smash the ccm step together?

Inclined to think the two-pass may be better, though

cimbar/cimbar.py

@@ -260,10 +260,12 @@ def update(c, r, g, b):
     else:
         pos = [(67, 0), (0, 67), (conf.TOTAL_SIZE-79, 0), (0, conf.TOTAL_SIZE-79)]
 
+    colors = []
     for x, y in pos:
         iblock = img.crop((x, y, x + 4, y + 4))
-        r, g, b = avg_color(iblock, False)
-        update(cc, *avg_color(iblock, False))
+        ac = avg_color(iblock, False)
+        colors.append(ac)
+        update(cc, *ac)
 
     print(f'tint is {cc}')
     return cc['r'], cc['g'], cc['b']
@@ -307,8 +309,9 @@ def _decode_iter(ct, img, color_img, state_info={}):
         #matrix_colour_correction_Finlayson2015
 
         if cc_setting in (3, 4, 5):
-            exp = numpy.array(possible_colors(ct.dark, BITS_PER_COLOR))
-            observed = numpy.array([v for k,v in sorted(color_lookups[0].items())])
+            exp = numpy.array(possible_colors(ct.dark, BITS_PER_COLOR) + [(255,255,255)])
+            white = state_info['white']
+            observed = numpy.array([v for k,v in sorted(color_lookups[0].items())] + [white])
             from colour.characterisation.correction import matrix_colour_correction_Cheung2004
             der = matrix_colour_correction_Cheung2004(observed, exp)
 
@@ -318,13 +321,14 @@ def _decode_iter(ct, img, color_img, state_info={}):
             else:  # cc_setting == 3,5
                 ct.ccm = der.dot(ct.ccm)
 
-        if splits:
+        if splits:  # 6,7
             from colour.characterisation.correction import matrix_colour_correction_Cheung2004
-            exp = numpy.array(possible_colors(ct.dark, BITS_PER_COLOR))
+            exp = numpy.array(possible_colors(ct.dark, BITS_PER_COLOR) + [(255,255,255)])
+            white = state_info['white']
             ccms = list()
             i = 0
             while i < splits:
-                observed = numpy.array([v for k,v in sorted(color_lookups[i].items())])
+                observed = numpy.array([v for k,v in sorted(color_lookups[i].items())] + [white])
                 der = matrix_colour_correction_Cheung2004(observed, exp)
                 ccms.append(der)
                 i += 1
@@ -369,22 +373,19 @@ def decode_iter(src_image, dark, should_preprocess, color_correct, deskew, auto_
     img = _preprocess_for_decode(color_img) if should_preprocess else color_img
 
     if color_correct:
-        from colormath.chromatic_adaptation import _get_adaptation_matrix
-        ct.ccm = white = _get_adaptation_matrix(numpy.array([*compute_tint(color_img, dark)]),
-                                        numpy.array([255, 255, 255]), 2, 'von_kries')
+        white = compute_tint(color_img, dark)
         if color_correct == 2:
+            from colormath.chromatic_adaptation import _get_adaptation_matrix
+            ct.ccm = _get_adaptation_matrix(numpy.array([*white]),
+                                            numpy.array([255, 255, 255]), 2, 'von_kries')
             for _ in _decode_iter(ct, img, color_img):
                 pass
             clusters = ClusterSituation(ct.color_metrics, 2**BITS_PER_COLOR)
             clusters.plot('/tmp/foo.png')
             clusters.index = {i: ct.best_color(*k) for i,k in enumerate(clusters.centers())}
             ct.color_clusters = clusters
-
-            '''observed = [c for _, c in ct.color_metrics]
-            exp = numpy.array(possible_colors(dark, BITS_PER_COLOR))
-            from colour.characterisation.correction import matrix_colour_correction_Cheung2004
-            der = matrix_colour_correction_Cheung2004(observed, exp)
-            ct.ccm = der.dot(white)'''
+        else:
+            state_info['white'] = white
 
     yield from _decode_iter(ct, img, color_img, state_info)