0
for path_index in np.arange(len(selected_paths)):
#components_to_plot = all_components
full_path_frame = get_full_path_frame(site[path_index],selected_paths[path_index], full_csv_name)
full_path_frame_1 = get_full_path_frame_1(site[path_index],selected_paths[path_index], full_csv_name)
#components_to_plot = np.array(['re_zz0+re_zz1','re_zz0-re_zz1','Sz0+Sz1' ,'Sz0-Sz1'])
#components_to_plot = np.array(['im_xx0+im_xx1'])
if(site[path_index] == 1):
components_to_plot = np.array(['N_a-N_b', 'Sz', 're_xx', 'im_xx','re_yy', 'im_yy'])
#components_to_plot = np.array(['re_xx', 'im_xx','re_yy', 'im_yy'])
#component_names = { 'N_a-N_b': r"$O$", 'Sz': r"$Sz$", 're_xx': r"$\phi_x^R$", 'im_xx': r"$\phi_x^I$",'re_yy': r"$\phi_y^R$", 'im_yy': r"$\phi_y^I$"}
component_names = { 'N_a-N_b': r"$O$", 'Sz': r"$S^z$", 're_xx': r"$R^x$", 'im_xx': r"$I^x$",'re_yy': r"$R^y$", 'im_yy': r"$I^y$" }
#component_names = { 're_xx': r"$R_x$", 'im_xx': r"$I_x$",'re_yy': r"$R_y$", 'im_yy': r"$I_y$" }
if(site[path_index] == 2):
components_to_plot = np.array(['$S^x_{0}$', '$S^y_{0}$', '$S^z_{0}$'])
#components_to_plot = np.array([ 're_xx0', 'im_xx0','re_yy0', 'im_yy0'])
#component_names = { 'N_a0-N_b0': r"$O$", 'Sz0': r"$S^z$", 're_xx0': r"$\phi_x^R$", 'im_xx0': r"$\phi_x^I$",'re_yy0': r"$\phi_y^R$", 'im_yy0': r"$\phi_y^I$"}
component_names = { 'N_a0-N_b0': r"$O$", 'Sz0': r"$S^z$", 're_xx0': r"$R^x$", 'im_xx0': r"$I^x$",'re_yy0': r"$\R^y$", 'im_yy0': r"$I^y$"}
component_names = { '$S^x_{0}$': r"$\chi^{xx}$", '$S^y_{0}$': r"$\chi^{yy}$", '$S^z_{0}$': r"$\chi^{zz}$"}
#print(components_to_plot, all_betas, all_crystal_fields, all_dopings)
component_index = 0
spectra = np.load(os.path.join(selected_paths_sp[path_index], "spectra.npy"))
wgrid = np.load(os.path.join(selected_paths_sp[path_index], "wgrid.npy"))
for crystal_field in all_crystal_fields:
for component in components_to_plot:
mode_style = "physical"
#mode_style = "diagonal"
cross_hopping = 0
parity = "odd"
impurity_solver = "alps"
U_val = 4.0
##beta = 30.0
beta = betas[path_index]
doping = 0
if(component_index != 3):
path_frame = full_path_frame.query('cross_hopping == ' + str(cross_hopping)
+ '& beta == ' + str(beta)
+ ' & impurity_solver == "' + impurity_solver + '"'
+ ' & mode_style == "' + mode_style + '"')
else:
path_frame = full_path_frame_1.query('cross_hopping == ' + str(cross_hopping)
+ '& beta == ' + str(beta)
+ ' & impurity_solver == "' + impurity_solver + '"'
+ ' & mode_style == "' + mode_style + '"')
all_crystal_fields = np.sort(path_frame['crystal_field'].unique())[::-1]
all_dopings = np.sort(path_frame['doping'].unique())[::-1]
del_index = np.where(all_dopings==1.5)
all_dopings = np.delete(all_dopings, del_index)
all_mode_styles = np.sort(path_frame['mode_style'].unique())
all_components = np.sort(path_frame['component'].unique())
all_cross_hoppings = np.sort(path_frame['cross_hopping'].unique())[::-1]
nb_crytal_fields = len(all_crystal_fields)
all_betas = np.sort(path_frame['beta'].unique())[::-1]
print(selected_paths)
print(component)
#col_index = (full_index - 1) % nb_components_per_line
#line_index = (full_index - 1) // nb_components_per_line
#line_index, col_index = get_lin_col_indices(crystal_field, all_crystal_fields, component, components_to_plot)
