def plotPerfSizeDist(foldername):
rs = ReadSetupFile()
dicoCost = {}
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(rs.sizeOfTarget[i]) + "/" + foldername + "/Cost/"
costs = getCostData(name)
for k, v in costs.items():
for j in range(len(v)):
distance = round(rs.getDistanceToTarget(v[j][0],v[j][1]),2)
if not distance in dicoCost.keys():
dicoCost[distance] = {}
if not rs.sizeOfTarget[i] in dicoCost[distance].keys():
dicoCost[distance][rs.sizeOfTarget[i]] = []
dicoCost[distance][rs.sizeOfTarget[i]].append(v[j][2])
plotTab = []
fig = plt.figure(1, figsize=(16,9))
plt.ylabel("performance")
plt.xlabel("Target size (mm)")
for key in sorted(dicoCost.keys()):
plotTab.append(plt.plot([i for i in sorted(dicoCost[key].keys())], [np.mean(dicoCost[key][i]) for i in sorted(dicoCost[key].keys())], label = str("Distance: " + str(key))))
plt.legend(loc = 0)
plt.savefig("ImageBank/perfdist"+foldername+".png", bbox_inches='tight')
plt.show(block = True)
def plotPerfSizeDist(foldername):
rs = ReadSetupFile()
dicoCost = {}
for i in range(len(rs.sizeOfTarget)):
name = rs.CMAESpath + str(
rs.sizeOfTarget[i]) + "/" + foldername + "/Cost/"
costs = getCostData(name)
for k, v in costs.items():
for j in range(len(v)):
distance = round(rs.getDistanceToTarget(v[j][0], v[j][1]), 2)
if not distance in dicoCost.keys():
dicoCost[distance] = {}
if not rs.sizeOfTarget[i] in dicoCost[distance].keys():
dicoCost[distance][rs.sizeOfTarget[i]] = []
dicoCost[distance][rs.sizeOfTarget[i]].append(v[j][2])
plotTab = []
fig = plt.figure(1, figsize=(16, 9))
plt.ylabel("performance")
plt.xlabel("Target size (mm)")
for key in sorted(dicoCost.keys()):
plotTab.append(
plt.plot([i for i in sorted(dicoCost[key].keys())], [
np.mean(dicoCost[key][i]) for i in sorted(dicoCost[key].keys())
],
label=str("Distance: " + str(key))))
plt.legend(loc=0)
plt.savefig("ImageBank/perfdist" + foldername + ".png",
bbox_inches='tight')
plt.show(block=True)
def plotCostColorMap(what, foldername = "None", targetSize = "All"):
'''
Cette fonction permet d'afficher le profil de cout 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 + "/Cost/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for k, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = ax.scatter(x0, y0, c=cost, marker=u'o', s=5, 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'))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = ax.scatter(x0, y0, c='b', marker=u'o', s=20)
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_title(str("Cost map for target " + str(rs.sizeOfTarget[i])))
else:
if what == "CMAES":
name = rs.CMAESpath + targetSize + "/" + foldername + "/Cost/"
elif what == "Brent":
name = BrentTrajectoriesFolder
else:
name = rs.NNpath + foldername + "/Cost/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for k, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = plt.scatter(x0, y0, c=cost, marker=u'o', s=5, 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)
t1 = plt.scatter(x0, y0, c='b', marker=u'o', s=20)
plt.xlabel("X (m)")
plt.ylabel("Y (m)")
plt.title("Cost map for " + what)
plt.savefig("ImageBank/"+what+'_costmap'+foldername+'.png', bbox_inches='tight')
plt.show(block = True)
def plotCostColorMap(what, foldername="None", targetSize="All"):
'''
Cette fonction permet d'afficher le profil de cout 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 + "/Cost/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for k, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4, 0.4, 100)
yi = np.linspace(0.12, 0.58, 100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = ax.scatter(x0,
y0,
c=cost,
marker=u'o',
s=5,
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'))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = ax.scatter(x0, y0, c='b', marker=u'o', s=20)
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_title(str("Cost map for target " + str(rs.sizeOfTarget[i])))
else:
if what == "CMAES":
name = rs.CMAESpath + targetSize + "/" + foldername + "/Cost/"
elif what == "Brent":
name = BrentTrajectoriesFolder
else:
name = rs.RBFNpath + foldername + "/Cost/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for k, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4, 0.4, 100)
yi = np.linspace(0.12, 0.58, 100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = plt.scatter(x0,
y0,
c=cost,
marker=u'o',
s=5,
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)
t1 = plt.scatter(x0, y0, c='b', marker=u'o', s=20)
plt.xlabel("X (m)")
plt.ylabel("Y (m)")
plt.title("Cost map for " + what)
plt.savefig("ImageBank/" + what + '_costmap' + foldername + '.png',
bbox_inches='tight')
plt.show(block=True)
def plotCostColorMapFor12(what, rs, foldername = "None", targetSize = "All"):
'''
Cette fonction permet d'afficher le profil de cout des muscles 1 et 2 des trajectoires
Entrees: -what: choix des donnees a afficher
'''
fig = plt.figure(1, figsize=(16,9))
if what == "OPTI" and targetSize == "All":
for i in range(len(rs.target_size)):
ax = plt.subplot2grid((2,2), (i/2,i%2))
name = rs.OPTIpath + str(rs.target_size[i]) + "/" + foldername + "/CostU12/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for _, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = ax.scatter(x0, y0, c=cost, marker=u'o', s=5, cmap=cm.get_cmap('RdYlBu'))
ax.scatter(rs.XTarget, rs.YTarget, c ='g', marker='v', s=200)
ax.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = ax.scatter(x0, y0, c='b', marker=u'o', s=20)
ax.set_xlabel("X (m)")
ax.set_ylabel("Y (m)")
ax.set_title(str("Cost map U 1 and 2 for target " + str(rs.target_size[i])))
imageFolder = rs.OPTIpath + "/ImageBank/"
else:
if what == "OPTI":
name = rs.OPTIpath + targetSize + "/" + foldername + "/CostU12/"
imageFolder = rs.OPTIpath + "/ImageBank/"
elif what == "Brent":
name = BrentTrajectoriesFolder
imageFolder = "ImageBank/"
else:
name = rs.path + foldername + "/CostU12/"
imageFolder = rs.path + "/ImageBank/"
costs = getCostData(name)
x0 = []
y0 = []
cost = []
for _, v in costs.items():
for j in range(len(v)):
x0.append(v[j][0])
y0.append(v[j][1])
cost.append(v[j][2])
xi = np.linspace(-0.4,0.4,100)
yi = np.linspace(0.12,0.58,100)
zi = griddata(x0, y0, cost, xi, yi)
t1 = plt.scatter(x0, y0, c=cost, marker=u'o', s=5, cmap=cm.get_cmap('RdYlBu'))
plt.scatter(rs.XTarget, rs.YTarget, c ='g', marker='v', s=200)
plt.contourf(xi, yi, zi, 15, cmap=cm.get_cmap('RdYlBu'))
fig.colorbar(t1, shrink=0.5, aspect=5)
t1 = plt.scatter(x0, y0, c='b', marker=u'o', s=20)
plt.xlabel("X (m)")
plt.ylabel("Y (m)")
plt.title("Cost map U 1 and 2 for " + what)
checkIfFolderExists(imageFolder)
plt.savefig(imageFolder+'costmapU.svg', bbox_inches='tight')
plt.show(block = True)
