def get_plot(
self,
properties=("conductivity", "seebeck", "thermal conductivity"),
x_property=None,
doping_idx=None,
temperature_idx=None,
grid=None,
height=None,
width=None,
doping_type=None,
conductivity_label=None,
conductivity_min=None,
conductivity_max=None,
log_conductivity=None,
seebeck_label=None,
seebeck_min=None,
seebeck_max=None,
log_seebeck=None,
mobility_label=None,
mobility_min=None,
mobility_max=None,
log_mobility=None,
thermal_conductivity_label=None,
thermal_conductivity_min=None,
thermal_conductivity_max=None,
log_thermal_conductivity=None,
power_factor_label=None,
power_factor_min=None,
power_factor_max=None,
log_power_factor=None,
xlabel=None,
xmin=None,
xmax=None,
logx=None,
legend=True,
axes=None,
return_plot_data=False,
plt=None,
style=None,
no_base_style=False,
fonts=None,
):
if axes is None:
if grid is None or len(grid) == 0:
grid = (1, len(properties))
if np.product(grid) < len(properties):
raise ValueError(
"Grid is not large enough to plot all properties")
width, height = get_figsize(*grid, width=width, height=height)
_, axes = pretty_subplot(*grid, width=width, height=height)
else:
if not isinstance(axes, (list, tuple, np.ndarray)):
# single axis given
grid = (1, 1)
else:
axes = np.array(axes)
if grid is None:
grid = axes.shape
if len(grid) == 1:
grid = (1, grid[0])
if np.product(grid) < len(properties):
raise ValueError("Not enough axes to plot all properties")
if doping_type is not None and doping_idx is not None:
warnings.warn(
"Both doping type and doping indexes have been set. This can cause "
"unexpected behaviour.")
prop_dict = {
"conductivity": {
"ylabel": conductivity_label,
"ymin": conductivity_min,
"ymax": conductivity_max,
"logy": log_conductivity,
},
"mobility": {
"ylabel": mobility_label,
"ymin": mobility_min,
"ymax": mobility_max,
"logy": log_mobility,
},
"seebeck": {
"ylabel": seebeck_label,
"ymin": seebeck_min,
"ymax": seebeck_max,
"logy": log_seebeck,
},
"thermal conductivity": {
"ylabel": thermal_conductivity_label,
"ymin": thermal_conductivity_min,
"ymax": thermal_conductivity_max,
"logy": log_thermal_conductivity,
},
"power factor": {
"ylabel": power_factor_label,
"ymin": power_factor_min,
"ymax": power_factor_max,
"logy": log_power_factor,
},
}
if np.product(grid) > len(properties):
n_missing = np.product(grid) - len(properties)
properties = list(properties) + [None] * n_missing
plot_data = []
for (x, y), prop in zip(np.ndindex(grid), properties):
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[y]
elif grid[1] == 1:
ax = axes[x]
else:
ax = axes[x, y]
if prop is None:
ax.axis("off")
else:
prop_data = self.plot_property(
ax,
prop,
x_property=x_property,
temperature_idx=temperature_idx,
doping_idx=doping_idx,
doping_type=doping_type,
xmin=xmin,
xmax=xmax,
xlabel=xlabel,
logx=logx,
**prop_dict[prop],
)
plot_data.append(prop_data)
if legend:
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[-1]
elif grid[1] == 1:
ax = axes[0]
else:
ax = axes[0, -1]
ax.legend(loc="upper left", bbox_to_anchor=(1.01, 1), ncol=1)
if return_plot_data:
return matplotlib.pyplot, plot_data
return matplotlib.pyplot
def get_plot(
self,
plot_fd_tols: bool = False,
plot_total_rate: bool = False,
ymin: float = None,
ymax: float = None,
xmin: float = None,
xmax: float = None,
normalize_energy: bool = True,
separate_rates: bool = True,
doping_idx=0,
temperature_idx=0,
legend=True,
