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However, the MI-FNO method can be used to tackle much larger systems." + "Our use case here is the hydrogen fluoride (HF) system defined below, using the `sto-3g` basis, chosen for simplicity. However, the MI-FNO method can be used to tackle much larger systems." ] }, { @@ -27,7 +27,7 @@ " F 0.0000 0.0000 0.0000\n", " H 0.0000 0.0000 0.9168\n", "\"\"\"\n", - "basis = \"cc-pvdz\"\n", + "basis = \"sto-3g\"\n", "charge = 0 \n", "spin = 0" ] @@ -106,7 +106,7 @@ " F 0.0000 0.0000 0.0000\n", " H 0.0000 0.0000 0.9168\n", "\"\"\"\n", - "basis = \"cc-pvdz\"\n", + "basis = \"sto-3g\"\n", "charge = 0\n", "spin = 0\n", "\n", @@ -119,7 +119,7 @@ "# Method of Increments (MI).\n", "hbci_solver = HBCI()\n", "fno = FNO(hbci_solver, export_fragment_data=True)\n", - "mi_solver = IncrementalDecomposition(solver=fno, truncation_order=2)\n", + "mi_solver = IncrementalDecomposition(solver=fno, truncation_order=3)\n", "\n", "# Submitting the problem to the cloud.\n", "HF_handle = mi_solver.simulate(molecule=HF_mol)\n", @@ -136,6 +136,16 @@ "import json\n", "with open(\"your_file_path\", \"w\") as f:\n", " json.dump(HF_result, f)\n", + "\n", + "for n__trunc, frags in HF_result[\"subproblem_data\"].items():\n", + " for frag_id, frag in frags.items():\n", + " prob_handle = frag[\"problem_handle\"]\n", + "\n", + " if problem_handle:\n", + " frag_res = get_results(prob_handle)\n", + "\n", + " with open(f\"your_folder_path\"/{prob_handle}.json\", \"w\") as f:\n", + " json.dump(frag_res, f)\n", "```" ] }, @@ -182,25 +192,43 @@ "output_type": "stream", "text": [ "(All the energy values are in hartree)\n", - "Total MI-FNO energy = -100.2187315187088\n", - "Correlation energy = -0.19931281562172387\n", - "Mean-field energy = -100.01941870308707\n", - " energy_total epsilon energy_correlation correction\n", - "(1,) -100.033502 -0.014083 -0.014083 -0.006195\n", - "(2,) -100.046650 -0.027232 -0.027232 -0.007127\n", - "(3,) -100.038718 -0.019299 -0.019299 -0.008654\n", - "(4,) -100.038718 -0.019299 -0.019299 -0.008654\n", - "(1, 2) -100.072596 -0.011862 -0.053177 -0.030123\n", - "(1, 3) -100.070297 -0.017496 -0.050878 -0.040116\n", - "(1, 4) -100.070297 -0.017496 -0.050878 -0.040116\n", - "(2, 3) -100.088137 -0.022187 -0.068718 -0.048697\n", - "(2, 4) -100.088137 -0.022187 -0.068718 -0.048697\n", - "(3, 4) -100.086189 -0.028172 -0.066770 -0.056031\n" + "Total MI-FNO energy = -98.59655271223816\n", + "Correlation energy = -0.025795120623911316\n", + "Mean-field energy = -98.57075759161424\n", + " epsilon problem_handle correction energy_correlation \\\n", + "(1,) -0.001326 65652562505002413 0.0 -0.001326 \n", + "(2,) -0.019846 10837505518890413 0.0 -0.019846 \n", + "(3,) -0.000862 31462118862908845 0.0 -0.000862 \n", + "(4,) -0.000756 49501973643554221 0.0 -0.000756 \n", + "(1, 2) -0.003024 65302015864237516 0.0 -0.024195 \n", + "(1, 3) 0.000085 53405772498103756 0.0 -0.002102 \n", + "(1, 4) 0.000142 13411621153304012 0.0 -0.001939 \n", + "(2, 3) -0.000845 22700772126125516 0.0 -0.021553 \n", + "(2, 4) 0.000124 27549614109650380 0.0 -0.020477 \n", + "(3, 4) 0.000078 23150438022147532 0.0 -0.001540 \n", + "(1, 2, 3) 0.000466 30910159730798073 0.0 -0.025351 \n", + "(1, 2, 4) -0.000016 13137250052500985 0.0 -0.024701 \n", + "(2, 3, 4) -0.000017 17864205159132665 0.0 -0.022123 \n", + "\n", + " energy_total \n", + "(1,) -98.572083 \n", + "(2,) -98.590604 \n", + "(3,) -98.571619 \n", + "(4,) -98.571513 \n", + "(1, 2) -98.594953 \n", + "(1, 3) -98.572860 \n", + "(1, 4) -98.572697 \n", + "(2, 3) -98.592310 \n", + "(2, 4) -98.591235 \n", + "(3, 4) -98.572297 \n", + "(1, 2, 3) -98.596109 \n", + "(1, 2, 4) -98.595458 \n", + "(2, 3, 4) -98.592881 \n" ] } ], "source": [ - "fno_fragments = MIFNOHelper(json_file=\"./data/HF_MIFNO_trunc2.json\")\n", + "fno_fragments = MIFNOHelper(mi_json_file=\"./data/HF_STO3G_MIFNO_HBCI.json\", fno_json_folder=\"./data\")\n", "print(fno_fragments)" ] }, @@ -287,7 +315,7 @@ "\n", "Below, we treat a given fragment with Quantum Imaginary Time Evolution (QITE) to obtain its energy. We made sure to enter values for `n_electrons` and `n_spinorbitals` that are consistent with our MI-FNO parameters.