import math # parameter for angles pps = 25000 time_us_angle_zero = float(400) # it's just a random value, it must be tested (us = micro second) time_us_per_point = float(1000000 / pps) # 40 us for 25kpps (us = micro second) # parmeter for brightness max_lengh = 50 # in pixel, random value as well import sys def debug(*args, **kwargs): print(*args, file=sys.stderr, **kwargs) def different_position(p1, p2): return (int(p2[0]) != int(p1[0])) or (int(p2[1]) != int(p1[1])) def sub(p1, p2): return [] def no_blanks_points(*points): for p in points: if p[2] == 0: return False return True def angle_exist(p1, p2, p3): return no_blanks_points(p1, p2, p3) and different_position(p1, p2) and different_position(p2, p3) def scalar_product(v1, v2): return v1[0] * v2[0] + v1[1] * v2[1] def length(v): return math.sqrt(scalar_product(v, v)) def normalize(v): l = length(v) return [v[0] / l, v[1] / l] def sub(p1, p2): return [p1[0] - p2[0], p1[1] - p2[1]] def add(p1, p2): return [p1[0] + p2[0], p1[1] + p2[1]] def mult_by_scalar(p, scalar): return [p[0] * scalar, p[1] * scalar] # 90 deg rotate to the right of v1 when y axes is directed to the floor def rot_90_right(v): return [-v[1], v[0]] def get_angle_degree(p1, p2, p3): v1 = sub(p2, p1) v2 = sub(p2, p3) d1x = normalize(v1) d1y = rot_90_right(d1x) x = scalar_product(d1x, v2) y = scalar_product(d1y, v2) angle = 180 - abs(math.degrees(math.atan2(y, x))) return angle def point_to_add(angle): return int(float((1 - (angle / 180.0)) * time_us_angle_zero) / time_us_per_point) def adjusts_angles(pl): if len(pl) < 3: return pl new_pl = [] previous = pl[0] middle = pl[1] new_pl.append(pl[0]) for ensuing in pl[2:]: if angle_exist(previous, middle, ensuing): angle = get_angle_degree(previous, middle, ensuing) nb_point_added = point_to_add(angle) for i in range(nb_point_added): new_pl.append(middle) new_pl.append(middle) previous = middle middle = ensuing new_pl.append(pl[-1]) return new_pl def adjusts_brightness(pl): new_pl = [] if len(pl) < 1: return pl new_pl.append(pl[0]) prev = pl[0] for current in pl[1:]: new_pl.append(prev) if no_blanks_points(prev, current): diff = sub(current, prev) l = length(diff) if l > max_lengh: nb_add = math.ceil(l / max_lengh) print("\n\n===") print("from:", prev) print("to:", current) print("diff:", diff) for i in range(nb_add): factor = float(i) / float(nb_add) print("factor:", factor) new_point = add(prev, mult_by_scalar(diff, factor)) + [prev[2]] print(new_point) new_pl.append(new_point) #else: # new_pl.append() prev = current new_pl.append(pl[-1]) return new_pl def adjust_ending_point(pl): # si il y a trop de point noir, on en enleve # si il y a un que 1 point noir: # on en met un autre return pl def optimizer(pl): initial_length = len(pl) pl = adjusts_angles(pl) added_by_angle = len(pl) - initial_length pl = adjusts_brightness(pl) added_by_brightness = len(pl) - (added_by_angle + initial_length) #points_added = added_by_angle + added_by_brightness #print("\n\ninital_lenght:", initial_length, "\tadded by angles:", added_by_angle, "\tadded by brightness:", added_by_brightness ) return pl if __name__ == '__main__': # The 3 pl_somthing are used to test and debug the algorythm without # using all the programe archithecture. The goal is to be able to execute # the code snippet without errors being caught by LJ. 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)] 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]] 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]] optimizer(pl_brightness) ###########################################################################3333 # | Not used yet, it's for the eulerian graph optimization, probably comming soon =) # v # #class Node: # def __init__(self, sid, color): # self.sid = sid # self.connected = [] # self.used = False # self.color = color # self.is_free = None # may be an other value to initialise # self.blank_connection = "" # # def add_nodes(self, neighbord): # not_the_same = neighbord != self.sid # not_allrady_inside = neighbord not in self.connected # # if neighbord != self.sid and neighbord not in self.connected: # self.connected.append(neighbord) # # # print the content of the objet to debug with print() # def __repr__(self): # is_free = " \t###" if self.is_free else " \t___" # return is_free + str(self.connected) + "\n" # #class Component: # def __init__(self, all_nodes, comp_nodes): # self.all_nodes = all_nodes # self.id_nodes = comp_nodes # self.id_free_nodes = [] # self.is_eulerian_circuit = True # # centre x,y # # bounding box # # other # pass # #class Graph: # nodes = {} # dict of all nodes # # def __init__(selt): # pass # #def list_to_nodes(pl): # all_nodes = {} # it will contain all nodes # sid_prev = None # # for p in pl: # sid = str([int(p[0]), int(p[1])]) # is_colored = p[2] != 0 # # if is_colored: # if sid not in all_nodes: # all_nodes[sid] = Node(sid, p[2]) # if sid_prev != None: # all_nodes[sid].add_nodes(sid_prev) # all_nodes[sid_prev].add_nodes(sid) # sid_prev = sid if is_colored else None # return all_nodes # ## recursiv function witch get all connected node for one component and tag them as used #def get_one_comp(id_elem, nodes): # comp = [] # # comp.append(id_elem) # nodes[id_elem].used = True # for id_near in nodes[id_elem].connected: # if nodes[id_near].used == False: # comp += get_one_comp(id_near, nodes) # return comp # #def get_comps(nodes): # comps = [] #all component # iter_nodes = iter(nodes) # nb_elem = len(nodes) # # for id_nodes in iter_nodes: # if nodes[id_nodes].used == False: # comps.append(get_one_comp(id_nodes, nodes)) # return comps # ## 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 #def set_free_vertices(components, nodes): # for comp in components: # all_even_neighbord = True # for id_node in comp: # if len(nodes[id_node].connected) % 2 == 0: # test if even neighbord # nodes[id_node].is_free = False # else: # nodes[id_node].is_free = True # all_even_neighbord = False # if all_even_neighbord: # for id_node in comp: # nodes[id_node].is_free = True # #def optimizer_old(pl): # all_nodes = {} # it will contain all nodes # 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) ##@ print("\n\nall_nodes:\n", all_nodes) ##@ print("\n\nconnected_components:\n", components) # return pl #