def plot_flow_rate_v2_road_length():
"""Convenice function used to plot the data gathered for the road_length test"""
style.use('bmh')
data1_road = load_flow_data(road_length=500, n_iterations=10000, vmax=5)
data2_road = load_flow_data(road_length=200, n_iterations=10000, vmax=5)
data3_road = load_flow_data(road_length=100, n_iterations=10000, vmax=5)
data4_road = load_flow_data(road_length=50, n_iterations=10000, vmax=5)
fig, ax = plt.subplots()
ax.plot(data1_road[:, 0], data1_road[:, 1], lw=1, c='r', label='500')
ax.plot(data2_road[:, 0], data2_road[:, 1], lw=1, c='b', label='200')
ax.plot(data3_road[:, 0],
data3_road[:, 1],
lw=1,
c='limegreen',
label='100')
ax.plot(data4_road[:, 0], data4_road[:, 1], lw=1, c='black', label='50')
ax.set_xlim(0, 0.8)
ax.set_ylim(0, 1)
ax.set_ylabel(r'$Flow \ Rate \ \frac{passes}{iteration}$',
labelpad=10,
fontsize=30)
ax.set_xlabel(r'$Density \ \frac{cars}{sites}$', labelpad=10, fontsize=30)
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes, mark_inset
# zoom-factor: 2.5, location: upper-left
axins = zoomed_inset_axes(ax, 2.5, loc='upper right')
axins.plot(data1_road[:, 0], data1_road[:, 1], lw=1, c='r', label='500')
axins.plot(data2_road[:, 0], data2_road[:, 1], lw=1, c='b', label='200')
axins.plot(data3_road[:, 0],
data3_road[:, 1],
lw=1,
c='limegreen',
label='100')
axins.plot(data4_road[:, 0], data4_road[:, 1], lw=1, c='black', label='50')
x1, x2, y1, y2 = 0.1, 0.25, 0.6, 0.8 # specify the limits
axins.set_xlim(x1, x2) # apply the x-limits
axins.set_ylim(y1, y2)
axins.legend(loc='upper right', prop={'size': 20})
ax.minorticks_on()
axins.minorticks_on()
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
# #
plt.show()
def plot_2d_flow():
data1 = load_flow_data(road_length=500, n_iterations=10000, vmax=5)
data2 = pf.load_flow_data(road_length=500, n_iterations=10000, vmax=5)
font = {
'family': 'serif',
'color': 'black',
'weight': 'normal',
'size': 15
}
style.use('bmh')
fig, ax = plt.subplots()
ax.plot(data1[:, 0], data1[:, 1], lw=1, c='r', label='Double Lane')
ax.plot(data2[:, 0], data2[:, 1], lw=1, c='b', label='Single Lane')
ax.legend(loc='upper right', prop={'size': 15})
ax.minorticks_on()
ax.set_ylabel(r'$Flow \ Rate \ \frac{Passes}{Iteration}$',
labelpad=10,
fontdict=font)
ax.set_xlabel(r'$Density \ \frac{Cars}{Sites}$',
labelpad=10,
fontdict=font)
plt.show()
def plot_flow_rate_v2_proba():
"""Convenice function used to plot the data gathered for the probability test"""
style.use('bmh')
data1_road = load_flow_data(road_length=500,
n_iterations=9995,
vmax=5,
type='proba')
data2_road = load_flow_data(road_length=500, n_iterations=10000, vmax=5)
data3_road = load_flow_data(road_length=500,
n_iterations=9998,
vmax=5,
type='proba')
data4_road = load_flow_data(road_length=500,
n_iterations=9997,
vmax=5,
type='proba')
fig, ax = plt.subplots()
ax.plot(data1_road[:, 0], data1_road[:, 1], lw=1, c='r', label='0.05')
ax.plot(data2_road[:, 0], data2_road[:, 1], lw=1, c='b', label='0.1')
ax.plot(data3_road[:, 0],
data3_road[:, 1],
lw=1,
c='limegreen',
label='0.2')
ax.plot(data4_road[:, 0], data4_road[:, 1], lw=1, c='black', label='0.3')
ax.set_xlim(0, 0.8)
ax.set_ylim(0, 1)
ax.set_ylabel(r'$Flow \ Rate \ \frac{passes}{iteration}$',
labelpad=10,
fontsize=30)
ax.set_xlabel(r'$Density \ \frac{cars}{sites}$', labelpad=10, fontsize=30)
ax.legend(loc='upper right', prop={'size': 20})
ax.minorticks_on()
plt.show()
def plot_flow_rate_v2_profiles():
style.use('bmh')
data_perfect = load_flow_data(road_length=500, n_iterations=10000, vmax=15)
data1 = load_flow_data(road_length=500,
n_iterations=10000,
vmax=15,
type='profiles',
profile='0.2')
data2 = load_flow_data(road_length=500,
n_iterations=10000,
vmax=15,
type='profiles',
profile='0.3')
data3 = load_flow_data(road_length=500,
n_iterations=10000,
vmax=15,
type='profiles',
profile='0.5')
fig, ax = plt.subplots()
ax.plot(data_perfect[:, 0],
data_perfect[:, 1],
c='r',
label='Perfect',
lw=1)
ax.plot(data1[:, 0], data1[:, 1], c='black', label='Profile 1', lw=1)
ax.plot(data2[:, 0], data2[:, 1], c='limegreen', label='Profile 2', lw=1)
ax.plot(data3[:, 0], data3[:, 1], c='b', label='Profile 3', lw=1)
ax.legend(loc='upper right', prop={'size': 20})
ax.set_ylabel(r'$Flow \ Rate \ \frac{passes}{iteration}$',
labelpad=10,
fontsize=30)
ax.set_xlabel(r'$Density \ \frac{cars}{sites}$', labelpad=10, fontsize=30)
ax.minorticks_on()
plt.show()