mirror of
https://github.com/gsi-upm/senpy
synced 2024-12-23 13:38:12 +00:00
Refactored conversion and postprocessing
This commit is contained in:
J. Fernando Sánchez
parent
b48730137d
commit
41aa142ce0
35
senpy/api.py
35
senpy/api.py
@ -3,10 +3,8 @@ from .models import Error, Results, Entry, from_string
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import logging
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logger = logging.getLogger(__name__)
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boolean = [True, False]
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API_PARAMS = {
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"algorithm": {
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"aliases": ["algorithms", "a", "algo"],
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@ -140,6 +138,15 @@ NIF_PARAMS = {
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}
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}
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BUILTIN_PARAMS = {}
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for d in [
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NIF_PARAMS, CLI_PARAMS, WEB_PARAMS, PLUGINS_PARAMS, EVAL_PARAMS,
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API_PARAMS
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]:
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for k, v in d.items():
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BUILTIN_PARAMS[k] = v
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def parse_params(indict, *specs):
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if not specs:
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@ -164,7 +171,7 @@ def parse_params(indict, *specs):
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continue
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if "options" in options:
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if options["options"] == boolean:
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outdict[param] = outdict[param] in [None, True, 'true', '1']
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outdict[param] = str(outdict[param]).lower() in ['true', '1']
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elif outdict[param] not in options["options"]:
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wrong_params[param] = spec[param]
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if wrong_params:
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@ -180,11 +187,19 @@ def parse_params(indict, *specs):
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return outdict
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def parse_extra_params(request, plugin=None):
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def parse_extra_params(request, plugins=None):
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plugins = plugins or []
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params = request.parameters.copy()
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if plugin:
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extra_params = parse_params(params, plugin.get('extra_params', {}))
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params.update(extra_params)
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for plugin in plugins:
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if plugin:
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extra_params = parse_params(params, plugin.get('extra_params', {}))
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for k, v in extra_params.items():
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if k not in BUILTIN_PARAMS:
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if k in params: # Set by another plugin
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del params[k]
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else:
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params[k] = v
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params['{}.{}'.format(plugin.name, k)] = v
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return params
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@ -194,12 +209,12 @@ def parse_call(params):
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params = parse_params(params, NIF_PARAMS)
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if params['informat'] == 'text':
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results = Results()
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entry = Entry(nif__isString=params['input'],
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id='#') # Use @base
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entry = Entry(nif__isString=params['input'], id='#') # Use @base
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results.entries.append(entry)
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elif params['informat'] == 'json-ld':
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results = from_string(params['input'], cls=Results)
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else: # pragma: no cover
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raise NotImplementedError('Informat {} is not implemented'.format(params['informat']))
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raise NotImplementedError('Informat {} is not implemented'.format(
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params['informat']))
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results.parameters = params
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return results
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@ -197,7 +197,9 @@ def api_root(plugin):
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plugin = plugin.replace('+', '/')
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plugin = plugin.split('/')
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req.parameters['algorithm'] = tuple(plugin)
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return current_app.senpy.analyse(req)
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results = current_app.senpy.analyse(req)
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results.analysis = set(i.id for i in results.analysis)
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return results
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@api_blueprint.route('/evaluate/', methods=['POST', 'GET'])
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@ -6,7 +6,6 @@ from future import standard_library
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standard_library.install_aliases()
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from . import plugins, api
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from .plugins import Plugin, evaluate
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from .models import Error, AggregatedEvaluation
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from .blueprints import api_blueprint, demo_blueprint, ns_blueprint
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@ -17,7 +16,6 @@ import copy
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import errno
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import logging
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from . import gsitk_compat
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logger = logging.getLogger(__name__)
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@ -25,6 +23,7 @@ logger = logging.getLogger(__name__)
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class Senpy(object):
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""" Default Senpy extension for Flask """
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def __init__(self,
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app=None,
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plugin_folder=".",
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@ -50,7 +49,7 @@ class Senpy(object):
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self.add_folder('plugins', from_root=True)
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else:
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# Add only conversion plugins
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self.add_folder(os.path.join('plugins', 'conversion'),
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self.add_folder(os.path.join('plugins', 'postprocessing'),
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from_root=True)
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self.app = app
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if app is not None:
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@ -115,6 +114,7 @@ class Senpy(object):
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raise AttributeError("Not a folder or does not exist: %s", folder)
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def _get_plugins(self, request):
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'''Get a list of plugins that should be run for a specific request'''
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if not self.analysis_plugins:
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raise Error(
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status=404,
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@ -132,33 +132,32 @@ class Senpy(object):
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plugins = list()
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for algo in algos:
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algo = algo.lower()
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if algo == 'conversion':
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continue # Allow 'conversion' as a virtual plugin, which does nothing
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if algo not in self._plugins:
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msg = ("The algorithm '{}' is not valid\n"
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"Valid algorithms: {}").format(algo,
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self._plugins.keys())
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logger.debug(msg)
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raise Error(
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status=404,
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message=msg)
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raise Error(status=404, message=msg)
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plugins.append(self._plugins[algo])
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return plugins
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def _process_entries(self, entries, req, plugins):
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def _process(self, req, pending, done=None):
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"""
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Recursively process the entries with the first plugin in the list, and pass the results
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to the rest of the plugins.