\n", "\n", - "This code cell can take several minutes to execute. After its execution, the value of `qite.final_energy` should be about `-100.0273068`." + "This code cell can take several minutes to execute. After its execution, the value of `qite.final_energy` should be about `-98.57208`." ] }, { @@ -299,32 +327,42 @@ "name": "stdout", "output_type": "stream", "text": [ - "Iteration 1 of QITE with starting energy -100.01941870308704\n", - "Iteration 2 of QITE with starting energy -100.02295490797948\n", - "Iteration 3 of QITE with starting energy -100.02490654238967\n", - "Iteration 4 of QITE with starting energy -100.02598299547269\n", - "Iteration 5 of QITE with starting energy -100.02657658219128\n", - "Iteration 6 of QITE with starting energy -100.02690389633094\n", - "Iteration 7 of QITE with starting energy -100.02708440915514\n", - "Iteration 8 of QITE with starting energy -100.02718398984186\n", - "Iteration 9 of QITE with starting energy -100.02723894751776\n", - "Iteration 10 of QITE with starting energy -100.0272692962144\n", - "Iteration 11 of QITE with starting energy -100.0272860687878\n", - "Iteration 12 of QITE with starting energy -100.02729534822525\n", - "Iteration 13 of QITE with starting energy -100.0273004892957\n", - "Iteration 14 of QITE with starting energy -100.02730334285128\n", - "Iteration 15 of QITE with starting energy -100.02730493054182\n", - "Iteration 16 of QITE with starting energy -100.02730581668975\n", - "Iteration 17 of QITE with starting energy -100.0273063132873\n", - "Iteration 18 of QITE with starting energy -100.0273065930274\n", - "Iteration 19 of QITE with starting energy -100.02730675164818\n", - "Final energy of QITE is -100.02730684233332\n" + "Iteration 1 of QITE with starting energy -98.57075759161438\n", + "Iteration 2 of QITE with starting energy -98.57113742411626\n", + "Iteration 3 of QITE with starting energy -98.57140787802587\n", + "Iteration 4 of QITE with starting energy -98.57160051301045\n", + "Iteration 5 of QITE with starting energy -98.57173778000022\n", + "Iteration 6 of QITE with starting energy -98.57183564772347\n", + "Iteration 7 of QITE with starting energy -98.57190547356048\n", + "Iteration 8 of QITE with starting energy -98.57195533523226\n", + "Iteration 9 of QITE with starting energy -98.57199097826164\n", + "Iteration 10 of QITE with starting energy -98.57201648984791\n", + "Iteration 11 of QITE with starting energy -98.57203477805021\n", + "Iteration 12 of QITE with starting energy -98.57204791248209\n", + "Iteration 13 of QITE with starting energy -98.57205736652219\n", + "Iteration 14 of QITE with starting energy -98.57206418950516\n", + "Iteration 15 of QITE with starting energy -98.57206912913362\n", + "Iteration 16 of QITE with starting energy -98.57207271850743\n", + "Iteration 17 of QITE with starting energy -98.57207533800045\n", + "Iteration 18 of QITE with starting energy -98.57207725926021\n", + "Iteration 19 of QITE with starting energy -98.57207867649848\n", + "Iteration 20 of QITE with starting energy -98.57207972874916\n", + "Iteration 21 of QITE with starting energy -98.57208051570359\n", + "Iteration 22 of QITE with starting energy -98.57208110898029\n", + "Iteration 23 of QITE with starting energy -98.57208156014813\n", + "Iteration 24 of QITE with starting energy -98.57208190643986\n", + "Iteration 25 of QITE