def intensity_1d(self, intensity, ms=20., lw=2., fs=20., title=r'$|\psi^{(j)}|^2$'):
'''
Plot intensity for 1D lattices.
:param intensity: np.array. Field intensity.
:param ms: Positive Float. Default value 20. Markersize.
:param lw: Positive Float. Default value 2. Linewith, connect sublattice sites.
:param fs: Positive Float. Default value 20. Font size.
:param title: String. Default value 'Intensity'. Figure title.
'''
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.positive_real(ms, 'ms')
error_handling.positive_real(lw, 'lw')
error_handling.positive_real(fs, 'fs')
error_handling.string(title, 'title')
fig, ax = plt.subplots()
ax.set_xlabel('$j$', fontsize=fs)
ax.set_ylabel(title, fontsize=fs)
ax.set_title(title, fontsize=fs)
for t, c in zip(self.sys.lat.tags, self.colors):
plt.plot(self.sys.lat.coor['x'][self.sys.lat.coor['tag'] == t],
intensity[self.sys.lat.coor['tag'] == t],
'-o', color=c, ms=ms, lw=lw)
plt.xlim([-1., self.sys.lat.sites])
plt.ylim([0., np.max(intensity)+.05])
fig.set_tight_layout(True)
plt.draw()
return fig
def dir_name(self, dir_name):
'''
Set the name of the directory in which the figures are stored.
:param dir_name: String. Directory name.
'''
error_handling.string(dir_name, 'dir_name')
dir_name = self.dir_main + dir_name
return dir_name
def dir_name(self, dir_name):
'''
Set the name of the directory in which the figures are stored.
:param dir_name: String. Directory name.
'''
error_handling.string(dir_name, 'dir_name')
dir_name = self.dir_main + dir_name
return dir_name
def intensity_disk(self,
intensity,
s=200.,
fs=20.,
lims=None,
figsize=None,
title=r'$|\psi|^2$'):
'''
Plot the intensity. Colormap with identical disk shape.
:param intensity: np.array.Field intensity.
:param s: Default value 200. Disk size.
:param fs: Default value 20. Font size.
:param lims: List. Default value None. Colormap limits.
:param figsize: Tuple. Default value None. Figure size.
:param title: String. Default value '$|\psi_n|^2$'. Title.
:returns:
* **fig** -- Figure.
'''
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.positive_real(s, 's')
error_handling.positive_real(fs, 'fs')
error_handling.tuple_2elem(figsize, 'figsize')
error_handling.string(title, 'title')
fig, ax = plt.subplots(figsize=figsize)
plt.title(title, fontsize=fs + 5)
map_red = plt.get_cmap('Reds')
if lims is None:
lims = [0., np.max(intensity)]
y_ticks = ['0', 'max']
else:
y_ticks = lims
plt.scatter(self.sys.lat.coor['x'],
self.sys.lat.coor['y'],
c=intensity,
s=s,
cmap=map_red,
vmin=lims[0],
vmax=lims[1])
cbar = plt.colorbar(ticks=lims)
ax.set_xticks([])
ax.set_yticks([])
ax.set_xlim(
np.min(self.sys.lat.coor['x']) - 1.,
np.max(self.sys.lat.coor['x']) + 1.)
ax.set_ylim(
np.min(self.sys.lat.coor['y']) - 1.,
np.max(self.sys.lat.coor['y']) + 1.)
cbar.ax.set_yticklabels([y_ticks[0], y_ticks[1]])
cbar.ax.tick_params(labelsize=fs)
ax.set_aspect('equal')
fig.set_tight_layout(True)
plt.draw()
return fig
def fig_lat(self, fig, name):
'''
Save the figure in the directory defined by the method *dir_name()*.
:param fig: Matplotlib fig.
:param name: String. First part of the file name.
'''
error_handling.fig(fig)
error_handling.string(name, 'name')
name_file = self.dir_name + '/' + name + '.' + self.file_format
fig.savefig(name_file, format=self.file_format)
def fig_lat(self, fig, name):
'''
Save the figure in the directory defined by the method *dir_name()*.
:param fig: Matplotlib fig.
:param name: String. First part of the file name.
