move vline to sequenceplot superclass

itten/visuals.py

@@ -73,6 +73,25 @@ class SequencePlot(object):
 
         return (ax, axt)
 
+    # TODO Überführbar in Superclass?
+    # evtl. auch eher feature drer View Klasse
+    # TODO self._x sollte eine array sein
+    def _vlines(self, view, mark, mark_gt, mark_lt):
+
+        npx = np..array(self._x)
+        if mark_gt:
+            poss = npx[view > mark_gt]
+            for pos in poss:
+                self._ax.axvline(pos, color='#a6e22e', alpha=0.4, linewidth=3)
+        if mark_lt:
+            poss = npx[view < mark_lt]
+            for pos in poss:
+                self._ax.axvline(pos, color='#f92672', alpha=0.4, linewidth=3)
+        if mark:
+            for pos in mark:
+                print(self._ax)
+                self._ax.axvline(pos, color='#66d9ef', alpha=0.4, linewidth=3)
+
     def saveplt(self, title=False, fname='plot.png'):
         if title:
             self._ax.set_title(title, {'fontsize': 14}, y=1.18)
@@ -90,7 +109,7 @@ class MultivariatePlot(SequencePlot):
         self.fig = plt.figure()
         self._ax = plt.axes()
 
-    def plot(self, view):
+    def plot(self, view, mark_gt=False, mark_lt=False, mark=False):
         x = view[:, 0]
         y = view[:, 1]
         value = view[:, 2]
@@ -103,6 +122,9 @@ class MultivariatePlot(SequencePlot):
         # axt.scatter(x, y, c=y, cmap='Greys_r', s=thickness, linewidths=0) # DOC: vmin/vmax sorgt für die Verteilung der Fraben der Colorm
         # ax.scatter(x, y, c=y, cmap='hsv', s=thickness, linewidths=0)
 
+        if mark:
+            self._vlines(view, mark, False, False)
+
         self.fig.tight_layout()
         self.fig.set_size_inches(self.width, self.height)
 
@@ -124,21 +146,8 @@ class UnivariatePlot(SequencePlot):
         # contrast_points = savitzky_golay(np.array(contrast_points), 51, 7)
         self._axt.plot(self._x, view, label=view.feature)
 
-        # TODO Überführbar in Superclass?
-        # evtl. auch eher feature drer View Klasse
-        # TODO self._x sollte eine array sein
-        npx = np.array(self._x)
-        if mark_gt:
-            poss = npx[view > mark_gt]
-            for pos in poss:
-                self._ax.axvline(pos, color='#a6e22e', alpha=0.3, linewidth=3)
-        if mark_lt:
-            poss = npx[view < mark_lt]
-            for pos in poss:
-                self._ax.axvline(pos, color='#f92672', alpha=0.3, linewidth=3)
-        if mark:
-            for pos in mark:
-                self._ax.axvline(pos, color='#66d9ef', alpha=0.3, linewidth=3)
+        if any([mark, mark_gt, mark_lt]):
+            self._vlines(view, mark, mark_gt, mark_lt)
 
         self._axt.legend()
 

testing/bootstrap.py

 from itten.movie import Movie
 from itten.views import MultivariateSequence
+from itten.views import UnivariateSequence
 from itten.visuals import MultivariatePlot
+from itten.visuals import UnivariatePlot
 
 movie = Movie(prefix='wwz_', folder='../DHd-2017/Data/Frames/WWZ/')
 # movie._frames.start = 367
 # movie._frames.end = 1000
 cont = MultivariateSequence(movie._frames,)
-cont.populate(frm_stp=1, ctrst='saturation')
+# cont = UnivariateSequence(movie._frames,)
+cont.populate(frm_stp=3, ctrst='light_dark')
 viz = MultivariatePlot(cont)
 viz.plot(cont, mark=[243, 1885, 3430, 4237, 4543])
 # cont.seqper(frm_stp=5, ctrst='saturation', perc=50)