diff --git a/devices/clients/attribute_wrapper.py b/devices/clients/attribute_wrapper.py
index 397f11e0bcc437e82699a472c5f2a297f0e5c2e4..12e5c83516e2c68c2216aca5ba9b39a1fa6f4f8c 100644
--- a/devices/clients/attribute_wrapper.py
+++ b/devices/clients/attribute_wrapper.py
@@ -9,156 +9,156 @@ logger = logging.getLogger()
class attribute_wrapper(attribute):
- """
- Wraps all the attributes in a wrapper class to manage most of the redundant code behind the scenes
- """
-
- def __init__(self, comms_id=None, comms_annotation=None, datatype=None, dims=(1,), access=AttrWriteType.READ, init_value=None, **kwargs):
- """
- wraps around the tango Attribute class. Provides an easier interface for 1d or 2d arrays. Also provides a way to abstract
- managing the communications interface.
-
- comms_id: user-supplied identifier that is attached to this object, to identify which communication class will need to be attached
- comms_annotation: data passed along to the attribute. can be given any form of data. handling is up to client implementation
- datatype: any numpy datatype
- dims: dimensions of the attribute as a tuple, or (1,) for a scalar.
- init_value: value
- """
-
- # ensure the type is a numpy array.
- # see also https://pytango.readthedocs.io/en/stable/server_api/server.html?highlight=devlong#module-tango.server for
- # more details about type conversion Python/numpy -> PyTango
- if "numpy" not in str(datatype) and datatype != str:
- raise TypeError("Attribute needs to be a Tango-supported numpy or str type, but has type \"%s\"" % (datatype,))
-
- self.comms_id = comms_id # store data that can be used to identify the comms interface to use. not used by the wrapper itself
- self.comms_annotation = comms_annotation # store data that can be used by the comms interface. not used by the wrapper itself
-
- self.init_value = init_value
- is_scalar = dims == (1,)
-
- # tango doesn't recognise numpy.str_, for consistencies sake we convert it here and hide this from the top level
- # NOTE: discuss, idk if this is an important detail somewhere else
- if datatype is numpy.str_ or datatype is numpy.str:
- datatype = str
-
- self.numpy_type = datatype # tango changes our attribute to their representation (E.g numpy.int64 becomes "DevLong64")
-
- # check if not scalar
- if is_scalar:
- # scalar, just set the single dimension.
- # Tango defines a scalar as having dimensions (1,0), see https://pytango.readthedocs.io/en/stable/server_api/attribute.html
- max_dim_x = 1
- max_dim_y = 0
- else:
- # get first dimension
- max_dim_x = dims[0]
-
- # single dimension/spectrum requires the datatype to be wrapped in a tuple
- datatype = (datatype,)
-
- if len(dims) == 2:
- # get second dimension
- max_dim_y = dims[1]
- # wrap the datatype tuple in another tuple for 2d arrays/images
- datatype = (datatype,)
- else:
- max_dim_y = 0
-
- if access == AttrWriteType.READ_WRITE:
- """ if the attribute is of READ_WRITE type, assign the RW and write function to it"""
-
- @only_when_on()
- @fault_on_error()
- def read_RW(device):
- # print("read_RW {}, {}x{}, {}, {}".format(me.name, me.dim_x, me.dim_y, me.attr_type, me.value))
- """
- read_RW returns the value that was last written to the attribute
- """
- try:
- return device.value_dict[self]
- except Exception as e:
- raise Exception("Attribute read_RW function error, attempted to read value_dict with key: `%s`, are you sure this exists?",
- self) from e
-
- @only_when_on()
- @fault_on_error()
- def write_RW(device, value):
- """
- _write_RW writes a value to this attribute
- """
-
- self.write_function(value)
- device.value_dict[self] = value
-
- self.fget = read_RW
- self.fset = write_RW
-
-
- else:
- """ if the attribute is of READ type, assign the read function to it"""
-
- @only_when_on()
- @fault_on_error()
- def read_R(device):
- """
- _read_R reads the attribute value, stores it and returns it"
