Python math.pi() Examples

The following are 30 code examples for showing how to use math.pi(). These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.

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Example 1
Project: BiblioPixelAnimations   Author: ManiacalLabs   File: Wave.py    License: MIT License 7 votes vote down vote up
def step(self, amt=1):
        for i in range(self._size):
            y = math.sin(
                math.pi *
                float(self.cycles) *
                float(self._step * i) /
                float(self._size))

            if y >= 0.0:
                # Peaks of sine wave are white
                y = 1.0 - y  # Translate Y to 0.0 (top) to 1.0 (center)
                r, g, b = self.palette(0)
                c2 = (int(255 - float(255 - r) * y),
                      int(255 - float(255 - g) * y),
                      int(255 - float(255 - b) * y))
            else:
                # Troughs of sine wave are black
                y += 1.0  # Translate Y to 0.0 (bottom) to 1.0 (center)
                r, g, b = self.palette(0)
                c2 = (int(float(r) * y),
                      int(float(g) * y),
                      int(float(b) * y))
            self.layout.set(self._start + i, c2)

        self._step += amt 
Example 2
Project: BiblioPixelAnimations   Author: ManiacalLabs   File: Wave.py    License: MIT License 6 votes vote down vote up
def step(self, amt=1):
        for i in range(self._size):
            y = math.sin((math.pi * float(self.cycles) * float(i) / float(self._size)) + self._moveStep)

            if y >= 0.0:
                # Peaks of sine wave are white
                y = 1.0 - y  # Translate Y to 0.0 (top) to 1.0 (center)
                r, g, b = self.palette(0)
                c2 = (int(255 - float(255 - r) * y), int(255 - float(255 - g) * y), int(255 - float(255 - b) * y))
            else:
                # Troughs of sine wave are black
                y += 1.0  # Translate Y to 0.0 (bottom) to 1.0 (center)
                r, g, b = self.palette(0)
                c2 = (int(float(r) * y),
                      int(float(g) * y),
                      int(float(b) * y))
            self.layout.set(self._start + i, c2)

        self._moveStep += amt
        self._moveStep += 1
        if(self._moveStep >= self._size):
            self._moveStep = 0 
Example 3
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_gym_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _get_observation_upper_bound(self):
    """Get the upper bound of the observation.

    Returns:
      The upper bound of an observation. See GetObservation() for the details
        of each element of an observation.
    """
    upper_bound = np.zeros(self._get_observation_dimension())
    num_motors = self.minitaur.num_motors
    upper_bound[0:num_motors] = math.pi  # Joint angle.
    upper_bound[num_motors:2 * num_motors] = (
        motor.MOTOR_SPEED_LIMIT)  # Joint velocity.
    upper_bound[2 * num_motors:3 * num_motors] = (
        motor.OBSERVED_TORQUE_LIMIT)  # Joint torque.
    upper_bound[3 * num_motors:] = 1.0  # Quaternion of base orientation.
    return upper_bound 
Example 4
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def MapToMinusPiToPi(angles):
  """Maps a list of angles to [-pi, pi].

  Args:
    angles: A list of angles in rad.
  Returns:
    A list of angle mapped to [-pi, pi].
  """
  mapped_angles = copy.deepcopy(angles)
  for i in range(len(angles)):
    mapped_angles[i] = math.fmod(angles[i], TWO_PI)
    if mapped_angles[i] >= math.pi:
      mapped_angles[i] -= TWO_PI
    elif mapped_angles[i] < -math.pi:
      mapped_angles[i] += TWO_PI
  return mapped_angles 
Example 5
def ResetTerrainExample():
  """An example showing resetting random terrain env."""
  num_reset = 10
  steps = 100
  env = minitaur_randomize_terrain_gym_env.MinitaurRandomizeTerrainGymEnv(
      render=True,
      leg_model_enabled=False,
      motor_velocity_limit=np.inf,
      pd_control_enabled=True)
  action = [math.pi / 2] * 8
  for _ in xrange(num_reset):
    env.reset()
    for _ in xrange(steps):
      _, _, done, _ = env.step(action)
      if done:
        break 
Example 6
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_trotting_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _gen_signal(self, t, phase):
    """Generates a sinusoidal reference leg trajectory.