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"""
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if not plugins:
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for i in entries:
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yield i
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return
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plugin = plugins[0]
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specific_params = api.parse_extra_params(req, plugin)
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req.analysis.append({'plugin': plugin,
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'parameters': specific_params})
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results = plugin.analyse_entries(entries, specific_params)
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for i in self._process_entries(results, req, plugins[1:]):
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yield i
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done = done or []
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if not pending:
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return req
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plugin = pending[0]
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results = plugin.process(req, conversions_applied=done)
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if plugin not in results.analysis:
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results.analysis.append(plugin)
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return self._process(results, pending[1:], done)
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def install_deps(self):
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plugins.install_deps(*self.plugins())
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@ -170,17 +169,88 @@ class Senpy(object):
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by api.parse_call().
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"""
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logger.debug("analysing request: {}".format(request))
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entries = request.entries
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request.entries = []
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plugins = self._get_plugins(request)
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results = request
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for i in self._process_entries(entries, results, plugins):
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results.entries.append(i)
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self.convert_emotions(results)
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logger.debug("Returning analysis result: {}".format(results))
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results.analysis = [i['plugin'].id for i in results.analysis]
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request.parameters = api.parse_extra_params(request, plugins)
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results = self._process(request, plugins)
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logger.debug("Got analysis result: {}".format(results))
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results = self.postprocess(results)
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logger.debug("Returning post-processed result: {}".format(results))
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return results
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def convert_emotions(self, resp):
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"""
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Conversion of all emotions in a response **in place**.
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In addition to converting from one model to another, it has
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to include the conversion plugin to the analysis list.
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Needless to say, this is far from an elegant solution, but it works.
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@todo refactor and clean up
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"""
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plugins = resp.analysis
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params = resp.parameters
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toModel = params.get('emotionModel', None)
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if not toModel:
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return resp
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logger.debug('Asked for model: {}'.format(toModel))
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output = params.get('conversion', None)
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candidates = {}
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for plugin in plugins:
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try:
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fromModel = plugin.get('onyx:usesEmotionModel', None)
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candidates[plugin.id] = next(self._conversion_candidates(fromModel, toModel))
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logger.debug('Analysis plugin {} uses model: {}'.format(
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plugin.id, fromModel))
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except StopIteration:
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e = Error(('No conversion plugin found for: '
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'{} -> {}'.format(fromModel, toModel)),
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status=404)
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e.original_response = resp
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e.parameters = params
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raise e
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newentries = []
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done = []
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for i in resp.entries:
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if output == "full":
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newemotions = copy.deepcopy(i.emotions)
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else:
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newemotions = []
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for j in i.emotions:
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plugname = j['prov:wasGeneratedBy']
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candidate = candidates[plugname]
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done.append({'plugin': candidate, 'parameters': params})
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for k in candidate.convert(j, fromModel, toModel, params):
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k.prov__wasGeneratedBy = candidate.id
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if output == 'nested':
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k.prov__wasDerivedFrom = j
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newemotions.append(k)
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i.emotions = newemotions
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newentries.append(i)
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resp.entries = newentries
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return resp
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def _conversion_candidates(self, fromModel, toModel):
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candidates = self.plugins(plugin_type=plugins.EmotionConversion)
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for candidate in candidates:
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for pair in candidate.onyx__doesConversion:
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logging.debug(pair)
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if candidate.can_convert(fromModel, toModel):
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yield candidate
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def postprocess(self, response):
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'''
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Transform the results from the analysis plugins.
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It has some pre-defined post-processing like emotion conversion,
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and it also allows plugins to auto-select themselves.
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'''
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response = self.convert_emotions(response)
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for plug in self.plugins(plugin_type=plugins.PostProcessing):
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if plug.check(response, response.analysis):
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response = plug.process(response)
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return response
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def _get_datasets(self, request):
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if not self.datasets:
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raise Error(
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@ -191,8 +261,8 @@ class Senpy(object):
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for dataset in datasets_name:
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if dataset not in self.datasets:
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logger.debug(("The dataset '{}' is not valid\n"
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"Valid datasets: {}").format(dataset,
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self.datasets.keys()))
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"Valid datasets: {}").format(
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dataset, self.datasets.keys()))
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raise Error(
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status=404,
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message="The dataset '{}' is not valid".format(dataset))
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@ -219,77 +289,18 @@ class Senpy(object):
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results.parameters = params
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datasets = self._get_datasets(results)
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plugins = self._get_plugins(results)
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for eval in evaluate(plugins, datasets):
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for eval in plugins.evaluate(plugins, datasets):
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results.evaluations.append(eval)
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if 'with_parameters' not in results.parameters:
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del results.parameters
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logger.debug("Returning evaluation result: {}".format(results))
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return results
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def _conversion_candidates(self, fromModel, toModel):
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candidates = self.plugins(plugin_type='emotionConversionPlugin')
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for candidate in candidates:
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for pair in candidate.onyx__doesConversion:
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logging.debug(pair)
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if pair['onyx:conversionFrom'] == fromModel \
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and pair['onyx:conversionTo'] == toModel:
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yield candidate
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def convert_emotions(self, resp):
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"""
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Conversion of all emotions in a response **in place**.
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In addition to converting from one model to another, it has
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to include the conversion plugin to the analysis list.