'''
error_handling.fig(fig)
error_handling.string(name, 'name')
name_file = self.dir_name + '/' + name + '.' + self.file_format
fig.savefig(name_file, format=self.file_format)
def __init__(self, dir_name, dir_main=None, params={}, file_format='png'):
error_handling.string(dir_name, 'dir_name')
error_handling.string(dir_main, 'dir_main')
error_handling.file_format(file_format)
self.params = params
self.file_format = file_format
if dir_main is None:
self.dir_main = 'figs/'
else:
self.dir_main = dir_name
self.dir_name = self.dir_name(dir_name)
self.create_dir()
def __init__(self, dir_name, dir_main=None, params={}, file_format='png'):
error_handling.string(dir_name, 'dir_name')
error_handling.string(dir_main, 'dir_main')
error_handling.file_format(file_format)
self.params = params
self.file_format = file_format
if dir_main is None:
self.dir_main = 'figs/'
else:
self.dir_main = dir_name
self.dir_name = self.dir_name(dir_name)
self.create_dir()
def intensity_area(self, intensity, s=1000., lw=1., fs=20., plt_hop=False,
figsize=None, title=r'$|\psi|^2$'):
'''
Plot the intensity. Intensity propotional to disk shape.
:param intensity: np.array. Intensity.
:param s: Positive Float. Default value 1000.
Circle size given by s * intensity.
:param lw: Positive Float. Default value 1. Hopping linewidths.
:param fs: Positive Float. Default value 20. Fontsize.
:param plt_hop: Boolean. Default value False. Plot hoppings.
:param figsize: Tuple. Default value None. Figure size.
:param title: String. Default value '$|\psi_{ij}|^2$'. Figure title.
:returns:
* **fig** -- Figure.
'''
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.positive_real(s, 's')
error_handling.positive_real(fs, 'fs')
error_handling.boolean(plt_hop, 'plt_hop')
error_handling.tuple_2elem(figsize, 'figsize')
error_handling.string(title, 'title')
fig, ax = plt.subplots()
ax.set_xlabel('$i$', fontsize=fs)
ax.set_ylabel('$j$', fontsize=fs)
ax.set_title(title, fontsize=fs)
if plt_hop:
plt.plot([self.sys.lat.coor['x'][self.sys.hop['i'][:]],
self.sys.lat.coor['x'][self.sys.hop['j'][:]]],
[self.sys.lat.coor['y'][self.sys.hop['i'][:]],
self.sys.lat.coor['y'][self.sys.hop['j'][:]]],
'k', lw=lw)
for tag, color in zip(self.sys.lat.tags, self.colors):
plt.scatter(self.sys.lat.coor['x'][self.sys.lat.coor['tag'] == tag],
self.sys.lat.coor['y'][self.sys.lat.coor['tag'] == tag],
s=100*s*intensity[self.sys.lat.coor['tag'] == tag],
c=color, alpha=0.5)
ax.set_aspect('equal')
ax.axis('off')
x_lim = [np.min(self.sys.lat.coor['x'])-2., np.max(self.sys.lat.coor['x'])+2.]
y_lim = [np.min(self.sys.lat.coor['y'])-2., np.max(self.sys.lat.coor['y'])+2.]
ax.set_xlim(x_lim)
ax.set_ylim(y_lim)
fig.set_tight_layout(True)
plt.draw()
return fig
def intensity_disk(self, intensity, s=200., fs=20., lims=None, figsize=None,
title=r'$|\psi|^2$'):
'''
Plot the intensity. Colormap with identical disk shape.
:param intensity: np.array.Field intensity.
:param s: Default value 200. Disk size.
:param fs: Default value 20. Font size.
:param lims: List. Default value None. Colormap limits.
:param figsize: Tuple. Default value None. Figure size.
:param title: String. Default value '$|\psi_n|^2$'. Title.
:returns:
* **fig** -- Figure.
'''
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.positive_real(s, 's')
error_handling.positive_real(fs, 'fs')
error_handling.tuple_2elem(figsize, 'figsize')
error_handling.string(title, 'title')
fig, ax = plt.subplots(figsize=figsize)
plt.title(title, fontsize=fs+5)
map_red = plt.get_cmap('Reds')
if lims is None:
lims = [0., np.max(intensity)]
y_ticks = ['0', 'max']
else:
y_ticks = lims
plt.scatter(self.sys.lat.coor['x'], self.sys.lat.coor['y'], c=intensity, s=s,
cmap=map_red, vmin=lims[0], vmax=lims[1])
cbar = plt.colorbar(ticks=lims)
ax.set_xticks([])
ax.set_yticks([])
ax.set_xlim(np.min(self.sys.lat.coor['x'])-1., np.max(self.sys.lat.coor['x'])+1.)
ax.set_ylim(np.min(self.sys.lat.coor['y'])-1., np.max(self.sys.lat.coor['y'])+1.)
cbar.ax.set_yticklabels([y_ticks[0], y_ticks[1]])
cbar.ax.tick_params(labelsize=fs)
ax.set_aspect('equal')
fig.set_tight_layout(True)
plt.draw()
return fig
def butterfly(self, betas, butterfly, lw=1., fs=20., lims=None, title=''):
'''
Plot energies depending on a parameter.