    The foot (leg tip) will move in a ellipse specified by extension and swing
    amplitude.

    Args:
      t: Current time in simulation.
      phase: The phase offset for the periodic trajectory.

    Returns:
      The desired leg extension and swing angle at the current time.
    """
    period = 1 / self._step_frequency
    extension = self._extension_amplitude * math.cos(
        2 * math.pi / period * t + phase)
    swing = self._swing_amplitude * math.sin(2 * math.pi / period * t + phase)
    return extension, swing 
Example 7
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_trotting_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _signal(self, t):
    """Generates the trotting gait for the robot.

    Args:
      t: Current time in simulation.

    Returns:
      A numpy array of the reference leg positions.
    """
    # Generates the leg trajectories for the two digonal pair of legs.
    ext_first_pair, sw_first_pair = self._gen_signal(t, 0)
    ext_second_pair, sw_second_pair = self._gen_signal(t, math.pi)

    trotting_signal = np.array([
        sw_first_pair, sw_second_pair, sw_second_pair, sw_first_pair,
        ext_first_pair, ext_second_pair, ext_second_pair, ext_first_pair
    ])
    signal = np.array(self._init_pose) + trotting_signal
    return signal 
Example 8
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_ball_gym_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _get_observation(self):
    world_translation_minitaur, world_rotation_minitaur = (
        self._pybullet_client.getBasePositionAndOrientation(
            self.minitaur.quadruped))
    world_translation_ball, world_rotation_ball = (
        self._pybullet_client.getBasePositionAndOrientation(self._ball_id))
    minitaur_translation_world, minitaur_rotation_world = (
        self._pybullet_client.invertTransform(world_translation_minitaur,
                                              world_rotation_minitaur))
    minitaur_translation_ball, _ = (
        self._pybullet_client.multiplyTransforms(minitaur_translation_world,
                                                 minitaur_rotation_world,
                                                 world_translation_ball,
                                                 world_rotation_ball))
    distance = math.sqrt(minitaur_translation_ball[0]**2 +
                         minitaur_translation_ball[1]**2)
    angle = math.atan2(minitaur_translation_ball[0],
                       minitaur_translation_ball[1])
    self._observation = [angle - math.pi / 2, distance]
    return self._observation 
Example 9
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_reactive_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _get_observation_upper_bound(self):
    """Get the upper bound of the observation.

    Returns:
      The upper bound of an observation. See _get_true_observation() for the
      details of each element of an observation.
    """
    upper_bound_roll = 2 * math.pi
    upper_bound_pitch = 2 * math.pi
    upper_bound_roll_dot = 2 * math.pi / self._time_step
    upper_bound_pitch_dot = 2 * math.pi / self._time_step
    upper_bound_motor_angle = 2 * math.pi
    upper_bound = [
        upper_bound_roll, upper_bound_pitch, upper_bound_roll_dot,
        upper_bound_pitch_dot
    ]

    if self._use_angle_in_observation:
      upper_bound.extend([upper_bound_motor_angle] * NUM_MOTORS)
    return np.array(upper_bound) 
Example 10
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_gym_env_example.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def ResetPoseExample(log_path=None):
  """An example that the minitaur stands still using the reset pose."""
  steps = 10000
  environment = minitaur_gym_env.MinitaurGymEnv(
      urdf_version=minitaur_gym_env.DERPY_V0_URDF_VERSION,
      render=True,
      leg_model_enabled=False,
      motor_velocity_limit=np.inf,
      pd_control_enabled=True,
      accurate_motor_model_enabled=True,
      motor_overheat_protection=True,
      hard_reset=False,
      log_path=log_path)
  action = [math.pi / 2] * 8
  for _ in range(steps):
    _, _, done, _ = environment.step(action)
    time.sleep(1./100.)
    if done:
      break 
Example 11
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_terrain_randomizer.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def sample(self):
    """Samples new points around some existing point.