with starting energy -98.57208217482489\n", + "Iteration 26 of QITE with starting energy -98.57208238491202\n", + "Iteration 27 of QITE with starting energy -98.57208255102157\n", + "Iteration 28 of QITE with starting energy -98.57208268366516\n", + "Iteration 29 of QITE with starting energy -98.57208279060387\n", + "Final energy of QITE is -98.57208287760601\n" ] }, { "data": { "text/plain": [ - "-100.02730684233332" + "-98.57208287760601" ] }, "execution_count": 6, @@ -367,9 +405,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Reconstructed energy: -100.21873178117285\n", - "MIFNO QEMIST Cloud energy: -100.2187315187088\n", - "Difference: 2.6246405582242005e-07\n" + "Reconstructed energy: -98.59655271223812\n", + "MIFNO QEMIST Cloud energy: -98.59655271223816\n", + "Difference: 4.263256414560601e-14\n" ] } ], diff --git a/tangelo/problem_decomposition/incremental/mifno_helper.py b/tangelo/problem_decomposition/incremental/mifno_helper.py index 43986379b..afb3e4322 100644 --- a/tangelo/problem_decomposition/incremental/mifno_helper.py +++ b/tangelo/problem_decomposition/incremental/mifno_helper.py @@ -13,13 +13,13 @@ # limitations under the License. """This file provides helpers in order to import data coming from a MI-FNO job -from QEMIST Cloud, providing the users with both fragment information as well as +run on QEMIST Cloud, providing the users with both fragment information as well as reference results obtained by the classical solvers in QEMIST Cloud. The fragments can be passed to a quantum solver or be used for a quantum computing experiment. Currently, the fragment energies can only be recomputed with a quantum -algorihtms (the interface of MI-FNO fragments and classical algorithms is not +algorihtms (the interface between MI-FNO fragments and classical algorithms is not implemented yet). """ @@ -37,9 +37,9 @@ class MIFNOHelper(): """Python object to post-process, fetch and manipulate QEMIST Cloud MI-FNO - results. The use case for this is to map MI-FNO subproblems into + results. The use case for this is to map MI-FNO subproblems to fermionic Hamiltonians acting as inputs. This object keeps track of the - classical results. + classical calculation results. Attributes: e_tot (float): Total MI-FNO energy. @@ -50,6 +50,7 @@ class MIFNOHelper(): refering to the sampled active space (e.g. '(1,)' or '(0, 2)') They contain information about the correction term, epsilon, list of truncated orbitals and more. + verbose (bool): To print or not to print warnings. Properties: to_dataframe (pandas.DataFrame): Converted frag_info dict into a pandas @@ -59,56 +60,109 @@ class MIFNOHelper(): layer (keys = truncation number). """ - def __init__(self, json_file=None, results_object=None): + def __init__(self, mi_json_file=None, fno_json_folder=None, mi_dict=None, + fno_dicts=None, verbose=False): """Initialization method to process the classical results. A json path - or a python dictionary object can be passed to the method (not both). + or a python dictionary can be passed to the method for the MI + or each FNO fragment results. Passing both a path and a dictionary + raises an error. Not all fragment results need to be imported: + in case of missing data, MIFNOHelper raises an error + mentionning the missing pieces. Args: - json_file (string): Path to a json file containing the results from - QEMIST Cloud. - results_object (dict): Classical computation results (QEMIST Cloud + mi_json_file (string): Path to a json file containing the MI results + from QEMIST Cloud. + fno_json_folder (string): Path to a folder containing the FNO + fragment (json files) results from QEMIST-Cloud. + mi_dict (dict): MI results (QEMIST Cloud output). + fno_dicts (list of dicts): FNO fragment results (QEMIST Cloud output). + verbose (bool): Verbosity. """ # Raise error/warnings if input is not as expected. Only a single input # must be provided to avoid conflicts. - if not (bool(json_file) ^ bool(results_object)): - raise ValueError(f"A json file path OR a dictionary object must be provided when instantiating {self.