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Needless to say, this is far from an elegant solution, but it works.
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@todo refactor and clean up
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"""
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plugins = [i['plugin'] for i in resp.analysis]
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params = resp.parameters
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toModel = params.get('emotionModel', None)
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if not toModel:
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return
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logger.debug('Asked for model: {}'.format(toModel))
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output = params.get('conversion', None)
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candidates = {}
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for plugin in plugins:
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try:
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fromModel = plugin.get('onyx:usesEmotionModel', None)
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candidates[plugin.id] = next(self._conversion_candidates(fromModel, toModel))
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logger.debug('Analysis plugin {} uses model: {}'.format(plugin.id, fromModel))
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except StopIteration:
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e = Error(('No conversion plugin found for: '
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'{} -> {}'.format(fromModel, toModel)),
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status=404)
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e.original_response = resp
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e.parameters = params
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raise e
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newentries = []
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for i in resp.entries:
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if output == "full":
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newemotions = copy.deepcopy(i.emotions)
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else:
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newemotions = []
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for j in i.emotions:
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plugname = j['prov:wasGeneratedBy']
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candidate = candidates[plugname]
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resp.analysis.append({'plugin': candidate,
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'parameters': params})
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for k in candidate.convert(j, fromModel, toModel, params):
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k.prov__wasGeneratedBy = candidate.id
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if output == 'nested':
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k.prov__wasDerivedFrom = j
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newemotions.append(k)
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i.emotions = newemotions
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newentries.append(i)
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resp.entries = newentries
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@property
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def default_plugin(self):
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if not self._default or not self._default.is_activated:
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candidates = self.plugins(plugin_type='analysisPlugin',
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is_activated=True)
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candidates = self.plugins(
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plugin_type='analysisPlugin', is_activated=True)
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if len(candidates) > 0:
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self._default = candidates[0]
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else:
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@ -299,7 +310,7 @@ class Senpy(object):
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@default_plugin.setter
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def default_plugin(self, value):
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if isinstance(value, Plugin):
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if isinstance(value, plugins.Plugin):
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if not value.is_activated:
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raise AttributeError('The default plugin has to be activated.')
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self._default = value
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@ -351,7 +362,8 @@ class Senpy(object):
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logger.info("Activating plugin: {}".format(plugin.name))
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if sync or not getattr(plugin, 'async', True) or getattr(plugin, 'sync', False):
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if sync or not getattr(plugin, 'async', True) or getattr(
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plugin, 'sync', False):
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return self._activate(plugin)
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else:
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th = Thread(target=partial(self._activate, plugin))
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@ -374,7 +386,8 @@ class Senpy(object):
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self._set_active(plugin, False)
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if sync or not getattr(plugin, 'async', True) or not getattr(plugin, 'sync', False):
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if sync or not getattr(plugin, 'async', True) or not getattr(
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plugin, 'sync', False):
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self._deactivate(plugin)
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else:
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th = Thread(target=partial(self._deactivate, plugin))
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@ -1,7 +1,6 @@
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from future import standard_library
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standard_library.install_aliases()
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from future.utils import with_metaclass
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from functools import partial
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@ -10,7 +9,6 @@ import os
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import re
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import pickle
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import logging
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import copy
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import pprint
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import inspect
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@ -26,7 +24,6 @@ from .. import api
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from .. import gsitk_compat
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from .. import testing
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logger = logging.getLogger(__name__)
|
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@ -46,16 +43,19 @@ class PluginMeta(models.BaseMeta):
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if doc:
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attrs['description'] = doc
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else:
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logger.warn(('Plugin {} does not have a description. '
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'Please, add a short summary to help other developers').format(name))
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logger.warning(
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('Plugin {} does not have a description. '
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'Please, add a short summary to help other developers'
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).format(name))
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cls = super(PluginMeta, mcs).__new__(mcs, name, bases, attrs)
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if alias in mcs._classes:
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if os.environ.get('SENPY_TESTING', ""):
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raise Exception(('The type of plugin {} already exists. '
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'Please, choose a different name').format(name))
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raise Exception(
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('The type of plugin {} already exists. '
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'Please, choose a different name').format(name))
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else:
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logger.warn('Overloading plugin class: {}'.format(alias))
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logger.warning('Overloading plugin class: {}'.format(alias))
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mcs._classes[alias] = cls
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return cls
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@ -87,10 +87,12 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
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if info:
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self.update(info)
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self.validate()
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self.id = 'endpoint:plugins/{}_{}'.format(self['name'], self['version'])
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self.id = 'endpoint:plugins/{}_{}'.format(self['name'],
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self['version'])
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self.is_activated = False
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self._lock = threading.Lock()
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self._directory = os.path.abspath(os.path.dirname(inspect.getfile(self.__class__)))
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self._directory = os.path.abspath(
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os.path.dirname(inspect.getfile(self.__class__)))
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data_folder = data_folder or os.getcwd()
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subdir = os.path.join(data_folder, self.name)
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@ -118,7 +120,8 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
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if x not in self:
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missing.append(x)
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if missing:
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raise models.Error('Missing configuration parameters: {}'.format(missing))
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raise models.Error(
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'Missing configuration parameters: {}'.format(missing))
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def get_folder(self):
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return os.path.dirname(inspect.getfile(self.__class__))
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@ -129,22 +132,60 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
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def deactivate(self):
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pass
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|
||||
def process(self, request, **kwargs):
|
||||
"""
|
||||
An implemented plugin should override this method.
