#!/usr/bin/env python3.8
# coding: latin-1
# (c) Massachusetts Institute of Technology 2015-2018
# (c) Brian Teague 2018-2022
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
cytoflow.utility.custom_traits
------------------------------
Custom traits for `cytoflow`
`PositiveInt`, `PositiveFloat` -- versions of `traits.trait_types.Int` and `traits.trait_types.Float` that must be
positive (and optionally 0).
`PositiveCInt`, `PositiveCFloat` -- versions of `traits.trait_types.CInt`, `traits.trait_types.CFloat` that must
be positive (and optionally 0).
`IntOrNone`, `FloatOrNone` -- versions of `traits.trait_types.Int` and `traits.trait_types.Float` that may also
hold the value ``None``.
`CIntOrNone`, `CFloatOrNone` -- versions of `traits.trait_types.CInt` and `traits.trait_types.CFloat` that may also
hold the value ``None``.
`ScaleEnum` -- an enumeration whose value is one of the registered scales.
`Removed` -- a trait that was present in a previous version but was removed.
`Deprecated` -- a trait that was present in a previous version but was renamed.
"""
from warnings import warn
import inspect
from traits.api import (BaseInt, BaseCInt, BaseFloat, BaseCFloat, BaseEnum, TraitType)
from . import scale
from . import CytoflowError, CytoflowWarning
import cytoflow
[docs]class PositiveInt(BaseInt):
"""
Defines a trait whose value must be a positive integer
"""
info_text = 'a positive integer'
[docs] def validate(self, obj, name, value):
if self.allow_none and value == None:
return None
value = super().validate(obj, name, value)
if (value > 0 or (self.allow_zero and value >= 0)):
return value
self.error(obj, name, value)
[docs]class PositiveCInt(BaseCInt):
"""
Defines a trait whose converted value must be a positive integer
"""
info_text = 'a positive integer'
[docs] def validate(self, obj, name, value):
if self.allow_none and (value == "" or value == None):
return None
value = super().validate(obj, name, value)
if (value > 0 or (self.allow_zero and value >= 0)):
return value
self.error(obj, name, value)
[docs]class PositiveFloat(BaseFloat):
"""
Defines a trait whose value must be a positive float
"""
info_text = 'a positive float'
[docs] def validate(self, obj, name, value):
if self.allow_none and value == None:
return None
value = super().validate(obj, name, value)
if (value > 0.0 or (self.allow_zero and value >= 0.0)):
return value
self.error(obj, name, value)
[docs]class PositiveCFloat(BaseCFloat):
"""
Defines a trait whose converted value must be a positive float
"""
info_text = 'a positive float'
[docs] def validate(self, obj, name, value):
if self.allow_none and (value == "" or value == None):
return None
value = super().validate(obj, name, value)
if (value > 0.0 or (self.allow_zero and value >= 0.0)):
return value
self.error(obj, name, value)
[docs]class FloatOrNone(BaseFloat):
"""
Defines a trait whose value must be a float or None
"""
info_text = 'a float or None'
[docs] def validate(self, obj, name, value):
if value == "" or value == None:
return None
else:
return super().validate(obj, name, value)
[docs]class CFloatOrNone(BaseCFloat):
"""
Defines a trait whose converted value must be a float or None
"""
info_text = 'a float or None'
[docs] def validate(self, obj, name, value):
if value == None or value == "":
return None
else:
return super().validate(obj, name, value)
[docs]class IntOrNone(BaseInt):
"""
Defines a trait whose value must be an integer or None
"""
info_text = 'an int or None'
[docs] def validate(self, obj, name, value):
if value == None:
return None
else:
return super().validate(obj, name, value)
[docs]class CIntOrNone(BaseCInt):
"""
Defines a trait whose converted value must be an integer or None
"""
info_text = 'an int or None'
[docs] def validate(self, obj, name, value):
if value == None or value == "":
return None
else:
return super().validate(obj, name, value)
[docs]class ScaleEnum(BaseEnum):
"""
Defines an enumeration that contains one of the registered data scales
"""
info_text = 'an enum containing one of the registered scales'
def __init__ ( self, *args, **metadata ):
""" Returns an Enum trait with values from the registered scales
"""
self.name = None
self.values = list(scale._scale_mapping.keys())
super(BaseEnum, self).__init__(scale._scale_default, **metadata )
[docs] def get_default_value(self):
# this is so silly. get_default_value is ... called once? as traits
# sets up? idunno. anyways, instead of returning _scale_default, we
# need to return a reference to a function that returns _scale_default.
return (7, (self._get_default_value, (), None))
def _get_default_value(self):
return scale._scale_default
[docs]class Removed(TraitType):
"""
Names a trait that was present in a previous version but was removed.
Trait metadata:
- **err_string** : the error string in the error
- **gui** : if ``True``, don't return a backtrace (because it's very slow)
- **warning** : if ``True``, raise a warning when the trait is referenced.
Otherwise, raise an exception.
"""
def __init__(self, **metadata):
metadata.setdefault('err_string', 'Trait {} has been removed')
metadata.setdefault('transient', True)
super().__init__(**metadata)
[docs] def get(self, obj, name):
if not cytoflow.RUNNING_IN_GUI:
# TODO - this is quite slow. come up with a better way.
curframe = inspect.currentframe()
calframe = inspect.getouterframes(curframe)
if calframe[1][3] == "copy_traits" or calframe[1][3] == "trait_get":
return
if self.warning:
warn(self.err_string.format(name), CytoflowWarning)
else:
raise CytoflowError(self.err_string.format(name))
[docs] def set(self, obj, name, value):
if not cytoflow.RUNNING_IN_GUI:
curframe = inspect.currentframe()
calframe = inspect.getouterframes(curframe, 2)
if calframe[1][3] == "copy_traits":
return
if self.warning:
warn(self.err_string.format(name), CytoflowWarning)
else:
raise CytoflowError(self.err_string.format(name))
[docs]class Deprecated(TraitType):
"""
Names a trait that was present in a previous version but was renamed.
When the trait is accessed, a warning is raised, and the access
is passed through to the new trait.
Trait metadata:
- **new** : the name of the new trait
- **err_string** : the error string in the error
- **gui** : if ``True``, don't return a backtrace (because it's very slow)
"""
def __init__(self, **metadata):
metadata.setdefault('err_string', 'Trait {} is deprecated; please use {}')
metadata.setdefault('transient', True)
super().__init__(**metadata)
[docs] def get(self, obj, name):
if not cytoflow.RUNNING_IN_GUI:
curframe = inspect.currentframe()
calframe = inspect.getouterframes(curframe)
if calframe[1][3] != "copy_traits" and calframe[1][3] != 'trait_get':
warn(self.err_string.format(name, self.new), CytoflowWarning)
return getattr(obj, self.new)
[docs] def set(self, obj, name, value):
if not cytoflow.RUNNING_IN_GUI:
curframe = inspect.currentframe()
calframe = inspect.getouterframes(curframe)
if calframe[1][3] != "copy_traits":
warn(self.err_string.format(name, self.new), CytoflowWarning)
setattr(obj, self.new, value)