__class__.__name__}.") + if not (bool(mi_json_file) ^ bool(mi_dict)): + raise ValueError(f"A json file path OR a dictionary object for MI \ + results must be provided when instantiating \ + {self.__class__.__name__}.") - if json_file: - assert os.path.isfile(json_file), f"The file {json_file} does not exist." + if not (bool(fno_json_folder) ^ bool(fno_dicts)): + raise ValueError(f"A json folder path OR a dictionary object for \ + FNO fragment results must be provided when \ + instantiating {self.__class__.__name__}.") - with open(json_file, "r") as f: - results_object = json.loads(f.read()) + self.verbose = verbose - results_object["subproblem_data"] = {int(k): v for k, v in results_object["subproblem_data"].items()} + if mi_json_file: + assert os.path.isfile(mi_json_file), f"The file {mi_json_file} does not exist." + + with open(mi_json_file, "r") as f: + mi_dict = json.loads(f.read()) + + mi_dict["subproblem_data"] = {int(k): v for k, v in mi_dict["subproblem_data"].items()} # Incremental (problem decomposition) quantities. - self.e_tot = results_object["energy_total"] - self.e_corr = results_object["energy_correlation"] - self.e_mf = results_object["mean_field_energy"] + self.e_tot = mi_dict["energy_total"] + self.e_corr = mi_dict["energy_correlation"] + self.e_mf = mi_dict["mean_field_energy"] + + # Select only the MI relevant keys. + self.frag_info = dict() + for n_body, fragments_per_truncation in mi_dict["subproblem_data"].items(): + self.frag_info[n_body] = dict() + for frag_id, frag_result in fragments_per_truncation.items(): + if frag_result.get("problem_handle", None) is not None: + self.frag_info[n_body][frag_id] = {k: frag_result.get(k, None) for k in {"epsilon", "problem_handle"}} + + # Read fragment results stored in json files in a specified folder. + if fno_json_folder: + absolute_path = os.path.abspath(fno_json_folder) - relevant_info = { + fno_dicts = list() + for file in os.listdir(absolute_path): + if file.endswith(".json"): + with open(os.path.join(absolute_path, file), "r") as f: + frag_results = json.loads(f.read()) + fno_dicts.append(frag_results) + + fragment_relevant_info = { "energy_total", "energy_correlation", - "epsilon", "correction", "frozen_orbitals_truncated", "mo_coefficients" } - # Selecting only the FNO keys found in 'relevant_info'. - self.frag_info = dict() - for n_body, fragments_per_truncation in results_object["subproblem_data"].items(): - self.frag_info[n_body] = dict() - for frag_id, frag_result in fragments_per_truncation.items(): - self.frag_info[n_body][frag_id] = {k: frag_result.get(k, None) for k in relevant_info} + # Clean FNO fragment results. + for frag_id in self.fragment_ids: + n_body = len(eval(frag_id)) + + # Default value if fragment information is not detected. + frag_results = dict() + + for fno_frag in fno_dicts: + # Fragments are identified by the active occupied orbital space, + # or their unique problem_handle. + if str(tuple(fno_frag["active_occupied_orbital_space"])) == frag_id: + + # If the mean-field energy for the fragment is not the same, + # the coordinates, spin, basis or charge of the problem + # might be different. + assert round(self.e_mf, 6) == round(fno_frag["mean_field_energy"], 6), \ + f"The mean-field energy for fragment {frag_id} is " \ + "different than the one detected in the MI results." - # Verify if the MO coefficients are there. - if "mo_coefficients" not in frag_result: - raise KeyError(f"MO coefficient not found in the {frag_id} " - "results. Verify