import numpy as np import dataAcquisitionMulti as datAc import plotting as plo import matplotlib.pyplot as plt plt.close('all') folderStr = "../simResults/44/160224/" simValues = datAc.readStateFile(folderStr+"simStates.txt") xTime = np.arange(0,4.95,0.05) #simValues_nA = np.delete(simValues, np.s_[-1],1) # plo.plotter2d((simValues,),("perfect",)) # plt.close('all') ##Direct input plt.rcParams['text.latex.preamble']=[r"\usepackage{lmodern}"] #Options params = {'text.usetex' : True, 'font.size' : 11, 'font.family' : 'lmodern', 'text.latex.unicode': True # 'figure.autolayout': True } plt.rcParams.update(params) figHeight = 5 figWidth = 6.2 colorL = ['r','g','b','y'] styleL = ['solid','dashed','dotted','dash-dot'] cnt = 0
def printMeanVar(est, sim): namelist = ['unconstr Dip A: ', 'unconstr Cyl A:', 'constr Dip A: ', 'constr Cyl A:', ] cnt = 0 for i in est: dif = sim-i mean = np.mean(np.linalg.norm(dif, axis=1)) var = np.var(dif)**2 print "%s %s +- %s" % (namelist[cnt], mean, var) # print "var of "+namelist[cnt], var cnt += 1 folderStr = "../simResults/24/160225/" simValues = datAc.readStateFile(folderStr+"simStates.txt") simValues_nA = np.delete(simValues, np.s_[3],1) simValues_nA = np.delete(simValues_nA, np.s_[6],1) # simValues_nA = np.delete(simValues_nA, np.s_[9],1) # simValues_nA = np.delete(simValues_nA, np.s_[12],1) loc = folderStr print "witout ad-ab:" uDip_nAt = datAc.readStateFile(loc+"estAng_dip0") uCyl_nAt = datAc.readStateFile(loc+"estAng_cyl0") cDip_nAt = datAc.readStateFile(loc+"estAng_dip1") cCyl_nAt = datAc.readStateFile(loc+"estAng_cyl1") # add dip... uDip_nA = addDip(uDip_nAt) uCyl_nA = addDip(uCyl_nAt)
lineEst = mlines.Line2D([], [], color=colorL[1], markersize=15, label='Estimated States') plt.figlegend((lineMCP,linePIP,lineDIP,linePHI,linePerf,lineEst), (r'$\theta_{MCP}$',r'$\theta_{PIP}$',r'$\theta_{DIP}$',r'$\phi_{MCP}$', 'Perfect States', 'Estimated States'), loc='center right',bbox_to_anchor=(0.9,1.05), ncol=3) # plt.subplots_adjust(top=0.8) plt.savefig("../thesis/pictures/plots/difMult.png", dpi=300, bbox_inches='tight') return fig folderStr = "../simResults/44/160224/" simValues = datAc.readStateFile(folderStr+"simStates.txt") simValues_nA = np.delete(simValues, np.s_[3],1) simValues_nA = np.delete(simValues_nA, np.s_[6],1) simValues_nA = np.delete(simValues_nA, np.s_[9],1) simValues_nA = np.delete(simValues_nA, np.s_[12],1) cCyl_A44 = datAc.readStateFile(folderStr+"estAng_cyl_A0") #cCyl_A44 = addDip(cCyl_A44t) #cCyl_nA12 = datAc.readStateFile("../simResults/12/160224/"+"estAng_cyl1") plt.close('all') pl = plotDif_sub([simValues, cCyl_A44])
# plotDif_ind(b,estCA, tMag, 'estCA 14') """ for plotting least best result """ # sstring = "set5" # estCA = datAc.readStateFile("../datasets/evalSets/estResults/160226_real/"+sstring+"_cylA14.txt") # (tLeap,lInd,lMid,lRin,lPin) = datAc.readLeap("../datasets/evalSets/"+sstring+"_leap") # (tMag,s1,s2,s3,s4) = datAc.readMag("../datasets/evalSets/"+sstring+"_mag") # b = resampleLeap_point((tLeap,lInd), tMag)[0] # b = b[:-1] # tMag = tMag[:-1] # plotDif_ind(b,estCA, tMag, 'estCA') # plotDif(b,estCA, tMag, 'estCA') """ for plotting 44 estimation... """ sstring = "set6" estCA = datAc.readStateFile("../datasets/44/160210_" + sstring + "cylA44.txt") (tLeap, lInd, lMid, lRin, lPin) = datAc.readLeap("../datasets/160210/160210_" + sstring + "_leap") (tMag, s1, s2, s3, s4) = datAc.readMag("../datasets/160210/160210_" + sstring + "_mag") (indRe, midRe, rinRe, pinRe) = resampleLeap_point((tLeap, lInd, lMid, lRin, lPin), tMag) tMag = tMag[:-1] # plotDif_ind(indRe[:-1],estCA[:,:4], tMag, 'estCA Index') # plotDif_ind(rinRe[:-1],estCA[:,4:8], tMag, 'estCA Middle') # plotDif_ind(midRe[:-1],estCA[:,8:12], tMag, 'estCA Ring') # plotDif_ind(pinRe[:-1],estCA[:,12:], tMag, 'estCA Pinky') # plotMulti([indRe[:-1],midRe[:-1]],estCA,tMag) lIndN = np.linalg.norm(indRe, axis=1) lMidN = np.linalg.norm(midRe, axis=1) lRinN = np.linalg.norm(rinRe, axis=1) lPinN = np.linalg.norm(pinRe, axis=1)
# first bbox_image0 = BboxImage( Bbox([[lowerCorner[0], lowerCorner[1]], [upperCorner[0], upperCorner[1]]]), norm=None, origin=None, clip_on=False, ) bbox_image0.set_data(imread("../thesis/pictures/statePics/bestLeap/out-0.jpg")) difP.add_artist(bbox_image0) # second lowC1 = difP.transData.transform((lowPos[0] + 6.5, lowPos[1])) upC1 = difP.transData.transform((upPos[0] + 6.5, upPos[1])) bbox_image1 = BboxImage(Bbox([[lowC1[0], lowC1[1]], [upC1[0], upC1[1]]]), norm=None, origin=None, clip_on=False) bbox_image1.set_data(imread("../thesis/pictures/statePics/bestLeap/out-5.jpg")) difP.add_artist(bbox_image1) plt.savefig("../thesis/pictures/plots/bestEstTEST.png", dpi=300, bbox_inches="tight") plt.close("all") """ for plotting best result """ sstring = "set4" estCA = datAc.readStateFile("../datasets/evalSets/estResults/160217_real/" + sstring + "_cylA12.txt") (tLeap, lInd, lMid, lRin, lPin) = datAc.readLeap("../datasets/evalSets/" + sstring + "_leap") (tMag, s1, s2, s3, s4) = datAc.readMag("../datasets/evalSets/" + sstring + "_mag") b = resampleLeap_point((tLeap, lInd), tMag)[0] b = b[:-1] tMag = tMag[:-1] plotDif_ind(b, estCA, tMag, "estCA 14")