def generate_background_vertex_list(self):
"""Generate a reusable vertex/color list of all background stars. It
will be invoked as background_vertex_list.draw(pyglet.gl.GL_POINTS). """
background_star_vertices = []
background_star_colors = []
# randomly generate background stars
for coordinate in utilities.random_dispersed_coordinates(amount=8000, dispersion=3):
[background_star_vertices.append(component) for component in coordinate]
color = []
for index in range(0,3):
color.append(64)
# allow one or two of the bytes to be less, which allows slight coloration
color[random.randint(0,2)] = random.randint(32,64)
color[random.randint(0,2)] = random.randint(32,64)
[background_star_colors.append(component) for component in color]
self.background_vertex_list = pyglet.graphics.vertex_list(
8000,
('v2i/static', background_star_vertices),
('c3B/static', background_star_colors)
)
def __init__(self, coordinates, primary_color_name=None):
super(Nebula, self).__init__(coordinates)
if primary_color_name is None:
primary_color_name = random.choice(Lobe.color_names.keys())
if not Lobe.color_names.has_key(primary_color_name):
raise DataError, "invalid primary color name: %s"%primary_color_name
self.primary_color_name = primary_color_name
number_of_lobes = random.randint(Nebula.min_lobes, Nebula.max_lobes)
self.lobes = []
permutation_index = random.randint(0,1000)
for lobe_coordinate in utilities.random_dispersed_coordinates(
-Nebula.lobe_offset_bounds, -Nebula.lobe_offset_bounds,
Nebula.lobe_offset_bounds, Nebula.lobe_offset_bounds,
amount = number_of_lobes,
dispersion = 15
):
# cycle through all lobe secondary/image combinations
permutation_index += 1
self.lobes.append( Lobe(lobe_coordinate, self.primary_color_name, permutation_index) )
logger.debug("lobe count: %s", len(self.lobes))
def generate(self, amount, edges): # minimize repetition of nebula colors lobe_primary_color_names = Lobe.color_names.keys() lobe_primary_color_index = random.randint(0, 1000) for coordinate in utilities.random_dispersed_coordinates( edges[0], edges[1], edges[2], edges[3], amount=amount, dispersion=Nebula.max_offset*2 ): lobe_primary_color_index = lobe_primary_color_index % len(lobe_primary_color_names ) primary_color_name = lobe_primary_color_names[lobe_primary_color_index] self.list.append( Nebula(coordinate, primary_color_name) ) # cycle to next lobe primary color lobe_primary_color_index += 1
def generate_stars_and_black_holes(self, config): # generate coordinates for stars AND black holes in one pass # since they may not overlap object_coordinates = utilities.random_dispersed_coordinates( config.limits[0], config.limits[1], config.limits[2], config.limits[3], amount=config.star_count, dispersion=config.dispersion ) self.stars = stars.Stars(self.orbitals) self.black_holes = black_holes.BlackHoles() for coordinate in object_coordinates: object_type = utilities.choose_from_probability(config.object_pool) if object_type == 'black hole': self.black_holes.add(coordinate) else: # object_type is color self.stars.add(coordinate, object_type)
layer1 = pyglet.graphics.OrderedGroup(0) layer2 = pyglet.graphics.OrderedGroup(1) layer3 = pyglet.graphics.OrderedGroup(2) layer4 = pyglet.graphics.OrderedGroup(3) batch1 = pyglet.graphics.Batch() batch2 = pyglet.graphics.Batch() # outline of box to be divided batch1.add(4, GL_LINE_LOOP, layer1, ( 'v2i', (left-1,bottom-1, left-1,top+1, right+1,top+1, right+1,bottom-1)), ( 'c3B', (128,128,128, 128,128,128, 128,128,128, 128,128,128)) ) for coordinate in utilities.random_dispersed_coordinates(bottom,left,top,right,amount,dispersion): layer = layer2 batch2.add(1, GL_POINTS, layer, ( 'v2i', (coordinate[0], coordinate[1])), ( 'c3B', (0, 255, 255)) ) @window.event def on_draw(): window.clear() glMatrixMode(GL_PROJECTION) glLoadIdentity() gluOrtho2D(-512, 512, -364, 364) glMatrixMode(GL_MODELVIEW) batch1.draw() batch2.draw()
def testCoordinatesWithinMargin(self): "Given an evenly-divisible rectangle and maximum margins, coordinates should be known." coordinates = utilities.random_dispersed_coordinates( 0, 0, 2, 5, amount=2, dispersion=2 ) self.assertEqual(coordinates, [(1, 1), (4, 1)])
def testCoordinateCount(self): "The number of coordinates returned should equal the number requested." coordinates = utilities.random_dispersed_coordinates( amount=5133, dispersion=1 ) self.assertEqual(len(coordinates), 5133)