that the export_fragment_data flag is set " - "to True for the MI-FNO calculation in QEMIST Cloud.") + # The mo_coefficients data are essential to recompute + # fermionic operators. + assert "mo_coefficients" in fno_frag, "MO coefficients "\ + f"not found in the {frag_id} results. Verify that " \ + "the `export_fragment_data` flag is set to True for " \ + "the MI-FNO calculation in QEMIST Cloud." + + frag_results = fno_frag + + self.frag_info[n_body][frag_id].update({k: frag_results.get(k, None) for k in fragment_relevant_info}) def __repr__(self): """Format the object to print the energies and the fragment information @@ -137,12 +191,12 @@ def to_dataframe(self): @property def fragment_ids(self): - """Outputs the fragment ids in a list.""" + """Output the fragment ids in a list.""" return list(itertools.chain.from_iterable([d.keys() for d in self.frag_info.values()])) @property def frag_info_flattened(self): - """Outputs the nested frag_info without the first layer.""" + """Output the nested frag_info without the first layer.""" return reduce(lambda a, b: {**a, **b}, self.frag_info.values()) def retrieve_mo_coeff(self, destination_folder=os.getcwd()): @@ -168,23 +222,27 @@ def retrieve_mo_coeff(self, destination_folder=os.getcwd()): i_file = 1 for n_body_fragments in self.frag_info.values(): for frag_id, frag in n_body_fragments.items(): - file_path = os.path.join(absolute_path, frag["mo_coefficients"]["key"] + ".hdf5") + if frag["mo_coefficients"]: + file_path = os.path.join(absolute_path, frag["mo_coefficients"]["key"] + ".hdf5") - if not os.path.exists(file_path): - print(f"Downloading and writing MO coefficients file to {file_path} ({i_file} / {n_files})") - response = requests.get(frag["mo_coefficients"]["s3_url"]) + if not os.path.exists(file_path): + print(f"Downloading and writing MO coefficients file to {file_path} ({i_file} / {n_files})") + response = requests.get(frag["mo_coefficients"]["s3_url"]) - with open(file_path, "wb") as file: - file.write(response.content) - i_file += 1 + with open(file_path, "wb") as file: + file.write(response.content) - with h5py.File(file_path, "r") as file: - mo_coeff = np.array(file["mo_coefficients"]) + with h5py.File(file_path, "r") as file: + mo_coeff = np.array(file["mo_coefficients"]) - n_body_fragments[frag_id]["mo_coefficients"]["array"] = mo_coeff + n_body_fragments[frag_id]["mo_coefficients"]["array"] = mo_coeff + else: + print(f"MO coefficients for fragment {frag_id} ({i_file} / {n_files}) not available.") + + i_file += 1 def compute_fermionoperator(self, molecule, frag_id): - """Computes the fermionic Hamiltonian for a MI-FNO fragment. + """Compute the fermionic Hamiltonian for a MI-FNO fragment. Args: molecule (SecondQuantizedMolecule): Full molecule description. @@ -193,11 +251,14 @@ def compute_fermionoperator(self, molecule, frag_id): Returns: FermionOperator: Fermionic operator for the specified fragment id. """ + n_body = len(eval(frag_id)) - if not all(["array" in d["mo_coefficients"] for d in self.frag_info_flattened.values()]): - raise RuntimeError(f"The molecular orbital coefficients are not available. Please call the {self.__class__.__name__}.get_mo_coeff method.") + if self.frag_info[n_body][frag_id]["mo_coefficients"] is None: + raise RuntimeError(f"The fragment information has not been imported.") + + if self.frag_info[n_body][frag_id]["mo_coefficients"].get("array", None) is None: + raise RuntimeError(f"The molecular orbital coefficients are not available. Please call the {self.__class__.