mirror of
https://github.com/slsdetectorgroup/slsDetectorPackage.git
synced 2025-04-20 02:40:03 +02:00
118 lines
3.3 KiB
Python
Executable File
118 lines
3.3 KiB
Python
Executable File
# SPDX-License-Identifier: LGPL-3.0-or-other
|
|
# Copyright (C) 2021 Contributors to the SLS Detector Package
|
|
from .detector_property import DetectorProperty
|
|
from functools import partial
|
|
import numpy as np
|
|
import _slsdet
|
|
from .detector import freeze
|
|
dacIndex = _slsdet.slsDetectorDefs.dacIndex
|
|
class Dac(DetectorProperty):
|
|
"""
|
|
This class represents a dac on the detector. One instance handles all
|
|
dacs with the same name for a multi detector instance.
|
|
|
|
.. note ::
|
|
|
|
This class is used to build up DetectorDacs and is in general
|
|
not directly accessed to the user.
|
|
|
|
|
|
"""
|
|
def __init__(self, name, enum, low, high, default, detector):
|
|
|
|
super().__init__(partial(detector.getDAC, enum, False),
|
|
lambda x, y : detector.setDAC(enum, x, False, y),
|
|
detector.size,
|
|
name)
|
|
|
|
self.min_value = low
|
|
self.max_value = high
|
|
self.default = default
|
|
|
|
|
|
|
|
def __repr__(self):
|
|
"""String representation for a single dac in all modules"""
|
|
dacstr = ''.join([f'{item:5d}' for item in self.get()])
|
|
return f'{self.__name__:15s}:{dacstr}'
|
|
|
|
|
|
class DetectorDacs:
|
|
_dacs = []
|
|
_dacnames = [_d[0] for _d in _dacs]
|
|
_allowed_attr = ['_detector', '_current']
|
|
_frozen = False
|
|
|
|
def __init__(self, detector):
|
|
# We need to at least initially know which detector we are connected to
|
|
self._detector = detector
|
|
|
|
# Index to support iteration
|
|
self._current = 0
|
|
|
|
# Populate the dacs
|
|
for _d in self._dacs:
|
|
setattr(self, '_'+_d[0], Dac(*_d, detector))
|
|
|
|
self._frozen = True
|
|
|
|
def __getattr__(self, name):
|
|
return self.__getattribute__('_' + name)
|
|
|
|
|
|
def __setattr__(self, name, value):
|
|
if name in self._dacnames:
|
|
return self.__getattribute__('_' + name).__setitem__(slice(None, None, None), value)
|
|
else:
|
|
if self._frozen == True and name not in self._allowed_attr:
|
|
raise AttributeError(f'Dac not found: {name}')
|
|
super().__setattr__(name, value)
|
|
|
|
|
|
def __next__(self):
|
|
if self._current >= len(self._dacs):
|
|
self._current = 0
|
|
raise StopIteration
|
|
else:
|
|
self._current += 1
|
|
return self.__getattr__(self._dacnames[self._current-1])
|
|
|
|
def __iter__(self):
|
|
return self
|
|
|
|
def __repr__(self):
|
|
r_str = ['========== DACS =========']
|
|
r_str += [repr(dac) for dac in self]
|
|
return '\n'.join(r_str)
|
|
|
|
def get_asarray(self):
|
|
"""
|
|
Read the dacs into a numpy array with dimensions [ndacs, nmodules]
|
|
"""
|
|
dac_array = np.zeros((len(self._dacs), len(self._detector)))
|
|
for i, _d in enumerate(self):
|
|
dac_array[i,:] = _d[:]
|
|
return dac_array
|
|
|
|
def to_array(self):
|
|
return self.get_asarray()
|
|
|
|
def set_from_array(self, dac_array):
|
|
"""
|
|
Set the dacs from an numpy array with dac values. [ndacs, nmodules]
|
|
"""
|
|
dac_array = dac_array.astype(np.int)
|
|
for i, _d in enumerate(self):
|
|
_d[:] = dac_array[i]
|
|
|
|
def from_array(self, dac_array):
|
|
self.set_from_array(dac_array)
|
|
|
|
def set_default(self):
|
|
"""
|
|
Set all dacs to their default values
|
|
"""
|
|
for _d in self:
|
|
_d[:] = _d.default
|
|
|