add variables as class parameters for VHistStack

itten/contrasts.py

@@ -14,11 +14,40 @@ from copy import deepcopy
 # andere ownership Probleme könne angeblich mit out= gelöst werden
 # "Use __new__ when you need to control the creation of a new instance.
 # Use __init__ when you need to control initialization of a new instance."
-class Contrast(np.ndarray):
-    """Core class for a color contrast in a movie
-
-       subclasses a numpy array"""
-    def __new__(cls, frames, input_array=None):
+class View(np.ndarray):
+    """Core class for the representation of colour contrasts in Movies
+       
+       View is the basis class for specific ways to represent colour contrasts.
+       It does hold the definitions of contrasts itself. Objects of class View
+       subclass the numpy array class and hence inherit numpy methods. However,
+       it is not recommended to use functions which manipulate the array in
+       terms of structure. In this case some of the additional functions which
+       are implemented by this class and its subclasses might not lead to
+       reasonable results.
+
+       Attributes:
+       TODO Docstring komplettieren und Verfahren überprüfen
+       """
+    def __new__(cls, frames, input_array=None, ctrst='lightDark',
+                frm_stp=10, savefig=False):
+        """instantiates the view class
+
+           instantiation complies with the recommendation for subclassing
+           numpy.ndarray
+
+           Parameters
+           ----------
+           frames : itten.movie.Frames
+           input_array : itten.contrasts.View  # TODO wie schaffte np lower case object
+           contrast : String  # Modifizieren Channel Integer to String
+           frame_step : Int
+           savefig : Boolean
+
+           Returns
+           -------
+           Object : View
+               Empty numpy.ndarray of type View
+        """
         obj = input_array
         if type(obj) == np.ndarray:
             obj = np.asarray(input_array, dtype=np.uint8).view(cls).copy()
@@ -26,19 +55,19 @@ class Contrast(np.ndarray):
             input_array = np.zeros((0), dtype=np.uint8)
             obj = np.asarray(input_array).view(cls).copy()
         obj._frames = frames
-        obj._channel = 2
-        obj._frm_step = 50
-        obj._save = False
+        obj._contrast = ctrst
+        obj._frame_step = frm_stp
+        obj._savefig = savefig
         return obj
 
     def __array_finalize__(self, obj):
         if obj is None: return
         self._frames = getattr(obj, '_frames', None)
-        self._channel = getattr(obj, '_channel', None)
-        self._frm_step = getattr(obj, '_frame_step', None)
+        self._contrast = getattr(obj, '_contrast', None)
+        self._frame_step = getattr(obj, '_frame_step', None)
         self._bins = getattr(obj, '_bins', None)
         self._threshold = getattr(obj, '_threshold', None)
-        self._save = getattr(obj, '_save', None)
+        self._savefig = getattr(obj, '_savefig', None)
 
     def __array_wrap__(self, out_arr, context=None):
         return np.ndarray.__array_wrap__(self, out_arr, context)
@@ -46,16 +75,39 @@ class Contrast(np.ndarray):
 
 # subclassing subclass of numpy http://stackoverflow.com/questions/7342637/how-to-subclass-a-subclass-of-numpy-ndarray
 # TODO es gibt noch das Problem, dass numpy nach mehreren Berechnungen von drive eine max recursion Warnung ausgiebt, warum? Brauche ich __del__
-class VHistStack(Contrast):
-    def __new__(cls, frames, input_array=None):
-        obj = Contrast.__new__(cls, frames, input_array)
-        obj._bins = 16
-        obj._threshold = 60000
+class VHistStack(View):
+    def __new__(cls, frames, input_array=None, ctrst='lightDark',
+                frm_stp=10, bins=16, thrsh=60000, savefig=False):
+        """Represents a movie contrast in terms of stacked histograms
+
+           For each defined frame a histogram is calculated and each bin that
+           exceeds threshold is considered in the output array
+
+           Parameters
+           ----------
+           bins : Int
+               Number of bins for the calculation of the histogram
+           thrsh : Int
+               Threshhold defining the number of pixels a bin needs to contain
+               to be considered in the result
+
+           Returns
+           -------
+           Object : VHistStack
+               VHistStack is a 2-dimensional numpy array which contains
+               the frame number, the bin number and a quantifier which
+               represents the relative weight of the bin in the frame
+        """
+
+        obj = View.__new__(cls, frames, input_array=input_array, ctrst=ctrst,
+                           frm_stp=frm_stp, savefig=savefig)
+        obj._bins = bins
+        obj._threshold = thrsh
         return obj
 
     def __array_finalize__(self, obj):
         if obj is None: return
-        Contrast.__array_finalize__(self, obj)
+        View.__array_finalize__(self, obj)
         self._bins = getattr(obj, '_bins', None)
         self._threshold = getattr(obj, '_threshold', None)
 
@@ -64,12 +116,12 @@ class VHistStack(Contrast):
     def derive(self):
         contrast_points = []
         # pwd list sollte in Frames sein und hier nur durchlaufen werden
-        for frm_nr in range(self._frames.start, self._frames.end, self._frm_step):
+        for frm_nr in range(self._frames.start, self._frames.end, self._frame_step):
             pwd = self._frames.folder + self._frames.prefix + str(frm_nr) + '.png'
 
             img = cv2.imread(pwd)
 
-            if self._channel == 2:
+            if self._contrast == 2:
                 _img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
                 luminances = luminance(_img)
                 hist_value, _ = np.histogram(luminances, bins=self._bins, range=(0, 255))
@@ -77,7 +129,7 @@ class VHistStack(Contrast):
             else:
 
                 img_hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV_FULL)
-                hist_value = cv2.calcHist([img_hsv], [self._channel], None, [16], [0, 256])
+                hist_value = cv2.calcHist([img_hsv], [self._contrast], None, [16], [0, 256])
 
             for bin_index, point in enumerate(hist_value):
                 if point > self._threshold:

testing/bootstrap.py

@@ -2,4 +2,4 @@ from itten.movie import Movie
 from itten.contrasts import VHistStack
 
 movie = Movie(prefix='rec_', folder='../DHd-2017/Data/Frames/Rec/')
-cont = VHistStack(movie._frames)
+cont = VHistStack(movie._frames, ctrst=2)