def exploremonitor(params=None):
if hasattr(exploremonitor, "prevparams"):
# Convert params to numerical value
params = sym2num(params)
# Compute number of new dimensions explored
newdims = sum([np.count_nonzero(param > ubparam) + np.count_nonzero(param < lbparam)
for param, ubparam, lbparam in zip(params, exploremonitor.ub, exploremonitor.lb)])
# Update lower and upper bounds
exploremonitor.lb = [np.minimum(prevparam, param)
for prevparam, param in zip(exploremonitor.prevparams, params)]
exploremonitor.ub = [np.maximum(prevparam, param)
for prevparam, param in zip(exploremonitor.prevparams, params)]
# Update previous params
exploremonitor.prevparams = params
# Compute the total number of parameters
numparams = sum([np.size(param) for param in params])
# Compute the volume of the quadratic hull
hullvol = np.prod(np.array([np.prod(np.abs(ubparam - lbparam))
for ubparam, lbparam in zip(exploremonitor.ub, exploremonitor.lb)]))
# Return
return "| Explored Dimensions: {} of {} || Hull Volume: {} |".format(int(newdims),
int(numparams),
float(hullvol))
else:
# Log params
exploremonitor.prevparams = sym2num(params)
# Log lower and upper bounds
exploremonitor.lb = exploremonitor.prevparams
exploremonitor.ub = exploremonitor.prevparams
# Return
return "| Explored Dimensions: N/A |"
def exploremonitor(params=None):
if hasattr(exploremonitor, "prevparams"):
# Convert params to numerical value
params = nu.sym2num(params)
# Compute number of new dimensions explored
newdims = sum([np.count_nonzero(param > ubparam) + np.count_nonzero(param < lbparam)
for param, ubparam, lbparam in zip(params, exploremonitor.ub, exploremonitor.lb)])
# Update lower and upper bounds
exploremonitor.lb = [np.minimum(prevparam, param)
for prevparam, param in zip(exploremonitor.prevparams, params)]
exploremonitor.ub = [np.maximum(prevparam, param)
for prevparam, param in zip(exploremonitor.prevparams, params)]
# Update previous params
exploremonitor.prevparams = params
# Compute the total number of parameters
numparams = sum([np.size(param) for param in params])
# Compute the volume of the quadratic hull
hullvol = np.prod(np.array([np.prod(np.abs(ubparam - lbparam))
for ubparam, lbparam in zip(exploremonitor.ub, exploremonitor.lb)]))
# Return
return "| Explored Dimensions: {} of {} || Hull Volume: {} |".format(int(newdims),
int(numparams),
float(hullvol))
else:
# Log params
exploremonitor.prevparams = nu.sym2num(params)
# Log lower and upper bounds
exploremonitor.lb = exploremonitor.prevparams
exploremonitor.ub = exploremonitor.prevparams
# Return
return "| Explored Dimensions: N/A |"
def updatenormmonitor(params):
if hasattr(updatenormmonitor, "prevparams"):
# Convert to num
params = sym2num(params)
# Compute update norm
updnorm = sum([np.sum((currparam - prevparam) ** 2)
for currparam, prevparam in zip(params, updatenormmonitor.prevparams)])
# Log
updatenormmonitor.prevparams = params
return "| Update Norm: {0:.7f} |".format(float(updnorm))
else:
updatenormmonitor.prevparams = sym2num(params)
return "| Update Norm: N/A |"
pass
def updatenormmonitor(params):
if hasattr(updatenormmonitor, "prevparams"):
# Convert to num
params = nu.sym2num(params)
# Compute update norm
updnorm = sum([np.sum((currparam - prevparam) ** 2)
for currparam, prevparam in zip(params, updatenormmonitor.prevparams)])
# Log
updatenormmonitor.prevparams = params
return "| Update Norm: {0:.7f} |".format(float(updnorm))
else:
updatenormmonitor.prevparams = nu.sym2num(params)
return "| Update Norm: N/A |"
pass