java - LibGDX + Box2D : Object Positioning -


i'm trying code breakout games libgdx , box2d. there 1 point don't understand. there must 2 bricks touch edge. on emulator saw 2 bricks nested.

here's createbox method's code:

private void createbox(float posx, float posy, float boxw, float boxh) {     bodydef bodydef = new bodydef();     bodydef.type = bodydef.bodytype.staticbody;     bodydef.position.set(posx, posy);      body body = world.createbody(bodydef);      polygonshape shape = new polygonshape();     shape.setasbox(boxw, boxh);      fixturedef fixturedef = new fixturedef();     fixturedef.shape = shape;     fixturedef.density = 1f;      fixture fixture = body.createfixture(fixturedef);      shape.dispose(); }

enter image description here

edit: multiplied code.

createbox(cons_holder.bricks_left_margin + (i * cons_holder.brick_width * 2 ),                         cons_holder.brick_top_screen_margin + (j * cons_holder.brick_height * 2 ) + cons_holder.bricks_top_margin,                         cons_holder.brick_width / 2,                         cons_holder.brick_height / 2);

the documentation setasbox(float, float) states parameters half-width , half-height. should divide dimensions of boxes in half in order correct size.

private void createbox(float posx, float posy, float boxw, float boxh) {     bodydef bodydef = new bodydef();     bodydef.type = bodydef.bodytype.staticbody;     bodydef.position.set(posx, posy);      body body = world.createbody(bodydef);      polygonshape shape = new polygonshape();     shape.setasbox(boxw / 2.f, boxh / 2.f);      fixturedef fixturedef = new fixturedef();     fixturedef.shape = shape;     fixturedef.density = 1f;      fixture fixture = body.createfixture(fixturedef);      shape.dispose(); }

documentation: https://libgdx.badlogicgames.com/nightlies/docs/api/com/badlogic/gdx/physics/box2d/polygonshape.html#setasbox-float-float-


-

Comments

Post a Comment

Popular posts from this blog

serialization - Convert Any type in scala to Array[Byte] and back -

i have following question: i have variable value in program declared value. i want convert value byte array.. how can serialize byte array , back? found examples related other types such double or int, not any. this should need. it's pretty similar how 1 in java. import java.io.{bytearrayinputstream, bytearrayoutputstream, objectinputstream, objectoutputstream} object serialization extends app { def serialise(value: any): array[byte] = { val stream: bytearrayoutputstream = new bytearrayoutputstream() val oos = new objectoutputstream(stream) oos.writeobject(value) oos.close stream.tobytearray } def deserialise(bytes: array[byte]): = { val ois = new objectinputstream(new bytearrayinputstream(bytes)) val value = ois.readobject ois.close value } println(deserialise(serialise("my test"))) println(deserialise(serialise(list(1)))) println(deserialise(serialise(map(1 -> 2)))) println(deserialise(seri
Read more

matplotlib support failed in PyCharm on OSX -

any idea how fix ? how can debug might problem ? not seem : https://youtrack.jetbrains.com/issue/py-15520 i in console: python 2.6.9 (unknown, jul 14 2015, 19:46:31) [gcc 4.2.1 compatible apple llvm 6.0 (clang-600.0.39)] on darwin >>> import matplotlib.pyplot plt matplotlib support failed the backend : >>> import matplotlib >>> print(matplotlib.rcparams['backend']) macosx
Read more

python - Matplotlib: TypeError: 'AxesSubplot' object is not callable -

i new programming please pardon me if rookie mistake. i writing python script have defined functions create subplots of distributions. i have slider widget end user change value of variables(mu , sigma) , see effect on distribution. here's code import numpy np print np.__version__ import scipy print scipy.__version__ scipy.stats import norm, lognorm, uniform import matplotlib print matplotlib.__version__ import matplotlib.pyplot plt matplotlib.widgets import slider, button, radiobuttons, checkbuttons #####calculating mean , standard deviation##### global mu_a1 mu_a1 = 1 global mu_b1 mu_b1 = 10 global mu_c1 mu_c1 = -13 global sigma_a1 sigma_a1 = 0.14 global sigma_b1 sigma_b1 = 1.16 global sigma_c1 sigma_c1 = 2.87 mu_x01 = -11 sigma_x01 = 1.9 #####_____##### #####generating random data##### a1 = 0.75*mu_a1 + (1.25 - 0.75)*sigma_a1*np.random.sample(10000) b1 = 8*mu_b1 + (12 - 8)*sigma_b1*np.random.sample(10000) c1 = -12*mu_c1 + 2*sigma_c1*np.random.sample(10000)
Read more