:param betas: np.array. Parameter values.
:param butterfly: np.array. Eigenvalues.
:param lw: Positive Float. Default value 1. Hopping linewidths.
:param fs: Positive Float. Default value 20. Fontsize.
:param lims: List, lims[0] energy min, lims[1] energy max.
:param title: Default value ''. Figure title.
'''
error_handling.ndarray_empty(betas, 'betas')
error_handling.ndarray_empty(butterfly, 'butterfly')
error_handling.positive_real(lw, 'lw')
error_handling.positive_real(fs, 'fs')
error_handling.lims(lims)
error_handling.string(title, 'title')
i_beta_min = np.argmin(np.abs(betas))
if lims is None:
lims = [butterfly[i_beta_min, 0], butterfly[i_beta_min, -1]]
ind_en = np.argwhere((butterfly[i_beta_min, :] > lims[0])
& (butterfly[i_beta_min, :] < lims[1]))
ind_en = np.ravel(ind_en)
fig, ax = plt.subplots()
plt.title('Energies depending on strain', fontsize=fs)
plt.xlabel(r'$\beta/\beta_{max}$', fontsize=fs)
plt.ylabel('$E$', fontsize=fs)
ax.set_title(title, fontsize=fs)
plt.yticks(np.arange(lims[0], lims[1] + 1, (lims[1] - lims[0]) / 4),
fontsize=fs)
plt.ylim(lims)
beta_max = max(self.sys.betas)
plt.xticks([-beta_max, -0.5 * beta_max, 0, 0.5 * beta_max, beta_max],
fontsize=fs)
ax.set_xticklabels(('-1', '-1/2', '0', '1/2', '1'))
plt.xlim([betas[0], betas[-1]])
for i in ind_en:
plt.plot(betas, butterfly[:, i], 'b', lw=lw)
fig.set_tight_layout(True)
plt.draw()
return fig
def butterfly(self, betas, butterfly, lw=1., fs=20., lims=None, title=''):
'''
Plot energies depending on a parameter.
:param betas: np.array. Parameter values.
:param butterfly: np.array. Eigenvalues.
:param lw: Positive Float. Default value 1. Hopping linewidths.
:param fs: Positive Float. Default value 20. Fontsize.
:param lims: List, lims[0] energy min, lims[1] energy max.
:param title: Default value ''. Figure title.
'''
error_handling.ndarray_empty(betas, 'betas')
error_handling.ndarray_empty(butterfly, 'butterfly')
error_handling.positive_real(lw, 'lw')
error_handling.positive_real(fs, 'fs')
error_handling.lims(lims)
error_handling.string(title, 'title')
i_beta_min = np.argmin(np.abs(betas))
if lims is None:
lims = [butterfly[i_beta_min, 0], butterfly[i_beta_min, -1]]
ind_en = np.argwhere((butterfly[i_beta_min, :] > lims[0]) &
(butterfly[i_beta_min, :] < lims[1]))
ind_en = np.ravel(ind_en)
fig, ax = plt.subplots()
plt.title('Energies depending on strain', fontsize=fs)
plt.xlabel(r'$\beta/\beta_{max}$', fontsize=fs)
plt.ylabel('$E$', fontsize=fs)
ax.set_title(title, fontsize=fs)
plt.yticks(np.arange(lims[0], lims[1]+1, (lims[1]-lims[0])/4), fontsize=fs)
plt.ylim(lims)
beta_max = max(self.sys.betas)
plt.xticks([-beta_max, -0.5*beta_max, 0,
0.5*beta_max, beta_max], fontsize=fs)
ax.set_xticklabels(('-1', '-1/2', '0', '1/2', '1'))
plt.xlim([betas[0], betas[-1]])
for i in ind_en:
plt.plot(betas, butterfly[:, i], 'b', lw=lw)
fig.set_tight_layout(True)
plt.draw()
return fig
def intensity_1d(self,
intensity,
ms=20.,
lw=2.,
fs=20.,
title=r'$|\psi^{(j)}|^2$'):
'''
Plot intensity for 1D lattices.
