def test_strip_number_suffix(self):
self.assertEquals(fut.strip_number_suffix('abc123'), 'abc')
self.assertEquals(fut.strip_number_suffix('12345'), '')
self.assertEquals(fut.strip_number_suffix('9'), '')
self.assertEquals(fut.strip_number_suffix('hello'), 'hello')
self.assertEquals(fut.strip_number_suffix('12AB34'), '12AB')
self.assertEquals(fut.strip_number_suffix(''), '')
self.assertEquals(fut.strip_number_suffix('hello_'), 'hello')
self.assertEquals(fut.strip_number_suffix('abc_123'), 'abc')
self.assertEquals(fut.strip_number_suffix('12AB_34'), '12AB')
self.assertEquals(fut.strip_number_suffix('_'), '')
def test_strip_number_suffix(self):
self.assertEquals(fut.strip_number_suffix('abc123'), 'abc')
self.assertEquals(fut.strip_number_suffix('12345'), '')
self.assertEquals(fut.strip_number_suffix('9'), '')
self.assertEquals(fut.strip_number_suffix('hello'), 'hello')
self.assertEquals(fut.strip_number_suffix('12AB34'), '12AB')
self.assertEquals(fut.strip_number_suffix(''), '')
self.assertEquals(fut.strip_number_suffix('hello_'), 'hello')
self.assertEquals(fut.strip_number_suffix('abc_123'), 'abc')
self.assertEquals(fut.strip_number_suffix('12AB_34'), '12AB')
self.assertEquals(fut.strip_number_suffix('_'), '')
def create_filter(self,
param_dict_or_ftype,
pipeline=None): # TO-DO Break this up <<<<<<<<<<<<
"""Extract the right filter dictionary from the factory_dict.
Store a reference in the object to the factory that made it.
Pass in the filter_attrs so the new object has right attributes.
Alternative parameter is just the ftype.
Dictionary validation is enforced before the first use.
TO-DO: pipeline is (a str? an object? required??)
"""
if not self._filter_dict_validated:
self._validate_filter_dict()
# TO-DO: update these comments
# If the filter isn't typed explicitly by the param dict, give
# it an ftype that is the name, with any trailing digits
# removed (necessary because there are more than one of that type.)
# Simple use of make_filter() is by passing in the ftype
try:
param_dict_or_ftype + ''
ftype = param_dict_or_ftype
param_dict = dict(ftype=ftype)
except TypeError:
param_dict = param_dict_or_ftype
# Search for filter in pypes directory first. This overrides any
# programmatically defined filters/pipelines.
## if param_dict.get('_name') in pypes:
ftype_or_name = param_dict.get('ftype',
param_dict.get('_name', ''))
if ftype_or_name.startswith('pype_'):
## ftype = param_dict['_name'][5:]
ftype = ftype_or_name[5:]
param_dict['ftype'] = ftype
try:
filter_attrs = dict(_class=ppln.PipelineForPypes,
config=self.pypes[ftype])
except KeyError:
msg = 'Filter type "%s" not found in the pypes directory'
raise dfb.FilterNameError, msg % ftype
else:
# Use explicit ftype setting in config if available.
# Otherwise, try to read the filter type from the name.
try:
ftype = param_dict['ftype']
except KeyError:
# Break up the name into parts separated by '_'. Strip off
# parts from the right-hand side, until we find a valid
# ftype.
short_name = fut.strip_number_suffix(param_dict['_name'])
name_parts = short_name.split('_')
for j in xrange(len(name_parts), 0, -1):
ftype = '_'.join(name_parts[:j])
if ftype in self.factory_dict:
break
else:
### Last chance before giving up -- is it in pypes?
##if param_dict['name'] in pypes:
##ftype = param_dict['name']
##else:
# We can't get the type from the name
msg = 'Can\'t get filter type from "%s"'
raise dfb.FilterError, msg % param_dict['_name']
param_dict['ftype'] = ftype
try:
filter_attrs = copy.copy(self.factory_dict[ftype])
except KeyError:
# Make a pipeline with this config.
try:
filter_attrs = dict(_class=ppln.PipelineForPypes,
config=self.pypes[ftype])
except KeyError:
msg = 'Filter type "%s" not found in the filter ' + \
'factory class map dictionary'
raise dfb.FilterNameError, msg % ftype
# !! If create_filter receives a string, the except clause isn't
# executed so filter_attrs isn't defined.
filter_attrs['factory'] = self
filter_attrs['pipeline'] = pipeline
# Update the dictionary so far with the parameters passed in.
filter_attrs.update(param_dict)
# Everything is now in place for the actual creation of the filter
class_to_create = filter_attrs['_class']
# If the config for this filter has dynamic == True, use metaclass
## if filter_attrs.get('dynamic', False) == 'meta':
if filter_attrs.get('dynamic', False):
class_to_create2 = dfb.DynamicMetaClass(
'DynMeta' + class_to_create.__name__, (class_to_create, ), {})
else:
class_to_create2 = class_to_create
new_filter = class_to_create2(**filter_attrs)