|
||||
Here, we assume that a process_entries method exists."""
|
||||
newentries = list(
|
||||
self.process_entries(request.entries, request.parameters))
|
||||
request.entries = newentries
|
||||
return request
|
||||
|
||||
def process_entries(self, entries, parameters):
|
||||
for entry in entries:
|
||||
self.log.debug('Processing entry with plugin {}: {}'.format(
|
||||
self, entry))
|
||||
results = self.process_entry(entry, parameters)
|
||||
if inspect.isgenerator(results):
|
||||
for result in results:
|
||||
yield result
|
||||
else:
|
||||
yield results
|
||||
|
||||
def process_entry(self, entry, parameters):
|
||||
"""
|
||||
This base method is here to adapt plugins which only
|
||||
implement the *process* function.
|
||||
Note that this method may yield an annotated entry or a list of
|
||||
entries (e.g. in a tokenizer)
|
||||
"""
|
||||
raise NotImplementedError(
|
||||
'You need to implement process, process_entries or process_entry in your plugin'
|
||||
)
|
||||
|
||||
def test(self, test_cases=None):
|
||||
if not test_cases:
|
||||
if not hasattr(self, 'test_cases'):
|
||||
raise AttributeError(('Plugin {} [{}] does not have any defined '
|
||||
'test cases').format(self.id,
|
||||
inspect.getfile(self.__class__)))
|
||||
raise AttributeError(
|
||||
('Plugin {} [{}] does not have any defined '
|
||||
'test cases').format(self.id,
|
||||
inspect.getfile(self.__class__)))
|
||||
test_cases = self.test_cases
|
||||
for case in test_cases:
|
||||
try:
|
||||
self.test_case(case)
|
||||
self.log.debug('Test case passed:\n{}'.format(pprint.pformat(case)))
|
||||
self.log.debug('Test case passed:\n{}'.format(
|
||||
pprint.pformat(case)))
|
||||
except Exception as ex:
|
||||
self.log.warn('Test case failed:\n{}'.format(pprint.pformat(case)))
|
||||
self.log.warning('Test case failed:\n{}'.format(
|
||||
pprint.pformat(case)))
|
||||
raise
|
||||
|
||||
def test_case(self, case, mock=testing.MOCK_REQUESTS):
|
||||
if 'entry' not in case and 'input' in case:
|
||||
entry = models.Entry(_auto_id=False)
|
||||
entry.nif__isString = case['input']
|
||||
case['entry'] = entry
|
||||
entry = models.Entry(case['entry'])
|
||||
given_parameters = case.get('params', case.get('parameters', {}))
|
||||
expected = case.get('expected', None)
|
||||
@ -152,21 +193,25 @@ class Plugin(with_metaclass(PluginMeta, models.Plugin)):
|
||||
responses = case.get('responses', [])
|
||||
|
||||
try:
|
||||
params = api.parse_params(given_parameters, self.extra_params)
|
||||
request = models.Response()
|
||||
request.parameters = api.parse_params(given_parameters,
|
||||
self.extra_params)
|
||||
request.entries = [
|
||||
entry,
|
||||
]
|
||||
|
||||
method = partial(self.analyse_entries, [entry, ], params)
|
||||
method = partial(self.process, request)
|
||||
|
||||
if mock:
|
||||
res = list(method())
|
||||
res = method()
|
||||
else:
|
||||
with testing.patch_all_requests(responses):
|
||||
res = list(method())
|
||||
res = method()
|
||||
|
||||
if not isinstance(expected, list):
|
||||
expected = [expected]
|
||||
utils.check_template(res, expected)
|
||||
for r in res:
|
||||
r.validate()
|
||||
utils.check_template(res.entries, expected)
|
||||
res.validate()
|
||||
except models.Error:
|
||||
if should_fail:
|
||||
return
|
||||
@ -203,40 +248,26 @@ class Analysis(Plugin):
|
||||
A subclass of Plugin that analyses text and provides an annotation.
|
||||
'''
|
||||
|
||||
def analyse(self, *args, **kwargs):
|
||||
raise NotImplementedError(
|
||||
'Your plugin should implement either analyse or analyse_entry')
|
||||
|
||||
def analyse_entry(self, entry, parameters):
|
||||
""" An implemented plugin should override this method.
|
||||
This base method is here to adapt old style plugins which only
|
||||
implement the *analyse* function.