- """
- device.value_dict[self] = self.read_function()
- return device.value_dict[self]
-
- self.fget = read_R
-
- super().__init__(dtype=datatype, max_dim_y=max_dim_y, max_dim_x=max_dim_x, access=access, **kwargs)
-
- return
-
- def initial_value(self):
- """
- returns a numpy array filled with zeroes fit to the size of the attribute. Or if init_value is not the default None, return that value
- """
- if self.init_value is not None:
- return self.init_value
-
- if self.dim_y > 1:
- dims = (self.dim_x, self.dim_y)
- else:
- dims = (self.dim_x,)
-
- # x and y are swapped for numpy and Tango. to maintain tango conventions, x and y are swapped for numpy
- if len(dims) == 2:
- numpy_dims = tuple((dims[1], dims[0]))
- else:
- numpy_dims = dims
-
- if self.dim_x == 1:
-
- if self.numpy_type == str:
- value = ''
- else:
- value = self.numpy_type(0)
- else:
- value = numpy.zeros(numpy_dims, dtype=self.numpy_type)
-
- return value
-
- def set_comm_client(self, client):
- """
- takes a communications client as input arguments This client should be of a class containing a "get_mapping" function
- and return a read and write function that the wrapper will use to get/set data.
- """
- try:
- self.read_function, self.write_function = client.setup_attribute(self.comms_annotation, self)
- except Exception as e:
-
- logger.error("Exception while setting {} attribute with annotation: '{}' {}".format(client.__class__.__name__, self.comms_annotation, e))
- raise Exception("Exception while setting %s attribute with annotation: '%s'", client.__class__.__name__, self.comms_annotation) from e
-
- def set_pass_func(self):
- def pass_func(value=None):
- pass
-
- logger.debug("using pass function for attribute with annotation: {}".format(self.comms_annotation))
-
- self.read_function = pass_func
- self.write_function = pass_func
+ """
+ Wraps all the attributes in a wrapper class to manage most of the redundant code behind the scenes
+ """
+
+ def __init__(self, comms_id=None, comms_annotation=None, datatype=None, dims=(1,), access=AttrWriteType.READ, init_value=None, **kwargs):
+ """
+ wraps around the tango Attribute class. Provides an easier interface for 1d or 2d arrays. Also provides a way to abstract
+ managing the communications interface.
+
+ comms_id: user-supplied identifier that is attached to this object, to identify which communication class will need to be attached
+ comms_annotation: data passed along to the attribute. can be given any form of data. handling is up to client implementation
+ datatype: any numpy datatype
+ dims: dimensions of the attribute as a tuple, or (1,) for a scalar.
+ init_value: value
+ """
+
+ # ensure the type is a numpy array.
+ # see also https://pytango.readthedocs.io/en/stable/server_api/server.html?highlight=devlong#module-tango.server for
+ # more details about type conversion Python/numpy -> PyTango
+ if "numpy" not in str(datatype) and datatype != str:
+ raise TypeError("Attribute needs to be a Tango-supported numpy or str type, but has type \"%s\"" % (datatype,))
+
+ self.comms_id = comms_id # store data that can be used to identify the comms interface to use. not used by the wrapper itself
+ self.comms_annotation = comms_annotation # store data that can be used by the comms interface. not used by the wrapper itself
+
+ self.init_value = init_value
+ is_scalar = dims == (1,)
+
+ # tango doesn't recognise numpy.str_, for consistencies sake we convert it here and hide this from the top level
+ # NOTE: discuss, idk if this is an important detail somewhere else
+ if datatype is numpy.str_ or datatype is numpy.str:
+ datatype = str
+
+ self.numpy_type = datatype # tango changes our attribute to their representation (E.g numpy.int64 becomes "DevLong64")
+
+ # check if not scalar
+ if is_scalar:
+ # scalar, just set the single dimension.
