forked from protonphoton/LJ
256 lines
15 KiB
Python
256 lines
15 KiB
Python
import math
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# parameter for angles
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pps = 25000
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time_us_angle_zero = float(400) # it's just a random value, it must be tested (us = micro second)
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time_us_per_point = float(1000000 / pps) # 40 us for 25kpps (us = micro second)
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# parmeter for brightness
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max_lengh = 50 # in pixel, random value as well
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import sys
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def debug(*args, **kwargs):
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print(*args, file=sys.stderr, **kwargs)
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def different_position(p1, p2):
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return (int(p2[0]) != int(p1[0])) or (int(p2[1]) != int(p1[1]))
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def sub(p1, p2):
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return []
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def no_blanks_points(*points):
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for p in points:
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if p[2] == 0:
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return False
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return True
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def angle_exist(p1, p2, p3):
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return no_blanks_points(p1, p2, p3) and different_position(p1, p2) and different_position(p2, p3)
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def scalar_product(v1, v2):
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return v1[0] * v2[0] + v1[1] * v2[1]
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def length(v):
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return math.sqrt(scalar_product(v, v))
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def normalize(v):
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l = length(v)
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return [v[0] / l, v[1] / l]
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def sub(p1, p2):
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return [p1[0] - p2[0], p1[1] - p2[1]]
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def add(p1, p2):
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return [p1[0] + p2[0], p1[1] + p2[1]]
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def mult_by_scalar(p, scalar):
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return [p[0] * scalar, p[1] * scalar]
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# 90 deg rotate to the right of v1 when y axes is directed to the floor
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def rot_90_right(v):
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return [-v[1], v[0]]
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def get_angle_degree(p1, p2, p3):
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v1 = sub(p2, p1)
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v2 = sub(p2, p3)
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d1x = normalize(v1)
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d1y = rot_90_right(d1x)
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x = scalar_product(d1x, v2)
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y = scalar_product(d1y, v2)
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angle = 180 - abs(math.degrees(math.atan2(y, x)))
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return angle
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def point_to_add(angle):
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return int(float((1 - (angle / 180.0)) * time_us_angle_zero) / time_us_per_point)
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def adjusts_angles(pl):
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if len(pl) < 3:
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return pl
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new_pl = []
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previous = pl[0]
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middle = pl[1]
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new_pl.append(pl[0])
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for ensuing in pl[2:]:
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if angle_exist(previous, middle, ensuing):
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angle = get_angle_degree(previous, middle, ensuing)
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nb_point_added = point_to_add(angle)
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for i in range(nb_point_added):
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new_pl.append(middle)
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new_pl.append(middle)
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previous = middle
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middle = ensuing
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new_pl.append(pl[-1])
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return new_pl
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def adjusts_brightness(pl):
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new_pl = []
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if len(pl) < 1:
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return pl
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new_pl.append(pl[0])
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prev = pl[0]
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for current in pl[1:]:
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new_pl.append(prev)
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if no_blanks_points(prev, current):
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diff = sub(current, prev)
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l = length(diff)
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if l > max_lengh:
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nb_add = math.ceil(l / max_lengh)
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print("\n\n===")
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print("from:", prev)
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print("to:", current)
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print("diff:", diff)
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for i in range(nb_add):
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factor = float(i) / float(nb_add)
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print("factor:", factor)
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new_point = add(prev, mult_by_scalar(diff, factor)) + [prev[2]]
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print(new_point)
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new_pl.append(new_point)
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#else:
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# new_pl.append()
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prev = current
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new_pl.append(pl[-1])
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return new_pl
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def adjust_ending_point(pl):
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# si il y a trop de point noir, on en enleve
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# si il y a un que 1 point noir:
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# on en met un autre
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return pl
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def optimizer(pl):
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initial_length = len(pl)
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pl = adjusts_angles(pl)
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added_by_angle = len(pl) - initial_length
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pl = adjusts_brightness(pl)
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added_by_brightness = len(pl) - (added_by_angle + initial_length)
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#points_added = added_by_angle + added_by_brightness
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#print("\n\ninital_lenght:", initial_length, "\tadded by angles:", added_by_angle, "\tadded by brightness:", added_by_brightness )
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return pl
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if __name__ == '__main__':
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# The 3 pl_somthing are used to test and debug the algorythm without
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# using all the programe archithecture. The goal is to be able to execute
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# the code snippet without errors being caught by LJ.
