def plot_moment(self):
fig = figure((10, 4))
plot_signal(self.t,
self.torque_disturbance() * 1000,
plot_label="Disturbance",
color="darkred",
zorder=2)
plot_signal(self.t[:-2],
moving_average(self.torque_omega_dot(), 3) * 1000,
plot_label="Steering",
color="#fcdc9a",
zorder=1)
plot_signal(
self.t[:-2],
moving_average(
(self.torque_omega_dot() + self.torque_disturbance()), 3) *
1000,
plot_label="Total",
color="darkblue",
zorder=0,
# Axes
x_bounds=[0, 24],
y_bounds=[-6, 6],
# Labels
x_label="t [s]",
y_label="T [mNm]")
import matplotlib.pyplot as plt
plt.legend(prop={'family': 'monospace'})
plt.tight_layout()
plt.show()
def f_delta(self):
fig = figure((12, 4))
plot_signal(x=self.t,
y=deg(self.psi),
color="orange",
plot_label="Ψ [deg]")
plot_signal(x=self.t,
y=deg(self.delta),
color="green",
plot_label="δ [deg]")
plot_signal(
x=self.t,
y=deg(self.omega),
plot_label="ω [deg s-1]",
# Axes
x_label="t [s]",
y_label="[deg]",
# Ticks
tick_number=13,
# Bounds
x_bounds=[0, 24],
y_bounds=[-110, 110])
import matplotlib.pyplot as plt
plt.legend(prop={'family': 'monospace'})
plt.tight_layout()
plt.show()
def test_demo(self):
fig = figure((18, 8), backend=backend)
ax1 = plt.subplot2grid((2, 6), (0, 0),
colspan=2,
rowspan=2,
projection='3d',
facecolor="#fff6e6")
ax2 = plt.subplot2grid((2, 6), (0, 3), rowspan=1, aspect=1)
ax3 = plt.subplot2grid((2, 6), (1, 3), rowspan=1, aspect=1)
ax4 = plt.subplot2grid((2, 6), (0, 5), rowspan=1, aspect=1)
ax5 = plt.subplot2grid((2, 6), (1, 5), rowspan=1, aspect=1)
surface(fig=fig,
ax=ax1,
title="Demo",
title_size=70,
title_weight="bold",
title_font="Pump Triline",
title_color="#e69300",
plot_label="Surface",
background_color_plot="#fff6e6",
edge_color="lightgrey",
edges_to_rgba=True,
azim=-160,
elev=43)
fill_area(fig=fig, ax=ax2, plot_label="Fill", aspect=1, grid=False)
quiver(fig=fig, ax=ax3, plot_label="Quiver", grid=False)
heatmap(fig=fig,
ax=ax4,
title="No label",
plot_label="Heatmap",
grid=False)
streamline(fig=fig,
ax=ax5,
line_density=1,
title="No label",
plot_label="Streamline",
grid=False)
custom_canvas2(fig=fig,
ax=ax2,
background_color_figure="#fff6e6",
legend=True,
legend_loc=(0.6725, 0.425),
resize_axes=False)
if show:
plt.show()
def f_path(self):
fig = figure((12, 4))
scatter(x=self.x,
y=self.y,
plot_label="Reference points",
marker="x",
point_size=30,
color="#7aa9ff",
zorder=0,
resize_axes=False)
plot_signal(
x=self.rx,
y=self.path,
color="darkorange",
plot_label="Path",
# Axes
x_label="x [m]",
y_label="y [m]",
# Ticks
tick_number=10,
# Bounds
x_bounds=[0, 54],
y_bounds=[-2, 16])
import matplotlib.pyplot as plt
# Contour plots
x_0 = np.arange(0, 9, self.dx)
y_0 = np.zeros(len(x_0))
x_c60 = np.arange(9, self.X_60, self.dx)
y_c60 = np.linspace(0, self.Y_60, len(x_c60))
x_60 = np.arange(self.X_60, self.X_60 + 12, self.dx)
y_60 = self.Y_60 * np.ones(len(x_60))
x_90 = np.arange(self.X_60 + 12, self.x_90[-1], self.dx)
y_90 = np.zeros(len(x_90))
x_ref = np.concatenate((x_0, x_c60, x_60, x_90))
y_ref = np.concatenate((y_0, y_c60, y_60, y_90))
plt.plot(x_ref,
y_ref,
label="Reference",
linewidth=1,
