From d442baf1f10970219afbb3307e7a377e8d34116c Mon Sep 17 00:00:00 2001
From: kris <kris.kennaway@gmail.com>
Date: Tue, 2 Nov 2021 12:30:43 +0000
Subject: [PATCH] Tidy a bit

---
 ntsc_colours.py | 20 +++++++++++---------
 palette_ntsc.py |  1 +
 2 files changed, 12 insertions(+), 9 deletions(-)

diff --git a/ntsc_colours.py b/ntsc_colours.py
index b2682a8..b926766 100644
--- a/ntsc_colours.py
+++ b/ntsc_colours.py
@@ -1,6 +1,5 @@
 """Precomputes all possible colours available via NTSC emulation."""
 
-import colour
 import numpy as np
 from PIL import Image
 import screen
@@ -14,6 +13,7 @@ def main():
 
     print("import numpy as np")
     print()
+    print("# Indexed by (trailing 8-bit dot pattern, x % 4)")
     print("SRGB = {")
     # For each sequence of 8 pixels, compute the RGB colour of the right-most
     # pixel, using NTSC emulation.
@@ -21,28 +21,30 @@ def main():
     # position with respect to NTSC phase.
     # TODO: should be 3?  Do I have a compensating off-by-one in bitmap_to_ntsc?
     ntsc_shift = 2
-    for j in range(ntsc_shift, ntsc_shift+4):
-        bitmap = np.zeros((1, 11+ntsc_shift), dtype=np.bool)
+    for j in range(ntsc_shift, ntsc_shift + 4):
+        bitmap = np.zeros((1, 11 + ntsc_shift), dtype=np.bool)
         for bits in range(256):
             bits8 = np.empty((8,), dtype=np.bool)
             for i in range(8):
                 bits8[i] = bits & (1 << i)
 
-            bitmap[0, j:j+8] = bits8
+            bitmap[0, j:j + 8] = bits8
 
+            # bitmap_to_ntsc produces 3 output pixels for each DHGR input
             ntsc = s.bitmap_to_ntsc(bitmap)
-            last_colour = ntsc[0, 3*(j+8)-1, :]
-            colours[(bits, j-ntsc_shift)] = last_colour
+            last_colour = ntsc[0, 3 * (j + 8) - 1, :]
+            colours[(bits, j - ntsc_shift)] = last_colour
             unique.add(tuple(last_colour))
             print("  (%d, %d): np.array((%d, %d, %d))," % (
-                bits, j-ntsc_shift, last_colour[0], last_colour[1], last_colour[2]))
+                bits, j - ntsc_shift, last_colour[0], last_colour[1],
+                last_colour[2]))
     print("}")
     print("# %d unique colours" % len(unique))
 
     # Show spectrum of available colours sorted by HSV hue value
-    im = np.zeros((128*4, 256 * 16, 3), dtype=np.uint8)
+    im = np.zeros((128 * 4, 256 * 16, 3), dtype=np.uint8)
     for x, j in colours:
-        im[128*j:128*(j+1), x * 16: (x + 1) * 16, :] = colours[x,j]
+        im[128 * j:128 * (j + 1), x * 16: (x + 1) * 16, :] = colours[x, j]
 
     Image.fromarray(im).show()
 
diff --git a/palette_ntsc.py b/palette_ntsc.py
index 1c65e84..2934c3a 100644
--- a/palette_ntsc.py
+++ b/palette_ntsc.py
@@ -1,5 +1,6 @@
 import numpy as np
 
+# Indexed by (trailing 8-bit dot pattern, x % 4)
 SRGB = {
   (0, 0): np.array((0, 0, 0)),
   (1, 0): np.array((0, 37, 0)),