Oops, no that was wrong. I forgot to cross-check against OpenEmulator <o>

This commit is contained in:
kris 2021-11-03 12:40:22 +00:00
parent bf76271d75
commit b7174778e6
2 changed files with 924 additions and 921 deletions

File diff suppressed because it is too large Load Diff

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@ -80,54 +80,57 @@ class DHGRScreen:
def _read(self, line, pos):
if pos < 0:
return 0
return 1 if line[pos] else 0
def bitmap_to_image_ntsc(self, bitmap: np.ndarray) -> np.ndarray:
y_width = 12
i_width = 24
q_width = 24
u_width = 24
v_width = 24
contrast = 1
saturation = 1
# DHGR has a timing shift of 1/4 phase, i.e x=0 is actually 1/4 phase.
# XXX should use (x + 1) % 4 ?
hue = math.pi / 2
# TODO: This is necessary to match OpenEmulator. I think it is because
# they introduce an extra (unexplained) factor of 2 when applying the
# Chebyshev/Lanczos filtering to the u and v components.
saturation = 2
# TODO: this phase shift is necessary to match OpenEmulator. I'm not
# sure where it comes from - e.g. it doesn't match the phaseInfo
# calculation for the signal phase at the start of the visible region.
hue = 0.2 * (2 * np.pi)
# Apply effect of saturation
yiq_to_rgb = np.array(
yuv_to_rgb = np.array(
((1, 0, 0), (0, saturation, 0), (0, 0, saturation)), dtype=np.float)
# Apply hue phase rotation
yiq_to_rgb = np.matmul(np.array(
yuv_to_rgb = np.matmul(np.array(
((1, 0, 0), (0, np.cos(hue), np.sin(hue)), (0, -np.sin(hue),
np.cos(hue)))),
yiq_to_rgb)
# Y'IQ to R'G'B' conversion
yiq_to_rgb = np.matmul(np.array(
((1, 0.956, 0.621), (1, -0.272, -.647), (1, -1.107, 1.704))),
yiq_to_rgb)
yuv_to_rgb)
# Y'UV to R'G'B' conversion
yuv_to_rgb = np.matmul(np.array(
((1, 0, 1.139883), (1, -0.394642, -.5806227), (1, 2.032062, 0))),
yuv_to_rgb)
# Apply effect of contrast
yiq_to_rgb *= contrast
yuv_to_rgb *= contrast
out_rgb = np.empty((bitmap.shape[0], bitmap.shape[1] * 3, 3),
dtype=np.uint8)
for y in range(bitmap.shape[0]):
ysum = 0
isum = 0
qsum = 0
usum = 0
vsum = 0
line = np.repeat(bitmap[y], 3)
for x in range(bitmap.shape[1] * 3):
ysum += self._read(line, x) - self._read(line, x - y_width)
isum += self._read(line, x) * self._sin(x) - self._read(
line, x - i_width) * self._sin((x - i_width))
qsum += self._read(line, x) * self._cos(x) - self._read(
line, x - q_width) * self._cos((x - q_width))
usum += self._read(line, x) * self._sin(x) - self._read(
line, x - u_width) * self._sin((x - u_width))
vsum += self._read(line, x) * self._cos(x) - self._read(
line, x - v_width) * self._cos((x - v_width))
rgb = np.matmul(
yiq_to_rgb, np.array(
(ysum / y_width, isum / i_width,
qsum / q_width)).reshape((3, 1))).reshape(3)
yuv_to_rgb, np.array(
(ysum / y_width, usum / u_width,
vsum / v_width)).reshape((3, 1))).reshape(3)
r = min(255, max(0, rgb[0] * 255))
g = min(255, max(0, rgb[1] * 255))
b = min(255, max(0, rgb[2] * 255))