126 lines
4.0 KiB
Python
Executable File
126 lines
4.0 KiB
Python
Executable File
# import matplotlib
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# matplotlib.use('Agg')
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import numpy as np
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import matplotlib.pyplot as plt
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#### Draw IMU data
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fig, axs = plt.subplots(2)
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imu=np.loadtxt('imu_pbp.txt')
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time=imu[:,0]
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axs[0].set_title('Gyroscope')
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axs[1].set_title('Accelerameter')
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lab_1 = ['gyr-x', 'gyr-y', 'gyr-z']
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lab_2 = ['acc-x', 'acc-y', 'acc-z']
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for i in range(3):
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#if i==1:
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axs[0].plot(time, imu[:,i+1],'.-', label=lab_1[i])
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axs[1].plot(time, imu[:,i+4],'.-', label=lab_2[i])
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for i in range(2):
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#axs[i].set_xlim(386,389)
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axs[i].grid()
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axs[i].legend()
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plt.grid()
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#fig, axs = plt.subplots(5)
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#axs[0].set_title('miss')
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#axs[1].set_title('miss')
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#axs[2].set_title('miss')
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#axs[3].set_title('miss')
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#axs[4].set_title('miss')
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#len_time1 = np.arange(0,1977)
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#len_time2 = np.arange(1977, 3954)
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#len_time3 = np.arange(3954,5931)
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#len_time4 = np.arange(5931,7908)
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#len_time5 = np.arange(7908,9885)
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#if i==1:
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#axs[0].plot(len_time1, time[0:1977],'.-', label='check')
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#axs[1].plot(len_time2, time[1977:3954],'.-', label='check')
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#axs[2].plot(len_time3, time[3954:5931],'.-', label='check')
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#axs[3].plot(len_time4, time[5931:7908],'.-', label='check')
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#axs[4].plot(len_time5, time[7908:9885],'.-', label='check')
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#axs[i].set_xlim(386,389)
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#axs[0].grid()
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#axs[0].legend()
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#axs[1].grid()
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#axs[1].legend()
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#axs[2].grid()
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#axs[2].legend()
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#axs[3].grid()
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#axs[3].legend()
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#axs[4].grid()
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#axs[4].legend()
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#plt.grid()
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#fig, axs = plt.subplots(5)
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#axs[0].set_title('miss')
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#axs[1].set_title('miss')
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#axs[2].set_title('miss')
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#axs[3].set_title('miss')
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#axs[4].set_title('miss')
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#len_time1 = np.arange(9885,9885+1977)
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#len_time2 = np.arange(9885+1977,9885+3954)
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#len_time3 = np.arange(9885+3954,9885+5931)
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#len_time4 = np.arange(9885+5931,9885+7908)
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#len_time5 = np.arange(9885+7908,9885+9885)
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#if i==1:
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#axs[0].plot(len_time1, time[9885+0:9885+1977],'.-', label='check')
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#axs[1].plot(len_time2, time[9885+1977:9885+3954],'.-', label='check')
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#axs[2].plot(len_time3, time[9885+3954:9885+5931],'.-', label='check')
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#axs[3].plot(len_time4, time[9885+5931:9885+7908],'.-', label='check')
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#axs[4].plot(len_time5, time[9885+7908:9885+9885],'.-', label='check')
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#axs[i].set_xlim(386,389)
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#axs[0].grid()
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#axs[0].legend()
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#axs[1].grid()
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#axs[1].legend()
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#axs[2].grid()
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#axs[2].legend()
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#axs[3].grid()
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#axs[3].legend()
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#axs[4].grid()
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#axs[4].legend()
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#plt.grid()
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# #### Draw time calculation
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# plt.figure(3)
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# fig = plt.figure()
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# font1 = {'family' : 'Times New Roman',
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# 'weight' : 'normal',
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# 'size' : 12,
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# }
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# c="red"
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# a_out1=np.loadtxt('Log/mat_out_time_indoor1.txt')
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# a_out2=np.loadtxt('Log/mat_out_time_indoor2.txt')
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# a_out3=np.loadtxt('Log/mat_out_time_outdoor.txt')
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# # n = a_out[:,1].size
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# # time_mean = a_out[:,1].mean()
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# # time_se = a_out[:,1].std() / np.sqrt(n)
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# # time_err = a_out[:,1] - time_mean
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# # feat_mean = a_out[:,2].mean()
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# # feat_err = a_out[:,2] - feat_mean
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# # feat_se = a_out[:,2].std() / np.sqrt(n)
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# ax1 = fig.add_subplot(111)
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# ax1.set_ylabel('Effective Feature Numbers',font1)
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# ax1.boxplot(a_out1[:,2], showfliers=False, positions=[0.9])
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# ax1.boxplot(a_out2[:,2], showfliers=False, positions=[1.9])
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# ax1.boxplot(a_out3[:,2], showfliers=False, positions=[2.9])
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# ax1.set_ylim([0, 3000])
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# ax2 = ax1.twinx()
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# ax2.spines['right'].set_color('red')
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# ax2.set_ylabel('Compute Time (ms)',font1)
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# ax2.yaxis.label.set_color('red')
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# ax2.tick_params(axis='y', colors='red')
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# ax2.boxplot(a_out1[:,1]*1000, showfliers=False, positions=[1.1],boxprops=dict(color=c),capprops=dict(color=c),whiskerprops=dict(color=c))
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# ax2.boxplot(a_out2[:,1]*1000, showfliers=False, positions=[2.1],boxprops=dict(color=c),capprops=dict(color=c),whiskerprops=dict(color=c))
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# ax2.boxplot(a_out3[:,1]*1000, showfliers=False, positions=[3.1],boxprops=dict(color=c),capprops=dict(color=c),whiskerprops=dict(color=c))
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# ax2.set_xlim([0.5, 3.5])
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# ax2.set_ylim([0, 100])
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# plt.xticks([1,2,3], ('Outdoor Scene', 'Indoor Scene 1', 'Indoor Scene 2'))
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# # # print(time_se)
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# # # print(a_out3[:,2])
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# plt.grid()
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# plt.savefig("time.pdf", dpi=1200)
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plt.show()
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