minor changes

setup.py

@@ -5,7 +5,7 @@
 
 setup(
     name="temmeta",
-    version="0.0.4",
+    version="0.0.6",
     description=("TEMMETA is a library for transmission electron microscopy "
                  "(TEM) (meta)data manipulation"),
     url='https://github.com/din14970/TEMMETA',
@@ -27,12 +27,9 @@
         'openpyxl',
         'pandas',
         'scipy',
-        'jupyter',
         'hyperspy',
         'matplotlib_scalebar',
         'tqdm',
         'Pillow',
-        'opencv-python',
-        'PyQt5'
     ],
 )

temmeta/algebrautils.py

@@ -19,3 +19,14 @@ def distance(x1, y1, x2, y2):
     """Get the euclidian distance between two points"""
     le = np.sqrt((x2-x1)**2+(y2-y1)**2)
     return le
+
+
+def get_center_and_radius(x1, y1, x2, y2, x3, y3):
+    """Get the coordinates of the center and radius of
+    a circle defined by 3 points p_i=(x_i, y_i)"""
+    cx = (((x1**2-x3**2+y1**2-y3**2)*(y2-y1) -
+          (x1**2-x2**2+y1**2-y2**2)*(y3-y1)) /
+          (2*((x2-x1)*(y3-y1)-(x3-x1)*(y2-y1))))
+    cy = (-(x1**2-x2**2+y1**2-y2**2)-2*(x2-x1)*cx)/(2*(y2-y1))
+    r = ((x1-cx)**2+(y1-cy)**2)**0.5
+    return (cx, cy), r

temmeta/data_io.py

@@ -23,15 +23,15 @@
 from PIL import Image
 
 # My own modules
-from . import plottingtools as pl
-from . import image_filters as imf
-from ._decorators import timeit
-from .guitools import file_dialog as fdo
-from . import processing as proc
-from . import metadata as mda
-from . import jsontools as jt
-from . import algebrautils as algutil
-from .roi import line
+from temmeta import plottingtools as pl
+from temmeta import image_filters as imf
+from temmeta._decorators import timeit
+from temmeta.guitools import file_dialog as fdo
+from temmeta import processing as proc
+from temmeta import metadata as mda
+from temmeta import jsontools as jt
+from temmeta import algebrautils as algutil
+from temmeta.roi import line
 
 import concurrent.futures as cf
 from multiprocessing import Pool, cpu_count
@@ -3188,13 +3188,11 @@ def get_frame(self, frame_index):
                                 process)
         return nimg
 
+    @property
     def average(self):
         """Average the frames, return GeneralImage object"""
         # Sum becomes a uint64 image
-        dt = self.data.dtype
-        data = self.data.sum(axis=0)
-        # Rescale to turn it back into the same datatype as before
-        data = imf.normalize_convert(data, dtype=dt)
+        data = self.data.mean(axis=0)
         process = "Averaged all frames in stack"
         nimg = create_new_image(data, self.pixelsize, self.pixelunit, self,
                                 process)