linestyle="--",
zorder=0)
# Other
plt.gca().set_facecolor('#ffeed9')
fig.patch.set_facecolor('#ffeed9')
plt.legend(prop={'family': 'monospace'})
plt.tight_layout()
plt.show()
def plot_gear_ratio(self):
fig = figure((6, 4))
plot_signal(
self.t,
np.cos(self.delta_f),
# Labels
x_label="t [s]",
y_label="GR [-]",
# Ticks
tick_number=6,
# Axes
x_bounds=[0, 24],
y_bounds=[0, 2])
import matplotlib.pyplot as plt
plt.tight_layout()
plt.show()
def n_pane_single(cls,
x,
y,
labels=None,
legend_labels=None,
filename=None,
where_does_this_go=None,
**kwargs):
fig = figure((5 * len(y), 3.5))
for i in range(len(y)):
ax_transient = plt.subplot2grid((1, len(y)), (0, i),
rowspan=1,
colspan=1)
if i < (len(y) - 1):
line(x=x,
y=y[i],
color=one()[i],
ax=ax_transient,
fig=fig,
y_label=labels[i]
if not isinstance(labels, type(None)) else None,
plot_label=legend_labels[i]
if not isinstance(legend_labels, type(None)) else None)
else:
line(x=x,
y=y[i],
color=one()[i],
ax=ax_transient,
fig=fig,
y_label=labels[i]
if not isinstance(labels, type(None)) else None,
legend=True
if not isinstance(legend_labels, type(None)) else False,
plot_label=legend_labels[i]
if not isinstance(legend_labels, type(None)) else None,
legend_loc=(0.875, 0.425),
**kwargs)
plt.subplots_adjust(left=0.1, right=0.85, wspace=0.6, hspace=0.35)
if not isinstance(filename, type(None)) and not isinstance(
where_does_this_go, type(None)):
plt.savefig(f"{where_does_this_go}/{filename}.pdf")
plt.show()
def test_basic(self):
# backend = "Qt5Agg" # None -> regular non-interactive matplotlib output
fig = figure(figsize=(10, 10), backend=backend)
ax0 = plt.subplot2grid((2, 2), (0, 0), rowspan=1, aspect=1, fig=fig)
ax1 = plt.subplot2grid((2, 2), (1, 0), rowspan=1, aspect=1, fig=fig)
ax2 = plt.subplot2grid((2, 2), (0, 1), rowspan=1, aspect=1, fig=fig)
ax3 = plt.subplot2grid((2, 2), (1, 1), rowspan=1, aspect=12, fig=fig)
axes = [ax0, ax1, ax2, ax3]
plots = [line, quiver, streamline, fill_area]
for i in range(len(plots)):
plots[i](fig=fig, ax=axes[i], backend=backend)
if show:
plt.show()
def n_pane_comparison(cls,
t,
y,
axis_labels=None,
legend_labels=None,
filename=None,
where_does_this_go=None,
zorders=None,
colors=None,
alphas=None,
save=False,
show=True):
t, y = to_ndarrays(t, y)
t = cls.comparison_input_match(t, y)
zorders = if_none(zorders, np.arange(len(y) + 1, 0, -1))
colors = if_none(colors, [one()[n] for n in range(len(y))])
print(colors)
alphas = if_none(alphas, np.ones(len(y)))
fig = figure((5 * len(y), 3.5))
for i in range(len(y)):
ax_transient = plt.subplot2grid((1, len(y)), (0, i),
rowspan=1,
colspan=1)
if i < (len(y) - 1):
cls.comparison(
[t[i][n] for n in range(len(y[1]))],
[y[i][n] for n in range(len(y[1]))],
ax_transient,
fig,
y_label=axis_labels[i]
if not isinstance(axis_labels, type(None)) else None,
zorders=zorders,
colors=colors,
alphas=alphas,
)
else:
cls.comparison(
[t[i][n] for n in range(len(y[1]))],
[y[i][n] for n in range(len(y[1]))],
ax_transient,
fig,
y_label=axis_labels[i]
if not isinstance(axis_labels, type(None)) else None,
zorders=zorders,
colors=colors,
alphas=alphas,
