Bug fix in fermisurface2d plot. skimage contour output was mesh index…

… points instead of kmesh grid. Needed an interpolation to map back to kmesh from the mesh index

pyprocar/core/fermisurface.py

@@ -176,6 +176,9 @@ def plot(self,mode:str, interpolation=500):
             xmin : xmax : interpolation * 1j, ymin : ymax : interpolation * 1j
         ]
 
+        unique_x = xnew[:,0]
+        unique_y = ynew[0,:]
+
         # interpolation
         n_spins = self.bands.shape[2]
         for i_spin in range(n_spins):
@@ -209,7 +212,6 @@ def plot(self,mode:str, interpolation=500):
             bnew = np.array(bnew)
 
             # Generates colors per band
-
             n_bands = bands.shape[0]
             cmap = cm.get_cmap(self.config['cmap']['value'])
             if i_spin == 1:
@@ -219,10 +221,20 @@ def plot(self,mode:str, interpolation=500):
             solid_color_surface = np.arange(n_bands) / n_bands + factor
             band_colors = np.array([cmap(norm(x)) for x in solid_color_surface[:]]).reshape(-1, 4)
             plots = []
+
             for i_band,band_energies in enumerate(bnew):
                 contours = measure.find_contours(band_energies, self.energy)
                 for i_contour,contour in enumerate(contours):
-                    points = np.array([contour[:, 0], contour[:, 1]]).T.reshape(-1, 1, 2)
+                    # measure.find contours returns a list of coordinates indcies of the mesh. 
+                    # However, due to the algorithm they take values that are in between mesh points. 
+                    # We need to interpolate the values to the original kmesh
+                    x_vals=contour[:,0]
+                    y_vals=contour[:,1]
+                    x_interp=np.interp(x_vals, np.arange(0,unique_x.shape[0]), unique_x)
+                    y_interp=np.interp(y_vals, np.arange(0,unique_y.shape[0]), unique_y)
+                    points=np.array([[x_interp,y_interp]])
+                    points=np.moveaxis(points, -1, 0)
+
                     segments = np.concatenate([points[:-1], points[1:]], axis=1)
                     if mode=='plain':
                         lc = LineCollection(segments, 
@@ -243,7 +255,7 @@ def plot(self,mode:str, interpolation=500):
                                 label=f'Band {band_labels[i_band]}'
                             lc.set_label(label)
                     if mode=='parametric':
-                        c = griddata((x, y), spd[i_band,:], (contour[:, 0], contour[:, 1]), method="nearest")
+                        c = griddata((x, y), spd[i_band,:], (x_interp, y_interp), method="cubic")
                         lc = LineCollection(segments, cmap=plt.get_cmap(self.config['cmap']['value']), norm=norm)
                         lc.set_array(c)
 
@@ -297,6 +309,7 @@ def spin_texture(self, sx, sy, sz,
         # selecting components of K-points
         x, y = self.kpoints[:, 0], self.kpoints[:, 1]
 
+
         if self.band_indices is None:
             bands = self.bands[:,self.useful_bands_by_spins[0],0].transpose()
             band_labels = np.unique(self.useful_bands_by_spins[0])
@@ -367,7 +380,7 @@ def spin_texture(self, sx, sy, sz,
                 if self.config['arrow_size']['value'] is not None:
                     # This is so the density scales the way you think. increasing number means increasing density. 
                     # The number in the numerator is so it scales reasonable with 0-20
-                    scale  = 10/self.config['arrow_size']['value']
+                    scale = 10/self.config['arrow_size']['value']
                     scale_units = "xy"
                     angles="xy"
                 else: