with the instruction on how to recover the corrected data

UntiltPlane.py

@@ -7,53 +7,53 @@
 
 class UntiltPlane(object):
     """Level the plane if the sample is tilted.
-    
+
     Left click on the image to select the points which will be used to create
     the offset plane. On right-click, this plane will be substracted from
     your image's original data, and the image will be redrawn with updated values.
     Attention: The resulting data will always have zero as its' minimal value.
     That is because after substracting the plane, we also substract the minimum
     of that result.
     Important Note: There is a strong assumption that the offset plane is linear.
-        
+
     Parameters:
     -----------
     data: 2D numpy.ndarray
-        Your input data. NaNs are fine. 
+        Your input data. NaNs are fine.
     a, b, c: floats
         The initial parameters of the flat offset plane.
         Defaults: `a = np.nanmin(data)`, `b = 0`, `c = 0`
     ftol: float
         What precision of the fit is satisfactory? Default is 1e-10
     **kwargs:
         Arguments passed on to matplotlib.figure
-    
+
     Output:
     ----------
     corrected_data: numpy.ndarray
         The updated ("untilted") values of your input array.
     plane_params: tuple(float, float, float)
         The tuple of fitted plane parameters (a, b, c). You can also recover them
         as `a`, `b` and `c`
-    
-    
-    
+
+
+
     Example:
     ---------
     ```
     # You just need to run something like:
     >>>my_untilter = UntiltPlane(data)
     # Then, if you want to recover the corrected data:
-    >>>corrected_data = my.untilter.corrected_data
+    >>>corrected_data = my_untilter.corrected_data
     # If you wish to reconstruct the offset plane:
     >>>a, b, c = my_untilter.plan_params
     >>>offset_plane = np.fromfunction(lambda y, x: a + b*x + c*y, data.shape)
     ```
     """
-    
+
     def __init__(self, data, a="min", b=0, c=0, ftol=1e-10, **kwargs):
-        
-        self.data = data        
+
+        self.data = data
         if a == "min":
             self.a = np.nanmin(self.data)
         else:
@@ -66,12 +66,12 @@ def __init__(self, data, a="min", b=0, c=0, ftol=1e-10, **kwargs):
         self.plane_data = []
         self.my_points = []
 
-        
+
         figsize = kwargs.pop("figsize", (12, 8))
         facecolor = kwargs.pop("facecolor", "oldlace")
         self.fig, self.aximg = plt.subplots(figsize=figsize, facecolor=facecolor,
                                             **kwargs)
-        
+
         self.img = self.aximg.imshow(self.data, cmap="cividis")
         self.aximg.tick_params(top=True, labeltop=True, bottom=False, labelbottom=False)
         self.aximg.set_title("Left-click to assign the points that will define\n"+
@@ -82,7 +82,7 @@ def __init__(self, data, a="min", b=0, c=0, ftol=1e-10, **kwargs):
 
     def flat_plane_z(self, y, x):
         return self.a + self.b*x + self.c*y
-    
+
     def optimize_flat_plane_z(self, independent_coords, a, b, c):
         x = independent_coords[:, 0]
         y = independent_coords[:, 1]
@@ -105,15 +105,15 @@ def onclick(self, event):
         elif event.button != 1:
             self.fig.canvas.mpl_disconnect(self.cid)
             self.detilt()
-                
+
     def detilt(self):
         """Remove the points, fit the (linear) plane, and update the image"""
-        
+
         # Remove all the points:
         for point in self.my_points:
             point.remove()
         self.my_points = []
-        
+
         clicked_data = np.array(self.plane_data)
         independent_coords = clicked_data[:, :2]
         measured_z = clicked_data[:, 2]
@@ -127,18 +127,18 @@ def detilt(self):
                                                            initial_guess,
                                                            method="lm",
                                                            ftol=self.ftol)
-        
-        
+
+
         self.a, self.b, self.c = self.plane_params
         base_plane = np.fromfunction(self.flat_plane_z, self.data.shape)
         self.corrected_data = self.data - base_plane
         # Correct the offset (not sure whether we should do this or not)
         self.corrected_data -= np.nanmin(self.corrected_data)
-        
+
         im_min, im_max = 0, np.nanmax(self.corrected_data)
         gs = gridspec.GridSpec(1,2)
         self.aximg.set_position(gs[0].get_position(self.fig))
-        self.aximg.set_subplotspec(gs[0]) 
+        self.aximg.set_subplotspec(gs[0])
         self.axcorr = self.fig.add_subplot(gs[1])
         self.axcorr.imshow(self.corrected_data, cmap="cividis")
         self.axcorr.tick_params(top=True, labeltop=True, bottom=False, labelbottom=False)

test.py

@@ -16,3 +16,8 @@
 raw = np.flipud(np.loadtxt(filename, delimiter=','))
 
 my_plane = UntiltPlane(raw)
+
+# %%
+######## Run the line below only afer you've finished the above ########
+########          (shift + enter to run cell by cell)           ########
+my_corrected_data = my_plane.corrected_data