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pl_component = [(355, 262, 0), (355, 262, 16777215), (300, 130, 16777215), (432, 75, 16777215), (487, 207, 16777215), (355, 262, 16777215), (355, 262, 0), (0, 435, 0), (0, 480, 16777215), (0, 300, 16777215), (135, 300, 16777215), (135, 570, 16777215), (135, 570, 16777215), (135, 300, 16777215), (135, 300, 0), (135, 300, 16777215), (225, 480, 16777215), (225, 480, 0), (510, 450, 0), (510, 450, 16777215), (600, 420, 16777215), (600, 300, 16777215), (720, 300, 16777215), (720, 420, 16777215), (810, 450, 16777215), (810, 450, 0)]
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pl_brightness = [[50, 50, 0], [50, 50, 16777215], [50, 750, 16777215], [750, 750, 16777215], [750, 50, 16777215], [50, 50, 16777215], [50, 50, 0], [100, 100, 0], [100, 100, 16777215], [100, 700, 16777215], [700, 700, 16777215], [700, 100, 16777215], [100, 100, 16777215], [100, 100, 0], [150, 150, 0], [150, 150, 16777215], [150, 650, 16777215], [650, 650, 16777215], [650, 150, 16777215], [150, 150, 16777215], [150, 150, 0], [200, 200, 0], [200, 200, 16777215], [200, 600, 16777215], [600, 600, 16777215], [600, 200, 16777215], [200, 200, 16777215], [200, 200, 0], [250, 250, 0], [250, 250, 16777215], [250, 550, 16777215], [550, 550, 16777215], [550, 250, 16777215], [250, 250, 16777215], [250, 250, 0], [300, 300, 0], [300, 300, 16777215], [300, 500, 16777215], [500, 500, 16777215], [500, 300, 16777215], [300, 300, 16777215], [300, 300, 0], [350, 350, 0], [350, 350, 16777215], [350, 450, 16777215], [450, 450, 16777215], [450, 350, 16777215], [350, 350, 16777215], [350, 350, 0]]
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pl_angle = [[10.0, 83.0, 0], [10.0, 83.0, 16777215], [85, 83, 16777215], [160.0, 83.0, 16777215], [160.0, 83.0, 0], [160.0, 87.0, 0], [160.0, 87.0, 16777215], [85, 87, 16777215], [10.0, 87.0, 16777215], [10.0, 87.0, 0], [170.2853976431191, 76.46331929392564, 0], [170.2853976431191, 76.46331929392564, 16777215], [245, 83, 16777215], [319.7146023568809, 76.46331929392564, 16777215], [319.7146023568809, 76.46331929392564, 0], [319.7146023568809, 93.53668070607436, 0], [319.7146023568809, 93.53668070607436, 16777215], [245, 87, 16777215], [170.2853976431191, 93.53668070607436, 16777215], [170.2853976431191, 93.53668070607436, 0], [331.1394185240844, 69.97638667498022, 0], [331.1394185240844, 69.97638667498022, 16777215], [405, 83, 16777215], [478.8605814759156, 69.97638667498022, 16777215], [478.8605814759156, 69.97638667498022, 0], [478.8605814759156, 100.02361332501978, 0], [478.8605814759156, 100.02361332501978, 16777215], [405, 87, 16777215], [331.1394185240844, 100.02361332501978, 16777215], [331.1394185240844, 100.02361332501978, 0], [492.55556302831985, 63.58857161731095, 0], [492.55556302831985, 63.58857161731095, 16777215], [565, 83, 16777215], [637.4444369716801, 63.58857161731095, 16777215], [637.4444369716801, 63.58857161731095, 0], [637.4444369716801, 106.41142838268905, 0], [637.4444369716801, 106.41142838268905, 16777215], [565, 87, 16777215], [492.55556302831985, 106.41142838268905, 16777215], [492.55556302831985, 106.41142838268905, 0], [14.523053441056874, 217.34848925057486, 0], [14.523053441056874, 217.34848925057486, 16777215], [85, 243, 16777215], [155.47694655894313, 217.34848925057486, 16777215], [155.47694655894313, 217.34848925057486, 0], [155.47694655894313, 272.65151074942514, 0], [155.47694655894313, 272.65151074942514, 16777215], [85, 247, 16777215], [14.523053441056874, 272.65151074942514, 16777215], [14.523053441056874, 272.65151074942514, 0], [177.02691597225126, 211.30363036944755, 0], [177.02691597225126, 211.30363036944755, 16777215], [245, 243, 16777215], [312.97308402774877, 211.30363036944755, 16777215], [312.97308402774877, 211.30363036944755, 0], [312.97308402774877, 278.69636963055245, 0], [312.97308402774877, 278.69636963055245, 16777215], [245, 247, 16777215], [177.02691597225126, 278.69636963055245, 16777215], [177.02691597225126, 278.69636963055245, 0], [340.0480947161671, 205.5, 0], [340.0480947161671, 205.5, 16777215], [405, 243, 16777215], [469.9519052838329, 205.5, 16777215], [469.9519052838329, 205.5, 0], [469.9519052838329, 284.5, 0], [469.9519052838329, 284.5, 16777215], [405, 247, 16777215], [340.0480947161671, 284.5, 16777215], [340.0480947161671, 284.5, 0], [503.5635966783256, 199.98176727367155, 0], [503.5635966783256, 199.98176727367155, 16777215], [565, 243, 16777215], [626.4364033216743, 199.98176727367155, 16777215], [626.4364033216743, 199.98176727367155, 0], [626.4364033216743, 290.01823272632845, 0], [626.4364033216743, 290.01823272632845, 16777215], [565, 247, 16777215], [503.5635966783256, 290.01823272632845, 16777215], [503.5635966783256, 290.01823272632845, 0], [27.546666766076648, 354.79092927350956, 0], [27.546666766076648, 354.79092927350956, 16777215], [85, 403, 16777215], [142.45333323392336, 354.79092927350956, 16777215], [142.45333323392336, 354.79092927350956, 0], [142.45333323392336, 455.20907072649044, 0], [142.45333323392336, 455.20907072649044, 16777215], [85, 407, 16777215], [27.546666766076648, 455.20907072649044, 16777215], [27.546666766076648, 455.20907072649044, 0], [191.96699141100893, 349.96699141100896, 0], [191.96699141100893, 349.96699141100896, 16777215], [245, 403, 16777215], [298.03300858899104, 349.96699141100896, 16777215], [298.03300858899104, 349.96699141100896, 0], [298.03300858899104, 460.03300858899104, 0], [298.03300858899104, 460.03300858899104, 16777215], [245, 407, 16777215], [191.96699141100893, 460.03300858899104, 16777215], [191.96699141100893, 460.03300858899104, 0], [356.79092927350956, 345.54666676607667, 0], [356.79092927350956, 345.54666676607667, 16777215], [405, 403, 16777215], [453.20907072649044, 345.54666676607667, 