def __init__(self, models, expSpeed, eig, speed):
# the plot should have eigenvalues for each rider in a different color
# and plot dots for the eigenvalues from the model
self.fig = bp.plot_eigenvalues([mod.bicycle for mod in models.values()], speed)
# plot eigenvalues of the experimental models
self.ax = self.fig.axes[0]
self.ax.set_ylim((-10., 10.))
#self.real = self.ax.plot(expSpeed, np.real(eig), '.k')
self.real = []
for eigs in eig.T:
eigWithImag = abs(np.imag(eigs)) > 1e-10
self.real.append(self.ax.scatter(expSpeed, np.real(eigs),
c=eigWithImag))
self.imag = self.ax.plot(expSpeed, abs(np.imag(eig)), 'ob')
self.canvas = mpgtk.FigureCanvasGTK(self.fig)
self.canvas.show()
# Geometry Plot
benchmark.plot_bicycle_geometry(show=False, inertiaEllipse=False, color='grey',
ax=axes[0])
optimal.plot_bicycle_geometry(show=False, inertiaEllipse=False, color='black',
ax=axes[0])
axes[0].set_title('Bicycle Geometry')
axes[0].set_xlabel('Distance [m]')
axes[0].set_ylabel('Distance [m]')
# Eigenvalues Versus Speed Plot
speeds = np.linspace(0.0, 10.0, num=100)
bp.plot_eigenvalues([benchmark, optimal], speeds, ax=axes[1],
colors=['grey', 'black'])
axes[1].set_ylim((-10, 15))
l = axes[1].legend(['Benchmark', 'Optimal @ 5 m/s'])
#l = axes[1].legend(['Benchmark', 'Falkor @ 5 m/s'])
l.remove()
axes[1].set_ylabel('Real & Imaginary\nParts of the\nEigenvalues [1/s]')
# Handling Quality Metric Plot
benchmark_hqm_data = np.loadtxt('data/hqmbenchmark.csv'.format(speed),
delimiter=',')
optimal_hqm_data = np.loadtxt('data/hqm{}.csv'.format(speed), delimiter=',')
#optimal_hqm_data = np.loadtxt('data/hqm-falkor.csv', delimiter=',')
axes[2].plot(*benchmark_hqm_data.T, color='grey')
import bicycleparameters as bp
import numpy as np
bikeNames = ['Browserins', 'Browser', 'Pista',
'Fisher', 'Yellow', 'Yellowrev']
colors = ['k'] * 3 + ['gray'] * 3
linestyles = ['-', '-.', '--'] * 2
bikes = []
for name in bikeNames:
bikes.append(bp.Bicycle(name, pathToData='../data'))
speeds = np.linspace(0., 10., num=100)
bp.plot_eigenvalues(bikes, speeds, colors=colors,
linestyles=linestyles), largest=True)
bp.plt.vlines([2.5, 5., 7.], -0.5, 4.)
#bp.plt.savefig('../plots/largest.png')
bp.plt.show()
#!/usr/bin/env python
import numpy as np
import bicycleparameters as bp
from dtk import bicycle
pathToData = '/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data'
speeds = np.linspace(0., 10., num=100)
# compare a bike with rider and bike without rider
stratos = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratosRider = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratosRider.add_rider('Jason')
compareRider = bp.plot_eigenvalues([stratos, stratosRider], speeds)
ax = compareRider.axes[0]
ax.set_ylim(-10, 10)
ax.legend_.get_texts()[1].set_text('Stratos + Jason')
compareRider.savefig('../../figures/parameterstudy/compare-rider-eig.png',
dpi=200)
# compare the benchmark parameters to some of the bicycles I measured
benchmark = bp.Bicycle('Benchmark', pathToData=pathToData)
browser = bp.Bicycle('Browser', pathToData=pathToData, forceRawCalc=True)
browser.add_rider('Jason')
stratos = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratos.add_rider('Jason')
benchmarkReal = bp.plot_eigenvalues([benchmark, browser, stratos], speeds)
#!/usr/bin/env python
import numpy as np
import bicycleparameters as bp
from dtk import bicycle
pathToData = '/media/Data/Documents/School/UC Davis/Bicycle Mechanics/BicycleParameters/data'
speeds = np.linspace(0., 10., num=100)
# compare a bike with rider and bike without rider
stratos = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratosRider = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratosRider.add_rider('Jason')
compareRider = bp.plot_eigenvalues([stratos, stratosRider], speeds)
ax = compareRider.axes[0]
ax.set_ylim(-10, 10)
ax.legend_.get_texts()[1].set_text('Stratos + Jason')
compareRider.savefig('../../figures/parameterstudy/compare-rider-eig.png',
dpi=200)
# compare the benchmark parameters to some of the bicycles I measured
benchmark = bp.Bicycle('Benchmark', pathToData=pathToData)
browser = bp.Bicycle('Browser', pathToData=pathToData, forceRawCalc=True)
browser.add_rider('Jason')
stratos = bp.Bicycle('Stratos', pathToData=pathToData, forceRawCalc=True)
stratos.add_rider('Jason')
benchmarkReal = bp.plot_eigenvalues([benchmark, browser, stratos], speeds)
