CI: Enable flake8 for the scripts/ directory

.github/workflows/pythonapp.yml

@@ -201,7 +201,7 @@ jobs:
         run: pip list
 
       - name: Run flake8
-        run: flake8 nanoqm test setup.py
+        run: flake8 nanoqm test setup.py scripts
 
       - name: Run pydocstyle
         run: pydocstyle nanoqm

scripts/convert_legacy_hdf5.py

@@ -53,8 +53,10 @@ def copy_orbitals(self) -> None:
         points = [k for k in self.source[self.project].keys() if k.startswith("point_")]
         keys = {"coefficients", "eigenvalues", "energy"}
         # "project/point_x/cp2k/mo/<coefficients,eigenvalues,energy>"
-        old_names = chain(*[[f"{self.project}/{point}/cp2k/mo/{k}" for point in points] for k in keys])
-        new_names = chain(*[[f"{k}/{point}" for point in points] for k in keys])
+        old_names = chain.from_iterable(
+            [f"{self.project}/{point}/cp2k/mo/{k}" for point in points] for k in keys
+        )
+        new_names = chain.from_iterable([f"{k}/{point}" for point in points] for k in keys)
         self.copy_node_values(old_names, new_names)
 
     def copy_couplings(self) -> None:

scripts/hamiltonians/plot_mos_energies.py

@@ -58,9 +58,6 @@ def read_cmd_line(parser: argparse.ArgumentParser) -> tuple[str, str, int, int,
     Parse Command line options.
     """
     args = parser.parse_args()
-
-    attributes = ['p', 'ts', 'ihomo', 'nhomos', 'nlumos']
-
     return (args.p, args.ts, args.ihomo, args.nhomos, args.nlumos)
 
 

scripts/pyxaid/iconds_excess_energy.py

@@ -1,8 +1,9 @@
 #! /usr/bin/env python
 
 """
-This program finds the indexes of the states for electron and hole cooling calculations (ONLY!)
-extrapolated at a desired initial condition. It reads the me_energies0 file from pyxaid [at initial condition t=0].
+This program finds the indexes of the states for electron and hole cooling calculations (ONLY!) \
+extrapolated at a desired initial condition. It reads the me_energies0 file from \
+pyxaid [at initial condition t=0].
 
 Example:
 

scripts/pyxaid/plot_cooling.py

@@ -1,5 +1,6 @@
 #!/usr/bin/env python
-"""This program plots the average electronic energy during a NAMD simulation averaged over several initial conditions.
+"""This program plots the average electronic energy during a NAMD simulation \
+averaged over several initial conditions.
 
 It plots both the SH and SE population based energies.
 
@@ -46,7 +47,11 @@ def plot_stuff(
     plt.xlabel('Time (fs)')
     plt.ylabel('Energy (eV)')
     for iconds in range(nconds):
-        plt.imshow(y_grid[iconds, :, :].T, aspect='auto', extent=(0, len(ts)*dt, np.min(x_grid), np.max(x_grid)), origin='lower', interpolation='bicubic', cmap='hot')
+        plt.imshow(
+            y_grid[iconds, :, :].T, aspect='auto',
+            extent=(0, len(ts)*dt, np.min(x_grid), np.max(x_grid)),
+            origin='lower', interpolation='bicubic', cmap='hot',
+        )
     plt.plot(ts * dt, w_en, 'w')
     interactive(True)
     plt.show()
@@ -55,7 +60,11 @@ def plot_stuff(
     plt.xlabel('Time (fs)')
     plt.ylabel('Excess Energy (eV)')
     for iconds in range(nconds):
-        plt.imshow(y_grid_scaled[iconds, :, :].T, aspect='auto', extent=(0, len(ts)*dt, np.min(x_grid_scaled), np.max(x_grid_scaled)), origin='lower', interpolation='bicubic', cmap='hot')
+        plt.imshow(
+            y_grid_scaled[iconds, :, :].T, aspect='auto',
+            extent=(0, len(ts)*dt, np.min(x_grid_scaled), np.max(x_grid_scaled)),
+            origin='lower', interpolation='bicubic', cmap='hot',
+        )
     plt.plot(ts * dt, w_en_scaled, 'w')
     interactive(True)
     plt.show()
@@ -64,7 +73,10 @@ def plot_stuff(
     plt.xlabel('Time (fs)')
     plt.ylabel('State Number')
     for iconds in range(nconds):
-        plt.imshow(outs[:, :, iconds].T, aspect='auto', origin='lower', extent = ( 0, len(ts) * dt, 0, outs.shape[1]), interpolation='bicubic', cmap='hot')
+        plt.imshow(
+            outs[:, :, iconds].T, aspect='auto', origin='lower',
+            extent=(0, len(ts) * dt, 0, outs.shape[1]), interpolation='bicubic', cmap='hot'
+        )
     interactive(True)
     plt.show()
 
@@ -94,7 +106,11 @@ def plot_stuff(
     plt.xlabel('Freqencies cm-1')
     sd_int = sd[:, 0, :int(sd.shape[2]/2)]
     sd_freq = sd[0, 1, :int(sd.shape[2]/2)]
-    plt.imshow(sd_int, aspect='auto', origin='lower', extent = (np.min(sd_freq), np.max(sd_freq), 0, sd_int.shape[0] ), interpolation='bicubic', cmap='hot')
+    plt.imshow(
+        sd_int, aspect='auto', origin='lower',
+        extent=(np.min(sd_freq), np.max(sd_freq), 0, sd_int.shape[0]),
+        interpolation='bicubic', cmap='hot',
+    )
     interactive(False)
     plt.show()
 
