General improvements

- Cleaned up unneeded comments.
- Added support for HF method.
- Parallel computation support using %pal.
- Black beautification.

qcengine/programs/orca.py

@@ -49,15 +49,6 @@ class OrcaHarness(ProgramHarness):
  }
  # fmt: on
 
- # Different open-shell scenarios:
- # - Restricted references
- # RHF-RMP2 (like RHF-UMP2 using Molpro's naming convention for CC methods)
- # RHF-UCCSD
- # RHF-UCCSD(T)
- # RHF-RCCSD
- # RHF-RCCSD(T)
- # - Unrestricted references (Only supported up to UMP2, no CC support)
- # UHF-UMP2
  # NOTE: Unrestricted SCF methods must be specified by using keyword reference
  _hf_methods: Set[str] = {"HF", "RHF"}
  _restricted_post_hf_methods: Set[str] = {"MP2", "CCSD", "CCSD(T)"} # RMP2, RCCSD, RCCSD(T)}
@@ -183,20 +174,8 @@ def build_input(
  if "reference" in caseless_keywords and caseless_keywords["reference"] == "unrestricted":
  unrestricted = True
 
- # Memory is in megawords per core for Molpro
- # memory_mw_core = int(config.memory * (1024 ** 3) / 8e6 / config.ncores)
- # input_file.append("memory,{},M".format(memory_mw_core))
- # input_file.append("")
-
  # Write the geom
  xyz_block = input_model.molecule.to_string(dtype="orca", units="Angstrom")
- # input_file.append(xyz_block)
-
- # Write the basis set
- # input_file.append("basis={")
- # input_file.append(f"default,{input_model.model.basis}")
- # input_file.append("}")
- # input_file.append("")
 
  # Determine what SCF type (restricted vs. unrestricted)
  hf_type = "RHF"
@@ -207,19 +186,20 @@ def build_input(
 
  # Write energy call
  energy_call = []
- # If post-hf method is called then make sure to write a HF call first
+
  if input_model.model.method.upper() in self._post_hf_methods: # post SCF case
  energy_call.append(f"{{{hf_type}}}")
  energy_call.append("")
  energy_call.append(f"{{{input_model.model.method}}}")
- # If DFT call make sure to write {rks,method}
+
  elif input_model.model.method.upper() in self._dft_functionals: # DFT case
  input_file.append("! SP {} {}".format(input_model.model.method, input_model.model.basis))
  input_file.append(xyz_block)
 
- # energy_call.append(f"{{{dft_type},{input_model.model.method}}}")
  elif input_model.model.method.upper() in self._hf_methods: # HF case
- energy_call.append(f"{{{hf_type}}}")
+ input_file.append("! SP {} {}".format(input_model.model.method, input_model.model.basis))
+ input_file.append(xyz_block)
+
  else:
  raise InputError(f"Method {input_model.model.method} not implemented for Molpro.")
 
@@ -231,6 +211,9 @@ def build_input(
  else:
  raise InputError(f"Driver {input_model.driver} not implemented for Molpro.")
 
+ parallel = "%pal nproc {} end".format(config.ncores)
+ input_file.append(parallel)
+
  input_file = "\n".join(input_file)
  else:
  # Some of the potential different template options
@@ -262,6 +245,7 @@ def parse_output(self, outfiles: Dict[str, str], input_model: "AtomicInput") ->
 
  properties = {}
  extras = {}
+ extras["ev_to_hartrees"] = 0.0367493
 
  # Process basis set data
  properties["calcinfo_nbasis"] = data.nbasis
@@ -275,7 +259,7 @@ def parse_output(self, outfiles: Dict[str, str], input_model: "AtomicInput") ->
  # Determining the final energy
  # Throws an error if the energy isn't found for the method specified from the input_model.
  try:
- final_energy = data.scfenergies[-1] * 0.0367493
+ final_energy = data.scfenergies[-1] * extras["ev_to_hartrees"]
  except:
  raise KeyError(f"Could not find {method} total energy")
 
@@ -284,7 +268,7 @@ def parse_output(self, outfiles: Dict[str, str], input_model: "AtomicInput") ->
 
  # Determining return_result
  if input_model.driver == "energy":
- output_data["return_result"] = final_energy 
+ output_data["return_result"] = final_energy
  extras["CURRENT ENERGY"] = final_energy
 
  elif input_model.driver == "gradient":
@@ -302,6 +286,7 @@ def parse_output(self, outfiles: Dict[str, str], input_model: "AtomicInput") ->
  output_data["success"] = True
 
  import uuid
+
  myid = str(uuid.uuid4())
  with open("/tmp/orcafiles/{}".format(myid), "wb") as handle:
  handle.write(outfiles["outfiles"]["dispatch.gbw"])
@@ -310,8 +295,7 @@ def parse_output(self, outfiles: Dict[str, str], input_model: "AtomicInput") ->
  return AtomicResult(**output_data)
 
  def get_gradient(self, gradient_file):
- """Get gradient from engrad Orca file
- """
+ """Get gradient from engrad Orca file"""
  copy = False
  found = False
  gradient = []
@@ -325,7 +309,7 @@ def get_gradient(self, gradient_file):
  gradient.append(float(line))
  except ValueError:
  pass
- 
+
  dim = np.sqrt(len(gradient)).astype(int)
 
- return np.array(gradient).reshape(dim, dim)
+ return np.array(gradient).reshape(dim, dim)