16777215], [453.20907072649044, 345.54666676607667, 0], [453.20907072649044, 464.45333323392333, 0], [453.20907072649044, 464.45333323392333, 16777215], [405, 407, 16777215], [356.79092927350956, 464.45333323392333, 16777215], [356.79092927350956, 464.45333323392333, 0], [521.9817672736715, 341.5635966783256, 0], [521.9817672736715, 341.5635966783256, 16777215], [565, 403, 16777215], [608.0182327263285, 341.5635966783256, 16777215], [608.0182327263285, 341.5635966783256, 0], [608.0182327263285, 468.4364033216744, 0], [608.0182327263285, 468.4364033216744, 16777215], [565, 407, 16777215], [521.9817672736715, 468.4364033216744, 16777215], [521.9817672736715, 468.4364033216744, 0], [47.49999999999999, 498.0480947161671, 0], [47.49999999999999, 498.0480947161671, 16777215], [85, 563, 16777215], [122.5, 498.0480947161671, 16777215], [122.5, 498.0480947161671, 0], [122.5, 631.951905283833, 0], [122.5, 631.951905283833, 16777215], [85, 567, 16777215], [47.49999999999999, 631.951905283833, 16777215], [47.49999999999999, 631.951905283833, 0], [213.30363036944755, 495.02691597225123, 0], [213.30363036944755, 495.02691597225123, 16777215], [245, 563, 16777215], [276.69636963055245, 495.02691597225123, 16777215], [276.69636963055245, 495.02691597225123, 0], [276.69636963055245, 634.9730840277488, 0], [276.69636963055245, 634.9730840277488, 16777215], [245, 567, 16777215], [213.30363036944755, 634.9730840277488, 16777215], [213.30363036944755, 634.9730840277488, 0], [379.34848925057486, 492.52305344105685, 0], [379.34848925057486, 492.52305344105685, 16777215], [405, 563, 16777215], [430.65151074942514, 492.52305344105685, 16777215], [430.65151074942514, 492.52305344105685, 0], [430.65151074942514, 637.4769465589432, 0], [430.65151074942514, 637.4769465589432, 16777215], [405, 567, 16777215], [379.34848925057486, 637.4769465589432, 16777215], [379.34848925057486, 637.4769465589432, 0], [545.5885716173109, 490.55556302831985, 0], [545.5885716173109, 490.55556302831985, 16777215], [565, 563, 16777215], [584.4114283826891, 490.55556302831985, 16777215], [584.4114283826891, 490.55556302831985, 0], [584.4114283826891, 639.4444369716801, 0], [584.4114283826891, 639.4444369716801, 16777215], [565, 567, 16777215], [545.5885716173109, 639.4444369716801, 16777215], [545.5885716173109, 639.4444369716801, 0], [71.97638667498022, 649.1394185240844, 0], [71.97638667498022, 649.1394185240844, 16777215], [85, 723, 16777215], [98.02361332501978, 649.1394185240844, 16777215], [98.02361332501978, 649.1394185240844, 0], [98.02361332501978, 800.8605814759156, 0], [98.02361332501978, 800.8605814759156, 16777215], [85, 727, 16777215], [71.97638667498022, 800.8605814759156, 16777215], [71.97638667498022, 800.8605814759156, 0], [238.46331929392565, 648.285397643119, 0], [238.46331929392565, 648.285397643119, 16777215], [245, 723, 16777215], [251.53668070607435, 648.285397643119, 16777215], [251.53668070607435, 648.285397643119, 0], [251.53668070607435, 801.714602356881, 0], [251.53668070607435, 801.714602356881, 16777215], [245, 727, 16777215], [238.46331929392565, 801.714602356881, 16777215], [238.46331929392565, 801.714602356881, 0], [405.0, 648.0, 0], [405.0, 648.0, 16777215], [405, 723, 16777215], [405.0, 648.0, 16777215], [405.0, 648.0, 0], [405.0, 802.0, 0], [405.0, 802.0, 16777215], [405, 727, 16777215], [405.0, 802.0, 16777215], [405.0, 802.0, 0]]
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optimizer(pl_brightness)
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###########################################################################3333
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# | Not used yet, it's for the eulerian graph optimization, probably comming soon =)
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# v
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#
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#class Node:
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# def __init__(self, sid, color):
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# self.sid = sid
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# self.connected = []
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# self.used = False
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# self.color = color
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# self.is_free = None # may be an other value to initialise
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# self.blank_connection = ""
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#
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# def add_nodes(self, neighbord):
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# not_the_same = neighbord != self.sid
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# not_allrady_inside = neighbord not in self.connected
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#
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# if neighbord != self.sid and neighbord not in self.connected:
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# self.connected.append(neighbord)
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#
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# # print the content of the objet to debug with print()
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# def __repr__(self):
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# is_free = " \t###" if self.is_free else " \t___"
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# return is_free + str(self.connected) + "\n"
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#
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#class Component:
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# def __init__(self, all_nodes, comp_nodes):
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# self.all_nodes = all_nodes