|
||||
Note that this method may yield an annotated entry or a list of
|
||||
entries (e.g. in a tokenizer)
|
||||
"""
|
||||
text = entry['nif:isString']
|
||||
params = copy.copy(parameters)
|
||||
params['input'] = text
|
||||
results = self.analyse(**params)
|
||||
for i in results.entries:
|
||||
yield i
|
||||
def analyse(self, request, parameters):
|
||||
return super(Analysis, self).process(request)
|
||||
|
||||
def analyse_entries(self, entries, parameters):
|
||||
for entry in entries:
|
||||
self.log.debug('Analysing entry with plugin {}: {}'.format(self, entry))
|
||||
results = self.analyse_entry(entry, parameters)
|
||||
if inspect.isgenerator(results):
|
||||
for result in results:
|
||||
yield result
|
||||
else:
|
||||
yield results
|
||||
for i in super(Analysis, self).process_entries(entries, parameters):
|
||||
yield i
|
||||
|
||||
def test_case(self, case):
|
||||
if 'entry' not in case and 'input' in case:
|
||||
entry = models.Entry(_auto_id=False)
|
||||
entry.nif__isString = case['input']
|
||||
case['entry'] = entry
|
||||
super(Analysis, self).test_case(case)
|
||||
def process(self, request, **kwargs):
|
||||
return self.analyse(request, request.parameters)
|
||||
|
||||
def process_entries(self, entries, parameters):
|
||||
for i in self.analyse_entries(entries, parameters):
|
||||
yield i
|
||||
|
||||
def process_entry(self, entry, parameters, **kwargs):
|
||||
if hasattr(self, 'analyse_entry'):
|
||||
for i in self.analyse_entry(entry, parameters):
|
||||
yield i
|
||||
else:
|
||||
super(Analysis, self).process_entry(entry, parameters, **kwargs)
|
||||
|
||||
|
||||
AnalysisPlugin = Analysis
|
||||
@ -247,7 +278,20 @@ class Conversion(Plugin):
|
||||
A subclass of Plugins that convert between different annotation models.
|
||||
e.g. a conversion of emotion models, or normalization of sentiment values.
|
||||
'''
|
||||
pass
|
||||
|
||||
def process(self, response, plugins=None, **kwargs):
|
||||
plugins = plugins or []
|
||||
newentries = []
|
||||
for entry in response.entries:
|
||||
newentries.append(
|
||||
self.convert_entry(entry, response.parameters, plugins))
|
||||
response.entries = newentries
|
||||
return response
|
||||
|
||||
def convert_entry(self, entry, parameters, conversions_applied):
|
||||
raise NotImplementedError(
|
||||
'You should implement a way to convert each entry, or a custom process method'
|
||||
)
|
||||
|
||||
|
||||
ConversionPlugin = Conversion
|
||||
@ -284,12 +328,28 @@ class EmotionConversion(Conversion):
|
||||
'''
|
||||
A subclass of Conversion that converts emotion annotations using different models
|
||||
'''
|
||||
pass
|
||||
|
||||
def can_convert(self, fromModel, toModel):
|
||||
'''
|
||||
Whether this plugin can convert from fromModel to toModel.
|
||||
If fromModel is None, it is interpreted as "any Model"
|
||||
'''
|
||||
for pair in self.onyx__doesConversion:
|
||||
if (pair['onyx:conversionTo'] == toModel) and \
|
||||
((fromModel is None) or (pair['onyx:conversionFrom'] == fromModel)):
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
EmotionConversionPlugin = EmotionConversion
|
||||
|
||||
|
||||
class PostProcessing(Plugin):
|
||||
def check(self, request, plugins):
|
||||
'''Should this plugin be run for this request?'''
|
||||
return False
|
||||
|
||||
|
||||
class Box(AnalysisPlugin):
|
||||
'''
|
||||
Black box plugins delegate analysis to a function.
|
||||
@ -314,9 +374,10 @@ class Box(AnalysisPlugin):
|
||||
return output
|
||||
|
||||
def predict_one(self, input):
|
||||
raise NotImplementedError('You should define the behavior of this plugin')
|
||||
raise NotImplementedError(
|
||||
'You should define the behavior of this plugin')
|
||||
|
||||
def analyse_entries(self, entries, params):
|
||||
def process_entries(self, entries, params):
|
||||
for entry in entries:
|
||||
input = self.input(entry=entry, params=params)
|
||||
results = self.predict_one(input=input)
|
||||
@ -385,7 +446,6 @@ class EmotionBox(TextBox, EmotionPlugin):
|
||||
|
||||
|
||||
class MappingMixin(object):
|
||||
|
||||
@property
|
||||
def mappings(self):
|
||||
return self._mappings
|
||||
@ -395,11 +455,10 @@ class MappingMixin(object):
|
||||
self._mappings = value
|
||||
|
||||
def output(self, output, entry, params):
|
||||
output = self.mappings.get(output,
|
||||
self.mappings.get('default', output))
|
||||
return super(MappingMixin, self).output(output=output,
|
||||
entry=entry,
|
||||
params=params)
|
||||
output = self.mappings.get(output, self.mappings.get(
|
||||
'default', output))
|
||||
return super(MappingMixin, self).output(
|
||||
output=output, entry=entry, params=params)
|
||||
|
||||
|
||||
class ShelfMixin(object):
|
||||
@ -412,7 +471,8 @@ class ShelfMixin(object):
|
||||
with self.open(self.shelf_file, 'rb') as p:
