Making convergence and functional = all work; changing appearance of …

…printout

src/koopmans/calculators/_koopmans_cp.py

@@ -339,6 +339,7 @@ def read_ham_xml_files(self, bare=False) -> List[np.ndarray]:
         return ham_matrix
 
     def _ham_pkl_file(self, bare: bool = False) -> Path:
+        assert self.directory is not None
         if bare:
             suffix = '.bare_ham.pkl'
         else:
@@ -549,7 +550,7 @@ def files_to_convert_with_spin2_to_spin1(self):
                 prefix, suffix = f.split('.')
             nspin_2_files.append(f'{prefix}1.{suffix}')
 
-        parent = self.parameters.outdir / f'{self.parameters.prefix}_{self.parameters.ndr}.save/K00001'
+        parent = self.read_directory / 'K00001'
         return {'spin_2_files': [(self, parent / f1) for f1 in nspin_2_files], 'spin_1_files': nspin_1_files}
 
     @property
@@ -570,14 +571,14 @@ def files_to_convert_with_spin1_to_spin2(self):
             nspin_2up_files.append(f'{prefix}1.{suffix}')
             nspin_2dw_files.append(f'{prefix}2.{suffix}')
 
-        parent = self.parameters.outdir / f'{self.parameters.prefix}_{self.parameters.ndr}.save/K00001'
+        parent = self.read_directory / 'K00001'
 
         return {'spin_1_files': [(self, parent / f) for f in nspin_1_files],
                 'spin_2_up_files': nspin_2up_files,
                 'spin_2_down_files': nspin_2dw_files}
 
     def convert_wavefunction_2to1(self):
-        nspin2_tmpdir = self.parameters.outdir / f'{self.parameters.prefix}_{self.parameters.ndr}.save/K00001'
+        nspin2_tmpdir = self.read_directory / 'K00001'
         nspin1_tmpdir = self.parameters.outdir / f'{self.parameters.prefix}_98.save/K00001'
 
         for directory in [nspin2_tmpdir, nspin1_tmpdir]:
@@ -643,6 +644,16 @@ def convert_wavefunction_1to2(self):
                 with open(file_out, 'wb') as fd:
                     fd.write(contents)
 
+    @property
+    def read_directory(self) -> Path:
+        assert isinstance(self.parameters.outdir, Path)
+        return self.parameters.outdir / f'{self.parameters.prefix}_{self.parameters.ndr}.save'
+
+    @property
+    def write_directory(self):
+        assert isinstance(self.parameters.outdir, Path)
+        return self.parameters.outdir / f'{self.parameters.prefix}_{self.parameters.ndw}.save'
+
 
 def convert_flat_alphas_for_kcp(flat_alphas: List[float],
                                 parameters: settings.KoopmansCPSettingsDict) -> List[List[float]]:

src/koopmans/references.bib

@@ -112,8 +112,9 @@ @misc{Dabo2009
   author = {Dabo, I. and Cococcioni, M. and Marzari, N.},
   year = {2009},
   month = jan,
+  eprint = {0901.2637},
   abstract = {In effective single-electron theories, self-interaction manifests itself through the unphysical dependence of the energy of an electronic state as a function of its occupation, which results in important deviations from the ideal Koopmans trend and strongly affects the accuracy of electronic-structure predictions. Here, we study the non-Koopmans behavior of local and semilocal density-functional theory (DFT) total energy methods as a means to quantify and to correct self-interaction errors. We introduce a non-Koopmans self-interaction correction that generalizes the Perdew-Zunger scheme, and demonstrate its considerably improved performance in correcting the deficiencies of DFT approximations for self-interaction problems of fundamental and practical relevance.},
-  archiveprefix = {arxiv}
+  archiveprefix = {arXiv}
 }
 
 @article{Dabo2010,

src/koopmans/workflows/_convergence.py

@@ -21,6 +21,7 @@
 import numpy as np
 
 from koopmans import cell, utils
+from koopmans.outputs import OutputModel
 
 from ._workflow import Workflow
 
@@ -215,8 +216,16 @@ def ConvergenceVariableFactory(conv_var, **kwargs) -> ConvergenceVariable:
                                   'construct your ConvergenceWorkflow using the ConvergenceWorkflowFactory')
 
