1. In opt_orb_pytorh_dpsi, add IO.change_info.get_info_max()

Author: PeizeLin

tools/opt_orb_pytorch_dpsi/IO/change_info.py

@@ -1,4 +1,6 @@
 import addict
+import util
+import itertools
 
 def change_info(info_old, weight_old):
 	info_stru = [None] * info_old.Nst
@@ -28,4 +30,47 @@ def change_info(info_old, weight_old):
 	info_opt.cal_T = info_old.cal_T
 	info_opt.cal_smooth = info_old.cal_smooth
 
-	return info_stru, info_element, info_opt
+	return info_stru, info_element, info_opt
+
+	"""
+	info_stru =
+	[{'Na': {'C': 2},
+	  'Nb': 6,
+	  'weight': tensor([0.1250, 0.1250, 0.1150, 0.1150, 0.0200, 0.0000])},
+	 {'Na': {'C': 2},
+	  'Nb': 6,
+	  'weight': tensor([0.1250, 0.1250, 0.0896, 0.0896, 0.0707, 0.0000])}]
+
+	info_element =
+	{'C': {'Ecut': 200,
+       'Ne': 19,
+       'Nl': 3,
+       'Nu': [2, 2, 1],
+       'Rcut': 6,
+       'dr': 0.01}}
+
+	info_opt =
+	{'cal_T': False,
+	 'cal_smooth': False,
+	 'lr': 0.01}
+	"""
+
+
+def get_info_max(info_stru, info_element):
+	info_max = [None] * len(info_stru)
+	for ist in range(len(info_stru)):
+		Nt = info_stru[ist].Na.keys()
+		info_max[ist] = addict.Dict()
+		info_max[ist].Nt = len(Nt)
+		info_max[ist].Na = max((info_stru[ist].Na[it] for it in Nt))
+		info_max[ist].Nl = max([info_element[it].Nl for it in Nt])
+		info_max[ist].Nm = max((util.Nm(info_element[it].Nl-1) for it in Nt))
+		info_max[ist].Nu = max(itertools.chain.from_iterable([info_element[it].Nu for it in Nt]))
+		info_max[ist].Ne = max((info_element[it].Ne for it in Nt))
+		info_max[ist].Nb = info_stru[ist].Nb
+	return info_max
+
+	"""
+	[{'Na': 2, 'Nb': 6, 'Ne': 19, 'Nl': 3, 'Nm': 5, 'Nt': 1, 'Nu': 2},
+	 {'Na': 2, 'Nb': 6, 'Ne': 19, 'Nl': 3, 'Nm': 5, 'Nt': 1, 'Nu': 2}]
+	"""