def plotTimeDistanceTarget(foldername):
rs = ReadSetupFile()
dicoTime = {}
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
trajTimes = getTrajTimeData(name)
for k, v in trajTimes.items():
for j in range(len(v)):
distance = round(rs.getDistanceToTarget(v[j][0],v[j][1]),2)
if not distance in dicoTime.keys():
dicoTime[distance] = {}
if not rs.sizeOfTarget[i] in dicoTime[distance].keys():
dicoTime[distance][rs.sizeOfTarget[i]] = []
dicoTime[distance][rs.sizeOfTarget[i]].append(v[j][2])
plotTab = []
fig = plt.figure(1, figsize=(16,9))
plt.ylabel("time (s)")
plt.xlabel("Target size (mm)")
for key in sorted(dicoTime.keys()):
plotTab.append(plt.plot([i for i in sorted(dicoTime[key].keys())], [np.mean(dicoTime[key][i]) for i in sorted(dicoTime[key].keys())], label = str("Distance: " + str(key))))
plt.legend(loc = 0)
plt.savefig("ImageBank/timedist"+foldername+'.png', bbox_inches='tight')
plt.show(block = True)
def plotTimeDistanceTarget(foldername):
rs = ReadSetupFile()
dicoTime = {}
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(
rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
trajTimes = getTrajTimeData(name)
for k, v in trajTimes.items():
for j in range(len(v)):
distance = round(rs.getDistanceToTarget(v[j][0], v[j][1]), 2)
if not distance in dicoTime.keys():
dicoTime[distance] = {}
if not rs.sizeOfTarget[i] in dicoTime[distance].keys():
dicoTime[distance][rs.sizeOfTarget[i]] = []
dicoTime[distance][rs.sizeOfTarget[i]].append(v[j][2])
plotTab = []
fig = plt.figure(1, figsize=(16, 9))
plt.ylabel("time (s)")
plt.xlabel("Target size (mm)")
for key in sorted(dicoTime.keys()):
plotTab.append(
plt.plot([i for i in sorted(dicoTime[key].keys())], [
np.mean(dicoTime[key][i]) for i in sorted(dicoTime[key].keys())
],
label=str("Distance: " + str(key))))
plt.legend(loc=0)
plt.savefig("ImageBank/timedist" + foldername + '.png',
bbox_inches='tight')
plt.show(block=True)
def plotFittsLaw(foldername, rbfn=False):
rs = ReadSetupFile()
timeDistWidth = []
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(
rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
trajTimes = getTrajTimeData(name)
for k, v in trajTimes.items():
for j in range(len(v)):
distance = rs.getDistanceToTarget(v[j][0], v[j][1])
trajtime = v[j][2]
size = rs.sizeOfTarget[i]
timeDistWidth.append((distance, size, trajtime))
MT, DI = [], []
for el in timeDistWidth:
MT.append(el[2])
DI.append(np.log2(el[0] / el[1]))
slope, intercept, r_value, p_value, std_err = stats.linregress(DI, MT)
yLR = slope * np.asarray(DI) + intercept
plt.figure()
for el in timeDistWidth:
if el[0] <= 0.15:
plt.scatter(np.log2(el[0] / el[1]), el[2], c='blue')
elif el[0] <= 0.28:
plt.scatter(np.log2(el[0] / el[1]), el[2], c='green')
else:
plt.scatter(np.log2(el[0] / el[1]), el[2], c='red')
plt.plot(DI, yLR)
plt.title("a = " + str(slope) + " b = " + str(intercept) + " r^2 = " +
str(r_value**2))
plt.xlabel("log(D/W)/log(2)")
plt.ylabel("Movement time (s)")
plt.savefig("ImageBank/fitts" + foldername + ".png", bbox_inches='tight')
plt.show(block=True)
def plotFittsLaw(foldername, rs, rbfn = False):
plt.figure(1, figsize=(16,9))
timeDistWidth = []
for i in range(len(rs.target_size)):
name = rs.OPTIpath + str(rs.target_size[i]) + "/" + foldername + "/TrajTime/"
trajTimes = getTrajTimeData(name)
for _, v in trajTimes.items():
for j in range(len(v)):
distance = rs.getDistanceToTarget(v[j][0],v[j][1])
trajtime = v[j][2]
size = rs.target_size[i]
timeDistWidth.append((distance, size, trajtime))
MT, DI = [], []
for el in timeDistWidth:
MT.append(el[2])
DI.append(np.log2(el[0]/el[1]))
slope, intercept, r_value, _, _ = stats.linregress(DI,MT)
yLR = slope * np.asarray(DI) + intercept
for el in timeDistWidth:
if el[0]<=0.15:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='blue')
elif el[0]<=0.28:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='green')
else:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='red')
plt.plot(DI, yLR)
plt.title("a = " + str(slope) + " b = " + str(intercept) + " r^2 = " + str(r_value**2))
plt.xlabel("log(D/W)/log(2)")
plt.ylabel("Movement time (s)")
imageFolder = rs.OPTIpath + "/ImageBank/"
checkIfFolderExists(imageFolder)
plt.savefig(imageFolder+"Fitts.svg", bbox_inches='tight')
plt.show(block = True)
def plotFittsLaw(foldername, rbfn = False):
rs = ReadSetupFile()
timeDistWidth = []
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
trajTimes = getTrajTimeData(name)
for k, v in trajTimes.items():
for j in range(len(v)):
distance = rs.getDistanceToTarget(v[j][0],v[j][1])
trajtime = v[j][2]
size = rs.sizeOfTarget[i]