:param intensity: np.array. Field intensity.
:param ms: Positive Float. Default value 20. Markersize.
:param lw: Positive Float. Default value 2. Linewith, connect sublattice sites.
:param fs: Positive Float. Default value 20. Font size.
:param title: String. Default value 'Intensity'. Figure title.
'''
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.positive_real(ms, 'ms')
error_handling.positive_real(lw, 'lw')
error_handling.positive_real(fs, 'fs')
error_handling.string(title, 'title')
fig, ax = plt.subplots()
ax.set_xlabel('$j$', fontsize=fs)
ax.set_ylabel(title, fontsize=fs)
ax.set_title(title, fontsize=fs)
for t, c in zip(self.sys.lat.tags, self.colors):
plt.plot(self.sys.lat.coor['x'][self.sys.lat.coor['tag'] == t],
intensity[self.sys.lat.coor['tag'] == t],
'-o',
color=c,
ms=ms,
lw=lw)
plt.xlim([-1., self.sys.lat.sites])
plt.ylim([0., np.max(intensity) + .05])
fig.set_tight_layout(True)
plt.draw()
return fig
def intensity_area(self,
intensity,
s=1000.,
lw=1.,
fs=20.,
plt_hop=False,
figsize=None,
title=r'$|\psi|^2$'):
'''
Plot the intensity. Intensity propotional to disk shape.
:param intensity: np.array. Intensity.
:param s: Positive Float. Default value 1000.
Circle size given by s * intensity.
:param lw: Positive Float. Default value 1. Hopping linewidths.
:param fs: Positive Float. Default value 20. Fontsize.
:param plt_hop: Boolean. Default value False. Plot hoppings.
:param figsize: Tuple. Default value None. Figure size.
:param title: String. Default value '$|\psi_{ij}|^2$'. Figure title.
:returns:
* **fig** -- Figure.
'''
error_handling.empty_ndarray(self.sys.lat.coor, 'sys.get_lattice')
error_handling.ndarray(intensity, 'intensity', self.sys.lat.sites)
error_handling.positive_real(s, 's')
error_handling.positive_real(fs, 'fs')
error_handling.boolean(plt_hop, 'plt_hop')
error_handling.tuple_2elem(figsize, 'figsize')
error_handling.string(title, 'title')
fig, ax = plt.subplots()
ax.set_xlabel('$i$', fontsize=fs)
ax.set_ylabel('$j$', fontsize=fs)
ax.set_title(title, fontsize=fs)
if plt_hop:
plt.plot([
self.sys.lat.coor['x'][self.sys.hop['i'][:]],
self.sys.lat.coor['x'][self.sys.hop['j'][:]]
], [
self.sys.lat.coor['y'][self.sys.hop['i'][:]],
self.sys.lat.coor['y'][self.sys.hop['j'][:]]
],
'k',
lw=lw)
for tag, color in zip(self.sys.lat.tags, self.colors):
plt.scatter(
self.sys.lat.coor['x'][self.sys.lat.coor['tag'] == tag],
self.sys.lat.coor['y'][self.sys.lat.coor['tag'] == tag],
s=100 * s * intensity[self.sys.lat.coor['tag'] == tag],
c=color,
alpha=0.5)
ax.set_aspect('equal')
ax.axis('off')
x_lim = [
np.min(self.sys.lat.coor['x']) - 2.,
np.max(self.sys.lat.coor['x']) + 2.
]
y_lim = [
np.min(self.sys.lat.coor['y']) - 2.,
np.max(self.sys.lat.coor['y']) + 2.
]
ax.set_xlim(x_lim)
ax.set_ylim(y_lim)
fig.set_tight_layout(True)
plt.draw()
return fig
def ani(self, ani, name, fps=10):
error_handling.ani(ani)
error_handling.string(name, 'name')
error_handling.positive_int(fps, 'fps')
name_file = self.dir_name + '/' + name + '.mp4'
ani.save(name_file, fps=fps, extra_args=['-vcodec', 'libx264'])
def ani(self, ani, name, fps=10):
error_handling.ani(ani)
error_handling.string(name, 'name')
error_handling.positive_int(fps, 'fps')
name_file = self.dir_name + '/' + name + '.mp4'
ani.save(name_file, fps=fps, extra_args=['-vcodec', 'libx264'])