__name__}.retrieve_mo_coeff method.") - n_body = len(eval(frag_id)) mo_coeff = self.frag_info[n_body][frag_id]["mo_coefficients"]["array"] frozen_orbitals = self.frag_info[n_body][frag_id]["frozen_orbitals_truncated"] @@ -208,13 +269,19 @@ def compute_fermionoperator(self, molecule, frag_id): "the results. Please verify that the molecular quantities are "\ "the same as the one in the MI-FNO computation." - # Returning a new molecule with the right frozen orbital. - new_molecule = molecule.freeze_mos(frozen_orbitals, inplace=False) + # Returning a new molecule with the frozen orbitals. + try: + new_molecule = molecule.freeze_mos(frozen_orbitals, inplace=False) + except ValueError: + raise ValueError(f"All orbitals except {frag_id} are frozen from " + "the FNO truncation. That means no " + "correlation energy can be extracted from this " + "fragment.") return new_molecule._get_fermionic_hamiltonian(mo_coeff) - def mi_summation(self, user_provided_energies=None): - r"""Recomputes the total energy for the method of increments (MI). + def mi_summation(self, user_provided_energies=None, force_negative_epsilon=False): + r"""Recompute the total energy for the method of increments (MI). Each increment corresponds to "new" correlation energy from the n-body problem. This method makes computing the total energy with new results possible. @@ -230,21 +297,33 @@ def mi_summation(self, user_provided_energies=None): user_provided_energies (dict): New energy values provided by the user, used instead of the corresponding pre-computed ones. E.g. {"(0, )": -1.234} or {"(1, )": -1.234, "(0, 1)": -5.678}. + force_negative_epsilon (bool): Force positive epsilons to 0. Returns: float: Method of increment total energy. """ + fragment_energies = {k: v["energy_total"] for k, v in self.frag_info_flattened.items()} + + if any([e is None for e in fragment_energies.values()]): + raise ValueError("All fragment data must be imported to " + "recompute the total MI-FNO energy.") + if user_provided_energies is None: user_provided_energies = dict() else: fragment_correction = {k: v["correction"] for k, v in self.frag_info_flattened.items()} - user_provided_energies = {frag_id: e + fragment_correction[frag_id] for frag_id, e in user_provided_energies.items()} - fragment_energies = {k: v["energy_total"] for k, v in self.frag_info_flattened.items()} + if any(fragment_correction[frag_id] is None for frag_id in user_provided_energies.keys()): + raise RuntimeError(f"Not all the fragments in {list(user_provided_energies.keys())} " + "have been imported. The MP2 correction must be known " + "for all fragments to recompute the total MI-FNO energy.") + + user_provided_energies = {frag_id: e + fragment_correction[frag_id] for frag_id, e in user_provided_energies.items()} # Update to consider energies taken from a calculation. fragment_energies.update(user_provided_energies) + # Equivalent to truncation_order in QEMIST Cloud. n_body_max = max(self.frag_info.keys()) # Perform the incremental sumamtion. @@ -259,12 +338,15 @@ def mi_summation(self, user_provided_energies=None): for frag_increment in itertools.combinations(eval(frag_id), n_increment): epsilons[frag_id] -= epsilons[str(frag_increment)] - # Check if epsilon < 0, i.e. positive correlation energy increment. + # Check if epsilon > 0, i.e. positive correlation energy increment. for frag_id, eps in epsilons.items(): if eps > 0.: - warnings.warn(f"Epsilon for frag_id {frag_id} is positive " - f"({eps}). With MI, there is no reason to consider a " - "fragment returning a positive correlation energy. Please " - "check your calculations.", RuntimeWarning) + if self.verbose: + warnings.warn(f"Epsilon for frag_id {frag_id} is positive " + f"({eps}). With MI, there is no reason to consider a " + "fragment returning a positive correlation energy. " + "Please check your calculations.", RuntimeWarning) + if force_negative_epsilon: + epsilons[frag_id] = 0. return self.e_mf + sum(epsilons.values()) diff --git a/tangelo/problem_decomposition/tests/incremental/data/2506660533805782.json