plot_labels=legend_labels,
legend=True
if not isinstance(legend_labels, type(None)) else False,
legend_loc=(0.875, 0.425))
plt.subplots_adjust(left=0.1, right=0.85, wspace=0.6, hspace=0.35)
legend = (c for c in ax_transient.get_children()
if isinstance(c, mpl.legend.Legend))
if save:
filename = input("Filename:") if isinstance(filename, type(None)) \
else filename
where_does_this_go = input("Destination directory:") if isinstance(where_does_this_go, type(None)) \
else where_does_this_go
try:
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
except FileNotFoundError:
print_color(
"Destination directory does not exist. Destination directory:",
"blue")
where_does_this_go = input()
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
if show:
plt.show()
def n_pane_single(cls,
x,
y,
labels=None,
legend_labels=None,
filename=None,
where_does_this_go=None,
**kwargs):
# Regular defaults
backend = kwargs.pop('backend', None) # Setup
legend_loc = kwargs.pop('legend_loc', (0.875, 0.55)) # Legend
show = kwargs.pop('show', False) # Display
save = kwargs.pop('save', False)
legend = kwargs.pop('legend',
True if not isinstance(legend_labels, type(None))
else True) # Legend
# Figure setup
fig = figure((5 * len(y), 3.5), backend=backend)
import matplotlib.pyplot as plt
# Plot
for i in range(len(y)):
ax_transient = plt.subplot2grid((1, len(y)), (0, i),
rowspan=1,
colspan=1)
if i < (len(y) - 1):
line(x=x,
y=y[i],
color=one()[i],
ax=ax_transient,
fig=fig,
y_label=labels[i]
if not isinstance(labels, type(None)) else None,
plot_label=legend_labels[i]
if not isinstance(legend_labels, type(None)) else None,
backend=backend)
else:
line(x=x,
y=y[i],
color=one()[i],
ax=ax_transient,
fig=fig,
y_label=labels[i]
if not isinstance(labels, type(None)) else None,
legend=True
if not isinstance(legend_labels, type(None)) else False,
plot_label=legend_labels[i]
if not isinstance(legend_labels, type(None)) else None,
legend_loc=legend_loc,
backend=backend,
**kwargs)
plt.subplots_adjust(left=0.1, right=0.85, wspace=0.6, hspace=0.35)
if not isinstance(filename, type(None)) and not isinstance(
where_does_this_go, type(None)):
plt.savefig(f"{where_does_this_go}/{filename}.pdf")
plt.show()
if show:
plt.show()
if save:
filename = input("Filename:") if isinstance(filename, type(None)) \
else filename
where_does_this_go = input("Destination directory:") if isinstance(where_does_this_go, type(None)) \
else where_does_this_go
try:
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
except FileNotFoundError:
print_color(
"Destination directory does not exist. Destination directory:",
"blue")
where_does_this_go = input()
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
if show:
plt.show()
def n_pane_comparison(cls,
t,
y,
axis_labels=None,
legend_labels=None,
zorders=None,
colors=None,
alphas=None,
filename=None,
where_does_this_go=None,
**kwargs):
# Input check
t, y = lists_to_ndarrays(t, y)
t = cls.comparison_input_match(t, y)
# Special parameters
zorders = if_none(zorders, np.arange(len(y) + 1, 0, -1))
colors = if_none(colors, [one()[n] for n in range(len(y))])