|
||||
self._sh = pickle.load(p)
|
||||
except (IndexError, EOFError, pickle.UnpicklingError):
|
||||
self.log.warning('Corrupted shelf file: {}'.format(self.shelf_file))
|
||||
self.log.warning('Corrupted shelf file: {}'.format(
|
||||
self.shelf_file))
|
||||
if not self.get('force_shelf', False):
|
||||
raise
|
||||
return self._sh
|
||||
@ -460,8 +520,7 @@ def pfilter(plugins, plugin_type=Analysis, **kwargs):
|
||||
plugin_type = plugin_type[0].upper() + plugin_type[1:]
|
||||
pclass = globals()[plugin_type]
|
||||
logger.debug('Class: {}'.format(pclass))
|
||||
candidates = filter(lambda x: isinstance(x, pclass),
|
||||
plugins)
|
||||
candidates = filter(lambda x: isinstance(x, pclass), plugins)
|
||||
except KeyError:
|
||||
raise models.Error('{} is not a valid type'.format(plugin_type))
|
||||
else:
|
||||
@ -471,8 +530,7 @@ def pfilter(plugins, plugin_type=Analysis, **kwargs):
|
||||
|
||||
def matches(plug):
|
||||
res = all(getattr(plug, k, None) == v for (k, v) in kwargs.items())
|
||||
logger.debug(
|
||||
"matching {} with {}: {}".format(plug.name, kwargs, res))
|
||||
logger.debug("matching {} with {}: {}".format(plug.name, kwargs, res))
|
||||
return res
|
||||
|
||||
if kwargs:
|
||||
@ -506,14 +564,14 @@ def install_deps(*plugins):
|
||||
for req in requirements:
|
||||
pip_args.append(req)
|
||||
logger.info('Installing requirements: ' + str(requirements))
|
||||
process = subprocess.Popen(pip_args,
|
||||
stdout=subprocess.PIPE,
|
||||
stderr=subprocess.PIPE)
|
||||
process = subprocess.Popen(
|
||||
pip_args, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
|
||||
_log_subprocess_output(process)
|
||||
exitcode = process.wait()
|
||||
installed = True
|
||||
if exitcode != 0:
|
||||
raise models.Error("Dependencies not properly installed: {}".format(pip_args))
|
||||
raise models.Error(
|
||||
"Dependencies not properly installed: {}".format(pip_args))
|
||||
nltk_resources |= set(info.get('nltk_resources', []))
|
||||
|
||||
installed |= nltk.download(list(nltk_resources))
|
||||
@ -556,7 +614,7 @@ def from_folder(folders, loader=from_path, **kwargs):
|
||||
|
||||
|
||||
def from_info(info, root=None, install_on_fail=True, **kwargs):
|
||||
if any(x not in info for x in ('module',)):
|
||||
if any(x not in info for x in ('module', )):
|
||||
raise ValueError('Plugin info is not valid: {}'.format(info))
|
||||
module = info["module"]
|
||||
|
||||
@ -593,7 +651,8 @@ def one_from_module(module, root, info, **kwargs):
|
||||
if '@type' in info:
|
||||
cls = PluginMeta.from_type(info['@type'])
|
||||
return cls(info=info, **kwargs)
|
||||
instance = next(from_module(module=module, root=root, info=info, **kwargs), None)
|
||||
instance = next(
|
||||
from_module(module=module, root=root, info=info, **kwargs), None)
|
||||
if not instance:
|
||||
raise Exception("No valid plugin for: {}".format(module))
|
||||
return instance
|
||||
@ -617,7 +676,8 @@ def _instances_in_module(module):
|
||||
|
||||
def _from_module_name(module, root, info=None, **kwargs):
|
||||
module = load_module(module, root)
|
||||
for plugin in _from_loaded_module(module=module, root=root, info=info, **kwargs):
|
||||
for plugin in _from_loaded_module(
|
||||
module=module, root=root, info=info, **kwargs):
|
||||
yield plugin
|
||||
|
||||
|
||||
@ -629,9 +689,10 @@ def _from_loaded_module(module, info=None, **kwargs):
|
||||
|
||||
|
||||
def evaluate(plugins, datasets, **kwargs):
|
||||
ev = gsitk_compat.Eval(tuples=None,
|
||||
datasets=datasets,
|
||||
pipelines=[plugin.as_pipe() for plugin in plugins])
|
||||
ev = gsitk_compat.Eval(
|
||||
tuples=None,
|
||||
datasets=datasets,
|
||||
pipelines=[plugin.as_pipe() for plugin in plugins])
|
||||
ev.evaluate()
|
||||
results = ev.results
|
||||
evaluations = evaluations_to_JSONLD(results, **kwargs)
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
---
|
||||
name: Ekman2FSRE
|
||||
module: senpy.plugins.conversion.emotion.centroids
|
||||
module: senpy.plugins.postprocessing.emotion.centroids
|
||||
description: Plugin to convert emotion sets from Ekman to VAD
|
||||
version: 0.2
|
||||
# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
|
||||
@ -1,6 +1,6 @@
|
||||
---
|
||||
name: Ekman2PAD
|
||||
module: senpy.plugins.conversion.emotion.centroids
|
||||
module: senpy.plugins.postprocessing.emotion.centroids
|
||||
description: Plugin to convert emotion sets from Ekman to VAD
|
||||
version: 0.2
|
||||
# No need to specify onyx:doesConversion because centroids.py adds it automatically from centroids_direction
|
||||
196
senpy/plugins/postprocessing/emotion/maxEmotion_plugin.py
Normal file
196
senpy/plugins/postprocessing/emotion/maxEmotion_plugin.py
Normal file
@ -0,0 +1,196 @@
|
||||
from senpy import PostProcessing, easy_test
|
||||
