def getPolicy_NNet(pra, extent, vown, vint=0., nbin=250, ra=-1, bounds=[]):
# Load network of given pRA into Python
nnet_file_name = "networks/VertCAS_pra%02d_v4_45HU_200.nnet" % (pra + 1)
net = NNet(nnet_file_name)
tauMin, tauMax, hMin, hMax = extent
# Get safeable bounds
possAdv = getPossibleAdvisories(pra)
# Generate a heat map using the bounds for each set
# Use meshgrid to define array of all inputs to network
hVec = np.linspace(hMin, hMax, nbin)
tauVec = np.linspace(tauMin, tauMax, nbin)
hMesh, tauMesh = np.meshgrid(hVec, tauVec)
hMesh = hMesh.reshape(nbin**2, 1)
tauMesh = tauMesh.reshape(nbin**2, 1)
vownMesh = np.ones((nbin**2, 1)) * vown
vintMesh = np.ones((nbin**2, 1)) * vint
netIn = np.concatenate((hMesh, vownMesh, vintMesh, tauMesh), axis=1)
# Evaluate network on all inputs
netOut = net.evaluate_network_multiple(netIn)
# Convert outputs to best advisories
bestAdv = np.argmax(netOut, axis=1)
heatMap = np.array([possAdv[i] for i in bestAdv])
# Highlight SAT points if bounds given
if len(bounds) > 0:
for i in range(nbin**2):
if heatMap[i] == ra and satisfiesBounds(bounds, netIn[i, 0],
netIn[i, 3]):
heatMap[i] = 10
# Reshape the map and flip around the axes for plotting purposes
heatMap = heatMap.reshape((nbin, nbin)).T[::-1]
return heatMap