b/tangelo/problem_decomposition/tests/incremental/data/2506660533805782.json new file mode 100644 index 000000000..319f4d5dc --- /dev/null +++ b/tangelo/problem_decomposition/tests/incremental/data/2506660533805782.json @@ -0,0 +1 @@ +{"log_url": null, "num_elec": 6, "num_basis": 6, "correction": -3.796187295520073e-05, "num_virtual": 4, "energy_total": -15.576307968219917, "num_occupied": 3, "mo_coefficients": {"key": "733b113af090aa768d7665be26e7e84e961e85f8a31b1f228bb1eda6a3516856", "s3_url": "https://qemistmocoefficients.s3.us-west-2.amazonaws.com/733b113af090aa768d7665be26e7e84e961e85f8a31b1f228bb1eda6a3516856", "s3_bucket_name": "qemistmocoefficients"}, "mp2_correlation": -0.01082351689226376, "mean_field_energy": -15.560312342811814, 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"sub_problems": []} \ No newline at end of file diff --git a/tangelo/problem_decomposition/tests/incremental/data/36122231393264357.json b/tangelo/problem_decomposition/tests/incremental/data/36122231393264357.json new file mode 100644 index 000000000..7529bd25e --- /dev/null +++ b/tangelo/problem_decomposition/tests/incremental/data/36122231393264357.json @@ -0,0 +1 @@ +{"log_url": null, "num_elec": 6, "num_basis": 6, "correction": -9.70184252835609e-05, "num_virtual": 4, "energy_total": -15.57655011813111, "num_occupied": 3, "mo_coefficients": {"key": "ec1e1c08168920d28d95c268bdd5ff8eb2fa8b5f0b9abd43079c01c0de7df0ef", "s3_url": "https://qemistmocoefficients.s3.us-west-2.amazonaws.com/ec1e1c08168920d28d95c268bdd5ff8eb2fa8b5f0b9abd43079c01c0de7df0ef", "s3_bucket_name": "qemistmocoefficients"}, "mp2_correlation": -0.011072416597546935, "mean_field_energy": -15.560312342811814, "energy_correlation": -0.016237775319295267, "virtual_orbital_space": [3, 4, 5, 6], "complete_orbital_space": 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a/tangelo/problem_decomposition/tests/incremental/data/60128336913933014.json b/tangelo/problem_decomposition/tests/incremental/data/60128336913933014.json new file mode 100644 index 000000000..4cea2cbfc --- /dev/null +++ b/tangelo/problem_decomposition/tests/incremental/data/60128336913933014.json @@ -0,0 +1 @@ +{"log_url": null, "num_elec": 6, "num_basis": 6, "correction": -3.796187305220647e-05, "num_virtual": 4, "energy_total": -15.576307968219549, "num_occupied": 3, "mo_coefficients": {"key": "a46a6c3ed399e63f915c8692d0c95cfc8153e18f241d320ec6faaed2b92ac96a", "s3_url": "https://qemistmocoefficients.s3.us-west-2.amazonaws.com/a46a6c3ed399e63f915c8692d0c95cfc8153e18f241d320ec6faaed2b92ac96a", "s3_bucket_name": "qemistmocoefficients"}, "mp2_correlation": -0.01082351689145825, "mean_field_energy": -15.560312342811814, "energy_correlation": -0.015995625407734693, "virtual_orbital_space": [3, 4, 5, 6], "complete_orbital_space": [0, 1, 2, 3, 4, 5, 6], "occupied_orbital_space": [0, 1, 2], 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a/tangelo/problem_decomposition/tests/incremental/data/BeH2_STO3G_3MIFNO_FCI.json +++ /dev/null @@ -1 +0,0 @@ -{"energy_total": -15.59517686892268, "energy_correlation": -0.03486452611087287, "complete_orbital_space": [0, 1, 2, 3, 4, 5, 6], "occupied_orbital_space": [0, 1, 2], "virtual_orbital_space": [3, 4, 5, 6], "frozen_occupied_orbital_space": [], "active_occupied_orbital_space": [0, 1, 2], "frozen_virtual_orbital_space": [], "active_virtual_orbital_space": [3, 4, 5, 6], "subproblem_data": {"1": {"(0,)": {"energy_total": -15.560451843011553, "energy_correlation": -0.00013950019974551253, "complete_orbital_space": [0, 1, 2, 3, 4, 5, 6], "occupied_orbital_space": [0, 1, 2], "virtual_orbital_space": [3, 4, 5, 6], "frozen_occupied_orbital_space": [1, 2], "active_occupied_orbital_space": [0], "frozen_virtual_orbital_space": [], "active_virtual_orbital_space": [3, 