# Filter has now been made
# Reversible dynamic approach doesn't work.
### If config file for filter has set 'dynamic', use reversible method
### to make it dynamic. Note the need to test equality with True, because
### of the option for the value to be 'meta'.
##if filter_attrs.get('dynamic', False) == True:
##new_filter.make_dynamic(True)
if new_filter.name != new_filter.name.lower():
raise dfb.FilterError, 'Filter name "%s" is not lower case' % (
new_filter.name)
# Check the ftype made matches the request
try:
type_made = new_filter.__class__.ftype # OK for filter
except AttributeError:
type_made = new_filter.ftype # For pipeline
# TO-DO Replace ftype check, which fails when making external pype:
# e.g. 'align_supf' != 'p0001_align_supf'
# Bad overloading of ftype.
#if type_made != ftype:
#msg = 'Filter type requested was "%s", but "%s" was made'
#raise dfb.FilterAttributeError, msg % (ftype,
#new_filter.__class__.ftype)
return new_filter
def create_filter(self, param_dict_or_ftype, pipeline=None): # TO-DO Break this up <<<<<<<<<<<<
"""Extract the right filter dictionary from the factory_dict.
Store a reference in the object to the factory that made it.
Pass in the filter_attrs so the new object has right attributes.
Alternative parameter is just the ftype.
Dictionary validation is enforced before the first use.
TO-DO: pipeline is (a str? an object? required??)
"""
if not self._filter_dict_validated:
self._validate_filter_dict()
# TO-DO: update these comments
# If the filter isn't typed explicitly by the param dict, give
# it an ftype that is the name, with any trailing digits
# removed (necessary because there are more than one of that type.)
# Simple use of make_filter() is by passing in the ftype
try:
param_dict_or_ftype + ''
ftype = param_dict_or_ftype
param_dict = dict(ftype=ftype)
except TypeError:
param_dict = param_dict_or_ftype
# Search for filter in pypes directory first. This overrides any
# programmatically defined filters/pipelines.
## if param_dict.get('_name') in pypes:
ftype_or_name = param_dict.get('ftype', param_dict.get('_name', ''))
if ftype_or_name.startswith('pype_'):
## ftype = param_dict['_name'][5:]
ftype = ftype_or_name[5:]
param_dict['ftype'] = ftype
try:
filter_attrs = dict(_class=ppln.PipelineForPypes,
config=self.pypes[ftype])
except KeyError:
msg = 'Filter type "%s" not found in the pypes directory'
raise dfb.FilterNameError, msg % ftype
else:
# Use explicit ftype setting in config if available.
# Otherwise, try to read the filter type from the name.
try:
ftype = param_dict['ftype']
except KeyError:
# Break up the name into parts separated by '_'. Strip off
# parts from the right-hand side, until we find a valid
# ftype.
short_name = fut.strip_number_suffix(param_dict['_name'])
name_parts = short_name.split('_')
for j in xrange(len(name_parts), 0, -1):
ftype = '_'.join(name_parts[:j])
if ftype in self.factory_dict:
break
else:
### Last chance before giving up -- is it in pypes?
##if param_dict['name'] in pypes:
##ftype = param_dict['name']
##else:
# We can't get the type from the name
msg = 'Can\'t get filter type from "%s"'
raise dfb.FilterError, msg % param_dict['_name']
param_dict['ftype'] = ftype
try:
filter_attrs = copy.copy(self.factory_dict[ftype])
except KeyError:
# Make a pipeline with this config.
try:
filter_attrs = dict(_class=ppln.PipelineForPypes,
config=self.pypes[ftype])
except KeyError:
msg = 'Filter type "%s" not found in the filter ' + \
'factory class map dictionary'
raise dfb.FilterNameError, msg % ftype
# !! If create_filter receives a string, the except clause isn't
# executed so filter_attrs isn't defined.
filter_attrs['factory'] = self
filter_attrs['pipeline'] = pipeline
# Update the dictionary so far with the parameters passed in.
filter_attrs.update(param_dict)
# Everything is now in place for the actual creation of the filter
class_to_create = filter_attrs['_class']
# If the config for this filter has dynamic == True, use metaclass
## if filter_attrs.get('dynamic', False) == 'meta':
if filter_attrs.get('dynamic', False):
class_to_create2 = dfb.DynamicMetaClass(
'DynMeta' + class_to_create.__name__,
(class_to_create,), {})
else:
class_to_create2 = class_to_create
new_filter = class_to_create2(**filter_attrs)
# Filter has now been made
# Reversible dynamic approach doesn't work.
### If config file for filter has set 'dynamic', use reversible method
### to make it dynamic. Note the need to test equality with True, because
### of the option for the value to be 'meta'.
##if filter_attrs.get('dynamic', False) == True:
##new_filter.make_dynamic(True)
if new_filter.name != new_filter.name.lower():
raise dfb.FilterError, 'Filter name "%s" is not lower case' % (
new_filter.name)
# Check the ftype made matches the request
try:
type_made = new_filter.__class__.ftype # OK for filter
except AttributeError:
type_made = new_filter.ftype # For pipeline
# TO-DO Replace ftype check, which fails when making external pype:
# e.g. 'align_supf' != 'p0001_align_supf'
# Bad overloading of ftype.
#if type_made != ftype:
#msg = 'Filter type requested was "%s", but "%s" was made'
#raise dfb.FilterAttributeError, msg % (ftype,
#new_filter.__class__.ftype)
return new_filter
