def __init__(self, model, api=None): if not (isinstance(model, dict) and 'resource' in model and model['resource'] is not None): if api is None: api = BigML(storage=STORAGE) self.resource_id = get_model_id(model) if self.resource_id is None: raise Exception( api.error_message(model, resource_type='model', method='get')) query_string = ONLY_MODEL model = retrieve_model(api, self.resource_id, query_string=query_string) BaseModel.__init__(self, model, api=api) if ('object' in model and isinstance(model['object'], dict)): model = model['object'] if ('model' in model and isinstance(model['model'], dict)): status = get_status(model) if ('code' in status and status['code'] == FINISHED): distribution = model['model']['distribution']['training'] self.ids_map = {} self.tree = Tree(model['model']['root'], self.fields, objective_field=self.objective_field, root_distribution=distribution, parent_id=None, ids_map=self.ids_map) self.terms = {} else: raise Exception("The model isn't finished yet") else: raise Exception("Cannot create the Model instance. Could not" " find the 'model' key in the resource:\n\n%s" % model) if self.tree.regression: try: import numpy import scipy self.regression_ready = True except ImportError: self.regression_ready = False
def __init__(self, model, api=None): """The Model constructor can be given as first argument: - a model structure - a model id - a path to a JSON file containing a model structure """ # the string can be a path to a JSON file if isinstance(model, basestring): try: with open(model) as model_file: model = json.load(model_file) self.resource_id = get_model_id(model) if self.resource_id is None: raise ValueError("The JSON file does not seem" " to contain a valid BigML model" " representation.") except IOError: # if it is not a path, it can be a model id self.resource_id = get_model_id(model) if self.resource_id is None: if model.find('model/') > -1: raise Exception( api.error_message(model, resource_type='model', method='get')) else: raise IOError("Failed to open the expected JSON file" " at %s" % model) except ValueError: raise ValueError("Failed to interpret %s." " JSON file expected.") if not (isinstance(model, dict) and 'resource' in model and model['resource'] is not None): if api is None: api = BigML(storage=STORAGE) query_string = ONLY_MODEL model = retrieve_resource(api, self.resource_id, query_string=query_string) BaseModel.__init__(self, model, api=api) if 'object' in model and isinstance(model['object'], dict): model = model['object'] if 'model' in model and isinstance(model['model'], dict): status = get_status(model) if 'code' in status and status['code'] == FINISHED: distribution = model['model']['distribution']['training'] self.ids_map = {} self.tree = Tree(model['model']['root'], self.fields, objective_field=self.objective_id, root_distribution=distribution, parent_id=None, ids_map=self.ids_map) self.terms = {} else: raise Exception("The model isn't finished yet") else: raise Exception("Cannot create the Model instance. Could not" " find the 'model' key in the resource:\n\n%s" % model) if self.tree.regression: try: import numpy import scipy self.regression_ready = True except ImportError: self.regression_ready = False
def __init__(self, model, api=None): if (isinstance(model, dict) and 'resource' in model and model['resource'] is not None): self.resource_id = model['resource'] else: if api is None: api = BigML(storage=STORAGE) self.resource_id = get_model_id(model) if self.resource_id is None: raise Exception(error_message(model, resource_type='model', method='get')) model = retrieve_model(api, self.resource_id) if ('object' in model and isinstance(model['object'], dict)): model = model['object'] if ('model' in model and isinstance(model['model'], dict)): status = get_status(model) if ('code' in status and status['code'] == FINISHED): if 'model_fields' in model['model']: fields = model['model']['model_fields'] # pagination or exclusion might cause a field not to # be in available fields dict if not all(key in model['model']['fields'] for key in fields.keys()): raise Exception("Some fields are missing" " to generate a local model." " Please, provide a model with" " the complete list of fields.") for field in fields: field_info = model['model']['fields'][field] fields[field]['summary'] = field_info['summary'] fields[field]['name'] = field_info['name'] else: fields = model['model']['fields'] objective_field = model['objective_fields'] self.objective_field = extract_objective(objective_field) self.uniquify_varnames(fields) self.inverted_fields = invert_dictionary(fields) self.all_inverted_fields = invert_dictionary(model['model'] ['fields']) self.tree = Tree( model['model']['root'], fields, self.objective_field) self.description = model['description'] self.field_importance = model['model'].get('importance', None) if self.field_importance: self.field_importance = [element for element in self.field_importance if element[0] in fields] self.locale = model.get('locale', DEFAULT_LOCALE) else: raise Exception("The model isn't finished yet") else: raise Exception("Cannot create the Model instance. Could not" " find the 'model' key in the resource:\n\n%s" % model)