#full_index = 1 + len(components_to_plot) * line_index + col_index
pivot_table = get_pivot_table2(component, crystal_field, mode_style, cross_hopping, parity, impurity_solver)
if (pivot_table is None):
print ("none", component)
# Do not create axes if no data to plot
#continue
vmax = 1.0
print(len(selected_paths))
print(len(components_to_plot))
line_index, col_index = path_index, component_index
full_index = 1 + (len(components_to_plot)) * line_index + col_index
print(line_index, component_index, full_index)
if (component_index != 3):
ax = fig.add_subplot(len(selected_paths), len(components_to_plot), full_index)
else:
#ax = fig.add_subplot(len(selected_paths), len(components_to_plot), full_index, projection='3d')
ax = fig.add_subplot(len(selected_paths), len(components_to_plot), full_index)
#ax = fig.add_subplot(7, 6, full_index)
axes.append(ax)
if(line_index < len(selected_paths)-1 and component_index !=3 ):
ax.xaxis.set_ticks([])
elif(component_index < 3):
ax.set_xticks(x_positions)
ax.set_xticklabels(x_labels)
print(crystal_field)
#set_axis_style(ax, crystal_field, all_crystal_fields, component, components_to_plot)
if (component_index != 6):
to_plot_x = pivot_table.columns
to_plot_y = pivot_table.index.values
data = pivot_table.values
#######################################
#### Definition of the function to plot
#######################################
#to_plot_z = np.log10(data + 1e-5)
to_plot_z = data / (5.5 + data)
to_plot_z2 = data
#Z=to_plot_z
def f(x, y):
return np.absolute(data)
X=to_plot_x
Y=to_plot_y
X, Y = np.meshgrid(to_plot_x,to_plot_y)
Z = f(X, Y)
print(X.shape, Z.shape)
#print(X.shape)
#print(to_plot_x.shape)
#print(Z.shape)
#########################################
#### Plotting instruction with parameters
#########################################
if (component_index != 3):
im = plt.pcolormesh(to_plot_x, to_plot_y, to_plot_z,
rasterized=True,
cmap=plt.get_cmap('jet'),
#cmap=plt.get_cmap('gist_stern_r'),
vmin=0, vmax=vmax
#vmax = min(40, np.amax(to_plot_z))
)
else:
norm = plt.Normalize(Z.min(), Z.max())
colors = cm.viridis(norm(Z))
rcount, ccount, _ = colors.shape
print(rcount, ccount)
if(path_index != 10):
#print(Z[:30, 95])
Z[:, 100] = 1.0 * (Z[:, 95])
#ax.plot_surface(X, Y, Z, cmap=plt.get_cmap('jet'), rstride=1, cstride=1, edgecolor='none')
#surf = ax.plot_surface(X, Y, Z, rcount=30, ccount=20,
# facecolors=colors, shade=False)
ax.set_ylim([0, 0.25])
#ax.plot_wireframe(X, Y, Z, rstride=200, cstride=5, cmap='jet')
ax.plot(wgrid, spectra, linewidth=3.2)
#surf.set_facecolor((0,0,0,0))
#ax.view_init(50, -40)
#fig.colorbar(im, ax=ax)
if (component_index == 0):
x_pos = [1.7, 1.7]
y_pos = [0.22, 0.22]
x_direct = moment_x[path_index]
y_direct = moment_z[path_index]
if(path_index != 0):
ax.quiver(x_pos,y_pos,x_direct,y_direct, color=['r','y'], scale=2.5, width=0.03)
#ax.axis([-2.5,2.5,-2.5,2.5])
text_size = 42
for tick in ax.xaxis.get_major_ticks():
tick.label.set_fontsize(text_size+10)
for tick in ax.yaxis.get_major_ticks():
tick.label.set_fontsize(text_size+10)
if (col_index == 3):
for tick in ax.xaxis.get_major_ticks():
tick.label.set_fontsize(text_size-25)
for tick in ax.yaxis.get_major_ticks():
tick.label.set_fontsize(text_size-25)
#for tick in ax.zaxis.get_major_ticks():
# tick.label.set_fontsize(text_size-28)
specw = np.zeros_like(to_plot_x)