timeDistWidth.append((distance, size, trajtime))
MT, DI = [], []
for el in timeDistWidth:
MT.append(el[2])
DI.append(np.log2(el[0]/el[1]))
slope, intercept, r_value, p_value, std_err = stats.linregress(DI,MT)
yLR = slope * np.asarray(DI) + intercept
plt.figure()
for el in timeDistWidth:
if el[0]<=0.15:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='blue')
elif el[0]<=0.28:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='green')
else:
plt.scatter(np.log2(el[0]/el[1]), el[2], c ='red')
plt.plot(DI, yLR)
plt.title("a = " + str(slope) + " b = " + str(intercept) + " r^2 = " + str(r_value**2))
plt.xlabel("log(D/W)/log(2)")
plt.ylabel("Movement time (s)")
plt.savefig("ImageBank/fitts"+foldername+".png", bbox_inches='tight')
plt.show(block = True)
def plotTimeColorMap(what, foldername = "None", targetSize = "All"):
'''
Cette fonction permet d'afficher le profil de temps des trajectoires
Entrees: -what: choix des donnees a afficher
'''
rs = ReadSetupFile()
fig = plt.figure(1, figsize=(16,9))
if what == "CMAES" and targetSize == "All":
for i in range(len(rs.sizeOfTarget)):
ax = plt.subplot2grid((2,2), (i/2,i%2))
name = rs.CMAESpath + str(rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
times = getTrajTimeData(name)
x0 = []
y0 = []
time = []
for k, v in times.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
time.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, time, xi, yi)
t1 = ax.scatter(x0, y0, c=time, marker=u'o', s=50, cmap=cm.get_cmap('RdYlBu'))
ax.scatter(rs.XTarget, rs.YTarget, c ='g', marker='v', s=200)
CS = ax.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_title(str("Time map for target " + str(rs.sizeOfTarget[i])))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = ax.scatter(x0, y0, c='b', marker=u'o', s=20)
else:
if what == "CMAES":
name = rs.CMAESpath + targetSize + "/" + foldername + "/TrajTime/"
elif what == "Brent":
name = BrentTrajectoriesFolder
else:
name = rs.NNpath + foldername + "/TrajTime/"
times = getTrajTimeData(name)
x0 = []
y0 = []
time = []
for k, v in times.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
time.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, time, xi, yi)
t1 = plt.scatter(x0, y0, c=time, marker=u'o', s=50, cmap=cm.get_cmap('RdYlBu'))
plt.scatter(rs.XTarget, rs.YTarget, c ='g', marker='v', s=200)
CS = plt.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
fig.colorbar(t1, shrink=0.5, aspect=5)
plt.scatter(x0, y0, c='b', marker=u'o', s=20)
plt.xlabel("X (m)")
plt.ylabel("Y (m)")
plt.savefig("ImageBank/"+what+'_timemap'+foldername+'.png', bbox_inches='tight')
plt.show(block = True)
def plotTimeColorMap(what, foldername="None", targetSize="All"):
'''
Cette fonction permet d'afficher le profil de temps des trajectoires
Entrees: -what: choix des donnees a afficher
'''
rs = ReadSetupFile()
fig = plt.figure(1, figsize=(16, 9))
if what == "CMAES" and targetSize == "All":
for i in range(len(rs.sizeOfTarget)):
ax = plt.subplot2grid((2, 2), (i / 2, i % 2))
name = rs.CMAESpath + str(
rs.sizeOfTarget[i]) + "/" + foldername + "/TrajTime/"
times = getTrajTimeData(name)
x0 = []
y0 = []
time = []
for k, v in times.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
time.append(v[j][2])
xi = np.linspace(-0.4, 0.4, 100)
yi = np.linspace(0.12, 0.58, 100)
zi = griddata(x0, y0, time, xi, yi)
t1 = ax.scatter(x0,
y0,
c=time,
marker=u'o',
s=50,
cmap=cm.get_cmap('RdYlBu'))
ax.scatter(rs.XTarget, rs.YTarget, c='g', marker='v', s=200)
CS = ax.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_title(str("Time map for target " + str(rs.sizeOfTarget[i])))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = ax.scatter(x0, y0, c='b', marker=u'o', s=20)
else:
if what == "CMAES":
name = rs.CMAESpath + targetSize + "/" + foldername + "/TrajTime/"
elif what == "Brent":
name = BrentTrajectoriesFolder
else:
name = rs.RBFNpath + foldername + "/TrajTime/"
times = getTrajTimeData(name)
x0 = []
y0 = []
time = []
for k, v in times.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
time.append(v[j][2])
xi = np.linspace(-0.4, 0.4, 100)
yi = np.linspace(0.12, 0.58, 100)
zi = griddata(x0, y0, time, xi, yi)
t1 = plt.scatter(x0,
y0,
c=time,
marker=u'o',
s=50,
cmap=cm.get_cmap('RdYlBu'))
plt.scatter(rs.XTarget, rs.YTarget, c='g', marker='v', s=200)
CS = plt.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
fig.colorbar(t1, shrink=0.5, aspect=5)
plt.scatter(x0, y0, c='b', marker=u'o', s=20)
plt.xlabel("X (m)")
plt.ylabel("Y (m)")
plt.savefig("ImageBank/" + what + '_timemap' + foldername + '.png',
bbox_inches='tight')
plt.show(block=True)