def __init__(self, directions, invalid=10, min_range=0.2, max_range=10,
noise=None):
'''
:param directions: array of orientations
:param invalid: value for invalid data (i.e., out of range)
'''
self.invalid = invalid
self.min_range = min_range
self.max_range = max_range
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else
instantiate_spec(self.noise_spec))
spec = {
'desc': 'Range-finder',
'shape': [len(directions)],
'format': 'C',
'range': [0, +1],
'extra': {'directions': np.array(directions).tolist(),
'noise': noise,
'invalid': float(invalid),
'max_range': float(max_range),
'min_range': float(min_range)}
}
VehicleSensor.__init__(self, spec)
MyRaytracer.__init__(self, directions)
def __init__(self,
directions,
invalid=10,
min_range=0.2,
max_range=10,
noise=None):
'''
:param directions: array of orientations
:param invalid: value for invalid data (i.e., out of range)
'''
self.invalid = invalid
self.min_range = min_range
self.max_range = max_range
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else instantiate_spec(
self.noise_spec))
spec = {
'desc': 'Range-finder',
'shape': [len(directions)],
'format': 'C',
'range': [0, +1],
'extra': {
'directions': np.array(directions).tolist(),
'noise': noise,
'invalid': float(invalid),
'max_range': float(max_range),
'min_range': float(min_range)
}
}
VehicleSensor.__init__(self, spec)
MyRaytracer.__init__(self, directions)
def __init__(self, num_sensels):
spec = {
'desc': 'Random sensor',
'shape': [num_sensels],
'format': 'C',
'range': [0, +1],
'extra': {}
}
VehicleSensor.__init__(self, spec)
self.num_sensels = num_sensels
def __init__(self, num_sensels):
spec = {
'desc': 'Random sensor',
'shape': [num_sensels],
'format': 'C',
'range': [0, +1],
'extra': {}
}
VehicleSensor.__init__(self, spec)
self.num_sensels = num_sensels
def __init__(self, directions, noise=None, invalid=0.5):
self.invalid = invalid
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else
instantiate_spec(self.noise_spec))
spec = {
'desc': 'Photoreceptors',
'shape': [len(directions)],
'format': 'C',
'range': [0, +1],
'extra': {'directions': directions.tolist(),
'invalid': invalid,
'sono': 'qui',
'noise': self.noise_spec}
}
VehicleSensor.__init__(self, spec)
TexturedRaytracer.__init__(self, directions)
def __init__(self, directions, noise=None, invalid=0.5):
self.invalid = invalid
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else instantiate_spec(
self.noise_spec))
spec = {
'desc': 'Photoreceptors',
'shape': [len(directions)],
'format': 'C',
'range': [0, +1],
'extra': {
'directions': directions.tolist(),
'invalid': invalid,
'sono': 'qui',
'noise': self.noise_spec
}
}
VehicleSensor.__init__(self, spec)
TexturedRaytracer.__init__(self, directions)
def __init__(self, positions,
min_value=0, max_value=1, normalize=False, noise=None,
shape=None):
'''
:param positions: 2D positions of the sensels
'''
if normalize:
logger.warning('normalize=True is deprecated')
if shape is None:
shape = [len(positions)]
self.num_sensels = len(positions)
self.positions = np.array(positions)
self.min_value = min_value
self.max_value = max_value
self.normalize = normalize
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else
instantiate_spec(self.noise_spec))
boot_spec = {
'desc': 'Field sampler',
'shape': shape,
'format': 'C',
'range': [float(self.min_value), float(self.max_value)],
'extra': {'positions': self.positions.tolist(),
'normalize': bool(normalize),
'max_value': float(max_value),
'min_value': float(min_value),
'noise': self.noise_spec}
}
VehicleSensor.__init__(self, boot_spec)
self.primitives = None
def __init__(self, directions, spatial_sigma_deg, upsample=10,
noise=None, invalid=0.5):
self.invalid = invalid
self.noise_spec = noise
self.noise = (None if self.noise_spec is None else
instantiate_spec(self.noise_spec))
spatial_sigma_rad = np.deg2rad(spatial_sigma_deg)
self.delta = np.linspace(-3, 3, upsample) * spatial_sigma_rad
directions2 = []
for d in directions:
for s in self.delta:
directions2.append(d + s)
self.directions_o = np.array(directions)
def kernel(x):
return np.exp(-(x ** 2))
self.coeff = kernel(self.delta)
self.coeff = self.coeff / np.sum(self.coeff)
spec = {
'desc': 'Photoreceptors',
'shape': [len(directions)],
'format': 'C',
'range': [0, +1],
'extra': {'directions': self.directions_o.tolist(),
'noise': self.noise_spec,
'delta': self.delta.tolist(),
'coeff': self.coeff.tolist(),
'spatial_sigma_deg': spatial_sigma_deg},
}
VehicleSensor.__init__(self, spec)
TexturedRaytracer.__init__(self, np.array(directions2))