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# self.id_nodes = comp_nodes
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# self.id_free_nodes = []
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# self.is_eulerian_circuit = True
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# # centre x,y
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# # bounding box
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# # other
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# pass
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#
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#class Graph:
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# nodes = {} # dict of all nodes
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#
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# def __init__(selt):
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# pass
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#
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#def list_to_nodes(pl):
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# all_nodes = {} # it will contain all nodes
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# sid_prev = None
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#
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# for p in pl:
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# sid = str([int(p[0]), int(p[1])])
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# is_colored = p[2] != 0
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#
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# if is_colored:
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# if sid not in all_nodes:
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# all_nodes[sid] = Node(sid, p[2])
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# if sid_prev != None:
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# all_nodes[sid].add_nodes(sid_prev)
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# all_nodes[sid_prev].add_nodes(sid)
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# sid_prev = sid if is_colored else None
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# return all_nodes
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#
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## recursiv function witch get all connected node for one component and tag them as used
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#def get_one_comp(id_elem, nodes):
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# comp = []
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#
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# comp.append(id_elem)
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# nodes[id_elem].used = True
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# for id_near in nodes[id_elem].connected:
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# if nodes[id_near].used == False:
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# comp += get_one_comp(id_near, nodes)
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# return comp
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#
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#def get_comps(nodes):
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# comps = [] #all component
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# iter_nodes = iter(nodes)
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# nb_elem = len(nodes)
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#
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# for id_nodes in iter_nodes:
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# if nodes[id_nodes].used == False:
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# comps.append(get_one_comp(id_nodes, nodes))
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# return comps
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#
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## if ther is a class for the component it would be a good idea to set en atribute about eulerian graph or non eulerian graph
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#def set_free_vertices(components, nodes):
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# for comp in components:
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# all_even_neighbord = True
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# for id_node in comp:
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# if len(nodes[id_node].connected) % 2 == 0: # test if even neighbord
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# nodes[id_node].is_free = False
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# else:
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# nodes[id_node].is_free = True
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# all_even_neighbord = False
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# if all_even_neighbord:
|
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# for id_node in comp:
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# nodes[id_node].is_free = True
|
|
#
|
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#def optimizer_old(pl):
|
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# all_nodes = {} # it will contain all nodes
|
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# components = [] # list of connected node as a graph
|
|
#
|
|
# # construct dict of connected all_nodes
|
|
# all_nodes = list_to_nodes(pl)
|
|
# components = get_comps(all_nodes)
|
|
# set_free_vertices(components, all_nodes)
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|
##@ print("\n\nall_nodes:\n", all_nodes)
|
|
##@ print("\n\nconnected_components:\n", components)
|
|
# return pl
|
|
#
|