+ # Tango defines a scalar as having dimensions (1,0), see https://pytango.readthedocs.io/en/stable/server_api/attribute.html
+ max_dim_x = 1
+ max_dim_y = 0
+ else:
+ # get first dimension
+ max_dim_x = dims[0]
+
+ # single dimension/spectrum requires the datatype to be wrapped in a tuple
+ datatype = (datatype,)
+
+ if len(dims) == 2:
+ # get second dimension
+ max_dim_y = dims[1]
+ # wrap the datatype tuple in another tuple for 2d arrays/images
+ datatype = (datatype,)
+ else:
+ max_dim_y = 0
+
+ if access == AttrWriteType.READ_WRITE:
+ """ if the attribute is of READ_WRITE type, assign the RW and write function to it"""
+
+ @only_when_on()
+ @fault_on_error()
+ def read_RW(device):
+ # print("read_RW {}, {}x{}, {}, {}".format(me.name, me.dim_x, me.dim_y, me.attr_type, me.value))
+ """
+ read_RW returns the value that was last written to the attribute
+ """
+ try:
+ return device.value_dict[self]
+ except Exception as e:
+ raise Exception("Attribute read_RW function error, attempted to read value_dict with key: `%s`, are you sure this exists?",
+ self) from e
+
+ @only_when_on()
+ @fault_on_error()
+ def write_RW(device, value):
+ """
+ _write_RW writes a value to this attribute
+ """
+
+ self.write_function(value)
+ device.value_dict[self] = value
+
+ self.fget = read_RW
+ self.fset = write_RW
+
+
+ else:
+ """ if the attribute is of READ type, assign the read function to it"""
+
+ @only_when_on()
+ @fault_on_error()
+ def read_R(device):
+ """
+ _read_R reads the attribute value, stores it and returns it"
+ """
+ device.value_dict[self] = self.read_function()
+ return device.value_dict[self]
+
+ self.fget = read_R
+
+ super().__init__(dtype=datatype, max_dim_y=max_dim_y, max_dim_x=max_dim_x, access=access, **kwargs)
+
+ return
+
+ def initial_value(self):
+ """
+ returns a numpy array filled with zeroes fit to the size of the attribute. Or if init_value is not the default None, return that value
+ """
+ if self.init_value is not None:
+ return self.init_value
+
+ if self.dim_y > 1:
+ dims = (self.dim_x, self.dim_y)
+ else:
+ dims = (self.dim_x,)
+
+ # x and y are swapped for numpy and Tango. to maintain tango conventions, x and y are swapped for numpy
+ if len(dims) == 2:
+ numpy_dims = tuple((dims[1], dims[0]))
+ else:
+ numpy_dims = dims
+
+ if self.dim_x == 1:
+
+ if self.numpy_type == str:
+ value = ''
+ else:
+ value = self.numpy_type(0)
+ else:
+ value = numpy.zeros(numpy_dims, dtype=self.numpy_type)
+
+ return value
+
+ def set_comm_client(self, client):
+ """
+ takes a communications client as input arguments This client should be of a class containing a "get_mapping" function
+ and return a read and write function that the wrapper will use to get/set data.
+ """
+ try:
+ self.read_function, self.write_function = client.setup_attribute(self.comms_annotation, self)
+ except Exception as e:
+
+ logger.error("Exception while setting {} attribute with annotation: '{}' {}".format(client.__class__.__name__, self.comms_annotation, e))
+ raise Exception("Exception while setting %s attribute with annotation: '%s'", client.__class__.__name__, self.comms_annotation) from e
+
+ def set_pass_func(self):
+ def pass_func(value=None):
+ pass
+
+ logger.debug("using pass function for attribute with annotation: {}".format(self.comms_annotation))
+
+ self.read_function = pass_func
+ self.write_function = pass_func