data clean

GW/Scripts/dataToImage.py

@@ -7,15 +7,25 @@
 
 # I mount my cube1 home folder on remotes/cube1, for this to work you need to
 # provide your own path
-pathToFiles = "/home/ruben/remotes/cube1/pent_yambo/bands/bands.out/"
-data = np.loadtxt(pathToFiles + f"o.bands_interpolated")[:, 1:-3]
+pathToFiles = "/Users/bbaumeie/work/PentaceneDFT/GW/bands_DFT.out/"
+data_DFT = np.loadtxt(pathToFiles + f"o.bands_interpolated")[:, 1:-3]
 for i in range(1, 260):
  if i == 99: # yeah weird, but I think this one is corrupted or something, so I skip it
  continue
- data = np.concatenate([data,
+ data_DFT = np.concatenate([data_DFT,
  np.loadtxt(pathToFiles + f"o.bands_interpolated_{i:02d}")[:, 1:-3]
  ], axis=1)
 
+
+pathToFiles = "/Users/bbaumeie/work/PentaceneDFT/GW/bands_GW.out/"
+data_GW = np.loadtxt(pathToFiles + f"o.bands_interpolated")[:, 1:-3]
+for i in range(1, 260):
+ if i == 99: # yeah weird, but I think this one is corrupted or something, so I skip it
+ continue
+ data_GW = np.concatenate([data_GW,
+ np.loadtxt(pathToFiles + f"o.bands_interpolated_{i:02d}")[:, 1:-3]
+ ], axis=1) 
+
 def energiesToDensity(energy_range: np.ndarray,
  allEnergiesAtKPoint: np.ndarray,
  resolution: int = 100,
@@ -29,27 +39,30 @@ def energiesToDensity(energy_range: np.ndarray,
  return res
 
 energy_range = np.array([0, 12])
-energyShift = -6.6 # manual shift for the GW calculation
+# after Yambo, the interpolated bands are energy shifted such that 
+# EFermi is in the middle of the Gap.
+energyShift = -3.5 # manual shift for the DFT calculation = -Work function
+
 
 fig, ax = plt.subplots(1, 3, figsize=(21, 7.5))
 results = []
 for i in range(61):
  yval = energiesToDensity(energy_range,
- data[i,:] + energyShift,
+ data_DFT[i,:] + energyShift,
  sigma=0.2,
  resolution=100)
  results.append(yval)
 
 results = np.array(results).transpose()
 
-c = ax[1].imshow(-np.power(results,1),
+c = ax[0].imshow(-np.power(results,1),
  cmap="viridis",
  extent=[0, 1, energy_range[0], energy_range[1]],
  aspect="auto",
  interpolation="bilinear",
  origin="lower")
-ax[1].set_ylabel("Energy (eV)")
-ax[1].set_title("Yambo Bands")
+ax[0].set_ylabel("Energy (eV)")
+ax[0].set_title("DFT")
 
 # Experimental data, this comes from the RawData folder of the repo
 
@@ -99,67 +112,37 @@ def visualizeARRES(fig,
 # CREATE REFERENCE PLOT, 1 LAYER ARRES
 arres1 = arres1 / np.max(arres1)
 visualizeARRES(fig,
- ax[0],
+ ax[1],
  arres1,
  x_labels=['R', 'G', 'V'],
  label_loc=tick_loc,
  cmap='viridis',
  addBar=False)
-ax[0].set_ylim([energy_range[0], energy_range[1]])
-
-
-# And a reference dft calculation
-energyShift = -9.869 # The shift we determined from vaccuum levels
-def processDFT(orderedFileList: list,
- energy_range: np.ndarray,
- convFactor: float = 13.6,
- shift: float = 0.0,
- resolution=100,
- sigma=0.1) -> np.ndarray:
- """ processes the res_<nr> output files. """
- results = []
- for file in orderedFileList:
- data = np.loadtxt(file)
- energies = convFactor * data[:, 1] + shift
- yval = energiesToDensity(energy_range, energies, resolution, sigma)
- results.append(yval)
- return np.array(results).transpose()
-
-
-def visualizeNumExp(ax,
- basename: str,
- shift: float,
- addBar: bool = False,
- sigma: float = 0.05,
- Ef: float = None) -> None:
- """ Visualize the data from the numerical experiments as a imshow graphic.
-
- This function is not general, it assumes a K-path of 59 steps.
- """
- fileList = []
- for i in range(0, 59):
- fileList.append(f"../../NumericalExperiments/{basename}/res_{i}.dat")
- results = processDFT(fileList,
- energy_range,
- shift=energyShift + shift,
- resolution=400,
- sigma=sigma)
-
- c = ax.imshow(-np.power(results, 1),
- cmap="viridis",
- extent=[0, 1, energy_range[0], energy_range[1]],
- aspect="auto",
- interpolation="bilinear",
- origin="lower")
- ax.set_ylim(energy_range)
- ax.set_title(f"{basename}, shift {energyShift+shift}eV")
- ax.set_xticks(tick_loc)
- ax.set_xticklabels(['R', 'G', 'V'])
- if addBar:
- fig.colorbar(c, ax=ax)
- if not Ef is None:
- ax.axhline(Ef + energyShift + shift, color='red', lw='2')
+ax[1].set_ylim([energy_range[0], energy_range[1]])
+
+
+# And a reference GW calculation
+# after Yambo, the interpolated bands are energy shifted such that 
+# EFermi is in the middle of the Gap.
+energyShift = -3.87 # manual shift for the GW calculation = -Work function + shifted Efermi
+
+results = []
+for i in range(61):
+ yval = energiesToDensity(energy_range,
+ data_GW[i,:] + energyShift,
+ sigma=0.2,
+ resolution=100)
+ results.append(yval)
 
-visualizeNumExp(ax[2], "pent_bulk", 0.0, addBar=False, sigma=0.2)
+results = np.array(results).transpose()
+
+c = ax[2].imshow(-np.power(results,1),
+ cmap="viridis",
+ extent=[0, 1, energy_range[0], energy_range[1]],
+ aspect="auto",
+ interpolation="bilinear",
+ origin="lower")
+ax[2].set_ylabel("Energy (eV)")
+ax[2].set_title("GW")
 
 # %%