alphas = if_none(alphas, np.ones(len(y)))
# Regular defaults
backend = kwargs.pop('backend', None) # Setup
legend_loc = kwargs.pop('legend_loc', (0.875, 0.55)) # Legend
show = kwargs.pop('show', False) # Display
save = kwargs.pop('save', False)
# Figure setup
fig = figure((5 * len(y), 3.5), backend=backend)
import matplotlib.pyplot as plt
# Plot
for i in range(len(y)):
ax_transient = plt.subplot2grid((1, len(y)), (0, i),
rowspan=1,
colspan=1)
if i < (len(y) - 1):
cls.comparison(
[t[i][n] for n in range(len(y[1]))],
[y[i][n] for n in range(len(y[1]))],
ax=ax_transient,
fig=fig,
backend=backend,
y_label=axis_labels[i]
if not isinstance(axis_labels, type(None)) else None,
zorders=zorders,
colors=colors,
alphas=alphas,
legend=False)
else:
cls.comparison(
[t[i][n] for n in range(len(y[1]))],
[y[i][n] for n in range(len(y[1]))],
ax=ax_transient,
fig=fig,
backend=backend,
y_label=axis_labels[i]
if not isinstance(axis_labels, type(None)) else None,
zorders=zorders,
colors=colors,
alphas=alphas,
plot_labels=legend_labels,
legend=True
if not isinstance(legend_labels, type(None)) else False,
legend_loc=legend_loc,
**kwargs)
plt.subplots_adjust(left=0.1, right=0.85, wspace=0.6, hspace=0.35)
legend = (c for c in ax_transient.get_children()
if isinstance(c, mpl.legend.Legend))
if save:
filename = input("Filename:") if isinstance(filename, type(None)) \
else filename
where_does_this_go = input("Destination directory:") if isinstance(where_does_this_go, type(None)) \
else where_does_this_go
try:
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
except FileNotFoundError:
print_color(
"Destination directory does not exist. Destination directory:",
"blue")
where_does_this_go = input()
plt.savefig(
f"{where_does_this_go}/{filename}.pdf",
bbox_extra_artists=legend,
)
if show:
plt.show()
class Plot:
mc = MC()
fig = figure((15, 10))
n_ticks = 3
tick_label_size = 10
axis_font_size = 15
axis_title_pad = 10
def reaction(self):
self.y_bounds = [-100, 100]
self.torque_bound = 13
self.torque_bound_factor = self.torque_bound / max(
self.mc.forward_motoring()[0])
self.main()
def reaction_s(self):
self.saturation = True
self.n_ticks = 17
self.y_bounds = [-20, 20]
self.torque_bound = self.mc.forward_motoring()[0].max() / (
self.mc.forward_braking()[1].max() / 20)
self.torque_bound_factor = self.torque_bound / max(
self.mc.forward_motoring()[0])
self.main()
def main(self):
import matplotlib.pyplot as plt
self.basic(x=self.mc.forward_motoring()[0],
y=self.mc.forward_motoring()[1],
color="darkred")
self.basic(x=self.mc.forward_braking()[0],
y=self.mc.forward_braking()[1],
color="darkred")
self.basic(x=self.mc.reverse_braking()[0],
y=self.mc.reverse_braking()[1],
color="darkred")
self.zero_lines()
self.heat_lines()
self.fill_continous_operation()
self.fill_intermittent_operation()
LC().plot()
self.style(x=self.mc.reverse_motoring()[0],
y=self.mc.reverse_motoring()[1],
color="darkred")
plt.xticks(np.linspace(-max(self.mc.forward_motoring()[0]),
max(self.mc.forward_motoring()[0]),
self.n_ticks),
fontname="serif",
fontsize=self.tick_label_size)
self.second_axis()