|
||||
|
||||
class MaxEmotion(PostProcessing):
|
||||
'''Plugin to extract the emotion with highest value from an EmotionSet'''
|
||||
author = '@dsuarezsouto'
|
||||
version = '0.1'
|
||||
|
||||
def process_entry(self, entry, params):
|
||||
if len(entry.emotions) < 1:
|
||||
yield entry
|
||||
return
|
||||
|
||||
set_emotions = entry.emotions[0]['onyx:hasEmotion']
|
||||
|
||||
# If there is only one emotion, do not modify it
|
||||
if len(set_emotions) < 2:
|
||||
yield entry
|
||||
return
|
||||
|
||||
max_emotion = set_emotions[0]
|
||||
|
||||
# Extract max emotion from the set emotions (emotion with highest intensity)
|
||||
for tmp_emotion in set_emotions:
|
||||
if tmp_emotion['onyx:hasEmotionIntensity'] > max_emotion[
|
||||
'onyx:hasEmotionIntensity']:
|
||||
max_emotion = tmp_emotion
|
||||
|
||||
if max_emotion['onyx:hasEmotionIntensity'] == 0:
|
||||
max_emotion['onyx:hasEmotionCategory'] = "neutral"
|
||||
max_emotion['onyx:hasEmotionIntensity'] = 1.0
|
||||
|
||||
entry.emotions[0]['onyx:hasEmotion'] = [max_emotion]
|
||||
|
||||
entry.emotions[0]['prov:wasGeneratedBy'] = "maxSentiment"
|
||||
yield entry
|
||||
|
||||
def check(self, request, plugins):
|
||||
return 'maxemotion' in request.parameters and self not in plugins
|
||||
|
||||
# Test Cases:
|
||||
# 1 Normal Situation.
|
||||
# 2 Case to return a Neutral Emotion.
|
||||
test_cases = [
|
||||
{
|
||||
"name":
|
||||
"If there are several emotions within an emotion set, reduce it to one.",
|
||||
"entry": {
|
||||
"@type":
|
||||
"entry",
|
||||
"emotions": [
|
||||
{
|
||||
"@id":
|
||||
"Emotions0",
|
||||
"@type":
|
||||
"emotionSet",
|
||||
"onyx:hasEmotion": [
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "anger",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "joy",
|
||||
"onyx:hasEmotionIntensity": 0.3333333333333333
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "negative-fear",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "sadness",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "disgust",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"nif:isString":
|
||||
"Test"
|
||||
},
|
||||
'expected': {
|
||||
"@type":
|
||||
"entry",
|
||||
"emotions": [
|
||||
{
|
||||
"@id":
|
||||
"Emotions0",
|
||||
"@type":
|
||||
"emotionSet",
|
||||
"onyx:hasEmotion": [
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "joy",
|
||||
"onyx:hasEmotionIntensity": 0.3333333333333333
|
||||
}
|
||||
],
|
||||
"prov:wasGeneratedBy":
|
||||
'maxSentiment'
|
||||
}
|
||||
],
|
||||
"nif:isString":
|
||||
"Test"
|
||||
}
|
||||
},
|
||||
{
|
||||
"name":
|
||||
"If the maximum emotion has an intensity of 0, return a neutral emotion.",
|
||||
"entry": {
|
||||
"@type":
|
||||
"entry",
|
||||
"emotions": [{
|
||||
"@id":
|
||||
"Emotions0",
|
||||
"@type":
|
||||
"emotionSet",
|
||||
"onyx:hasEmotion": [
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "anger",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "joy",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id":
|
||||
"_:Emotion_1538121033.74",
|
||||
"@type":
|
||||
"emotion",
|
||||
"onyx:hasEmotionCategory":
|
||||
"negative-fear",
|
||||
"onyx:hasEmotionIntensity":
|
||||
0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory":
|
||||
"sadness",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
},
|
||||
{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory":
|
||||
"disgust",
|
||||
"onyx:hasEmotionIntensity": 0
|
||||
}]
|
||||
}],
|
||||
"nif:isString":
|
||||
"Test"
|
||||
},
|
||||
'expected': {
|
||||
"@type":
|
||||
"entry",
|
||||
"emotions": [{
|
||||
"@id":
|
||||
"Emotions0",
|
||||
"@type":
|
||||
"emotionSet",
|
||||
"onyx:hasEmotion": [{
|
||||
"@id": "_:Emotion_1538121033.74",
|
||||
"@type": "emotion",
|
||||
"onyx:hasEmotionCategory": "neutral",
|
||||
"onyx:hasEmotionIntensity": 1
|
||||
}],
|
||||
"prov:wasGeneratedBy":
|
||||
'maxSentiment'
|
||||
}],
|
||||
"nif:isString":
|
||||
"Test"
|
||||
}
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
easy_test()
|
||||
@ -138,14 +138,14 @@ class BlueprintsTest(TestCase):
|
||||
# Calling dummy twice, should return the same string
|
||||
self.assertCode(resp, 200)
|
||||
js = parse_resp(resp)
|
||||
assert len(js['analysis']) == 2
|
||||
assert len(js['analysis']) == 1
|
||||
assert js['entries'][0]['nif:isString'] == 'My aloha mohame'
|
||||
|
||||
resp = self.client.get("/api/Dummy+Dummy?i=My aloha mohame")
|
||||
# Same with pluses instead of slashes
|
||||
self.assertCode(resp, 200)
|
||||
js = parse_resp(resp)
|
||||
assert len(js['analysis']) == 2
|
||||
assert len(js['analysis']) == 1
|
||||
assert js['entries'][0]['nif:isString'] == 'My aloha mohame'
|
||||
|
||||
def test_error(self):
|
||||
|
||||
@ -121,8 +121,8 @@ class ExtensionsTest(TestCase):