for q_index in np.arange(to_plot_x.shape[0]):
specw[q_index] = np.trapz(to_plot_z2[:300, q_index], to_plot_y[:300])
if(path_index == 1 and q_index == 100):
specw[q_index] = specw[q_index - 1]
ax.plot(to_plot_x, specw/10.0, color='w', linewidth= 3.2)
if(component_index == 2):
ax.tick_params(labelleft=False,labeltop=False, labelright=True)
ax.tick_params(left=False,top=False, right=True, length=5, width=4)
elif(component_index == 0):
ax.tick_params(left=True,top=False, right=False, length=5, width=4)
if(component_index == 2):
ax.yaxis.set_label_position("right")
if (col_index > 0 and col_index < 2 and col_index !=3 ):
ax.yaxis.set_ticks([])# s_position('none')
elif(col_index !=3):
if(col_index == 0):
if(path_index ==1):
ax.text(0.55, 0.95, r"$T=$"+ str(temps[path_index]),
verticalalignment='top', horizontalalignment='right',
transform=ax.transAxes,
color='white', fontsize=50)
else:
ax.text(0.62, 0.95, r"$T=$"+ str(temps[path_index]),
verticalalignment='top', horizontalalignment='right',
transform=ax.transAxes,
color='white', fontsize=50)
#if(path_index < 2):
# ax.text(0.57, 0.75, r"$H=0$" + "," + " " + phase[path_index],
# verticalalignment='top', horizontalalignment='right',
# transform=ax.transAxes,
# color='white', fontsize=30)
#else:
# ax.text(0.45, 0.75, r"$H=0$" + "," + " " + phase[path_index],
# verticalalignment='top', horizontalalignment='right',
# transform=ax.transAxes,
# color='white', fontsize=30)
#ax.yaxis.set_ticks([0.1, 0.2, 0.3, 0.4])# s_position('none')
ax.yaxis.set_ticks([0.2, 0.4, 0.6, 0.8])
if(col_index == 0):
ax.set_ylabel(r"Energy", fontsize=text_size+10)
elif(col_index == 2):
ax.set_ylabel(r"SW", fontsize=text_size+10)
if(col_index == 2):
ax.set_yticks(y_positions)
ax.set_yticklabels(y_labels, fontsize=text_size+10 )
if (col_index == 0):
#ax.set_ylabel(r"$\Delta$ = " + str(crystal_field), fontsize=text_size+2)
pass
if (line_index < len(all_crystal_fields) - 1):
ax.xaxis.set_ticks([])# s_position('none')
#if (line_index == 0):
# ax.set_title(component_names[component], fontsize=text_size+2, pad=26)
#########################################
#########################################
if(component_index == 6):
ax.set_yticks([0, 0.25])
ax.set_zticks([0, 10, 20, 30])
if(path_index == 0):
#plt.title(component, fontsize=50, pad=20)
#if(component_index == 3):
# plt.title(component, fontsize=50, pad=78)
ax.set_title(component_names[component], fontsize=text_size+25, pad=42)
if(component_index == 3):
ax.set_title(component_names[component], fontsize=text_size+25, pad=92)
#full_index += 1
if (component_index != 3):
ax.set_ylim([0., 0.5])
#fig.tight_layout(pad=0.5)
#fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.01, hspace=0.05)
#else:
#fig.subplots_adjust(left=None, bottom=None, right=None, top=None, wspace=0.1, hspace=0.05)
if (component_index == 3):
ax.set_ylim([0, 2.0])
ax.set_xlim([-1.5, 1.5])
#ax.set_zlim([0, 30.0])
component_index += 1
#plt.subplots_adjust(left=0.125,bottom=0.1, right=0.9, top=0.9, wspace=0.1, hspace=0.1)
#plt.subplot_tool()
#plt.show()
#for i in np.arange(to_plot_x.shape[0]):
# print(i, to_plot_x[i])
plt.tight_layout()
plt.savefig("all_dispersions_IR_U_" + str(U_val) + "_ch_" + str(cross_hopping) + "_beta_" + str(beta) + "_" + mode_style + "_fine.png")