    Removes the sampling base point and also stores the new jksampled points if
    they are far enough from all existing points.
    """
    active_point = self._active_list.pop()
    for _ in xrange(self._max_sample_size):
      # Generate random points near the current active_point between the radius
      random_radius = np.random.uniform(self._min_radius, 2 * self._min_radius)
      random_angle = np.random.uniform(0, 2 * math.pi)

      # The sampled 2D points near the active point
      sample = random_radius * np.array(
          [np.cos(random_angle), np.sin(random_angle)]) + active_point

      if not self._is_in_grid(sample):
        continue

      if self._is_close_to_existing_points(sample):
        continue

      self._active_list.append(sample)
      self._grid[self._point_to_index_1d(sample)] = sample 
Example 12
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur_gym_env_example.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def ResetPoseExample():
  """An example that the minitaur stands still using the reset pose."""
  steps = 1000
  randomizer = (minitaur_env_randomizer.MinitaurEnvRandomizer())
  environment = minitaur_gym_env.MinitaurBulletEnv(
      render=True,
      leg_model_enabled=False,
      motor_velocity_limit=np.inf,
      pd_control_enabled=True,
      accurate_motor_model_enabled=True,
      motor_overheat_protection=True,
      env_randomizer =  randomizer,
      hard_reset=False)
  action = [math.pi / 2] * 8
  for _ in range(steps):
    _, _, done, _ = environment.step(action)
    if done:
      break
  environment.reset() 
Example 13
Project: soccer-matlab   Author: utra-robosoccer   File: minitaur.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def ConvertFromLegModel(self, actions):
    """Convert the actions that use leg model to the real motor actions.

    Args:
      actions: The theta, phi of the leg model.
    Returns:
      The eight desired motor angles that can be used in ApplyActions().
    """

    motor_angle = copy.deepcopy(actions)
    scale_for_singularity = 1
    offset_for_singularity = 1.5
    half_num_motors = int(self.num_motors / 2)
    quater_pi = math.pi / 4
    for i in range(self.num_motors):
      action_idx = i // 2
      forward_backward_component = (-scale_for_singularity * quater_pi * (
          actions[action_idx + half_num_motors] + offset_for_singularity))
      extension_component = (-1)**i * quater_pi * actions[action_idx]
      if i >= half_num_motors:
        extension_component = -extension_component
      motor_angle[i] = (
          math.pi + forward_backward_component + extension_component)
    return motor_angle 
Example 14
Project: soccer-matlab   Author: utra-robosoccer   File: kuka.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def __init__(self, urdfRootPath=pybullet_data.getDataPath(), timeStep=0.01):
    self.urdfRootPath = urdfRootPath
    self.timeStep = timeStep
    self.maxVelocity = .35
    self.maxForce = 200.
    self.fingerAForce = 2 
    self.fingerBForce = 2.5
    self.fingerTipForce = 2
    self.useInverseKinematics = 1
    self.useSimulation = 1
    self.useNullSpace =21
    self.useOrientation = 1
    self.kukaEndEffectorIndex = 6
    self.kukaGripperIndex = 7
    #lower limits for null space
    self.ll=[-.967,-2 ,-2.96,0.19,-2.96,-2.09,-3.05]
    #upper limits for null space
    self.ul=[.967,2 ,2.96,2.29,2.96,2.09,3.05]
    #joint ranges for null space
    self.jr=[5.8,4,5.8,4,5.8,4,6]
    #restposes for null space
    self.rp=[0,0,0,0.5*math.pi,0,-math.pi*0.5*0.66,0]
    #joint damping coefficents
    self.jd=[0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001,0.00001]
    self.reset() 
Example 15
Project: soccer-matlab   Author: utra-robosoccer   File: test_pybullet_sim_gym_env.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def ResetPoseExample(steps):
  """An example that the minitaur stands still using the reset pose."""
  