4, 5, 6], "frozen_orbitals_truncated": [1, 2], "frozen_virtual_orbital_space_truncated": [], 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a/tangelo/problem_decomposition/tests/incremental/data/fb52353e87823089c5ecfccc394d441602d8078ee5d618a82348ea0a9255e7d5.hdf5 and /dev/null differ diff --git a/tangelo/problem_decomposition/tests/incremental/test_mifno_helper.py b/tangelo/problem_decomposition/tests/incremental/test_mifno_helper.py index 5bd1581e3..e5d11687a 100644 --- a/tangelo/problem_decomposition/tests/incremental/test_mifno_helper.py +++ b/tangelo/problem_decomposition/tests/incremental/test_mifno_helper.py @@ -19,11 +19,19 @@ from tangelo.problem_decomposition import MIFNOHelper pwd_this_test = os.path.dirname(os.path.abspath(__file__)) -json_file = os.path.join(pwd_this_test, "data", "BeH2_STO3G_3MIFNO_FCI.json") +json_files = os.path.join(pwd_this_test, "data") +mi_results = os.path.join(json_files, "BeH2_STO3G_MIFNO_HBCI.json") -with open(json_file, "r") as f: - results_object = json.loads(f.read()) -results_object["subproblem_data"] = {int(k): v for k, v in results_object["subproblem_data"].items()} +with open(mi_results, "r") as f: + mi_object = json.loads(f.read()) +mi_object["subproblem_data"] = {int(k): v for k, v in mi_object["subproblem_data"].items()} + +frag_objects = list() +for f_path in os.listdir(json_files): + if f_path.endswith(".json"): + file_path = os.path.join(json_files, f_path) + with open(file_path, "r") as f: + frag_objects.append(json.loads(f.read())) class MIFNOHelperTest(unittest.TestCase): @@ -31,39 +39,39 @@ class MIFNOHelperTest(unittest.TestCase): def test_init_from_file(self): """Verify initialization with a json file.""" - beh2_mifno = MIFNOHelper(json_file) + beh2_mifno = MIFNOHelper(mi_json_file=mi_results, fno_json_folder=json_files) - self.assertAlmostEquals(beh2_mifno.e_tot, -15.595176868) - self.assertAlmostEquals(beh2_mifno.e_corr, -0.034864526) - self.assertAlmostEquals(beh2_mifno.e_mf, -15.560312342) + self.assertAlmostEquals(beh2_mifno.e_tot, -15.595177739) + self.assertAlmostEquals(beh2_mifno.e_corr, -0.034865396) + self.assertAlmostEquals(beh2_mifno.e_mf, -15.560312343) # Testing the number of detected increments. - self.assertEqual(len(beh2_mifno.frag_info), 3) + self.assertEqual(len(beh2_mifno.frag_info), 2) def test_init_from_dict(self): """Verify initialization with a dict object.""" - beh2_mifno = MIFNOHelper(results_object=results_object) + beh2_mifno = MIFNOHelper(mi_dict=mi_object, fno_dicts=frag_objects) - self.assertAlmostEquals(beh2_mifno.e_tot, -15.595176868) - self.assertAlmostEquals(beh2_mifno.e_corr, -0.034864526) - self.assertAlmostEquals(beh2_mifno.e_mf, -15.560312342) + self.assertAlmostEquals(beh2_mifno.e_tot, -15.595177739) + self.assertAlmostEquals(beh2_mifno.e_corr, -0.034865396) + self.assertAlmostEquals(beh2_mifno.e_mf, -15.560312343) # Testing the number of detected increments. - self.assertEqual(len(beh2_mifno.frag_info), 3) + self.assertEqual(len(beh2_mifno.frag_info), 2) def test_fragment_ids(self): """Verify if the fragment_ids property returns all the fragment ids..""" - beh2_mifno = MIFNOHelper(json_file) + beh2_mifno = MIFNOHelper(mi_json_file=mi_results, fno_json_folder=json_files) frag_ids = beh2_mifno.fragment_ids - self.assertEquals(frag_ids, ["(0,)", "(1,)", "(2,)", "(0, 1)", "(0, 2)", "(1, 2)", "(0, 1, 2)"]) + self.assertEquals(frag_ids, ["(0,)", "(1,)", "(2,)", "(0, 1)", "(0, 2)", "(1, 2)"]) def test_mi_summation(self): """Verify that the energy can be recomputed with the incremental method.""" - beh2_mifno = MIFNOHelper(json_file) + beh2_mifno = MIFNOHelper(mi_json_file=mi_results, fno_json_folder=json_files) beh2_mifno.retrieve_mo_coeff(os.path.join(pwd_this_test, "data")) e_mi = beh2_mifno.mi_summation()