In EDA, give an error if the output will likely be lost when redirected to one file

examples/36-amlo_eda.py

@@ -42,8 +42,9 @@
 
 mol_list = [mol1, mol2]
 
-eda_result = eda.eval_ALMO_EDA_2_energies(mol_list, xc = "wB97M-V")
+eda_result, dft_result = eda.eval_ALMO_EDA_2_energies(mol_list, xc = "wB97M-V")
 print(f"EDA result in dict form: {eda_result}")
+print(f"DFT energies of each fragment and the total system: {dft_result}")
 
 ### Reference output:
 # Fragment 0 energy = -76.4334344665 Hartree

gpu4pyscf/properties/eda.py

@@ -29,6 +29,7 @@
 from gpu4pyscf.lib.diis import DIIS
 from gpu4pyscf.lib import logger
 import time
+import warnings
 
 # np.set_printoptions(linewidth = np.iinfo(np.int32).max, threshold = np.iinfo(np.int32).max, precision = 16, suppress = True)
 
@@ -1080,6 +1081,7 @@ def _make_mf(mol, if_kernel = True, dispersion_free_xc = None):
         mf.direct_scf_tol = 1e-16
         if if_kernel:
             energy = mf.kernel()
+            mf.mol.stdout.flush()
             assert mf.converged
             return mf, energy
         else:
@@ -1092,9 +1094,17 @@ def _get_gradient(mf):
         gradient = grad_obj.kernel()
         if isinstance(gradient, cp.ndarray):
             gradient = gradient.get()
+        mf.mol.stdout.flush()
         return grad_obj.kernel()
 
     n_frag = len(mol_list)
+    for i_frag in range(n_frag):
+        for j_frag in range(i_frag + 1, n_frag):
+            if mol_list[i_frag].stdout != mol_list[j_frag].stdout:
+                warnings.warn("The stdout of each mol in mol_list is not consistent. We do not guarantee which stdout to write. "
+                              "Notice if the mol objects share the same \"output\" value, then the same output file is opened "
+                              "more than once, and the outputs of earlier-created mol will be lost.")
+
     mf_list = []
     frag_energy_list = []
     frag_gradient_list = []