  
  environment = pybullet_sim_gym_env.PyBulletSimGymEnv(
      pybullet_sim_factory=boxstack_pybullet_sim,
      debug_visualization=False,
      render=True, action_repeat=30)
  action = [math.pi / 2] * 8
  
  vid = video_recorder.VideoRecorder(env=environment,path="vid.mp4")
  
  for _ in range(steps):
    print(_)
    startsim = time.time()
    _, _, done, _ = environment.step(action)
    stopsim = time.time()
    startrender = time.time()
    #environment.render(mode='rgb_array')
    vid.capture_frame()
    stoprender = time.time()
    print ("env.step " , (stopsim - startsim))
    print ("env.render " , (stoprender - startrender))
    if done:
    	environment.reset() 
Example 16
Project: PyOptiX   Author: ozen   File: common.py    License: MIT License 6 votes vote down vote up
def calculate_camera_variables(eye, lookat, up, fov, aspect_ratio, fov_is_vertical=False):
    import numpy as np
    import math

    W = np.array(lookat) - np.array(eye)
    wlen = np.linalg.norm(W)
    U = np.cross(W, np.array(up))
    U /= np.linalg.norm(U)
    V = np.cross(U, W)
    V /= np.linalg.norm(V)

    if fov_is_vertical:
        vlen = wlen * math.tan(0.5 * fov * math.pi / 180.0)
        V *= vlen
        ulen = vlen * aspect_ratio
        U *= ulen
    else:
        ulen = wlen * math.tan(0.5 * fov * math.pi / 180.0)
        U *= ulen
        vlen = ulen * aspect_ratio
        V *= vlen

