def anchors_noise_offsets(anchors, offsets, rows, cols, spacing, z_step, x_indices_str, y_indices_str, x_minscale, y_minscale, x_maxscale, y_maxscale):
from noise import pnoise3
from plat.interpolate import lerp
only_anchor = None
if len(anchors) == 1:
only_anchor = anchors[0]
dim = len(anchors[0])
x_offset = offset_from_string(x_indices_str, offsets, dim)
y_offset = offset_from_string(y_indices_str, offsets, dim)
num_row_anchors = (rows + spacing - 1) / spacing
num_col_anchors = (cols + spacing - 1) / spacing
newanchors = []
cur_anchor_index = 0
for j in range(num_row_anchors):
y_frac = float(j) / num_row_anchors
for i in range(num_col_anchors):
if only_anchor is None:
cur_anchor = anchors[cur_anchor_index]
cur_anchor_index += 1
else:
cur_anchor = only_anchor
x_frac = float(i) / num_col_anchors
n1 = 0.5 * (1.0 + pnoise3(x_frac, y_frac, z_step, octaves=4, repeatz=2))
n2 = 0.5 * (1.0 + pnoise3(100+x_frac, 100+y_frac, z_step, octaves=4, repeatz=2))
x_scale = lerp(n1, x_minscale, x_maxscale)
y_scale = lerp(n2, y_minscale, y_maxscale)
# print("{}, {} produced {} -> {}, {} = {}".format(i,j,n1,x_minscale, x_maxscale,x_scale))
newanchors.append(cur_anchor + x_scale * x_offset + y_scale * y_offset)
return np.array(newanchors)
def anchors_json_offsets(anchors, offsets, rows, cols, spacing, z_step,
x_indices_str, y_indices_str, x_minscale, y_minscale,
x_maxscale, y_maxscale, range_data):
only_anchor = None
if len(anchors) == 1:
only_anchor = anchors[0]
dim = len(anchors[0])
x_offset = offset_from_string(x_indices_str, offsets, dim)
y_offset = offset_from_string(y_indices_str, offsets, dim)
num_row_anchors = (rows + spacing - 1) / spacing
num_col_anchors = (cols + spacing - 1) / spacing
newanchors = []
cur_anchor_index = 0
for j in range(num_row_anchors):
y_frac = float(j) / num_row_anchors
for i in range(num_col_anchors):
if only_anchor is None:
cur_anchor = anchors[cur_anchor_index]
cur_anchor_index += 1
else:
cur_anchor = only_anchor
x_frac = float(i) / num_col_anchors
n1 = range_data[z_step][0]
n2 = range_data[z_step][1]
x_scale = lerp(n1, x_minscale, x_maxscale)
y_scale = lerp(n2, y_minscale, y_maxscale)
# print("{}, {} produced {} -> {}, {} = {}".format(i,j,n1,x_minscale, x_maxscale,x_scale))
newanchors.append(cur_anchor + x_scale * x_offset +
y_scale * y_offset)
return np.array(newanchors)
def cur_pos(self, is_s):
if is_s:
if self.s_cur_frame >= self.num_anim_frames:
return self.s_dest_x, self.s_dest_y
v = float(self.s_cur_frame) / self.num_anim_frames
x = lerp(v, self.s_x, self.s_dest_x)
y = lerp(v, self.s_y, self.s_dest_y)
return x, y
else:
if self.d_cur_frame >= self.num_anim_frames:
return self.d_dest_x, self.d_dest_y
v = float(self.d_cur_frame) / self.num_anim_frames
x = lerp(v, self.d_x, self.d_dest_x)
y = lerp(v, self.d_y, self.d_dest_y)
return x, y
def anchors_noise_offsets(anchors, offsets, rows, cols, spacing, z_step,
x_indices_str, y_indices_str, x_minscale, y_minscale,
x_maxscale, y_maxscale):
from noise import pnoise3
from plat.interpolate import lerp
only_anchor = None
if len(anchors) == 1:
only_anchor = anchors[0]
dim = len(anchors[0])
x_offset = offset_from_string(x_indices_str, offsets, dim)
y_offset = offset_from_string(y_indices_str, offsets, dim)
num_row_anchors = (rows + spacing - 1) / spacing
num_col_anchors = (cols + spacing - 1) / spacing
newanchors = []
cur_anchor_index = 0
for j in range(num_row_anchors):
y_frac = float(j) / num_row_anchors
for i in range(num_col_anchors):
if only_anchor is None:
cur_anchor = anchors[cur_anchor_index]
cur_anchor_index += 1
else:
cur_anchor = only_anchor
x_frac = float(i) / num_col_anchors
n1 = 0.5 * (1.0 +
pnoise3(x_frac, y_frac, z_step, octaves=4, repeatz=2))
n2 = 0.5 * (1.0 + pnoise3(
100 + x_frac, 100 + y_frac, z_step, octaves=4, repeatz=2))
x_scale = lerp(n1, x_minscale, x_maxscale)
y_scale = lerp(n2, y_minscale, y_maxscale)
# print("{}, {} produced {} -> {}, {} = {}".format(i,j,n1,x_minscale, x_maxscale,x_scale))
newanchors.append(cur_anchor + x_scale * x_offset +
y_scale * y_offset)
return np.array(newanchors)
def anchors_wave_offsets(anchors, offsets, rows, cols, spacing, radial_wave,
clip_wave, z_step, x_indices_str, x_minscale,
x_maxscale):
only_anchor = None
if len(anchors) == 1:
only_anchor = anchors[0]
dim = len(anchors[0])
x_offset = offset_from_string(x_indices_str, offsets, dim)
num_row_anchors = (rows + spacing - 1) / spacing
num_col_anchors = (cols + spacing - 1) / spacing
newanchors = []
cur_anchor_index = 0
center_pt = [(num_col_anchors - 1) / 2.0, (num_row_anchors - 1) / 2.0]
max_dist = distance_2d([0, 0], center_pt)
for j in range(num_row_anchors):
for i in range(num_col_anchors):
if only_anchor is None:
cur_anchor = anchors[cur_anchor_index]
cur_anchor_index += 1
else:
cur_anchor = only_anchor
cur_dist = distance_2d([i, j], center_pt)
if radial_wave:
x_frac = (max_dist - cur_dist) / max_dist
else:
x_frac = float(i) / num_col_anchors
wave_val = z_step + x_frac
n1 = compute_wave(wave_val, clip_wave)
x_scale = lerp(n1, x_minscale, x_maxscale)
# if wave_val < 0.0 or wave_val > 1.0:
# x_scale = x_minscale
# else:
# if wave_val < 0.5:
# n1 = wave_val * 2
# else:
# n1 = (1.0 - wave_val) * 2
# x_scale = lerp(n1, x_minscale, x_maxscale)
# print("{}, {} produced {} -> {}, {} = {}".format(i,j,n1,x_minscale, x_maxscale,x_scale))
newanchors.append(cur_anchor + x_scale * x_offset)
return np.array(newanchors)