|
||||
# Leaf (defaultdict with __setattr__ and __getattr__.
|
||||
r1 = analyse(self.senpy, algorithm="Dummy", input="tupni", output="tuptuo")
|
||||
r2 = analyse(self.senpy, input="tupni", output="tuptuo")
|
||||
assert r1.analysis[0] == "endpoint:plugins/Dummy_0.1"
|
||||
assert r2.analysis[0] == "endpoint:plugins/Dummy_0.1"
|
||||
assert r1.analysis[0].id == "endpoint:plugins/Dummy_0.1"
|
||||
assert r2.analysis[0].id == "endpoint:plugins/Dummy_0.1"
|
||||
assert r1.entries[0]['nif:isString'] == 'input'
|
||||
|
||||
def test_analyse_empty(self):
|
||||
@ -156,8 +156,8 @@ class ExtensionsTest(TestCase):
|
||||
r2 = analyse(self.senpy,
|
||||
input="tupni",
|
||||
output="tuptuo")
|
||||
assert r1.analysis[0] == "endpoint:plugins/Dummy_0.1"
|
||||
assert r2.analysis[0] == "endpoint:plugins/Dummy_0.1"
|
||||
assert r1.analysis[0].id == "endpoint:plugins/Dummy_0.1"
|
||||
assert r2.analysis[0].id == "endpoint:plugins/Dummy_0.1"
|
||||
assert r1.entries[0]['nif:isString'] == 'input'
|
||||
|
||||
def test_analyse_error(self):
|
||||
@ -165,7 +165,7 @@ class ExtensionsTest(TestCase):
|
||||
mm.id = 'magic_mock'
|
||||
mm.name = 'mock'
|
||||
mm.is_activated = True
|
||||
mm.analyse_entries.side_effect = Error('error in analysis', status=500)
|
||||
mm.process.side_effect = Error('error in analysis', status=500)
|
||||
self.senpy.add_plugin(mm)
|
||||
try:
|
||||
analyse(self.senpy, input='nothing', algorithm='MOCK')
|
||||
@ -175,8 +175,7 @@ class ExtensionsTest(TestCase):
|
||||
assert ex['status'] == 500
|
||||
|
||||
ex = Exception('generic exception on analysis')
|
||||
mm.analyse.side_effect = ex
|
||||
mm.analyse_entries.side_effect = ex
|
||||
mm.process.side_effect = ex
|
||||
|
||||
try:
|
||||
analyse(self.senpy, input='nothing', algorithm='MOCK')
|
||||
@ -211,27 +210,28 @@ class ExtensionsTest(TestCase):
|
||||
'emoml:valence': 0
|
||||
}))
|
||||
response = Results({
|
||||
'analysis': [{'plugin': plugin}],
|
||||
'analysis': [plugin],
|
||||
'entries': [Entry({
|
||||
'nif:isString': 'much ado about nothing',
|
||||
'emotions': [eSet1]
|
||||
})]
|
||||
})
|
||||
params = {'emotionModel': 'emoml:big6',
|
||||
'algorithm': ['conversion'],
|
||||
'conversion': 'full'}
|
||||
r1 = deepcopy(response)
|
||||
r1.parameters = params
|
||||
self.senpy.convert_emotions(r1)
|
||||
self.senpy.analyse(r1)
|
||||
assert len(r1.entries[0].emotions) == 2
|
||||
params['conversion'] = 'nested'
|
||||
r2 = deepcopy(response)
|
||||
r2.parameters = params
|
||||
self.senpy.convert_emotions(r2)
|
||||
self.senpy.analyse(r2)
|
||||
assert len(r2.entries[0].emotions) == 1
|
||||
assert r2.entries[0].emotions[0]['prov:wasDerivedFrom'] == eSet1
|
||||
params['conversion'] = 'filtered'
|
||||
r3 = deepcopy(response)
|
||||
r3.parameters = params
|
||||
self.senpy.convert_emotions(r3)
|
||||
self.senpy.analyse(r3)
|
||||
assert len(r3.entries[0].emotions) == 1
|
||||
r3.jsonld()
|
||||
|
||||
@ -8,7 +8,7 @@ import tempfile
|
||||
from unittest import TestCase, skipIf
|
||||
from senpy.models import Results, Entry, EmotionSet, Emotion, Plugins
|
||||
from senpy import plugins
|
||||
from senpy.plugins.conversion.emotion.centroids import CentroidConversion
|
||||
from senpy.plugins.postprocessing.emotion.centroids import CentroidConversion
|
||||
from senpy.gsitk_compat import GSITK_AVAILABLE
|
||||
|
||||
import pandas as pd
|
||||
|
||||
Loading…
Reference in New Issue
Block a user