 
+class ConvergenceOutputs(OutputModel):
+
+    converged_values: Dict[str, Any]
+
+
 class ConvergenceWorkflow(Workflow):
 
+    output_model = ConvergenceOutputs  # type: ignore
+    outputs: ConvergenceOutputs
+
     '''
     A Workflow class that wraps another workflow in a convergence procedure in order to converge the observable within the specified tolerance with respect to the variables
     '''
@@ -297,22 +306,19 @@ def _run(self) -> None:
                 subwf = self._subworkflow_class.fromparent(self)
 
                 # For each parameter we're converging wrt...
-                header = ''
-                subdir = Path()
+                label = ''
                 for index, variable in zip(indices, self.variables):
                     value = variable.values[index]
                     if isinstance(value, float):
                         value_str = f'{value:.1f}'
                     else:
                         value_str = str(value)
-                    header += f'{variable.name} = {value_str}, '
 
                     if isinstance(value, list):
                         value_str = ''.join([str(x) for x in value])
 
                     # Create new working directory
-                    subdir /= f'{variable.name}_{value_str}'.replace(
-                        ' ', '_').replace('.', 'd')
+                    label += f' {variable.name} {value_str}'.replace('.', '_')
 
                     # Set the value
                     variable.set_value(subwf, value)
@@ -329,9 +335,8 @@ def _run(self) -> None:
                     #         for _ in range(extra_orbitals)]
                     # utils.write_alpha_file(directory=Path(), alphas=alphas, filling=filling)
 
-                self.print(header.rstrip(', '), style='subheading')
-
                 # Perform calculation
+                subwf.name += label
                 subwf.run()
 
                 # Store the result
@@ -371,6 +376,8 @@ def _run(self) -> None:
                 self.print('\n Converged variables are '
                            + ', '.join([f'{p.name} = {p.converged_value}' for p in self.variables]))
 
+                self.outputs = self.output_model(converged_values={v.name: v.converged_value for v in self.variables})
+
                 return
             else:
                 # Work out which variables are yet to converge, and line up more calculations
@@ -379,7 +386,7 @@ def _run(self) -> None:
                 new_array_shape = list(np.shape(results))
                 new_array_slice: List[Union[int, slice]] = [
                     slice(None) for _ in indices]
-                self.print('Progress update', style='heading')
+                self.print('\nProgress update', style='heading')
                 for index, var in enumerate(self.variables):
                     subarray_slice = [slice(None) for _ in self.variables]
                     subarray_slice[index] = slice(0, -1)
@@ -403,6 +410,7 @@ def _run(self) -> None:
                         var.extend()
                         new_array_shape[index] += 1
                         new_array_slice[index] = slice(None, -1)
+                self.print()
 
                 new_results = np.empty(new_array_shape)
                 new_results[:] = np.nan

src/koopmans/workflows/_dft.py

@@ -27,16 +27,18 @@ def __init__(self, *args, **kwargs):
         self.parameters.functional = 'dft'
 
 
+class DFTCPOutput(OutputModel):
+    pass
+
+
 class DFTCPWorkflow(DFTWorkflow):
+    output_model = DFTCPOutput  # type: ignore
+    outputs: DFTCPOutput
 
     def _run(self):
 
         calc = self.new_calculator('kcp')
 
-        # Removing old directories
-        if self.parameters.from_scratch:
-            utils.system_call(f'rm -r {calc.parameters.outdir} 2>/dev/null', False)
-
         calc.prefix = 'dft'
         calc.directory = '.'
         calc.parameters.ndr = 50
@@ -59,8 +61,15 @@ def _run(self):
         return calc
 
 
+class DFTPWOutput(OutputModel):
+    pass
+
+
 class DFTPWWorkflow(DFTWorkflow):
 
+    output_model = DFTPWOutput  # type: ignore
+    outputs: DFTPWOutput
+
     def _run(self):
 
         # Create the calculator