plt.show()
def basic(self, x, y, color):
line(
x=x,
y=y,
color=color,
line_width=2,
spines_removed=[],
fig=self.fig,
)
def style(self, x, y, color):
line(x=x,
y=y,
color=color,
line_width=2,
x_bounds=[-self.torque_bound, self.torque_bound],
x_upper_resize_pad=0,
x_lower_resize_pad=0,
y_bounds=self.y_bounds,
y_upper_resize_pad=0,
y_lower_resize_pad=0,
y_custom_tick_locations=[
self.mc.forward_braking()[1].max(),
self.mc.reverse_braking()[1].min()
],
spines_removed=["top", "right"],
x_tick_number=self.n_ticks,
y_tick_number=self.n_ticks,
tick_ndecimals=2,
x_tick_label_size=self.tick_label_size,
y_tick_label_size=self.tick_label_size,
grid=True,
grid_color="lightgrey",
grid_lines="--",
title="",
x_label="T [Nm]",
x_label_size=self.axis_font_size,
y_label="ω [rad s-1]",
y_label_size=self.axis_font_size,
y_label_rotation=90,
x_label_pad=self.axis_title_pad,
y_label_pad=5,
fig=self.fig,
resize_axes=True)
def second_axis(self):
"""
Second axis
"""
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter
ax2 = plt.gca().twiny()
ax2.set_xlim(left=-0.920 * self.torque_bound_factor,
right=0.920 * self.torque_bound_factor)
ax2.xaxis.set_major_formatter(FormatStrFormatter('%.2f'))
plt.xticks(self.mc.i(self.n_ticks),
fontname="serif",
fontsize=self.tick_label_size)
ax2.set_title("I [A]",
fontname="serif",
fontsize=self.axis_font_size,
pad=self.axis_title_pad)
def zero_lines(self):
"""
Zero lines
"""
import matplotlib.pyplot as plt
plt.axvline(0, color="grey", linestyle="--")
plt.axhline(0, color="grey", linestyle="--")
def heat_lines(self):
"""
Heat lines
"""
import matplotlib.pyplot as plt
plt.axvline(self.mc.t_max_thermal(), color="red", linestyle="-")
plt.axvline(-self.mc.t_max_thermal(), color="red", linestyle="-")
def fill_continous_operation(self):
# Thermal limit intersection
limit = self.mc.t_max_thermal()
idx_low = find_nearest_idx(self.mc.forward_braking()[0], -limit)
idx_high = find_nearest_idx(self.mc.forward_motoring()[0], limit)
x = np.concatenate((self.mc.forward_braking()[0][idx_low::],
self.mc.forward_motoring()[0][::idx_high]))
y = np.concatenate((self.mc.forward_braking()[1][idx_low::],
self.mc.forward_motoring()[1][::idx_high]))
z = np.concatenate((self.mc.reverse_motoring()[1][idx_low::],
self.mc.reverse_braking()[1][::idx_high]))
fill_area(x=x,
y=y,
z=z,
between=True,
color="#c7ffd6",
resize_axes=False,
zorder=0)
def fill_intermittent_operation(self):
# Thermal limit intersection
limit = self.mc.t_max_thermal()
idx_low = find_nearest_idx(self.mc.forward_braking()[0], -limit)
idx_high = find_nearest_idx(self.mc.forward_motoring()[0], limit)
x_low = self.mc.forward_braking()[0][:idx_low]
y_low = self.mc.forward_braking()[1][:idx_low]
z_low = self.mc.reverse_motoring()[1][:idx_low]
fill_area(x=x_low,
y=y_low,
z=z_low,
between=True,
color="darkred",
resize_axes=False,
zorder=0)
x_high = self.mc.forward_motoring()[0][idx_high:]
y_high = self.mc.forward_motoring()[1][idx_high:]
z_high = self.mc.reverse_braking()[1][idx_high:]
fill_area(x=x_high,
y=y_high,
z=z_high,
between=True,
color="darkred",
resize_axes=False,
zorder=0)