total_color=None,
show_dfde=False,
plot_type="rate",
title=True,
axes=None,
style=None,
no_base_style=False,
fonts=None,
):
if normalize_energy and self.is_metal:
norm_e = self.fermi_levels[0][0]
elif normalize_energy:
cb_idx = {s: v + 1 for s, v in self.vb_idx.items()}
norm_e = np.max([self.energies[s][: cb_idx[s]] for s in self.spins])
else:
norm_e = 0
if doping_idx is None and len(self.doping) == 1:
doping_idx = 0
if temperature_idx is None and len(self.temperatures) == 1:
temperature_idx = 0
if doping_idx is None and temperature_idx is None:
ny = len(self.doping)
nx = len(self.temperatures)
p_idx = [[(x, y) for y in range(nx)] for x in range(ny)]
elif doping_idx is None:
nx = len(self.doping)
ny = 1
p_idx = [[(x, temperature_idx) for x in range(nx)]]
elif temperature_idx is None:
nx = len(self.temperatures)
ny = 1
p_idx = [[(doping_idx, x) for x in range(nx)]]
else:
nx = 1
ny = 1
p_idx = [[(doping_idx, temperature_idx)]]
if axes is None:
_, axes = plt.subplots(ny, nx, figsize=get_figsize(ny, nx))
for y_idx, p_x_idx in enumerate(p_idx):
for x_idx, (n, t) in enumerate(p_x_idx):
if nx == 1 and ny == 1:
ax = axes
elif ny == 1:
ax = axes[x_idx]
else:
ax = axes[y_idx, x_idx]
if x_idx == nx - 1 and y_idx == ny - 1 and legend:
show_legend = True
else:
show_legend = False
doping_fmt = fancy_format_doping(self.doping[n])
temp_fmt = fancy_format_temp(self.temperatures[t])
title_str = f"{doping_fmt} {temp_fmt}"
self.plot_rates_to_axis(
ax,
n,
t,
plot_type=plot_type,
separate_rates=separate_rates,
plot_total_rate=plot_total_rate,
plot_fd_tols=plot_fd_tols,
ymin=ymin,
ymax=ymax,
xmin=xmin,
xmax=xmax,
show_legend=show_legend,
legend_kwargs=_legend_kwargs,
normalize_energy=norm_e,
total_color=total_color,
show_dfde=show_dfde,
)
if title:
ax.set(title=title_str)
return plt
def get_plot(
self,
doping_idx=None,
temperature_idx=None,
properties=("conductivity", "seebeck", "thermal conductivity"),
labels=None,
x_property=None,
grid=None,
height=None,
width=None,
doping_type=None,
conductivity_label=None,
conductivity_min=None,
conductivity_max=None,
log_conductivity=None,
seebeck_label=None,
seebeck_min=None,
seebeck_max=None,
log_seebeck=None,
mobility_label=None,
mobility_min=None,
mobility_max=None,
log_mobility=None,
thermal_conductivity_label=None,
thermal_conductivity_min=None,
thermal_conductivity_max=None,
log_thermal_conductivity=None,
power_factor_label=None,
power_factor_min=None,
power_factor_max=None,
log_power_factor=None,
xlabel=None,
xmin=None,
xmax=None,
logx=None,
legend=True,
axes=None,
plt=None,
style=None,
no_base_style=False,
fonts=None,
):
if axes is None:
if grid is None or len(grid) == 0:
grid = (1, len(properties))
if np.product(grid) < len(properties):
raise ValueError(
"Grid is not large enough to plot all properties")
width, height = get_figsize(*grid, width=width, height=height)
_, axes = pretty_subplot(*grid, width=width, height=height)
else:
if not isinstance(axes, (list, tuple, np.ndarray)):
# single axis given
grid = (1, 1)
else:
axes = np.array(axes)
if grid is None:
grid = axes.shape
if len(grid) == 1:
grid = (1, grid[0])
if np.product(grid) < len(properties):
raise ValueError("Not enough axes to plot all properties")
if doping_type is not None and doping_idx is not None:
warnings.warn(
"Both doping type and doping indexes have been set. This can cause "
"unexpected behaviour.")
