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Stricter runtime type checks

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This commit is contained in:
Joel Collins 2020-12-01 17:30:53 +00:00
parent fd42e2e2b6
commit f2a2d880f2
1 changed files with 24 additions and 13 deletions
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33
openflexure_microscope/stage/sanga.py
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@ -1,6 +1,7 @@
import logging import logging
import time import time
from collections.abc import Iterable from collections.abc import Iterable
from types import GeneratorType
from typing import Optional, Tuple, Union from typing import Optional, Tuple, Union
import numpy as np import numpy as np
@ -58,7 +59,7 @@ class SangaStage(BaseStage):
return self.board.position return self.board.position
@property @property
def backlash(self): def backlash(self) -> np.ndarray:
"""The distance used for backlash compensation. """The distance used for backlash compensation.
Software backlash compensation is enabled by setting this property to a value Software backlash compensation is enabled by setting this property to a value
other than `None`. The value can either be an array-like object (list, tuple, other than `None`. The value can either be an array-like object (list, tuple,
@ -73,16 +74,17 @@ class SangaStage(BaseStage):
back by ``backlash[i]``. This is computed per-axis, so if some axes are moving back by ``backlash[i]``. This is computed per-axis, so if some axes are moving
in the same direction as ``backlash``, they won't do two moves. in the same direction as ``backlash``, they won't do two moves.
""" """
if isinstance(self._backlash, (list, np.ndarray)): if isinstance(self._backlash, np.ndarray):
return self._backlash return self._backlash
elif isinstance(self._backlash, list):
return np.array(self._backlash)
elif isinstance(self._backlash, int): elif isinstance(self._backlash, int):
return np.array([self._backlash] * self.n_axes) return np.array([self._backlash] * self.n_axes)
else: else:
return np.array([0] * self.n_axes) return np.array([0] * self.n_axes)
@backlash.setter @backlash.setter
def backlash(self, blsh) -> Optional[np.ndarray]: def backlash(self, blsh):
logging.debug("Setting backlash to %s", (blsh)) logging.debug("Setting backlash to %s", (blsh))
if blsh is None: if blsh is None:
self._backlash = None self._backlash = None
@ -105,7 +107,10 @@ class SangaStage(BaseStage):
def read_settings(self) -> dict: def read_settings(self) -> dict:
"""Return the current settings as a dictionary""" """Return the current settings as a dictionary"""
blsh = self.backlash.tolist() if self.backlash is not None:
blsh = self.backlash.tolist()
else:
blsh = None
config = { config = {
"backlash": {"x": blsh[0], "y": blsh[1], "z": blsh[2]}, "backlash": {"x": blsh[0], "y": blsh[1], "z": blsh[2]},
"settle_time": self.settle_time, "settle_time": self.settle_time,
@ -152,15 +157,21 @@ class SangaStage(BaseStage):
raise ValueError("axis must be one of x, y, or z") raise ValueError("axis must be one of x, y, or z")
# Create the displacement array # Create the displacement array
displacement_array: np.ndarray = np.array([ displacement_array: np.ndarray = np.array(
displacement if axis == "x" else 0, [
displacement if axis == "y" else 0, displacement if axis == "x" else 0,
displacement if axis == "z" else 0, displacement if axis == "y" else 0,
]) displacement if axis == "z" else 0,
]
)
else: elif isinstance(displacement, np.ndarray):
displacement_array = displacement
elif isinstance(displacement, (list, tuple, GeneratorType)):
# Convert our displacement tuple/generator into a numpy array # Convert our displacement tuple/generator into a numpy array
displacement_array = np.array(list(displacement)) displacement_array = np.array(list(displacement))
else:
raise TypeError(f"Unsupported displacement type {type(displacement)}")
# Calculate main movement # Calculate main movement
initial_move: np.ndarray = displacement_array initial_move: np.ndarray = displacement_array