    return U, V, W 
Example 17
Project: robosuite   Author: StanfordVL   File: transform_utils.py    License: MIT License 6 votes vote down vote up
def random_quat(rand=None):
    """Return uniform random unit quaternion.
    rand: array like or None
        Three independent random variables that are uniformly distributed
        between 0 and 1.
    >>> q = random_quat()
    >>> np.allclose(1.0, vector_norm(q))
    True
    >>> q = random_quat(np.random.random(3))
    >>> q.shape
    (4,)
    """
    if rand is None:
        rand = np.random.rand(3)
    else:
        assert len(rand) == 3
    r1 = np.sqrt(1.0 - rand[0])
    r2 = np.sqrt(rand[0])
    pi2 = math.pi * 2.0
    t1 = pi2 * rand[1]
    t2 = pi2 * rand[2]
    return np.array(
        (np.sin(t1) * r1, np.cos(t1) * r1, np.sin(t2) * r2, np.cos(t2) * r2),
        dtype=np.float32,
    ) 
Example 18
Project: torch-toolbox   Author: PistonY   File: loss.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def __init__(
            self,
            classes,
            m=0.5,
            s=64,
            easy_margin=True,
            weight=None,
            size_average=None,
            ignore_index=-100,
            reduce=None,
            reduction='mean'):
        super(ArcLoss, self).__init__(weight, size_average, reduce, reduction)
        self.ignore_index = ignore_index
        assert s > 0.
        assert 0 <= m <= (math.pi / 2)
        self.s = s
        self.m = m
        self.cos_m = math.cos(m)
        self.sin_m = math.sin(m)
        self.mm = math.sin(math.pi - m) * m
        self.threshold = math.cos(math.pi - m)
        self.classes = classes
        self.easy_margin = easy_margin 
Example 19
Project: torch-toolbox   Author: PistonY   File: loss.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def _get_body(self, x, target):
        cos_t = torch.gather(x, 1, target.unsqueeze(1))  # cos(theta_yi)
        if self.easy_margin:
            cond = torch.relu(cos_t)
        else:
            cond_v = cos_t - self.threshold
            cond = torch.relu(cond_v)
        cond = cond.bool()
        # Apex would convert FP16 to FP32 here
        # cos(theta_yi + m)
        new_zy = torch.cos(torch.acos(cos_t) + self.m).type(cos_t.dtype)
        if self.easy_margin:
            zy_keep = cos_t
        else:
            zy_keep = cos_t - self.mm  # (cos(theta_yi) - sin(pi - m)*m)
        new_zy = torch.where(cond, new_zy, zy_keep)
        diff = new_zy - cos_t  # cos(theta_yi + m) - cos(theta_yi)
        gt_one_hot = F.one_hot(target, num_classes=self.classes)
        body = gt_one_hot * diff
        return body 
Example 20
Project: audio   Author: pytorch   File: kaldi.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _feature_window_function(window_type: str,
                             window_size: int,
                             blackman_coeff: float,
                             device: torch.device,
                             dtype: int,
                             ) -> Tensor:
    r"""Returns a window function with the given type and size
    """
    if window_type == HANNING:
        return torch.hann_window(window_size, periodic=False, device=device, dtype=dtype)
    elif window_type == HAMMING:
        return torch.hamming_window(window_size, periodic=False, alpha=0.54, beta=0.46, device=device, dtype=dtype)
    elif window_type == POVEY:
        # like hanning but goes to zero at edges
        return torch.hann_window(window_size, periodic=False, device=device, dtype=dtype).pow(0.85)
    elif window_type == RECTANGULAR:
        return torch.ones(window_size, device=device, dtype=dtype)
    elif window_type == BLACKMAN:
        a = 2 * math.pi / (window_size - 1)
        window_function = torch.arange(window_size, device=device, dtype=dtype)
        # can't use torch.blackman_window as they use different coefficients
        return (blackman_coeff - 0.5 * torch.cos(a * window_function) +
                (0.5 - blackman_coeff) * torch.cos(2 * a * window_function)).to(device=device, dtype=dtype)
    else:
        raise Exception('Invalid window type ' + window_type) 
Example 21
Project: audio   Author: pytorch   File: transforms.py    License: BSD 2-Clause "Simplified" License 6 votes vote down vote up
def _fade_in(self, waveform_length: int) -> Tensor:
        fade = torch.linspace(0, 1, self.fade_in_len)
        ones = torch.ones(waveform_length - self.fade_in_len)

        if self.fade_shape == "linear":
            fade = fade

        if self.fade_shape == "exponential":
            fade = torch.pow(2, (fade - 1)) * fade

        if self.fade_shape == "logarithmic":
            fade = torch.log10(.1 + fade) + 1

        if self.fade_shape == "quarter_sine":
            fade = torch.sin(fade * math.pi / 2)

        if self.fade_shape == "half_sine":
            fade = torch.sin(fade * math.pi - math.pi / 2) / 2 + 0.5