@@ -120,12 +136,16 @@ def main(path_output: str, nstates: int, nconds: int, dt: float, sigma: float) -
     energies_scaled = np.stack([
         energies[:, istate, :] - lowest_hl_gap for istate in range(nstates-1)
     ])
-    energies_scaled = energies_scaled.swapaxes(0,1) # Just reshape to have the energies shape (time, nstates, nconds)
+    # Just reshape to have the energies shape (time, nstates, nconds)
+    energies_scaled = energies_scaled.swapaxes(0, 1)
     x_grid_scaled = np.linspace(0, np.max(energies_scaled), 100)
     y_grid_scaled = np.stack([
         np.stack([
-            convolute(energies_scaled[time, :, iconds], outs[time, :, iconds], x_grid_scaled, sigma)
-            for time in range(energies_scaled.shape[0])
+            convolute(
+                energies_scaled[time, :, iconds],
+                outs[time, :, iconds],
+                x_grid_scaled, sigma,
+            ) for time in range(energies_scaled.shape[0])
         ]) for iconds in range(nconds)
     ])
     # This part is done
@@ -135,9 +155,9 @@ def main(path_output: str, nstates: int, nconds: int, dt: float, sigma: float) -
     el_ene_outs = np.sum(eav_outs, axis=1)
     # Scale them to the lowest excitation energy
     ene_outs_ref0 = el_ene_outs - lowest_hl_gap
-    #Average over initial conditions
+    # Average over initial conditions
     ene_outs_ref0 = np.average(ene_outs_ref0, axis=1)
-    el_ene_av = np.average(el_ene_outs, axis = 1)
+    el_ene_av = np.average(el_ene_outs, axis=1)
     ##################################
     # Compute autocorrelation function for consecutive pair of states
     d_en = np.stack(
@@ -150,7 +170,10 @@ def main(path_output: str, nstates: int, nconds: int, dt: float, sigma: float) -
     #################################
     # Call plotting function
     ts = np.arange(energies.shape[0])
-    plot_stuff(x_grid, y_grid, x_grid_scaled, y_grid_scaled, sd, el_ene_av, ene_outs_ref0, nconds, outs, energies, ts, dt)
+    plot_stuff(
+        x_grid, y_grid, x_grid_scaled, y_grid_scaled, sd, el_ene_av,
+        ene_outs_ref0, nconds, outs, energies, ts, dt,
+    )
 
 
 def read_cmd_line(parser: argparse.ArgumentParser) -> tuple[str, int, int, float, float]:

scripts/pyxaid/plot_spectra_pyxaid.py

@@ -147,7 +147,7 @@ def main(path_output: str, s1: int, s2: int, dt: float, wsd: int, wdeph: int) ->
     # Take the transpose to have the correct shape for spectral_density
     acf = np.stack([autocorrelate(en_states[i, :]) for i in range(en_states.shape[0])]).T
     # Compute the spectral density for each column using the normalized acf
-    sd = np.stack([spectral_density(acf[:, 1, i], dt)  for i in range(en_states.shape[0])])
+    sd = np.stack([spectral_density(acf[:, 1, i], dt) for i in range(en_states.shape[0])])
     # Compute the dephasing time for the uncorrelated acf between two states
     deph, rate = dephasing(acf[:, 0, 2], dt)
     # Plot stuff

scripts/qmflows/convolution.py

@@ -1,5 +1,6 @@
 #! /usr/bin/env python
-""" This script convolutes the calculated oscillator strengts for different snapshots in a MD trajectory and plot the average spectrum.
+""" This script convolutes the calculated oscillator strengts for different snapshots \
+in a MD trajectory and plot the average spectrum.
 
 Usage:
 convolution.py -sigma 0.05 -n 2 -nm True -write True
@@ -94,7 +95,8 @@ def read_cmd_line(parser) -> tuple[float, int, bool, bool]:
 # ============<>===============
 if __name__ == "__main__":
 
-    msg = """convolution.py -sigma <sigma parameter of the gaussian functions> -n <plot only the spectrum of structure n>
+    msg = """convolution.py -sigma <sigma parameter of the gaussian functions> \
+    -n <plot only the spectrum of structure n> \
     -nm <plot in nm> -write <write the coordinates from the convolution>"""
 
     parser = argparse.ArgumentParser(description=msg)

scripts/qmflows/coordination_ldos.py

@@ -101,7 +101,13 @@ def create_ldos_lists(coord: NestedDict) -> Settings:
     return s
 
 
-def compute_ldos(mol: Molecule, coord: NestedDict, name: str, workdir: str, path_results: str) -> None:
+def compute_ldos(
+    mol: Molecule,
+    coord: NestedDict,
+    name: str,
+    workdir: str,
+    path_results: str,
+) -> None:
     """Compute the DOS projected on subsets of atoms given through lists.
 
     These lists are divided by atom type and coordination number.

scripts/qmflows/dos_cp2k.py

@@ -1,5 +1,6 @@
 #! /usr/bin/env python
-"""This programs performs a density of states (DOS) calculation  with cp2k using generic settings, i.e. DFT/PBE
+"""This programs performs a density of states (DOS) calculation  with cp2k \
+using generic settings, i.e. DFT/PBE
 
 Note that is mandatory to define a cell_parameter, and a xyz structure.
 If you have a restart file, a basis set and you can also define it