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fix: SimCamera return uint16, SimMonitor uint32

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appel_c 2024-02-26 11:29:00 +01:00 committed by wakonig_k
parent f1e9d1ceaa
commit dc9634b739
2 changed files with 20 additions and 14 deletions
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6
ophyd_devices/sim/sim.py
View File

@ -58,8 +58,9 @@ class SimMonitor(Device):
USER_ACCESS = ["sim", "registered_proxies"]
sim_cls = SimulatedDataMonitor
BIT_DEPTH = np.uint32
readback = Cpt(ReadOnlySignal, value=0, kind=Kind.hinted, compute_readback=True)
readback = Cpt(ReadOnlySignal, value=BIT_DEPTH(0), kind=Kind.hinted, compute_readback=True)
SUB_READBACK = "readback"
_default_sub = SUB_READBACK
@ -113,6 +114,7 @@ class SimCamera(Device):
sim_cls = SimulatedDataCamera
SHAPE = (100, 100)
BIT_DEPTH = np.uint16
SUB_MONITOR = "monitor"
_default_sub = SUB_MONITOR
@ -127,7 +129,7 @@ class SimCamera(Device):
image = Cpt(
ReadOnlySignal,
name="image",
value=np.empty(SHAPE, dtype=np.uint16),
value=np.empty(SHAPE, dtype=BIT_DEPTH),
compute_readback=True,
kind=Kind.omitted,
)

28
ophyd_devices/sim/sim_data.py
View File

@ -329,6 +329,7 @@ class SimulatedDataMonitor(SimulatedDataBase):
def __init__(self, *args, parent=None, device_manager=None, **kwargs) -> None:
self._model_lookup = self.init_lmfit_models()
super().__init__(*args, parent=parent, device_manager=device_manager, **kwargs)
self.bit_depth = self.parent.BIT_DEPTH
self._init_default()
def _get_additional_params(self) -> None:
@ -421,9 +422,9 @@ class SimulatedDataMonitor(SimulatedDataBase):
if compute_readback:
method = self._compute
value = self.execute_simulation_method(method=method, signal_name=signal_name)
self.update_sim_state(signal_name, value)
self.update_sim_state(signal_name, self.bit_depth(value))
def _compute(self, *args, **kwargs) -> float:
def _compute(self, *args, **kwargs) -> int:
"""
Compute the return value for given motor position and active model.
@ -436,25 +437,24 @@ class SimulatedDataMonitor(SimulatedDataBase):
else:
motor_pos = 0
method = self._model
value = float(method.eval(params=self._model_params, x=motor_pos))
value = int(method.eval(params=self._model_params, x=motor_pos))
return self._add_noise(value, self.sim_params["noise"], self.sim_params["noise_multiplier"])
def _add_noise(self, v: float, noise: NoiseType, noise_multiplier: float) -> float:
def _add_noise(self, v: int, noise: NoiseType, noise_multiplier: float) -> int:
"""
Add the currently activated noise to the simulated data.
If NoiseType.NONE is active, the value will be returned
Args:
v (float): Value to add noise to.
v (int): Value to add noise to.
Returns:
float: Value with added noise.
int: Value with added noise.
"""
if noise == NoiseType.POISSON:
ceiled_v = np.ceil(v)
v = np.random.poisson(ceiled_v, 1)[0] if ceiled_v > 0 else ceiled_v
v = np.random.poisson(v)
return v
elif noise == NoiseType.UNIFORM:
v += np.random.uniform(-1, 1) * noise_multiplier
v += np.round(np.random.uniform(-1, 1) * noise_multiplier).astype(int)
return v
return v
@ -467,6 +467,7 @@ class SimulatedDataCamera(SimulatedDataBase):
self._all_default_model_params = defaultdict(dict)
self._init_default_camera_params()
super().__init__(*args, parent=parent, device_manager=device_manager, **kwargs)
self.bit_depth = self.parent.BIT_DEPTH
self._init_default()
def _init_default(self) -> None:
@ -547,6 +548,7 @@ class SimulatedDataCamera(SimulatedDataBase):
)
else:
value = self._compute_empty_image()
value = value.astype(self.bit_depth)
self.update_sim_state(signal_name, value)
def _compute_empty_image(self) -> np.ndarray:
@ -567,7 +569,7 @@ class SimulatedDataCamera(SimulatedDataBase):
"""Compute a return value for SimulationType2D constant."""
try:
shape = self.parent.image_shape.get()
v = self.sim_params.get("amplitude") * np.ones(shape, dtype=np.float64)
v = self.sim_params.get("amplitude") * np.ones(shape, dtype=np.uint16)
v = self._add_noise(v, self.sim_params["noise"], self.sim_params["noise_multiplier"])
return self._add_hot_pixel(
v,
@ -682,10 +684,12 @@ class SimulatedDataCamera(SimulatedDataBase):
noise (NoiseType): Type of noise to add.
"""
if noise == NoiseType.POISSON:
v = np.random.poisson(np.round(v), v.shape)
v = np.random.poisson(np.round(v), v.shape).astype("uint16")
return v
if noise == NoiseType.UNIFORM:
v += np.random.uniform(-noise_multiplier, noise_multiplier, v.shape)
v += np.round(np.random.uniform(-noise_multiplier, noise_multiplier, v.shape)).astype(
"uint16"
)
return v
if noise == NoiseType.NONE:
return v