        return torch.cat((fade, ones)).clamp_(0, 1) 
Example 22
Project: unicorn-hat-hd   Author: pimoroni   File: demo.py    License: MIT License 5 votes vote down vote up
def tunnel(x, y, step):
    speed = step / 100.0
    x -= (u_width / 2)
    y -= (u_height / 2)
    xo = math.sin(step / 27.0) * 2
    yo = math.cos(step / 18.0) * 2
    x += xo
    y += yo
    if y == 0:
        if x < 0:
            angle = -(math.pi / 2)
        else:
            angle = (math.pi / 2)
    else:
        angle = math.atan(x / y)
    if y > 0:
        angle += math.pi
    angle /= 2 * math.pi  # convert angle to 0...1 range
    hyp = math.sqrt(math.pow(x, 2) + math.pow(y, 2))
    shade = hyp / 2.1
    shade = 1 if shade > 1 else shade
    angle += speed
    depth = speed + (hyp / 10)
    col1 = hue_to_rgb[step % 255]
    col1 = (col1[0] * 0.8, col1[1] * 0.8, col1[2] * 0.8)
    col2 = hue_to_rgb[step % 255]
    col2 = (col2[0] * 0.3, col2[1] * 0.3, col2[2] * 0.3)
    col = col1 if int(abs(angle * 6.0)) % 2 == 0 else col2
    td = .3 if int(abs(depth * 3.0)) % 2 == 0 else 0
    col = (col[0] + td, col[1] + td, col[2] + td)
    col = (col[0] * shade, col[1] * shade, col[2] * shade)
    return (col[0] * 255, col[1] * 255, col[2] * 255) 
Example 23
Project: indras_net   Author: gcallah   File: agent.py    License: GNU General Public License v3.0 5 votes vote down vote up
def ratio_to_sin(ratio):
    """
    Take a ratio of y to x and turn it into a sine.
    """
    return sin(ratio * pi / 2) 
Example 24
Project: indras_net   Author: gcallah   File: grid_env.py    License: GNU General Public License v3.0 5 votes vote down vote up
def get_angle(self, agent1, agent2, grid_view=None):
        """
        Use two agents to find the angle they make, using their coordinates
        """
        dy = abs(agent1.pos[Y] - agent2.pos[Y])
        dx = abs(agent1.pos[X] - agent2.pos[X])
        if(dy == 0):
            return 180
        if(dx == 0):
            return 90
        else:
            rad = math.atan(dy / dx)
            angle = rad * (180 / math.pi)
            return angle 
Example 25
Project: pepper-robot-programming   Author: maverickjoy   File: asthama_search.py    License: MIT License 5 votes vote down vote up
def _transformTheta(self, theta):
        # CONVERTING THETA { THETA' % 360}
        if (float(theta) == math.radians(360)):
            theta = 0.0

        if (float(theta) == -(math.radians(360))):
            theta = 0.0

        if (float(theta) == math.radians(270)):
            theta = -math.pi/2

        if (float(theta) == -(math.radians(270))):
            theta = math.pi/2

        return theta 
Example 26
Project: EDeN   Author: fabriziocosta   File: graph_layout.py    License: MIT License 5 votes vote down vote up
def _compute_initial_pos(self, graph):
        _radius = 1
        _offset = 0
        n = len(graph)
        pos = {id: np.array([_radius * math.cos(theta - math.pi / 2) + _offset,
                             _radius * math.sin(theta - math.pi / 2) + _offset]
                            )
               for id, theta in enumerate(
            np.linspace(0, 2 * math.pi * (1 - 1 / float(n)), num=n))}
        return pos 
Example 27
def warmup_cosine(x, warmup=0.002):
    if x < warmup:
        return x/warmup
    return 0.5 * (1.0 + torch.cos(math.pi * x)) 
Example 28
def gelu(x):
    """Implementation of the gelu activation function.
        For information: OpenAI GPT's gelu is slightly different (and gives slightly different results):
        0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) * (x + 0.044715 * torch.pow(x, 3))))
    """
    return x * 0.5 * (1.0 + torch.erf(x / math.sqrt(2.0))) 
Example 29
Project: comet-commonsense   Author: atcbosselut   File: opt.py    License: Apache License 2.0 5 votes vote down vote up
def warmup_cosine(x, warmup=0.002):
    s = 1 if x <= warmup else 0
    return s*(x/warmup) + (1-s)*(0.5 * (1 + torch.cos(math.pi * x))) 
Example 30
Project: comet-commonsense   Author: atcbosselut   File: gpt.py    License: Apache License 2.0 5 votes vote down vote up
def gelu(x):
    return (0.5 * x * (1 + torch.tanh(math.sqrt(2 / math.pi) *
            (x + 0.044715 * torch.pow(x, 3)))))