if temperature_idx is None and doping_idx is None:
if len(self.doping) == 1 or x_property == "temperature":
warnings.warn(
"Either one of temperature-idx or doping-idx should be "
"set. Using doping-idx of 0")
if doping_type:
if doping_type == "n":
doping_idx = [
i for i, d in enumerate(self.doping) if d <= 0
]
else:
doping_idx = [
i for i, d in enumerate(self.doping) if d >= 0
]
if len(doping_idx) == 0:
raise ValueError(
f"{doping_type}-type doping specified but no doping "
f"concentrations of this type are in the calculations"
)
else:
doping_idx = doping_idx[0]
else:
doping_idx = [0]
else:
warnings.warn(
"Either one of temperature-idx or doping-idx should be "
"set. Using temperature-idx of 0")
temperature_idx = [0]
prop_dict = {
"conductivity": {
"ylabel": conductivity_label,
"ymin": conductivity_min,
"ymax": conductivity_max,
"logy": log_conductivity,
},
"mobility": {
"ylabel": mobility_label,
"ymin": mobility_min,
"ymax": mobility_max,
"logy": log_mobility,
},
"seebeck": {
"ylabel": seebeck_label,
"ymin": seebeck_min,
"ymax": seebeck_max,
"logy": log_seebeck,
},
"thermal conductivity": {
"ylabel": thermal_conductivity_label,
"ymin": thermal_conductivity_min,
"ymax": thermal_conductivity_max,
"logy": log_thermal_conductivity,
},
"power factor": {
"ylabel": power_factor_label,
"ymin": power_factor_min,
"ymax": power_factor_max,
"logy": log_power_factor,
},
}
title = None
for (x, y), prop in zip(np.ndindex(grid), properties):
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[y]
elif grid[1] == 1:
ax = axes[x]
else:
ax = axes[x, y]
title = self.plot_property(
ax,
prop,
x_property=x_property,
doping_type=doping_type,
temperature_idx=temperature_idx,
doping_idx=doping_idx,
xmin=xmin,
xmax=xmax,
xlabel=xlabel,
logx=logx,
labels=labels,
**prop_dict[prop],
)
if legend:
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[-1]
elif grid[1] == 1:
ax = axes[0]
else:
ax = axes[0, -1]
ax.legend(loc="upper left",
bbox_to_anchor=(1.01, 1),
ncol=1,
title=title)
return matplotlib.pyplot
def get_plot(
self,
x_property=None,
doping_idx=None,
temperature_idx=None,
doping_type=None,
grid=None,
height=None,
width=None,
ylabel=None,
ymin=None,
ymax=None,
logy=None,
xlabel=None,
xmin=None,
xmax=None,
logx=None,
legend=True,
title=True,
total_color=None,
axes=None,
style=None,
no_base_style=False,
fonts=None,
):
if doping_type is not None and doping_idx is not None:
warnings.warn(
"Both doping type and doping indexes have been set. This can cause "
"unexpected behaviour.")
if temperature_idx is None:
temperature_idx = np.arange(self.temperatures.shape[0])
elif isinstance(temperature_idx, int):
temperature_idx = [temperature_idx]
if doping_idx is None:
doping_idx = np.arange(self.doping.shape[0])
elif isinstance(doping_idx, int):
doping_idx = [doping_idx]
if doping_type == "n":
doping_idx = [i for i in doping_idx if self.doping[i] <= 0]
elif doping_type == "p":
doping_idx = [i for i in doping_idx if self.doping[i] >= 0]
if x_property is None and len(temperature_idx) == 1:
x_property = "doping"
elif x_property is None:
x_property = "temperature"
if x_property == "doping":
if grid is None or len(grid) == 0:
grid = (1, len(temperature_idx))
primary_idxs = temperature_idx
secondary_idxs = doping_idx
elif x_property == "temperature":
if grid is None or len(grid) == 0:
grid = (1, len(doping_idx))
primary_idxs = doping_idx
secondary_idxs = temperature_idx
else:
raise ValueError(f"Unrecognised x_property: {x_property}")
if axes is None:
width, height = get_figsize(*grid, width=width, height=height)
_, axes = pretty_subplot(*grid, width=width, height=height)
else:
if not isinstance(axes, (list, tuple, np.ndarray)):
# single axis given
grid = (1, 1)
else:
axes = np.array(axes)
if grid is None:
grid = axes.shape
if len(grid) == 1:
grid = (1, grid[0])
if len(primary_idxs) > np.product(grid):
raise ValueError(
"Axes array not commensurate with doping_idx and temperature_idx"
)
for (x, y), primary_idx in zip(np.ndindex(grid), primary_idxs):
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[y]
elif grid[1] == 1:
ax = axes[x]
else:
ax = axes[x, y]
self.plot_mobility(
ax,
x_property,
primary_idx,
secondary_idxs,
xlabel=xlabel,
xmin=xmin,
xmax=xmax,
logx=logx,
ylabel=ylabel,
ymin=ymin,
ymax=ymax,
logy=logy,
title=title,
total_color=total_color,
)
ax.set()
if legend and (self.separate_mobility or not self.average):
if grid[0] == 1 and grid[1] == 1:
ax = axes
elif grid[0] == 1:
ax = axes[-1]
elif grid[1] == 1:
ax = axes[0]
else:
ax = axes[0, -1]
ax.legend(loc="upper left", bbox_to_anchor=(1.01, 1), ncol=1)
return matplotlib.pyplot